Neuron

The decision criterion is foundational to theories of decision-making, yet little is known about its neural underpinnings. In memory-based decision making, the criterion sets the minimal memory strength for something to be familiar, but whether or how it is distinctly represented from memory strength is unknown. We recorded single neurons in the medial frontal cortex (MFC) and medial temporal lobe (MTL), both implicated in memory-based decisions, while participants made decisions under different decision criteria. We identified criterion-selective (CS) neurons in the MFC that tracked the criterion regardless of memory strength, and memory-selective (MS) neurons in both regions that tracked memory strength regardless of the criterion. CS neurons signaled the criterion before MS neurons signaled memory strength, and a race model incorporating both neuron types outperformed one using MS neurons alone. These findings reveal two independent cellular substrates, one for the decision criterion and one for memory strength, whose joint activity underlies memory-based decisions.

Natural vision is continuously shaped by an animal's own movements, which determine what enters the visual system and when visual input changes. Gaze shifts are known to initiate a temporally structured sequence of activity in primary visual cortex (V1), but how the visual content sampled by each movement contributes to this sequence has remained unclear. We recorded visual input, eye and head movements, and V1 activity in freely moving mice, and asked how the visual content sampled on each gaze shift shapes the response. The magnitude of visual change induced by each gaze shift scaled the amplitude of responses according to each neuron's characteristic response profile, while movement amplitude alone did not reproduce this modulation in darkness, supporting a role of visual input in driving the sequence. Activity following gaze shifts reflected each neuron's spatial receptive field structure, and visual filters estimated under head-fixed conditions predicted the relative timing of spike responses during gaze shifts of freely moving animals, demonstrating that gaze shift responses encode visual information. At the population level, decoded V1 activity shifted toward the scene sampled after each gaze shift. Thus, across single-neuron, spatial, temporal, and population measures, V1 activity tracked the content of each sample beyond movement timing alone, indicating that gaze shifts act as sampling events that result in V1 encoding visual information in temporally ordered responses.

A prevailing view in affective neuroscience holds that innate and learned behaviors are processed through distinct neuroanatomical pathways, one pre-wired, the other running on synaptic plasticity. However, here we show that processing innate and learned threats in the lateral amygdala deviates fundamentally from this view. We tracked the three core elements of circuit function (excitatory neurons, inhibitory neurons, and neuromodulators) in mice, as they were exposed to an innately aversive looming stimulus and as they learned a cued threat. Tracking the same neurons across sessions, revealed a subpopulation of excitatory neurons recruited by the innate threat that was preferentially potentiated following auditory threat learning. Furthermore, both forms of threat converged on the same modulatory mechanisms: the disinhibitory VIP/SST motif and norepinephrine release, but with a critical difference. While the innately aversive stimulus possessed privileged access to these pathways, the learned cue acquired access through synaptic plasticity. In this instance, learning about a new threat apparently recruits a circuit that protects animals from natural threats.

Flexible behavior requires generalizable memory and learning. For example, we rapidly learn to commute in new cities by reusing our knowledge of Euclidean two-dimensional space and structures like roundabouts and subway systems without forgetting how to get to a favorite restaurant back home. Yet we lack a detailed understanding of how the brain uses existing knowledge to generalize while retaining the memory of specific past experiences. To address this gap, we combine behavioral measurements, neural recordings, and computational modeling in an abstract sequential image navigation task to study three forms of generalization: mnemonic generalization, from visual to mental navigation; transitive generalization, from trained to novel routes; and structural generalization, from familiar to new environments. In contrast to monkeys and humans, recurrent neural networks failed at all generalizations. We found that a structured entorhinal-hippocampal memory model, which provides a content-independent metric scaffold based on grid cells for storing experience, coupled to a policy recurrent network, succeeds at all three. The content-independent scaffold enables mnemonic and transitive generalization through path integration and facilitates structural generalization by allowing reuse of a previously learned action policy network. Moreover, the scaffold's high combinatorial capacity permits continual learning without catastrophic forgetting. We recorded neural activity from the entorhinal cortex and posterior parietal cortex of two monkeys performing the task and found two distinct computations across the neural population. Modularizing an entorhinal and parietal action policy network to separately track distance and initiate actions captured the distinct population dynamics and improved model performance. Finally, we added a reinforcement learning module to the network that enabled it to learn an appropriate scale factor to align the grid periodicity with the environmental temporal structure. Our findings reveal that an architecture which factorizes invariant metric representations from rapid sensory associations and a transferable policy learns, generalizes, and remembers like the brain.

Psilocybin profoundly alters visual perception, yet the neuronal mechanisms underlying these effects remain unclear. Here we combined large-scale Neuropixels recordings with cell-type specific optogenetics in head-fixed mice performing a visual change-detection task. Psilocybin severely impaired task performance without overt motor deficits. In cortex, the drug modestly suppressed activity of layer 5 neurons while preserving representations of image identity. By contrast, psilocybin imposed a 4-Hz oscillation on visually evoked activity that preferentially affected neurons encoding image change rather than image identity. Under psilocybin, expected image repetitions aberrantly recruited change-encoding ensembles and shifted cortical population dynamics towards trajectories normally evoked by genuine stimulus changes. These effects were strongest in somatostatin-expressing (SST) interneurons in visual cortex. The strength of this modulation depended on image structure and was greatest for images with clear, continuous contours, which preferentially recruited change-encoding ensembles. These findings demonstrate that psilocybin drives internally generated cortical surprise signals, providing a circuit mechanism for altered perception in the acute psychedelic state.

Neurovascular coupling (NVC) links neuronal activity to local hemodynamics, underlies functional imaging signals such as fMRI, and is often disrupted in neurological disorders. Although inhibitory interneurons can directly signal to blood vessels, their relative contribution to NVC during sensory processing remains unclear. Here, we combined mesoscale cell-type-specific calcium imaging, hemodynamic imaging, and chemogenetic silencing to determine how parvalbumin-expressing (PV) and somatostatin-expressing (SOM) interneurons shape functional hyperemia in the mouse barrel cortex. During single-whisker stimulations, PV and SOM activity exhibited strong spatial co-variation with local hemodynamic responses across the barrel field. Silencing PV interneurons produced variable changes in local hemodynamic responses that closely tracked excitatory activity while disproportionately broadening the spatial spread of the hemodynamic response, whereas SOM silencing exerted comparatively modest effects. Together, these findings suggest that NVC predominantly reflects overall circuit activity, even when inhibitory signaling is broadly impaired.

UFMylation, a ubiquitin-like protein modification, drives tau spread through the brain, but what keeps this process in check has remained unclear. We show that TRAPPC8 acts as a natural brake on UFMylation, binding directly to the E1 enzyme UBA5 to dampen pathway activity. In Alzheimer's disease brain tissue, TRAPPC8 is reduced while UFMylation is elevated, suggesting this brake fails as disease progresses. Sustaining UFMylation in human iPSC-derived neurons increased tau aggregation and spread while disrupting lysosomal function and lipid balance. Restoring TRAPPC8-UBA5 binding reversed these defects through the lysosomal protein CLN8, which restored lysosomal function and reduced tau pathology. Notably, expressing just the UBA5-binding region of TRAPPC8 was enough to suppress tau pathology in vivo, marking it as a promising therapeutic target.

Inflammatory activation and lipid remodeling are linked features of microglial states, but how inflammatory transcription factors shape microglial lipid handling is unclear. Here we show that STAT1 sets neutral-lipid content in microglia through a route not predicted by lipid-handling transcription. Acute STAT1 depletion in primary microglia lowered neutral-lipid content while lipid-uptake and lipid-storage programs were induced, and interferon-{gamma} activation moved inflammatory transcription in the opposite direction yet lowered lipid content alike. Single-cell transcriptomic and chromatin profiling of Stat1- and Irf1-deficient mice showed that STAT1 and IRF1 organize overlapping inflammatory and lipid-handling programs, with genome-wide accessibility changes that did not predict transcriptional output at individual lipid-handling loci. Microglia co-expressing STAT1 and APOE recurred across Alzheimer's disease and multiple sclerosis datasets. Transcriptional program engagement is therefore separable from cellular lipid state, and lipid-handling gene expression cannot be read as a proxy for microglial lipid content.

All physical interactions between an organism and its environment occur within the space immediately adjacent to and surrounding its body, its peripersonal space (PPS). This space has been extensively studied behaviorally in humans, and through sparse single-neuron recordings in primates. However, how PPS is represented and organized at cellular and circuit scales remains poorly understood. Here, using dense extracellular recordings in the mouse rostro-lateral visual cortex (VISrl; >19,000 single units), we reveal the cellular and circuit organization of PPS in mice. Visuo-tactile neurons prioritize near-body space while also representing farther space in a direction-selective manner, tracking approaching but not receding objects across the environment. VISrl PPS neurons integrate vision and touch nonlinearly, and their tactile responses are progressively facilitated as visual objects near the body. PPS neurons are embedded in structured networks characterized by "like-to-like" functional connectivity and remap according to recent visuo-tactile statistics. Together, these findings establish VISrl as a circuit-accessible substrate for PPS, and reveal how near-body space is represented by a dynamic, plastic, multisensory cortical network.

The corticothalamic neurons from layer 6 (L6CT) of primary sensory cortices provide extensive input to the thalamus in addition to projecting within the cortex, positioning them to play a key hypothesized role in shaping thalamocortical signaling. With the expansion of tools for precise functional identification of L6CT neurons for in-vivo electrophysiology, increasing evidence highlights L6CT neurons as dynamic gain modulators of thalamocortical sensory responses. However much of the work to date has been conducted under anesthesia and not in the context of awake and/or behaving animals. In this study, we show that L6CT neurons in the awake mouse convey information about ascending sensory inputs, the timing of which is fast enough to contribute to the sensory response of neurons throughout the thalamocortical circuit. Overall, L6CT neurons robustly encode the presence vs absence of a sensory stimulus but are relatively weak encoders of the fine details. Benchmarked against the activity of other excitatory cortical neuron, we also provide evidence for L6CT neurons as predictors of the behavioral outcome during a trained detection task. Taken together, the results in this study tie L6CT neurons to behavior in tactile detection, one of the most fundamental functional roles of the pathway.

Elucidating the neuronal circuitry that underpins memory formation is critical to understanding how organisms use past experience to guide adaptive behaviour. While memory formation has long been framed as the reactivation of a static ensemble of neurons established during initial learning, growing evidence suggests that memory traces are highly dynamic and undergo substantial reorganisation during consolidation. During the formation of auditory fear memory, initial acquisition is primarily mediated by the basolateral amygdala (BLA), whereas long-term expression relies on the medial prefrontal cortex (mPFC). However, the circuit motifs that coordinate this systemic redistribution remain poorly understood. Here, using targeted anatomical tracing and electrophysiology, we show that the reciprocal connectivity between the mPFC and BLA is organised as a parallel topography along the rostro-caudal axis. Leveraging this novel anatomical understanding of reciprocal communication between the amygdala and prefrontal cortex, we reveal an underlying circuitry mechanism by which fear memory traces are redistributed into subcortical-cortical networks after learning. Using activity-dependent engram capture and optogenetic manipulation, we demonstrate that post-learning engagement of a distinct sub-circuit linking the rostral BLA and rostral mPFC is a hallmark of the consolidated fear memory. These insights reveal that the consolidated engram requires the targeted engagement of a post-learning engram circuit, rather than a simple reactivation of neurons engaged during initial learning.

Frontal cortex neurons are sensory responsive and send long-range feedback to multiple different sensory cortices, but whether these functions are carried out by the same neurons or by distinct modality-specific circuits remains unknown. Using large-scale electrophysiology, two-photon calcium imaging, and viral circuit tracing in awake mice, we identify rich, modality-specific sensory coding in the frontal cortex (secondary motor/anterior cingulate cortex) that is largely dissociated from the neurons providing feedback to sensory cortex. Frontal cortex neurons exhibited robust sensory-evoked activity, with response magnitudes, latencies, and feature selectivity comparable to those observed in primary sensory cortex. Individual neurons displayed tuning for distinct sensory modalities, while population-level activity reliably decoded both sensory modality and stimulus identity. Anatomically, primary auditory (A1) and visual (V1) cortex axons were largely intermingled in anterior frontal cortex but more segregated in posterior regions, revealing spatial variation in the integration of sensory inputs. Frontal cortex neurons responsive to auditory stimuli were biased more anterior compared to visually-responsive neurons. Dual retrograde tracing identified distinct frontal cortex populations projecting back to A1 and V1 that were biased to the posterior and medial extent of the frontal cortex. A1- and V1-projecting frontal neurons were minimally sensory responsive, and no more likely to be responsive than other frontal neurons. Together, these findings reveal a division of labor within the frontal cortex, in which detailed sensory representations and corticocortical feedback arise from partially distinct neuronal populations. This circuit architecture provides a means through which specific sensory information can be transformed within the frontal cortex before being communicated back to the sensory cortex according to behavioral demands.

Fluid behavior requires temporal coordination across brain systems that orchestrate movement. A clear example is locomotion, in which left and right turns are not only precisely coordinated with the ongoing stepping rhythm but occur at opposite phases of the stepping cycle. The circuits underlying this coordination remain poorly understood. We discover that neuronal activity in the mouse superior colliculus, a conserved midbrain structure involved in turning behavior, is tightly phase-locked to the stepping rhythm. Notably, neurons selective for left and right turns fire at opposite phases of the stepping cycle. Moreover, this phase opposition is already evident during straight locomotion, before the animal initiates a turn. By aligning the activity of left and right turn neurons to opposite phases of the stepping cycle, the superior colliculus may create alternating windows of opportunity for left and right turns, facilitating the seamless execution of turns during locomotion.

Information handling and storage by neural circuits is thought to involve dynamic changes in the synaptic connectome, yet how this process unfolds at the level of individual synapses in vivo remains unclear. We took advantage of a well-defined thalamocortical anatomical framework to monitor identifiable individual synapses in barrel cortex during rhythmic whisker stimulation (RWS). Multiplexed ratiometric readouts from genetically targeted optical sensors showed that RWS-induced long-term potentiation (LTP) increased glutamate release per action potential in RWS-responsive axons while recruiting previously silent thalamocortical connections. Fast high-resolution imaging revealed pronounced inter-synaptic glutamate transients and global extracellular GABA waves triggered by brief RWS. LTP induction had no detectable effect on the evoked GABA signal but further enhanced glutamate crosstalk beyond thalamocortical synapses. Strikingly, neural-network simulations suggest that such volume-transmitted excitatory signals can improve associative memory retrieval in sparsely connected networks. Together, these findings uncover key plasticity features of the cortical synaptic connectome and point to a potential computational consequence of glutamate spillover for brain circuit function.

The ability to retain information over tens of seconds is essential for carrying out many routine tasks. Recurrently connected circuits are thought to support memory over these timescales, yet how they maintain and represent remembered information remains unclear. We asked whether the medial entorhinal cortex (mEC), where recurrent attractor dynamics generate grid-cell firing patterns and single toroidal attractor manifolds in two-dimensional environments, also supports low-dimensional neural activity patterns during memory retention. During a working-memory task, delay-period mEC dynamics did not show key features of grid firing in simple environments. Instead, broader mEC populations, not limited to grid cells, expressed multiple sequences and recurring activity patterns. Periodically repeating delay-period sequences retained task-relevant information, including past locations and future turn directions. These findings suggest that the mEC network generates low-dimensional dynamics more broadly, with grid-cell activity representing one manifestation and more complex manifold topologies supporting task-related representations during working memory.

Recording and manipulating brain activity during behavior is critical to understanding the underlying mechanisms of decision-making. Linking neural activity to behavior requires behavioral hardware and software tightly integrated with recording and perturbation systems on a shared clock. We built SPOUT (State-machine Platform for Operant Uni/dual-spout Tasks), an open-source, Teensy-driven state-machine platform with a MATLAB interface that runs 10 unique decision-making tasks (with dozens of variations available through user-friendly settings) to study behavior in head-restrained mice. The platform is built on several custom hardware devices: a dual-lick detector, headplate designs for optogenetics and two-photon calcium imaging, a three-axis motorized spout manipulator, and an optogenetics power modulator. The firmware differentiates between one and two lick spout tasks and can be controlled by a user-friendly interface. Task settings can be selected through the interface or by loading predefined settings files. We validated the clock speed and lick detection against an independent, external acquisition system and identified highly precise, sub-millisecond detection of single licks. Using a pseudo-random synchronization pulse generated by SPOUT, we corrected for missing data due to glitches in the acquisition system and clock drift. We showcase the versatility of SPOUT by training mice on an uninstructed lick-left/lick-right task in which the rewarded side switches unexpectedly and found that mice use history-dependent action-outcome associations to guide future behavior. Transiently inhibiting the anterior lateral motor cortex (ALM) during cue presentation induced contralateral deficits, without affecting ipsilateral trials. Finally, two-photon imaging of ALM neurons revealed stronger population responses during contralateral choice licks compared to ipsilateral ones. Together, SPOUT offers an open-source, affordable platform to study decision-making in head-restrained mice while combining neural recordings and manipulations.

Decision making is associated with frontal brain circuits and spatial navigation with the hippocampus. In addition, recent work in spatial decision making tasks found single neurons in both areas encoding space conjunctively with other task-relevant variables. However, circuit function is not determined by tuning alone, but also by representational geometry, i.e. the representation of task-relevant variables in neural state space. Here, using Neuropixel recordings in a complex spatial decision making task combined with nonlinear dimensionality reduction, we show an intrinsically low-dimensional neural manifold in medial prefrontal cortex (mPFC) on which key task variables were represented as smooth gradients. This geometry resembled the hippocampal (HPC) map. The mPFC and HPC manifolds from one mouse can predict the behavior across other mice and brain areas. A non-linear representational map between the mPFC and HPC manifolds demonstrates alignment in time. Our work suggests that the representational geometry in HPC and mPFC is distributed and time-aligned using low-dimensional neural codes.

Dopamine (DA) drives locomotion by modulating striatal activity in the dorsolateral striatum (DLS). How DA regulates motor function on subsecond timescales remains poorly understood. To address this question, we performed spectrally resolved triple-color fiber photometry, allowing us to simultaneously monitor DA, glutamatergic inputs, and pathway-specific spiny projection neuron (SPN) activity in freely moving mice during spontaneous behaviors as measured by unsupervised behavior quantifications. We showed that DA dynamics were temporally distinct from spontaneous locomotor kinematics or behavioral states. Instead, peri-event DA levels predicted SPN input-output (I/O) efficacy, defined as SPN activity relative to glutamatergic input, with opposite relationships across pathways: higher DA predicted enhanced efficacy in direct-pathway SPNs but reduced efficacy in indirect-pathway SPNs. Paired with unsupervised behavior quantification, elevating extracellular DA with methylphenidate, a DA re-uptake inhibitor, shifted direct-pathway SPNs toward higher I/O gain and indirect-pathway SPNs toward lower neuronal activity outputs, while biasing behavior toward selected mobile and turning states. Reserpine administration, which mediates DA vesicular depletion, resulted in the opposite efficacy shifts and increased occupancy of immobile states. Together, these findings support that DA does not simply encode spontaneous movement, but acts as a pathway-specific gain controller that dynamically tunes the transformation of glutamatergic input into SPN output to bias locomotor-state transitions in vivo.

B cell-derived IgG in the dorsal root ganglia (DRG) drives neuropathic pain after peripheral nerve injury (PNI), but the site of B cell organization is unclear. Here, PNI induced leukocyte clusters in the DRG meninges, enveloped by lymphatic endothelium and apposed to high endothelial venules. These clusters resemble tertiary lymphoid structures (TLSs) with germinal center-like features, including germinal center B cells and plasma cells, and follicular dendritic and follicular helper T cells. Single-cell RNA sequencing revealed enrichment of germinal center B cells in the DRG meninges after PNI. Germinal center B cells regulate TLS organization: TLSs were absent after deletion of Ezh2 from germinal center-experienced B cells. Intrathecal CD20 monoclonal antibody to locally deplete B cells also disrupted TLS organization. Conversely, intrathecal B cell transfer to B cell-deficient (muMT) mice was sufficient for TLS organization after PNI. Allodynia did not develop when TLS organization was disordered. Similar TLSs formed in pig DRG after tail docking and in human donors with chronic pain, where B cell receptor clonotype analysis confirmed functional maturity. Together, these data establish that germinal center B cells are required for TLS organization, and that disrupting this process abolishes the development of neuropathic pain after PNI.

Injury, stroke, and neurological diseases cause persistent accumulation of cellular debris that deteriorates lesion microenvironment and impedes central nervous system (CNS) repair. Debris clearance in the injured CNS has long been attributed primarily to microglia and infiltrating macrophages. Here, we identify perivascular cells as previously unrecognized phagocytes that expand after injury and exhibit robust phagocytic activity. Perivascular cell phagocytosis is conserved across multiple mouse models of CNS injury and human stroke lesions. These cells exhibit key hallmarks of phagocytosis, including LC3-associated phagocytosis for efficient lysosomal degradation. Mechanistically, phosphatidylserine serves as the eat-me signal and Axl mediates myelin debris uptake. Myelin phagocytosis drives perivascular cell proliferation, fibrosis and lesion progression. Genetic deletion of Axl in perivascular cells or pharmacological inhibition with the FDA-approved Axl inhibitor Gilteritinib reduces pathology and improves functional recovery after spinal cord injury. Together, these findings establish Axl-dependent perivascular cell phagocytosis as a therapeutic target for CNS repair.