scholarly journals Adolescent tuning of association cortex in human structural brain networks

2017 ◽  
Author(s):  
František Váša ◽  
Jakob Seidlitz ◽  
Rafael Romero-Garcia ◽  
Kirstie J. Whitaker ◽  
Gideon Rosenthal ◽  
...  
Keyword(s):  
Sharp Decrease ◽  
Brain Regions ◽  
Brain Network ◽  
Association Cortex ◽  
Structural Correlation ◽  
Age Related ◽  
Cortical Regions ◽  
Structural Networks ◽  
The Brain ◽  
Age Related Changes

AbstractMotivated by prior data on local cortical shrinkage and intracortical myelination, we predicted age-related changes in topological organisation of cortical structural networks during adolescence. We estimated structural correlation from magnetic resonance imaging measures of cortical thickness at 308 regions in a sample of N=297 healthy participants, aged 14-24 years. We used a novel sliding-window analysis to measure age-related changes in network attributes globally, locally and in the context of several community partitions of the network. We found that the strength of structural correlation generally decreased as a function of age. Association cortical regions demonstrated a sharp decrease in nodal degree (hubness) from 14 years, reaching a minimum at approximately 19 years, and then levelling off or even slightly increasing until 24 years. Greater and more prolonged age-related changes in degree of cortical regions within the brain network were associated with faster rates of adolescent cortical myelination and shrinkage. The brain regions that demonstrated the greatest age-related changes were concentrated within prefrontal modules. We conclude that human adolescence is associated with biologically plausible changes in structural imaging markers of brain network organization, consistent with the concept of tuning or consolidating anatomical connectivity between frontal cortex and the rest of the connectome.

scholarly journals Dwelling quietly in the rich club: brain network determinants of slow cortical fluctuations

2015 ◽  
Vol 370 (1668) ◽  
pp. 20140165 ◽  
Author(s):  
Leonardo L. Gollo ◽  
Andrew Zalesky ◽  
R. Matthew Hutchison ◽  
Martijn van den Heuvel ◽  
Michael Breakspear
Keyword(s):  
Spatial Scales ◽  
Brain Regions ◽  
Brain Network ◽  
Morphological Properties ◽  
Brain Organization ◽  
Rich Club ◽  
Guiding Principle ◽  
The Rich ◽  
Cortical Regions ◽  
The Brain

For more than a century, cerebral cartography has been driven by investigations of structural and morphological properties of the brain across spatial scales and the temporal/functional phenomena that emerge from these underlying features. The next era of brain mapping will be driven by studies that consider both of these components of brain organization simultaneously—elucidating their interactions and dependencies. Using this guiding principle, we explored the origin of slowly fluctuating patterns of synchronization within the topological core of brain regions known as the rich club, implicated in the regulation of mood and introspection. We find that a constellation of densely interconnected regions that constitute the rich club (including the anterior insula, amygdala and precuneus) play a central role in promoting a stable, dynamical core of spontaneous activity in the primate cortex. The slow timescales are well matched to the regulation of internal visceral states, corresponding to the somatic correlates of mood and anxiety. In contrast, the topology of the surrounding ‘feeder’ cortical regions shows unstable, rapidly fluctuating dynamics likely to be crucial for fast perceptual processes. We discuss these findings in relation to psychiatric disorders and the future of connectomics.

scholarly journals Mapping individual differences across brain network structure to function and behavior with connectome embedding

2021 ◽  
Author(s):  
Gidon Levakov ◽  
Joshua Faskowitz ◽  
Galia Avidan ◽  
Olaf Sporns
Keyword(s):  
Individual Differences ◽  
Functional Connectivity ◽  
Predictive Accuracy ◽  
Structural Connectivity ◽  
Brain Regions ◽  
Brain Network ◽  
Global Network ◽  
Age Related ◽  
And Behavior ◽  
The Brain

AbstractThe connectome, a comprehensive map of the brain’s anatomical connections, is often summarized as a matrix comprising all dyadic connections among pairs of brain regions. This representation cannot capture higher-order relations within the brain graph. Connectome embedding (CE) addresses this limitation by creating compact vectorized representations of brain nodes capturing their context in the global network topology. Here, nodes “context” is defined as random walks on the brain graph and as such, represents a generative model of diffusive communication around nodes. Applied to group-averaged structural connectivity, CE was previously shown to capture relations between inter-hemispheric homologous brain regions and uncover putative missing edges from the network reconstruction. Here we extend this framework to explore individual differences with a novel embedding alignment approach. We test this approach in two lifespan datasets (NKI: n=542; Cam-CAN: n=601) that include diffusion-weighted imaging, resting-state fMRI, demographics and behavioral measures. We demonstrate that modeling functional connectivity with CE substantially improves structural to functional connectivity mapping both at the group and subject level. Furthermore, age-related differences in this structure-function mapping are preserved and enhanced. Importantly, CE captures individual differences by out-of-sample prediction of age and intelligence. The resulting predictive accuracy was higher compared to using structural connectivity and functional connectivity. We attribute these findings to the capacity of the CE to incorporate aspects of both anatomy (the structural graph) and function (diffusive communication). Our novel approach allows mapping individual differences in the connectome through structure to function and behavior.

Age-related changes in the brain transfer of blood-borne horseradish peroxidase in the hippocampus of senescence-accelerated mouse

1997 ◽  
Vol 93 (3) ◽  
pp. 233-240 ◽  
Author(s):  
M. Ueno ◽  
Ichiro Akiguchi ◽  
Masanori Hosokawa ◽  
Masahiko Shinnou ◽  
Haruhiko Sakamoto ◽  
...  
Keyword(s):  
Horseradish Peroxidase ◽  
Age Related ◽  
The Brain ◽  
Senescence Accelerated Mouse ◽  
Age Related Changes

scholarly journals Physical positioning markedly enhances brain transduction after intrathecal AAV9 infusion

2018 ◽  
Vol 4 (11) ◽  
pp. eaau9859 ◽  
Author(s):  
Michael J. Castle ◽  
Yuhsiang Cheng ◽  
Aravind Asokan ◽  
Mark H. Tuszynski
Keyword(s):  
Gene Expression ◽  
Gene Delivery ◽  
Neurological Disorders ◽  
Fold Increase ◽  
Brain Regions ◽  
Intrathecal Administration ◽  
Simple Method ◽  
Virus Serotype ◽  
Cortical Regions ◽  
The Brain

Several neurological disorders may benefit from gene therapy. However, even when using the lead vector candidate for intrathecal administration, adeno-associated virus serotype 9 (AAV9), the strength and distribution of gene transfer to the brain are inconsistent. On the basis of preliminary observations that standard intrathecal AAV9 infusions predominantly drive reporter gene expression in brain regions where gravity might cause cerebrospinal fluid to settle, we tested the hypothesis that counteracting vector “settling” through animal positioning would enhance vector delivery to the brain. When rats are either inverted in the Trendelenburg position or continuously rotated after intrathecal AAV9 infusion, we find (i) a significant 15-fold increase in the number of transduced neurons, (ii) a marked increase in gene delivery to cortical regions, and (iii) superior animal-to-animal consistency of gene expression. Entorhinal, prefrontal, frontal, parietal, hippocampal, limbic, and basal forebrain neurons are extensively transduced: 95% of transduced cells are neurons, and greater than 70% are excitatory. These findings provide a novel and simple method for broad gene delivery to the cortex and are of substantial relevance to translational programs for neurological disorders, including Alzheimer’s disease and related dementias, stroke, and traumatic brain injury.

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 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 A Graphlet-Based Topological Characterization of the Resting-State Network in Healthy People

2021 ◽  
Vol 15 ◽  
Author(s):  
Paolo Finotelli ◽  
Carlo Piccardi ◽  
Edie Miglio ◽  
Paolo Dulio
Keyword(s):  
Resting State ◽  
Brain Regions ◽  
Brain Network ◽  
Induced Subgraphs ◽  
Topological Characterization ◽  
Network Information ◽  
The Subject ◽  
Euclidean Distances ◽  
The Brain

In this paper, we propose a graphlet-based topological algorithm for the investigation of the brain network at resting state (RS). To this aim, we model the brain as a graph, where (labeled) nodes correspond to specific cerebral areas and links are weighted connections determined by the intensity of the functional magnetic resonance imaging (fMRI). Then, we select a number of working graphlets, namely, connected and non-isomorphic induced subgraphs. We compute, for each labeled node, its Graphlet Degree Vector (GDV), which allows us to associate a GDV matrix to each one of the 133 subjects of the considered sample, reporting how many times each node of the atlas “touches” the independent orbits defined by the graphlet set. We focus on the 56 independent columns (i.e., non-redundant orbits) of the GDV matrices. By aggregating their count all over the 133 subjects and then by sorting each column independently, we obtain a sorted node table, whose top-level entries highlight the nodes (i.e., brain regions) most frequently touching each of the 56 independent graphlet orbits. Then, by pairwise comparing the columns of the sorted node table in the top-k entries for various values of k, we identify sets of nodes that are consistently involved with high frequency in the 56 independent graphlet orbits all over the 133 subjects. It turns out that these sets consist of labeled nodes directly belonging to the default mode network (DMN) or strongly interacting with it at the RS, indicating that graphlet analysis provides a viable tool for the topological characterization of such brain regions. We finally provide a validation of the graphlet approach by testing its power in catching network differences. To this aim, we encode in a Graphlet Correlation Matrix (GCM) the network information associated with each subject then construct a subject-to-subject Graphlet Correlation Distance (GCD) matrix based on the Euclidean distances between all possible pairs of GCM. The analysis of the clusters induced by the GCD matrix shows a clear separation of the subjects in two groups, whose relationship with the subject characteristics is investigated.

Exercise Impacts Age-Related Changes in Cognitive Function and Neural Complexity

2016 ◽  
Vol 5 (1) ◽  
pp. 30-38 ◽  
Author(s):  
Jennifer J. Heisz ◽  
Ana Kovacevic
Keyword(s):  
Older Adults ◽  
Cognitive Function ◽  
Executive Functions ◽  
Cognitive Outcomes ◽  
Physically Active ◽  
Age Related ◽  
The Neural Network ◽  
Future Work ◽  
The Brain ◽  
Age Related Changes

Age-related changes in the brain can compromise cognitive function. However, in some cases, the brain is able to functionally reorganize to compensate for some of this loss. The present paper reviews the benefits of exercise on executive functions in older adults and discusses a potential mechanism through which exercise may change the way the brain processes information for better cognitive outcomes. Specifically, older adults who are more physically active demonstrate a shift toward local neural processing that is associated with better executive functions. We discuss the use of neural complexity as a sensitive measure of the neural network plasticity that is enhanced through exercise. We conclude by highlighting the future work needed to improve exercise prescriptions that help older adults maintain their cognitive and physical functions for longer into their lifespan.

Relative potencies of testosterone and 5α-dihydrotestosterone on crowing and cloacal gland growth in the Japanese quail (Coturnix coturnix japonica)

1984 ◽  
Vol 100 (1) ◽  
pp. 19-23 ◽  
Author(s):  
J. Balthazart ◽  
M. Schumacher ◽  
G. Malacarne
Keyword(s):  
Coturnix Japonica ◽  
Coturnix Coturnix Japonica ◽  
Coturnix Coturnix ◽  
Behavioural Activity ◽  
Age Related ◽  
Female Quail ◽  
The Brain ◽  
Relative Potencies ◽  
Cloacal Gland ◽  
Age Related Changes

ABSTRACT It has been suggested that testosterone is less effective at inducing crowing behaviour in young birds than in adults because of the presence of higher levels of steroid 5β-reductase in the young brain, which converts testosterone to inactive 5β-reduced metabolites. This hypothesis was tested indirectly by comparing the relative potencies of 5α-dihydrotestosterone (5α-DHT), which cannot be converted to 5β-metabolities, and testosterone at inducing crowing in young gonadectomized male and female quail. The promotion of cloacal gland growth by these treatments was also assessed since there are no age-related changes in 5β-reductase in this organ. Silicone elastomer implants (2·5, 5 and 10 mm) containing 5α-DHT were more effective at stimulating crowing than similar implants of testosterone whilst there was little difference in their potency at inducing cloacal gland growth. These results are consistent with the hypothesis that brain steroid 5β-reductase regulates the behavioural activity of testosterone in the brain of young birds. J. Endocr. (1984) 100, 19–23

Age-related changes in transmitter glutamate and NMDA receptor/channels in the brain of senescence-accelerated mouse

1992 ◽  
Vol 137 (2) ◽  
pp. 169-172 ◽  
Author(s):  
Yoshihisa Kitamura ◽  
Xue-Hui Zhao ◽  
Toshio Ohnuki ◽  
Makiko Takei ◽  
Yasuyuki Nomura
Keyword(s):  
Nmda Receptor ◽  
Age Related ◽  
The Brain ◽  
Senescence Accelerated Mouse ◽  
Transmitter Glutamate ◽  
Age Related Changes
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