Past events

: A central goal of sensory neuroscience is to understand the nature of the neural code in sensory cortex to the point where we could “read” the code – i.e., account for a subject’s perceptual capabilities using solely the relevant cortical signals, and “write” the code – i.e., substitute sensory stimuli with direct cortical stimulation that is perceptually equivalent.  Distributed representations and topography are two key properties of primate sensory cortex. For example, in primary visual cortex (V1), a localized stimulus activates millions of V1 neurons that are distributed over multiple mm2, and neurons that are similarly tuned are clustered together at the sub-mm scale and form several overlaid topographic maps. The distributed and topographic nature of V1’s representation raises the possibility that in some visual tasks, the neural code in V1 operates at the topographic scale rather than at the scale of single neurons. If this were the case, then the fundamental unit of information would be clusters of similarly tuned neurons (e.g., orientation columns), and to account for the subjects’ performance, it would be necessary and sufficient to consider the summed activity of the thousands of neurons within each cluster. A long-term goal of my lab is to test the topographic population code hypothesis.  In this presentation, I will describe our progress toward developing a bi-directional, read-write, optical-genetic toolbox for directly testing this hypothesis in behaving macaques.

:The non-linearity and variability in individual mood responses pose multiple analytic and experimental challenges. These challenges limit our understanding of mental health disorders with aberrant mood dynamics such as depression, and the development of more effective treatments. Computational approaches can help overcome some of these challenges by creating and modeling individual mood transitions. I will describe a study where closed-loop control approach was used to generate individual mood transitions and then a computational modeling approach was used to characterize the temporal effects on these mood changes. This study showed that early events exert a stronger influence on reported mood compared to recent events (a primacy weighting), in contrary to previous theoretical accounts which assumed that recent events are most influential on mood. This Primacy model accounted better for mood reports compared to a range of alternative temporal representations, in random, consistent, or dynamic reward environments, across different age groups, and in both healthy and depressed participants. Moreover, I will show how this temporal relation between early experiences and mood is mediated by specific neural signals. Interestingly, in repetitive reward environments or resting-state conditions, we found that mood reports consistently decline over time, stressing the importance of accounting for temporal effects in mood responses. These findings hold implications for the timing of events when addressing mood and behavior in experimental and in clinical settings.

The effect of the detailed connectivity of a neural circuit on its function and the resulting behavior of the organism, is a key question in many neural systems Here, I study the circuit for nociception in C elegans which is composed of the same neurons in the two sexes, that are wired differently I set out to elucidate how the topological design of a compact neuronal circuit affects its behavioral output, how genetic sex affects the connectivity and dynamics of a circuit, and how specific circuit components orchestrate together to establish the behavioral sexual dimorphism I used behavioral assays, optogenetics calcium and glutamate imaging, measurement of protein expression, artificial connectivity, molecular and genetic tools, and show that the nociceptive sensory neurons respond similarly in the two sexes, yet the animals display sexually dimorphic behaviors to the same aversive stimuli To uncover the role of the downstream network topology in shaping behavior, I measured the neuronal activity of a key interneuron, and found dimorphic responses to the stimulus as well as dimorphic intrinsic basal interneuron activity I then showed that neuron specific genetic sex plays a role in shaping connectivity and circuit dynamics, and proceed to an artificial subtle synaptic rewiring which flips behavior between sexes Interestingly, when presented with aversive cues, rewired males were compromised in finding mating partners, suggesting that network topologies that enable efficient avoidance of noxious cues have a reproductive " My results present a deconstruction of the design of a neural circuit that controls sexual behavior, and how to reprogram it

Working memory (WM), the process through which information is transiently maintained and manipulated over a brief period of time, is essential for most cognitive functions. However, the mechanisms underlying the generation and stability of WM neuronal representations at the population level remain elusive. To uncover these mechanisms, we trained head-fixed mice to perform  an olfactory working memory task and used optogenetics to delineate circuits causal for behavioral performance. We used mesoscopic and light bead  two photon imaging to record from up to 35,000 secondary motor cortical neurons simulataneously across multiple days and show differential stabilization of different task parameters with learning and practice of the task. We find that cortical working memory representations causal for task performance are highly volatile but only stabilize after multiple days of practice well after task learning. We hypothesize that representational drift soon after learning may allow for higher levels of flexibility for new task rules.  I will also review some of the new open-source tools developed for large-scale imaging of neural activity patterns in freely behaving animals.