Understanding sensorimotor control at global and local scales
The brain is remarkably flexible, and appears to instantly reconfigure its processing depending on what’s needed to solve a task at hand: fMRI studies indicate that distal brain areas appear to fluidly couple and decouple with one another depending on behavioral context. We investigated how the brain coordinates its activity across areas to inform complex, top-down control behaviors. Animals were trained to perform a novel brain machine interface task to guide a visual cursor to a reward zone, using activity recorded with widefield calcium imaging. This allowed us to screen for cortical areas implicated in causal neural control of the visual object. Animals could decorrelate normally highly-correlated areas to perform the task, and used an explore-exploit search in neural activity space to discover successful strategies. Higher visual and parietal areas were more active during the task in expert animals. Single unit recordings targeted to these areas indicated that the sensory representation of an object was sensitive to an animal’s subjective sense of controlling it.
Reverse engineering neural control of movement in Hydra
Hydra is a fascinating model organism for neuroscience. It is transparent; new genetic lines allow one to image activity in both neurons (Dupre and Yuste, 2017) and muscle cells (Szymanski and Yuste, 2019) ; it exhibits rich behavior, and it continually rebuilds itself. Hydra’s fairly simply physical structure as a two-layered fluid-filled hydrostat and the accessibility of information about neural and muscle activity opens the possibility of a complete model of neural control of behavior. This requires understanding the transformations that occur in the muscle cell layers and a biomechanical model of the body column. We show that we can use this modeling to reverse engineer how neural activity drives behavior.
The complexity of the ordinary – neural control of locomotion
Today, considerable information is available on the organization and operation of the neural networks that generate the motor output for animal locomotion, such as swimming, walking, or flying. In recent years, the question of which neural mechanisms are responsible for task-specific and flexible adaptations of locomotor patterns has gained increased attention in the field of motor control. I will report on advances we made with respect to this topic for walking in insects, i.e. the leg muscle control system of phasmids and fruit flies. I will present insights into the neural basis of speed control, heading, walking direction, and the role of ground contact in insect walking, both for local control and intersegmental coordination. For these changes in motor activity modifications in the processing of sensory feedback signals play a pivotal role, for instance for movement and load signals in heading and curve walking or for movement signals that contribute to intersegmental coordination. Our recent findings prompt future investigations that aim to elucidate the mechanisms by which descending and intersegmental signals interact with local networks in the generation of motor flexibility during walking in animals.