Biophysical Modeling of Nonlinear Dendritic Computations Akshan Bansal
Nonlinear dendritic integration is crucial for the optimal processing of correlated inputs, may play a role in the location of dendritic clusters, and can be modeled biophysically. Linear integration is necessary for the processing of uncorrelated inputs where presynaptic neurons and postsynaptic dendrites are at a distance. The study make advancements in the field by expanding the study of dendritic computation to large scale networks using in vivo and in vitro statistics and produces high resolution results. Further studies need to involve optogenetic tools, and vary controls from spontaneous network activity to nonnaturalistic activity across single stimulus dimensions. Understanding of neural mechanisms related to processing can in the future be applied to neuromorphic hardware and machine learning for greater efficiency in processing.
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