Showing posts with label brain function. Show all posts
Showing posts with label brain function. Show all posts

Thursday, June 19, 2025

Research Byte: Positive #schoolclimate can make a difference in #reading, #mentalhealth and #coritical thinning - #schoolpsychology #SPED #EDPSY #cognition


Positive school climate boosts children’s reading achievement, mental health and cortical thinning.  

Brain and Cognition.  Sorry, not an open access article you can download.  ðŸ˜’


Abstract

Growing evidence underscores school climate as an important protective factor for children’s academic achievement and mental health. However, whether and how school climate impacts child development from behavioral to brain has remained largely unknown. This study aimed to investigate the protective roles of school climate in children’s reading achievement, mental health, and cortical thickness. Behavioral and neuroimaging data were obtained from 400 children aged 6–12 years (mean age = 9.65 years). First, results showed that a positive school climate was significantly associated with better reading performance and reduced internalizing/externalizing problems. Notably, school climate compensated for disadvantaged family environments, particularly among children with less educated parents. Second, externalizing problems significantly mediated the link between school climate and reading achievement. Third, compared with their peers, children from schools with more positive climate showed accelerated cortical thinning in the lingual/ pericalcarine/ cuneus and postcentral regions, the hubs for visual processing and sensorimotor integration. Fourth, the cortical thickness of the lingual/ pericalcarine/cuneus and postcentral gyri significantly mediated the role of school climate in reading achievement. These results highlight school climate as a multi-level protective factor that fosters academic resilience via behavioral regulation and cortical thinning.

Wednesday, May 07, 2025

Research Byte: A #hierarchical model of early #brain #functional #network development - excellent #review #cognition #cognitive #brain networks #schoolpsychology

Click on image to enlarge for easy viewing

A good overview/review article of the evolution of brain networks with an excellent visual-graphic summary (I love good visual summaries, which I label in my blog as being a Gv Figure Hall of Fame)

A hierarchical model of early brain functional network development 
Wei Gao, Open access (you can download and read) in Trends in Cognitive Science

Abstract 

Functional brain networks emerge prenatally, grow interactively during the first years of life, and optimize both within-network topology and between-network interactions as individuals age. This review summarizes research that has characterized this process over the past two decades, and aims to link functional network growth with emerging behaviors, thereby developing a more holistic understanding of the developing brain and behavior from a functional network perspective. This synthesis suggests that the development of the brain's functional networks follows an overlapping hierarchy, progressing from primary sensory/motor to socioemotional-centered development and finally to higher-order cognitive/executive control networks. Risk-related alterations, resilience factors, treatment effects, and novel therapeutic opportunities are also dis-cussed to encourage the consideration of future imaging-assisted methods for identifying risks and interventions.

Thursday, December 12, 2024

Research byte: Prediction of human #intelligence (#g #Gf #Gc) from #brain (#network) #connectivity - #CHC

Choosing explanation over performance: Insights from machine learning-based prediction of human intelligence from brain connectivity 

PNAS Nexus, Volume 3, Issue 12, December 2024, pgae519,
Online and PDF download available at this link:  https://doi.org/10.1093/pnasnexus/pgae519

Abstract

A growing body of research predicts individual cognitive ability levels from brain characteristics including functional brain connectivity. The majority of this research achieves statistically significant prediction performance but provides limited insight into neurobiological processes underlying the predicted concepts. The insufficient identification of predictive brain characteristics may present an important factor critically contributing to this constraint. Here, we encourage to design predictive modeling studies with an emphasis on interpretability to enhance our conceptual understanding of human cognition. As an example, we investigated in a preregistered study which functional brain connections successfully predict general, crystallized, and fluid intelligence in a sample of 806 healthy adults (replication: N = 322). The choice of the predicted intelligence component as well as the task during which connectivity was measured proved crucial for better understanding intelligence at the neural level. Further, intelligence could be predicted not solely from one specific set of brain connections, but from various combinations of connections with system-wide locations. Such partially redundant, brain-wide functional connectivity characteristics complement intelligence-relevant connectivity of brain regions proposed by established intelligence theories. In sum, our study showcases how future prediction studies on human cognition can enhance explanatory value by prioritizing a systematic evaluation of predictive brain characteristics over maximizing prediction performance (emphasis added).

Monday, January 11, 2016

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.

Monday, September 30, 2013

IQ score differences across time may relfect real changes in the brain

Lay people and many professionals often express consternation when an individuals measured IQ scores are different at different times in their life.  This concern is particularly heightened in high stakes settings where differences in IQ scores can result in changes in eligibility for programs (e.g., social security disability income) or life-or-death decisions (e.g., Atkins MR/ID death penalty cases).

Factors contributing to significant IQ score differences are many (McGrew, in press a) and may include: (a) procedural or test administration errors (e.g., scoring errors; improper nonstandardized test administration; malingering; age vs. grade norms; practice effects), (b) test norm or standardization differences (e.g., norm obsolescence or the Flynn Effect; McGrew, in press b), (c) content differences across different test batteries or between different editions of the same battery, or (d) variations in a person’s performance on different occasions.

 An article "in press" (Neuroimage) by Burgaleta et al. (click here to view copy with annotated comments)  provides the important reminder that differences in IQ scores for an individual (across time) may be due to real changes in general intelligence related to real changes in brain development.  These researchers found that changes in cortical brain thickness were related to changes in IQ scores.  They concluded that "the dynamic nature of intelligence-brain relations...support the idea that changes in IQ across development can reflect meaningful general cognitive ability changes and have a neuroanatomical substrate" (viz., changes in cortical thickness in key brain regions).  The hypothesis was offered that changes in the the cortical areas of  frontoparietal brain network (see P-FIT model of intelligence) may be related to changes in working memory, which in turn has been strongly associated with general reasoning (fluid intelligence; Gf).

The cortical thickness-IQ change relation was deemed consistent with "cellular events that are sensitive to postnatal development and experience."  Possible causal factors suggested included insufficient education or social stimulation during sensitive developmental periods, as well as lifestyle, diet and nutrition, and genetic factors.

  • McGrew, K. S. (in press a).  Intellectual functioning:  Conceptual issues.  In E. Polloway (Ed.), Determining intellectual disability in the courts:  Focus on capital cases.  AAIDD, Washington, DC.

  •  McGrew, K. S. (in press b).  Norm obsolescence:  The Flynn Effect.  In E. Polloway (Ed.), Determining intellectual disability in the courts:  Focus on capital cases.  AAIDD, Washington, DC.


[Click on images to enlarge]








Tuesday, May 17, 2011

Journal of Cognitive Neuroscience: Simply AWESOME




I just spent some time browsing the articles lined up for forthcoming publication in the Journal of Cognitive Neuroscience. As a researcher who is looking for good research that links my primary are of interest (intelligence and measurement of intelligence) with underlying brain mechanisms, I think I have found the pot-o-gold at the end of the brain-behavior rainbow. Below is the list of articles the journal currently has "waiting in the wings." The depth and breadth is amazing. I have added this journal to my RSS feed so I can stay up-to-date when articles are published.

What a way to start my day. Finding this will sipping my morning java. Now if I could only fine time to read just a 1/4 of these articles.

Well MIT Press.

Double click on images to enlarge



























































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Saturday, February 12, 2011

The Cognitive Atlas Project - way cool stuff

Very intriguing article and description of the Cognitive Atlas Project, a scientific social collaborative knowledge project.









Poldrack, R. A. (2010). Mapping Mental Function to Brain Structure: How Can Cognitive Neuroimaging Succeed? Perspectives on Psychological Science, 5(6), 753-761

Abstract

The goal of cognitive neuroscience is to identify the mapping between brain function and mental processing. In this article, I examine the strategies that have been used to identify such mappings and argue that they may be fundamentally unable to identify selective structure–function mappings. To understand the functional anatomy of mental processes, it will be necessary for researchers to move from the brain-mapping strategies that the field has employed toward a search for selective associations. This will require a greater focus on the structure of cognitive processes, which can be achieved through the development of formal ontologies that describe the structure of mental processes. In this article, I outline the Cognitive Atlas Project, which is developing such ontologies, and show how this knowledge could be used in conjunction with data-mining approaches to more directly relate mental processes and brain function.










The article , with annotations, is available here, as part of this blogs IQ's Reading feature.



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Thursday, February 10, 2011

Research Bytes: Neuro-imaging research--brain networks and public interest


Beck, D. M. (2010). The Appeal of the Brain in the Popular Press. Perspectives on Psychological Science, 5(6), 762-766.

Since the advent of human neuroimaging, and of functional magnetic resonance imaging (fMRI) in particular, the popular press has shown an increasing interest in brain-related findings. In this article, I explore possible reasons behind this interest, including recent data suggesting that people find brain images and neuroscience language more convincing than results that make no reference to the brain (McCabe & Castel, 2008; Weisberg, Keil, Goodstein, Rawson, & Gray, 2008). I suggest that part of the allure of these data are the deceptively simply messages they afford, as well as general, but sometimes misguided, confidence in biological data. In addition to cataloging some misunderstandings by the press and public, I highlight the responsibilities of the research scientist in carefully conveying their work to the general public.


Gonsalves, B. D., & Cohen, N. J. (2010). Brain Imaging, Cognitive Processes, and Brain Networks. Perspectives on Psychological Science, 5(6), 744-752.


McDonald, R. P. (2010). Structural Models and the Art of Approximation. Perspectives on Psychological Science, 5(6), 675-686

Structural equation models have provided a seemingly rigorous method for investigating causal relations in nonexperimental data in the presence of measurement error or multiple measures of putative causes or effects. Methods have been developed for fitting these very complex models globally and obtaining global fit statistics or global measures of their approximation to sample data. Structural equation models are idealizations that can serve only as approximations to real multivariate data. Further, these models are multidimensional, and the approximation is itself multidimensional. Tests of “significance” and global indices of approximation do not provide an adequate basis for judging the acceptability of the approximation. Standard applications of structural models use a composite of two models—a measurement (path) model and a path (causal) model. Separate analyses of the measurement model and the path model provide an informed judgment, whereas the composite global analysis can easily yield unreasonable conclusions. Separating the component models enables a careful assessment of the actual constraints implied by the path model, using recently developed methods. An empirical example shows how the conventional global treatment yields unacceptable conclusions


Poldrack, R. A. (2010). Mapping Mental Function to Brain Structure: How Can Cognitive Neuroimaging Succeed? Perspectives on Psychological Science, 5(6), 753-761

The goal of cognitive neuroscience is to identify the mapping between brain function and mental processing. In this article, I examine the strategies that have been used to identify such mappings and argue that they may be fundamentally unable to identify selective structure–function mappings. To understand the functional anatomy of mental processes, it will be necessary for researchers to move from the brain-mapping strategies that the field has employed toward a search for selective associations. This will require a greater focus on the structure of cognitive processes, which can be achieved through the development of formal ontologies that describe the structure of mental processes. In this article, I outline the Cognitive Atlas Project, which is developing such ontologies, and show how this knowledge could be used in conjunction with data-mining approaches to more directly relate mental processes and brain function.


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