Next Generation Connectomics: Laminar and Spectral Specificity

DFG-SPP 2041 “Computational Connectomics”

The human brain is a highly complex, but structured network. Interactions between brain regions are layer-specific and entail neuronal oscillations in different frequency ranges. Yet, current large-scale connectomics largely ignore these features and typically characterize brain networks as uniform connections between monolithic nodes. The central goal of this project is to overcome this limitation. We will develop and employ novel simultaneous ultra-high field MRI (9.4 T) and EEG to map the laminar connectome of the human brain and to link it to frequency specific neuronal activity. Based on this next-generation connectome, we aim to identify unifying computational principles of corticocortical interactions. In particular, we want to test the hypothesis that interactions between brain regions involve generic patterns of layer-specific interactions and frequency specific neuronal activity. In summary, this interdisciplinary project will employ a novel cutting-edge methodological approach to establish next generation connectomics of the human brain. This may provide fundamental new insights into the large-scale computational principles underlying human cognition and behavior.

Funding total:  435.000€

Hypothesized layer and frequency specific interactions. Anatomically, feedforward connections predominantly project from supragranular to granular layers, while feedback connections project from infragranular to supra- and infragranular layers. We hypothesize a corresponding pattern of laminar specific function connectivity that is associated with gamma-band activity for supragranular-granular interactions (feedforward) and alpha-beta band activity for infragranular-supragranular interactions (feedback).
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