Biology subjects

Churchland, A. K.

Publications and source records attributed to Churchland, A. K..

At least 19 recordsLinked to original sources

bioRxiv2026

Miniscope Zero: a fully wireless, single-cell-resolution miniature microscope for imaging neural dynamics in freely behaving animals

Imaging neural fluorescence dynamics during unconstrained behavior remains a major challenge in neuroscience. Head-mounted miniature one-photon microscopes enable in vivo recordings from freely behaving animals. Still, their power and data requirements typically necessitate tethers or heavy batteries, which constrain experiments and may introduce behavioral artifacts. We present Miniscope Zero, a fully wireless miniature microscope platform combining quasistatic cavity resonance (QSCR) wireless power transfer with a high-bandwidth optical data link. The system delivers >500 mW of receiver power across a 2,500 cm2 behavioral arena and streams imaging data at 8 Mbps, supporting real-time data acquisition. Miniscope Zero provides a typical field of view of 600 m x 600 m and a 2.6-fold higher light-collection efficiency than the UCLA Miniscope v4. We demonstrate wireless CA1 GCaMP6f recordings during open-field navigation, enclosed-maze exploration, simultaneous multi-animal imaging, and extended three-dimensional behavior, enabling long-duration cellular-resolution imaging without tether-induced constraints.

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bioRxiv2025

Altered Use of Prior Expectations and Modified Neural Dynamics in a Mouse Model of Autism

In dynamic environments, updating beliefs based on past experiences (priors) is essential for optimal decision-making. Prior utilization is often impaired in psychiatric disorders, affecting perception and behavior. We investigate how Neurexin1 (Nrxn1 ) loss-of-function disrupts this process, providing insight into circuit deficits underlying sensorimotor dysfunction. While the synaptic role of Nrxn1 role is well studied, its impact on network dynamics and decision-making behavior remain unclear. Using widefield calcium imaging, we assess cortex-wide activity in mice performing a two-choice task to probe how priors influence visually-guided decisions. This task requires the mouse to combine sensory evidence with the prior probability over the stimulus side. We find Nrxn1 KO mice underutilized priors and were slower to update choices based on feedback. During decision-making, cortex-wide cortical activity is both elevated and increasingly correlated in Nrxn1 KO mice, independent of task period. Moreover, a larger fraction of cortical variance was explained by movement variables, consistent with stronger coupling of cortical activity to motor signals and a bias toward movement-related dynamics. These findings suggest that core computations underlying decision-making, such as integrating past experience with current evidence, depend on intact synaptic mechanisms shaped by genes like Nrxn1.

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bioRxiv2025

Age-related changes in behavioral and neural variability in a decision-making task

Age-related cognitive decline in learning and decision-making may arise from increased variability of neural responses. Here, we investigated how ageing affects behavioural and neural variability by recording >18,000 neurons across 16 brain regions (including cortex, hippocampus, thalamus, midbrain, and basal ganglia) in younger and older mice performing a visual decision-making task. Older mice showed more variable response times, reproducing a common finding in human ageing studies. Ageing globally increased firing rates and post-stimulus neural variability (quantified using the Fano factor), and decreased variability quenching-the reduction in neural variability upon stimulus presentation. Older animals showed higher overall firing rates across areas of visual and motor cortex, striatum, midbrain, and hippocampus, but lower firing rates in thalamic areas. Age-related attenuation in stimulus-induced variability quenching was most prominent in visual and motor cortex, striatum, and thalamic area. These findings show how large-scale neural recordings can help uncover regional specificity of ageing effects in single neurons, ultimately improving our understanding of the neural basis of age-related cognitive decline.

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bioRxiv2025

Anterior cingulate cortex mixes retrospective cognitive signals and ongoing movement signatures during decision-making

In dynamic environments, animals must closely monitor the effects of their actions to inform switches in behavioral strategy. Anterior cingulate cortex (ACC) neurons track decision outcomes in these environments. Yet, it remains unclear whether ACC neurons similarly monitor behavioral history in static environments and, if so, whether these signals are distinct from movement representations. We recorded large-scale ACC activity in freely moving mice making visual evidence-accumulation decisions. Many ACC neurons exhibited nonlinear mixed selectivity for previous choices and outcomes (trial history) and were modulated by movements. Trial history could be stably decoded from population activity and accounted for a separable component of neural activity than posture and movements. Trial history encoding was conserved across different subjects and was unaffected by fluctuating behavioral biases. These findings demonstrate that trial history monitoring in ACC is implemented in a conserved population code that is independent of the volatility of subjects task environment.

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bioRxiv2024

Interactive data exploration websites for large-scale electrophysiology

Methodological advances in neuroscience have enabled the collection of massive datasets which demand innovative approaches for scientific communication. Existing platforms for data storage lack intuitive tools for data exploration, limiting our ability to interact effectively with these brain-wide datasets. We introduce two public websites: (Data and Atlas) developed for the International Brain Laboratory which provide access to millions of behavioral trials and hundreds of thousands of individual neurons. These interfaces allow users to discover both the raw and processed brain-wide data released by the IBL at the scale of the whole brain, individual sessions, trials, and neurons. By hosting these data interfaces as websites they are available cross-platform with no installation. By releasing each sites code as a modular open-source framework, other researchers can easily develop their own web interfaces and explore their own data. As neuroscience datasets continue to expand, customizable web interfaces offer a glimpse into a future of streamlined data exploration and act as blueprints for future tools.

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bioRxiv2023

Large scale, simultaneous chronic neural recordings from multiple brain areas

Understanding how brain activity is related to animal behavior requires measuring multi-area interactions on multiple timescales. However, methods to perform chronic, simultaneous recordings of neural activity from many brain areas are lacking. Here, we introduce a novel approach for independent chronic probe implantation that enables flexible, simultaneous interrogation of neural activity from many brain regions during head restrained or freely moving behavior. The approach, that we called indie (independent dovetail implants for electrophysiology), enables repeated retrieval and reimplantation of probes. The chronic implantation approach can be combined with other modalities such as skull clearing for cortex wide access and optogenetics with optic fibers. Using this approach, we implanted 6 probes chronically in one hemisphere of the mouse brain. The implant is lightweight, allows flexible targeting with different angles, and offers enhanced stability. Our approach broadens the applications of chronic recording while retaining its main advantages over acute recordings (superior stability, longitudinal monitoring of activity and freely moving interrogations) and provides an appealing venue to study processes not accessible by acute methods, such as the neural substrate of learning across multiple areas.

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bioRxiv2023

DREDge: robust motion correction for high-density extracellular recordings across species

High-density microelectrode arrays (MEAs) have opened new possibilities for systems neuroscience in human and non-human animals, but brain tissue motion relative to the array poses a challenge for downstream analyses, particularly in human recordings. We introduce DREDge (Decentralized Registration of Electrophysiology Data), a robust algorithm which is well suited for the registration of noisy, nonstationary extracellular electrophysiology recordings. In addition to estimating motion from spikes in the action potential (AP) frequency band, DREDge enables automated tracking of motion at high temporal resolution in the local field potential (LFP) frequency band. In human intraoperative recordings, which often feature fast (period <1s) motion, DREDge correction in the LFP band enabled reliable recovery of evoked potentials, and significantly reduced single-unit spike shape variability and spike sorting error. Applying DREDge to recordings made during deep probe insertions in nonhuman primates demonstrated the possibility of tracking probe motion of centimeters across several brain regions while simultaneously mapping single unit electrophysiological features. DREDge reliably delivered improved motion correction in acute mouse recordings, especially in those made with an recent ultra-high density probe. We also implemented a procedure for applying DREDge to recordings made across tens of days in chronic implantations in mice, reliably yielding stable motion tracking despite changes in neural activity across experimental sessions. Together, these advances enable automated, scalable registration of electrophysiological data across multiple species, probe types, and drift cases, providing a stable foundation for downstream scientific analyses of these rich datasets.

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bioRxiv2023

Reusable, flexible, and lightweight chronic implants for Neuropixels probes

Electrophysiology has proven invaluable to record neural activity, and the development of Neuropixels probes dramatically increased the number of recorded neurons. These probes are often implanted acutely, but acute recordings cannot be performed in freely moving animals and the recorded neurons cannot be tracked across days. To study key behaviors such as navigation, learning, and memory formation, the probes must be implanted chronically. An ideal chronic implant should (1) allow stable recordings of neurons for weeks; (2) allow reuse of the probes after explantation; (3) be light enough for use in mice. Here, we present the "Apollo Implant", an open-source and editable device that meets these criteria and accommodates up to two Neuropixels 1.0 or 2.0 probes. The implant comprises a "payload" module which is attached to the probe and is recoverable, and a "docking" module which is cemented to the skull. The design is adjustable, making it easy to change the distance between probes, the angle of insertion, and the depth of insertion. We tested the implant across eight labs in head-fixed mice, freely moving mice, and freely moving rats. The number of neurons recorded across days was stable, even after repeated implantations of the same probe. The Apollo implant provides an inexpensive, lightweight, and flexible solution for reusable chronic Neuropixels recordings.

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bioRxiv2023

A Brain-Wide Map of Neural Activity during Complex Behaviour

A key challenge in neuroscience is understanding how neurons in hundreds of interconnected brain regions integrate sensory inputs with prior expectations to initiate movements and thereby make decisions. It is difficult to meet this challenge if different laboratories apply different analyses to different recordings in different regions during different behaviours. Here, we report a comprehensive set of recordings from 621733 neurons across 139 mice in 12 labs performing a decision-making task with sensory, motor, and cognitive components, obtained with 699 Neuropixels probe insertions covering 279 brain areas in the left forebrain and midbrain and the right hindbrain and cerebellum. We provide an initial appraisal of this brain-wide map, assessing how neural activity encoded key task variables. Representations of visual stimuli appeared transiently in classical visual areas after stimulus onset and then spread to ramp-like activity in a collection of mid- and hindbrain regions that also encoded choices. Neural responses correlated with motor action almost everywhere in the brain. Responses to reward delivery and consumption versus negative feedback were also widespread. This publicly available dataset represents an unprecedented resource for understanding how computations distributed across and within brain areas drive behaviour.

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bioRxiv2023

Brain-wide representations of prior information in mouse decision-making

The neural representations of prior information about the state of the world are poorly understood. To investigate them, we examined brain-wide Neuropixels recordings and widefield calcium imaging collected by the International Brain Laboratory. Mice were trained to indicate the location of a visual grating stimulus, which appeared on the left or right with prior probability alternating between 0.2 and 0.8 in blocks of variable length. We found that mice estimate this prior probability and thereby improve their decision accuracy. Furthermore, we report that this subjective prior is encoded in at least 20% to 30% of brain regions which, remarkably, span all levels of processing, from early sensory areas (LGd, VISp) to motor regions (MOs, MOp, GRN) and high level cortical regions (ACAd, ORBvl). This widespread representation of the prior is consistent with a neural model of Bayesian inference involving loops between areas, as opposed to a model in which the prior is incorporated only in decision-making areas. This study offers the first brain-wide perspective on prior encoding at cellular resolution, underscoring the importance of using large scale recordings on a single standardized task.

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bioRxiv2023

Engaged decision-makers align spontaneous movements to stereotyped task demands

Existing work demonstrates that animals alternate between engaged and disengaged states during perceptual decision-making. To understand the neural signature of these states, we performed cortex-wide measurements of neural activity in mice making auditory decisions. The trial-averaged magnitude of neural activity was similar in the two states. However, the trial-to-trial variance in neural activity was higher during disengagement. To understand this increased variance, we trained separate linear encoding models on neural data from each state. The models demonstrated that although task variables and task-aligned movements impacted neural activity similarly during the two states, movements that are independent of task events explained more variance during disengagement. Behavioral analyses uncovered that during disengagement, movements become uncoupled to task events. Taken together, these results argue that the neural signature of disengagement, though obscured in trial-averaged neural activity, is evident in trial-to-trial variability driven by changing patterns of spontaneous movements.

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bioRxiv2022

Reproducibility of in-vivo electrophysiological measurements in mice

Understanding brain function relies on the collective work of many labs generating reproducible results. However, reproducibility has not been systematically assessed within the context of electrophysiological recordings during cognitive behaviors. To address this, we formed a multi-lab collaboration using a shared, open-source behavioral task and experimental apparatus. Experimenters in ten laboratories repeatedly targeted Neuropixels probes to the same location (spanning secondary visual areas, hippocampus, and thalamus) in mice making decisions; this generated a total of 121 experimental replicates, a unique dataset for evaluating reproducibility of electrophysiology experiments. Despite standardizing both behavioral and electrophysiological procedures, some experimental outcomes were highly variable. A closer analysis uncovered that variability in electrode targeting hindered reproducibility, as did the limited statistical power of some routinely used electrophysiological analyses, such as single-neuron tests of modulation by individual task parameters. Reproducibility was enhanced by histological and electrophysiological quality-control criteria. Our observations suggest that data from systems neuroscience is vulnerable to a lack of reproducibility, but that across-lab standardization, including metrics we propose, can serve to mitigate this.

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bioRxiv2022

Two roles for choice selective inhibition in decision-making circuits

During perceptual decision-making, the firing rates of cortical neurons reflect upcoming choices. Recent work showed that excitatory and inhibitory neurons are equally selective for choice. However, functional consequences of inhibitory choice selectivity in decision-making circuits are unknown. We developed a circuit model of decision-making which accounts for the specificity of inputs to and outputs from inhibitory neurons. We found that selective inhibition expands the space of circuits supporting decision-making, allowing for weaker or stronger recurrent excitation when connected in a competitive or feedback motif. The specificity of inhibitory outputs sets the trade-off between speed and accuracy of decisions by altering the attractor dynamics in the circuit. Recurrent neural networks trained to make decisions display the same dependence on inhibitory specificity and the strength of recurrent excitation. Our results reveal two concurrent roles for selective inhibition in decision-making circuits: stabilizing strongly connected excitatory populations and maximizing competition between oppositely selective populations.

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bioRxiv2021

Pyramidal cell types drive functionally distinct cortical activity patterns during decision-making

Understanding how cortical circuits generate complex behavior requires investigating the cell types that comprise them. Functional differences across pyramidal neuron (PyN) types have been observed within cortical areas, but it is not known whether these local differences extend throughout the cortex, nor whether additional differences emerge when larger-scale dynamics are considered. We used genetic and retrograde labeling to target pyramidal tract (PT), intratelencephalic (IT) and corticostriatal projection neurons and measured their cortex-wide activity. Each PyN type drove unique neural dynamics, both at the local and cortex-wide scale. Cortical activity and optogenetic inactivation during an auditory decision task also revealed distinct functional roles: all PyNs in parietal cortex were recruited during perception of the auditory stimulus, but, surprisingly, PT neurons had the largest causal role. In frontal cortex, all PyNs were required for accurate choices but showed distinct choice-tuning. Our results reveal that rich, cell-type-specific cortical dynamics shape perceptual decisions.

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bioRxiv2020

Mice alternate between discrete strategies during perceptual decision-making

Classical models of perceptual decision-making assume that subjects use a single, consistent strategy to form decisions, or that strategies evolve slowly over time. Here we present new analyses suggesting that this common view is incorrect. We analyzed data from mouse and human decision-making experiments and found that choice behavior relies on an interplay between multiple interleaved strategies. These strategies, characterized by states in a hidden Markov model, persist for tens to hundreds of trials before switching, and may alternate multiple times within a session. The identified mouse decision-making strategies were highly consistent across individuals and comprised a single "engaged" state, in which decisions relied heavily on the sensory stimulus, and several biased states in which errors frequently occurred. These results provide a powerful alternate explanation for "lapses" often observed in rodent psychophysical experiments, and suggest that standard measures of performance mask the presence of dramatic changes in strategy across trials.

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bioRxiv2020

Citric Acid water as an alternative to water scheduling in behaving mice

AO_SCPLOWBSTRACTC_SCPLOWPowerful neural measurement and perturbation tools have positioned mice as an ideal species for probing the neural circuit mechanisms of cognition. Crucial to this success is the ability to motivate animals to perform specific behaviors. One successful strategy is to restrict their water intake, rewarding them with water during a behavioral task. However, water restriction requires rigorous monitoring of animals health and hydration status and can be challenging for some mice. We present an alternative that allows mice more control over their water intake: free home-cage access to water, made slightly sour by a small amount of citric acid (CA). In a previous study, rats with free access to CA water readily performed a behavioral task for water rewards, although completing fewer trials than under water restriction (Reinagel, 2018). We here extend this approach to mice and confirm its robustness across multiple laboratories. Mice reduced their intake of CA water while maintaining healthy weights. Continuous home-cage access to CA water only subtly impacted their willingness to perform a decision-making task, in which they were rewarded with sweetened water. When free CA water was used instead of water restriction only on weekends, learning and decision-making behavior were unaffected. CA water is thus a promising alternative to water restriction, allowing animals more control over their water intake without interfering with behavioral performance. SO_SCPLOWIGNIFICANCEC_SCPLOW SO_SCPLOWTATEMENTC_SCPLOWHigh-throughput, reliable behavioral training is a key requirement for the use of mice in behavioral and systems neuroscience, but depends crucially on ability to motivate animals to perform specific behaviors. Here, we present an alternative method to commonly used methods of water restriction: free home-cage access to water, made slightly sour by a small amount of citric acid. This non-labor-intensive, low-error option benefits animal health without hindering behavioral training progress. Citric acid water can serve as a reliable and standardized strategy to achieve high quality task behavior, further facilitating the use of mice in high-throughput behavioral studies.

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bioRxiv2020

A standardized and reproducible method to measure decision-making in mice

Progress in science requires standardized assays whose results can be readily shared, compared, and reproduced across laboratories. Reproducibility, however, has been a concern in neuroscience, particularly for measurements of mouse behavior. Here we show that a standardized task to probe decision-making in mice produces reproducible results across multiple laboratories. We designed a task for head-fixed mice that combines established assays of perceptual and value-based decision making, and we standardized training protocol and experimental hardware, software, and procedures. We trained 140 mice across seven laboratories in three countries, and we collected 5 million mouse choices into a publicly available database. Learning speed was variable across mice and laboratories, but once training was complete there were no significant differences in behavior across laboratories. Mice in different laboratories adopted similar reliance on visual stimuli, on past successes and failures, and on estimates of stimulus prior probability to guide their choices. These results reveal that a complex mouse behavior can be successfully reproduced across multiple laboratories. They establish a standard for reproducible rodent behavior, and provide an unprecedented dataset and open-access tools to study decision-making in mice. More generally, they indicate a path towards achieving reproducibility in neuroscience through collaborative open-science approaches.

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bioRxiv2019

Data architecture and visualization for a large-scale neuroscience collaboration

Effective data management is a major challenge for neuroscience labs, and even greater for collaborative projects. In the International Brain laboratory (IBL), ten experimental labs spanning 7 geographically distributed sites measure neural activity across the brains of mice making perceptual decisions. Here, we report a novel, modular architecture that allows users to contribute, access, and analyze data across this collaboration. Users contribute data using a web-based electronic lab notebook (Alyx), which automatically registers recorded data files and uploads them to a central server. Users access data with a lightweight interface, the Open Neurophysiology Environment (ONE), which searches data from all labs and loads it into MATLAB or Python. To analyze data, we have developed pipelines based on DataJoint, which automatically populate a website displaying a graphical summary of results to date. This architecture provides a new framework to contribute, access and analyze data, surmounting many challenges currently faced by neuroscientists.

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