Movement-Related Signals in Sensory Areas: Roles in Natural Behavior

Abstract

Recent studies have demonstrated prominent and widespread movement-related signals in the brain of head-fixed mice, even in primary sensory areas. However, it is still unknown what role these signals play in sensory processing. Why are these sensory areas 'contaminated' by movement signals? During natural behavior, animals actively acquire sensory information as they move through the environment and use this information to guide ongoing actions. In this context, movement-related signals could allow sensory systems to predict self-induced sensory changes and extract additional information about the environment. In this review we summarize recent findings on the presence of movement-related signals in sensory areas and discuss how their study, in the context of natural freely moving behaviors, could advance models of sensory processing.

Keywords: active sensation; cortical processing; ethology; sensory physiology.

Figure 1.. Overview of studies revealing movement-related signals in sensory areas in rodents.

A) A subset of mouse V1 neurons respond to a visual feature at a single location despite its repeated presence along a linear track, suggesting place cell-like encoding. Based on [25], and see also [24]. B) Movement-modulated activity in mouse primary sensory cortical neurons is often best explained by models incorporating uninstructed movements during a task, rather than instructed movements or stimulus presentations. Based on [27]. C) Linking the presence of a single tone to locomotion using auditory virtual reality (aVR) in mice leads to M1-mediated suppression of locomotor gain modulation in A1 at that specific frequency. Based on [23]. D) Alignment of odorant responses in mouse olfactory bulb mitral/tufted cells to odorant responses belie robust responses that become apparent when spikes are warped to match the phase of the sniff cycle. Based on [62]. E) The magnitude of rat S1 responses to whisker contacts depends on the phase within the whisking cycle. Based on [33]. F) Locomotion increases the gain of mouse V1 responses without affecting orientation tuning, and shifts the local field potential toward higher frequencies. Based on [14].

Figure 2.. Examples of freely moving ethological paradigms for the study of movement-related signals in sensory processing.

A) Laboratory mice reliably pursue and capture cricket prey after only a short habituation period, showing a consistently narrow range of head angles relative to the cricket that decrease as the mouse approaches the cricket. Modified from [88]. B) Mice spontaneously cross a gap by first judging the target platform distance with their whiskers. The incorporation of a short-latency variable gap showed that whisker protractions match the expected, rather than actual, position of the platform, and thus each whisking phase encodes a mismatch signal. Modified from [89]. C) Mice rapidly learn to report the location of an odor plume source. Unsupervised computational techniques parse complex trajectories into a sequence of movement motifs. Many of these motifs synchronize to the sniff cycle with 10s of ms precision [134].

Figure 3,. Key Figure. Experimental techniques for investigating sensory processing during freely moving natural behavior.

A) (1) Miniature head-mounted cameras facing outward and at the eye can measure the visual scene and eye movements to estimate the current visual input. (2) Chemical sensors and/or fluid dynamic modeling can indicate the spatiotemporal distribution of odor concentration, intranasal temperature or pressure measurement can reveal sniffing, and video tracking or head mounted accelerometers can capture active sampling movements. B) Concurrent measurement of neural activity with microelectrodes (1) or miniaturized microscopes permits alignment of neural data with known sensor dynamics and sensory inputs. Optogenetic and chemogenetic protein expression in defined subpopulations (2) allows identification of neuron types in electrophysiology recordings, or manipulation of circuits to test hypotheses about movement-related inputs to sensory areas. C) Continuous behavioral monitoring with markerless video tracking (1) permits alignment of neural and sensory data with body movements. Supervised and unsupervised analyses reveal substructures in behavior (2) that further refine analysis of the relationship between neural activity and sensory input.