@article {67814, title = {Internal Models in Control, Bioengineering, and Neuroscience}, journal = {Annual Review of Control, Robotics, and Autonomous Systems}, volume = {5}, year = {2022}, month = {2021 Nov 29}, abstract = {

Internal models are nowadays customarily used in different domains of science and engineering to describe how living organisms or artificial computational units embed their acquired knowledge about recurring events taking place in the surrounding environment. This article reviews the internal model principle in control theory, bioengineering, and neuroscience, illustrating the fundamental concepts and theoretical developments of the few last decades of research.

}, issn = {2573-5144}, doi = {10.1146/control.2022.5.issue-110.1146/annurev-control-042920-102205}, url = {https://www.annualreviews.org/toc/control/5/1https://www.annualreviews.org/doi/10.1146/annurev-control-042920-102205https://www.annualreviews.org/doi/pdf/10.1146/annurev-control-042920-102205}, author = {Bin, Michelangelo and Huang, Jie and Isidori, Alberto and Marconi, Lorenzo and Mischiati, Matteo and Sontag, Eduardo} } @article {67657, title = {Disrupting cortico-cerebellar communication impairs dexterity.}, journal = {eLife}, volume = {10}, year = {2021}, month = {2021 Jul 29}, abstract = {

To control reaching, the nervous system must generate large changes in muscle activation to drive the limb toward the target, and must also make smaller adjustments for precise and accurate behavior. Motor cortex controls the arm through projections to diverse targets across the central nervous system, but it has been challenging to identify the roles of cortical projections to specific targets. Here, we selectively disrupt cortico-cerebellar communication in the mouse by optogenetically stimulating the pontine nuclei in a cued reaching task. This perturbation did not typically block movement initiation, but degraded the precision, accuracy, duration, or success rate of the movement. Correspondingly, cerebellar and cortical activity during movement were largely preserved, but differences in hand velocity between control and stimulation conditions predicted from neural activity were correlated with observed velocity differences. These results suggest that while the total output of motor cortex drives reaching, the cortico-cerebellar loop makes small adjustments that contribute to the successful execution of this dexterous movement.

}, issn = {2050-084X}, doi = {10.7554/eLife.65906}, author = {Guo, Jian-Zhong and Sauerbrei, Britton A and Cohen, Jeremy D and Mischiati, Matteo and Graves, Austin R and Pisanello, Ferruccio and Branson, Kristin M and Hantman, Adam W} } @article {65259, title = {Cortical pattern generation during dexterous movement is input-driven.}, journal = {Nature}, volume = {577}, year = {2020}, month = {2020 Jan 16}, pages = {386-91}, abstract = {

The motor cortex controls skilled arm movement by sending temporal patterns of activity to lower motor centres. Local cortical dynamics are thought to shape these patterns throughout movement execution. External inputs have been implicated in setting the initial state of the motor cortex, but they may also have a pattern-generating role. Here we dissect the contribution of local dynamics and inputs to cortical pattern generation during a prehension task in mice. Perturbing cortex to an aberrant state prevented movement initiation, but after the perturbation was released, cortex either bypassed the normal initial state and immediately generated the pattern that controls reaching or failed to generate this pattern. The difference in these two outcomes was probably a result of external inputs. We directly investigated the role of inputs by inactivating the thalamus; this perturbed cortical activity and disrupted limb kinematics at any stage of the movement. Activation of thalamocortical axon terminals at different frequencies disrupted cortical activity and arm movement in a graded manner. Simultaneous recordings revealed that both thalamic activity and the current state of cortex predicted changes in cortical activity. Thus, the pattern generator for dexterous arm movement is distributed across multiple, strongly interacting brain regions.

}, issn = {1476-4687}, doi = {10.1038/s41586-019-1869-9}, author = {Sauerbrei, Britton A and Guo, Jian-Zhong and Cohen, Jeremy D and Mischiati, Matteo and Guo, Wendy and Kabra, Mayank and Verma, Nakul and Mensh, Brett and Branson, Kristin and Hantman, Adam W} } @conference {56205, title = {Internal models in control, biology and neuroscience.}, booktitle = {2018 IEEE Conference on Decision and Control (CDC)}, year = {2019}, month = {2019 Jan 21}, abstract = {

This tutorial paper deals with the Internal Model Principle (IMP) from different perspectives. The goal is to start from the principle as introduced and commonly used in the control theory and then enlarge the vision to other fields where {\textquotedblleft}internal models{\textquotedblright} play a role. The biology and neuroscience fields are specifically targeted in the paper. The paper ends by presenting an {\textquotedblleft}abstract{\textquotedblright} theory of IMP applicable to a large class of systems.

}, doi = {10.1109/CDC.2018.8619624}, author = {Huang, J and Isidori, A and Marconi, L and Mischiati, Matteo and Sontag, E and Wonham, W M} } @article {49585, title = {Motor cortex is an input-driven dynamical system controlling dexterous movement.}, journal = {bioRxiv}, year = {2018}, month = {2018-12-14}, pages = {266320}, abstract = {

Skillful control of movement is central to our ability to sense and manipulate the world. A large body of work in nonhuman primates has demonstrated that motor cortex provides flexible, time-varying activity patterns that control the arm during reaching and grasping. Previous studies have suggested that these patterns are generated by strong local recurrent dynamics operating autonomously from inputs during movement execution. An alternative possibility is that motor cortex requires coordination with upstream brain regions throughout the entire movement in order to yield these patterns. Here, we developed an experimental preparation in the mouse to directly test these possibilities using optogenetics and electrophysiology during a skilled reach-to-grab-to-eat task. To validate this preparation, we first established that a specific, time-varying pattern of motor cortical activity was required to produce coordinated movement. Next, in order to disentangle the contribution of local recurrent motor cortical dynamics from external input, we optogenetically held the recurrent contribution constant, then observed how motor cortical activity recovered following the end of this perturbation. Both the neural responses and hand trajectory varied from trial to trial, and this variability reflected variability in external inputs. To directly probe the role of these inputs, we used optogenetics to perturb activity in the thalamus. Thalamic perturbation at the start of the trial prevented movement initiation, and perturbation at any stage of the movement prevented progression of the hand to the target; this demonstrates that input is required throughout the movement. By comparing motor cortical activity with and without thalamic perturbation, we were able to estimate the effects of external inputs on motor cortical population activity. Thus, unlike pattern-generating circuits that are local and autonomous, such as those in the spinal cord that generate left-right alternation during locomotion, the pattern generator for reaching and grasping is distributed across multiple, strongly-interacting brain regions.

}, doi = {10.1101/266320}, author = {Sauerbrei, Britton and Guo, Jian-Zhong and Mischiati, Matteo and Guo, Wendy and Kabra, Mayank and Verma, Nakul and Branson, Kristin M and Hantman, Adam W} } @article {45720, title = {Internal models direct dragonfly interception steering.}, journal = {Nature}, year = {2014}, month = {2014 Dec 10}, abstract = {

Sensorimotor control in vertebrates relies on internal models. When extending an arm to reach for an object, the brain uses predictive models of both limb dynamics and target properties. Whether invertebrates use such models remains unclear. Here we examine to what extent prey interception by dragonflies (Plathemis lydia), a behaviour analogous to targeted reaching, requires internal models. By simultaneously tracking the position and orientation of a dragonfly{\textquoteright}s head and body during flight, we provide evidence that interception steering is driven by forward and inverse models of dragonfly body dynamics and by models of prey motion. Predictive rotations of the dragonfly{\textquoteright}s head continuously track the prey{\textquoteright}s angular position. The head-body angles established by prey tracking appear to guide systematic rotations of the dragonfly{\textquoteright}s body to align it with the prey{\textquoteright}s flight path. Model-driven control thus underlies the bulk of interception steering manoeuvres, while vision is used for reactions to unexpected prey movements. These findings illuminate the computational sophistication with which insects construct behaviour.

}, issn = {1476-4687}, doi = {10.1038/nature14045}, author = {Mischiati, Matteo and Lin, Huai-Ti and Herold, Paul and Imler, Elliot and Olberg, Robert and Leonardo, Anthony} }