A neural model of the interaction of tectal columns in prey-catching behavior

Saccadic interception of a moving visual target after a spatiotemporal perturbation

Animals can make saccadic eye movements to intercept a moving object at the right place and time. Such interceptive saccades indicate that, despite variable sensorimotor delays, the brain is able to estimate the current spatiotemporal (hic et nunc) coordinates of a target at saccade end. The present work further tests the robustness of this estimate in the monkey when a change in eye position and a delay are experimentally added before the onset of the saccade and in the absence of visual feedback. These perturbations are induced by brief microstimulation in the deep superior colliculus (dSC). When the microstimulation moves the eyes in the direction opposite to the target motion, a correction saccade brings gaze back on the target path or very near. When it moves the eye in the same direction, the performance is more variable and depends on the stimulated sites. Saccades fall ahead of the target with an error that increases when the stimulation is applied more caudally in the dSC. The numerous cases of compensation indicate that the brain is able to maintain an accurate and robust estimate of the location of the moving target. The inaccuracies observed when stimulating the dSC that encodes the visual field traversed by the target indicate that dSC microstimulation can interfere with signals encoding the target motion path. The results are discussed within the framework of the dual-drive and the remapping hypotheses.

Dynamic response properties of visual neurons and context-dependent surround effects on receptive fields in the tectum of the salamander Plethodon shermani

Neuronal responses to complex prey-like stimuli and rectangles were investigated in the tectum of the salamander Plethodon shermani using extracellular single-cell recording. Cricket dummies differing in size, contrast or movement pattern or a rectangle were moved singly through the excitatory receptive field of a neuron. Paired presentations were performed, in which a reference stimulus was moved inside and the different cricket dummies or the rectangle outside the excitatory receptive field. Visual object recognition involves much more complex spatial and temporal processing than previously assumed in amphibians. This concerns significant changes in absolute number of spikes, temporal discharge pattern, and receptive field size. At single presentation of stimuli, the number of discharges was significantly changed compared with the reference stimulus, and in the majority of neurons the temporal pattern of discharges was changed in addition. At paired presentation of stimuli, neurons mainly revealed a significant decrease in average spike number and a reduction of excitatory receptive field size to presentation of the reference stimulus inside the excitatory receptive field, when a large-sized cricket stimulus or the rectangle was located outside the excitatory receptive field. This inhibition was significantly greater for the large-sized cricket stimulus than for the rectangle, and indicates the biological relevance of the prey-like stimulus in object selection. The response properties of tectal neurons at single or paired presentation of stimuli indicate that tectal neurons integrate information across a much larger part of visual space than covered by the excitatory receptive field. The spike number of a tectal neuron and the spatio-temporal extent of its excitatory receptive field are not fixed but depend on the context, i.e. the stimulus type and combination. This dynamic processing corresponds with the selection of the stimuli in the visual orienting behavior of Plethodon investigated in a previous study, and we assume that tectal processing is modulated by top down processes as well as feedback circuitries.

A neural model of interactions subserving prey-predator discrimination and size preference in anuran amphibia

The model described is an extension of a previous model of the optic tectum (Arbib & Lara, 1982; Lara, Arbib & Cromarty, 1982; Lara & Arbib, 1982) and takes into consideration anatomical, physiological and behavioral studies in anurans, as well as earlier modelling efforts (Ewert & Von Seelen, 1974; Didday, 1976). Computer simulations were conducted to analyze how interactions among retina, optic tectum and pretectum may give frogs and toads the ability to discriminate between prey and predator stimuli. Results from simulations have allowed us to reproduce empirical observations, to suggest new experiments, and to postulate what neural mechanisms might be involved in some phenomena related to prey-catching orienting behavior, with direction invariance of prey-predator recognition being a consequence of tectal architecture, and size preference and response latency depending on the motivational state of the animal.

Sensori-motor transformations in the brain (with a critique of the tensor theory of cerebellum)

Section 1 lists 12 points which must be addressed by neural models of sensorimotor coordination. Section 2 addresses the problem of extrapolating motor output from noisy data or from sensory input. The Pellionisz-Llinas cerebellar lookahead module addresses this problem for the noise-free case, and we suggest theoretical and experimental tests of the model; we then suggest the investigation of neural analogs of the Kalman-Bucy filter. Section 3 offers a brief exposition of mechanics in a tensor framework to provide the irreducible minimum of mathematical machinery to evaluate the Pellionisz-Llinás tensor theory of brain function and to suggest fruitful new hypotheses. Our critique of this theory in section 4 leads us to conclude that what they offer is based on metaphorical use of terminology from Euclidean tensors, not on rigorous application of the mathematics of tensor analysis. The central claim of their theory--that the input is a covariant intention vector transformed by a metric tensor encoded in the cerebellum to a contravariant execution vector--has not been substantiated and probably cannot be substantiated. However, we do point the way to further use of tensor analysis in the study of neural control of movement. The concluding section then returns to the points raised in section 1 with a highly selective survey of models of cerebellum and tectum.

A global model of the neural mechanisms responsible for visuomotor coordination in toads

A model of how the nervous system of toads processes visual information to control motor behaviour is proposed. The problem of visuomotor coordination in toads is studied through the integration of two different approaches: a top-down approach through schema theory developed in the studies of cognitive psychology, artificial intelligence and brain theory; and a bottom-up approach through the integration of physiological, anatomical, ethological, and neural modelling. The model proposes that visual information is processed in a parallel distributed way through different brain layers whose interaction defines the proper motor response for that specific situation. It is postulated that visual processing of information is organized into main schemata, which set the goal to be attained and, depending on the specific circumstances of the animal, activates different brain layers; the main schemata may use other schemata to solve a specific subproblem to reach the schemata, and a programme of schema co-ordination. With this model we have simulated how toads plan their route to reach a prey or the route to go away form a predator, depending on the state of their three-dimensional world. The model postulates specific hypotheses that could be tested experimentally on the processing of information in the toad's nervous system.

A neural model of the interaction of tectal columns in prey-catching behavior

Building on a simple model of a tectal column as the unit of processing in the amphibian tectum, we conduct a computer analysis of the interaction of a linear array of such columns. The model suggests that the inhibitory and excitatory activity in the tectum may have three functions: 1) spatio-temporal facilitation of column activity to a moving stimulus; 2) preference for the head of the stimulus, probably to avoid possible defensive reactions of the prey; and 3) modulating the state of excitation of the column once it has produced a response. The model also shows that the spatio-temporal effects of excitation and inhibition increases the acuity of the animal to the direction of the prey, through processes similar to lateral inhibition.