Biology subjects

Petersen, R. S.

Publications and source records attributed to Petersen, R. S..

4 recordsLinked to original sources

bioRxiv2025

Efficient mixed representation of active and passive motion in the mouse visual thalamus during natural behaviour

Most retinal motion is generated by the observer's movements. These are often self-generated (active) but can also arise from external forces such as gravity (passive). Active movements modulate spontaneous and visually evoked activity throughout the visual system, providing neural circuits with information about behavioural state. By contrast, much less is known about how visual circuits represent passive movements. Critically, it remains unclear whether the retina-recipient thalamus tracks passive motion and, if so, whether this representation is separable from active motion. To address these questions, we developed a paradigm that dissociates active and passive motion in freely moving mice and used it to examine their effects on neural activity. Mice actively explored an arena while intermittent floor tilts induced passive movement. By combining 3D reconstructions of animal pose and arena motion, we quantified active and passive linear and angular motion independently, even when they occurred simultaneously. We found that neurons in the dorsal lateral geniculate nucleus (dLGN) and surrounding regions tracked combinations of active and passive motion signals both in the dark and during visual stimulation. Individual neurons differentially weighted active and passive motion signals. This diversity enabled active and passive motion signals to be linearly decoded and partially separated from population activity, while recurrent dynamics retained passive motion information over timescales of several seconds. These findings identify a coding strategy through which early visual circuits integrate active and passive motion into an estimate of self-motion while preserving information about whether visual inputs arise from self-generated or externally imposed movements.

neuroscience↗

bioRxiv2024

Embodied processing in whisker somatosensory cortex during exploratory behaviour in freely moving mice

Sensory systems have evolved to solve computational challenges that animals face during behaviour in their natural environments. To illuminate how sensory cortex operates under such conditions, we investigated the function of neurons in whisker-related Somatosensory Cortex (wS1) of freely moving mice, engaged in tactile exploratory behaviour. By recording neural activity from wS1 whilst tracking the mouse body in 3D, we found that wS1 neurons are substantially modulated by body state (configuration of individual body-parts and their derivatives), even in the absence of whisker afferent input. Most neurons were modulated by multiple dimensions of body state, with the most prominently encoded being the angle of the head to the body and locomotion speed. Overall, our data suggest that sensory cortex functions as an embodied representation, which integrates signals from its associated sense organ within a body schema.

neuroscience↗

bioRxiv2019

A system for tracking whisker kinematics and whisker shape in three dimensions

Quantification of behaviour is essential for systems neuroscience. Since the whisker system is a major model system for investigating the neural basis of behaviour, it is important to have methods for measuring whisker movements from behaving animals. Here, we developed a high-speed imaging system that measures whisker movements simultaneously from two vantage points. We developed an algorithm that uses the stereo video data to track multiple whiskers by fitting 3D curves to the basal section of each target whisker. By using temporal information to constrain the fits, the algorithm is able to track multiple whiskers in parallel with low error rate. We used the output of the tracker to produce a 3D description of each tracked whisker, including its 3D orientation and 3D shape, as well as bending-related mechanical force. In conclusion, we present an automatic system to track whiskers in 3D from high-speed video, creating the opportunity for comprehensive 3D analysis of sensorimotor behaviour and its neural basis.\n\nAuthor summaryThe great ethologist Niko Tinbergen described a crucial challenge in biology to measure the \"total movements made by the intact animal\". Advances in high-speed video and machine analysis of such data have made it possible to make profound advances. Here, we target the whisker system. The whisker system is a major experimental model in neurobiology and, since the whiskers are readily imageable, the system is ideally suited to machine vision. Rats and mice explore their environment by sweeping their whiskers to and fro. It is important to measure whisker movements in 3D, since whiskers move in 3D and since the mechanical forces that act on them are 3D. However, the problem of automatically tracking whiskers in 3D from video has generally been regarded as prohibitively difficult. Our innovation here is to extract 3D information about whiskers using a two-camera, high-speed imaging system and to develop computational methods to infer 3D whisker state from the imaging data. Our hope is that this study will facilitate comprehensive, 3D analysis of whisker behaviour and, more generally, contribute new insight into brain mechanisms of perception and behaviour.

neuroscience↗

bioRxiv2018

Prediction of Choice from Competing Mechanosensory and Choice-Memory Cues During Active Tactile Decision Making

Perceptual decision making is an active process where animals move their sense organs to extract task-relevant information. To investigate how the brain translates sensory input into decisions during active sensation, we developed a mouse active touch task where the mechanosensory input can be precisely measured and that challenges animals to use multiple mechanosensory cues. Mice were trained to localise a pole using a single whisker and to report their decision by selecting one of three choices. Using high-speed imaging and machine vision we estimated whisker-object mechanical forces at millisecond resolution. Mice solved the task by a sensory-motor strategy where both the strength and direction of whisker bending were informative cues to pole location. We found competing influences of immediate sensory input and choice memory on mouse choice. On correct trials, choice could be predicted from the direction and strength of whisker bending, but not from previous choice. In contrast, on error trials, choice could be predicted from previous choice but not from whisker bending. This study shows that animal choices during active tactile decision making can be predicted from mechanosenory and choice-memory signals; and provides a new task, well-suited for future study of the neural basis of active perceptual decisions.\n\nSIGNIFICANCE STATEMENTDue to the difficulty of measuring the sensory input to moving sense organs, active perceptual decision making remains poorly understood. The whisker system provides a way forward since it is now possible to measure the mechanical forces due to whisker-object contact during behaviour. Here we train mice in a novel behavioural task that challenges them to use rich mechanosensory cues, but can be performed using one whisker and enables task-relevant mechanical forces to be precisely estimated. This approach enables rigorous study of how sensory cues translate into action during active, perceptual decision making. Our findings provide new insight into active touch and how sensory/internal signals interact to determine behavioural choices.

animal behavior and cognition↗