It is common for animals to use self-generated movements to actively sense the surrounding environment. For instance, rodents rhythmically move their whiskers to explore the space close to their body. The mouse whisker system has become a standard model to study active sensing and sensorimotor integration through feedback loops. In this work, we developed a bioinspired spiking neural network model of the sensorimotor peripheral whisker system, modelling trigeminal ganglion, trigeminal nuclei, facial nuclei, and central pattern generator neuronal populations. This network was embedded in a virtual mouse robot, exploiting the Neurorobotics Platform, a simulation platform offering a virtual environment to develop and test robots driven by brain-inspired controllers. Eventually, the peripheral whisker system was properly connected to an adaptive cerebellar network controller. The whole system was able to drive active whisking with learning capability, matching neural correlates of behaviour experimentally recorded in mice.

The ability to reach, grasp, and manipulate objects is a remarkable expression of motor skill, and the loss of this ability in injury, stroke, or disease can be devastating. These behaviors are controlled by the coordinated activity of tens of millions of neurons distributed across many CNS regions, including the primary motor cortex. While many studies have characterized the activity of single cortical neurons during reaching, the principles governing the dynamics of large, distributed neural populations remain largely unknown. Recent work in primates has suggested that during the execution of reaching, motor cortex may autonomously generate the neural pattern controlling the movement, much like the spinal central pattern generator for locomotion. In this seminar, I will describe recent work that tests this hypothesis using large-scale neural recording, high-resolution behavioral measurements, dynamical systems approaches to data analysis, and optogenetic perturbations in mice. We find, by contrast, that motor cortex requires strong, continuous, and time-varying thalamic input to generate the neural pattern driving reaching. In a second line of work, we demonstrate that the cortico-cerebellar loop is not critical for driving the arm towards the target, but instead fine-tunes movement parameters to enable precise and accurate behavior. Finally, I will describe my future plans to apply these experimental and analytical approaches to the adaptive control of locomotion in complex environments.

In this presentation, we will discuss the cellular and molecular properties of the retrotrapezoid nucleus (RTN), an integrative and interoceptive control node for the respiratory motor system. We will present the molecular profiling that has allowed definitive identification of a cluster of tonically active neurons that provide a requisite drive to the respiratory central pattern generator (CPG) and other pre-motor neurons. We will discuss the ionic basis for steady pacemaker-like firing, including by a large subthreshold oscillation; and for neuromodulatory influences on RTN activity, including by arousal state-dependent neurotransmitters and CO2/H+. The CO2/H+-dependent modulation of RTN excitability represents the sensory component of a homeostatic system by which the brain regulates breathing to maintain blood gases and tissue pH; it relies on two intrinsic molecular proton detectors, both a proton-activated G protein-coupled receptor (GPR4) and a proton-inhibited background K+ channel (TASK-2). We will also discuss downstream neurotransmitter signaling to the respiratory CPG, focusing especially on a newly-identified peptidergic modulation of the preBötzinger complex that becomes activated following birth and the initiation of air breathing. Finally, we will suggest how the cellular and molecular properties of RTN neurons identified in rodent models may contribute to understanding human respiratory disorders, such as congenital central hypoventilation syndrome (CCHS) and sudden infant death syndrome (SIDS).