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

Quantity as a Fish Views It: Behavior and Neurobiology

An ability to estimate quantities, such as the number of conspecifics or the size of a predator, has been reported in vertebrates. Fish, in particular zebrafish, may be instrumental in advancing the understanding of magnitude cognition. We review here the behavioral studies that have described the ecological relevance of quantity estimation in fish and the current status of the research aimed at investigating the neurobiological bases of these abilities. By combining behavioral methods with molecular genetics and calcium imaging, the involvement of the retina and the optic tectum has been documented for the estimation of continuous quantities in the larval and adult zebrafish brain, and the contributions of the thalamus and the dorsal-central pallium for discrete magnitude estimation in the adult zebrafish brain. Evidence for basic circuitry can now be complemented and extended to research that make use of transgenic lines to deepen our understanding of quantity cognition at genetic and molecular levels.

Numerosities and Other Magnitudes in the Brains: A Comparative View

The ability to represent, discriminate, and perform arithmetic operations on discrete quantities (numerosities) has been documented in a variety of species of different taxonomic groups, both vertebrates and invertebrates. We do not know, however, to what extent similarity in behavioral data corresponds to basic similarity in underlying neural mechanisms. Here, we review evidence for magnitude representation, both discrete (countable) and continuous, following the sensory input path from primary sensory systems to associative pallial territories in the vertebrate brains. We also speculate on possible underlying mechanisms in invertebrate brains and on the role played by modeling with artificial neural networks. This may provide a general overview on the nervous system involvement in approximating quantity in different animal species, and a general theoretical framework to future comparative studies on the neurobiology of number cognition.

Levels of modeling of mechanisms of visually guided behavior

Intermediate constructs are required as bridges between complex behaviors and realistic models of neural circuitry. For cognitive scientists in general, schemas are the appropriate functional units; brain theorists can work with neural layers as units intermediate between structures subserving schemas and small neural circuits.

After an account of different levels of analysis, we describe visuomotor coordination in terms of perceptual schemas and motor schemas. The interest of schemas to cognitive science in general is illustrated with the example of perceptual schemas in high-level vision and motor schemas in the control of dextrous hands.

Rana computatrix, the computational frog, is introduced to show how one constructs an evolving set of model families to mediate flexible cooperation between theory and experiment. Rana computatrix may be able to do for the study of the organizational principles of neural circuitry what Aplysia has done for the study of subcellular mechanisms of learning. Approach, avoidance, and detour behavior in frogs and toads are analyzed in terms of interacting schemas. Facilitation and prey recognition are implemented as tectal-pretectal interactions, with the tectum modeled by an array of tectal columns. We show how layered neural computation enters into models of stereopsis and how depth schemas may involve the interaction of accommodation and binocular cues in anurans.

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.

The effect of stimulus features on the visual orienting behaviour of the salamander Plethodon jordani

The effects of the visual features of prey-like objects on the orienting behaviour of the salamander Plethodon jordani were studied. Two stimuli (cricket dummies, rectangles), moving in opposite directions, were presented simultaneously on a computer screen. They differed in size, contrast, velocity and movement pattern of the entire body or the body appendages. Size and velocity appeared to be the dominant features; shape was of lesser importance. Contrast and movement pattern were of intermediate importance and local motion of little importance. This rank order was the same when the probability of a response to the different stimuli was estimated by means of the maximum-likelihood method. Cluster analysis revealed that in all animals stimuli could be grouped into five clusters. Among individuals, the rank order of stimuli was similar for high- and low-ranking stimuli and varied for those of intermediate rank; stimuli could be grouped into 3–5 clusters. Our findings favour the view that, in amphibians, prey recognition is guided by a number of visual features acting either alone or in combination and depending on internal motivational or attentional states and individual experience.

Movie available on-line: http://www.biologists.com/JEB/movies/jeb3864.html.

A framework for models of biological behaviour

Modelling is most clearly understood as a adjunct in the process of deriving predictions from hypotheses. By representing a hypothesised mechanism in a model we hope by manipulating the model to understand the hypotheses' consequences. Eight dimensions on which models of biological behaviour can vary are described: the degree of realism with which they apply to biology; the level of biology they represent; the generality or range of systems the model is supposed to cover; the abstraction or amount of biological detail represented; the accuracy of representation of the mechanisms; the medium in which the model is built; the match of the model behaviour to biological behaviour; and the utility of the model in providing biological understanding and/or technical insight. It is hoped this framework will help to clarify debates over different approaches to modelling, particularly by pointing out how the above dimensions are relatively independent and should not be conflated.

Modeling neural mechanisms of vertebrate habituation: locus specificity and pattern discrimination

A critical problem in neurobiology is to explain how the central nervous system coordinates pattern discrimination and locus specificity in learning. This problem is investigated in anuran amphibians who demonstrate both locus specificity and pattern discrimination in visual habituation. A neural mechanism is proposed whereby neural circuitry for pattern discrimination is shared by a spatial memory system. Such learning processes are argued to occur in the medial pallium (MP), the anuran's homolog of mammalian hippocampus. Necessary mapping from the shared network to spatial memory is set up by a mechanism that forms topographical connections, with desired orientation determined by activity gradient in presynaptic and postsynaptic layers. The model of MP is tested on both locus and stimulus specific habituation, which involve short-term as well as long-term synaptic plasticity. Successful modeling yields a set of predictions concerning MP organization and learning properties.

Prey-catching and predator-avoidance in frog and toad: defining the schemas

The present model postulates the construction of motor actions through the interaction of different motor schemas via a process of competition and co-operation wherein there is no need for a unique schema to win the competition (although that might well be the result) since two or more schemas may simultaneously be active and co-operate to yield a more complicated motor pattern. Based on lesion data, our model is structured on the principles of segregation of co-ordinate systems and participation of maps intermediate between sensory and motor schemas. The motor schemas are driven by specific internal maps which between them constitute a distributed internal representation of the world. These maps collectively provide the transition from topographically-coded sensory information to frequency-coded inputs to the diverse motor schemas that drive muscle activity. We stimulate data on approach and avoidance behavior of the frog or toad under normal conditions and under lesion of different brain centers. For example, the model generates different motor zones for prey-catching behavior which match those observed experimentally in normal conditions and in the medullary hemifield deficit, and offers predictions for new experiments on both approach and avoidance behaviors.

Mathematical model and simulation of retina and tectum opticum of lower vertebrates

The processing of information within the retino-tectal visual system of amphibians is decomposed into five major operational stages, three of them taking place in the retina and two in the optic tectum. The stages in the retina involve (i) a spatially local high-pass filtering in connection to the perception of moving objects, (ii) separation of the receptor activity into ON- and OFF-channels regarding the distinction of objects on both light and dark backgrounds, (iii) spatial integration via near excitation and far-reaching inhibition. Variation of the spatial range of excitation and inhibition allows to account for typical activities observed in a variety of classes of retina ganglion cells. Mathematical description of the operations in the tectum opticum include (i) spatial summation of retinal output (mainly of class-2 and class-3 retina ganglion cells), and (ii) direct or indirect lateral inhibition between tectal cells. In the computer simulation, first the output of the mathematical retina model is computed which, then, is used as the input to the tectum model. The full spatio-temporal dynamics is taken into account. The simulations show that different combinations of strength of lateral inhibition on the one side and the response properties of the retina ganglion cells on the other side determine the response properties of tectal cell types involved in object recognition.