Novel techniques for large-scale manipulations of cortical networks in non-human primates

Author(s):  
Azadeh Yazdan-Shahmorad ◽  
Daniel B. Silversmith ◽  
Philip N. Sabes
2019 ◽  
Author(s):  
Daniel A Llano ◽  
Chihua Ma ◽  
Umberto Di Fabrizio ◽  
Aynaz Taheri ◽  
Kevin A. Stebbings ◽  
...  

AbstractNetwork analysis of large-scale neuroimaging data has proven to be a particularly challenging computational problem. In this study, we adapt a novel analytical tool, known as the community dynamic inference method (CommDy), which was inspired by social network theory, for the study of brain imaging data from an aging mouse model. CommDy has been successfully used in other domains in biology; this report represents its first use in neuroscience. We used CommDy to investigate aging-related changes in network parameters in the auditory and motor cortices using flavoprotein autofluorescence imaging in brain slices and in vivo. Analysis of spontaneous activations in the auditory cortex of slices taken from young and aged animals demonstrated that cortical networks in aged brains were highly fragmented compared to networks observed in young animals. Specifically, the degree of connectivity of each activated node in the aged brains was significantly lower than those seen in the young brain, and multivariate analyses of all derived network metrics showed distinct clusters of these metrics in young vs. aged brains. CommDy network metrics were then used to build a random-forests classifier based on NMDA-receptor blockade data, which successfully recapitulated the aging findings, suggesting that the excitatory synaptic substructure of the auditory cortex may be altered during aging. A similar aging-related decline in network connectivity was also observed in spontaneous activity obtained from the awake motor cortex, suggesting that the findings in the auditory cortex are reflections of general mechanisms that occur during aging. Therefore, CommDy therefore provides a new dynamic network analytical tool to study the brain and provides links between network-level and synaptic-level dysfunction in the aging brain.


Neurology ◽  
2019 ◽  
Vol 92 (22) ◽  
pp. e2550-e2558 ◽  
Author(s):  
Gianluca Coppola ◽  
Antonio Di Renzo ◽  
Barbara Petolicchio ◽  
Emanuele Tinelli ◽  
Cherubino Di Lorenzo ◽  
...  

ObjectiveWe investigated resting-state (RS)-fMRI using independent component analysis (ICA) to determine the functional connectivity (FC) between networks in chronic migraine (CM) patients and their correlation with clinical features.MethodsTwenty CM patients without preventive therapy or acute medication overuse underwent 3T MRI scans and were compared to a group of 20 healthy controls (HC). We used MRI to collect RS data in 3 selected networks, identified using group ICA: the default mode network (DMN), the executive control network (ECN), and the dorsal attention system (DAS).ResultsCompared to HC, CM patients had significantly reduced functional connectivity between the DMN and the ECN. Moreover, in patients, the DAS showed significantly stronger FC with the DMN and weaker FC with the ECN. The higher the severity of headache, the increased the strength of DAS connectivity, and the lower the strength of ECN connectivity.ConclusionThese results provide evidence for large-scale reorganization of functional cortical networks in chronic migraine. They suggest that the severity of headache is associated with opposite connectivity patterns in frontal executive and dorsal attentional networks.


2004 ◽  
Vol 17 (2) ◽  
pp. 203-223 ◽  
Author(s):  
N.F. Rulkov ◽  
I. Timofeev ◽  
M. Bazhenov

2013 ◽  
Vol 25 (7) ◽  
pp. 1163-1179 ◽  
Author(s):  
Willem Huijbers ◽  
Aaron P. Schultz ◽  
Patrizia Vannini ◽  
Donald G. McLaren ◽  
Sarah E. Wigman ◽  
...  

fMRI studies have linked the posteromedial cortex to episodic learning (encoding) and remembering (retrieval) processes. The posteromedial cortex is considered part of the default network and tends to deactivate during encoding but activate during retrieval, a pattern known as the encoding/retrieval flip. Yet, the exact relationship between the neural correlates of memory performance (hit/miss) and memory stage (encoding/retrieval) and the extent of overlap with intrinsic cortical networks remains to be elucidated. Using task-based fMRI, we isolated the pattern of activity associated with memory performance, memory stage, and the interaction between both. Using resting-state fMRI, we identified which intrinsic large-scale functional networks overlapped with regions showing task-induced effects. Our results demonstrated an effect of successful memory performance in regions associated with the control network and an effect of unsuccessful memory performance in the ventral attention network. We found an effect of memory retrieval in brain regions that span the default and control networks. Finally, we found an interaction between memory performance and memory stage in brain regions associated with the default network, including the posteromedial cortex, posterior parietal cortex, and parahippocampal cortex. We discuss these findings in relation to the encoding/retrieval flip. In general, the findings demonstrate that task-induced effects cut across intrinsic cortical networks. Furthermore, regions within the default network display functional dissociations, and this may have implications for the neural underpinnings of age-related memory disorders.


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