Neuropixels recordings

Animals use previous knowledge to flexibly guide behaviour, quickly learning to respond appropriately to novel stimuli, for example using rewards as a teaching signal. Task-relevant information and behavioural states are represented globally in the brain, which suggests distributed representations during sensorimotor learning. However, these brain-wide representations have been measured in distinct expert or naive animals with ”stationary” representations. It remains unclear how de novo learning of a sensorimotor transformation involves distributed, parallel activity throughout the brain. To a

Neural population dynamics are shaped by many cellular, synaptic, and network properties. Not only is it important to understand how coordinated changes in circuit parameters alter neural activity, but also when dynamics are unaffected by---or invariant to---such changes. Computational modeling has revealed invariances in single neurons and small circuits that are thought to reflect their robustness against variability and perturbations. However, generalizing these insights to larger circuits in cortex and other brain areas remains challenging. A key bottleneck lies in inverse modeling of neur

Single neurons show complex responses during cognitive tasks and dimensionality reduction has been a successful approach for finding structure in heterogeneous neural activity. When applied to neural response patterns in a population state space, where each axis represents activity of one neuron, dimensionality reduction methods often reveal low-dimensional manifolds encoding behaviorally relevant variables. Alternatively, when the same responses are viewed in a selectivity space, where each axis represents a response feature (e.g., task condition or time), dimensionality reduction methods can

Sex-steroid hormones powerfully influence internal states, mood, and social drives. In many species, including mice, females exhibit increased sexual receptivity during the peri-ovulatory phase following an estrogen surge. However, we lack understanding of how these hormones alter neural computations to regulate social behaviors, particularly their effects on neural dynamics in key regions for top-down control of social choice, such as the medial prefrontal cortex (mPFC). One potential, but unexplored role of the estrogen surge is to enable persistent neural states to facilitate costly behavio

…of display engineering, large-scale Neuropixels recordings, and computational methods,

Ongoing neural activity fluctuates over a broad range of timescales. Variations in intrinsic timescales across the forebrain relate to the functional specialization of cortical areas along the visual hierarchy [1, 2]. Furthermore, these timescales adapt to task demands, for example, during selective attention [3] and working memory [4] tasks. However, the distribution of timescales and their relationship to brain structure and behavior have not been characterized beyond the forebrain, despite the evolutionary relevance of midbrain and hindbrain areas. These areas are preserved across different

…model parameters to match experimental recordings, i.e., inverse modeling, is challenging, and often requires a trade-off between model complexity and tractability. Consequently, models often use fixed or manually tuned parameters, limiting their dynamic range and explanatory power while making cross-study

…available dataset of simultaneous Neuropixels recordings across the brain from the International Brain Laboratory collaboration. We analyzed 74

…the limitations of longitudinal recordings. Mice are first pretrained on an auditory detection task and, once expert, are transferred to a whisker-based tactile detection ta

Most brain functions rely on constant interactions among specialized brain areas. In primates, synchronized oscillations in distinct frequency bands have been suggested to facilitate the routing of feedforward and feedback signals across hierarchically organized visual areas. However, the underlying mechanisms remain largely unknown. Previous studies in mice identified two distinct visually induced gamma rhythms: a luminance-dependent narrowband high gamma rhythm (~60Hz) in both V1 and higher visual areas and a context-dependent low gamma rhythm (~30Hz) in V1. Our analysis of the open-source A

The emotional value of a stimulus shapes decision-making and drives strategic behavioral choices. This value depends on the context in which a stimulus is encountered and can be altered by internal motivational states as well as learned associations. However, due to environmental complexity, stimuli can take different emotional values in different contexts, meaning that decision-related representations must be dynamically updated to maximize positive outcomes while avoiding negative ones. This strategic flexibility relies strongly on prefrontal-cortex (PFC), with its ventral sub-division thoug

The mammalian brain continuously integrates sensory and proprioceptive information. This dynamic process enables adaptation to rapidly changing environments and is critical for perception and action selection. However, the exact underlying neuronal computations remain poorly understood, particularly in freely moving animals where behavioral and sensorial transitions are rapid. Relating neural activity to natural behavior has been technically challenging due to a lack of tools to quantify postural dynamics at ethologically relevant timescales. Furthermore, sensory systems have traditionally bee

Humans and social animals interpret the body language of others to infer intentions and adjust their actions instantaneously. To explore neural representations of conspecific kinematics during goal-directed behavior, we trained pairs of freely moving mice to jointly perform a two-alternative forced-choice task. The mice had to discriminate the location of a visual grating to earn water rewards. Using high-speed videography, we showed that mice engage in stereotypical trajectories from the trial initiation site to the chosen reward lick port across hundreds of trials. By decomposing movement in

…context-specific, by analyzing chronic Neuropixels recordings over consecutive sessions in which rats performed two related, but distinct, decision-making tasks. In

TCF7L2 is a high-confidence risk gene for neurodevelopmental disorders (NDs), but its role in their pathogenesis is unknown. It is highly expressed in the thalamus - candidate structure for NDs pathogenesis - regulating its electrophysiological maturation. To understand the role of thalamus-expressed Tcf7l2 in signal processing in thalamocortical circuits, we investigated consequences of its deficiency in the somatosensory circuit: first- and higher-order thalamic nuclei (VPM and POM) and the barrel cortex.Tcf7l2 postnatal thalamic knockout mice were used to assess signal gating mechanism in v

While sleeping, many vertebrate groups alternate between at least two sleep stages: rapid eye movement (REM) and slow wave sleep (SWS), in part characterized by wake-like and synchronous brain activity respectively. Sleep stage alternation has been implicated in learning and memory function experimentally1, and has motivated several techniques in training artificial neural networks2. If the functions ascribed to 2-stage sleep are truly general, one might expect to find similar phenomena outside the vertebrate lineage. Here we delineate neural and behavioral correlates of 2-stage sleep in octop

Understanding how the brain builds maps of novel environments on behavioral timescales (seconds-minutes) is a fundamental question for neuroscience. Theoretical works posit a Hebbian plasticity mechanism for integrating novel landmarks [1]. Drosophila have been shown to use such a mechanism to integrate novel landmarks on timescales of minutes [2,3]. However, current evidence suggests that plasticity in the medial entorhinal cortex (MEC) operates on the timescale of days [4] — leaving open the question of how the mammalian brain maps novel environments on behavioral timescales. Here we investi

Recent studies show that behaving animals transition between discrete strategies during sensory decision-making and that arousal modulates task performance. However, it remains a challenge to understand (i) the relationships between arousal and task strategy during sensory discrimination and (ii) the neural mechanisms underlying optimal performance states. To address these topics, we combined behavioral, neurophysiological, and computational approaches to uncover the neural mechanisms underlying arousal-dependent sensory discrimination. We implemented two-alternative-choice tasks, prompting mi

Drift-diffusion models have been widely used to study the neural mechanisms of decisions guided by noisy stimuli. In this framework, momentary evidence is integrated through a scalar decision variable, which has been found to correlate with spike rates in many brain areas. However, the relationship between the decision variable (i.e., accumulated evidence) and spike rate is widely assumed to be fixed over the course of a single trial, even though sensory and motor weights on spiking activity vary over time. Allowing the weight of the decision variable to be temporally inhomogeneous may capture

…Here, we report that Neuropixels recordings in mouse V1 during slow-wave sleep (SWS) reveal internally generated low-dimensional manifold structure that is mostly preserved in the awake state. However, the awake state has more variance in “off-manifold” dimensions, defined as those ex

Successful navigation requires the integration of egocentric (body-centered) and allocentric (world-centered) strategies. Previous studies have shown how these two systems could be integrated by coordinating different functional cell types in the medial entorhinal cortex (MEC): grid cells, which are thought to serve as path integrators encoding egocentric information, and landmark cells, which encode allocentric information [1]. Theoretical work has shown how landmark cells could learn to serve as an error correction mechanism to grid cells via Hebbian plasticity, and experiments have found th

Neural circuit computations are modulated by combinations of internal and external factors. For example, neurons in the medial entorhinal cortex (MEC) change their firing patterns or “remap” during a reward-seeking task, responding to changing task conditions and environmental cues. Why does this remapping occur? What unifying principles (if any) underlie remapping? Recent work proposes that remapping reflects hidden state inference—changes to an animal’s internal beliefs about the world. Recent experimental evidence suggests that remapping can indeed arise from latent behavioral or cognitive