scholarly journals Determining the Hierarchical Architecture of the Human Brain Using Subject-Level Clustering of Functional Networks

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Teddy J. Akiki ◽  
Chadi G. Abdallah
Keyword(s):  
Large Scale ◽  
Community Organization ◽  
Hierarchical Architecture ◽  
Imaging Data ◽  
Large Scale Network ◽  
Human Connectome Project ◽  
Neuronal Connections ◽  
Scale Network ◽  
Cortical Regions

AbstractOptimal integration and segregation of neuronal connections are necessary for efficient large-scale network communication between distributed cortical regions while allowing for modular specialization. This dynamic in the cortex is enabled at the network mesoscale by the organization of nodes into communities. Previous in vivo efforts to map the mesoscale architecture in humans had several limitations. Here we characterize a consensus multiscale community organization of the functional cortical network. We derive this consensus from the clustering of subject-level networks. We applied this analysis to magnetic resonance imaging data from 1003 healthy individuals part of the Human Connectome Project. The hierarchical atlas and code will be made publicly available for future investigators.

scholarly journals Determining the Hierarchical Architecture of the Human Brain Using Subject-Level Clustering of Functional Networks

2018 ◽  
Author(s):  
Teddy J. Akiki ◽  
Chadi G. Abdallah
Keyword(s):  
Large Scale ◽  
Community Organization ◽  
Hierarchical Architecture ◽  
Imaging Data ◽  
Large Scale Network ◽  
Human Connectome Project ◽  
Neuronal Connections ◽  
Cortical Regions ◽  
The Individual

AbstractOptimal integration and segregation of neuronal connections are necessary for efficient large-scale network communication between distributed cortical regions while allowing for modular specialization. This dynamic in the cortex is enabled at the network mesoscale—the organization of nodes into communities. Previous in vivo efforts to map the mesoscale architecture in humans had several limitations. Here we characterize a consensus multiscale community organization of the functional cortical network. We derive this consensus from the clustering of subject-level networks. We show that this subject-derived consensus framework yields clusters that better map to the individual, compared to the widely-used group-derived consensus approach. We applied this analysis to magnetic resonance imaging data from 1003 healthy individuals part of the Human Connectome Project. The hierarchical atlas and code will be made publicly available for future investigators.

scholarly journals Multimodal Imaging Evidence for a Frontoparietal Modulation of Visual Cortex during the Selective Processing of Conditioned Threat

2017 ◽  
Vol 29 (6) ◽  
pp. 953-967 ◽  
Author(s):  
Nathan M. Petro ◽  
L. Forest Gruss ◽  
Siyang Yin ◽  
Haiqing Huang ◽  
Vladimir Miskovic ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Large Scale ◽  
Anterior Insula ◽  
Causal Modeling ◽  
Middle Frontal Gyrus ◽  
Large Scale Network ◽  
Inferior Parietal Cortex ◽  
Scale Network ◽  
Cortical Regions ◽  
Visual Cortical

Emotionally salient cues are detected more readily, remembered better, and evoke greater visual cortical responses compared with neutral stimuli. The current study used concurrent EEG-fMRI recordings to identify large-scale network interactions involved in the amplification of visual cortical activity when viewing aversively conditioned cues. To generate a continuous neural signal from pericalcarine visual cortex, we presented rhythmic (10/sec) phase-reversing gratings, the orientation of which predicted the presence (CS+) or absence (CS−) of a cutaneous electric shock (i.e., the unconditioned stimulus). The resulting single trial steady-state visual evoked potential (ssVEP) amplitude was regressed against the whole-brain BOLD signal, resulting in a measure of ssVEP-BOLD coupling. Across all trial types, ssVEP-BOLD coupling was observed in both primary and extended visual cortical regions, the rolandic operculum, as well as the thalamus and bilateral hippocampus. For CS+ relative to CS− trials during the conditioning phase, BOLD-alone analyses showed CS+ enhancement at the occipital pole, superior temporal sulci, and the anterior insula bilaterally, whereas ssVEP-BOLD coupling was greater in the pericalcarine cortex, inferior parietal cortex, and middle frontal gyrus. Dynamic causal modeling analyses supported connectivity models in which heightened activity in pericalcarine cortex for threat (CS+) arises from cortico-cortical top–down modulation, specifically from the middle frontal gyrus. No evidence was observed for selective pericalcarine modulation by deep cortical structures such as the amygdala or anterior insula, suggesting that the heightened engagement of pericalcarine cortex for threat stimuli is mediated by cortical structures that constitute key nodes of canonical attention networks.

Voltage-Sensitive Dye Imaging

2015 ◽  
Author(s):  
William Frost ◽  
Jian-young Wu
Keyword(s):  
Large Scale ◽  
Brain Slices ◽  
Network Activity ◽  
Neural Signals ◽  
Voltage Sensitive Dye ◽  
Large Scale Network ◽  
Scale Network ◽  
Invertebrate Ganglia ◽  
Voltage Sensitive Dye Imaging

Voltage sensitive dye imaging (VSD) can be used to record neural activity in hundreds of locations in preparations ranging from mammalian cortex to invertebrate ganglia. Because fast VSDs respond to membrane potential changes with microsecond temporal resolution, these are better suited than calcium indicators for recording rapid neural signals. Here we describe methods for using a 464- element photodiode array and fast VSDs to record signals ranging from large scale network activity in brain slices and in vivo mammalian preparations, to action potentials in over 100 individual neurons in invertebrate ganglia.

Large-Scale Network Analysis for Online Social Brand Advertising

MIS Quarterly ◽  
2016 ◽  
Vol 40 (4) ◽  
pp. 849-868 ◽  
Author(s):  
Kunpeng Zhang ◽  
◽  
Siddhartha Bhattacharyya ◽  
Sudha Ram ◽  
◽  
...  
Keyword(s):  
Network Analysis ◽  
Large Scale ◽  
Large Scale Network ◽  
Brand Advertising ◽  
Scale Network

Attention Biases Visual Activity in Visual Short-term Memory

2014 ◽  
Vol 26 (7) ◽  
pp. 1377-1389 ◽  
Author(s):  
Bo-Cheng Kuo ◽  
Mark G. Stokes ◽  
Alexandra M. Murray ◽  
Anna Christina Nobre
Keyword(s):  
Large Scale ◽  
Short Term Memory ◽  
Control Mechanisms ◽  
Top Down ◽  
Short Term ◽  
Visual Activity ◽  
Visual Short Term Memory ◽  
Large Scale Network ◽  
Visual Areas ◽  
Scale Network

In the current study, we tested whether representations in visual STM (VSTM) can be biased via top–down attentional modulation of visual activity in retinotopically specific locations. We manipulated attention using retrospective cues presented during the retention interval of a VSTM task. Retrospective cues triggered activity in a large-scale network implicated in attentional control and led to retinotopically specific modulation of activity in early visual areas V1–V4. Importantly, shifts of attention during VSTM maintenance were associated with changes in functional connectivity between pFC and retinotopic regions within V4. Our findings provide new insights into top–down control mechanisms that modulate VSTM representations for flexible and goal-directed maintenance of the most relevant memoranda.

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