A multiscale perspective of cortical computational dynamics
Abstract: What does a quantitative theory of cortex entail? What are the computational principles that underlie cortical dynamics? Despite the fast pace of discoveries and progress in disparate domains of neuroscience, the lack of unifying principles and fundamental theories of the cortex is vividly apparent. The key shortcoming is that the inherent nature of the brain as a complex adaptive system and multiscale aspects of information processing in neuronal networks are mostly ignored or sacrificed to fit the reductionist approach. To develop a theory of cortical computation, one must address collective information processing and understand ensemble pattern formation at multiple scales. In search of a global theory of cortex, I explored several aspects of neuro-signals at multiple scales and conditions. These included the variability of oscillatory patterns, oscillatory entrainment of ensemble spiking, wave propagation, ensemble excitation/ inhibition balance, and the emergence of network disorder (seizure).
The insights gleaned from these collective computational dynamics provide the foundation for a multiscale cortical quantitative theory of cortex that will guide us in the design of the next generation of neuro-inspired computational algorithms and biomedical devices.
About the speaker:
Nima Dehghani is a Computational and Theoretical Neuroscientist at MIT physics department. After his medical training, as a research fellow at the HMS/MGH/MIT Martinos center and then at the UCSD Multimodal Imaging Lab and MGH Cortical Neurophysiology Lab, he worked on multimodal investigation and electromagnetic source localization of sleep rhythms and thalamocortical oscillations. His PhD work at Unite de Neurosciences, Information et Complexite (UNIC) of Centre National de la Recherche Scientifique (CNRS), was on spectral dynamics of MEG/EEG, assessment of self-organized criticality in multi-electrode ensemble recordings, and analyzing network properties of excitation/inhibition in micro-circuitry of the cerebral cortex. At Harvard's Wyss Institute for Biologically Inspired Engineering, and lately at New England Complex Systems Institute and MIT Physics he uses multimodal techniques in conjunction with the theoretical implications of bioelectromagnetism, multiscale interaction, and complex systems to characterize the dynamic patterns of neuro-signals obtained from miniaturized high-throughput microdevices and large-scale recordings. He aims to use the theoretical perspective of of neuronal ensemble dynamics in design of bio-inspired intelligence and to further enhance their usability for clinical purposes.