Biomedical subjects

M A Arbib

Publications and source records attributed to M A Arbib.

At least 19 recordsLinked to original sources

PubMed1992

Modeling the dishabituation hierarchy: the role of the primordial hippocampus.

We present a neural model for the organization and neural dynamics of the medial pallium, the toad's homolog of mammalian hippocampus. A neural mechanism, called cumulative shrinking, is proposed for mapping temporal responses from the anterior thalamus into a form of population coding referenced by spatial positions. Synaptic plasticity is modeled as an interaction of two dynamic processes which simulates acquisition and both short-term and long-term forgetting. The structure of the medial pallium model plus the plasticity model allows us to provide an account of the neural mechanisms of habituation and dishabituation. Computer simulations demonstrate a remarkable match between the model performance and the original experimental data on which the dishabituation hierarchy was based. A set of model predictions is presented, concerning mechanisms of habituation and cellular organization of the medial pallium.

Animals↗

PubMed1992

A mathematical analysis of the force-stiffness characteristics of muscles in control of a single joint system.

Feldman (1966) has proposed that a muscle endowed with its spinal reflex system behaves as a non-linear spring with an adjustable resting length. In contrast, because of the length-tension properties of muscles, many researchers have modeled them as non-linear springs with adjustable stiffness. Here we test the merits of each approach: Initially, it is proven that the adjustable stiffness model predicts that isometric muscle force and stiffness are linearly related. We show that this prediction is not supported by data on the static stiffness-force characteristics of reflexive muscles, where stiffness grows non-linearly with force. Therefore, an intact muscle-reflex system does not behave as a non-linear spring with an adjustable stiffness. However, when the same muscle is devoid of its reflexes, the data shows that stiffness grows linearly with force. We aim to understand the functional advantage of the non-linear stiffness-force relationship present in the reflexive muscle. Control of an inverted pendulum with a pair of antagonist muscles is considered. Using an active-state muscle model we describe force development in an areflexive muscle. From the data on the relationship of stiffness and force in the intact muscle we derive the length-tension properties of a reflexive muscle. It is shown that a muscle under the control of its spinal reflexes resembles a non-linear spring with an adjustable resting length. This provides independent evidence in support of the Feldman hypothesis of an adjustable resting length as the control parameter of a reflexive muscle, but it disagrees with his particular formulation. In order to maintain stability of the single joint system, we prove that a necessary condition is that muscle stiffness must grow at least linearly with force at isometric conditions. This shows that co-contraction of antagonist muscles may actually destabilize the limb if the slope of this stiffness-force relationship is less than an amount specified by the change in the moment arm of the muscle as a function of joint configuration. In a reflexive muscle where stiffness grows faster than linearly with force, co-contraction will always lead to an increase in stiffness. Furthermore, with the reflexive muscles, the same level of joint stiffness can be produced by much smaller muscle forces because of the non-linear stiffness-force relationship. This allows the joint to remain stable at a fraction of the metabolic energy cost associated with maintaining stability with areflexive muscles.

Animals↗

PubMed1991

A model of anuran retina relating interneurons to ganglion cell responses.

A model is presented which accounts for many characteristic response properties used to classify anuran ganglion cell types while being consistent with data concerning interneurons. In the model color is ignored and input stimuli are assumed to be only black and white at high contrast. We show that accurate ganglion cell responses are obtained even with simplified receptors and horizontal cells: Receptors are modeled as responding with a step change, while horizontal cells respond only to global changes in intensity brought about by full field illumination changes. A hyperpolarizing and depolarizing bipolar cell are generated by subtracting local receptor and horizontal potentials. Two transient amacrine cells (On and Off) are generated using a high-pass filter like mechanism with a thresholded output which responds to positive going changes in the corresponding bipolar cell potentials. The model shows how a selective combination of bipolar and amacrine channels can account for many of the response properties used to classify the anuran ganglion cell types (class-0 through 4) and makes several experimental predictions.

Animals↗

PubMed1991

How does the toad's visual system discriminate different worm-like stimuli?

Behavioral experiments show that toads exhibit stimulus- and locus-specific habituation. Different worm-like stimuli that toads can discriminate at a certain visual location form a dishabituation hierarchy. What is the neural mechanism which underlies these behaviors? This paper proposes that the toad discriminates visual objects based on temporal responses, and that discrimination is reflected in different average neuronal firing rates at some higher visual center, hypothetically anterior thalamus. This theory is developed through a large-scale neural simulation which includes retina, tectum and anterior thalamus. The neural model based on this theory predicts that retinal R2 cells play a primary role in the discrimination via tectal small pear cells (SP) and R3 cells refine the feature analysis by inhibition. The simulation demonstrates that the retinal response to the trailing edge of a stimulus is as crucial for pattern discrimination as the response to the leading edge. The new dishabituation hierarchies predicted by this model by reversing contrast and shrinking stimulus size need to be tested experimentally.

Animals↗

PubMed1990

Stability and parameter dependency analysis of a facilitation tectal column (FTC) model.

Mathematical models and computer simulations have been widely used to study the spatio-temporal characteristics of the processing of information carried out by the central nervous system. When trying to show whether or not a neural model accounts for the phenomena under study, if the number of parameters whose values need to be calculated becomes large, then computer simulations alone become very inefficient to define such values. Here, we developed stability and parameter dependency analyses of the mathematical representation of a single facilitation tectal column (FTC) model, to show how by using techniques from non-linear systems theory we can define the ranges of parameter values under which the model would explain the required performance of the neural net model. The benefits of these analyses can be grouped in two parts: first, the advantage of using non-linear systems techniques to analyze, analytically, the dynamics of neural net models; and second, we get a deeper understanding of why the hypotheses embedded in the models yield the appropriate behaviors and what are the critical situations (parametric combinations) under which these behaviors are displayed.

Action Potentials↗

PubMed1988

The cue interaction model of depth perception: a stability analysis.

In this paper, we offer a stability analysis of "the cue interaction model" of depth perception (House (1984]. Depth estimation using stereopsis suffers from the "matching problem", the problem of correctly matching the retinal image of a feature in one eye, to its retinal image in the other eye. The Cue Interaction Model overcomes this by using monocular cues to disambiguate between the "correct matches" and the "incorrect matches". Its decision making is based on the concept of cooperation and competition in a neural network. A general class of cooperative and competitive models has been mathematically analysed by Amari and Arbib (1977), with special attention given to equilibrium states and stability. In this paper we adapt their methods to study the above model. In particular, we prove that if the parameters are correctly tuned, the model successfully achieves its goals by suppressing the cues which represent the "incorrect matches".

Animals↗

PubMed1987

The prey localisation model: a stability analysis.

This paper analyzes the "Prey localisation Model" (House 1984), for animals that are unable to verge their eyes. The Prey localisation Model selects a single point or a portion of the scene in its visual space. In particular it imitates the behaviour of frogs and toads of selecting the closer target when two equally attractive prey are presented to it. The model achieves its goal by tightly coupling two prey selection processes, one for each eye, with lens accommodation. In this paper we offer a stability analysis of the model, and show how lens accommodation, i.e. adjustment in the focal length of the lens, biases the selection of the proximal target. We examine the properties of the model that are responsible for its behaviour and derive a set of conditions which guarantees the localisation of the correct target.

Animals↗

PubMed1985

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.

Amphibians↗

PubMed1985

A model of the neural mechanisms responsible for pattern recognition and stimulus specific habituation in toads.

A neural model of the mechanisms possibly responsible for stimulus-specific habituation in toads is proposed. The model follows the hypothesis that prey-predator recognition is performed by command units as a result of retina-tectum-pretectum interaction. The model allow us to study the possible coding that the nervous system of toads uses for different prey stimuli, the neural mechanisms of habituation and dishabituation, and the dynamic changes that the command units may have during these processes. The model proposes specific hypothesis and experiments to clarify the nature of these processes and to test the validity of the command unit hypothesis.

Animals↗

PubMed1985

Brain theory and cooperative computation.

"Top-down" brain theory, based upon functional analysis of cognitive processes in terms of interacting schemas, is distinguished from "bottom-up" brain theory based on analysis of the dynamics of neural nets. "Cooperative computation" is proposed as the style of interaction of neural subsystems at various levels. Perceptual schemas are introduced as the building blocks for the representation of the perceived environment, and motor schemas serve as control systems to be coordinated into programs for the control of movement. A cooperative computation view of the design of machine vision systems is exemplified both by an algorithm for computing optic flow which offers interesting insights into the evolution of hierarchical neural structures, and by an analysis of knowledge representation for machine interpretation of visual scenes. The interaction between top-down analysis and detailed neural modelling is illustrated by the study of visuomotor coordination in frogs and toads.

Animals↗

PubMed1985

Schemas for the temporal organization of behaviour.

Those aspects of the timing of behaviour are emphasized which derive from the need for the organism to coordinate its actions with objects in the environment. Such coordination may require the serial performance of certain actions, yet permit elements of concurrency as well. Perceptual and motor schemas are introduced as units for the functional description of behaviour intermediate between a purely phenomenological description and an account of the detailed neural mechanisms of behaviour. The language of coordinated control programs is outlined to suggest how such schemas are orchestrated in visually and tactilely guided behaviour. Finally, a crucial property of the timing of many movements is discussed: their division into a fast (feedforward, ballistic) phase followed by a slow (feedback) phase. This division is analyzed in the light of the effect of brain damage on reaching movements.

Animals↗

PubMed1985

Rana computatrix: progress report, 1984.

This paper describes an approach to analyzing mechanisms of visuomotor coordination that is twofold: top-down, to offer a coordinated control program of interacting schemata (functional units, underlying behavior, which can be activated in different combinations) to achieve behavior noted by neuroethologists; and bottom-up, to provide detailed models of neural networks that are consistent with known anatomy and physiology, but that involve additional assumptions, amenable to experimental testing, to yield a network capable of exhibiting appropriate behavior. Rana computatrix, an evolving series of models of frog and toad visuomotor coordination, is described.

Animals↗

PubMed1975