BIOTACT.org

In this activity we will develop novel computational methods for the extraction of tactile properties of detected objects (texture, shape, etc.). We will also develop algorithms for classification, decision-making, and spatial mapping, based on these tactile codes. Work will focus on the following functional capacities and related computational principles:

• Tactile coding of object properties
• Classification, memory & decision-making

Tactile coding of object properties

Whiskered animals have remarkable capacities for detecting and responding to salient properties of surfaces and objects in their environment. For instance, rats are excellent judges of distance and relative position, and can perform fast and accurate discriminations based on shape and texture—often surpassing the performance of human subjects on similar tasks. Etruscan shrews are the world’s smallest mammal with a brain-size 20,000 times smaller than the human brain. Nevertheless, these animals also show remarkable tactile object recognition capacities indicating that high-level abstract sensory representations are neither restricted to the primates nor tied to large brain size. We will gather observations of the whisker-mediated behavioural capacities of rats and shrews interacting with objects both during free exploration and in tactile discrimination tasks. We will also record neuronal activity from multiple stations of the sensory pathway, from periphery to cortex, during these behaviours. Since the normal functioning of the sensory system entails the simultaneous solving of both spatial problems (where is the object?) and identification problems (what is the object?), we will pay close attention to the interaction of the two sorts of information. The goal of this activity will be to establish how information about tactile object properties can be effectively coded, and how such codes might be modified according to the behaviour in progress. Modelling approaches will include spiking neuron models, Bayesian models of pattern recognition, and abstract functional models of cortical microcircuits.

Classification, memory, and decision-making

Besides the accuracy of tactile behaviours in whiskered animals, a remarkable characteristic is the speed of transformation of complex sensory signals into decisions and the rapid execution of the appropriate choice action. Timescales, from start to finish, can be of the order of tens of milliseconds. In contrast, in the visual domain even task-experienced human observers take 300 ms to indicate the detection of a simple visual object. The rapidity of vibrissal-guided control implies a quick and accurate transformation of raw sense signals into activity states that represent distinct classes of task-relevant stimuli; each class associated with and transformed to its appropriate action. Understanding how biological systems accomplish this, in noisy and uncertain environments, will be critical to endowing biomimetic systems with accuracy, speed, and flexibility. Neurobiological investigations of this question will focus on neural circuits involving the sensory cortex, the hippocampus, and the prefrontal cortex, where we will seek to uncover the representation of information as it resides in short-term memory “buffers”. Experiments involving electrophysiological recording during behaviour will be complemented by others using stimulation of single neurons to assess the behavioural impact of their induced activity. Modelling approaches will use recurrent neural networks and biologically-realistic Hebbian learning rules, together with statistical models of optimal decision-making originally developed using human and primate data. The efficacy of the resulting systems will be tested using the BIOTACT sensor in tasks that involve making tactile discriminations between objects with a speed and accuracy intended to approach that seen in whiskered animals.