Hugh Tad Blair

Flexible decision making depends on internal representations that capture the latent structure of a task, allowing prior knowledge to be applied in novel circumstances. Spatial navigation provides a useful model for studying flexible choice behavior, because spatial location is itself a latent variable that must be inferred rather than directly perceived. Here, we trained rats on a navigation task that required them to reach the same goal via two distinct paths from different starting locations, and then return to one of the two starting locations before beginning the next trial. Some rats were trained to rely on distal visual landmarks, allowing task states to be identified from current sensory information, whereas others were trained to rely on path integration, requiring task states to be inferred from self-motion information accumulated over the preceding trajectory. Rats trained to rely on path integration acquired the task similarly to rats trained to rely on distal visual landmarks. However, reliance on path integration enhanced rats’ ability to generalize their learning to novel situations, including finding the goal from an untrained starting location and adapting to a relocated goal that reversed learned choice sequences. These findings suggest that reliance on path integration promotes the acquisition and use of mental representations that capture the latent spatial structure of navigational tasks, thereby favoring flexible navigational decisions over rigid retrieval of reinforced responses. More broadly, our findings demonstrate how information available during training can shape representations learned from experience and thereby constrain the flexibility of decision making during inference.

Goal-directed decisions depend on predictions of future outcomes and are thus sensitive to revaluation of expected outcomes, whereas habitual decisions depend on cached action values or stimulusresponse associations and are insensitive to outcome revaluation. Hippocampal neurons encode future states (potentially supporting prediction of future outcomes during goal-directed choice) as well as present states (potentially supporting retrieval of state-dependent action values during habitual choice). Prior studies suggest the role of the hippocampus in goal-directed, outcome-sensitive decision-making, but few studies have examined its role in outcome-insensitive action selection. Here, we tested this using a two-outcome spatial navigation task in which identical turning actions (left or right) led either to preferred milk or nonpreferred water outcomes, depending on the spatial location at which the choice was made. Rats (20 males, 22 females) were trained under conditions that either required hippocampal-dependent discrimination between choice points or allowed hippocampal-independent navigation using visual beacons. Rats then underwent 24 h water restriction, during which separate cohorts underwent Contingency Updating (CU), in which rats re-experienced the maze actionoutcome contingencies while thirsty, or Incentive Learning (IL), in which rats received only a two-bottle preference test while thirsty without re-experiencing maze contingencies. Both cohorts were later tested under thirst on an unbaited maze. CU rats shifted their choices toward water-associated responses, whereas IL rats perseverated on milk-associated responses, even when navigation depended on the hippocampus. These results provide novel evidence that hippocampal-dependent navigational decisions can show insensitivity to outcome revaluation, a widely used behavioral criterion for habitual control.

The hippocampus encodes cognitive maps that support goal-directed navigation. Hippocampal neurons can encode future states and trajectories, and disruption of the hippocampus can impair sensitivity to outcome revaluation when decisions depend on spatial or contextual memory, suggesting a link between hippocampal model-based representations and value-sensitive control. However, few studies have investigated whether hippocampal representations can support habitual, outcome-insensitive action selection. Here, we developed a two-outcome spatial navigation task in which identical turning actions (left or right) led to opposite rewards (milk or water) depending on spatial location. Separate groups of rats (16 males, 22 females) were trained under conditions that either required hippocampal-dependent discrimination between choice points or allowed hippocampal-independent performance based on visual beacons. Intrahippocampal muscimol confirmed the differential dependence of these task variants on the hippocampus. After extensive training, outcome sensitivity was assessed by water restriction, which reliably shifted preference from milk to water. When tested in extinction under water restriction, rats continued to select milk-associated responses despite the change in outcome value, indicating habitual, outcome-insensitive control. Critically, this insensitivity was observed regardless of whether task performance depended on the hippocampus. Outcome sensitivity emerged only after a fully reinforced revaluation training session, and did so independently of the original training condition. These findings demonstrate that hippocampal-dependent navigation can be governed by value-insensitive action policies, and thus show that reliance upon hippocampal representations for pathfinding is not sufficient to confer outcome-sensitive control, thereby dissociating the use of cognitive maps from value updating in navigational decision making. Significance Statement: The hippocampus is widely thought to support goal-directed navigation by constructing internal models (“cognitive maps”) that enable flexible decision making. In laboratory experiments, goal-directed behavior is typically defined by sensitivity to outcome revaluation. However, we show here that the hippocampus can support outcome-insensitive (habitual) action selection during a spatial task in which identical actions lead to different rewards depending on location. Even when accurate performance required the hippocampus, rats trained on this task failed to adjust their choices after outcome revaluation. Outcome sensitivity emerged only after a fully reinforced revaluation training session. These findings dissociate reliance on hippocampal representations from value-sensitive control, demonstrating that use of a cognitive map is not sufficient to confer goal-directed behavior.

Orbitofrontal cortex (OFC) and secondary motor cortex (M2) are both implicated in flexible reward learning but the conditions that differentially recruit these regions are not fully understood. We imaged calcium activity from single neurons in OFC or M2 during de novo learning of increasingly uncertain reward probability schedules. Predictions of choice were decoded from M2 neurons with high accuracy under all certainty conditions, but were more accurately decoded from OFC neurons under greater uncertainty. The number of choice- and reward-selective neurons was significantly higher in M2 than in OFC across schedules, but these proportions increased across levels of uncertainty only in OFC. Decoding accuracy of choice and outcome was predicted by behavioral strategies Win-Stay and Lose-Shift in OFC, but not M2. We also tested causal involvement of these regions with chemogenetic perturbation as rats learned increasing and then decreasing uncertainty schedules. Whereas inhibition of OFC neurons attenuated learning across all schedules, M2 neurons were found to support learning in the most certain reward schedule. Thus, OFC neurons preferentially encode choices and outcomes that foster a greater reliance on adaptive strategies under uncertainty. This reveals a novel functional heterogeneity within frontal cortex in support of flexible learning.

The cerebellum has been implicated in the regulation of social behavior. Its influence is thought to arise from communication, via the thalamus, to forebrain regions integral in the expression of social interactions, including the anterior cingulate cortex (ACC). However, the signals encoded or the nature of the communication between the cerebellum and these brain regions is poorly understood. Here, we describe an approach that overcomes technical challenges in exploring the coordination of distant brain regions at high temporal and spatial resolution during social behavior. We developed the E-Scope, an electrophysiology-integrated miniature microscope, to synchronously measure extracellular electrical activity in the cerebellum along with calcium imaging of the ACC. This single coaxial cable device combined these data streams to provide a powerful tool to monitor the activity of distant brain regions in freely behaving animals. During social behavior, we recorded the spike timing of multiple single units in cerebellar right Crus I (RCrus I) Purkinje cells (PCs) or dentate nucleus (DN) neurons while synchronously imaging calcium transients in contralateral ACC neurons. We found that during social interactions a significant subpopulation of cerebellar PCs were robustly inhibited, while most modulated neurons in the DN were activated, and their activity was correlated with positively modulated ACC neurons. These distinctions largely disappeared when only non-social epochs were analyzed suggesting that cerebellar-cortical interactions were behaviorally specific. Our work provides new insights into the complexity of cerebellar activation and co-modulation of the ACC during social behavior and a valuable open-source tool for simultaneous, multimodal recordings in freely behaving mice.

Aversive stimuli can cause hippocampal place cells to remap their firing fields, but it is not known whether remapping plays a role in storing memories of aversive experiences. Here, we addressed this question by performing in vivo calcium imaging of CA1 place cells in freely behaving rats (n = 14). Rats were first trained to prefer a short path over a long path for obtaining food reward, then trained to avoid the short path by delivering a mild footshock. Remapping was assessed by comparing place cell population vector similarity before acquisition versus after extinction of avoidance. Some rats received shock after systemic injections of the amnestic drug scopolamine at a dose (1 mg/kg) that impaired avoidance learning but spared spatial tuning and shock-evoked responses of CA1 neurons. Place cells remapped significantly more following remembered than forgotten shocks (drug-free versus scopolamine conditions); shock-induced remapping did not cause place fields to migrate toward or away from the shocked location and was similarly prevalent in cells that were responsive versus non-responsive to shocks. When rats were exposed to a neutral barrier rather than aversive shock, place cells remapped significantly less in response to the barrier. We conclude that place cell remapping occurs in response to events that are remembered rather than merely perceived and forgotten, suggesting that reorganization of hippocampal population codes may play a role in storing memories for aversive events.

Imaging large-population, single-cell fluorescent dynamics in freely behaving animals larger than mice remains a key endeavor of neuroscience. We present a large-field-of-view open-source miniature microscope (MiniLFOV) designed for large-scale (3.6 mm × 2.7 mm), cellular resolution neural imaging in freely behaving rats. It has an electrically adjustable working distance of up to 3.5 mm ± 100 μm, incorporates an absolute head orientation sensor, and weighs only 13.9 g. The MiniLFOV is capable of both deep brain and cortical imaging and has been validated in freely behaving rats by simultaneously imaging >1000 GCaMP7s-expressing neurons in the hippocampal CA1 layer and in head-fixed mice by simultaneously imaging ~2000 neurons in the dorsal cortex through a cranial window. The MiniLFOV also supports optional wire-free operation using a novel, wire-free data acquisition expansion board. We expect that this new open-source implementation of the UCLA Miniscope platform will enable researchers to address novel hypotheses concerning brain function in freely behaving animals.

Miniaturized calcium imaging is an emerging neural recording technique that has been widely used for monitoring neural activity on a large scale at a specific brain region of rats or mice. Most existing calcium-image analysis pipelines operate offline. This results in long processing latency, making it difficult to realize closed-loop feedback stimulation for brain research. In recent work, we have proposed an FPGA-based real-time calcium image processing pipeline for closed-loop feedback applications. It can perform real-time calcium image motion correction, enhancement, fast trace extraction, and real-time decoding from extracted traces. Here, we extend this work by proposing a variety of neural network based methods for real-time decoding and evaluate the tradeoff among these decoding methods and accelerator designs. We introduced the implementation of the neural network based decoders on the FPGA, and showed their speedup against the implementation on the ARM processor. Our FPGA implementation enables the real-time calcium image decoding with sub-ms processing latency for closed-loop feedback applications.

The cerebellum has been implicated in the regulation of social behavior. Its influence is thought to arise from communication, via the thalamus, to forebrain regions integral in the expression of social interactions, including the anterior cingulate cortex (ACC). However, the signals encoded or the nature of the communication between the cerebellum and these brain regions is poorly understood. Here, we describe an approach that overcomes technical challenges in exploring the coordination of distant brain regions at high temporal and spatial resolution during social behavior. We developed the E-Scope, an electrophysiology-integrated miniature microscope, to synchronously measure extracellular electrical activity in the cerebellum along with calcium imaging of the ACC. This single coaxial cable device combined these data streams to provide a powerful tool to monitor the activity of distant brain regions in freely behaving animals. During social behavior, we recorded the spike timing of multiple single units in cerebellar right Crus I (RCrus I) Purkinje cells (PCs) or dentate nucleus (DN) neurons while synchronously imaging calcium transients in contralateral ACC neurons. We found that during social interactions a significant subpopulation of cerebellar PCs were robustly inhibited, while most modulated neurons in the DN were activated, and their activity was correlated with positively modulated ACC neurons. These distinctions largely disappeared when only non-social epochs were analyzed suggesting that cerebellar-cortical interactions were behaviorally specific. Our work provides new insights into the complexity of cerebellar activation and co-modulation of the ACC during social behavior and a valuable open-source tool for simultaneous, multimodal recordings in freely behaving mice.

Epifluorescence miniature microscopes (‘miniscopes’) are widely used for in vivo calcium imaging of neural population activity. Imaging data are typically collected during a behavioral task and stored for later offline analysis, but emerging techniques for online imaging can support novel closed-loop experiments in which neural population activity is decoded in real time to trigger neurostimulation or sensory feedback. To achieve short feedback latencies, online imaging systems must be optimally designed to maximize computational speed and efficiency while minimizing errors in population decoding. Here we introduce DeCalciOn, an open-source device for real-time imaging and population decoding of in vivo calcium signals that is hardware compatible with all miniscopes that use the UCLA Data Acquisition (DAQ) interface. DeCalciOn performs online motion stabilization, neural enhancement, calcium trace extraction, and decoding of up to 1024 traces per frame at latencies of n = 12) running on a linear track from calcium fluorescence in the hippocampal CA1 layer, and can categorically classify behaviors performed by rats (n = 2) during an instrumental task from calcium fluorescence in orbitofrontal cortex. DeCalciOn achieves high decoding accuracy at short latencies using innovations such as field-programmable gate array hardware for real-time image processing and contour-free methods to efficiently extract calcium traces from sensor images. In summary, our system offers an affordable plug-and-play solution for real-time calcium imaging experiments in behaving animals.