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Thiberge, S. Y.

Publications and source records attributed to Thiberge, S. Y..

11 recordsLinked to original sources

Single-Cell Perturbations Reveal Selective Modulation of Causal Connectivity During Decision-Making

How does cortical connectivity support decision-making? Behavioral tasks often involve multiple sequential phases that implement different computations. For perceptual decision-making during navigation these can include evidence accumulation, decision commitment, and motor program read out. How are these different phases implemented in circuits with fixed anatomical synaptic connectivity? One potential contribution is that the connectivity of neurons is modulated in the different phases, but this has never been tested. Here we used an all-optical method to probe the causal connectivity of excitatory neurons in layer 2/3 of mouse retrosplenial cortex during different behavioral epochs of a navigation-based decision-making task, as well as in the absence of the task. In-task connectivity was different from no-task connectivity: furthermore, these differences were selective to the cue / decision phase, tapering off in later stages of the task. We propose that fast modulation of connectivity is a prevalent mechanism in neural circuit function.

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Working memory expands shared task representations in cortex

Cognition is thought to emerge from the flexible organization of neural activity, yet how this organization reconfigures across behaviors varying in cognitive load remains unclear. We investigated how the structure of working-memory representations in the cortex compares to task representations that do not involve working memory. We used a task-switching paradigm in virtual reality, where mice alternated between a navigation-based working-memory task and a simpler task with matched sensorimotor demands. During behavior, we simultaneously imaged three cortical areas: higher visual area AM, and two association areas--premotor (M2) and retrosplenial cortex. At the single-neuron level, trial-averaged activity appeared similar across tasks. However, pairwise correlations decreased during the working-memory task, particularly in association areas. In addition, the corresponding linear task subspace explained the variance of both tasks equally well, whereas the simpler task subspace failed to do so, suggesting an asymmetric relationship between them. Nonlinear dimensionality reduction revealed a shared low-dimensional structure across tasks. Yet, the organization of neuronal firing fields along this shared structure accounted for the difference in pairwise correlations: in the working-memory task, firing fields were more disjoint, especially among neurons in association areas that formed sequences along the memory dimension. Moreover, the degree of overlap between these firing fields predicted the mices behavioral reliance on working memory. We conclude that behaviors varying in cognitive demands are supported by a single low-dimensional neural structure, which can expand or contract depending on cognitive load. We thus provide a framework for how task representations across the cortex reconfigure to support cognitive processes.

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Error-driven changes in hippocampal representations accompany flexible re-learning

Flexible behavior requires both the learning of new associations, and the suppression of previous ones, but how neural circuits achieve this balance remains unclear. Here we show that continuous changes in hippocampal representations, known as drift, may facilitate this process. We used voluntary head-fixation and calcium imaging to record from CA1 in rats during an odor-guided navigation task that required frequent re-learning. We found systematic representational changes over the course of the multi-hour sessions that were increased following errors. A simple neural network model revealed that such error-driven drift can enable flexible re-learning by allowing new associations to form from new neural patterns. A consequence of this is that previous associations are maintained in latent synaptic weights. These findings reconcile the apparent tension between representational drift and stable memory storage, demonstrating how dynamic neural codes could support both flexible behavior and lasting memories.

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TWINKLE: An open-source two-photon microscope for teaching and research

Many laboratories use two-photon microscopy through commercial suppliers, or homemade designs of considerable complexity. The integrated nature of these systems complicates customization, troubleshooting, and training on the principles of two-photon microscopy. Here, we present "Twinkle": a microscope for Two-photon Imaging in Neuroscience, and Kit for Learning and Education. It is a fully open, high performing and easy-to-set-up microscope that can effectively be used for both education and research. The instrument features a > 1 mm field of view, using a modern objective with 3 mm working distance and 2 inch diameter optics combined with GaAsP photomultiplier tubes to maximize the fluorescence signal. We document our experiences using this system as a teaching tool in several two week long workshops, exemplify scientific use cases, and conclude with a broader note on the place of our work in the growing space of open scientific instrumentation.

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Magnetic voluntary head-fixation in transgenic rats enables lifetime imaging of hippocampal neurons

The precise neural mechanisms within the brain that contribute to the remarkable lifetime persistence of memory remain unknown. Existing techniques to record neurons in animals are either unsuitable for longitudinal recording from the same cells or make it difficult for animals to express their full naturalistic behavioral repertoire. We present a magnetic voluntary head-fixation system that provides stable optical access to the brain during complex behavior. Compared to previous systems that used mechanical restraint, there are no moving parts and animals can engage and disengage entirely at will. This system is failsafe, easy for animals to use and reliable enough to allow long-term experiments to be routinely performed. Together with a novel two-photon fluorescence collection scheme that increases two-photon signal and a transgenic rat line that stably expresses the calcium sensor GCaMP6f in dorsal CA1, we are able to track and record activity from the same hippocampal neurons, during behavior, over a large fraction of animals lives.

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BIFROST: a method for registering diverse imagingdatasets

The heterogeneity of brain imaging methods in neuroscience provides rich data that cannot be captured by a single technique, and our interpretations benefit from approaches that enable easy comparison both within and across different data types. For example, comparing brain-wide neural dynamics across experiments and aligning such data to anatomical resources, such as gene expression patterns or connectomes, requires precise alignment to a common set of anatomical coordinates. However, this is challenging because registering in vivo functional imaging data to ex vivo reference atlases requires accommodating differences in imaging modality, microscope specification, and sample preparation. We overcome these challenges in Drosophila by building an in vivo reference atlas from multiphoton-imaged brains, called the Functional Drosophila Atlas (FDA). We then develop a two-step pipeline, BrIdge For Registering Over Statistical Templates (BIFROST), for transforming neural imaging data into this common space and for importing ex vivo resources such as connectomes. Using genetically labeled cell types as ground truth, we demonstrate registration with a precision of less than 10 microns. Overall, BIFROST provides a pipeline for registering functional imaging datasets in the fly, both within and across experiments. SignificanceLarge-scale functional imaging experiments in Drosophila have given us new insights into neural activity in various sensory and behavioral contexts. However, precisely registering volumetric images from different studies has proven challenging, limiting quantitative comparisons of data across experiments. Here, we address this limitation by developing BIFROST, a registration pipeline robust to differences across experimental setups and datasets. We benchmark this pipeline by genetically labeling cell types in the fly brain and demonstrate sub-10 micron registration precision, both across specimens and across laboratories. We further demonstrate accurate registration between in-vivo brain volumes and ultrastructural connectomes, enabling direct structure-function comparisons in future experiments.

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Amplitude modulations of sensory responses, and deviations from Weber's Law in pulsatile evidence accumulation

How do animals make behavioral decisions based on noisy sensory signals, which are moreover a tiny fraction of ongoing activity in the brain? Some theories suggest that sensory responses should be accumulated through time to reduce noise. Others suggest that feedback-based gain control of sensory responses allow small signals to be selectively amplified to drive behavior. We recorded from neuronal populations across posterior cortex as mice performed a decision-making task based on accumulating randomly timed pulses of visual evidence. Here we focus on a subset of neurons, with putative sensory responses that were time-locked to each pulse. These neurons exhibited a variety of amplitude (gain-like) modulations, notably by choice and accumulated evidence. These neural data inspired a hypothetical accumulation circuit with a multiplicative feedback-loop architecture, which parsimoniously explains deviations in perceptual discrimination from Weber-Fechner Law. Our neural observations thus led to a model that synthesizes both accumulation and feedback hypotheses.

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Sequential and efficient neural-population coding of complex task information

Recent work has highlighted that many types of variables are represented in each neocortical area. How can these many neural representations be organized together without interference, and coherently maintained/updated through time? We recorded from large neural populations in posterior cortices as mice performed a complex, dynamic task involving multiple interrelated variables. The neural encoding implied that correlated task variables were represented by uncorrelated neural-population modes, while pairs of neurons exhibited a variety of signal correlations. This finding relates to principles of efficient coding for task-specific information, with neural-population modes as the encoding unit, and applied across posterior cortical regions and layers 2/3 and 5. Remarkably, this encoding function was multiplexed with sequential neural dynamics as well as reliably followed changes in task-variable correlations through time. We suggest that neural circuits can implement time-dependent encoding in a simple way by using random sequential dynamics as a temporal scaffold.

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Neural Correlates of Cognition in Primary Visual versus Neighboring Posterior Cortices during Visual Evidence-Accumulation-based Navigation

Studies of perceptual decision-making have often assumed that the main role of sensory cortices is to provide sensory input to downstream processes that accumulate and drive behavioral decisions. We performed a systematic comparison of neural activity in primary visual (V1) to secondary visual and retrosplenial cortices, as mice performed a task where they should accumulate pulsatile visual cues through time to inform a navigational decision. Even in V1, only a small fraction of neurons had sensory-like responses to cues. Instead, in all areas neurons were sequentially active, and contained information ranging from sensory to cognitive, including cue timings, evidence, place/time, decision and reward outcome. Per-cue sensory responses were amplitude-modulated by various cognitive quantities, notably accumulated evidence. This inspired a multiplicative feedback-loop circuit hypothesis that proposes a more intricate role of sensory areas in the accumulation process, and furthermore explains a surprising observation that perceptual discrimination deviates from Weber-Fechner Law.\n\nHighlights / eTOC BlurbO_LIMice made navigational decisions based on accumulating pulsatile visual cues\nC_LIO_LIThe bulk of neural activity in visual cortices was sequential and beyond-sensory\nC_LIO_LIAccumulated pulse-counts modulated sensory (cue) responses, suggesting feedback\nC_LIO_LIA feedback-loop neural circuit explains behavioral deviations from Webers Law\nC_LI\n\nIn a task where navigation was informed by accumulated pulsatile visual evidence, neural activity in visual cortices predominantly coded for cognitive variables across multiple timescales, including outside of a visual processing context. Even sensory responses to visual pulses were amplitude-modulated by accumulated pulse counts and other variables, inspiring a multiplicative feedback-loop circuit hypothesis that in turn explained behavioral deviations from Weber-Fechner Law.

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Shared Song Object Detector Neurons in Drosophila Male and Female Brains Drive Divergent, Sex-Specific Behaviors

Males and females often produce distinct responses to the same sensory stimuli. How such differences arise - at the level of sensory processing or in the circuits that generate behavior - remains largely unresolved across sensory modalities. We address this issue in the acoustic communication system of Drosophila. During courtship, males generate time-varying songs, and each sex responds with specific behaviors. We characterize male and female behavioral tuning for all aspects of song, and show that feature tuning is similar between sexes, suggesting sex-shared song detectors drive divergent behaviors. We then identify higher-order neurons in the Drosophila brain, called pC2, that are tuned for multiple temporal aspects of one mode of the males song, and drive sex-specific behaviors. We thus uncover neurons that are specifically tuned to an acoustic communication signal and that reside at the sensory-motor interface, flexibly linking auditory perception with sex-specific behavioral responses.

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An accumulation-of-evidence task using visual pulses for mice navigating in virtual reality

The gradual accumulation of sensory evidence is a crucial component of perceptual decision making, but its neural mechanisms are still poorly understood. Given the wide availability of genetic and optical tools for mice, they can be useful model organisms for the study of these phenomena; however, behavioral tools are largely lacking. Here, we describe a new evidence-accumulation task for head-fixed mice navigating in a virtual reality environment. As they navigate down the stem of a virtual T-maze, they see brief pulses of visual evidence on either side, and retrieve a reward on the arm with the highest number of pulses. The pulses occur randomly with Poisson statistics, yielding a diverse yet well-controlled stimulus set, making the data conducive to a variety of computational approaches. A large number of mice of different genotypes were able to learn and consistently perform the task, at levels similar to rats in analogous tasks. They are sensitive to side differences of a single pulse, and their memory of the cues is stable over time. Moreover, using non-parametric as well as modeling approaches, we show that the mice indeed accumulate evidence: they use multiple pulses of evidence from throughout the cue region of the maze to make their decision, albeit with a small overweighting of earlier cues, and their performance is affected by the magnitude but not the duration of evidence. Additionally, analysis of the mice's running patterns revealed that trajectories are fairly stereotyped yet modulated by the amount of sensory evidence, suggesting that the navigational component of this task may provide a continuous readout correlated to the underlying cognitive variables. Our task, which can be readily integrated with state-of-the-art techniques, is thus a valuable tool to study the circuit mechanisms and dynamics underlying perceptual decision making, particularly under more complex behavioral contexts.

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