Past events

The dynamics of learning in natural and artificial environments is a problem of great interest to both neuroscientists and artificial intelligence experts. However, standard analyses of animal training data either treat behavior as fixed, or track only coarse performance statistics (e.g., accuracy and bias), providing limited insight into the dynamic evolution of behavioral strategies over the course of learning. To overcome these limitations, we propose a dynamic psychophysical model that efficiently tracks trial-to-trial changes in behavior over the course of training. In this talk, I will describe recent work based on a dynamic logistic regression model that captures the time-varying dependencies of behavior on stimuli and other task covariates. We applied our method to psychophysical data from both human subjects and rats learning a sensory discrimination task. We successfully tracked the dynamics of psychophysical weights during training, capturing day-to-day and trial-to-trial fluctuations in behavioral strategy. We leverage the model's flexibility model to investigate why rats frequently make mistakes on easy trials, demonstrating that so-called "lapses" often arise from sub-optimal weighting of task covariates. Finally, I will describe recent work on adaptive optimal training, which combines ideas from reinforcement learning and adaptive experimental design to formulate methods for inferring animal learning rules from behavior, and using these rules to speed up animal training.

Perception is an active process, requiring the integration of both proprioceptive and exteroceptive information. In the rat’s vibrissal system, a classical model for the study of active sensing, previous works explored the relative contribution of the two information streams at the peripheral, thalamic and cortical levels. However, this issue was never addressed in the brainstem, and was only indirectly inferred from its thalamic projections. The current work addressed this gap in our knowledge by performing the first comparative study of the encoding of whisking and touch signals in the oralis, interpolaris and paratrigeminal nuclei. We also examined possible mechanisms for TIPs (Touch Induced Pumps) generation, a touch reflexive behavior mediated by the brainstem. By combining induction of artificial TIPs in anesthetized animals and computational models, we showed that passive retraction of the whisker pad is the most plausible mechanism for TIPs generation. Overall, our findings bridge a critical gap in our knowledge of the vibrissal system, providing the first characterization of responses to active touch in the trigeminal brainstem, the first evidence that the paratrigeminal nucleus is involved in the processing of vibrissal information and a novel mechanism for TIPs generation.

A fundamental problem in neuroscience is to elucidate the relationship between neuronal network anatomy and its functional dynamics. The nematode worm C. elegans is an ideal model to study these problems. Its nervous system has just 302 neurons and all synaptic connections between them have been fully mapped. Using a large-scale Ca2+-imaging approach, we previously discovered nervous system wide neuronal population dynamics in the worm that encode action commands. These dynamics feature various network attractor states during which neurons coordinate and synchronize their activities, thereby providing functional interaction maps. In this talk, I will discuss unpublished work where we combine graph-theoretical and experimental approaches to understand which anatomical features in network connectivity relate to these functional dynamics and interactions between neurons.

Denise Cai: Linking memories across time The compilation of memories, collected and aggregated across a lifetime defines our human experience. My lab is interested in dissecting how memories are stored, updated, integrated and retrieved across a lifetime. Recent studies suggest that a shared neural ensemble may link distinct memories encoded close in time. Using in vivo calcium imaging (with open-source Miniscopes in freely behaving mice), TetTag transgenic system, chemogenetics, electrophysiology and novel behavioral designs, we tested how hippocampal networks temporally link memories. Multiple convergent findings suggest that contextual memories encoded close in time are linked by directing storage into overlapping hippocampal ensembles, such that the recall of one memory can trigger the recall of another temporally-related memory. Alteration of this process (e.g. during aging, PTSD, etc) affect the temporal structure of memories, thus impairing efficient recall of related information. Tristan Shuman: Breakdown of spatial coding and interneuron synchronization in epileptic mice Temporal lobe epilepsy causes severe cognitive deficits yet the circuit mechanisms that alter cognition remain unknown. We hypothesized that the death and reorganization of inhibitory connections during epileptogenesis may disrupt synchrony of hippocampal inhibition. To test this, we simultaneously recorded from CA1 and dentate gyrus (DG) in pilocarpine-treated epileptic mice with silicon probes during head-fixed virtual navigation. We found desynchronized interneuron firing between CA1 and DG in epileptic mice. Since hippocampal interneurons control information processing, we tested whether CA1 spatial coding was altered in this desynchronized circuit using a novel wire-free Miniscope. We found that CA1 place cells in epileptic mice were unstable and completely remapped across a week. This place cell instability emerged ~6 weeks after status epilepticus, well after the onset of chronic spontaneous seizures and interneuron death. Finally, our CA1 network model showed that desynchronized inputs can impair information content and stability of CA1 place cells. Together, these results demonstrate that temporally precise intra-hippocampal communication is critical for spatial processing and hippocampal desynchronization contributes to spatial coding deficits in epileptic mice.

Sensory experience can change the structure and function of neurons in the brain over a wide range of timescales, from milliseconds-second modulation of synaptic activity to long-lasting alterations of genetic programs, lasting minutes to hours. While conversion of synaptic activity into long-lasting nuclear signaling is vital for learning and neuronal development, we still lack a clear understanding of its basic operating principles. To address this, I will describe recent advancements using two-photon fluorescence lifetime imaging and new biosensors which allowed us to image the activity of CREB, an activity-dependent transcription factor important for synaptic plasticity, at single cell resolution in awake mice. Simultaneous imaging of CREB and Ca2+ in the visual cortex permitted us to explore how sensory deprivation (dark-rearing) can modulate the sensitivity and duration of CREB activity to sensory-evoked Ca2+ elevations. Future work using this approach will allow us to unravel synapse to nucleus signaling dynamics underlying experience-dependent plasticity in the brain.

Integrating information from different sensory systems is essential for faithful representation of the external world. Different senses represent different aspects of the surrounding world. They operate at different time scales, and integrate information presented at different distances from the body. For example, tactile sensation enables sensing very proximal objects, whereas the auditory system allows us to sense very distant objects as well. In many instances, however, we simultaneously sense the same object using two or more modalities. This occurs, for example, when we use a hammer. In this case, we watch our movements and get tactile and auditory feedbacks for fine-tuning and precision. In this work, we are interested in revealing how the primary sensory cortices of both the auditory and somatosensory vibrissa systems integrate information they receive from a given source, in this case when the animal touches an object by moving its whiskers. We ask if such touch signals can produce audible signals that can be perceived by the auditory system. Towards this aim, we severed the infraorbital nerve (ION) of mice to eliminate somatosensory sensation going from the whiskers and the pad to the cortex. We then head fixed the mice and presented a piece of aluminum foil to the whiskers. Our preliminary results show that when the mouse whisked against the object it produced audible sound as we examined by using highly sensitive ultrasonic microphones. This sound differs from the environment both in amplitude and frequency range. Many neurons in the primary auditory cortex responded to the sound generated by the contact of the whiskers with the object. We propose that mice can use the two sensory systems in a complimentary manner in order to produce comprehensive representation of their proximal environment, perhaps similar to the way cane is used by visually impaired people. To demonstrate if the animal can use this auditory sensation, we will train head fixed and ION severed mice to respond to objects that produce sound by the whiskers’ touch. Showing that the auditory sensation can be relevant for the animal in identifying objects.

Internal states, including affective or homeostatic states, are important behavioral motivators. The amygdala is a key regulator of motivated behaviors, yet how distinct internal states are represented in amygdala circuits is unknown. Here, by longitudinally imaging neural calcium dynamics across different environments in freely moving mice, we identify changes in the activity levels of two major, non-overlapping populations of principal neurons in the basal amygdala (BA) that predict switches between exploratory and non-exploratory (defensive, anxiety-like) states. Moreover, the amygdala broadcasts state information via several output pathways to larger brain networks, and sensory responses in BA occur independently of behavioral state encoding. Thus, the brain processes external stimuli and internal states orthogonally, which may facilitate rapid and flexible selection of appropriate, state-dependent behavioral responses.