Neuron

Humans are remarkable at adapting to changing norms, yet we know little about how the human brain encodes these social signals at the single neuron level. Here, we recorded the activity of single neurons in the substantia nigra and globus pallidus in neurosurgical participants as they played an iterative ultimatum game versus human and computer avatars. Using computational modeling of behavior, we found that putative dopaminergic units in the substantia nigra tracked the valence of norm prediction errors, with greater encoding during gameplay with human versus computer avatars. Analogous analyses in the globus pallidus, a nucleus adjacent to the substantia nigra, found no significant effect. Our results identify a novel role for the substantia nigra in encoding social learning signals.

Decisions often involve trade-offs between benefits and costs, such as a small payment now vs. a larger payment after a delay. Although decision variables are distributed across frontal cortex, how these regions transform competing attributes into a choice remains unclear. Combining large-scale electrophysiology with causal perturbations as mice chose between different reward amounts and delays, we found that population geometry of decision variables differed across regions, reflecting distinct computations. Dorsal frontal areas, including motor cortex, collapsed competing attributes onto a decision axis shared across reward-delay contexts, with projection amplitude predicting choice probability; silencing these areas impaired action selection regardless of delay. In contrast, ventral prefrontal cortex (vPFC) represented choice in higher-dimensional subspaces organized by reward delay, whose geometry predicted how strongly delay influenced choice. Notably, inhibiting vPFC preserved the dorsal decision representation but selectively removed its modulation by reward delay, causing animals to behave as if delay no longer influenced choice. vPFC inhibition had no effect when mice chose between reward amounts. Frontal cortex therefore solves multi-attribute decisions through a generator-modulator architecture: dorsal frontal circuits maintain a shared choice axis guiding decisions across contexts, whereas vPFC maintains competing attributes in distinct subspaces that modulate decisions when options conflict.

Circulating RNA can capture molecular variation associated with amyotrophic lateral sclerosis (ALS) progression, but biofluid heterogeneity makes biologically organized signals difficult to recover. Here, we paired microRNA (miRNA) and messenger RNA (mRNA) profiles from glutamate-aspartate transporter (GLAST)-positive small extracellular-vesicles (sEVs) to estimate survival time and identify survival-associated programs. In 45 participants with ALS and 15 controls, biologically constrained multi-omic factor analysis identified a program in which reciprocal miRNA-mRNA states among target-supported pairs tracked survival. The miRNA arm was then evaluated in an independent total-plasma cohort of 248 participants with ALS, refining a five-miRNA panel that added prognostic information beyond functional decline and neurofilament light chain, particularly over longer survival horizons. The mRNA arm was evaluated across 586 cortical profiles from 308 donors and 527,261 nuclei from 69 donors, identifying a five-gene core associated with glial reactivity, vascular programs and reduced myelinating identity. Together, these findings establish a framework for integrating regulatory RNA layers in circulation to identify clinically relevant programs and relate them to disease-relevant cellular states.

Phasic ensemble bursting in subcortical neuromodulatory systems such as the basal forebrain (BF) provides a powerful format for broadcasting reward-prediction signals. These bursts encode reward prediction by varying population amplitude, yet their internal structure, reflected in cell-to-cell amplitude relationships, remains conserved. How neural circuits reconcile these competing constraints remains unknown. Here we show that BF bursting is generated by a dynamical attractor: burst structure is imposed not by feedforward inputs but by recurrent circuit dynamics, while burst amplitude is determined by approximately linear integration across concurrent inputs. Optogenetic activation of BF neurons expressing natriuretic peptide receptor 3 (Npr3) outside the behavioral task reproduced the low-dimensional dynamics of natural cue-evoked bursting, preserving the temporal envelope and cell-to-cell amplitude relationships across stimulation patterns. Critically, unilateral activation of non-overlapping Npr3 populations in either hemisphere recruited the full bilateral ensemble into the same native trajectory, showing that restricted inputs can nevertheless recruit the full ensemble. Matched ipsilateral and contralateral onset latencies exceeding 25 ms implicated recurrent interactions beyond the BF. Despite the conserved structure, population burst amplitude varied with stimulation strength and summed approximately linearly across concurrent unilateral inputs. This linear summation extended to natural sensory input during behavior: adding Npr3 stimulation to auditory cues increased cue-evoked burst amplitude, improved detection, and reduced subsequent reward responses, consistent with stronger reward prediction producing smaller reward prediction errors. Thus, a low-dimensional dynamical attractor preserves a shared BF burst structure across diverse inputs while integrating concurrent inputs into a scalar burst amplitude that encodes reward prediction.

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.

Phasic reward prediction signals in ventral tegmental area (VTA) dopamine (DA) neurons and basal forebrain (BF) noncholinergic bursting neurons are remarkably similar despite the distinct circuit organizations and functions of the two systems. Whether this similarity reflects independent computation within each system, inheritance from common upstream circuitry, or causal propagation from one system to the other remains unknown. Here we show that reward prediction signals are tightly coordinated across these two systems, with VTA DA activity causally driving BF bursting neurons on a millisecond timescale. Simultaneous recordings from freely moving rats revealed strong coupling between putative DA neurons and BF bursting neurons on individual trials, both in response amplitude and spike timing. DA activity consistently preceded BF bursting neuron activity by approximately 10 ms across well-trained behavior, learning, and even outside overt task events. In DAT-Cre mice, optogenetic activation of VTA DA neurons rapidly recruited BF bursting neurons at latencies matching those observed during natural DA-BF coupling, while activation of their BF terminals produced responses at still shorter latencies. Conversely, inhibition of DA neurons or their BF terminals suppressed both cue-evoked and, notably, ongoing activity in a substantial subset of BF bursting neurons. Fast DA-evoked BF recruitment persisted after D1/D2 receptor blockade, and anatomical tracing identified glutamatergic DA-to-BF synapses, supporting glutamate co-release as a candidate substrate. Together, these findings reveal a previously unrecognized causal link that enables rapid propagation of reward prediction signals between functionally distinct subcortical systems.

Neuromodulatory systems project broadly, yet computations engage specific neuronal populations. Whether neuromodulation can selectively influence task-engaged neurons remains unclear. During goal-directed navigation, neurons in the locus coeruleus (LC), the brain's principal norepinephrine source, responded at navigation onset. Concurrently, dopamine transients arose in micrometer-scale domains around LC axons in CA1. These transients preferentially enhanced nearby CA1 neurons with ramping dynamics, whose higher activity predicted later reward-anticipatory action. Brief LC activation evoked local dopamine, enhanced ramping dynamics, and delayed action initiation seconds later. Blocking D1-like, but not adrenergic, receptors weakened ramping dynamics and impaired reward anticipation. Modeling showed that selectivity can emerge when localized dopamine coincides with strong ongoing neuronal activity, without dedicated wiring. Thus, a widely projecting system can selectively modulate task-engaged neurons and shape behavior.

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.

Animals learn to select actions that maximize reward in complex environments. A central challenge in this process is credit routing: behavioral outcomes must be routed back to the neural populations that contributed to generating the relevant actions. One possible route is through thalamocortical pathways conveying learning signals from the basal ganglia and cerebellum, where plasticity is shaped by reward-prediction errors. However, how these pathways route such signals back to specific cortical circuits remains unclear. To address this question, we combined anatomical circuit mapping in mice with closed-loop circuit modeling. Anterograde transsynaptic tracing revealed that thalamic neurons receiving input from the substantia nigra pars reticulata or the lateral cerebellar nucleus were largely segregated, with partial overlap in the ventromedial thalamus. Nevertheless, their cortical axons shared a pronounced enrichment in layer 1a, most prominently in secondary motor cortex. In a brain- wide synergistic loop-circuit model, learning was enhanced when both pathways delivered additive and gain-modulating feedback aligned with the cortical action readout. Local activity- based calibration established this alignment, whereas dendritic-spike- and reward-prediction- error-dependent thalamocortical plasticity further refined behavioral output. Module-specific feedback was essential for a brain-machine interface task requiring the simultaneous conditioning of multiple target neurons. Together, these findings define a credit-routing architecture in which laminar convergence, plastic alignment, and modular feedback link parallel subcortical learning systems to cortical action representations.

Successful navigation requires the integration of self-motion signals with spatial representations, yet the circuits that provide velocity information necessary for stable grid cell firing remain incompletely understood. Here, we identify medial septal (MS) glutamatergic neurons as a critical component of this pathway. Using cell-type-specific optogenetic silencing combined with in vivo electrophysiology in freely moving mice, we show that MS glutamatergic neurons support the fidelity of firing rate-based speed coding in the medial entorhinal cortex (MEC). Silencing this population reduced grid cell spatial periodicity and stability and produced distortions of grid firing fields. Silencing also reduced theta phase-locking strength in strongly theta-modulated MEC neurons. Model simulations of a hybrid oscillatory interference-continuous attractor network with reductions in speed-signal fidelity disrupted grid periodicity and reproduced features of the spatial distortions observed in vivo. Together, these findings identify a septo-entorhinal circuit that coordinates self-motion information with the spatial and temporal organization of MEC activity to maintain a stable neural representation of space.

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.

Neuronal pathology plays a prominent role in the cognitive and neuropathic symptoms of multiple sclerosis; however, little is known about these pathological signals to neurons in the brain and their consequences on cognition. Here, using a transgenic reporter of IFN signaling with spatial RNA-sequencing, we determined myelin-specific autoimmune T cells enter the brain parenchyma through the interface between the fimbria and third ventricle. Here, astrocytes and microglia express high levels of MHC-II-associated transcripts. Using this reporter, we also showed microglia within the brain are not direct responders of IFNs, but express transcripts associated with synaptic pruning, potentially contributing to pathological remodeling of neuronal circuits. Moreover, both type-I and type-II IFNs are required for T cells to infiltrate the brain and initiate an IFN response associated with synaptic and metabolic programs in neurons and astrocytes in the cortex and hippocampus. In summary, this study elucidates multiple steps of the pathogenesis of EAE pathology within the brain independent of the spinal cord.

Learning about potential threats is indispensable for survival, and its deficits underlie numerous neuropsychiatric disorders. Human brain imaging suggests the anterior insular cortex (AIC) as a key neural correlate of threat learning, yet its mechanistic role remains unclear. Leveraging multimodal systems neuroscience approaches, we demonstrate that AIC excitatory neurons, specifically layer 5 pyramidal neurons projecting to the basolateral amygdala, are essential for higher-order threat learning/memory. They are specifically required when a predictor is temporally separated from an aversive event or when the predictive information is embedded within a diffuse context. In contrast, the AIC is dispensable for elementary, temporally contiguous threat learning. Surprisingly, while the AIC promotes memory formation, it also constrains the level of fear expression during retrieval in a context-dependent manner. This bidirectional control is mediated by the recruitment of distinct AIC neuronal ensembles. Together, we identify a novel circuit mechanism for bidirectional regulation of higher-order threat learning/memory.

Substantia nigra pars compacta (SNc) dopaminergic neurons integrate synaptic inputs through dendrites that project laterally within the SNc and ventrally into the substantia nigra pars reticulata (SNr), which then determines dopaminergic output. We use spatially-specific optogenetics to map excitatory subthalamic nucleus (STN) and pedunculopontine nucleus (PPN) as well as inhibitory SNr inputs that provide feedforward inhibition onto SNc neurons. Using multiple GABAergic mouse lines, we find that SNr inputs selectively inhibit SNc somas and proximal dendrites without preference for SNr versus SNc dendrites. Using glutamatergic mouse lines, we find that PPN inputs selectively excite somas and proximal dendrites, while STN inputs selectively excite SNr dendrites, mirroring dendrite-selective inhibition from striosomes. These findings reveal a high level of spatial organization in SNc synaptic inputs and point to separate functional roles for STN versus PPN control of dopaminergic activity. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=147 SRC="FIGDIR/small/742307v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@ac8c5borg.highwire.dtl.DTLVardef@32cb89org.highwire.dtl.DTLVardef@d08f79org.highwire.dtl.DTLVardef@7b546d_HPS_FORMAT_FIGEXP M_FIG C_FIG

To understand neural computations, one would like to relate circuit dynamics to neuronal intrinsic excitability and connectivity. We developed tools for large-scale all-optical electrophysiology and applied them to approximately 300 layer 1 interneurons per mouse in vivo. Across two mice, targeted stimulation and voltage imaging identified 1,469 inhibitory and 5,752 directed electrical connections among 14,312 tested pairs. Presynaptic identity was more strongly associated with inhibitory post-synaptic potential (IPSP) amplitude, whereas postsynaptic identity was more strongly associated with IPSP decay time. Gap junctional and synaptic interactions had distinct spatiotemporal kernels, with corresponding signatures in spontaneous activity. Excitability measured under optogenetic stimulus predicted spiking responses to subthreshold voltage, depolarization rate, and spike history during spontaneous firing. Genetic subtypes also showed different behavioral-state-dependent voltage-to-spike relationships despite similar population-average subthreshold voltages. These measurements link cellular properties and pairwise interactions to spontaneous circuit dynamics, establishing an approach for functional circuit mapping in vivo.

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.

Cortical glutamatergic neurons are generated through temporally ordered developmental programs that link neuronal birthdate to laminar position and identity. Yet, because differentiation continues after cell-cycle exit, it remains unclear how far post-mitotic identity can be reshaped by the environment and whether this residual competence varies across neuronal types. Here, we used transplantation to uncouple birthdate from final laminar position by placing newborn neurons in ectopic laminae in the postnatal mouse cortex. E13-born (i.e. deep layer-destined) and E15-born (i.e. superficial layer-destined) donor neurons displayed distinct birthdate-associated molecular programs before transplantation. After grafting into P0 hosts, both populations migrated and settled across cortical layers, enabling comparison across laminar environments. We simultaneously profiled transcriptomic, morphological and electrophysiological neuronal identities using Patch-seq. Transplanted neurons developed pyramidal morphologies and active membrane properties, but their final identity was not imposed by their laminar position. Thus, the postnatal cortex supports integration and maturation but does not impose canonical laminar identity. Critically, neuronal competence was asymmetric across birthdates. E15-born neurons remained committed toward a robust superficial layer neuron-like profile independently of cortical position, whereas E13-born neurons retained a broad, non-canonical differentiation rather than either converging on a deep- or superficial-layer reference state. This is consistent with the wider intrinsic repertoire of early-born neurons, which the postnatal environment does not resolve. Thus, post-mitotic identity is constrained by developmental history in a birthdate-dependent manner, with early- and late-born neurons retaining fundamentally different differentiation potentials after cell-cycle exit.

Human and non-human infants can form memories for events, but these memories are not successfully consolidated into remote memory. While the neurobiological basis of this phenomenon-known as infantile amnesia-remains unclear, it is hypothesized that the neural circuits required for successful consolidation are insufficiently mature. Here we find that heightened activity in the prelimbic cortex of developing mice triggers a sequalae of maturational steps that culminates in adult-like memory persistence: Activity-dependent increases in brain-derived neurotrophic factor (BDNF) promote myelination of prelimbic circuits via activation of tyrosine kinase receptor B (TrkB) receptors on oligodendrocyte precursor cells (OPCs). Inhibiting any of these steps within a critical developmental window delays the offset of infantile amnesia, whereas promoting this sequalae results in the precocial emergence of memory persistence. Similar to critical periods in sensory cortices, our results indicate that developmental myelination is required for proper circuit maturation and emergence of adult-like memory function.