ELSC Seminar Series

This talk will focus on the importance of using natural behaviors in neuroscience research – the “Natural Neuroscience” approach. I will illustrate this point by describing studies of neural codes for spatial behaviors and social behaviors, in flying bats – using wireless neurophysiology methods that we developed – and will highlight new neuronal representations that we discovered in animals navigating through 3D spaces, or in very large-scale environments, or engaged in social interactions. In particular, I will discuss: (1) A multi-scale neural code for very large environments, which we discovered in bats flying in a 200-meter long tunnel. This new type of neural code is fundamentally different from spatial codes reported in small environments – and we show theoretically that it is superior for representing very large spaces. (2) Rapid modulation of position × distance coding in the hippocampus during collision-avoidance behavior between two flying bats. This result provides a dramatic illustration of the extreme dynamism of the neural code. (3) Local-but-not-global order in 3D grid cells – a surprising experimental finding, which can be explained by a simple physics-inspired model, which successfully describes both 3D and 2D grids. These results strongly argue against many of the classical, geometrically-based models of grid cells. (4) I will also briefly describe new results on the social representation of other individuals in the hippocampus, in a highly social multi-animal setting. The lecture will propose that neuroscience experiments – in bats, rodents, monkeys or humans – should be conducted under evermore naturalistic conditions.

The dream of a systems neuroscientist is to be able to unravel neural mechanisms that give rise to behavior. It is increasingly appreciated that behavior involves the concerted distributed activity of multiple brain regions so the focus on single or few brain areas might hinder our understanding. There have been quite a few technological advancements in this domain. Functional ultrasound imaging (fUSi) is an emerging technique that allows us to measure neural activity from medial frontal regions down to subcortical structures up to a depth of 20 mm. It is a method for imaging transient changes in cerebral blood volume (CBV), which are proportional to neural activity changes. It has excellent spatial resolution (~100 μm X 100 μm X 400 μm); its temporal resolution can go down to 100 milliseconds. In this talk, I will present its use in two model systems: marmoset monkeys and rats. In marmoset monkeys, we used it to delineate a social – vocal network involved in vocal communication while in rats, we used it to gain insights into brain wide networks involved in evidence accumulation based decision making. fUSi has the potential to provide an unprecedented access to brain wide dynamics in freely moving animals performing complex behavioral tasks.

Our ability to understand ongoing events depends critically on general knowledge about how different kinds of situations work (schemas), and also on recollection of specific instances of these situations that we have previously experienced (episodic memory). The consensus around this general view masks deep questions about how these two memory systems interact to support event understanding: How do we build our library of schemas? and how exactly do we use episodic memory in the service of event understanding? Given rich, continuous inputs, when do we store and retrieve episodic memory “snapshots”, and how are they organized so as to ensure that we can retrieve the right snapshots at the right time? I will develop predictions about how these processes work using memory augmented neural networks (i.e., neural networks that learn how to use episodic memory in the service of task performance), and I will present results from relevant fMRI and behavioral studies.

Recent breakthroughs in neurobiology indicate that time is ripe to understand the cellular-level mechanisms of conscious experience. Accordingly, we have recently proposed that conscious processing depends on the integration between top-down and bottom-up information streams and that there exists a specific cellular mechanism that gates this integration. I will first describe this cellular mechanism and demonstrate how it controls signal propagation within the thalamocortical system. Then I will show how this cellular-level mechanism provides a natural explanation for why conscious experience is modulated by top-down processing. Besides shining new light on the neural basis of consciousness, this perspective unravels the mechanisms of internally generated perception, such as dreams, imagery, and hallucinations.

In this lecture, I will present our recent progress on three aspects of population responses in the primary visual cortex: encoding local stimulus attributes, electrical microstimulation and higher visual function. In the first part I will focus on population encoding and reconstruction of contour shapes in V1 and the comparison between monkey and mouse visual responses. In the second part of the talk I will present the effects of microstimulation on neural population in V1 and the relation to evoked saccades. In the final part of the talk I will discuss top-down influences in V1 and their relation to higher visual functions.

Studying the pathophysiology of late stage Parkinson’s disease (PD) – after the patients have experienced severe neuronal loss – has helped develop various symptomatic treatments for PD (e.g., deep brain stimulation). However, it has been of limited use in developing neuroprotective disease-modifying therapies (DMTs), because DMTs require interventions at much earlier stages of PD when vulnerable neurons are still intact. Because PD patients exhibit various non-motor prodromal symptoms (ie, symptoms that predate diagnosis), understanding the pathophysiology underlying these symptom could lead to earlier diagnosis and intervention. In my talk, I will present a recently elucidated example of how PD pathologies alter the channel biophysics of intact vagal motoneurons (known to be selectively vulnerable in PD) to drive dysautonomia that is reminiscent of prodromal PD. I will discuss how elucidating the pathophysiology of prodromal symptoms can lead to earlier diagnosis through the development of physiological biomarkers for PD.

Maintaining average activity level within a set-point range constitutes a fundamental property of central neural circuits. Accumulated evidence suggests that firing rate distributions and their means represent physiological variables regulated by homeostatic systems during sleep-wake cycle in central neural circuits. While intracellular Ca2+ has long been hypothesized as a feedback control signal, the source of Ca2+ and the molecular machinery enabling network-wide homeostatic responses remain largely unknown. I will present our hypothesis and framework on identifying homeostatic regulators in neural circuits. Next, I will show our new results on the role of mitochondria in the regulation of activity set-points and feedback responses. Finally, I will provide an evidence on state-dependent dysregulation of activity set-points at the presymptomatic disease stage in familial Alzheimer’s models.

Long-range projections link distant circuits in the brain, allowing efficient transfer of information between regions and synchronization of distributed patterns of neural activity. Understanding the functional roles of defined neuronal projection pathways requires temporally precise manipulation of their activity, and optogenetic tools appear to be an obvious choice for such experiments. However, we and others have previously shown that commonly-used inhibitory optogenetic tools have low efficacy and off-target effects when applied to presynaptic terminals. In my talk, I will present a new solution to this problem: a targeting-enhanced mosquito homologue of the vertebrate encephalopsin (eOPN3), which upon activation can effectively suppress synaptic transmission through the Gi/o signaling pathway. Brief illumination of presynaptic terminals expressing eOPN3 triggers a lasting suppression of synaptic output that recovers spontaneously within minutes in vitro and in vivo. The efficacy of eOPN3 in suppressing presynaptic release opens new avenues for functional interrogation of long-range neuronal circuits in vivo.

While various forms of cells have been found in relation to the hippocampus cognitive map and navigation system, how these cells are formed and what is read from them is still a mystery. In the current lecture I will talk about several projects which tackle these issues. First, I will show how the formation of border cells in the coginitive map is related to a coordinate transformation, second I will discuss the interaction between the reward system (VTA) and the hippocampus. Finally I will describe a project using place cells as a proxy for associative memory for assessing deficits in Alzheimer’s disease.

Bats are extreme aviators and amazing navigators. Many bat species nightly commute dozens of kilometres in search of food, and some bat species annually migrate over thousands of kilometres. Studying bats in their natural environment has always been extremely challenging because of their small size (mostly <50 gr) and agile nature. We have recently developed novel miniature technology allowing us to GPS-tag small bats, thus opening a new window to document their behaviour in the wild. We have used this technology to track fruit-bats pups over 5 months from birth to adulthood. Following the bats’ full movement history allowed us to show that they use novel short-cuts which are typical for cognitive-map based navigation. In a second study, we examined how nectar-feeding bats make foraging decisions under competition. We show that by relying on a simple reinforcement learning strategy, the bats can divide the resource between them without aggression or communication. Together, these results demonstrate the power of the large scale natural approach for studying animal behavior.

Rapidly changing inputs such as visual scenes and auditory landscapes are transmitted over several synaptic interfaces and perceived with little loss of detail, but individual neurons are typically “noisy” and cortico-cortical connections are typically “weak”. To understand how information embodied in spike train is transmitted in a lossless manner, we focus on a single synaptic interface: between pyramidal cells and putative interneurons. Using arbitrary white noise patterns injected intra-cortically as photocurrents to freely-moving mice, we find that directly-activated cells exhibit precision of several milliseconds, but post-synaptic, indirectly-activated cells exhibit higher precision. Considering multiple identical messages, the reliability of directly-activated cells peaks at a timescale of dozens of milliseconds, whereas indirectly-activated cells exhibit an order-of-magnitude faster timescale. Using data-driven modelling, we find that error correction is consistent with non-linear amplification of coincident spikes.

In this seminar, I will present new methods in magnetic resonance spectroscopy (MRS) we’ve been working on in the lab. The talk will be divided into two parts. In the first, I will talk about neurochemical changes we observe in glutamate and GABA during various paradigms, including simple motors tasks and reinforcement learning. In the second part, I’ll present a new approach to MRS that focuses on measuring the relaxation times (T1, T2) of metabolites, which reflect changes to specific cellular microenvironments. I will explain why these can be exciting markers for studying several in-vivo pathologies, and also present some preliminary data from a cohort of mild cognitive impairment (MCI) patients, showing changes that correlate to cognitive decline.

Animals control motor actions at multiple timescales. We use larval zebrafish and advanced optical microscopy to understand the underlying neural mechanisms. First, we examined the mechanisms of short-term motor learning by using whole-brain neural activity imaging. We found that the 5-HT system integrates the sensory outcome of actions and determines future motor patterns. Second, we established a method for recording spiking activity and membrane potential from a population of neurons during behavior. We identified putative motor command signals and internal copy signals that encode millisecond-scale details of the swimming dynamics. These results demonstrate that zebrafish provide a holistic and mechanistic understanding of the neural basis of motor control in vertebrate brains.