Past events

Inhibitory neurons are critically important for the adaptation of neural circuits to sensory experience, but the molecular mechanisms by which experience controls the connectivity between different types of inhibitory neurons to regulate cortical plasticity are largely unknown. In this talk, I will present studies demonstrating that sensory experience induces in cortical vasoactive intestinal peptide (VIP)-expressing neurons a gene program that is markedly distinct from that induced in excitatory neurons and other subtypes of inhibitory neuron. I will show that is Igf1 one of several activity-regulated genes that are specific to VIP neurons, that IGF1 functions cell-autonomously in VIP neurons to increase inhibitory synaptic input onto these neurons and that VIP neuron-derived IGF1 regulates visual acuity in an experience-dependent manner, likely by promoting the inhibition of disinhibitory neurons and affecting inhibition onto cortical pyramidal neurons. I will discuss how our findings support a model by which experience-induced transcriptional networks regulate the synaptic connectivity of each type of neuron according to a circuit-wide homeostatic logic and I will propose that the analysis of the genomic mechanisms regulating these transcriptional networks will allow us to evaluate the extent to which cell-type-specific homeostatic mechanisms contribute to the function of cortical circuits.

In all sensory modalities the response of cortical cells to repeated stimulus is highly variable from trial to trial and it is often correlated in nearby cells. Spiking mechanisms are highly reliable, suggesting that correlated variability of cortical response results from fluctuations in shared synaptic inputs, as we showed in our previous studies. However, the origin of correlated synaptic activities in the cortex is under dispute. Whereas some studies suggest that correlated variability originates from thalamic inputs, others claim that it emerges in the cortex due to recurrent local activity. By combining optogenetic silencing and paired intracellular recordings in the barrel cortex of anesthetized mice as well as using paired LFP-intracellular recordings in awake mice, we revealed the origin of synchronized ongoing and sensory evoked cortical activities.

: I will review a set of biologically inspired NeuroImaging methods (i.e. methods that take into consideration the brain topography, neuronal adaptation and population receptive fields, brain functional connectivity and so on), that we developed and/or refined to shed light on maps and computations in the human brain. Starting from retinotopy, we used partial correlations resting-state functional connectivity analysis to show that the large-scale topographical biases in all 3 dimensions of retinotopy are preserved in individuals without any visual experience. I will discuss how this result challenges classical views of retinotopy as the key organizational principle for computations in the visual system, and further suggest plasticity principles beyond classical Hebbian learning. Next, we use virtual environments to show that key retinotopic regions (mainly in the dorsal visual stream) are recruited not only during vision-based navigation but even when early-blind and sighted-blindfolded learn to navigate these same environments using audition. I will then show how such approaches can be applied to study the whole-body somatosensory-motor system, and demonstrate that topographical gradients are far more widespread than previously known. These findings help to bridge gaps between animal and human studies, and have clinical relevance to improve and refine deep-brain-stimulation and imaging-based diagnostics. Finally, I will briefly present the development of crossmodal adaptation and multiphase spectral analysis to study topographical binding and crossmodal integration. Based on all of these results I will discuss the intriguing hypothesis that our brain is topographically organized for high-order cognitive functions as well, and discuss our plans to combine the aforementioned approaches with the use of the high-field imaging (7T) that is required to test it. I will conclude by summarizing the wide set of tools that enable us to investigate and gain novel insights into the nature of the Topographical Multisensory Human Brain mind. (Most relevant papers for the talk: Striem-Amit et al. Neuron 2012; Cerbral Cortex 2012; Curr Biol 2014; Brain 2015; Zeharia et al. PNAS 2012; J Neurosci 2015; Saadon-Grosman et al. PNAS 2015; Murray, et al. Trends Neurosci 2016 (cond. accepted); Maidenbaum et al. (in preparation)); Siuda-Krzywicka et al. Elife 2016; Sabbah et al. NeuroImage 2016 (accepted).

: Recurrent neural networks are an important class of models for explaining neural computations. Recently, there has been progress both in training these networks to perform various tasks, and in relating their activity to that recorded in the brain. Despite this progress, there are many fundamental gaps towards a theory of these networks. Neither the conditions for successful learning, nor the dynamics of trained networks are fully understood. I will present the rationale for using such networks for neuroscience research, and a detailed analysis of very simple tasks as an approach to build a theory of general trained recurrent neural networks.

I will describe the extent and timescale with which sensory cortices can be recruited and modified by inputs coming from various natural or artificial sensory input modalities or even when conveying high-level cognitive information. Our approach uses longitudinal studies in individuals with various degrees of visual deprivation, ranging from sighted-blindfolded to lifelong deprivation in patients with undeveloped retinas. I will describe the two main types of plasticity that we observed in the brain: (1) task-switching plasticity; and (2) task-selective sensory-independent organization. I will propose possible mechanisms that might give rise to such brain (re)-organization. In addition, I will show how we recently expanded our theoretical framework to include possible developmental mechanisms and implications for clinical rehabilitation including the development of a multisensory approach to restore vision (e.g. the multisensory bionic eye). By presenting an overview of our findings I will question classical theories of 'critical periods' by showing that "visual" regions do maintain their specific typical functionality and functional connectivity patterns even if "reawakened" in later periods in life including adulthood. Overall, through our approach and findings, new insights will emerge into the effects of learning and training on the (re)-organization principles of the human brain. See also www.BrainVisionRehab.com (Most relevant reviews: Reich et al., Curr Opin Neurol 2012; Hannagan et al. Trends Cogn Sci 2015; Heimler et al., Curr Opin Neurobiol 2015; Maidenbaum et al. Neurosci Biobehav Rev 2014; Murray, Matusz & Amedi Curr Biol 2015; Murray et al. Trends Neurosci 2016 (cond. accepted)).

Local brain circuits are believed to exhibit diverse connectivity patterns. It is not yet clear to what extent these patterns are hard-wired genetically, or whether they arise during development under the influence of local plasticity mechanisms. In this talk I will address how spike-timing dependent plasticity (STDP) may affect the global structure of a neural circuit. We recently developed a theoretical framework that allows to address the consequences of STDP in recurrent neural circuits of arbitrary connectivity. I will show that in addition to the local influence of STDP on the synapses that connect pairs of neurons reciprocally, STDP induces non-local interactions between synapses of different neurons. These "high-order" interactions, which were neglected in previous studies, can have a pivotal influence on the global structure of a neural network in steady state. As an example, I will consider in the talk the spontaneous formation of two simple structures: wide synfire chains, in which groups of neurons project to each other sequentially, and self connected assemblies - both of which are important models for generation of structured neural dynamics. I will show that with appropriate choice of the biophysical parameters, these ordered structures can emerge autonomously under the influence of STDP and heterosynaptic competition, without exposing the neural network to any structured external inputs during learning. If time permits, I will also present briefly another recent work, concerned with the coding of an animal's position by grid cells in the entorhinal cortex.

Proper performance of voluntary movements requires the integration of both spatial and temporal information about the ensuing movements. The timing of actions is often considered to be dictated by cerebellar output that is relayed to the motor cortex via the motor thalamus. We investigated the mechanisms by which the cerebellar-thalamo-cortical (CTC) system controls temporal properties of motor cortical activity. We found that in primates the CTC pathway efficiently recruits motor cortical neurons in primary motor and premotor areas. Cortical responses to CTC activation were dominated by prolonged inhibition mediated by a feedforward mechanism. We further found that cortical cells that integrated CTC input fired transiently and synchronously at movement onset, when the timing of action is dictated. Moreover, when preventing the flow of information in the pathway the phasic firing at movement onset was reduced, but the preferred direction of the cells remained unchanged. These changes in neural firing were correlated with altered motor behavior: the monkeys were able to perform the task but with increased reaction and movement times. These results suggest that the CTC system affects cortical firing by changing the excitation-inhibition balance at movement onset in an extensive network of TC-activated motor cortical neurons. In this manner, the temporal pattern of neural firing is shaped, and firing across groups of neurons is synchronized to generate transiently enhanced firing.