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T J Prescott

Publications and source records attributed to T J Prescott.

7 recordsLinked to original sources

The brainstem reticular formation is a small-world, not scale-free, network.

Recently, it has been demonstrated that several complex systems may have simple graph-theoretic characterizations as so-called 'small-world' and 'scale-free' networks. These networks have also been applied to the gross neural connectivity between primate cortical areas and the nervous system of Caenorhabditis elegans. Here, we extend this work to a specific neural circuit of the vertebrate brain--the medial reticular formation (RF) of the brainstem--and, in doing so, we have made three key contributions. First, this work constitutes the first model (and quantitative review) of this important brain structure for over three decades. Second, we have developed the first graph-theoretic analysis of vertebrate brain connectivity at the neural network level. Third, we propose simple metrics to quantitatively assess the extent to which the networks studied are small-world or scale-free. We conclude that the medial RF is configured to create small-world (implying coherent rapid-processing capabilities), but not scale-free, type networks under assumptions which are amenable to quantitative measurement.

Animals↗

Testing computational hypotheses of brain systems function: a case study with the basal ganglia.

We develop a methodology for testing computational hypotheses about neural functionality articulated in models at the systems level of description. In this approach, the first step is to attempt the construction of a model of the underlying brain system which is consistent with the known anatomy and physiology, but which is also able to exhibit functional properties consistent with a putative computational hypothesis. If this is successful, the second step consists of including additional known pathways into the model and testing the new models to see whether they show an improvement in functional performance (using appropriate performance metrics). A positive outcome is taken as evidence in support of the hypothesis. A final step is to construct 'control' models by including pathways that are not consistent with biological data. In this case a performance detriment is taken as support for the hypothesis. The methodology is applied to the basal ganglia, and builds on a previously published model of this system (Gurney et al 2001 Biol. Cybern. 84 401-23) which was based on the hypothesis that the basal ganglia perform action selection. The realistically constrained models show a selection benefit, while control models show a decrement in selection ability. These results, taken together, provide further validation of our selection hypothesis of basal ganglia function.

Animals↗

A computational model of action selection in the basal ganglia. I. A new functional anatomy.

We present a biologically plausible model of processing intrinsic to the basal ganglia based on the computational premise that action selection is a primary role of these central brain structures. By encoding the propensity for selecting a given action in a scalar value (the salience), it is shown that action selection may be recast in terms of signal selection. The generic properties of signal selection are defined and neural networks for this type of computation examined. A comparison between these networks and basal ganglia anatomy leads to a novel functional decomposition of the basal ganglia architecture into 'selection' and 'control' pathways. The former pathway performs the selection per se via a feedforward off-centre on-surround network. The control pathway regulates the action of the selection pathway to ensure its effective operation, and synergistically complements its dopaminergic modulation. The model contrasts with the prevailing functional segregation of basal ganglia into 'direct' and 'indirect' pathways.

Animals↗

A computational model of action selection in the basal ganglia. II. Analysis and simulation of behaviour.

In a companion paper a new functional architecture was proposed for the basal ganglia based on the premise that these brain structures play a central role in behavioural action selection. The current paper quantitatively describes the properties of the model using analysis and simulation. The decomposition of the basal ganglia into selection and control pathways is supported in several ways. First, several elegant features are exposed--capacity scaling, enhanced selectivity and synergistic dopamine modulation--which might be expected to exist in a well designed action selection mechanism. The discovery of these features also lends support to the computational premise of selection that underpins our model. Second, good matches between model globus pallidus external segment output and globus pallidus internal segment and substantia nigra reticulata area output, and neurophysiological data, have been found which are indicative of common architectural features in the model and biological basal ganglia. Third, the behaviour of the model as a signal selection mechanism has parallels with some kinds of action selection observed in animals under various levels of dopaminergic modulation.

Animals↗

Is the short-latency dopamine response too short to signal reward error?

Unexpected stimuli that are behaviourally significant have the capacity to elicit a short-latency, short-duration burst of firing in mesencephalic dopaminergic neurones. An influential interpretation of the experimental data that characterize this response proposes that dopaminergic neurones have a crucial role in reinforcement learning because they signal error in the prediction of future reward. In this article we propose a different functional role for this 'short-latency dopamine response' in the mechanisms that underlie associative learning. We suggest that the initial burst of dopaminergic-neurone firing could represent an essential component in the process of switching attentional and behavioural selections to unexpected, behaviourally important stimuli. This switching response could be a crucial prerequisite for associative learning and might be part of a general short-latency response that is mediated by catecholamines and prepares the organism for an appropriate reaction to biologically significant events. Any act which in a given situation produces satisfaction becomes associated with that situation so that when the situation recurs the act is more likely than before to recur also. E.L. Thorndike (1911) 1.

Action Potentials↗

The basal ganglia: a vertebrate solution to the selection problem?

A selection problem arises whenever two or more competing systems seek simultaneous access to a restricted resource. Consideration of several selection architectures suggests there are significant advantages for systems which incorporate a central switching mechanism. We propose that the vertebrate basal ganglia have evolved as a centralized selection device, specialized to resolve conflicts over access to limited motor and cognitive resources. Analysis of basal ganglia functional architecture and its position within a wider anatomical framework suggests it can satisfy many of the requirements expected of an efficient selection mechanism.

Animals↗

A robot trace maker: modeling the fossil evidence of early invertebrate behavior.

The study of trace fossils, the fossilized remains of animal behavior, reveals interesting parallels with recent research in behavior-based robotics. This article reports robot simulations of the meandering foraging trails left by early invertebrates that demonstrate that such trails can be generated by mechanisms similar to those used for robot wall-following. We conclude with the suggestion that the capacity for intelligent behavior shown by many behavior-based robots is similar to that of animals of the late Precambrian and early Cambrian periods approximately 530 to 565 million years ago.

Animals↗