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• Review Article
• Published: 15 January 2024

Parkinson disease psychosis: from phenomenology to neurobiological mechanisms

• Javier Pagonabarraga   ORCID: orcid.org/0000-0002-3248-704X 1 , 2 , 3 , 4 ,
• Helena Bejr-Kasem 1 , 2 , 3 , 4 ,
• Saul Martinez-Horta 1 , 2 , 3 , 4 &
• Jaime Kulisevsky   ORCID: orcid.org/0000-0003-4870-1431 1 , 2 , 3 , 4  

Nature Reviews Neurology volume  20 ,  pages 135–150 ( 2024 ) Cite this article

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• Parkinson's disease
• Psychiatric disorders

Parkinson disease (PD) psychosis (PDP) is a spectrum of illusions, hallucinations and delusions that are associated with PD throughout its disease course. Psychotic phenomena can manifest from the earliest stages of PD and might follow a continuum from minor hallucinations to structured hallucinations and delusions. Initially, PDP was considered to be a complication associated with dopaminergic drug use. However, subsequent research has provided evidence that PDP arises from the progression of brain alterations caused by PD itself, coupled with the use of dopaminergic drugs. The combined dysfunction of attentional control systems, sensory processing, limbic structures, the default mode network and thalamocortical connections provides a conceptual framework to explain how new incoming stimuli are incorrectly categorized, and how aberrant hierarchical predictive processing can produce false percepts that intrude into the stream of consciousness. The past decade has seen the publication of new data on the phenomenology and neurobiological basis of PDP from the initial stages of the disease, as well as the neurotransmitter systems involved in PDP initiation and progression. In this Review, we discuss the latest clinical, neuroimaging and neurochemical evidence that could aid early identification of psychotic phenomena in PD and inform the discovery of new therapeutic targets and strategies.

Parkinson disease (PD) psychosis (PDP) comprises a spectrum of illusions, hallucinations and delusions that are associated with PD throughout its course.

PDP is attributable not only to the use of dopaminergic drugs but also to inherent disruptions linked to the disease, which lead to dysfunction of neural systems governing visual perception, multimodal sensory integration, reality monitoring and attention.

Both minor and structured hallucinations in PD are associated with a pattern of cortical atrophy that includes the cuneus, precuneus, middle occipital gyrus, lingual and fusiform gyri, supramarginal gyrus, angular gyrus, anterior cingulate cortex, hippocampal regions and thalamus.

Functional neuroimaging studies indicate that PDP is associated with failure of top-down processing of attentional networks, aberrant coupling of the default mode network with visual networks and disconnection between the thalamus and posterior brain areas, leading to aberrant disinhibition of the default mode network.

Cortical cholinergic denervation and elevated levels of 5-HT 2A serotonergic receptor binding in the ventral visual pathway, medial orbitofrontal cortex and insula have prominent roles in the development of visual hallucinations.

An important advance in the treatment of PDP has been the development of drugs that reduce the activity of cortical postsynaptic 5-HT 2A receptors, of which pimavanserin is the most notable.

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Processing of information on the basis of incoming data from the environment to form a perception.

The belief that another person, often a friend or relative, has been replaced by an identical or near-identical impostor.

Illusions in which a real object is perceived as another entity, for example, a lamp in the living room is perceived as a standing person.

Quantification of the influence that a brain region has across the rest of the network.

Recurrent suspicions, without justification, regarding the fidelity of one’s spouse or sexual partner.

The experience that one’s feelings, impulses, thoughts or actions are not one’s own but are being imposed by some external force.

The false belief that innocuous events or mere coincidences have strong personal significance.

The false belief that someone is stealing one’s belongings.

A visual illusion in which the shape of an object appears distorted.

The influence that a node exerts over another under a network model of causal dynamics, which defines the mechanisms of neuronal coupling.

Neuronal networks subserving the processing of internal mentations independently from environmental stimuli.

Neuronal networks and engrams involved in directing mental processes towards environmental stimuli.

The belief that another person, often a friend or relative, is able to disguise themself as an unfamiliar person to influence the behaviour of the patient.

Functional interactions among different brain regions.

The belief that another person, often a friend or relative, has been transformed both physically and psychologically into another person.

A visual illusion in which stationary objects seem to be moving.

A visual illusion in which colours of an object appear different from those in reality.

Misidentification and reduplication of oneself in the mirror.

Visual illusions in which formless visual stimuli, such as clouds, tree bark or patterns in carpets or wallpaper, are perceived as human faces or animals.

Pervasive distrust and suspicion of others such that their motives are interpreted as malevolent (exploiting, harming, threatening or deceiving).

The belief that a double of another person exists. Also known as the syndrome of subjective doubles.

The belief that oneself has been relocated to an identical or near-identical duplicated place.

Time delay between a perception and movements previously associated with that perception.

Visual perceptions of an animate being, object or event in the absence of any external stimulus.

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Pagonabarraga, J., Bejr-Kasem, H., Martinez-Horta, S. et al. Parkinson disease psychosis: from phenomenology to neurobiological mechanisms. Nat Rev Neurol 20 , 135–150 (2024). https://doi.org/10.1038/s41582-023-00918-8

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Mind-wandering in Parkinson's disease hallucinations reflects primary visual and default network coupling

Research output : Contribution to journal › Article › peer-review

Visual hallucinations are an underappreciated symptom affecting the majority of patients during the natural history of Parkinson's disease. Little is known about other forms of abstract and internally generated cognition – such as mind-wandering – in this population, but emerging evidence suggests that an interplay between the brain's primary visual and default networks might play a crucial role in both internally generated imagery and hallucinations. Here, we explored the association between mind-wandering and visual hallucinations in Parkinson's disease, and their relationship with brain network coupling. We administered a validated thought-sampling task to 38 Parkinson's disease patients (18 with hallucinations; 20 without) and 40 controls, to test the hypothesis that individuals with hallucinations experience an increased frequency of mind-wandering. Group differences in the association between mind-wandering frequency and brain network coupling were also examined using resting state functional magnetic resonance imaging. Our results showed that patients with hallucinations exhibited significantly higher mind-wandering frequencies compared to non-hallucinators, who in turn had reduced levels of mind-wandering relative to controls. At the level of brain networks, inter-network connectivity and seed-to-voxel analyses identified that increased mind-wandering in the hallucinating versus non-hallucinating group was associated with greater coupling between the primary visual cortex and dorsal default network. Taken together, our results suggest a relative preservation of mind-wandering in Parkinson's disease patients who experience visual hallucinations, which is associated with increased visual cortex-default network coupling. We propose that the preservation of florid abstract and internally generated cognition in the context of the Parkinson's disease can contribute to visual hallucinations, whereas healthy individuals experience only the vivid images of the mind's eye. These findings refine current models of visual hallucinations by identifying a specific cognitive phenomenon and neural substrate consistent with the top-down influences over perception that have been implicated in hallucinations across neuropsychiatric disorders.

• Default network
• Mind-wandering
• Parkinson's disease
• Resting state functional magnetic resonance imaging
• Visual hallucinations

ASJC Scopus subject areas

• Neuropsychology and Physiological Psychology
• Experimental and Cognitive Psychology
• Cognitive Neuroscience

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• Hallucinations Medicine & Life Sciences 100%
• Parkinson Disease Medicine & Life Sciences 73%
• brain Social Sciences 42%
• cognition Social Sciences 20%
• Visual Cortex Medicine & Life Sciences 18%
• Brain Medicine & Life Sciences 17%
• Cognition Medicine & Life Sciences 13%
• experience Social Sciences 11%

T1 - Mind-wandering in Parkinson's disease hallucinations reflects primary visual and default network coupling

AU - Walpola, Ishan C.

AU - Muller, Alana J.

AU - Hall, Julie M.

AU - Andrews-Hanna, Jessica R.

AU - Irish, Muireann

AU - Lewis, Simon J.G.

AU - Shine, James M.

AU - O'Callaghan, Claire

N1 - Funding Information: We thank Kelly Diederen for providing valuable comments on the manuscript. AJM is supported by an Australian Postgraduate Award through the University of Sydney. JMH is supported by a Western Sydney University Postgraduate Award. JAH is supported by a National Institutes of Aging Arizona Alzheimer's Disease Core Center grant (P30 AG019610). MI is supported by an Australian Research Council Future Fellowship (FT160100096) and an Australian Research Council Discovery Project (DP180101548). SJGL is supported by an NHMRC-ARC Dementia Fellowship (#1110414). JMS is supported by a National Health and Medical Research Council CJ Martin Fellowship (1072403). CO is supported by a National Health and Medical Research Council Neil Hamilton Fairley Fellowship (1091310) and by the Wellcome Trust (200181/Z/15/Z). The study was supported by a Seed Grant from Parkinson's NSW and funding to Forefront, a collaborative research group dedicated to the study of non-Alzheimer disease degenerative dementias, from the National Health and Medical Research Council of Australia program grant (#1037746 and #1095127). Funding Information: We thank Kelly Diederen for providing valuable comments on the manuscript. AJM is supported by an Australian Postgraduate Award through the University of Sydney . JMH is supported by a Western Sydney University Postgraduate Award . JAH is supported by a National Institutes of Aging Arizona Alzheimer’s Disease Core Center grant ( P30 AG019610 ). MI is supported by an Australian Research Council Future Fellowship ( FT160100096 ) and an Australian Research Council Discovery Project ( DP180101548 ). SJGL is supported by an NHMRC-ARC Dementia Fellowship ( #1110414 ). JMS is supported by a National Health and Medical Research Council CJ Martin Fellowship ( 1072403 ). CO is supported by a National Health and Medical Research Council Neil Hamilton Fairley Fellowship ( 1091310 ) and by the Wellcome Trust ( 200181/Z/15/Z ). The study was supported by a Seed Grant from Parkinson's NSW and funding to Forefront, a collaborative research group dedicated to the study of non-Alzheimer disease degenerative dementias, from the National Health and Medical Research Council of Australia program grant (# 1037746 and # 1095127 ). Publisher Copyright: © 2020 Elsevier Ltd

PY - 2020/4

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N2 - Visual hallucinations are an underappreciated symptom affecting the majority of patients during the natural history of Parkinson's disease. Little is known about other forms of abstract and internally generated cognition – such as mind-wandering – in this population, but emerging evidence suggests that an interplay between the brain's primary visual and default networks might play a crucial role in both internally generated imagery and hallucinations. Here, we explored the association between mind-wandering and visual hallucinations in Parkinson's disease, and their relationship with brain network coupling. We administered a validated thought-sampling task to 38 Parkinson's disease patients (18 with hallucinations; 20 without) and 40 controls, to test the hypothesis that individuals with hallucinations experience an increased frequency of mind-wandering. Group differences in the association between mind-wandering frequency and brain network coupling were also examined using resting state functional magnetic resonance imaging. Our results showed that patients with hallucinations exhibited significantly higher mind-wandering frequencies compared to non-hallucinators, who in turn had reduced levels of mind-wandering relative to controls. At the level of brain networks, inter-network connectivity and seed-to-voxel analyses identified that increased mind-wandering in the hallucinating versus non-hallucinating group was associated with greater coupling between the primary visual cortex and dorsal default network. Taken together, our results suggest a relative preservation of mind-wandering in Parkinson's disease patients who experience visual hallucinations, which is associated with increased visual cortex-default network coupling. We propose that the preservation of florid abstract and internally generated cognition in the context of the Parkinson's disease can contribute to visual hallucinations, whereas healthy individuals experience only the vivid images of the mind's eye. These findings refine current models of visual hallucinations by identifying a specific cognitive phenomenon and neural substrate consistent with the top-down influences over perception that have been implicated in hallucinations across neuropsychiatric disorders.

AB - Visual hallucinations are an underappreciated symptom affecting the majority of patients during the natural history of Parkinson's disease. Little is known about other forms of abstract and internally generated cognition – such as mind-wandering – in this population, but emerging evidence suggests that an interplay between the brain's primary visual and default networks might play a crucial role in both internally generated imagery and hallucinations. Here, we explored the association between mind-wandering and visual hallucinations in Parkinson's disease, and their relationship with brain network coupling. We administered a validated thought-sampling task to 38 Parkinson's disease patients (18 with hallucinations; 20 without) and 40 controls, to test the hypothesis that individuals with hallucinations experience an increased frequency of mind-wandering. Group differences in the association between mind-wandering frequency and brain network coupling were also examined using resting state functional magnetic resonance imaging. Our results showed that patients with hallucinations exhibited significantly higher mind-wandering frequencies compared to non-hallucinators, who in turn had reduced levels of mind-wandering relative to controls. At the level of brain networks, inter-network connectivity and seed-to-voxel analyses identified that increased mind-wandering in the hallucinating versus non-hallucinating group was associated with greater coupling between the primary visual cortex and dorsal default network. Taken together, our results suggest a relative preservation of mind-wandering in Parkinson's disease patients who experience visual hallucinations, which is associated with increased visual cortex-default network coupling. We propose that the preservation of florid abstract and internally generated cognition in the context of the Parkinson's disease can contribute to visual hallucinations, whereas healthy individuals experience only the vivid images of the mind's eye. These findings refine current models of visual hallucinations by identifying a specific cognitive phenomenon and neural substrate consistent with the top-down influences over perception that have been implicated in hallucinations across neuropsychiatric disorders.

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Cognitive Changes

Some people with Parkinson’s disease (PD) experience mild cognitive impairment. Feelings of distraction or disorganization can accompany cognitive impairment, along with finding it difficult to plan and accomplish tasks.

It may be harder to focus in situations that divide your attention, like a group conversation. When facing a task or situation on their own, a person with PD may feel overwhelmed by having to make choices. They may also have difficulty remembering information or have trouble finding the right words when speaking. These changes can range from being annoying to interfering with managing household affairs.

To some degree, cognitive impairment affects many people with PD. The same brain changes that lead to motor symptoms can also result in slowness in memory and thinking. Stress, medication and depression can also contribute to these changes.

Symptoms of mild cognitive impairment (MCI) often do not interfere with home and work life. They may not even be noticeable, but can be detected through testing. Doctors used to believe that cognitive changes did not develop until middle to late-stage PD , but recent research suggests that mild changes may be present at the time of diagnosis.

Tell your doctor if you have concerns about cognitive changes. You may need to change your medication or see a neurologist or neuropsychologist for assessment. An occupational therapist can also help you find strategies for adapting and coping with these symptoms. A speech therapist can help with language difficulties.

In general, mental and motor decline tend to occur together as the disease progresses. Significant cognitive impairment in PD is often associated with:

• Caregiver distress
• Worse day-to-day function
• Diminished quality of life
• Poorer treatment outcomes
• Greater medical costs due to nursing home placements
• Increased mortality

Cognitive impairment is different from dementia, which is when cognitive impairments occur in more than one area of cognition, leading to more severe loss of intellectual abilities that interferes with daily, independent living. While 20% to 50% of people with PD will experience mild cognitive impairment, not all lead to a dementia diagnosis.

Two long-term studies suggest that many people with PD will eventually develop a mild form of dementia as the disease progresses, usually many years after their initial diagnosis. One medication, Exelon (rivastigmine tartrate), can treat dementia in PD. Other medications are being studied.

What causes cognitive changes in people with PD?

One cause is a drop in the level of dopamine, the neurotransmitter that is involved in regulating the body’s movements. However, the cognitive changes associated with dopamine declines are typically mild and restricted.

Other brain changes are likely also involved in cognitive decline in PD. Scientists are looking at changes in two other chemical messengers — acetylcholine and norepinephrine — as possible additional causes of memory and executive function loss in Parkinson’s. 

Effects of Cognitive Changes

The cognitive changes that accompany Parkinson’s early on tend to be limited to one or two mental areas, with severity varying from person to person. Areas most often affected include:

• Difficulty with complex tasks that require person with PD to maintain or shift their attention.
• Problems with mental calculations or concentrating during a task.

Speed of Mental Processing

• Slowing in thinking is often associated with depression in PD.
• Signs include: a delay in responding to verbal or behavioral stimuli, taking longer to complete tasks and difficulty retrieving information from memory.

Problem-solving or Executive Function

• Trouble planning and completing activities.
• Difficulties in generating, maintaining, shifting and blending different ideas and concepts.
• More concrete in approach to tasks.
• Loved ones can help the person with PD by providing cues, reminders and greater structure of activity.

Memory Issues

• The basal ganglia and frontal lobes of the brain (both help the brain organize and recall of information) may be damaged in PD.
• Difficulty with common tasks such as making coffee, balancing a checkbook, etc.
• People with dementia can experience both short-term and long-term memory impairment.

Language Abnormalities

• Issues with word-finding, known as “tip of the tongue” phenomenon.
• Difficulty with language when under pressure or stress.
• Difficulty comprehending complex sentences where the question or information is included with other details.
• Problems with production of language and dysarthria — slurred or unarticulated speech due to weakened muscles caused by brain changes.
• Problems in naming or misnaming objects — more common in middle to late stages of PD.

Visuospatial Difficulties

• During early PD stages: difficulty with measuring distance and depth perception, which may interfere with parking a car or remembering where the car is parked.
• During advanced PD: in combination with dementia, problems with processing information about their surroundings or environment.
• Subtle visual-perceptual problems may contribute to the visual misperceptions or illusions.
• Increased chances of visual misperceptions or illusions in low-light situations (like nighttime) and if experiencing other visual problems (like macular degeneration).
• In severe cases, problems telling apart non-familiar faces or recognizing emotional expressions.

How are cognitive issues diagnosed?

Common ways to assess and diagnose cognitive disorders:

• Interview the person with PD.
• Ask family members or care partners about their observations.
• Administer cognitive screening tests such as the Mini-Mental State Examination (MMSE) or Montreal Cognitive Assessment (MOCA). The neurologist will ask questions that evaluate the person’s understanding of where and who they are, the date and year, attention, memory, language and problem-solving skills.
• A neurologist may suggest seeing a clinical neuropsychologist for a more detailed assessment.
• Neuropsychological assessment can be an important diagnostic tool for differentiating PD from other illnesses such as Alzheimer's disease, stroke or dementia.

How are cognitive changes in PD different than Alzheimer’s disease?

Overall, dementia produces a greater impact on social and occupational functioning in PD than Alzheimer’s due to the combination of motor and cognitive impairments.

There is some overlap between symptoms and biological changes seen in Alzheimer’s and PD. However, it is less likely for both disorders to occur at the same time. Development of dementia in people with PD represents progression of the disease, usually after several years of motor impairment.

Dementia may or may not occur in people with PD. According to recent research, 30% of people with Parkinson’s do not develop dementia as part of the disease progression.

See 10 Signs of Alzheimer’s.

What co-existing conditions affect thinking and memory?

There are other factors that can have a negative impact on a person’s cognitive skills, such as disorders of mood, anxiety and sleep. In some cases, these factors can make memory and thinking deficits worse, as well as directly affect a person’s quality of life.

• Up to 50% of people with PD experience some form of depression during the disease.
• More likely to occur in people who experience severe cognitive impairment.
• Successful treatment of depression with medication and psychotherapy can improve cognitive symptoms.
• Can make it difficult to control motor symptoms (such as tremor and balance problems) in PD.
• Tends to be more severe in people with worse motor symptoms.
• May be as common as depression in Parkinson’s.
• While less studied, up to 40% of people with PD experience some form of anxiety.
• Can interfere with memory storage, disrupt attention and complex task performance. For example, most people remember going blank on a school exam when feeling anxious.
• Negatively impacts social life. People with poorly controlled anxiety often avoid social situations, which can impact family and work relationships.
• People with PD may experience anticipatory anxiety in situations where they have to use cognitive skills.
• Similar to depression, successful treatment can lead to improvement of cognitive problems related to anxiety.

Sleep Issues

• The impact of poor sleep on attention, alertness and memory are well-known.
• Problems with falling and staying asleep are common in PD, especially as the disease progresses.
• Mild reductions in sleep can directly impair attention, judgment and the ability to multi-task because people with PD have a lower cognitive reserve or resistance of the brain to stressors.
• Undergoing a sleep study examines sleeping patterns and how often sleep is disrupted.
• Sleep problems are often addressed with medication and behavioral treatments. As sleep improves, its impact on thinking and memory is reduced.

Four types of sleep problems have been reported in PD:

• Issues staying asleep and early morning awakening (insomnia).
• Involuntary movements and pain that interrupt sleep.
• Increased nighttime urination.
• Nighttime agitation, vivid dreams and visual misperceptions or hallucinations.
• Just as fatigue can cause problems with movement and walking in PD, it can also impair thinking and memory. For example, a person with PD may have difficulty performing a complex cognitive task (like working on taxes over extended periods).
• Maximize attention and energy resources by dividing tasks into more manageable 10 to 15-minute sections. This helps minimize fatigue and keep you on task.
• Be aware that as the day wears on, people with PD may begin to fatigue — physically and cognitively.
• Medications can help improve energy and alertness (methylphenidate (Ritalin®) and modafinil (Provigil®)), but many have yet to be studied extensively for PD and fatigue.

Some medications used to treat PD have also been shown to have stimulating effects on thinking and energy levels (like selegiline (Eldepryl®) and amantadine).

Seeking Help for Cognitive Changes

Cognitive change is a sensitive issue. In fact, the doctor is often as hesitant to address this subject as the person with PD is to ask about it. Sometimes, the doctor will delay discussing cognitive impairment out of concern for the person who is still coping with the shock of a new PD diagnosis or struggling with motor symptoms.

For this reason, the person with PD often needs to be the one to initiate the conversation. Tell your doctor if you or your loved one is experiencing problems that upset the family or cause interruptions at work.

Cognitive issues are never too mild to address with your care team. A doctor can provide ways to help, often referring you to a psychiatrist, neuropsychologist, speech or occupational therapist for further evaluation and assistance. The neuropsychological evaluation can be particularly useful, especially in the early stages of a cognitive problem. Having this baseline test can help the doctor determine whether future changes are related to medications, the progression of the PD itself or to other factors such as depression.

When reporting symptoms of mild cognitive impairment, the doctor will first want to rule out causes other than PD, such as vitamin B-12 deficiency, depression, fatigue or sleep disturbances. It should be noted that PD does not cause sudden changes in mental functioning. If a sudden change occurs, the cause is likely to be something else, such as a medication side-effect.

If cognitive symptoms are traceable to PD, there are drug therapies available. Though developed for Alzheimer’s, these medications have been found to have some effect in PD. These include rivastigmine (the only medication approved by the FDA for dementia in PD), donepezil and galantamine. In addition, a person with attention difficulties that are due to daytime sleepiness may benefit from stimulants.

How are cognitive problems treated?

Much remains to be learned about the basic biology that underlies cognitive changes in PD. Researchers work towards the development of diagnostic tests to identify people who seem to be at greatest risk for cognitive changes and to differentiate cognitive problems in people with PD from those that occur in another disorder — related but different — known as dementia with Lewy bodies. A combination of medications and behavioral strategies is usually the best treatment for cognitive problems in PD.

Cognitive Remediation Therapy

For those with milder cognitive deficits, cognitive remediation therapy is a treatment that emphasizes teaching alternative ways to compensate for memory or thinking problems. In this treatment, the clinician uses information from neuropsychological testing to identify cognitive strengths that can be used to help overcome weaker areas of thinking.

• While widely used in the treatment of cognitive problems resulting from brain injury or stroke, there has been less use of this technique in people with PD.
• Does not reverse or cure cognitive disorders, but instead teaches strategies that can help with daily functioning and coping with cognitive problems.
• Depending on the severity of cognitive impairment, many can use these skills independently.
• In cases where the person is more impaired, care partners or family members can help apply these strategies.
• Usually conducted by a neuropsychologist or speech-language pathologist, who is specially trained in these techniques and can provide a supportive environment for the person with PD to express concerns and frustrations over changes in mental functioning.
• Works best with milder forms of cognitive deficits, as it requires insight into the person’s own memory and thinking problems.

Behavioral Management

In this type of treatment, changes in the environment can be made to help minimize memory, visual-perceptual or orientation difficulties.

• Strategies include simplifying the décor of the living area to reduce excessive stimuli and minimize confusion and using a nightlight or low-level lighting to reduce visual misperceptions and confusion at nighttime.
• Behavioral strategies can help deal with other problems such as impulsivity, wandering, poor initiation and problems with communication.
• A person with PD may benefit from a regular routine in their day-to-day activities and feel more comfortable with a clear, structured schedule.

Tips for Care Partners

• Offer help only when asked.
• Prompt the person — for example, instead of asking, “Did anyone call?” ask, “Did Linda call?”
• Say the name of the person and make eye contact when speaking to gain and hold attention.
• Put reminder notes and lists in a prominent place.
• Keep things in routine places.
• To ensure medications are taken on time, provide a dispenser, perhaps with a built-in alarm.
• Use photos on cell phone contact entries to prompt face-name association.
• If the person is searching for a word, provide a cue, such as, “the word you are looking for probably begins with ‘d’.”
• Do not finish the sentences of a person who needs more time to put them together.
• When presenting the person with a list of actions, first verbalize them, then write them down.
• Ask questions to moderate the conversation pace and allow catch up and reinforcement.

Page reviewed by Dr. Kathryn P Moore, Movement Disorders neurologist at Duke Health, a Parkinson's Foundation Center of Excellence.

Related Materials

Cognition: a mind guide to parkinson's disease, episode 27: more than movement: addressing cognitive and behavioral challenges in caring for pd, episode 65: recognizing non-motor symptoms in pd, related blog posts.

Mental Health Tips for Cognition, Mood and Sleep

Care Partner Deep Dive: Three Experts Discuss Sleep, Cognition and Mood in Parkinson's

Tips from the Pros: Maintaining Cognitive Brain Health in Parkinson's Disease

Parkinson's connection, personal information.

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Dynamic brain activity associated with mind wandering, revealing possible new targets for brain disorders.

Image: Hannah Moore

What’s happening in your brain when you’re spacing out?

by Eva Botkin-Kowacki | March 25, 2021 May 24, 2023

Categories: Brain Imaging , ADHD , Anxiety , Depression , John Gabrieli , Martinos Imaging Center , Poitras Center for Psychiatric Disorders Research

This story is adapted from a News@Northeastern post .

We all do it. One second you’re fully focused on the task in front of you, a conversation with a friend, or a professor’s lecture, and the next second your mind is wandering to your dinner plans.

But how does that happen?

“We spend so much of our daily lives engaged in things that are completely unrelated to what’s in front of us,” says Aaron Kucyi, neuroscientist and principal research scientist in the department of psychology at Northeastern. “And we know very little about how it works in the brain.”

So Kucyi and colleagues at Massachusetts General Hospital, Boston University, and the McGovern Institute at MIT started scanning people’s brains using functional magnetic resonance imaging (fMRI) to get an inside look. Their results, published Friday in the journal Nature Communications , add complexity to our understanding of the wandering mind.

It turns out that spacing out might not deserve the bad reputation that it receives. Many more parts of the brain seem to be engaged in mind-wandering than previously thought, supporting the idea that it’s actually a quite dynamic and fundamental function of our psychology.

“Many of those things that we do when we’re spacing out are very adaptive and important to our lives,” says Kucyi, the paper’s first author. We might be drafting an email in our heads while in the shower, or trying to remember the host’s spouse’s name while getting dressed for a party. Moments when our minds wander can allow space for creativity and planning for the future, he says, so it makes sense that many parts of the brain would be engaged in that kind of thinking.

But mind wandering may also be detrimental, especially for those suffering from mental illness, explains the study’s senior author, Susan Whitfield-Gabrieli. “For many of us, mind wandering may be a healthy, positive and constructive experience, like reminiscing about the past, planning for the future, or engaging in creative thinking,” says Whitfield-Gabrieli, a professor of psychology at Northeastern University and a McGovern Institute research affiliate. “But for those suffering from mental illness such as depression , anxiety or psychosis, reminiscing about the past may transform into ruminating about the past, planning for the future may become obsessively worrying about the future and creative thinking may evolve into delusional thinking.”

Identifying the brain circuits associated with mind wandering, she says, may reveal new targets and better treatment options for people suffering from these disorders.

Inside the wandering mind

To study wandering minds, the researchers first had to set up a situation in which people were likely to lose focus. They recruited test subjects at the McGovern Institute’s Martinos Imaging Center to complete a simple, repetitive, and rather boring task. With an fMRI scanner mapping their brain activity, participants were instructed to press a button whenever an image of a city scene appeared on a screen in front of them and withhold a response when a mountain image appeared.

Throughout the experiment, the subjects were asked whether they were focused on the task at hand. If a subject said their mind was wandering, the researchers took a close look at their brain scans from right before they reported loss of focus. The data was then fed into a machine-learning algorithm to identify patterns in the neurological connections involved in mind-wandering (called “stimulus-independent, task-unrelated thought” by the scientists).

Scientists previously identified a specialized system in the brain considered to be responsible for mind-wandering. Called the “default mode network,” these parts of the brain activated when someone’s thoughts were drifting away from their immediate surroundings and deactivated when they were focused. The other parts of the brain, that theory went, were quiet when the mind was wandering, says Kucyi.

The “default mode network” did light up in Kucyi’s data. But parts of the brain associated with other functions also appeared to activate when his subjects reported that their minds had wandered.

For example, the “default mode network” and networks in the brain related to controlling or maintaining a train of thought also seemed to be communicating with one another, perhaps helping explain the ability to go down a rabbit hole in your mind when you’re distracted from a task. There was also a noticeable lack of communication between the “default mode network” and the systems associated with sensory input, which makes sense, as the mind is wandering away from the person’s immediate environment.

“It makes sense that virtually the whole brain is involved,” Kucyi says. “Mind-wandering is a very complex operation in the brain and involves drawing from our memory, making predictions about the future, dynamically switching between topics that we’re thinking about, fluctuations in our mood, and engaging in vivid visual imagery while ignoring immediate visual input,” just to name a few functions.

The “default mode network” still seems to be key, Kucyi says. Virtual computer analysis suggests that if you took the regions of the brain in that network out of the equation, the other brain regions would not be able to pick up the slack in mind-wandering.

Kucyi, however, didn’t just want to identify regions of the brain that lit up when someone said their mind was wandering. He also wanted to be able to use that generalized pattern of brain activity to be able to predict whether or not a subject would say that their focus had drifted away from the task in front of them.

That’s where the machine-learning analysis of the data came in. The idea, Kucyi says, is that “you could bring a new person into the scanner and not even ask them whether they were mind-wandering or not, and have a good estimate from their brain data whether they were.”

The ADHD brain

To test the patterns identified through machine learning, the researchers brought in a new set of test subjects – people diagnosed with ADHD . When the fMRI scans lit up the parts of the brain Kucyi and his colleagues had identified as engaged in mind-wandering in the first part of the study, the new test subjects reported that their thoughts had drifted from the images of cities and mountains in front of them. It worked.

Kucyi doesn’t expect fMRI scans to become a new way to diagnose ADHD, however. That wasn’t the goal. Perhaps down the road it could be used to help develop treatments, he suggests. But this study was focused on “informing the biological mechanisms behind it.”

John Gabrieli , a co-author on the study and director of the imaging center at MIT’s McGovern Institute, adds that “there is recent evidence that ADHD patients with more mind-wandering have many more everyday practical and clinical difficulties than ADHD patients with less mind-wandering. This is the first evidence about the brain basis for that important difference, and points to what neural systems ought to be the targets of intervention to help ADHD patients who struggle the most.”

For Kucyi, the study of “mind-wandering” goes beyond ADHD. And the contents of those straying thoughts may be telling, he says.

“We just asked people whether they were focused on the task or away from the task, but we have no idea what they were thinking about,” he says. “What are people thinking about? For example, are those more positive thoughts or negative thoughts?” Such answers, which he hopes to explore in future research, could help scientists better understand other pathologies such as depression and anxiety, which often involve rumination on upsetting or worrisome thoughts.

Whitfield-Gabrieli and her team are already exploring whether behavioral interventions, such as mindfulness based real-time fMRI neurofeedback, can be used to help train people suffering from mental illness to modulate their own brain networks and reduce hallucinations, ruminations, and other troubling symptoms.

“We hope that our research will have clinical implications that extend far beyond the potential for identifying treatment targets for ADHD,” she says.

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Reconceptualizing mind wandering from a switching perspective

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• Published: 29 March 2022
• Volume 87 , pages 357–372, ( 2023 )

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• Yi-Sheng Wong   ORCID: orcid.org/0000-0002-5752-4679 1 , 2 , 3 ,
• Adrian R. Willoughby   ORCID: orcid.org/0000-0002-4214-2635 3 , 4 &
• Liana Machado   ORCID: orcid.org/0000-0002-0856-3831 1 , 2  

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Mind wandering is a universal phenomenon in which our attention shifts away from the task at hand toward task - unrelated thoughts. Despite it inherently involving a shift in mental set, little is known about the role of cognitive flexibility in mind wandering. In this article we consider the potential of cognitive flexibility as a mechanism for mediating and/or regulating the occurrence of mind wandering. Our review begins with a brief introduction to the prominent theories of mind wandering—the executive failure hypothesis, the decoupling hypothesis, the process - occurrence framework, and the resource - control account of sustained attention. Then, after discussing their respective merits and weaknesses, we put forward a new perspective of mind wandering focused on cognitive flexibility, which provides an account more in line with the data to date, including why older populations experience a reduction in mind wandering. After summarizing initial evidence prompting this new perspective, drawn from several mind - wandering and task - switching studies, we recommend avenues for future research aimed at further understanding the importance of cognitive flexibility in mind wandering.

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Introduction

In the past two decades, there has been growing interest in understanding the basic psychological processes of mind wandering and its underlying mechanisms (for a review, see Kvavilashvili & Rummel, 2020 ). Mind wandering refers to a phenomenon in which our attention shifts away from the task at hand toward task - unrelated thoughts (for reviews, see Smallwood et al., 2018 ; Smallwood & Schooler, 2006 , 2015 ). It has been estimated that up to 50% of our waking time is spent mind wandering (Kane et al., 2007 ; Killingsworth & Gilbert, 2010 ). Despite its prevalence, most people view mind wandering from a negative perspective, in which our performance will drop if our mind wanders (for reviews, see Mooneyham & Schooler, 2013 ; Stan & Christoff, 2018 ). Indeed, a number of studies have found a negative association between mind wandering and primary task performance, including poorer performance in daily functioning (McVay et al., 2009 ) and driving (Baldwin et al., 2017 ; Yanko & Spalek, 2014 ). However, studies have also shown a positive relationship between mind wandering and both mood and cognition (e.g., Gable et al., 2019 ; Mazzoni, 2019 ; Welz et al., 2018 ). In order to understand how to minimize the costs of mind wandering and maximize its benefits, it is therefore important to determine what factors regulate its occurrence.

Despite mind wandering inherently involving a shift in mental set, no existing study to our knowledge has explicitly examined the role of cognitive flexibility in mind wandering. In the present article, we consider the potential of cognitive flexibility to help explain the nature of mind wandering and its tendencies. In an effort to advance the field, here we first briefly review and discuss the most prominent theories of mind wandering—the executive failure hypothesis (McVay & Kane, 2009 , 2010 , 2012b ), the decoupling hypothesis (Smallwood & Schooler, 2006 ), the process - occurrence framework (Smallwood, 2013 ), and the resource - control account of sustained attention (Thomson et al., 2015 ). Then, we put forward a new perspective centered around cognitive flexibility that was prompted by findings from several mind - wandering studies in older adults (e.g., Gyurkovics et al., 2018 ; Jordão et al., 2019 ; Niedzwienska & Kvavilashvili, 2018 ) and mind - wandering studies involving task-switching paradigms in young adults (e.g., Arnau et al., 2020 ; Kam & Handy, 2014 ; Thomson et al., 2014 ). According to this new switching perspective, the reason why some populations (e.g., healthy older adults) experience distinct patterns of mind wandering stems from differences in cognitive flexibility, as instances of mind wandering are in fact instances of mental set shifting (see Murray & Krasich, 2020 , for a similar argument). After presenting the evidence supporting this new perspective, we put forward recommendations for future research aimed at further understanding the importance of cognitive flexibility in mind wandering.

Existing theories of mind wandering

Executive failure hypothesis.

According to the executive failure hypothesis (McVay & Kane, 2009 , 2010 , 2012b ), the occurrence of mind wandering represents a failure in the control of executive resources to keep attention on the current task, as the suppression of mind wandering requires executive control. One key form of executive control is working memory. This hypothesis posits that individuals with lower working memory capacity (i.e., those who are less able to hold information in an active, quickly retrievable state; Engle, 2002 ) are less capable of maintaining task focus over extended periods of time and keeping mind wandering at bay, and consequently experience more mind wandering. In support of this hypothesis, studies have found that individuals with lower working memory capacity have higher self - reported mind - wandering rates than individuals with higher working memory capacity (McVay & Kane, 2009 , 2012a , 2012b ; Robison & Unsworth, 2018 ; Unsworth & Robison, 2020 ), and working memory capacity can reliably predict how often one’s mind wanders (Kane et al., 2001 ; Robison & Unsworth, 2018 ). A meta - analysis that examined the association between mind wandering, executive resources (e.g., working memory capacity), and task performance also provided support for this hypothesis, by showing that individuals with lower working memory capacity tend to engage in more mind wandering than individuals with higher working memory capacity (Randall et al., 2014 ).

Additional evidence in support of the executive failure hypothesis comes from research on mind wandering involving individuals with attention - deficit/hyperactivity disorder (ADHD; for a review, see Bozhilova et al., 2018 )—a neurodevelopmental disorder characterized by inattentiveness, hyperactivity, and/or impulsivity (American Psychiatric Association, 2013 ). Using a probe - caught method, in which participants are intermittently interrupted during a vigilance task and probed to report where their attention is focused, Shaw & Giambra, ( 1993 ) showed that participants with a childhood history of ADHD diagnosis reported experiencing more task - unrelated thoughts during task performance than participants with no history of ADHD. Another study, which distinguished between deliberate mind wandering and spontaneous mind wandering, found that the occurrence of spontaneous, but not deliberate, mind wandering is positively associated with ADHD symptom severity (Seli et al., 2015 ). A similar result was obtained by Franklin et al., ( 2017 ), who found that a composite index of ADHD symptoms was positively correlated with both the frequency of mind wandering and a lack of awareness of mind wandering. More recently, Mowlem et al., ( 2019 ) demonstrated that elevated frequencies of mind wandering in adults with ADHD were positively correlated with self - reported measures of functional impairment across major life domains (e.g., school), and that the contribution of mind wandering to their impairment was independent of the core ADHD symptoms (inattention, hyperactivity, and impulsivity). Given that most individuals with ADHD have deficits in a variety of cognitive domains (e.g., Coutinho et al., 2018 ; Kasper et al., 2012 ; Ramos et al., 2020 ), these studies suggest that the excessive mind wandering they experience could be attributable to, at least in part, a failure of executive control (McVay & Kane, 2010 ).

Decoupling hypothesis

The decoupling hypothesis (Smallwood & Schooler, 2006 ) suggests that decreased performance during mind wandering occurs primarily because our attention has become decoupled from the task at hand and is instead coupled to task - unrelated thoughts. This decoupling process is important as it prevents information processing of extraneous stimuli from interfering with our current mental focus (Smallwood et al., 2011 ) in order to ensure continuity of the train of thought (Smallwood, 2013 ). In other words, the decoupling hypothesis proposes that mind wandering is a process that relies on some of the same cognitive mechanisms involved in maintaining focused attention on the task at hand and thus directly competes with primary task performance for executive resources (Smallwood & Schooler, 2006 ).

Several event - related potential (ERP) studies have provided strong evidence for this hypothesis. For example, using the sustained attention to response task (SART; Robertson et al., 1997 ), Smallwood et al., ( 2008 ) showed that participants had a reduced P300 amplitude during self - reported mind wandering relative to on - task episodes. The P300 is a positive potential that peaks around 300 ms after stimulus presentation and is believed to reflect the extent to which the stimulus representation is updated in working memory (Donchin, 1981 ; Donchin & Coles, 1988 ) and/or the amount of executive resources allocated toward the stimulus (Kramer & Strayer, 1988 ; Wickens et al., 1983 ), with higher amplitude indicating more revision of the representations and/or more executive resources directed to processing the stimulus (for reviews, see Polich, 2007 ; Verleger, 2020 ). Because the P300 can provide an index of executive resources (e.g., Kramer & Strayer, 1988 ; Wickens et al., 1983 ), the decreased P300 amplitude during mind wandering indicates that our executive resources have been withdrawn, at least partly, from the primary task and are presumably directed toward task - unrelated thoughts (Smallwood, 2010 ; Smallwood & Schooler, 2006 ). Similar results were obtained in subsequent studies (Baldwin et al., 2017 ; Barron et al., 2011 ; Kam et al., 2014 ; Maillet et al., 2020 ).

Process-occurrence framework

The process - occurrence framework, which was proposed by Smallwood, ( 2013 ), emphasizes the necessity of distinguishing between the onset of mind wandering and the continuation of the mind-wandering episode, linking McVay and Kane’s view (i.e., executive control failure) to the onset and Smallwood and Schooler’s view (i.e., mind wandering requires executive resources) to the continuation of the episode. According to this framework, under tasks requiring sustained attention, executive control can keep mind wandering at bay by ensuring the continuity of the train of task - related thought. However, when mind wandering occurs (e.g., due to executive control failure; McVay & Kane, 2009 , 2010 , 2012b ), executive control shifts away (i.e., decouples) from the task at hand to enable the continuation of the mind-wandering episode (which consumes the same executive resources as the task at hand; Smallwood & Schooler, 2006 ), leaving insufficient executive resources for the primary task, thereby resulting in impaired task performance (Smallwood et al., 2012 ).

As proposed by Smallwood, ( 2013 ), there are at least two reasons why one would mind wander more. First, because the individual has difficulties in ensuring the continuity of their train of thought (see also McVay & Kane, 2010 ). This account could explain why individuals with ADHD tend to experience more mind wandering episodes (Bozhilova et al., 2018 ; Franklin et al., 2017 ; Mowlem et al., 2019 ; Seli et al., 2015 ; Shaw & Giambra, 1993 ). Second, because the individual considers their currently relevant personal concerns or unresolved goals (e.g., submit the assignment before the end of the day) as having higher priority than the demands of the task at hand, and thus shifts their attention toward these concerns (see also Klinger, 1975 , 1999 ). This account could explain why older adults report less mind wandering than young adults (e.g., Jordão et al., 2019 ; Maillet & Schacter, 2016 ), as they tend to report having fewer concerns (Parks et al., 1989 ). In the former case, according to this framework (Smallwood, 2013 ), the individual should experience more frequent mind-wandering episodes, whereas in the latter case, the individual should experience longer episodes of mind wandering.

Although it is difficult to identify different states and processes involved in mind wandering, primarily because people normally do not realize when they first start mind wandering but only notice some time later (Smallwood, 2013 ; Zukosky & Wang, 2021 ), there has been one study to date that made an attempt at this (Voss et al., 2018 ). In this study, the researchers characterized the mind-wandering process by combining the self-caught and the probe-caught methods to estimate the duration of focus (defined as the time period from when the person first started focusing on the task at hand to the moment that mind wandering began), which was taken as a measure of one’s ability to maintain task focus and resist the occurrence of mind wandering, and the duration of mind wandering (defined as the time period from when the mind-wandering episode began to the moment that the individual caught themselves and reported it by pressing a button), which was taken as a measure of processes that keep one in the mind-wandering state. The researchers then investigated the association of these measures with working memory capacity. The results showed a strong positive correlation between the duration of focus and working memory capacity, which is consistent with previous findings that individuals with higher working memory capacity could maintain task focus over longer periods of time (Kane et al., 2001 ; McVay & Kane, 2009 , 2012a , 2012b ; Randall et al., 2014 ; Robison & Unsworth, 2018 ; Unsworth & Robison, 2020 ). However, no relationship was observed between the duration of mind wandering and working memory capacity, indicating that one’s tendency to engage in and detect the mind-wandering state was not affected by working memory capacity. The Voss et al., ( 2018 ) study, therefore, provides initial evidence to support the process - occurrence framework (Smallwood, 2013 ) that there are at least two distinct states and processes involved in mind wandering.

Resource-control account of sustained attention

According to the resource - control account of sustained attention (Thomson et al., 2015 ), mind-wandering state is the default mental state and thus there is a continuous bias for executive resources to be directed toward mind wandering (see also Baird et al., 2011 ; Smallwood, 2013 ; Smallwood et al., 2009 ). This theory posits that the occurrence of mind wandering should be associated with decreases in motivation and/or effort to keep attention on the task at hand over time. In other words, as time-on-task increases, executive resources are less likely to be allocated to the task at hand and are more likely to be allocated to mind wandering, leaving insufficient executive resources for the primary task and thereby resulting in impaired task performance. In support of this theory, studies have found a negative association between time on task and primary task performance, and a positive association between time on task and rates of self - reported mind wandering (Brosowsky et al., 2020 ; Krimsky et al., 2017 ; McVay & Kane, 2012a ; Thomson et al., 2014 ).

Interim summary

Taken together, these four theories suggest that mind wandering is a state of decoupled information processing (Smallwood and Schooler’s view) that involves at least two component processes (Smallwood’s view): the initiation of mind wandering, which can be attributed to a failure of executive control (McVay and Kane’s view), and the continuation of the mind-wandering episode, which is a resource-dependent process (Smallwood and Schooler’s and Thomson et al.’s view). Although these four theories significantly advance our understanding of mind wandering, they are not without weaknesses or alternative interpretations. In the next section, we discuss these and put forward a new perspective of mind wandering focused on cognitive flexibility, which offers novel insight that aids towards our general understanding of mind wandering.

Insight from a switching perspective

Cognitive flexibility, which can also be referred to as mental set shifting or switching, is one of the three core executive control functions (along with inhibitory control and working memory) that enables us to adjust our thoughts and actions in response to changed priorities or demands (Buttelmann & Karbach, 2017 ; Diamond, 2013 ; Miyake et al., 2000 ). To adapt to changing priorities, for example, we need to inhibit previously relevant thoughts and actions and activate newly relevant thoughts and actions in working memory. In this way, mental set shifting requires involvement of both inhibitory control and working memory (Diamond, 2013 ). With regard to mind wandering, we propose that it requires cognitive flexibility, as the occurrence of mind wandering entails inhibition of one’s primary task mental set (which enables decoupling to occur) and activation of task - unrelated thoughts in working memory (see Fig.  1 ).

Conceptual framework for viewing mind wandering from a switching perspective. Maintenance of both primary task and mind - wandering mental sets occur in working memory. Each change of mental set requires inhibition of the previously relevant mental set. Grey area represents the time in which primary task performance costs arise

Considering this switching view alongside existing frameworks and models such as the metacontrol state model (Hommel, 2015 ), which describes the balance between flexibility and persistence in cognitive processing (Zhang et al., 2020 ), may provide a way to understand variability in mind-wandering frequency. For instance, given that ADHD has long been found to be associated with dysregulated dopamine neurotransmission (Cook et al., 1995 ), and dopamine-related interindividual differences have been hypothesized to be associated with interindividual variability in metacontrol defaults (i.e., the control of the current cognitive-control settings; Hommel & Colzato, 2017 ), it seems possible that the increased mind wandering experienced by individuals with ADHD might be associated with a default metacontrol setting biased towards flexibility (i.e., weak goal shielding and weak mutual inhibition of task-related and task-unrelated mental sets) that may be related to imbalances of neurotransmitters. Moreover, given that older adults tend to report higher levels of positive affect (e.g., Frank et al., 2015 ) and motivation (e.g., Nicosia & Balota, 2021 ; Ryan & Campbell, 2021 ; Seli et al., 2021 ) than young adults during task performance, and situational factors such as these have been hypothesized to induce a metacontrol setting biased towards persistence (Hommel & Colzato, 2017 ), it seems possible that older adults’ less frequent reports of mind wandering (e.g., Arnicane et al., 2021 ; Jordão et al., 2019 ; Maillet & Schacter, 2016 ) might be associated with a stronger bias towards persistence (i.e., stronger goal shielding and stronger mutual inhibition of task-related and task-unrelated mental sets).

It may also be possible to account for the effect of mind wandering on creativity (e.g., Gable et al., 2019 ; Murray et al., 2021 ; Steindorf et al., 2021 ; Yamaoka & Yukawa, 2020 ) by integrating the switching perspective of mind wandering with both the metacontrol state model (Hommel, 2015 ) and the dynamic framework of thought (Christoff et al., 2016 )—a model that provides insight into how thoughts that focus on personally or affectively salient information (i.e., automatic constraints) and thoughts that focus on goal-related information (i.e., deliberate constraints) dynamically influence the nature of thought over time. For example, given that both of these schemas emphasize the importance of flexibility or shifting between mental states in idea generation (for reviews, see Girn et al., 2020 ; Zhang et al., 2020 ), it seems possible that the relationship between mind wandering and creative thinking might be mediated by cognitive flexibility. This speculation may be worthy of future research.

In short, we believe that viewing mind wandering from a switching perspective may help explain, at least in part, why some populations experience more mind-wandering episodes while others experience fewer episodes, why participants who indicate higher levels of motivation are less likely to engage in mind wandering during task performance, and why mind wandering is sometimes linked to enhanced creativity.

Limitations and an alternative viewpoint for the executive failure hypothesis

Although the executive failure hypothesis (McVay & Kane, 2009 , 2010 , 2012b ), which posits that working memory plays a critical role in keeping mind wandering at bay, could explain the higher levels of mind wandering in healthy young adults with lower working memory capacity and individuals with ADHD, mind-wandering research involving other cohorts with lower working memory capacity has yielded results that challenge this account. For instance, a meta - analysis of 21 studies investigating aging effects in mind wandering revealed that older adults tend to report fewer instances of mind wandering when engaged in cognitive tasks (Jordão et al., 2019 ). This is puzzling given that according to the executive failure hypothesis, one would expect the rates of mind wandering to increase—not decrease—in older adults (for a review, see Maillet & Schacter, 2016 ), as executive control functions generally decline with advancing age (e.g., Craik & Salthouse, 2011 ; Foster et al., 2007 ; Machado, 2021 ). Furthermore, using the SART, Gyurkovics et al. ( 2018 ) found that individuals with early-stage Alzheimer’s disease reported experiencing fewer task - unrelated thoughts and more task - related thoughts than healthy age - matched controls, again indicating reduced incidence of mind wandering despite individuals with Alzheimer's disease showing declines in executive functioning (Guarino et al., 2018 ). Similar results have been reported in studies involving individuals with Parkinson’s disease (Walpola et al., 2020 ), who are also known to suffer from executive dysfunction (Flannery et al., 2018 ; McKinlay et al., 2010 ; Ramos & Machado, 2021 ), and individuals with amnestic mild cognitive impairment (Niedzwienska & Kvavilashvili, 2018 ).

A counterargument to the claim that lower levels of mind wandering in these older populations stand against the executive failure hypothesis stems from the fact that mind - wandering studies mostly rely on self - report measures. In relation to this, some researchers have attributed the finding of reduced mind wandering in healthy and cognitively impaired older adults to a lack of validity of their mind - wandering reports (Gyurkovics et al., 2018 ; Jackson & Balota, 2012 ; Zavagnin et al., 2014 ). However, several studies have demonstrated that these populations’ self - reported mind-wandering data are as valid as those by controls, by demonstrating that during self - reported off - task episodes, the two groups exhibited similar levels of disrupted task performance (e.g., Arnicane et al., 2021 ; McVay et al., 2013 ; Niedzwienska & Kvavilashvili, 2018 ). Moreover, eye movement (Frank et al., 2015 ) and brain activation (Maillet & Rajah, 2016 ; Walpola et al., 2020 ) patterns reliably predicted self - reported mind - wandering episodes in older adults and individuals with Parkinson’s disease, indicating that they were able to report their mind - wandering episodes accurately. These results, therefore, suggest that the explanation that decreased mind wandering relates to lack of validity of mind-wandering measures in these older populations does not hold up.

To shed light on decreased mind wandering in older cohorts, here we offer an alternative account of mind wandering focused on cognitive flexibility (for a summary of other alternative explanations for age-related declines in mind wandering, see Seli, Maillet, et al., 2017 ; Seli, Ralph, et al., 2017 ). According to this account, the reduced mind - wandering frequency seen in healthy older adults and those with Alzheimer’s disease, Parkinson’s disease, and amnestic mild cognitive impairment could be attributable, at least partly, to declines in cognitive flexibility (e.g., a reduced ability to switch between task - related and task - unrelated thoughts; see Fig.  2 ). This line of reasoning fits well with research showing that these older populations generally have a reduced capability to activate (e.g., to initiate a switch of mental set) and maintain cognitive representations (e.g., to maintain the new mental set; Craik & Salthouse, 2011 ; Lindenberger & Mayr, 2014 ; Traykov et al., 2007 ), and exhibit longer response times and/or higher error rates on switch trials relative to repetition trials (e.g., Brett & Machado, 2017 ; Rey-Mermet & Gade, 2018 ; Wasylyshyn et al., 2011 ).

Summary of results gathered from several mind-wandering, working memory, and task-switching studies . AD Alzheimer’s disease, PD Parkinson’s disease, aMCI amnestic mild cognitive impairment, WMC working memory capacity. Red circle represents poorer performance and green circle represents better performance, relative to the comparison group. White thought bubble cloud represents mind-wandering frequency, with fewer clouds representing less frequent occurrences of mind wandering, relative to the comparison group

Furthermore, given that previous research in healthy young adults has revealed a negative association between working memory capacity and mind - wandering frequency (McVay & Kane, 2009 , 2012b ; Robison & Unsworth, 2018 ; Unsworth & Robison, 2020 ), and a negative correlation between working memory capacity and task - switching performance (Miyake et al., 2000 ; Oberauer et al., 2003 ; Shipstead et al., 2015 ; for more details, see Draheim et al., 2016 ), it seems plausible that healthy young adults with lower working memory capacity might be more capable of adjusting their executive resources to different mental sets (including task-unrelated mental sets) due to their superior switching abilities (see the “ Future directions ” for further elaboration of this conjecture; see Fig.  2 ). In short, although the executive failure hypothesis (McVay & Kane, 2009 , 2010 , 2012b ) holds up quite well for younger populations, the switching account of mind wandering put forward here could potentially also explain the patterns of results in these populations. Moreover, in contrast to the executive failure hypothesis which cannot account for the lower levels of mind wandering observed in older populations (as it predicts that these populations should exhibit elevated levels of mind wandering due to having lower working memory capacity), our switching account of mind wandering fits well with the existing data, suggesting that cognitive flexibility may play a more important role than working memory does in mediating and/or regulating the occurrence of mind wandering.

An alternative interpretation for the decoupling hypothesis

Although studies using ERPs have provided evidence in favor of the decoupling hypothesis (Smallwood & Schooler, 2006 ) by demonstrating that mind wandering reduces the cortical processing of the task at hand (as reflected by the reduced P300 amplitude during mind wandering; Baldwin et al., 2017 ; Barron et al., 2011 ; Kam et al., 2014 ; Maillet et al., 2020 ; Smallwood et al., 2008 ), these findings could also be interpreted from a switching perspective. Previous research on task switching has consistently revealed a reduced P300 amplitude on switch trials relative to repetition trials (e.g., Barcelo et al., 2002 ; Hsieh & Cheng, 2006 ; Kieffaber & Hetrick, 2005 ; Mueller et al., 2007 ; Poljac & Yeung, 2014 ; Vandamme et al., 2010 ; Wylie et al., 2003 ). According to Jost et al. ( 2008 ), the reduced P300 amplitude in switch trials is thought to indicate that context updating (i.e., the comparison of the attributes of an incoming stimulus with an internal representation and the subsequent updating of the internal representation; Donchin, 1981 ; Donchin & Coles, 1988 ) is less easily achieved. Another explanation comes from Wylie et al., ( 2003 ), who suggested that the reduced P300 amplitude reflects a competition between task sets or rules, with the idea being that on switch trials the competition between task - specific response sets or rules is greater. This results in both a reduction in P300 amplitude and an increase in response time and/or error rate because the activation of the currently relevant task representation is less enhanced. Using the findings from these task - switching studies as a foundation, we posit that the attenuated P300 amplitude during mind wandering could reflect two possible processes, including ( a ) less efficient context updating in working memory (Donchin, 1981 ; Donchin & Coles, 1988 ), and/or ( b ) competition between primary-task representations and task - unrelated thoughts.

Building on this alternative perspective, we suggest that the decoupling process is a component of the switching process. As such, mind wandering could be considered as a subset of task switching that typically would run serially with task performance (i.e., serial multitasking; e.g., Huijser et al., 2018 ; for more details, see Taatgen et al., 2021 ), although a recent study has shown that mind wandering can also run parallelly with particular kinds of tasks (i.e., parallel multitasking; e.g., Brosowsky et al., 2021 ). Furthermore, in the context of serial processing of multiple mental sets, switch costs should be observed regardless of whether the shift is from external to internal (e.g., shifting from a SART to task-irrelevant personal concerns), internal to external (e.g., shifting from task-irrelevant personal concerns back to the SART), or internal to internal (e.g., shifting from mental arithmetic to task-irrelevant personal concerns). According to our view, the detrimental effect of mind wandering on primary task performance reflects the costs of switching between mental sets (i.e., decoupling from the primary task’s mental set and coupling to task - unrelated thoughts; see Fig.  1 ), in addition to the costs of not paying attention to the primary task while decoupled. This proposal is in line with research on task switching that demonstrated that switch costs could still be observed when the tasks were relatively simple, when the task sequence was predictable, and when there was a cue signaling the upcoming switch (Koch, 2003 ).

A possible way to test the process-occurrence framework

Within the process-occurrence framework, Smallwood aptly noted the following:

…the processes that ensure the continuity of the experience of an internal train of thought are similar to those that can be engaged in standard task-relevant paradigms, and as a result, these processes are becoming reasonably well understood. By contrast, our understanding of why mind wandering occurs is less well specified, in part because we are unable to identify the moment of ignition for the state. (Smallwood, 2013 , p. 532).

Indeed, as mentioned earlier, one major challenge in investigating the length of mind-wandering episodes is how to determine the “when” of mind wandering (Franklin et al., 2013 ). Although Voss et al., ( 2018 ) have provided evidence in favor of the process-occurrence framework by identifying different states and processes of mind wandering (see the “ Process-occurrence framework ” for more details), one key limitation of this study, as pointed out by the researchers themselves, was that their assessment methods hinged on the assumption that the only way for an individual to redirect their attention from mind wandering back to the task at hand is through a mechanism reliant upon self-awareness (i.e., the meta-awareness system; Schooler et al., 2011 ). If one can return to a task-focused state without relying on such a mechanism (e.g., decoupling from task-unrelated thoughts and coupling to the primary task’s mental set without conscious awareness), and can have multiple switches between task-focused and mind-wandering states during a single self-caught episode, then the estimated duration of focus and mind-wandering episodes (defined earlier in the “ Process-occurrence framework ”) could in fact reflect multiple focus-mind-wandering episodes, rather than the duration of each individual task-focused/mind-wandering state (Voss et al., 2018 ).

To shed light on how to measure the component processes of mind wandering while acknowledging that mind wandering often consumes executive resources that are needed to perform the task (i.e., parallel processing of both high cognitive demand tasks and mind wandering is difficult to achieve; Smallwood & Schooler, 2006 ; Thomson et al., 2015 ), here we put forward a new approach that links the onset of mind wandering to the onset of a new mental set, and the continuation of the mind-wandering episode to the continuation of the new mental set. Previous task-switching studies have identified a number of distinct cognitive processes underlying an attentional set switch (e.g., Meiran et al., 2000 ; Rushworth et al., 2002 , 2005 ). For instance, Rushworth et al., ( 2002 ) found that mental set shifting consisted of at least three component cognitive processes, including: ( a ) initiation of a new mental set prior to selective focusing of attention, which was indexed by an early period of ERP modulation associated with dipole source estimates in the prefrontal cortex; ( b ) reconfiguration of the new mental set, which was indexed by a later period of ERP modulation associated with dipole source estimates at the ventromedial occipitotemporal junction; and ( c ) maintenance of the new mental set and possible interference from the previous mental set, which was indexed by the N200—a negative potential over the central posterior scalp that peaks around 200 ms after stimulus presentation and is believed to be associated with response suppression (Eimer, 1993 ; Kok, 1986 ; Patel & Azzam, 2005 ). Building on these findings, we posit that at the start of the mind-wandering episode, there should be activation in the prefrontal cortex (for a review, see Zamani et al., 2022 )—a region that has been found to play a central role in cognitive flexibility (Dove et al., 2000 ; Miller & Buschman, 2013 ; Miller & Cohen, 2001 ; Sakai & Passingham, 2003 ; Sohn et al., 2000 ) and mind wandering (Bertossi & Ciaramelli, 2016 ; Burgess et al., 2007 ; Christoff et al., 2009 ; Fox et al., 2015 ; Stawarczyk & D’Argembeau, 2015 ).

Using these findings as a foundation, it seems possible that the “when” of mind wandering (i.e., the onset of mental set shifting) can be estimated, at least approximately, from activity in the prefrontal cortex measured prior to periods of self-reported mind wandering. This conjecture seems to fit with findings that non-invasive transcranial direct current stimulation of the prefrontal cortex can increase the propensity to mind wander (e.g., Axelrod et al., 2015 , 2018 ; Filmer et al., 2019 ). To clarify, we postulate that positive-polarity stimulation “encourages” the recipient to initiate a switch of mental set, which according to the resource-control account of sustained attention (Thomson et al., 2015 ) is most likely to involve a switch to a task-unrelated mental set as mind wandering is thought to be the default mental state for most individuals.

Limitations and a possible extension for the resource-control account of sustained attention

Although the resource-control account of sustained attention (Thomson et al., 2015 ), which suggests that the occurrence of mind wandering is associated with decreases in motivation and/or effort to keep attention on the task at hand over time, could explain why older adults tend to report fewer instances of mind wandering than young adults during cognitive task performance—either because they are more motivated to perform the primary task (Frank et al., 2015 ; Jackson & Balota, 2012 ; Seli et al., 2021 ; Seli, Maillet, et al., 2017 ; Seli, Ralph, et al., 2017 ) or because they have spent a larger proportion of their executive resources on the primary task (Craik & Byrd, 1982 ) and thus have fewer resources left over to exhibit mind wandering (Giambra, 1989 ; Krawietz et al., 2012 ; Maillet & Rajah, 2013 )—this theory is not without its limitations. In particular, if executive control, which wanes over time on task, is required to prevent task-unrelated thoughts (i.e., the default mental state) from consuming executive resources needed for the task at hand, then given that healthy and cognitively impaired older adults generally have poorer executive control (e.g., Flannery et al., 2018 ; Guarino et al., 2018 ; McKinlay et al., 2010 ; Ramos & Machado, 2021 ), one might reasonably expect that as time-on-task increases, these older populations would report higher incidences of mind wandering and show more pronounced performance decrements. However, this prediction was not supported by Arnicane et al., ( 2021 ), who found that in comparison to the first block (i.e., the first 15 min) of a visual working memory task, in the sixth block healthy older adults reported similar levels of attentional lapses and demonstrated improved performance. These results, therefore, are inconsistent with the predictions of the resource-control account of sustained attention, as they showed that extended task duration in fact has positive effects on healthy older adults’ working memory performance.

Here, we posit that the occurrence of mind wandering should be also associated with fluctuations in activity in brain regions associated with executive control (the frontal-parietal and dorsal attention networks; Corbetta & Shulman, 2002 ; Corbetta et al., 2008 ; Posner & Dehaene, 1994 ; Vincent et al., 2008 ) and mind wandering (the default mode network; Raichle et al., 2001 ), and that these fluctuations should be inversely related (see also Esterman & Rothlein, 2019 ). According to this account, because normal aging is associated with significant decreases in the strength of functional connectivity density (i.e., the statistical relationship between brain regions; Tomasi & Volkow, 2010 ) in the dorsal attention and default mode networks (Tomasi & Volkow, 2012 ), the lower frequencies of mind wandering reported in healthy older adults could be attributable to less efficient switching and/or cooperation between these two networks to produce a train of thought during mind wandering (Smallwood et al., 2012 ). This proposal goes beyond the resource-control account of sustained attention, which cannot account for the findings that longer task duration does not lead to a higher incidence of mind wandering or more pronounced performance decrements in healthy older adults (Arnicane et al., 2021 ). In support of this proposal, studies have shown that mind wandering is associated with increased default mode network and decreased dorsal attention network activation (Christoff et al., 2009 ; Fortenbaugh et al., 2018 ; Kucyi et al., 2013 ; Mason et al., 2007 ; Robertson et al., 1997 ; Smallwood et al., 2013 ), indicating that there might be a push–pull relationship between these two networks that impacts the occurrence of mind wandering (cf. Esterman & Rothlein, 2019 ).

We have shown that the switching perspective is a useful addition to the four prominent theories of mind wandering. While acknowledging that other factors may be at play, this newly formulated view not only provides a plausible explanation as to why healthy and cognitively impaired older adults experience a reduction in mind wandering, but it also provides new insights for determining the initiation of mind-wandering episodes. In the next section, we present evidence to support our view.

Review of evidence supporting the switching perspective

The strongest evidence to date in support of this new perspective comes from research using the voluntary task - switching paradigm (Arrington & Logan, 2004 ), for which participants are free to switch tasks or continue with the same task at their preference. Somewhat paradoxically, research has consistently demonstrated that most of the participants decided to switch tasks despite negative consequences (i.e., switch costs; e.g., Irons & Leber, 2016 ; Kessler et al., 2009 ; Mittelstädt et al., 2019 ), although comparatively healthy older adults tended to initiate voluntary task switching less frequently than healthy young adults (Ardiale & Lemaire, 2012 ; Butler & Weywadt, 2013 ; Lockenhoff et al., 2020 ; Terry & Sliwinski, 2012 ). In light of cognitive aging, this finding may not seem surprising given that repeating the currently active task set requires fewer executive resources than switching to a different task set (Wirth et al., 2018 ) and switching between task sets or rules increases cognitive load (Arrington & Logan, 2004 ; Kool et al., 2010 ). In like manner, we argue that it should not be surprising either that healthy older adults and older adults with Alzheimer’s disease, Parkinson’s disease, and amnestic mild cognitive impairment experience less frequent mind wandering, as a reduced switching ability could contribute, at least in part, to getting “stuck” in a task - focus mode (cf. Walpola et al., 2020 ).

Additional evidence for the switching perspective of mind wandering comes from the intriguing finding that mind wandering does not always impair young adults’ performance in switching tasks, in contrast to tasks that require sustained attention. Using a probe - caught method, Kam & Handy, ( 2014 ) found no significant disruptive effects of mind wandering on task-switching performance. A further study, which investigated the association between mind wandering and task-switching performance over time, observed similar response times and accuracy rates for the trials leading up to “on-task” and “off-task” reports (Thomson et al., 2014 ), which again suggests that switching performance was unaffected by mind wandering. Similar results were obtained by Arnau et al., ( 2020 ), who investigated electrophysiological correlates of mind wandering during a switching task and did not observe slower response times during periods of self-reported mind wandering relative to on-task episodes.

The lack of performance costs, particularly response time costs, for switching tasks is puzzling because mind wandering has consistently been found to disrupt behavioral performance on tasks that tap the other two core executive function measures—inhibition (e.g., Kam & Handy, 2014 ; Smallwood et al., 2008 ; Stawarczyk et al., 2011 ) and working memory (e.g., Kam & Handy, 2014 ; Krimsky et al., 2017 ; Unsworth & Robison, 2016 ). Given this, one might expect that mind wandering should also significantly affect one’s task-switching performance. Although Kam & Handy, ( 2014 ) speculated that the null effect of mind wandering on switching-task performance might reflect cognitive flexibility being a less representative executive functioning skill (as it showed the weakest correlations with other executive function measures; for more details, see Miyake et al., 2000 ), these researchers also noted that switching from the task at hand to task-unrelated thoughts may be a form of switching. In the same manner, we posit that because switching either between task-related mental sets or between task-related and task-unrelated mental sets requires cognitive flexibility, when one mind wanders during performance of a switching task, they continue to engage in a “task-switching mind frame” (i.e., instead of switching between task-related mental sets, the individual switches between task-related and task-unrelated mental sets), and thereby can maintain task-switching performance. This conjecture appears to fit well with previous studies indicating that frequent task/response switches can shift the flexibility-persistence balance (Hommel, 2015 ) towards higher flexibility (e.g., Fröber & Dreisbach, 2017 ; Fröber et al., 2018 ; Zhuo et al., 2021 ; for a review, see Dreisbach & Fröber, 2019 ).

Future directions

Acknowledging that instances of mind wandering are instances of mental set shifting (see Murray & Krasich, 2020 , for a similar argument) opens up new avenues for future scientific investigations. First, to directly investigate this new perspective, future research could examine the association between cognitive flexibility and the tendency to mind wander, as despite a number of researchers using a task - switching paradigm as the primary task in their investigation of mind wandering (e.g., Arnau et al., 2020 ; Kam & Handy, 2014 ; Thomson et al., 2014 ), to our knowledge none have explicitly investigated the role of cognitive flexibility in mind wandering. Second, as there are many different types of switching (e.g., rule switching, task set switching, and response set switching), which have been found to activate different brain areas (Ravizza & Carter, 2008 ), it may be important to investigate how these switching abilities are related and which type is most closely associated with mind wandering. Determining this may help advance the current understanding of the higher incidence of mind wandering in ADHD, and may ultimately shed light on the inconsistent results regarding whether ADHD is associated with deficits in cognitive flexibility (e.g., Halleland et al., 2012 ; Irwin et al., 2019 ; Rohlf et al., 2012 ; Willcutt et al., 2005 ), which in turn may shed further light on the viability of the switching perspective forwarded here. Third, as an increasing number of studies have revealed distinct effects of intentional and unintentional mind wandering on task performance (e.g., Martínez-Pérez et al., 2021 ; Moran et al., 2021 ; Seli et al., 2016a , 2016b ; for a review, see Seli, et al., 2016a , 2016b ), future research could investigate whether intentional and unintentional mind wandering constitute distinct forms of task-set activation (e.g., counscious or uncounscious activation of task-unrelated mental sets; Arango-Muñoz & Bermúdez, 2021 ; Lau & Passingham, 2007 ; Reuss et al., 2011 ; Weibel et al., 2013 ) that involve distinct neural mechanisms and might differ with respect to their relationships with cognitive flexibility.

Fourth, considering that in a real-world setting we constantly multitask (e.g., writing an email while listening to music and eating a meal), and studies have found a positive association between self-reported frequency of concurrent use of multiple digital media streams and mind-wandering tendency (e.g., Kane et al., 2017 ; Ralph et al., 2014 ; Wiradhany & Koerts, 2021 ), future research could investigate the association between mind wandering, multitasking, and cognitive flexibility. Fifth, to understand past findings (e.g., McVay & Kane, 2009 ; Robison & Unsworth, 2018 ; Unsworth & Robison, 2020 ) in light of this switching perspective, future studies could investigate whether healthy young adults with higher self-reported mind-wandering tendencies have lower working memory capacity but superior switching abilities. In consideration of previous findings (e.g., McVay & Kane, 2009 , 2012b ; Miyake et al., 2000 ; Oberauer et al., 2003 ; Robison & Unsworth, 2018 ; Shipstead et al., 2015 ; Unsworth & Robison, 2020 ; as discussed in the “ Limitations and an alternative viewpoint for the executive failure hypothesis ”), the increased mind - wandering frequency seen in healthy young adults with lower working memory capacity could reflect a tendency to initiate more switches between task-related and task-unrelated mental sets in relation to superior switching abilities. Sixth, considering that the executive failure hypothesis (McVay & Kane, 2009 , 2010 , 2012b ) fits with the data in healthy young adults and individuals with ADHD, but does not account for the data in older adult populations discussed in this review, future research should explore the association between cognitive flexibility and the tendency to mind wander in different populations with age in mind, as it could be the case that the executive failure hypothesis applies to young adults whereas the switching account of mind wandering applies to older populations.

Concluding remarks

The findings reviewed in this article provide initial evidence to suggest that there may be an association between cognitive flexibility and mind wandering, and that distinct patterns of mind wandering may signal and be a product of altered cognitive flexibility. Although more research is needed, the switching perspective of mind wandering put forward here may provide a more comprehensive account of mind wandering that fits better with the experimental findings to date, including why healthy older adults and those with Alzheimer’s disease, Parkinson’s disease, and amnestic mild cognitive impairment experience less mind wandering (e.g., Gyurkovics et al., 2018 ; Jordão et al., 2019 ; Maillet & Schacter, 2016 ; Niedzwienska & Kvavilashvili, 2018 ; Walpola et al., 2020 ). This novel line of research may lead to the development of clinical detection tools and therapeutic approaches (e.g., task - switching training) aimed at preserving, or enhancing, the rates of mind wandering in populations with reduced levels of mind wandering (e.g., older adults), as mind wandering does have important functions such as facilitating future planning (e.g., Baird et al., 2011 ; Mazzoni, 2019 ; Seli, Maillet, et al., 2017 ; Seli, Ralph, et al., 2017 ; Stawarczyk et al., 2011 ) and the generation of creative ideas (e.g., Gable et al., 2019 ; Yamaoka & Yukawa, 2020 ) as well as promoting positive mood (e.g., Welz et al., 2018 ). Furthermore, recognizing that previous findings on mind wandering can be viewed from a switching perspective may provide an important contribution to our understanding of the basic psychological processes of mind wandering and its determinants, and may help future research to come up with a definition of mind wandering that will gain consensus in the field.

Data availability

Not applicable.

Code availability

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Y. - S.W. acknowledges the receipt of a PhD scholarship from the University of Otago. We thank Dr Marijn Kouwenhoven and Wayne Meighan for comments on earlier drafts. We have no known conflict of interest to disclose.

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Wong, YS., Willoughby, A. & Machado, L. Reconceptualizing mind wandering from a switching perspective. Psychological Research 87 , 357–372 (2023). https://doi.org/10.1007/s00426-022-01676-w

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Visual perspective and the characteristics of mind wandering

Affiliation.

• 1 School of Psychology, University of Aberdeen Aberdeen, UK.
• PMID: 24130538
• PMCID: PMC3793122
• DOI: 10.3389/fpsyg.2013.00699

When the mind wanders away from the here-and-now toward imaginary events, it typically does so from one of two visual vantage points-a first-person perspective (i.e., the world is seen as it is in everyday life) or a third-person perspective (i.e., the world is seen from the viewpoint of an outside observer). While extant evidence has detailed consequences that ensue from the utilization of these distinct points of view, less is known about their more basic properties. Here, we investigated the prevalence, demographics and qualities associated with the visual perspective that people spontaneously adopt when the mind wanders. The results from a cross-cultural survey (N = 400) revealed that almost half of the participants (46%) typically utilize a third-person perspective when mind wandering. Further, culture and gender were shown to impact the distribution of first- and third-person imagers. Specifically, a first-person perspective was more common among participants from Western nations and females, while participants from Eastern cultures resonated more strongly with a third-person perspective. Moreover, these factors were also shown to impact qualities (e.g., temporal locus, vividness) of mental imagery. Taken together, the current findings elucidate the prevalence of first- and third-person visual perspectives and detail individual differences that influence the qualia of mind wandering.

Keywords: cross cultural; mental imagery; mind wandering; third person; vantage point; visual perspective.

Researchers target neurogenesis in new approach to treat Parkinson's disease

Researchers at the University of Toronto have found a way to better control the preclinical generation of key neurons depleted in Parkinson's disease, pointing toward a new approach for a disease with no cure and few effective treatments.

The researchers used an antibody to selectively activate a receptor in a molecular signaling pathway to develop dopaminergic neurons. These neurons produce dopamine, a neurotransmitter critical to brain health.

Researchers around the world have been working to coax stem cells to differentiate into dopaminergic neurons, to replace those lost in patients living with Parkinson's disease. But efforts have been hindered in part by an inability to target specific receptors and areas of the brain.

"We used synthetic antibodies that we had previously developed to target the Wnt signaling pathway," said Stephane Angers, principal investigator on the study and director of the Donnelly Centre for Cellular and Molecular Biology.

"We can selectively activate this pathway to direct stem cells in the midbrain to develop into neurons by targeting specific receptors in the pathway," said Angers, who is also a professor in the Leslie Dan Faculty of Pharmacy and the Temerty Faculty of Medicine, and holds the Charles H. Best Chair of Medical Research at U of T. "This activation method has not been explored before."

The study was recently published in the journal Development .

Parkinson's disease is the second-most common neurological disorder after Alzheimer's, affecting over 100,000 Canadians. It particularly impacts older men, progressively impairing movement and causing pain as well as sleep and mental health issues.

Most previous research efforts to activate the Wnt signaling pathway have relied on a GSK3 enzyme inhibitor. This method involves multiple signaling pathways for stem cell proliferation and differentiation, which can lead to unintended effects on the newly produced neurons and activation of off-target cells.

"We developed an efficient method for stimulating stem cell differentiation to produce neural cells in the midbrain," said Andy Yang, first author on the study and a PhD student at the Donnelly Centre. "Moreover, cells activated via the FZD5 receptor closely resemble dopaminergic neurons of natural origin."

Another promising finding of the study was that implanting the artificially-produced neurons in a rodent model with Parkinson's disease led to improvement of the rodent's locomotive impairment.

"Our next step would be to continue using rodent or other suitable models to compare the outcomes of activating the FZD5 receptor and inhibiting GSK3," said Yang. "These experiments will confirm which method is more effective in improving symptoms of Parkinson's disease ahead of clinical trials."

This research was supported by the University of Toronto Medicine by Design program, which receives funding from the Canada First Research Excellence Fund, and the Canadian Institutes of Health Research.

• Parkinson's Research
• Diseases and Conditions
• Chronic Illness
• Disorders and Syndromes
• Parkinson's
• Alzheimer's
• Stem cell treatments
• Parkinson's disease
• Excitotoxicity and cell damage
• Biological psychiatry
• Deep brain stimulation
• Huntington's disease
• Multiple sclerosis
• Infectious disease

Story Source:

Materials provided by University of Toronto . Original written by Anika Hazra. Note: Content may be edited for style and length.

Journal Reference :

• Andy Yang, Rony Chidiac, Emma Russo, Hendrik Steenland, Quinn Pauli, Robert Bonin, Levi L. Blazer, Jarrett J. Adams, Sachdev S. Sidhu, Aleksandrina Goeva, Ali Salahpour, Stephane Angers. Exploiting spatiotemporal regulation of FZD5 during neural patterning for efficient ventral midbrain specification . Development , 2024; 151 (5) DOI: 10.1242/dev.202545

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Strange & offbeat.

How alternative, holistic therapies can help those with neurodegenerative disorders like Parkinson's

When Beth Elgort’s husband, Steve, was diagnosed with Parkinson’s disease around a dozen years ago, she made it her mission to optimize his quality of life while the couple adjusted to their new normal. 

Believing that South Florida’s tropical climate would be more conducive to helping him be active, the couple relocated from New York to Palm Beach Gardens. 

In addition to seeking the opinions of medical professionals, Beth, 67 — a longtime mental health counselor, social worker and nutrition expert — also did copious research on her own about alternative and holistic therapies. 

The Elgorts found that by keeping Steve, 77, physically active and creatively engaged, the worst symptoms of the neurodegenerative disease could be somewhat mitigated.

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Health priorities: We're in this together: Fighting the loneliness epidemic

And their success in combatting Steve’s disease progression led the couple to want to share what they’d learned with others who were living with Parkinson’s. 

“After years of social work practice, it was only natural to be a resource for my husband,” Beth Elgort said. “This grew into a desire to also advocate for others who have neurodegenerative diseases. My dream was to create a center that is a nurturing, safe environment where people can socialize and feel comfortable while taking classes to improve their neuroplasticity and movement.” 

From helping husband with Parkinson's to helping many

So, in February 2020, just before the world went into pandemic lockdown, Beth realized a years-long dream: She founded the nonprofit Mind, Music and Movement Foundation for Neurological Disorders. 

During that first year, most of the entity’s offerings were virtual. But as time passed and restrictions eased, they were able to begin offering in-person programming at Tropical Sands Christian Church (2726 Burns Road in Palm Beach Gardens). 

Among the offerings for Mind, Music and Movement clients: 

• The Voices of Parkinson’s Chorus 
• Yoga and meditation 
• Dance for fluidity 
• Nutritional counseling 
• Support services 

West Palm Beach neurologist Dr. Arif Dalvi, director of the Comprehensive Movement Disorders Program at Palm Beach Neuroscience Institute and a member of Mind, Music and Movement’s medical advisory committee, is a proponent of taking a multi-pronged approach to attacking neurodegenerative diseases. 

“Neurological disorders like Parkinson's disease are complex conditions that develop due to the death of the brain cells that produce dopamine,” Dalvi said. 

When medications are needed and potentially effective, Dalvi will certainly prescribe them. But he’s quick to add that “for someone with a neurological disorder, a holistic approach is needed — one that combines attention to diet, lifestyle, and supportive therapies, including physical and speech therapy.” 

Collaboration with Florida Atlantic University

As effective as Mind, Music and Movement has been at providing the community’s neurodegenerative disease sufferers with classes and advocacy, Beth wanted to reach even more people. 

So last month the organization announced a new partnership with Florida Atlantic University’s Stiles-Nicholson Brain Institute and Schmidt College of Medicine. 

“I have seen, firsthand, how alternative therapies help people thrive and possibly delay the progression of neurodegenerative diseases,” Elgort said. “This next step with FAU will help us reach even more people with our programming and events. And we are excited to participate in the Palm Beach County NeuroArts Collaborative with Palm Health Foundation and others.” 

Elgort explained that plans for the collaboration between her organization and FAU include integrating alternative therapy programs into FAU’s Schmidt College of Medicine to further provide resources and motivation for people to live well with neurodegenerative diseases. Early programming will include FAU High School STEM students volunteering community service hours to assist with their daily classes. The clients participating will also have access to be part of current research studies related to neurodegenerative diseases at FAU. 

“We are excited to partner with Mind, Music and Movement to expand the programs and services we provide to our students and our community to include the arts such as dance and music to enhance quality of life for those with Parkinson’s Disease,“ said Dr. Julie G. Pilitsis, dean of the Charles E. Schmidt College of Medicine and vice president for Medical Affairs at FAU. “This collaboration will help us to advance evidence-based clinical studies on alternative methods to improve movement, mood and cognition in those affected by neurodegenerative disorders, especially Parkinson’s disease.” 

“Our partnership with Mind, Music and Movement will enable us to combine our expertise and resources to provide our community with the latest advances and tools for brain health and will help to propel the arts in neuroscience in this region,” noted Dr. Randy D. Blakely, neuroscience professor of biomedical science in the FAU Schmidt College of Medicine. 

“In particular, the programs will provide an opportunity for faculty and trainees of the Institute’s David and Lynn Nicholson Center for Neurodegenerative Disease Research to engage closely with members of the community whose disorders they’re striving to understand and ultimately cure,” Blakely said. 

Mind, Music and Movement offers a variety of pricing options for its offerings (some of which are virtual) — ranging from an unlimited monthly membership to group bundles to individual classes. 

And for those who simply cannot afford the classes, Beth says “we believe wellness should be accessible to everyone no matter their financial status. If you’re unable to pay for classes, please contact us anyway because you may qualify for a scholarship.” 

To learn more about Mind, Music and Movement Foundation for Neurological Disorders, call 561-336-0902 or visit  m3f.org .