Biology subjects

Peters, A. J.

Publications and source records attributed to Peters, A. J..

7 recordsLinked to original sources

bioRxiv2026

The basal ganglia transform visual identity into behavioral relevance

The basal ganglia are thought to be essential for transforming sensory signals into appropriate actions, yet it remains unclear how this transformation unfolds across their nuclei. We recorded neuronal activity across the striatum, globus pallidus external (GPe), and substantia nigra pars reticulata (SNr) in mice that were either naive or trained in visuomotor associations. In naive mice, visual stimuli drove responses in all three nuclei. These responses were feature-selective in the striatum but less so in GPe and SNr. Task training potentiated visual responses across the circuit, particularly for stimuli associated with movement. Training affected nuclei differently: while the striatum continued to distinguish between stimuli associated with the same behavioral action, GPe and SNr did not, responding similarly to all "Go" cues while distinguishing them from "No-Go" cues. These results demonstrate that the basal ganglia progressively transform high-dimensional sensory representations into low-dimensional signals of behavioral relevance.

neuroscience↗

bioRxiv2025

Prefrontal cortex and striatum dissociate modality and learning order in cross-modal sensorimotor learning

AO_SCPLOWBSTRACTC_SCPLOWSensorimotor learning is accompanied by the emergence and strengthening of sensory responses in the prefrontal cortex (PFC) and striatum. However, it remains unclear whether learning-evoked sensory responses in these structures are modality-specific, or whether they represent a more generalized signal for modality-independent but behaviorally relevant stimuli. To address this question, we performed widefield calcium imaging while mice were trained on sensorimotor tasks involving either visual or auditory stimuli, with mice first learning one modality and then switching to the other. We found that the anterior PFC (aPFC) exhibited a bilateral response to both visual and auditory stimuli after learning the respective tasks, indicating a generalized sensory representation. In contrast, the medial PFC (mPFC) showed modality-specific activity, responding only to contralateral visual stimuli after learning. Mice were able to learn sensorimotor associations for both modalities in sequence, and were only able to transfer learned behavior from visual to auditory stimuli but not the reverse. Despite differences in cross-modal learning transfer, cortical responses to learned stimuli were the same regardless of learning order. In contrast, electrophysiological recordings in the anterior striatum revealed that visually responsive regions became co-responsive to auditory stimuli only in mice trained on the visual task first. The additional auditory responses arose from distinct neurons rather than those previously responsive to visual stimuli, indicating that co-responsiveness occurred at the regional rather than single-neuron level. Together, these findings reveal that learned sensory responses in the PFC and striatum uniquely dissociate modality and learning order, suggesting a divergence in their roles during sensorimotor learning.

neuroscience↗

bioRxiv2025

Striatal visual responses increase prior to visuomotor learning

SO_SCPLOWUMMARYC_SCPLOWThe cortex and basal ganglia exhibit interdependent changes during learning. However, it is not clear whether plasticity occurs in sequence or concurrently across these structures. To address this question, we simultaneously recorded cortical and striatal activity while training mice on a visuomotor association task, which involved turning a wheel to move a stimulus from a cue location to a target location. Prior to the development of learned behavior, visual responses increased in the visual-recipient striatum. This was followed by the emergence of stimulus responses in both the medial prefrontal cortex (mPFC) and mPFC-recipient striatum from the onset of learned behavior. All of these regions also exhibited increased responses to stimuli in the rewarded target position, but while the visual-recipient striatum was non-selective between cue and target stimuli, the mPFC and mPFC-recipient striatum switched from being target-stimulus responsive before learning to being cue-stimulus responsive after learning. Our results suggest that sensorimotor learning involves routing stimulus information first to the sensory striatum, and then to frontal motor circuits.

neuroscience↗

bioRxiv2022

Visuomotor learning promotes visually evoked activity in the medial prefrontal cortex

The medial prefrontal cortex (mPFC) is necessary for executing many learned associations between stimuli and movement. It is unclear, however, whether activity in the mPFC reflects sensory or motor aspects of sensorimotor associations and whether it evolves gradually during learning. To address these questions, we recorded cortical activity with widefield calcium imaging while mice learned a visuomotor task. The task involved associating a visual stimulus with a forelimb movement. After learning, the mPFC showed stimulus-evoked activity both during task performance and during passive viewing, when the stimulus evoked no action. This stimulus-evoked activity closely tracked behavioral performance across training, exhibiting jumps between training days. Electrophysiological recordings localized this activity to the secondary motor and anterior cingulate cortex. We conclude that learning a visuomotor task promotes a route for visual information to reach the prefrontal cortex, which develops responses to the relevant visual stimuli even outside the context of the task.

neuroscience↗

bioRxiv2019

Striatal activity reflects cortical activity patterns

The dorsal striatum is organized into domains that drive characteristic behaviors1-7, and receive inputs from different parts of the cortex8,9 which modulate similar behaviors10-12. Striatal responses to cortical inputs, however, can be affected by changes in connection strength13-15, local striatal circuitry16,17, and thalamic inputs18,19. Therefore, it is unclear whether the pattern of activity across striatal domains mirrors that across the cortex20-23 or differs from it24-28. Here we use simultaneous large-scale recordings in the cortex and the striatum to show that striatal activity can be accurately predicted by spatiotemporal activity patterns in the cortex. The relationship between activity in the cortex and the striatum was spatially consistent with corticostriatal anatomy, and temporally consistent with a feedforward drive. Each striatal domain exhibited specific sensorimotor responses that predictably followed activity in the associated cortical regions, and the corticostriatal relationship remained unvaried during passive states or performance of a task probing visually guided behavior. However, the tasks visual stimuli and corresponding behavioral responses evoked relatively more activity in the striatum than in associated cortical regions. This increased striatal activity involved an additive offset in firing rate, which was independent of task engagement but only present in animals that had learned the task. Thus, striatal activity largely reflects patterns of cortical activity, deviating from them in a simple additive fashion for learned stimuli or actions.

neuroscience↗

bioRxiv2019

RIGBOX: AN OPEN-SOURCE TOOLBOX FOR PROBING NEURONS AND BEHAVIOR

Setting up an experiment in behavioral neuroscience is a complex process that is often managed with ad hoc solutions. To streamline this process we developed Rigbox, a high-performance, open-source software toolbox that facilitates a modular approach to designing experiments (github.com/cortex-lab/Rigbox). Rigbox simplifies hardware I/O, synchronizes data streams from multiple sources, communicates with remote databases, and implements visual and auditory stimuli presentation. Its main submodule, Signals, allows intuitive programming of behavioral tasks. Here we illustrate its function with two interactive examples: a human psychophysics experiment, and the game of Pong. We give an overview of the other packages in Rigbox, provide benchmarks, and conclude with a discussion on the extensibility of the software and comparisons with similar toolboxes. Rigbox runs in MATLAB, with Java components to handle network communication, and a C library to boost performance.

neuroscience↗

bioRxiv2017

Aberrant Cortical Activity In Multiple GCaMP6-Expressing Transgenic Mouse Lines

Transgenic mouse lines are invaluable tools for neuroscience but as with any technique, care must be taken to ensure that the tool itself does not unduly affect the system under study. Here we report aberrant electrical activity, similar to interictal spikes, and accompanying fluorescence events in some genotypes of transgenic mice expressing GCaMP6 genetically-encoded calcium sensors. These epileptiform events have been observed particularly, but not exclusively, in mice with Emx1-Cre and Ai93 transgenes, across multiple laboratories. The events occur at >0.1 Hz, are very large in amplitude (>1.0 mV local field potentials, >10% df/f widefield imaging signals), and typically cover large regions of cortex. Many properties of neuronal responses and behavior seem normal despite these events, though rare subjects exhibit overt generalized seizures. The underlying mechanisms of this phenomenon remain unclear, but we speculate about possible causes on the basis of diverse observations. We encourage researchers to be aware of these activity patterns while interpreting neuronal recordings from affected mouse lines and when considering which lines to study.

neuroscience↗