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The fast, graceful, coordinated movements made by animals and humans are very different from the clumsy stereotyped movements that we characterise as “robotic”; neural control algorithms employed by biological systems probably contribute significantly to this superiority. In this activity, we will investigate and simulate the neural circuitry underlying sensor actuation and control in the vibrissal system. Our objective will be to understand how this system operates in different task settings, and how it is modulated by incoming sensory information so as to generate the intelligent, information-seeking behaviour we see in natural active touch. As part of this work, detailed investigations will be made of whisking in freely-moving animals using state-of-the-art technologies such as high-speed video recording and tracking, and wireless electrophysiology. We believe that results from these studies will be vital for devising artificial vibrissal technologies since, based on our active sensing hypothesis, we consider the control strategies used to position the sensory apparatus is as important an aspect of sensing as the properties of the sensor and of the stimulus. Sensorimotor control strategies observed in animals will be compared with, and where appropriate, modelled using techniques from control theory in which a number of project partners have significant track record. The following inter-twined issues will be investigated in depth:

• The nested-loop architecture for sensorimotor control
• Rhythmogenesis
• Task dependency in active touch
• The modulation of whisking pattern generation

The nested-loop architecture for sensorimotor control

A fundamental goal will be to explore the advantages for active sensing provided by the multiple sensorimotor loops in the neural control architecture for vibrissal touch. Large-scale closed loops have interesting computational properties that may optimise sensory processing. In the vibrissal system, these loops are organized in what appears to be a hierarchy, which likely preserves an evolutionary, and perhaps also a developmental, order. Higher levels generally add increased competence by modulating the behaviour/activity of lower levels. Research in robot control has demonstrated that layered control systems of this sort can combine the advantages of fast responsiveness with resistance to damage. Understanding the detailed operation of this complex architecture for vibrissal control should therefore generate insights that will aid the design of effective and robust controllers for artefacts such as autonomous robots.

Rhythmogenesis

Movements of the whiskers are driven from a population of “vibrissal motor neurons” (VMNs) in the brainstem facial nucleus whose rhythmic firing generates the rapid sweeping behaviour termed “whisking”. However, many other areas of the vibrissal sensorimotor system also exhibit some intrinsic rhythmic capacity. Understanding how whisking rhythms are generated and become synchronized (or desynchronized) through the interactions of different cell populations will provide a rich source of general insight into pattern formation in neural systems.

Task dependency in active touch

Human tactile sensing makes use of different strategies for positioning the sensory apparatus depending upon the task in hand. In fact, previous human studies have demonstrated that selection of non-optimal motor strategies can yield significant perceptual impairments that can be corrected by re-learning the task using optimal ones. Anecdotal evidence suggests that control of sensor movement in vibrissal sensory systems likewise adapts according to the current motivation of the animal. By exploring and analysing this task-dependency in detail, we will both uncover useful control strategies for active touch, and further our understanding of how motor control and signal processing in biological sensory systems vary with task demands.

The modulation of whisking pattern generation

Observations of whisking in animals that are stationary and whisking in air (‘free whisking’) reliably demonstrate bilateral symmetry and synchrony of whisker movements on the two sides of the snout. Likewise, within the two whisker fields, the whiskers move largely in phase with one another and at similar velocities. This had led to the assumption that whisking is a relatively stereotyped action that can be reasonably well characterized by describing the amplitude, frequency, and set-point of the overall whisking pattern. However, recent evidence shows that the whisking movements of freely-moving animals engaged in exploratory behaviour vary considerably and consistently in anticipation of head movements, or as a result of contacts with nearby surfaces. Evidence of significant variation in whisker movements within each whisker field is also beginning to accumulate. Investigation of how proprioceptive and sensory data modulates vibrissal control should provide insights applicable to understanding active sensing strategies in other species and modalities.