Past events

Recurrent connections are abundant in cortical circuitry but their functional role has been the subject of intense debates. The talk will present a computational approach to investigate the role of recurrent connections in the context of sensory processing. Specifically, I will describe a neural network model in which the recurrent connections evolve according to concrete learning rules that optimize the information representation of the network. Interestingly, these networks tend to operate near a "critical" point in their dynamics, namely close to a phase of "hallucinations", in which non-trivial spontaneous patterns of activity evolve even without structured input. Various scenarios, such as attenuation of the external inputs or increased plasticity, can lead the network to cross the border into the hallucinatory phase. The theory will be illustrated through applications to a model of a visual hypercolumn, a model of tinnitus and a model of synaesthesia. References: Shriki O. and Yellin D., Optimal Information Representation and Criticality in an Adaptive Sensory Recurrent Neural Network. PLoS Computational Biology 12(2): e1004698. doi:10.1371/journal.pcbi.1004698, 2016 Shriki O., Sadeh Y. and Ward J., The Emergence of Synaesthesia in a Neuronal Network Model via Changes in Perceptual Sensitivity and Plasticity. PLoS Computational Biology 12(7): e1004959. doi:10.1371/journal.pcbi.1004959, 2016.

Throughout adult life, adult neuronal stem cells (NSCs) continuously generate neurons in discrete brain regions. I am interested in harnessing this natural regenerative process for repairing the diseased and aging brain. To effectively use this regenerative capacity in a clinical setting requires first an advanced understanding of NSCs, adult neurogenesis and neuronal regeneration during neurodegenerative diseases and aging. Study of these areas, however, is challenging, as it requires profiling rare continuous processes in the adult brain. To this end, I developed sNuc-Seq, a method for profiling RNA in complex tissues with single nuclei resolution by RNA-sequencing, and Div-Seq, for profiling RNA in individual dividing cells. I applied sNuc-Seq to study the adult hippocampus brain region, revealing new cell-type specific and spatial expression patterns. I then applied Div-Seq to track transcriptional dynamics of newborn neurons within the adult hippocampal neurogenic region and to identify and profile rare newborn GABAergic neurons in the adult spinal cord. I am currently developing follow-up technologies to sNuc-Seq and applying them to study the cross-talk between neurons, NSCs, glia and immune cells during neurodegenerative diseases and its role in inhibiting or promoting regeneration. I will continue to work towards advancing our ability to mitigate and even reverse neurodegenerative disease and age-related pathologies. Incorporating in my work techniques from molecular neuroscience, single cell genomics, genome engineering and computational biology.

Touch is vital for many human and animal behaviors, but our understanding of it lags other senses. We have deployed a suite of techniques to dissect mechanisms of touch perception in the mouse, from the biophysics of whisker bending to optogenetic manipulation of specific cortical circuits. I will present our recent work exploring how circuits of primary somatosensory cortex process sensory and motor signals to create a neural representation of tactile features during whisker-based object exploration.