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Biology subjects

Giocomo, L. M.

Publications and source records attributed to Giocomo, L. M..

At least 19 recordsLinked to original sources

Inferring the evolving objectives that organize animal behavior

Understanding how the brain supports flexible, goal-directed behavior is a central aim of neuroscience. Yet such behavior is highly variable and unfolds over long timescales, making it challenging to understand its organization. Advances in behavioral tracking quantify movements but do not reveal the objectives that guide them. Motivated by this, we develop inverse reinforcement learning (IRL) into a general framework for inferring these objectives from naturalistic behavior. Our approach represents an animal's objectives as internal rewards, and infers these rewards as well as the policies they induce from observed behavior. It applies across diverse behavioral settings, from freely moving behaviors to structured tasks. It can infer objectives that switch over time or gradually change with experience. In mice capturing crickets, it identified a small set of objectives that the animals switched between over the course of a trial. In mice learning a cued labyrinth, it inferred how the animals' internal rewards changed as learning progressed. Across both datasets, the models predicted held-out actions and generated extended behavior that reproduced key features of animal performance. By transforming long, variable behavioral sequences into time-resolved estimates of the animal's objectives, our approach provides a quantitative basis for studying how the brain organizes natural behavior.

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Topographic CA1 input shapes subicular spatial coding

Precise anatomical topographic mapping in the brain supports high-fidelity information transfer for computations such as sensory alignment and motor coordination1,2. As a brain structure central to learning, memory, and navigation, the hippocampal formation is likewise organized with striking topographic precision3-8. Within this circuit, the subiculum plays a critical role in forming the cognitive map by integrating spatial and non-spatial information from both CA1 and the entorhinal cortex (EC)9-17. Inputs from these regions follow a continuous topography such that distal subiculum receives projections from proximal CA1 (pCA1) and medial EC (MEC), whereas proximal subiculum receives projections from distal CA1 (dCA1) and lateral EC (LEC)3-5,7,8. This anatomical architecture suggests that subicular computations may depend critically on the fidelity of these circuit topographies. However, because CA1 and EC provide partially overlapping spatial information, it remains unclear to what extent CA1-to-subiculum topography, independent of ECs contribution, shapes the physiological properties of subicular neurons. Here, by selectively disrupting CA1-to-subiculum topographic projections in latrophilin-2 conditional knockout mice, we show that precise topography shapes the anatomical distribution of subicular spatial coding while preserving single-cell tuning. Disrupted CA1 input topography also selectively impairs subicular boundary vector coding and long-term network stability. Thus, CA1 input topography is critical for organizing subicular spatial coding and network dynamics. HighlightsO_LICA1[->]subiculum topography organizes spatial coding distribution in the subiculum. C_LIO_LIDisrupted CA1 input topography spares individual subicular place cell tuning. C_LIO_LIDisrupted CA1 input topography selectively impairs subicular boundary vector coding. C_LIO_LILong-term subicular ensemble reactivation requires precise CA1 input topography. C_LI

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Environmental Novelty Modulates Rapid Cortical Plasticity During Navigation

In novel environments, animals quickly learn to navigate, and position-correlated spatial representations rapidly emerge in both the retrosplenial cortex (RSC) and primary visual cortex (V1). However, the role of plasticity in building these spatial representations, and how experience modulates this process, are not well understood. Here, we investigated the plasticity of spatial representations with real-time, cellular-resolution read and write control of neural activity using two-photon calcium imaging combined with holographic optogenetic stimulation in mice navigating virtual reality environments. Targeted stimulation of individual layer 2/3 neurons rapidly biased neural activity towards stimulation-paired locations in novel, but not familiar, environments. In contrast, RSC layer 5 neurons exhibited stimulation-induced plasticity regardless of environmental familiarity. These findings reveal a layer-specific, experience-dependent modulation of plasticity and offer a framework for how neocortical spatial representations strike a balance between stability of familiar environments with flexibility for continuous updates of relevant context information. HighlightsO_LIAll optical read-write approach reveals experience-dependent plasticity in cortex C_LIO_LIStimulating layer 2/3 neurons biases activity in novel but not familiar environments C_LIO_LILayer 5 neurons exhibit plasticity regardless of environmental familiarity C_LI

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Large-scale cellular-resolution read/write of activity enables discovery of cell types defined by complex circuit properties

The complexity of the mammalian brains vast population of interconnected neurons poses a formidable challenge to elucidate its underlying mechanisms of coordination and computation. A key step forward will be technologies that can perform large-scale, cellular-resolution monitoring and interrogation of distributed brain circuit activity in behaving animals. Here, we present an all-optical strategy for precise optogenetic activity control of [~]103 neurons and simultaneous activity monitoring of [~]104 neurons within and across areas of mouse cortex--an order-of-magnitude leap beyond previous capabilities. Tracking population responses following delivery of precisely-defined widely-distributed activity patterns to the visual cortex of awake mice, we were surprised to identify neurons robustly responsive to stimulation of diverse ensembles, defying conventional like-to-like wiring rules. These cells were primarily deep L2/3 somatostatin-positive (SST) interneurons with functional properties distinct from other SST neurons, and appeared to play a role in brain dynamics that could only have been identified through broad cellular-resolution circuit interrogation. Our work reveals the value of measuring large-scale circuit-dynamical properties of functionally-resolved single cells, beyond genetic and anatomical classification, to define and explore the roles of cell types in brain function.

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Unifying Subicular Function: A Predictive Map Approach

The successor representation has emerged as a powerful model for understanding mammalian navigation and memory; explaining the spatial coding properties of hippocampal place cells and entorhinal grid cells. However, the diverse spatial responses of subicular neurons, the primary output of the hippocampus, have eluded a unified account. Here, we demonstrate that incorporating rodent behavioural biases into the successor representation successfully reproduces the heterogeneous activity patterns of subicular neurons. This framework accounts for the emergence of boundary and corner cells - neuronal types absent in upstream hippocampal regions. We provide evidence that subicular firing patterns are more accurately described by the successor representation than a purely spatial or boundary vector cell model of subiculum. Our work reveals a temporal hierarchy in hippocampal-subicular processing, with subiculum encoding predictive representations over longer time horizons than CA1, capturing extended behavioural patterns and environmental affordances.

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Entorhinal cortex represents task-relevant remote locations independent of CA1

Neurons can collectively represent the current sensory experience while an animal is exploring its environment or remote experiences while the animal is immobile. These remote representations can reflect learned associations1-3 and be required for learning4. Neurons in the medial entorhinal cortex (MEC) reflect the animals current location during movement5, but little is known about what MEC neurons collectively represent during immobility. Here, we recorded thousands of neurons in superficial MEC and dorsal CA1 as mice learned to associate two pairs of rewarded locations. We found that during immobility, the MEC neural population frequently represented positions far from the animals location, which we defined as non-local coding. Cells with spatial firing fields at remote locations drove non-local coding, even as cells representing the current position remained active. While MEC non-local coding has been reported during sharp-wave ripples in downstream CA16, we observed non-local coding more often outside of ripples. In fact, CA1 activity was less coordinated with MEC during non-local coding. We further observed that non-local coding was pertinent to the task, as MEC preferentially represented remote task-relevant locations at appropriate times, while rarely representing task-irrelevant locations. Together, this work raises the possibility that MEC non-local coding could strengthen associations between locations independently from CA1.

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Spatial Coding Dysfunction and Network Instability in the Aging Medial Entorhinal Cortex

Across species, spatial memory declines with age, possibly reflecting altered hippocampal and medial entorhinal cortex (MEC) function. However, the integrity of cellular and network-level spatial coding in aged MEC is unknown. Here, we leveraged in vivo electrophysiology to assess MEC function in young, middle-aged, and aged mice navigating virtual environments. In aged grid cells, we observed impaired stabilization of context-specific spatial firing, correlated with spatial memory deficits. Additionally, aged grid networks shifted firing patterns often but with poor alignment to context changes. Aged spatial firing was also unstable in an unchanging environment. In these same mice, we identified 458 genes differentially expressed with age in MEC, 61 of which had expression correlated with spatial firing stability. These genes were enriched among interneurons and related to synaptic transmission. Together, these findings identify coordinated transcriptomic, cellular, and network changes in MEC implicated in impaired spatial memory in aging.

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Hippocampal sequences span experience relative to rewards

Hippocampal place cells fire in sequences that span spatial environments and non-spatial modalities, suggesting that hippocampal activity can anchor to the most behaviorally salient aspects of experience. As reward is a highly salient event, we hypothesized that sequences of hippocampal activity can anchor to rewards. To test this, we performed two-photon imaging of hippocampal CA1 neurons as mice navigated virtual environments with changing hidden reward locations. When the reward moved, the firing fields of a subpopulation of cells moved to the same relative position with respect to reward, constructing a sequence of reward-relative cells that spanned the entire task structure. The density of these reward- relative sequences increased with task experience as additional neurons were recruited to the reward- relative population. Conversely, a largely separate subpopulation maintained a spatially-based place code. These findings thus reveal separate hippocampal ensembles can flexibly encode multiple behaviorally salient reference frames, reflecting the structure of the experience.

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Hippocampal place code plasticity in CA1 requires postsynaptic membrane fusion

Rapid delivery of glutamate receptors to the postsynaptic membrane via vesicle fusion is a central component of synaptic plasticity. However, it is unknown how this process supports specific neural computations during behavior. To bridge this gap, we combined conditional genetic deletion of a component of the postsynaptic membrane fusion machinery, Syntaxin3 (Stx3), in hippocampal CA1 neurons of mice with population in vivo calcium imaging. This approach revealed that Stx3 is necessary for forming the neural dynamics that support novelty processing, spatial reward memory and offline memory consolidation. In contrast, CA1 Stx3 was dispensable for maintaining aspects of the neural code that exist presynaptic to CA1 such as representations of context and space. Thus, manipulating postsynaptic membrane fusion identified computations that specifically require synaptic restructuring via membrane trafficking in CA1 and distinguished them from neural representation that could be inherited from upstream brain regions or learned through other mechanisms.

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The subiculum encodes environmental geometry

Corners are a cardinal feature of many of the complex environmental geometries found in the natural world but the neural substrates that could underlie the perception of corners remain elusive. Here we show that the dorsal subiculum contains neurons that encode corners across environmental geometries in an allocentric reference frame. Corner cells changed their activity to reflect concave corner angles, wall height and the degree of wall intersection. A separate population of subicular neurons encoded convex corners. Both concave and convex corner cells were non-overlapping with subicular neurons that encoded environmental boundaries, suggesting that the subiculum contains the geometric information needed to re-construct the shape and layout of naturalistic spatial environments. One Sentence SummarySeparate neural populations in the subiculum encode concave and convex environmental corners.

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Ketamine evoked disruption of entorhinal and hippocampal spatial maps

Ketamine, a rapid-acting anesthetic and acute antidepressant, carries undesirable spatial cognition side effects including out-of-body experiences and spatial memory impairments. The neural substrates that underlie these alterations in spatial cognition however, remain incompletely understood. Here, we used electrophysiology and calcium imaging to examine ketamines impacts on the medial entorhinal cortex and hippocampus, which contain neurons that encode an animals spatial position, as mice navigated virtual reality and real world environments. Ketamine induced an acute disruption and long-term re-organization of entorhinal spatial representations. This acute ketamine-induced disruption reflected increased excitatory neuron firing rates and degradation of cell-pair temporal firing rate relationships. In the reciprocally connected hippocampus, the activity of neurons that encode the position of the animal was suppressed after ketamine administration. Together, these findings point to disruption in the spatial coding properties of the entorhinal-hippocampal circuit as a potential neural substrate for ketamine-induced changes in spatial cognition.

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Remapping in a recurrent neural network model of navigation and context inference

Neurons in navigational brain regions provide information about position, orientation, and speed relative to environmental landmarks. These cells also change their firing patterns ("remap") in response to changing contextual factors such as environmental cues, task conditions, and behavioral state, which influence neural activity throughout the brain. How can navigational circuits preserve their local computations while responding to global context changes? To investigate this question, we trained recurrent neural network models to track position in simple environments while at the same time reporting transiently-cued context changes. We show that these combined task constraints (navigation and context inference) produce activity patterns that are qualitatively similar to population-wide remapping in the entorhinal cortex, a navigational brain region. Furthermore, the models identify a solution that generalizes to more complex navigation and inference tasks. We thus provide a simple, general, and experimentally-grounded model of remapping as one neural circuit performing both navigation and context inference.

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Parahippocampal neurons encode task-relevant information for goal-directed navigation

A behavioral strategy crucial to survival is directed navigation to a goal, such as a food or home location. One potential neural substrate for supporting goal-directed navigation is the parahippocampus, which contains neurons that represent an animals position, orientation, and movement through the world, and that change their firing activity to encode behaviorally relevant variables such as reward. However, little prior work on the parahippocampus has considered how neurons encode variables during goal-directed navigation in environments that dynamically change. Here, we recorded single units from rat parahippocampal cortex while subjects performed a goal-directed task. The maze dynamically changed goal-locations via a visual cue on a trial-to-trial basis, requiring subjects to use cue-location associations to receive reward. We observed a mismatch-like signal, with elevated neural activity on incorrect trials, leading to rate-remapping. The strength of this remapping correlated with task performance. Recordings during open-field foraging allowed us to functionally define navigational coding for a subset of the neurons recorded in the maze. This approach revealed that head-direction coding units remapped more than other functional-defined units. Taken together, this work thus raises the possibility that during goal-directed navigation, parahippocampal neurons encode error information reflective of an animals behavioral performance.

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Dissociating encoding of memory and salience by manipulating long-term synaptic potentiation

Neural codes are thought to be reorganized during memory formation by long-term potentiation (LTP) of synapses. Here, using a novel approach for selectively blocking LTP, we found that eliminating LTP in hippocampal or striatal circuits only produces limited effects on learning and memory. To reconcile the discrepancy between the large physiological effect of blocking LTP and the absent effect on learning, we studied how LTP impacts neuronal computations in the hippocampus using in-vivo Ca2+-imaging. Contrary to current conceptual frameworks, we found that hippocampal CA1-region LTP is not required for accurate representations of space in hippocampal neurons, but rather endows these neurons with reward- and novelty-coding properties. Thus, instead of driving formation of cognitive maps and memory engrams, CA1-region LTP incorporates salience information into cognitive representations. One-Sentence SummaryA novel approach for studying long-term potentiation reveals its surprising and selective role in salience encoding

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Explaining heterogeneity in medial entorhinal cortex with task-driven neural networks

Medial entorhinal cortex (MEC) supports a wide range of navigational and memory related behaviors. Well-known experimental results have revealed specialized cell types in MEC -- e.g. grid, border, and head-direction cells -- whose highly stereotypical response profiles are suggestive of the role they might play in supporting MEC functionality. However, the majority of MEC neurons do not exhibit stereotypical firing patterns. How should the response profiles of these more "heterogeneous" cells be described, and how do they contribute to behavior? In this work, we took a computational approach to addressing these questions. We first performed a statistical analysis that shows that heterogeneous MEC cells are just as reliable in their response patterns as the more stereotypical cell types, suggesting that they have a coherent functional role. Next, we evaluated a spectrum of candidate models in terms of their ability to describe the response profiles of both stereotypical and heterogeneous MEC cells. We found that recently developed task-optimized neural network models are substantially better than traditional grid cell-centric models at matching most MEC neuronal response profiles -- including those of grid cells themselves -- despite not being explicitly trained for this purpose. Specific choices of network architecture (such as gated nonlinearities and an explicit intermediate place cell representation) have an important effect on the ability of the model to generalize to novel scenarios, with the best of these models closely approaching the noise ceiling of the data itself. We then performed in silico experiments on this model to address questions involving the relative functional relevance of various cell types, finding that heterogeneous cells are likely to be just as involved in downstream functional outcomes (such as path integration) as grid and border cells. Finally, inspired by recent data showing that, going beyond their spatial response selectivity, MEC cells are also responsive to non-spatial rewards, we introduce a new MEC model that performs reward-modulated path integration. We find that this unified model matches neural recordings across all variable-reward conditions. Taken together, our results point toward a conceptually principled goal-driven modeling approach for moving future experimental and computational efforts beyond overly-simplistic single-cell stereotypes.

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A positively Tuned Voltage Indicator Reveals Electrical Correlates of Calcium Activity in the Brain

Neuronal spiking activity is routinely recorded using genetically encoded calcium indicators (GECIs), but calcium imaging is limited in temporal resolution and does not report subthreshold voltage changes. Genetically encoded voltage indicators (GEVIs) offer better temporal resolution and subthreshold sensitivity, but spike detection with fast GEVIs has required specialized imaging equipment. Here, we report the ASAP4 subfamily of genetically encoded voltage indicators (GEVIs) that brighten in response to membrane depolarization, inverting the fluorescence-voltage relationship of previous ASAP GEVIs. Two variants, ASAP4b and ASAP4e, feature 128% and 178% fluorescence increases over 100-mV of depolarization, respectively, facilitating spike detection in single trials in vivo with standard 1 and 2-photon imaging systems. Simultaneous voltage and calcium imaging confirms improved temporal resolution and spike discernment by ASAP4 GEVIs. Thus, positively tuned ASAP4 voltage indicators enable recording of neuronal spiking activity using similar equipment as calcium imaging, while providing higher temporal resolution. One Sentence SummaryUpward ASAPs increase detection capability of GEVIs in vivo.

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Neural circuit dynamics of drug-context associative learning in the hippocampus

The environmental context associated with previous drug consumption serves as a potent trigger for relapse to drug use. The mechanism by which existing neural representations of context are modified to incorporate information associated with a given drug however, remains unknown. Using longitudinal calcium imaging in freely behaving mice, we reveal that drug-context associations for psychostimulants and opioids are encoded in a subset of hippocampal neurons. In these neurons, drug context pairing in a conditioned place preference task weakened their spatial coding for the nondrug-paired context, with drug-induced changes to spatial coding predictive of drug-seeking behavior. Furthermore, the dissociative drug ketamine blocked both the drug-induced changes to hippocampal coding and corresponding drug-seeking behavior. Together, this work reveals how drugs of abuse can alter the hippocampal circuit to encode drug-context associations and points to the hippocampus as a key node in the cognitive process of drug addiction and context-induced drug relapse.

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Dynamic and reversible remapping of network representations in an unchanging environment

In response to environmental changes, the medial entorhinal cortex alters its single-cell firing properties. This flexibility in neural coding is hypothesized to support navigation and memory by dividing sensory experience into unique contextual episodes. However, it is unknown how the entorhinal circuit transitions between different representations, particularly when sensory information is not delineated into discrete contexts. Here, we describe spontaneous and abrupt transitions between multiple spatial maps of an unchanging task and environment. These remapping events were synchronized across hundreds of medial entorhinal neurons and correlated with changes in running speed. While remapping altered spatial coding in individual neurons, we show that features of the environment were statistically preserved at the population-level, enabling simple decoding strategies. These findings provoke a reconsideration of how medial entorhinal cortex dynamically represents space and broadly suggest a remarkable capacity for higher-order cortical circuits to rapidly and substantially reorganize their neural representations.

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