scholarly journals Optimization of energy state transition trajectory supports the development of executive function during youth

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Zaixu Cui ◽  
Jennifer Stiso ◽  
Graham L Baum ◽  
Jason Z Kim ◽  
David R Roalf ◽  
...  
Keyword(s):  
Executive Function ◽  
State Transition ◽  
Energy State ◽  
Diffusion Imaging ◽  
Brain Regions ◽  
Network Control ◽  
Energetic Cost ◽  
Executive Performance ◽  
Structural Networks ◽  
Transition Trajectory

Executive function develops during adolescence, yet it remains unknown how structural brain networks mature to facilitate activation of the fronto-parietal system, which is critical for executive function. In a sample of 946 human youths (ages 8-23y) who completed diffusion imaging, we capitalized upon recent advances in linear dynamical network control theory to calculate the energetic cost necessary to activate the fronto-parietal system through the control of multiple brain regions given existing structural network topology. We found that the energy required to activate the fronto-parietal system declined with development, and the pattern of regional energetic cost predicts unseen individuals’ brain maturity. Finally, energetic requirements of the cingulate cortex were negatively correlated with executive performance, and partially mediated the development of executive performance with age. Our results reveal a mechanism by which structural networks develop during adolescence to reduce the theoretical energetic costs of transitions to activation states necessary for executive function.

scholarly journals Optimization of Energy State Transition Trajectory Supports the Development of Executive Function During Youth

2018 ◽  
Author(s):  
Zaixu Cui ◽  
Jennifer Stiso ◽  
Graham L. Baum ◽  
Jason Z. Kim ◽  
David R. Roalf ◽  
...  
Keyword(s):  
Executive Function ◽  
Control Theory ◽  
Brain Networks ◽  
Executive Dysfunction ◽  
Network Control ◽  
Energetic Cost ◽  
Sufficient Information ◽  
Executive Performance ◽  
Recent Advances ◽  
Structural Brain

ABSTRACTExecutive function develops rapidly during adolescence, and failures of executive function are associated with both risk-taking behaviors and psychopathology. However, it remains relatively unknown how structural brain networks mature during this critical period to facilitate energetically demanding transitions to activate the frontoparietal system, which is critical for executive function. In a sample of 946 human youths (ages 8-23 yr) who completed diffusion imaging as part of the Philadelphia Neurodevelopment Cohort, we capitalized upon recent advances in network control theory in order to calculate the control energy necessary to activate the frontoparietal system given the existing structural network topology. We found that the control energy required to activate the frontoparietal system declined with development. Moreover, we found that this control energy pattern contains sufficient information to make accurate predictions about individuals’ brain maturity. Finally, the control energy costs of the cingulate cortex were negatively correlated with executive performance, and partially mediated the development of executive performance with age. These results could not be explained by changes in general network control properties or in network modularity. Taken together, our results reveal a mechanism by which structural networks develop during adolescence to facilitate the instantiation of activation states necessary for executive function.SIGNIFICANCE STATEMENTExecutive function undergoes protracted development during youth, but it is unknown how structural brain networks mature to facilitate the activation of the frontoparietal cortex that is critical for executive processes. Here, we leverage recent advances in network control theory to establish that structural brain networks evolve in adolescence to lower the energetic cost of activating the frontoparietal system. Our results suggest a new mechanistic framework for understanding how brain network maturation supports cognition, with clear implications for disorders marked by executive dysfunction, such as ADHD and psychosis.

scholarly journals Hippocampal regenerative medicine: neurogenic implications for addiction and mental disorders

2021 ◽  
Author(s):  
Lee Peyton ◽  
Alfredo Oliveros ◽  
Doo-Sup Choi ◽  
Mi-Hyeon Jang
Keyword(s):  
Decision Making ◽  
Prefrontal Cortex ◽  
Executive Function ◽  
General Population ◽  
Mental Disorders ◽  
Psychiatric Illness ◽  
Neural Circuitry ◽  
Brain Regions ◽  
Neuropsychiatric Disease ◽  
Motivated Behavior

AbstractPsychiatric illness is a prevalent and highly debilitating disorder, and more than 50% of the general population in both middle- and high-income countries experience at least one psychiatric disorder at some point in their lives. As we continue to learn how pervasive psychiatric episodes are in society, we must acknowledge that psychiatric disorders are not solely relegated to a small group of predisposed individuals but rather occur in significant portions of all societal groups. Several distinct brain regions have been implicated in neuropsychiatric disease. These brain regions include corticolimbic structures, which regulate executive function and decision making (e.g., the prefrontal cortex), as well as striatal subregions known to control motivated behavior under normal and stressful conditions. Importantly, the corticolimbic neural circuitry includes the hippocampus, a critical brain structure that sends projections to both the cortex and striatum to coordinate learning, memory, and mood. In this review, we will discuss past and recent discoveries of how neurobiological processes in the hippocampus and corticolimbic structures work in concert to control executive function, memory, and mood in the context of mental disorders.

scholarly journals A Computational Network Control Theory Analysis of Depression Symptoms

2018 ◽  
Vol 1 ◽  
Author(s):  
Yoed N. Kenett ◽  
Roger E. Beaty ◽  
John D. Medaglia
Keyword(s):  
Control Theory ◽  
Diffusion Tensor ◽  
Brain Regions ◽  
Brain Network ◽  
Network Control ◽  
Depression Symptoms ◽  
Theory Approach ◽  
Imaging Data ◽  
The Brain ◽  
Subclinical Depression

AbstractRumination and impaired inhibition are considered core characteristics of depression. However, the neurocognitive mechanisms that contribute to these atypical cognitive processes remain unclear. To address this question, we apply a computational network control theory approach to structural brain imaging data acquired via diffusion tensor imaging in a large sample of participants, to examine how network control theory relates to individual differences in subclinical depression. Recent application of this theory at the neural level is built on a model of brain dynamics, which mathematically models patterns of inter-region activity propagated along the structure of an underlying network. The strength of this approach is its ability to characterize the potential role of each brain region in regulating whole-brain network function based on its anatomical fingerprint and a simplified model of node dynamics. We find that subclinical depression is negatively related to higher integration abilities in the right anterior insula, replicating and extending previous studies implicating atypical switching between the default mode and Executive Control Networks in depression. We also find that subclinical depression is related to the ability to “drive” the brain system into easy to reach neural states in several brain regions, including the bilateral lingual gyrus and lateral occipital gyrus. These findings highlight brain regions less known in their role in depression, and clarify their roles in driving the brain into different neural states related to depression symptoms.

scholarly journals Alterations of Expression of the Serotonin 5-HT4 Receptor in Brain Disorders

2018 ◽  
Vol 19 (11) ◽  
pp. 3581 ◽  
Author(s):  
Heike Rebholz ◽  
Eitan Friedman ◽  
Julia Castello
Keyword(s):  
Executive Function ◽  
Food Intake ◽  
Serotonin Receptor ◽  
Current Knowledge ◽  
Memory Loss ◽  
Brain Regions ◽  
Brain Disorders ◽  
Protein Levels ◽  
Preclinical Animal Models ◽  
Mood Depression

The serotonin 4 receptor, 5-HT4R, represents one of seven different serotonin receptor families and is implicated in a variety of physiological functions and their pathophysiological variants, such as mood and depression or anxiety, food intake and obesity or anorexia, or memory and memory loss in Alzheimer’s disease. Its central nervous system expression pattern in the forebrain, in particular in caudate putamen, the hippocampus and to lesser extent in the cortex, predispose it for a role in executive function and reward-related actions. In rodents, regional overexpression or knockdown in the prefrontal cortex or the nucleus accumbens of 5-HT4R was shown to impact mood and depression-like phenotypes, food intake and hypophagia; however, whether expression changes are causally involved in the etiology of such disorders is not clear. In this context, more data are emerging, especially based on PET technology and the use of ligand tracers that demonstrate altered 5-HT4R expression in brain disorders in humans, confirming data stemming from post-mortem tissue and preclinical animal models. In this review, we would like to present the current knowledge of 5-HT4R expression in brain regions relevant to mood/depression, reward and executive function with a focus on 5-HT4R expression changes in brain disorders or caused by drug treatment, at both the transcript and protein levels.

scholarly journals Integrative Structural Brain Network Analysis In Diffusion Tensor Imaging

2017 ◽  
Author(s):  
Moo K. Chung ◽  
Jamie L. Hanson ◽  
Nagesh Adluru ◽  
Andrew L. Alexander ◽  
Richard J. Davidson ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Diffusion Tensor ◽  
Structural Connectivity ◽  
Brain Regions ◽  
Brain Network ◽  
Node Degree ◽  
Fiber Tracts ◽  
White Matter Fiber Tracts ◽  
Structural Brain Network ◽  
Structural Networks

AbstractIn diffusion tensor imaging, structural connectivity between brain regions is often measured by the number of white matter fiber tracts connecting them. Other features such as the length of tracts or fractional anisotropy (FA) are also used in measuring the strength of connectivity. In this study, we investigated the effects of incorporating the number of tracts, the tract length and FA-values into the connectivity model. Using various node-degree based graph theory features, the three connectivity models are compared. The methods are applied in characterizing structural networks between normal controls and maltreated children, who experienced maltreatment while living in post-institutional settings before being adopted by families in the US.

scholarly journals Development of structure–function coupling in human brain networks during youth

2019 ◽  
Vol 117 (1) ◽  
pp. 771-778 ◽  
Author(s):  
Graham L. Baum ◽  
Zaixu Cui ◽  
David R. Roalf ◽  
Rastko Ciric ◽  
Richard F. Betzel ◽  
...  
Keyword(s):  
Executive Function ◽  
Structure Function ◽  
Cognitive Processes ◽  
Brain Connectivity ◽  
Critical Dimension ◽  
Functional Specialization ◽  
Cross Sectional ◽  
Executive Performance ◽  
Age Related ◽  
Adolescent Brain Development

The protracted development of structural and functional brain connectivity within distributed association networks coincides with improvements in higher-order cognitive processes such as executive function. However, it remains unclear how white-matter architecture develops during youth to directly support coordinated neural activity. Here, we characterize the development of structure–function coupling using diffusion-weighted imaging andn-back functional MRI data in a sample of 727 individuals (ages 8 to 23 y). We found that spatial variability in structure–function coupling aligned with cortical hierarchies of functional specialization and evolutionary expansion. Furthermore, hierarchy-dependent age effects on structure–function coupling localized to transmodal cortex in both cross-sectional data and a subset of participants with longitudinal data (n= 294). Moreover, structure–function coupling in rostrolateral prefrontal cortex was associated with executive performance and partially mediated age-related improvements in executive function. Together, these findings delineate a critical dimension of adolescent brain development, whereby the coupling between structural and functional connectivity remodels to support functional specialization and cognition.

scholarly journals Signal propagation via cortical hierarchies

2020 ◽  
Vol 4 (4) ◽  
pp. 1072-1090 ◽  
Author(s):  
Bertha Vézquez-Rodríguez ◽  
Zhen-Qi Liu ◽  
Patric Hagmann ◽  
Bratislav Misic
Keyword(s):  
Shortest Paths ◽  
Signal Propagation ◽  
Brain Regions ◽  
Hierarchical Organization ◽  
Attention Networks ◽  
Diffusion Spectrum Imaging ◽  
Cortical Hierarchy ◽  
Spectrum Imaging ◽  
Structural Networks ◽  
The Brain

The wiring of the brain is organized around a putative unimodal-transmodal hierarchy. Here we investigate how this intrinsic hierarchical organization of the brain shapes the transmission of information among regions. The hierarchical positioning of individual regions was quantified by applying diffusion map embedding to resting-state functional MRI networks. Structural networks were reconstructed from diffusion spectrum imaging and topological shortest paths among all brain regions were computed. Sequences of nodes encountered along a path were then labeled by their hierarchical position, tracing out path motifs. We find that the cortical hierarchy guides communication in the network. Specifically, nodes are more likely to forward signals to nodes closer in the hierarchy and cover a range of unimodal and transmodal regions, potentially enriching or diversifying signals en route. We also find evidence of systematic detours, particularly in attention networks, where communication is rerouted. Altogether, the present work highlights how the cortical hierarchy shapes signal exchange and imparts behaviorally relevant communication patterns in brain networks.

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