Optogenetics seminars

Sleep is an active state critical for processing emotional memories encoded during waking in both humans and animals. There is a remarkable overlap between the brain structures and circuits active during sleep, particularly rapid eye-movement (REM) sleep, and the those encoding emotions. Accordingly, disruptions in sleep quality or quantity, including REM sleep, are often associated with, and precede the onset of, nearly all affective psychiatric and mood disorders. In this context, a major biomedical challenge is to better understand the underlying mechanisms of the relationship between (REM) sleep and emotion encoding to improve treatments for mental health. This lecture will summarize our investigation of the cellular and circuit mechanisms underlying sleep architecture, sleep oscillations, and local brain dynamics across sleep-wake states using electrophysiological recordings combined with single-cell calcium imaging or optogenetics. The presentation will detail the discovery of a 'somato-dendritic decoupling'in prefrontal cortex pyramidal neurons underlying REM sleep-dependent stabilization of optimal emotional memory traces. This decoupling reflects a tonic inhibition at the somas of pyramidal cells, occurring simultaneously with a selective disinhibition of their dendritic arbors selectively during REM sleep. Recent findings on REM sleep-dependent subcortical inputs and neuromodulation of this decoupling will be discussed in the context of synaptic plasticity and the optimization of emotional responses in the maintenance of mental health.

Neural dynamics represent the hard-to-interpret substrate of circuit computations. Advances in large-scale recordings have highlighted the sheer spatiotemporal complexity of circuit dynamics within and across circuits, portraying in detail the difficulty of interpreting such dynamics and relating it to computation. Indeed, even in extremely simplified experimental conditions, one observes high-dimensional temporal dynamics in the relevant circuits. This complexity can be potentially addressed by the notion that not all changes in population activity have equal meaning, i.e., a small change in the evolution of activity along a particular dimension may have a bigger effect on a given computation than a large change in another. We term such conditions dimension-specific computation. Considering motor preparatory activity in a delayed response task we utilized neural recordings performed simultaneously with optogenetic perturbations to probe circuit dynamics. First, we revealed a remarkable robustness in the detailed evolution of certain dimensions of the population activity, beyond what was thought to be the case experimentally and theoretically. Second, the robust dimension in activity space carries nearly all of the decodable behavioral information whereas other non-robust dimensions contained nearly no decodable information, as if the circuit was setup to make informative dimensions stiff, i.e., resistive to perturbations, leaving uninformative dimensions sloppy, i.e., sensitive to perturbations. Third, we show that this robustness can be achieved by a modular organization of circuitry, whereby modules whose dynamics normally evolve independently can correct each other’s dynamics when an individual module is perturbed, a common design feature in robust systems engineering. Finally, we will recent work extending this framework to understanding the neural dynamics underlying preparation of speech.

Fear learning induces synaptic potentiation between engram neurons in the rat lateral amygdala. This study by Marios Abatis et al. demonstrates how fear conditioning strengthens synaptic connections between engram cells in the lateral amygdala, revealed through optogenetic identification of neuronal ensembles and electrophysiological measurements. The work provides crucial insights into memory formation mechanisms at the synaptic level, with implications for understanding anxiety disorders and developing targeted interventions. Presented by Dr. Kenneth Hayworth, this journal club will explore the paper's methodology linking engram cell reactivation with synaptic plasticity measurements, and discuss implications for memory decoding research.

Recent advances in techniques for monitoring and perturbing neural populations have greatly enhanced our ability to study circuits in the brain. In particular, two-photon holographic optogenetics now enables precise photostimulation of experimenter-specified groups of individual neurons, while simultaneous two-photon calcium imaging enables the measurement of ongoing and induced activity across the neural population. Despite the enormous space of potential photostimulation patterns and the time-consuming nature of photostimulation experiments, very little algorithmic work has been done to determine the most effective photostimulation patterns for identifying the neural population dynamics. Here, I will discuss ongoing development of active learning techniques to efficiently select which neurons to stimulate such that the resulting neural responses will best inform a dynamical model of the neural population activity. Presented in the van Vreeswijk Theoretical Neuroscience Seminar series (formerly WWTNS) on 2025-02-05. Recording duration: 00:42:29.

I’m interested in structure-function relationships in neural circuits and behavior, with a focus on motor and somatosensory areas of the mouse’s cortex involved in controlling forelimb movements. In one line of investigation, we take a bottom-up, cellularly oriented approach and use optogenetics, electrophysiology, and related slice-based methods to dissect cell-type-specific circuits of corticospinal and other neurons in forelimb motor cortex. In another, we take a top-down ethologically oriented approach and analyze the kinematics and cortical correlates of “oromanual” dexterity as mice handle food. I'll discuss recent progress on both fronts.

This webinar will showcase new approaches for electrophysiological recordings using our silicon neural probes and surface arrays combined with diverse optical methods such as wide-field or 2-photon imaging, fiber photometry, and optogenetic perturbations in awake, behaving mice. Multi-modal recording of single units and local field potentials across cortex, hippocampus and thalamus alongside calcium activity via GCaMP6F in cortical neurons in triple-transgenic animals or in hippocampal astrocytes via viral transduction are brought to bear to reveal hitherto inaccessible and under-appreciated aspects of coordinated dynamics in the brain.

How do cortical circuits acquire new dynamics that drive learned movements? This webinar will focus on mouse premotor cortex in relation to learned lick-timing and explore high-density electrophysiology using our silicon neural probes alongside region and cell-type-specific acute genetic manipulations of proteins required for synaptic plasticity.

Inhibition has long been thought to stabilize the activity of cortical networks at low rates, and to shape significantly their response to sensory inputs. In this talk, I will describe three recent collaborative projects that shed light on these issues. (1) I will show how optogenetic excitation of inhibition neurons is consistent with cortex being inhibition stabilized even in the absence of sensory inputs, and how this data can constrain the coupling strengths of E-I cortical network models. (2) Recent analysis of the effects of optogenetic excitation of pyramidal cells in V1 of mice and monkeys shows that in some cases this optogenetic input reshuffles the firing rates of neurons of the network, leaving the distribution of rates unaffected. I will show how this surprising effect can be reproduced in sufficiently strongly coupled E-I networks. (3) Another puzzle has been to understand the respective roles of different inhibitory subtypes in network stabilization. Recent data reveal a novel, state dependent, paradoxical effect of weakening AMPAR mediated synaptic currents onto SST cells. Mathematical analysis of a network model with multiple inhibitory cell types shows that this effect tells us in which conditions SST cells are required for network stabilization.

Recent studies identified memory engram neurons, a neuronal population that is recruited by initial learning and is reactivated during memory recall. Memory engram neurons are connected to one another through memory engram synapses in a distributed network of brain areas. Our central hypothesis is that an associative memory is encoded and consolidated by selective strengthening of engram synapses. We are testing this hypothesis, using a combination of engram cell labeling, optogenetic/chemogenetic, electrophysiological, and virus tracing approaches in rodent models of contextual fear conditioning. In this talk, I will discuss our findings on how synaptic plasticity in memory engram synapses contributes to the acquisition and consolidation of contextual fear memory in a distributed network of the amygdala, hippocampus, and neocortex.

To form a coherent perception of the world around us, we are constantly processing and integrating sensory information from multiple modalities. In fact, when auditory and visual stimuli occur within ~100 ms of each other, individuals tend to perceive the stimuli as a single event, even though they occurred separately. In recent years, our lab, and others, have developed rat models of audiovisual temporal perception using behavioural tasks such as temporal order judgments (TOJs) and synchrony judgments (SJs). While these rodent models demonstrate metrics that are consistent with humans (e.g., perceived simultaneity, temporal acuity), we have sought to confirm whether rodents demonstrate the hallmarks of audiovisual temporal perception, such as predictable shifts in their perception based on experience and sensitivity to alterations in neurochemistry. Ultimately, our findings indicate that rats serve as an excellent model to study the neural mechanisms underlying audiovisual temporal perception, which to date remains relativity unknown. Using our validated translational audiovisual behavioural tasks, in combination with optogenetics, neuropharmacology and in vivo electrophysiology, we aim to uncover the mechanisms by which inhibitory neurotransmission and top-down circuits finely control ones’ perception. This research will significantly advance our understanding of the neuronal circuitry underlying audiovisual temporal perception, and will be the first to establish the role of interneurons in regulating the synchronized neural activity that is thought to contribute to the precise binding of audiovisual stimuli.

Zoe has developed an open-source tool PhaSER, which allows her to perform real-time oscillatory phase estimation and apply optogenetic manipulations at precise phases of hippocampal theta during high-density electrophysiological recordings in head-fixed mice while they navigate a virtual environment. The precise timing of single-unit spiking relative to network-wide oscillations (i.e., phase locking) has long been thought to maintain excitatory-inhibitory homeostasis and coordinate cognitive processes, but due to intense experimental demands, the causal influence of this phenomenon has never been determined. Thus, we developed PhaSER (Phase-locked Stimulation to Endogenous Rhythms), a tool which allows the user to explore the temporal relationship between single-unit spiking and ongoing oscillatory activity.

Sensory neurons of the vagus nerve monitor distention and stretch in the gastrointestinal tract. We used genetically guided anatomical tracing, optogenetics and electrophysiology to identify and characterize two vagal sensory neuronal subtypes expressing Prox2 and Runx3. We show that these neuronal subtypes innervate the esophagus where they display regionalized innervation patterns. Electrophysiological analyses showed that they are both low threshold mechanoreceptors but possess different adaptation properties. Lastly, genetic ablation of Prox2 and Runx3 neurons demonstrated their essential roles for esophageal peristalsis and swallowing in freely behaving animals. Our work reveals the identity and function of the vagal neurons that provide mechanosensory feedback from the esophagus to the brain and could lead to better understanding and treatment of esophageal motility disorders.

A key issue in understanding circuit operations is the extent to which neuronal spiking reflects local computation or responses to upstream inputs. Several studies have lesioned or silenced inputs to area CA1 of the hippocampus - either area CA3 or the entorhinal cortex and examined the effect on CA1 pyramidal cells. However, the types of the reported physiological impairments vary widely, primarily because simultaneous manipulations of these redundant inputs have never been performed. In this study, I combined optogenetic silencing of unilateral and bilateral mEC, of the local CA1 region, and performed bilateral pharmacogenetic silencing of CA3. I combined this with high spatial resolution extracellular recordings along the CA1-dentate axis. Silencing the medial entorhinal largely abolished extracellular theta and gamma currents in CA1, without affecting firing rates. In contrast, CA3 and local CA1 silencing strongly decreased firing of CA1 neurons without affecting theta currents. Each perturbation reconfigured the CA1 spatial map. Yet, the ability of the CA1 circuit to support place field activity persisted, maintaining the same fraction of spatially tuned place fields. In contrast to these results, unilateral mEC manipulations that were ineffective in impacting place cells during awake behavior were found to alter sharp-wave ripple sequences activated during sleep. Thus, intrinsic excitatory-inhibitory circuits within CA1 can generate neuronal assemblies in the absence of external inputs, although external synaptic inputs are critical to reconfigure (remap) neuronal assemblies in a brain-state dependent manner.

Nuo Li (Baylor College of Medicine, USA) shares novel insights into coordinated interhemispheric large-scale neural network activity underpinning short-term memory in mice. Relevant techniques covered include: simultaneous multi-regional recordings using multiple 64-channel H probes during head-fixed behavior in mice. simultaneous optogenetics and population recording. analysis of population recordings to infer interactions between brain regions. Reference: Chen G, Kang B, Lindsey J, Druckmann S, Li N, (2021). Modularity and robustness of frontal cortex networks. Cell, 184(14):3717-3730.

How does our brain rapidly determine if something is good or bad? How do we know our place within a social group? How do we know how to behave appropriately in dynamic environments with ever-changing conditions? The Tye Lab is interested in understanding how neural circuits important for driving positive and negative motivational valence (seeking pleasure or avoiding punishment) are anatomically, genetically and functionally arranged. We study the neural mechanisms that underlie a wide range of behaviors ranging from learned to innate, including social, feeding, reward-seeking and anxiety-related behaviors. We have also become interested in “social homeostasis” -- how our brains establish a preferred set-point for social contact, and how this maintains stability within a social group. How are these circuits interconnected with one another, and how are competing mechanisms orchestrated on a neural population level? We employ optogenetic, electrophysiological, electrochemical, pharmacological and imaging approaches to probe these circuits during behavior.

In understanding circuit operations, a key issue is the extent to which neuronal spiking reflects local computation or responses to upstream inputs. Because pyramidal cells in CA1 do not have local recurrent projections, it is currently assumed that firing in CA1 is inherited from its inputs – thus, entorhinal inputs provide communication with the rest of the neocortex and the outside world, whereas CA3 inputs provide internal and past memory representations. Several studies have attempted to prove this hypothesis, by lesioning or silencing either area CA3 or the entorhinal cortex and examining the effect of firing on CA1 pyramidal cells. Despite the intense and careful work in this research area, the magnitudes and types of the reported physiological impairments vary widely across experiments. At least part of the existing variability and conflicts is due to the different behavioral paradigms, designs and evaluation methods used by different investigators. Simultaneous manipulations in the same animal or even separate manipulations of the different inputs to the hippocampal circuits in the same experiment are rare. To address these issues, I used optogenetic silencing of unilateral and bilateral mEC, of the local CA1 region, and performed bilateral pharmacogenetic silencing of the entire CA3 region. I combined this with high spatial resolution recording of local field potentials (LFP) in the CA1-dentate axis and simultaneously collected firing pattern data from thousands of single neurons. Each experimental animal had up to two of these manipulations being performed simultaneously. Silencing the medial entorhinal (mEC) largely abolished extracellular theta and gamma currents in CA1, without affecting firing rates. In contrast, CA3 and local CA1 silencing strongly decreased firing of CA1 neurons without affecting theta currents. Each perturbation reconfigured the CA1 spatial map. Yet, the ability of the CA1 circuit to support place field activity persisted, maintaining the same fraction of spatially tuned place fields, and reliable assembly expression as in the intact mouse. Thus, the CA1 network can maintain autonomous computation to support coordinated place cell assemblies without reliance on its inputs, yet these inputs can effectively reconfigure and assist in maintaining stability of the CA1 map.

Brendan Ito (Cornell University, USA) and Teja Bollu (Salk Institute, USA) share unique insights into rapid online motor corrections during mouse licking, analogous to primate goal-oriented reaching. Techniques covered include large-scale single unit recording during behaviour with optogenetics, and a deep-learning-based neural network to resolve 3D tongue kinematics during licking.

Coping with threatening situations requires both identifying stimuli predicting danger and selecting adaptive behavioral responses in order to survive. The dorso medial prefrontal cortex (dmPFC) is a critical structure involved in the regulation of threat-related behaviour, yet it is still largely unclear how threat-predicting stimuli and defensive behaviours are associated within prefrontal networks in order to successfully drive adaptive responses. Over the past years, we used a combination we used a combination of extracellular recordings, neuronal decoding approaches, and state of the art optogenetic manipulations to identify key neuronal elements and mechanisms controlling defensive fear responses. I will present an overview of our recent work ranging from analyses of dedicated neuronal types and oscillatory and synchronization mechanisms to artificial intelligence approaches used to decode the activity or large population of neurons. Ultimately these analyses allowed the identification of high dimensional representations of defensive behavior unfolding within prefrontal networks.

Optogenetics is a powerful tool that allows experimentalists to perturb neural circuits. What can we learn about a network from observing its response to perturbations? I will first describe the results of optogenetic activation of inhibitory neurons in mice cortex, and show that the results are consistent with inhibition stabilization. I will then move to experiments in which excitatory neurons are activated optogenetically, with or without visual inputs, in mice and monkeys. In some conditions, these experiments show a surprising result that the distribution of firing rates is not significantly changed by stimulation, even though firing rates of individual neurons are strongly modified. I will show in which conditions a network model of excitatory and inhibitory neurons can reproduce this feature.

Recent advances in optogenetics allow for stimulation of neurons with sub-millisecond spike jitter and single neuron selectivity. Already this precision has revealed new levels of cortical sensitivity: stimulating tens of neurons can yield changes in the mean firing rate of thousands of similarly tuned neurons. This extreme sensitivity suggests that cortical dynamics are near criticality. Criticality is often studied in neural systems as a non-equilibrium thermodynamic process in which scale-free patterns of activity, called avalanches, emerge between distinct states of spontaneous activity. While criticality is well studied, it is still unclear what these distinct states of spontaneous activity are and what responses we expect from stimulation of this activity. By answering these questions, optogenetic stimulation will become a new avenue for approaching criticality and understanding cortical dynamics. Here, for the first time, we study the effects of optogenetic-like stimulation on a model near criticality. We study a model of Inhibitory/Excitatory (I/E) Leaky Integrate and Fire (LIF) spiking neurons which display a region of high sensitivity as seen in experiments. We find that this region of sensitivity is, indeed, near criticality. We derive the Dynamic Mean Field Theory of this model and find that the distinct states of activity are asynchrony and synchrony. We use our theory to characterize response to various types and strengths of optogenetic stimulation. Our model and theory predict that asynchronous, near-critical dynamics can have two qualitatively different responses to stimulation: one characterized by high sensitivity, discrete event responses, and high trial-to-trial variability, and another characterized by low sensitivity, continuous responses with characteristic frequencies, and low trial-to-trial variability. While both response types may be considered near-critical in model space, networks which are closest to criticality show a hybrid of these response effects.