Study finds singing and imagining improvised music elicits flow-like brain states

 You just might want to have your doctor figure this out. It can't be any worse than the non-existent stroke protocols s/he has.

Study finds singing and imagining improvised music elicits flow-like brain states

MedicalXpress Breaking News-and-Events|October 15, 2021

A research team at Georgia State University has identified how the brain changes when artists are in a state of "flow" and found that simply imagining improvised performances elicits the same flow-like brain states as when musicians are singing.

In the new study, published in the journal Scientific Reports, researchers recruited 21 advanced jazz musicians, who were prompted to vocalize or imagine one of the four scores from the Bebop era of jazz based on a standard 12-bar blues chordal progression while undergoing functional magnetic resonance imaging (fMRI). The multidisciplinary research team—which includes experts in mathematics, physics, music, neuroscience and computer science—then used the fMRI data to identify how a musician's brain reconfigures connectivity depending on the degree of creativity required during jazz performances, focusing on two major brain networks: the default mode network and the executive control network.

"We estimated static functional network connectivity as jazz musicians were vocalizing, imagining, improvising or performing pre-learned, memorized scores," said principal investigator Victor M. Vergara.

Martin Norgaard, associate professor in the School of Music and co-author of the study, says the work provides new insight into the minds of expert jazz musicians at work.

"What's so fascinating is that we saw very similar brain patterns and activity whether they were actually scat singing or just imagining an improvised performance," said Norgaard.

The study builds on previous research demonstrating that subjects' brains show lower functional connectivity during musical improvisation. The new findings reveal that improvisation is associated with a state of weak connectivity to the brain's executive control network and to a feeling of "flow," which allows unhindered musical creation.

"The executive control network is typically active in many tasks, including solving problems. The default mode network seems to be more active when a subject is in the resting state," said Norgaard. "We saw that when expert musicians are improvising, the brain is interfering less with their creativity."

The study was conducted in collaboration with the Center for Translational Research in Neuroimaging and Data Science (TReNDS), which is supported by Georgia State, the Georgia Institute of Technology and Emory University. Vince Calhoun, founding director of TReNDS and a Distinguished University Professor in Psychology and Neuroscience, said the new study allowed researchers to observe widespread and richer effects of connectivity. It is the first analysis of whole brain connectivity during vocalized and imagined real-time production of creative output.

"The brain is highly dynamic, so mapping how brain function changes over time is a much more natural way to analyze the data and capture functional patterns linked to either behavioral conditions or to resting," said Calhoun.

As part of the team at TReNDS center, Vergara and his colleagues were able to extract signals from the brain using a non-invasive method to reduce any interference in the creative process. The team created a custom algorithm to identify the resting state networks.

"Brain imaging produces vast amounts of time-varying measurements that are difficult to parse. Pattern recognition algorithms were necessary to pinpoint the relevant brain areas involved in the creative process," said Vergara. "We then compared the different patterns to understand the differences between performing improvisation and pre-rehearsed music."

The study's paradigm allows for the inclusion of expert jazz performers with many different instrument specializations, which suggests the results may be broadly applicable to all improvising musicians. Future research could adapt the same paradigm to other activities where creation happens in real time—like in performing freestyle rap or spoken-word poetry and even playing sports—potentially identifying common threads in the creative process inside the human brain.

"Now there are more specific questions we can consider, like what changes are happening in the brain while someone improvises or which different networks are involved," said Norgaard. "That's called dynamic connectivity, and that's what we're hoping to research next."

The research team includes Robyn Miller, assistant professor of Computer Science, Mukesh Dhamala associate professor of Physics and Astronomy, as well as collaborators at Pennsylvania State University and Harvard Medical School.

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The Structural and Functional Neuroanatomy of Post-Stroke Depression and Executive Dysfunction: A Review of Neuroimaging Findings and Implications for Treatment

I can explain post stroke depression in two words. NO PROTOCOLS! If you had rehab protocols survivors wouldn't have time to be depressed, they would be counting reps and exercising all day long to get to recovery. Are you that fucking clueless that you are ignoring Occam's razor? And you came up with NO protocols for executive dysfunction. Useless.

The Structural and Functional Neuroanatomy of Post-Stroke Depression and Executive Dysfunction: A Review of Neuroimaging Findings and Implications for Treatment

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Abhishek Jaywant, PhD, Larissa DelPonte, BA, Dora Kanellopoulos, PhD, ...

First Published October 19, 2020 Review Article Find in PubMed 

https://doi.org/10.1177/0891988720968270

Article information

Abstract

Post-stroke depression and executive dysfunction co-occur and are highly debilitating. Few treatments alleviate both depression and executive dysfunction after stroke. Understanding the brain network changes underlying post-stroke depression with executive dysfunction can inform the development of targeted and efficacious treatment. In this review, we synthesize neuroimaging findings in post-stroke depression and post-stroke executive dysfunction and highlight the network commonalities that may underlie this comorbidity. Structural and functional alterations in the cognitive control network, salience network, and default mode network are associated with depression and executive dysfunction after stroke. Specifically, post-stroke depression and executive dysfunction are both linked to changes in intrinsic functional connectivity within resting state networks, functional over-connectivity between the default mode and salience/cognitive control networks, and reduced cross-hemispheric frontoparietal functional connectivity. Cognitive training and noninvasive brain stimulation targeted at these brain network abnormalities and specific clinical phenotypes may help advance treatment for post-stroke depression with executive dysfunction.

Keywords cerebrovascular disease, neuroimaging, magnetic resonance imaging, cognitive control, default mode network

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Motor dexterity and strength depend upon integrity of the attention-control system

So fucking what? What is your solution, don't just be a lazy asshole and describe a problem, come up with a solution.

Motor dexterity and strength depend upon integrity of the attention-control system

 Authors

1. Paul Rinne^a,¹,
2. Mursyida Hassan^a,^b,¹,
3. Cristina Fernandes^a,
4. Erika Han^a,
5. Emma Hennessy^a,
6. Adam Waldman^a,
7. Pankaj Sharma^c,
8. David Soto^d,^e,
9. Robert Leech^a,
10. Paresh A. Malhotra^a, and
11. Paul Bentley^a,²

1. ^aDivision of Brain Sciences, Charing Cross Hospital Campus, Imperial College London, London, W6 8RF, United Kingdom;
2. ^bSpeech Science Program, School of Rehabilitation Sciences, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, 50300 Kuala Lumpur, Malaysia;
3. ^cSchool of Biological Sciences, Royal Holloway University of London, Egham, Surrey, TW20 0EX, United Kingdom;
4. ^dBasque Center on Cognition, Brain and Language, 20009 Donostia, Spain;
5. ^eIkerbasque, Basque Foundation for Science, 48011 Bilbao, Spain

1. Edited by Peter L. Strick, University of Pittsburgh, Pittsburgh, PA, and approved November 15, 2017 (received for review September 7, 2017)

Significance

Simple voluntary movements (e.g., reaching or gripping) deteriorate with distraction, suggesting that the attention-control system—which suppresses distraction—influences motor control. Here, we tested the causal dependency of simple movements on attention control, and its neuroanatomical basis, in healthy elderly and patients with focal brain lesions. Not only did we find that attention control correlates with motor performance, correcting for lesion size, fatigue, etc., but we found a revealing pattern of dissociations: Severe motor impairment could occur with normal attention control whereas impaired attention control never occurred with disproportionately milder motor impairment—suggesting that attention control is required for normal motor performance. One implication is that a component of stroke paralysis arises from poor attentional control, which could itself be a therapeutic target.

 

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Abstract

Attention control (or executive control) is a higher cognitive function involved in response selection and inhibition, through close interactions with the motor system. Here, we tested whether influences of attention control are also seen on lower level motor functions of dexterity and strength—by examining relationships between attention control and motor performance in healthy-aged and hemiparetic-stroke subjects (n = 93 and 167, respectively). Subjects undertook simple-tracking, precision-hold, and maximum force-generation tasks, with each hand. Performance across all tasks correlated strongly with attention control (measured as distractor resistance), independently of factors such as baseline performance, hand use, lesion size, mood, fatigue, or whether distraction was tested during motor or nonmotor cognitive tasks. Critically, asymmetric dissociations occurred in all tasks, in that severe motor impairment coexisted with normal (or impaired) attention control whereas normal motor performance was never associated with impaired attention control (below a task-dependent threshold). This implies that dexterity and force generation require intact attention control. Subsequently, we examined how motor and attention-control performance mapped to lesion location and cerebral functional connectivity. One component of motor performance (common to both arms), as well as attention control, correlated with the anatomical and functional integrity of a cingulo-opercular “salience” network. Independently of this, motor performance difference between arms correlated negatively with the integrity of the primary sensorimotor network and corticospinal tract. These results suggest that the salience network, and its attention-control function, are necessary for virtually all volitional motor acts while its damage contributes significantly to the cardinal motor deficits of stroke.

• motor
• attention
• cognitive control
• stroke
• fMRI

Stroke is one of the commonest causes of adult disability, resulting in impairments of both physical (e.g., hemiparesis) and cognitive (e.g., aphasia and neglect) function (1). These two broad types of impairment are commonly regarded as having distinct neuroanatomical bases, entailing different therapeutic strategies, whereas, in fact, physical and cognitive functions may share mechanisms, and their measures interdepend. A well-known example of this is motor neglect (2), in which unilateral motor dysfunction arises from a lateralized attentional bias, rather than because of primary motor, or corticospinal tract, disruption. However, focal brain lesions also impair nonspatial forms of attention, such as alertness (1), that are associated with motor function (3, 4) although the nature of this relationship is unclear.

Associations could occur because lesions tend to overlap anatomically adjacent, yet functionally independent, motor and attention pathways (5) or because of general illness effects on mood or fatigue. Alternatively, motor disability or fatigue demands extra attentional resources, which may secondarily impair performance on tests of attention (6, 7). In the current study, we sought to distinguish these possibilities from the third reason for an association: That nonspatial attentional deficits are a cause of motor impairment.

The type of attention focused on here is attention control (also termed “executive control” or “cognitive control”), which refers to the ability to maintain performance as challenges increase, be they competitive choices or distraction (8, 9). It is an everyday observation that distraction worsens motor performance (e.g., on strength (10) or tracking (11) tasks), indicating that the motor system competes for finite attentional resources. Increasing evidence suggests that a distinct control system manages such resource allocation and is recruited during motor acts, even in the absence of experimental challenges, because purposeful movements entail inhibition of irrelevant or competing motor plans (12, 13), distractor suppression (14), rule following (15), error monitoring, and correction (16). In keeping with this, functional–anatomical associations have been found between basic motor functions (e.g., strength and dexterity) and cerebral regions involved in attention control, particularly cingulate, inferior frontal, and temporoparietal cortices (17, 18), that become more apparent with aging or brain injury (19⇓⇓–22). Such findings extend studies showing that higher motor functions (e.g., drawing, speech, object use, and walking) commonly engage executive systems (23⇓⇓–26). However, while imaging studies suggest anatomical overlap of motor with attention-control functions, they have not to date shown whether attention control is a requisite for basic motor functions—as is the objective here.

Given evidence for motor and attention-control interactions, and noting that stroke-induced impairments in these two functions are associated behaviorally (3, 4), and anatomically (5), we hypothesized that one component of stroke hemiparesis arises from damage to a domain-general, attention-control system, thereby implying that normal motor performance requires intact attention control. To test this, we observed the pattern of dissociations between motor and attention-control performance in a large cohort of hemiparetic stroke patients that, by random distribution, should include lesions with variable differential overlap of motor versus attention-control systems. We reasoned that, if attention control is necessary for motor function, then attention-control impairments would always be associated with motor deficits that are proportionate or worse (i.e., we would not find dissociations where severe attentional impairment coexists with relatively mild motor impairment). Conversely, if poor motor performance increases distractibility (6, 7), then severe motor impairment would always be associated with impaired attention control (i.e., we would not find dissociations of severe motor impairment and preserved attention control). A third possibility—that associations occur because of anatomical proximity, but not functional interaction, between attention-control and motor systems (5)—allows for both types of dissociation because, by chance, some lesions are likely to target either system solely or preferentially. To increase the likelihood of discovering such dissociations, we focused on subjects with mild-moderate deficits who had small lesions that are likely to result in variable relative overlap of two adjacent networks and without confounding cognitive deficits: e.g., gross executive impairments, neglect, or apraxia.

In the following experiments we (i) characterize motor performance in healthy subjects and hemiparetic stroke patients in terms of separable bilateral and unilateral components; (ii) show how these motor components relate to distractibility during motor and nonmotor cognitive tasks, correcting for lesion size and other potential confounds; (iii) characterize the profile of motor/attention-control dissociations; and (iv) ascertain how the two motor components and attention control relate to lesion overlap and functional connectivity, of a putative attention-control (“salience”) network (9), as opposed to other cognitive or motor networks.

Computer-Based Cognitive Training for Executive Functions after Stroke: A Systematic Review

Maybe your doctor can reuse this and create a stroke protocol out of this for your cognitive training. Not to be done on your own, that would be dangerous for your doctor when you realize the incompetency of the stroke world out there.

Computer-Based Cognitive Training for Executive Functions after Stroke: A Systematic Review

Renate M. van de Ven^1*, Jaap M. J. Murre¹, Dick J. Veltman² and Ben A. Schmand^1,3

• ¹Department of Psychology, Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
• ²Department of Psychiatry, VU University Medical Center, Amsterdam, Netherlands
• ³Department of Medical Psychology, Academic Medical Centre, University of Amsterdam, Netherlands

Background: Stroke commonly results in cognitive impairments in working memory, attention, and executive function, which may be restored with appropriate training programs. Our aim was to systematically review the evidence for computer-based cognitive training of executive dysfunctions.

Methods: Studies were included if they concerned adults who had suffered stroke or other types of acquired brain injury, if the intervention was computer training of executive functions, and if the outcome was related to executive functioning. We searched in MEDLINE, PsycINFO, Web of Science, and The Cochrane Library. Study quality was evaluated based on the CONSORT Statement. Treatment effect was evaluated based on differences compared to pre-treatment and/or to a control group.

Results: Twenty studies were included. Two were randomized controlled trials that used an active control group. The other studies included multiple baselines, a passive control group, or were uncontrolled. Improvements were observed in tasks similar to the training (near transfer) and in tasks dissimilar to the training (far transfer). However, these effects were not larger in trained than in active control groups. Two studies evaluated neural effects and found changes in both functional and structural connectivity. Most studies suffered from methodological limitations (e.g., lack of an active control group and no adjustment for multiple testing) hampering differentiation of training effects from spontaneous recovery, retest effects, and placebo effects.

Conclusions: The positive findings of most studies, including neural changes, warrant continuation of research in this field, but only if its methodological limitations are addressed.

Introduction

Stroke, resulting from brain hemorrhage or infarction, commonly results in cognitive impairments such as aphasia, neglect, reduced processing speed, impaired attention, and executive dysfunction (e.g., Cumming et al., 2013). Even though cognition can improve during the first year after stroke (Desmond et al., 1996; Tham et al., 2002; del Ser et al., 2005), cognitive impairment frequently persists long after. More than 60% of stroke survivors still reported mild to severe cognitive impairment up to 10 years after stroke (Maaijwee et al., 2014; Middleton et al., 2014). Furthermore, cognitive impairments continue to deteriorate in 11% of stroke survivors during the first year after stroke (Tham et al., 2002). Therefore, rehabilitation efforts to ameliorate these cognitive impairments are essential.

Guidelines for neurorehabilitation are mainly focused on compensational strategy training (Cicerone et al., 2011). These strategies do not aim to restore brain functions (i.e., restitution), but aim to compensate for the lost function by using remaining intact functions. In this approach, residual plasticity of the brain throughout adulthood, which may enable restitution of the impaired function, is ignored (e.g., Kelly et al., 2006; Takeuchi and Izumi, 2015).

Robertson and Murre (1999) postulated that depending on the amount of remaining connectivity, different types of intervention are needed, notably restitution or compensation. Mildly damaged brain networks might reconnect by everyday life activities, and no special intervention is necessary. Severely affected brain networks may not be able to reconnect at all. Therefore, in severe cases compensational interventions are required that make use of preserved networks. For moderately affected networks, restitution-based interventions may be needed to stimulate the relevant parts of the impaired network.

Restitution focused treatments commonly consist of massed frequent repetition or stimulation of the affected function (Hamzei et al., 2006). They have proven to be effective in the domains of language, motor function, and vision (e.g., Kurland et al., 2010; Thrane et al., 2014). For other cognitive domains, such as attention and executive function, restitution training may consist of, for example, training reaction speed. Conversely, compensation interventions may consist of, for example, time management training to teach the patient to take more time for task execution. One type of restitution-based interventions use computer tasks aimed at training of damaged networks.

To date it is not yet clear whether restitution-based computer training can improve attention, working memory, and executive functions. In healthy adults, training effects have been contradictory (e.g., Owen et al., 2010; Anguera et al., 2013; Corbett et al., 2015), but a recent meta-analysis concluded that cognition can be improved (Toril et al., 2014). A systematic review of 10 studies in stroke patients concluded that restitution- and compensation-based interventions improved executive functions (Poulin et al., 2012). Even though the review by Poulin et al. did not only focus on restitution-based computerized training programs, their review does provide ground to further evaluate these restitution-based training programs.

This systematic review provides an overview of the evidence concerning the effects of computer-based restitution rehabilitation after stroke and other acquired brain damage to restore executive functioning. The term executive function includes a spectrum of cognitive functions, all revolving around control of one's behavior. This includes mental set shifting (i.e., changing from one set of task rules to another), information updating, and inhibition of prepotent but inappropriate responses (Miyake et al., 2000). For this review we considered working memory and divided (or selective) attention as part of the executive domain. Training programs that only focused on vigilance, tonic alertness, and sustained attention without any divided or selective attention tasks were not included.

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Functional brain network modularity predicts response to cognitive training after brain injury

No clue what this means, so ask your doctor to decipher it and apply to your stroke protocols.

Functional brain network modularity predicts response to cognitive training after brain injury

1. Katelyn L. Arnemann, BA,
2. Anthony J.-W. Chen, MD,
3. Tatjana Novakovic-Agopian, PhD,
4. Caterina Gratton, PhD,
5. Emi M. Nomura, PhD and
6. Mark D'Esposito, MD

+Show Affiliations

| + Show Full Disclosures

1. Correspondence to Katelyn L. Arnemann: klarnemann@berkeley.edu

1. Published online before print March 18, 2015, doi: 10.1212/WNL.0000000000001476 Neurology 10.1212/WNL.0000000000001476

• Abstract
• Full Text (PDF)

Abstract

Objective: We tested the value of measuring modularity, a graph theory metric indexing the relative extent of integration and segregation of distributed functional brain networks, for predicting individual differences in response to cognitive training in patients with brain injury.

Methods: Patients with acquired brain injury (n = 11) participated in 5 weeks of cognitive training and a comparison condition (brief education) in a crossover intervention study design. We quantified the measure of functional brain network organization, modularity, from functional connectivity networks during a state of tonic attention regulation measured during fMRI scanning before the intervention conditions. We examined the relationship of baseline modularity with pre- to posttraining changes in neuropsychological measures of attention and executive control.

Results: The modularity of brain network organization at baseline predicted improvement in attention and executive function after cognitive training, but not after the comparison intervention. Individuals with higher baseline modularity exhibited greater improvements with cognitive training, suggesting that a more modular baseline network state may contribute to greater adaptation in response to cognitive training.

Conclusions: Brain network properties such as modularity provide valuable information for understanding mechanisms that influence rehabilitation of cognitive function after brain injury, and may contribute to the discovery of clinically relevant biomarkers that could guide rehabilitation efforts.

Cognitive control in the self-regulation of physical activity and sedentary behavior

Your doctor should be an expert at motivating you to get off your butt and exercise. Because unless YOU do the work you won't recover very well.
This might help your doctor create a stroke protocol on motivation. You can always hope your doctor is trainable.

Cognitive control in the self-regulation of physical activity and sedentary behavior

Jude Buckley¹, Jason D. Cohen², Arthur F. Kramer^2,3, Edward McAuley^2,3 and Sean P. Mullen^2,3*

• ¹School of Psychology, University of Auckland, Auckland, New Zealand
• ²Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, USA
• ³Beckman Institute for Advanced Science and Technology, Urbana, IL, USA

Cognitive control of physical activity and sedentary behavior is receiving increased attention in the neuroscientific and behavioral medicine literature as a means of better understanding and improving the self-regulation of physical activity. Enhancing individuals’ cognitive control capacities may provide a means to increase physical activity and reduce sedentary behavior. First, this paper reviews emerging evidence of the antecedence of cognitive control abilities in successful self-regulation of physical activity, and in precipitating self-regulation failure that predisposes to sedentary behavior. We then highlight the brain networks that may underpin the cognitive control and self-regulation of physical activity, including the default mode network, prefrontal cortical networks and brain regions and pathways associated with reward. We then discuss research on cognitive training interventions that document improved cognitive control and that suggest promise of influencing physical activity regulation. Key cognitive training components likely to be the most effective at improving self-regulation are also highlighted. The review concludes with suggestions for future research.

For nearly half of a century, researchers have been trying to uncover how to motivate people to become more physically active (Trost et al., 2002; Schutzer and Graves, 2004; Buckworth et al., 2013) and, recently, more effort has been made to understand how to motivate people to be less sedentary (Hamilton et al., 2008). Despite resources devoted to these efforts, more than 30% of the world’s population remains physically inactive (Hallal et al., 2012) and, on average, people are sitting for more than 300 min/day (Bauman et al., 2011). Our understanding of the regulation of these behaviors has advanced, but these prevalence rates suggest that our knowledge of physical activity and sedentary behavior remains incomplete. Research supports theoretical proposals that health behavior is dependent, in part, on self-regulation capacities (Bandura, 1986; De Ridder and de Wit, 2006), but only recently has research attention been directed toward the preceding factors of self-regulation that influence physical activity and sedentary behavior.

Recent theory (e.g., Temporal Self-Regulation Theory; Hall and Fong, 2007, 2010, 2013) and evidence suggest that the relation between physical activity and cognitive control is reciprocal (Daly et al., 2013). Most research has focused on the beneficial effects of regular physical activity on executive functions-the set of neural processes that define cognitive control. Considerable evidence shows that regular physical activity is associated with enhanced cognitive functions, including attention, processing speed, task switching, inhibition of prepotent responses and declarative memory (for reviews see Colcombe and Kramer, 2003; Smith et al., 2010; Guiney and Machado, 2013; McAuley et al., 2013). Recent research demonstrates a dose-response relationship between fitness and spatial memory (Erickson et al., 2011), however the long-term effects of physical activity on working memory have been less consistent (Smith et al., 2010).

Positive physical activity effects on executive function have been found in children for both acute and regular activity (Chang et al., 2012; Hillman et al., in press). For example, findings from a 9-month randomized controlled trial in 221 prepubertal children attending an afterschool physical activity program (vs. a wait-list control group), showed improvements in fitness (VO_2peak), cognitive control, and neuroelectrical activity (P3-ERP) during tasks that required significantly more cognitive control (Hillman et al., in press). In addition, a modest dose-response effect of program attendance on cognitive control measures was also found. Improvements in cognitive function are not always observed in older adults (Angevaren et al., 2008) or in children (Janssen et al., 2014) involved in physical activity programs. These findings suggest that the effects of physical activity on cognitive function may depend on the particular cognitive function being assessed. Taken together, this research suggests that physical activity training can enhance cognitive control abilities. The effects of physical activity on cognitive control appear to be underpinned by a variety of brain processes including: increased hippocampal volume, increased gray matter density in the prefrontal cortex (PFC), upregulation of neurotrophins and greater microvascular density (for a review see Voss et al., 2013). Much less is understood about the influence of cognitive control on physical activity but emerging evidence suggests that executive functions play an antecedent role in effective self-regulation of physical activity (Hall et al., 2008; Riggs et al., 2010; McAuley et al., 2011; Daly et al., 2013; Pentz and Riggs, 2013; Best et al., 2014).

The goals of this paper are (1) to review emerging evidence of the antecedence of cognitive control abilities in enabling successful self-regulation for physical activity, and in precipitating self-regulation failures that predispose individuals to remain sedentary; (2) to highlight neural networks that may underlie the cognitive control of physical activity and sedentary behavior; and (3) to review emerging research on training effects on cognitive and physical functioning and summarize components of training that may produce positive cognitive outcomes associated with increased physical activity engagement.

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