Timing Training in Female Soccer Players: Effects on Skilled Movement Performance and Brain Responses

Timing Training in Female Soccer Players: Effects on Skilled Movement Performance and Brain Responses. Frontiers in Human Neuroscience. Article link.

Marius Sommer, Charlotte K. Häger, Carl Johan Boraxbekk and Louise Rönnqvist

Abstract

Although trainers and athletes consider “good timing skills” critical for optimal sport
performance, little is known in regard to how sport-specific skills may benefit from timing training. Accordingly, this study investigated the effects of timing training on soccer skill performance and the associated changes in functional brain response in elite- and sub-elite female soccer players. Twenty-five players (mean age 19.5 years; active in the highest or second highest divisions in Sweden), were randomly assigned to either an experimental- or a control group. The experimental group (n = 12) was subjected to a 4-week program (12 sessions) of synchronized metronome training (SMT). We evaluated effects on accuracy and variability in a soccer cross-pass task. The associated brain response was captured by functional magnetic resonance imaging (fMRI) while watching videos with soccer-specific actions. SMT improved soccer cross-pass performance, with a significant increase in outcome accuracy, combined with a decrease in outcome variability. SMT further induced changes in the underlying brain response associated with observing a highly familiar soccer-specific action, denoted as decreased activation in the cerebellum post SMT. Finally, decreased cerebellar activation was associated with improved cross-pass performance and sensorimotor synchronization. These findings suggest a more efficient neural recruitment during action observation after SMT. To our knowledge, this is the first controlled study providing behavioral and neurophysiological evidence that timing training may positively influence soccer-skill, while strengthening the action-perception coupling via enhanced sensorimotor synchronization abilities, and thus influencing the underlying brain responses.

Conclusion

In summary, this is the first controlled study demonstrating that improved motor timing and multisensory integration, as an effect of SMT, also is associated with changes in functional brain response. The present study provides both behavioral and neurophysiological evidence that timing training positively influences soccer-skill, strengthens the action-perception coupling by means of enhanced sensorimotor synchronization abilities, and affect underlying brain responses. These findings are in accordance with the idea that SMT may result in increased brain communication efficiency and synchrony between brain regions (McGrew, 2013), which in the present study was evident by reduced activation within brain areas important for temporal planning, movement coordination and action recognition and understanding (cerebellum). Also, our results complement findings indicating that the cerebellum plays an important role in the action-perception coupling (Christensenetal.,2014),and confirm recent theories supporting a cognitive-perceptual role of the cerebellum (e.g., Roth et al., 2013).Probing the influence of timing training on the underlying brain activation during soccer specific action observation is an important approach as it provides a window into the brain plasticity associated with non-task specific (timing) training, and to the underlying brain activation of skilled performance. The present study suggests that the underlying brain activation during action observation, which is claimed to be important for action recognition and understanding (e.g., Rizzolatti and Craighero, 2004), may be influenced in other ways than through task-specific training (e.g., Calvo-Merino et al., 2005) or observational learning (e.g., Cross et al., 2013). Such knowledge of how SMT may alter brain activity within regions facilitating the action perception coupling is likely important for enhancing training techniques within sports, as well as for developing new rehabilitative techniques for many clinical populations.



- Posted using BlogPress from my iPad

White matter matters: Changes in white matter tracts due to reading intervention

More research supporting “white matter matters”.




Rapid and widespread white matter plasticity during an intensive reading intervention

Nature Communications

Elizabeth Huber, Patrick M. Donnelly, Ariel Rokem & Jason D. Yeatman

ABSTRACT

White matter tissue properties are known to correlate with performance across domains ranging from reading to math, to executive function. Here, we use a longitudinal intervention design to examine experience-dependent growth in reading skills and white matter in grade school-aged, struggling readers. Diffusion MRI data were collected at regular intervals during an 8-week, intensive reading intervention. These measurements reveal large-scale changes throughout a collection of white matter tracts, in concert with growth in reading skill. Additionally, we identify tracts whose properties predict reading skill but remain fixed throughout the intervention, suggesting that some anatomical properties stably predict the ease with which a child learns to read, while others dynamically reflect the effects of experience. These results underscore the importance of considering recent experience when interpreting cross-sectional anatomy–behavior correlations. Widespread changes throughout the white matter may be a hallmark of rapid plasticity associated with an intensive learning experience.

Very interesting. The arcuate fasciculus tracts have also been implicated in higher order thinking (Gf) such as in the P-FIT model of intelligence. Also see white paper that implicates the AF in temporal processing “brain clock” timing interventions




- Posted using BlogPress from my iPad

Higher intelligence related to more efficiently organized brains-bigger/larger not always better

Click on image to enlarge

Diffusion markers of dendritic density and arborization in gray matter predict differences in intelligence. Article link.

Erhan Genç, Christoph Fraenz, Caroline Schlüter, Patrick Friedrich, Rüdiger Hossiep, Manuel C. Voelkle, Josef M. Ling, Onur Güntürkün, & Rex E. Jung

Abstract

Previous research has demonstrated that individuals with higher intelligence are more likely to have larger gray matter volume in brain areas predominantly located in parieto-frontal regions. These findings were usually interpreted to mean that individuals with more cortical brain volume possess more neurons and thus exhibit more computational capacity during reasoning. In addition, neuroimaging studies have shown that intelligent individuals, despite their larger brains, tend to exhibit lower rates of brain activity during reasoning. However, the microstructural architecture underlying both observations remains unclear. By combining advanced multi-shell diffusion tensor imaging with a culture-fair matrix-reasoning test, we found that higher intelligence in healthy individuals is related to lower values of dendritic density and arborization. These results suggest that the neuronal circuitry associated with higher intelligence is organized in a sparse and efficient manner, fostering more directed information processing and less cortical activity during reasoning.

From discussion

Taken together, the results of the present study contribute to our understanding of human intelligence differences in two ways. First, our findings confirm an important observation from previous research, namely, that bigger brains with a higher number of neurons are associated with higher intelligence. Second, we demonstrate that higher intelligence is associated with cortical mantles with sparsely and well-organized dendritic arbor, thereby increasing processing speed and network efficiency. Importantly, the findings obtained from our experimental sample were confirmed by the analysis of an independent validation sample from the Human Connectome Project25



- Posted using BlogPress from my iPad

The salience brain network and personality (self-directedness; cognitive control)

Abstract:

A prevailing topic in personality neuroscience is the question how personality traits are
reflected in the brain. Functional and structural networks have been examined by functional and structural magnetic resonance imaging, however, the structural correlates of functionally defined networks have not been investigated in a personality context. By using the Temperament and Character Inventory (TCI) and Diffusion Tensor Imaging (DTI), the present study assesses in a sample of 116 healthy participants how personality traits proposed in the framework of the biopsychosocial theory on personality relate to white matter pathways delineated by functional network imaging. We show that the character trait self-directedness relates to the overall microstructural integrity of white matter tracts constituting the salience network as indicated by DTI-derived measures. Self-directedness has been proposed as the executive control component of personality and describes the tendency to stay focused on the attainment of long-term goals. The present finding corroborates the view of the salience network as an executive control network that serves maintenance of rules and task-sets to guide ongoing behavior.

Click here for info regarding one of the better brain network overview articles by Bressler and Menon.


Click on image to enlarge



- Posted using BlogPress from my iPad

The importance of differential psychology for school learning: 90% of school achievement variance is due to student characteristics

This is why the study of individual differences/differential psychology is so important. If you don’t want to read the article you can watch a video of Dr. Detterman where he summarizes his thinking and this paper.

Education and Intelligence: Pity the Poor Teacher because Student Characteristics are more Significant than Teachers or Schools. Article link.

Douglas K. Detterman

Case Western Reserve University (USA)

Abstract

Education has not changed from the beginning of recorded history. The problem is that focus has been on schools and teachers and not students. Here is a simple thought experiment with two conditions: 1) 50 teachers are assigned by their teaching quality to randomly composed classes of 20 students, 2) 50 classes of 20 each are composed by selecting the most able students to fill each class in order and teachers are assigned randomly to classes. In condition 1, teaching ability of each teacher and in condition 2, mean ability level of students in each class is correlated with average gain over the course of instruction. Educational gain will be best predicted by student abilities (up to r = 0.95) and much less by teachers' skill (up to r = 0.32). I argue that seemingly immutable education will not change until we fully understand students and particularly human intelligence. Over the last 50 years in developed countries, evidence has accumulated that only about 10% of school achievement can be attributed to schools and teachers while the remaining 90% is due to characteristics associated with students. Teachers account for from 1% to 7% of total variance at every level of education. For students, intelligence accounts for much of the 90% of variance associated with learning gains. This evidence is reviewed


- Posted using BlogPress from my iPad

Wig (2017, in press)-Segregated Systems of Human Brain Networks

Click on images to enlarge.

Article link.

This is an excellent and thought provoking brain network review that addresses the push-pull between optimal (and necessary) brain network segregation and more transient and fluid integration “on demand” to meet new task demands. Excellent summary.








ABSTRACT

The organization of the brain network enables its function. Evaluation of this organization has revealed that large-scale brain networks consist of multiple segregated subnetworks of interacting brain areas. Descriptions of resting-state network architecture have provided clues for understanding the functional significance of these segregated subnetworks, many of which correspond to distinct brain systems. The present report synthesizes accumulating evidence to reveal how maintaining segregated brain systems renders the human brain network functionally specialized, adaptable to task demands, and largely resilient following focal brain damage. The organizational properties
that support system segregation are harmonious with the properties that promote integration across the network, but confer unique and important features to the brain network that are central to its function and behavior.

- Posted using BlogPress from my iPad

More support for P-FIT model of intelligence

Abstract

The authors describe the brain regions involved in the process of intelligence using as a basis, the models of the theory of frontoparietal integration (P-FIT Model). They also correlate the model described with functional areas of Brodmann, integrating them into the tertiary brain areas and address the subcortical structures involved in cognitive processes, including the memory. The studies performed by functional magnetic resonance, also unmask various regions related with intelligence, neither previously described by Brodmann nor even in conventional models of learning. The anterior insular cortex presents itself as the most recent tertiary area to be considered. Subcortical structures, when injured, mimick injuries to the cerebral cortex, demonstrating their great participation in cognition. The topographies of aphasia and the functioning mechanisms of the bearers of learning disorders, including dyslexic, dysgraphia and dyscalculic should be reconsidered. A better understanding of this topographic anatomy may clarify the mechanisms used in those individuals with cerebral lesions.

Click on images to enlarge







- Posted using BlogPress from my iPad

Research Byte: Multivariate Associations of Fluid Intelligence (Gf) and NAA - Is the P-FIT it?

When it rains--it pours.  Second posting today of research study reinforcing the importance of the P-FIT neuro-model of intelligence.

In a prior Interactive Metronome-Home blog post I provide an overview description of the P-FIT model.

 

Multivariate Associations of Fluid Intelligence and NAA

1. Aki Nikolaidis1,2,
2. Pauline L. Baniqued1,3,4,
3. Michael B. Kranz1,3,
4. Claire J. Scavuzzo2,5,
5. Aron K. Barbey1,
6. Arthur F. Kramer1,2,3 and
7. Ryan J. Larsen1

+ Author Affiliations

1. ¹Beckman Institute for Advanced Science and Technology
2. ²Neuroscience Program and
3. ³Psychology Department, University of Illinois at Urbana-Champaign, Urbana, IL, USA
4. ⁴Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
5. ⁵Psychology Department, University of Alberta, Edmonton, Alberta, Canada

1. Address correspondence to Aki Nikolaidis. Email: g.aki.nikolaidis@gmail.com

Abstract

Understanding the neural and metabolic correlates of fluid intelligence not only aids scientists in characterizing cognitive processes involved in intelligence, but it also offers insight into intervention methods to improve fluid intelligence. Here we use magnetic resonance spectroscopic imaging (MRSI) to measure N-acetyl aspartate (NAA), a biochemical marker of neural energy production and efficiency. We use principal components analysis (PCA) to examine how the distribution of NAA in the frontal and parietal lobes relates to fluid intelligence. We find that a left lateralized frontal-parietal component predicts fluid intelligence, and it does so independently of brain size, another significant predictor of fluid intelligence. These results suggest that the left motor regions play a key role in the visualization and planning necessary for spatial cognition and reasoning, and we discuss these findings in the context of the Parieto-Frontal Integration Theory of intelligence.

White matter matters! Brain network communication and synchronization - An oldie-but-goodie (OBG) post

White matter, in contrast to the grey squiggly mass (the cerebrum) that most people associate with the human brain, was for many years the research step-child to the cerebrum. That is no more. White matter, which has been called the brain's subway, super information system, or interstate highway communication system, now has a glass slipper. Research during the past decade has implicated white matter as performing the critical task of connecting and synchronizing different brain regions or networks so they can perform a wide variety of complex human cognitive or motor behaviors. The white matter system is considered the communication backbone system for the flow of information in the brain. Of particular interest (to me) is the parietal-frontal network, which is implicated as central to abstract human intelligence, fluid intelligence (Gf), working memory and attentional control (see prior posts re: the P-FIT model).

In a MindHub white paper I hypothesized that increasing white matter tract integrity may be a key mechanism behind the efficacy of the Interactive Metronome neuro-timing intervention (see figure below). I have gone as far as suggesting that the efficacy of many brain training/fitness programs may stem from a common domain-general effect--improving communication between and within various brain network(s) via more efficient white matter tract speed and communication. [Click on image to enlarge]

White matter integrity or dysfunction as been implicated in a wide variety of cognitive disorders or abilities, including cognitive control, math and intellectual giftedness, fluid intelligence or reasoning, processing speed, reading, decrease in cognitive functioning, meditation, working memory, vascular cognitive impairment, ADHD, autism, and cognitve and language maturation in infants. A sampling of recent white matter research article abstracts I have accumulated can be found by clicking here.
White matter matters!

Posted with Blogsy

Your brain is a time machine: An oldie-but-goodie (OBG) post

This is an OBG (oldie-but-goodie) post I originally made on the IM-HOME blog

Time and space are the two fundamental dimensions of our lives. All forms of human behavior require us to process and understand information we receive from our environment in either spatial or temporal patterns. Even though mental timing (temporal processing) research is in a stage of infancy (when compared to spatial processing) important insights regarding the human brain clock have emerged.

Below is a list (albeit incomplete) of some of the major conclusions regarding the human brain clock. The sources for these statements come from my review of the temporal processing and brain clock literature during the past five years. Most of this information has been disseminated at the Brain Clock blog or the Brain Clock Evolving Web of Knowledge (EWOK). The goal of this post is to provide a Readers Digest summary of the major conclusions. This material can serve as a set of "talking points" at your next social event where you can impress your friends and family as you explain why you use the high-tech IM "clapper" (with a cowbell tone no less) either as a provider or as client.

Our brains measure time constantly. It's hard to find any complex human behavior where mental timing is not involved. Timing is required to walk, talk, perform complex movements and coordinate information flow across the brain for complex human thought. Think about moving your arm and hand to grasp a coffee cup. The messages to perform this task originate in your brain, which is not directly connected to your arm, hands and fingers. The ability to perform the necessary motor movements is possible only because the mind and extremities are connected via timing. Precisely timed neural messages connect your brain and extremities. You are a time machine.

Humans are remarkably proficient at internally perceiving and monitoring time to produce precisely timed behaviors and thinking. “We are aware of how long we have been doing a particular thing, how long it has been since we last slept, and how long it will be until lunch or dinner. We are ready, at any moment, to make complex movements requiring muscle coordination with microsecond accuracy, or to decode temporally complex auditory signals in the form of speech or music. Our timing abilities are impressive…” (Lewis & Walsh, 2005, p. 389).

To deal with time, humans have developed multiple timing systems that are active over more than 10 orders of magnitude with various degrees of precision (see figure below from Buhusi & Meck, 2005). These different timing systems can be classified into three general classes (viz., circadian, interval, and millisecond timing), each associated with different behaviors and brain structures and mechanisms. The fastest timing system (millisecond or interval timing) is involved in a numerous human behaviors such as speech and language, music perception and production, coordinated motor behaviors, attention, and thinking. This fast interval timing system is the most important timing system for understanding and diagnosing clinical disorders and for developing and evaluating effective treatment interventions for educational and rehabilitation settings. It is this timing system, and the relevant research, that is relevant to understanding Interactive Metronome. (Note.  See my conflict of interest statement at this blog.  I have an ongoing consulting relationship with IM).

Although there is consensus that the human brain contains some kind of clock, the jury is still out on the exact brain mechanisms and locations. It is also not clear whether there is one functional master clock or a series of clocks deployed in different brain areas. The areas of the brain most consistently associated with milli-second interval mental timing are the cerebellum, anterior cingulate, basal ganglia, the dorsolateral prefrontal cortex, right parietal cortex, motor cortex, and the frontal-striatal loop. That is a mouthful of technical brain terms. But, if you can memorize them and have them roll of your tongue with ease you will “shock and awe” your family and friends. Most of these areas of the brain are illustrated below. Now, if you really want to demonstrate your expertise, get your own illustrated “brain-in-a-pocket”. These images were generated by the free 3D Brain app available for your iPhone or iPad. Even cooler is the fact that you can rotate the images with your finger! You can give neuroanatomy lessons anytime…anywhere!

Research suggests that mental interval timing is controlled by two sub-systems. The automatic timing system processes discrete-event (discontinuous) timing in milliseconds. The cognitively-controlled timing system deals with continuous-event timing (in seconds) that requires controlled attention and working memory. Both systems are likely involved in IM. For example, the synchronized clapping requires motor planning and execution, functions most associated with the automatic timing system. However, the cognitive aspects of IM (focus, controlled attention, executive functions) invoke the cognitively controlled timing system. Aren’t these brain images awesome?

The dominant model in the brain clock research literature is that of a centralized internal clock that functions as per the pacemaker–accumulator model. Briefly, this is a model where an oscillator beating at a fixed frequency generates tics that are detected by a counter. For now I am just going to tease you with an image of this model. You can read more about this model at the Brain Clock blog.

Research suggests that the brain mechanisms underlying mental timing can be fine-tuned (modified) via experience and environmental manipulation. Modifiability of mental interval timing and subsequent transfer suggest a domain-general timing mechanism that, if harnessed via appropriately designed timing-based interventions, may improve human performance in a number of important cognitive and motor domains.

Mind wandering, the default network and controlled attention: An OBG video post

(This is an oldie-but-goodie blog post - OBG)

A few interesting video gems for your viewing.

First, forget multitasking and try mono-tasking.  Focus on just one thing...it may be beneficial.

Next, I have frequently blogged about the default mode or default brain network (Brain Clock posts; IM-HOME post).  The default mode (which is estimated to be active approximately 40% of our waking day) has been implicated in how our mind, when idling or resting, is very active--it does not rest while resting.  Difficulty quieting the default network has also been implicated in a variety of clinical disorders such as ADHD, Alzheimers, schizophrenia, and autism. This literature is now frequently referred to as mind wandering research (see Brain Clock mind wandering posts).  The following is a nice brief overview of the default brain network.

I have also suggested that some brain fitness technologies (Interactive Metronome in particular;  conflict of interest disclosure--I serve as a paid external consultant to IM regarding research) are achieving success by either directly or indirectly training controlled, focused attention, which requires shutting down and inhibiting the mind wandering predisposition of the default mode network.  I have posted both a set of PPT slides and the video of my recent IM keynote presentation at the Brain Clock blog where I presented the relevant research and hypotheses in detail.

Finally, a more lengthy, thought provoking video is presented last.  This video makes it clear that the brain is best conceptualized as an evolving interconnected network.

Enjoy.

MindHub Pub #2: The Science Behind Interactive Metronome: An Integration of Brain Clock, Temporal Processing, Brain Network and Neurocognitive Research and Theory

[This is an "oldie but goodie" (OBG) post that was originally posted on March 5, 2013]

The second MindHub Pub working paper is now available:  The Science Behind Interactive Metronome:  An Integration of Brain Clock, Temporal Processing, Brain Network and Neurocognitive Research and Theory.  The PDF document can be viewed/downloaded by clicking here.

This working paper is an integration of research and theory that attempts to explain the science behind the positive outcomes of the Interactive Metronome rehabilitative and brain training neurotechnology (the IM effect).  A three-level explanatory model involving three different levels of brain and neurocognitive constructs (McGrew, 2012) is described.   The three-levels are presented in the visual summary in the figure below.  Although the text focuses on explaining the IM effect on cognitive functions (focus, controlled attention, working memory, executive functions), the three-level hypothesized model should be considered a general explanatory framework for understanding the positive IM effect in other human performance domains as well (e.g., recovery from stroke; gait; motor coordination).

The three-level model described here can also be viewed as an IM-free integration of research and theory that explains the relations between the temporal processing (temporal g) of the human brain clock (s), brain regions and networks, brain network communication and synchronization (the parietal-frontal integration theory of intelligence [P-FIT] in particular), and the neurocognitive constructs of attentional control (focus), working memory, and executive functioning.

[Click on image to enlarge]

Brain networks and fine tunning the networks: An OBG post

[This is an OBG (oldie but goodie) post first posted December 16, 2011]

Man has always known that the brain is the center of human behavior.  Early attempts at understanding which locations in the brain controlled different functions were non-scientific and included such practices as phrenology.  This pseudoscience believed that by feeling the bumps of a persons head it was possible to draw conclusions about specific brain functions and traits of the person.

(double click on any image to enlarge)

Eventually brain science revealed that different regions of the brain where specialized for different specific cognitive processes (but it was not related to the phrenological brain bump maps).  This has been called the modular or functional specialization view of the brain, which is grounded in the conclusion that different brain areas acted more-or-less as independent mechanisms for completing specific cognitive functions.

One of the most exciting developments in contemporary neuroscience is the recognition that the human brain processes information via different brain circuits or loops which at a higher level can be studied as large scale brain networks. Although the modular view still provides important brain insights, the accumulating evidence suggests that it has serious limitations and might in fact be misleading (Bresslor and Menon, 2010).  One of the best summaries of this cutting edge research is that by Bresslor and Menon.

Large scale brain network research suggests that cognitive functioning is the result of interactions or communication between different brain systems distributed throughout the brain. That is, when performing a particular task, just one isolated brain area is not working alone.  Instead, different areas of the brain, often far apart from each other within the geographic space of the brain, are communicating through a fast-paced synchronized set of brain signals.  These networks can be considered preferred pathways for sending signals back and forth to perform a specific set of cognitive or motor behaviors. 

To understand preferred neural pathways, think of walking on a college campus where there are paved sidewalks connecting different buildings that house specialized knowledge and activities.  If you have spent anytime on a college campus, one typically finds foot-worn short cuts in the grass that are the preferred (and more efficient) means by which most people move between building A and B.  The combined set of frequently used paved and unpaved pathways are the most efficient or preferred pathways for moving efficiently between buildings.  The human brain has developed preferred communication pathways that link together different brain circuits or loops in order to quickly and efficiently complete specific tasks. 

According to Bresslor and Menon (2010), “a large-scale functional network can therefore be defined as a collection of interconnected brain areas that interact to perform circumscribed functions.”  More importantly, component brain areas in these large-scale brain networks perform different roles.  Some act as controllers or task switchers that coordinate, direct and synchronize the involvement of other brain networks.  Other brain networks handle the flow of sensory or motor information and engage in conscious manipulation of the information in the form of “thinking.” 

As illustrated in the figure above, neuroscientists have identified a number of core brain network nodes or circuits.  The important new insight is that these various nodes or circuits are integrated together into a grander set of higher-level core functional brain networks.  Three important core networks are receiving considerable attention in explaining human behavior. 

Major functional brain networks

The default mode (DMN) or default brain network (shown in blue) is what your brain does when not engaged in specific tasks.  It is the busy or active part of your brain when you are mentally passive.  According to Bresslor and Brennon the “DMN is seen to collectively comprise an integrated system for autobiographical, self-monitoring and social cognitive functions.”  It has also been characterized as responsible for REST (rapid episodic spontaneous thinking).  In other words, this is the spontaneous mind wandering and internal self-talk and thinking we engage in when not working on a specific task or, when completing a task that is so automatized (e.g., driving a car) that our mind starts to wander and generate spontaneous thoughts.  As I have discussed previously (at IM-HOME blog), the default network is responsible for the unquiet or noisy mind.  And, it is likely that people differ in amount of spontaneous mind wandering (which can be both positive creative thinking or distracting thoughts), with some having a very unquiet mind that is hard to turn off, while others can turn off the inner thought generation and self-talk and display tremendous self-focus or controlled attention to perform a cognitively or motorically demanding task.  A very interesting discussion of the serendipitous discovery and explanation of the default brain network is in the following soon to be published scientific article.

The salience network (shown in yellow) is a controller or network switcher.  It monitors information from within (internal input) and from the external world arounding us, which is constantly bombarding us with information.  Think of the salience network as the air traffic controller of the brain.  Its job is to scan all information bombarding us from the outside world and also that from within our own brains.  This controller decides which information is most urgent, task relevant, and which should receive priority in the que of sending brain signals to areas of the brain for processing.  This controlling network must suppress either the default or executive networks depending on the task at hand.  It must suppress one, and activate the other.  Needless to say, this decision making and distribution of information must require exquisite and efficient neural timing as regulated by the brain clock(s).

Finally, the central-executive network (CEN; shown in red) “is engaged in higher-order cognitive and attentional control.”  In other words, when you must engage your conscious brain to work on a problem, place information in your working memory as you think, focus your attention on a task or problem, etc., you are  “thinking” and must focus your controlled attention.  As I understand this research, the salience or controller network is a multi-switching mechanism that is constantly initiating dynamic switching between the REST (sponatenous and often creative unique mind wandering) and thinking networks to best match the current demands you are facing.

According to Bresslor and Melon, not only is this large scale brain network helping us better understand normal cognitive and motor behavior, it is providing insights into clinical disorders of the brain.  Poor synchronization between the three major brain networks has been implicated in Alzheimer’s, schizophrenia, autism, the manic phase of bipolar and Parkinson’s (Bresslor and Melon, 2010), disorders that have all been linked to a brain or neural timing (i.e, the brain clock or clocks).  I also believe that ADHD would be implicated.  If the synchronized millisecond based communication between and within these large networks is compromised, and if the network traffic controller (the salience network) is disrupted in particular, efficient and normal cognition or motor behavior can be compromised.

I find this emerging research fascinating.  I believe it provides a viable working hypothesis to explain why different brain fitness or training neurotechnologies have shown promise in improving cognitive function in working memory, ADHD, and other clinical disorders.  It is my current hypothesis that various brain training technologies may focus on different psychological constructs (e.g., working memory; planning; focus or controlled attention), but their effectiveness may all be directly or indirectly facilitating the sychronization between the major brain networks.  More specifically, by strengthening the ability to invoke the salience or controller network, a person can learn to suppress, inhibit or silence the REST-producing default brain network more efficiently, long enough to exert more controlled attention or focus when invoking the thinking central executive network.  Collectively these brain fitness technologies may all improving the use of those abilities called executive function, or what I have called the personal brain manager.  Those technologies that focus on rhythm or brain timing are those I find most fascinating.  For example, the recent example of the use of melodic intonation therapy with Congresswoman Gabby Giffords (she suffered serious brain trauma due to a gun shot) demonstrates how rhythm-based brain timing therapies may help repair destroyed preferred and efficient neural pathways or, develop new pathways, much like the development of a new foot worn pathway in the grass on a college campus if a preferred pathway is disrupted by a new building, temporary work or rennovation, or some other destruction of a preferred and efficient network of movement path.

To understand the beauty of the synchronized brain, it is best to see the patterns of brain network connections in action.  Below is a video called the “Meditating Mind.”  I urge you to view the video for a number of reasons.  

A number of observations should be clear.  First, during the first part of the video the brain is seen as active even during a resting state.  This is visual evidence of the silent private dialogue (REST) of the default mode or network of the brain.  Next, the video mentions the rhythm of increased and decreased neural activation as the brain responds to no visual information or presentation of a video.  The changes in color and sound demonstrate the rich rhythmic synchronization of large and different parts of the brain, depending on whether the brain is engaged in a passive or active cognitive task.  The beauty of the rapidly changing and spreading communication should make it obvious that efficient rhythmic synchronization of timing of brain signals to and from different networks or circuits is critical to efficient brain functioning.

Finally, the contrast between the same brain under normal conditions and when engaged in a form of meditation is striking.  Clearly when this person’s brain is mediating, the brain is responding with a change in rates and frequency of brain network activation and synchrony.  As I described in my personal IM-HOME based experience post, mastering Interactive Metronome (IM) therapy requires “becoming one with the tone”…which sounds similar to the language of those who engage in various forms of meditation.  Could it be that the rhythmic demans of IM, which require an individual to “lock on” to the auditory tone and stay in that synchronized, rhythmic and repetitive state for as long as possible, might be similar to the underlying mechanics of some forms of meditation, which also seek to suppress irrelevant and distracting thoughts and eventually “let the mind go"---posibsly to follow a specific train of thought with complete and distraction free focus. 

Yes…this is speculation.  I am trying to connect research-based and personal experience dots.  It is exciting.  My IM-HOME based induce personal focus experience  makes sense from the perspective of the function and interaction between the three major large scale brain networks.

Chronic smoking may impair the executive function and default brain networks

Click on image to enlarge

Saturday, March 7, 2015

6:49 PM

ADHD and ASD: Similar and difference "rich club" brain network hubs

Click on image to enlarege.

Saturday, March 7, 2015

6:40 PM

Large-scale functional brain network changes in taxi drivers: Evide... - PubMed

Content duration courtesy of IQ McGrew and the MindHub

http://www.ncbi.nlm.nih.gov/pubmed/25338709

Dreaming and the default network: A review, synthesis, and counterintuitive research proposal.

http://www.ncbi.nlm.nih.gov/pubmed/25723600?dopt=Abstract

Article: One Brain Network for All Mental Illness

One Brain Network for All Mental Illness
http://neurocritic.blogspot.com/2015/02/one-brain-network-for-all-mental-illness.html

Shared from Brain Now on Flipboard, your personal magazine.
Get it for free to keep up with the news you care about.

Smoking interfers with central executive "control" brain networks

​

Yet more research indicating the importance of brain network connectivity, this time demonstrating the detrimental effects of smoking on brain network communication, especially with the executive control and default brain networks.  Take away… smoking may impair the brain networks involved in cognitive control and make stopping smoking even more difficult.

Click on images to enlarge

A good concise definition of mind wandering: Due to default brain network

Mind-wandering has been defined as “a situation in which executive control shifts away from a primary task to the processing of personal goals . . . [and] often occurs without intention or even awareness that one's mind has drifted” (Smallwood & Schooler, 2006, p. 946).

Click on image to enalrge

 

Posted with Blogsy