A rapid whisker-based decision underlying skilled locomotion in mice

Abstract

Skilled motor behavior requires rapidly integrating external sensory input with information about internal state to decide which movements to make next. Using machine learning approaches for high-resolution kinematic analysis, we uncover the logic of a rapid decision underlying sensory-guided locomotion in mice. After detecting obstacles with their whiskers mice select distinct kinematic strategies depending on a whisker-derived estimate of obstacle location together with the position and velocity of their body. Although mice rely on whiskers for obstacle avoidance, lesions of primary whisker sensory cortex had minimal impact. While motor cortex manipulations affected the execution of the chosen strategy, the decision-making process remained largely intact. These results highlight the potential of machine learning for reductionist analysis of naturalistic behaviors and provide a case in which subcortical brain structures appear sufficient for mediating a relatively sophisticated sensorimotor decision.

Signatures of rapid synaptic learning in the hippocampus during novel experiences

“…Mice were head-fixed above a low-friction, light weight running wheel (Warren et al 2021). The axle of the running wheel was coupled to a rotary encoder, which connected to a circuit that decoded and buffered the quadrature data from the encoder and transmitted these position updates to an Intel NUC i5 mini-PC that was used to control the behavior system.…”

A cortico-cortical pathway targets inhibitory interneurons and modulates paw movement during locomotion in mice

“…Retrograde labeling of M1 neurons projecting to nwS1 and intracortical microstimulation should be combined in the same animal to address this issue. It is also possible that while M1 itself is crucial for baseline locomotion (Warren et al, 2021) or that the M1→nwS1 pathway is involved in a different function such as motor learning (Kawai et al, 2015). Lastly, the simple motor assays used in the present study may be insufficient to capture complex changes in paw kinematics caused by silencing of M1→nwS1 connections.…”

“…Interactions between wS1 and other cortical areas, such as M1 and S2, are important for initiating whisking and active sensing during whisking (Petreanu et al, 2012, Xu et al, 2012, Lee et al, 2013, Zagha et al, 2013, Sreenivasan et al, 2016). These cortico-cortical interactions also underlie tactile perception (Chen et al, 2013, Zuo et al, 2015, Kwon et al, 2016, Yamashita and Petersen, 2016) and obstacle avoidance during locomotion (Warren et al, 2021).…”

Behavioral and physiological monitoring for awake neurovascular coupling experiments: a how-to guide

“…For imaging experiments, mice can be either head-fixed on a spherical treadmill 7 , 8 , 19 , 41 , 50 – 52 , 58 – 76 [ Fig. S1(b) in the Supplemental Material ] or a rotating disk 77 – 80 which allows them to freely locomote.…”

“…Combining high-speed cameras with those advanced algorithms allows very sensitive body and limb movements tracking. 9 , 76 , 113 Here, we provided a simple example of body position and spine/tail curvature tracking using DeepLabCut. 18 , 112 For behavior imaging, we use a camera (FLIR blackfly USB camera) running at .…”