Dr. Jessica Ausborn’s group at Drexel University College of Medicine, in the Department of Neurobiology & Anatomy has a postdoctoral position available for an exciting new research project involving computational models of sensorimotor integration based on neural and behavior data in Drosophila. The interdisciplinary collaboration with the experimental group of Dr. Katie von Reyn (School of Biomedical Engineering) will involve a variety of computational techniques including the development of biophysically detailed and more abstract mathematical models together with machine learning and data science techniques to identify and describe the algorithms computed in neuronal pathways that perform sensorimotor transformations. The Ausborn laboratory is part of an interdisciplinary group of Drexel’s Neuroengineering program that includes computational and experimental investigators. This collaborative, interdisciplinary environment enables us to probe biological systems in a way that would not be possible with either an exclusively experimental or computational approach. Applicants should forward a cover letter, curriculum vitae, statement of research interests, and contact information of three references to Jessica Ausborn (ja696@drexel.edu). Salary will be commensurate with experience based on NIH guidelines.

This PhD is funded by the French ANR, under a 4 years' project on Sensorimotor integration of variability during birdsong learning. The applicant will develop an artificial neural model, developmental and brain-inspired, to learn the sound structure in real time and without explicit supervision. Until now, AI models for developmental learning of vocalizations have been solely validated by comparison against a human-annotated corpus and not yet via direct sensorimotor interactions with living animals. We expect to do so with an interactive robot under the framework of active inference and predictive coding.

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 cerebellum permits a wide range of behaviors that involve sensorimotor integration. We have been investigating how specific cellular and synaptic specializations of cerebellar neurons measured in vitro, give rise to circuit activity in vivo. We have investigated these issues by studying Purkinje neurons as well as the large neurons of the mouse cerebellar nuclei, which form the major excitatory premotor projection from the cerebellum. Large CbN cells have ion channels that favor spontaneous action potential firing and GABAA receptors that generate ultra-fast inhibitory synaptic currents, raising the possibility that these biophysical attributes may permit CbN cells to respond differently to the degree of temporal coherence of their Purkinje cell inputs. In vivo, self-initiated motor programs associated with whisking correlates with asynchronous changes in Purkinje cell simple spiking that are asynchronous across the population. The resulting inhibition converges with mossy fiber excitation to yield little change in CbN cell firing, such that cerebellar output is low or cancelled. In contrast, externally applied sensory stimuli elicits a transient, synchronous inhibition of Purkinje cell simple spiking. During the resulting strong disinhibition of CbN cells, sensory-induced excitation from mossy fibers effectively drives cerebellar outputs that increase the magnitude of reflexive whisking. Purkinje cell synchrony, therefore, may be a key variable contributing to the “positive effort” hypothesized by David Marr in 1969 to be necessary for cerebellar control of movement.