AbstractÑA 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 centralised selection device, specialised 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.

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.

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.

The basal ganglia are often conceptualised as three parallel domains that include all the constituent nuclei. The 'ventral domain' appears to be critical for learning flexible behaviours for exploration and foraging, as it is the recipient of converging inputs from amygdala, hippocampal formation and prefrontal cortex, putatively centres for stimulus evaluation, spatial navigation, and planning/contingency, respectively. However, compared to work on the dorsal domains, the rich potential for quantitative theories and models of the ventral domain remains largely untapped, and the purpose of this review is to provide the stimulus for this work. We systematically review the ventral domain's structures and internal organisation, and propose a functional architecture as the basis for computational models. Using a full schematic of the structure of inputs to the ventral striatum (nucleus accumbens core and shell), we argue for the existence of many identifiable processing channels on the basis of unique combinations of afferent inputs. We then identify the potential information represented in these channels by reconciling a broad range of studies from the hippocampal, amygdala and prefrontal cortex literatures with known properties of the ventral striatum from lesion, pharmacological, and electrophysiological studies. Dopamine's key role in learning is reviewed within the three current major computational frameworks; we also show that the shell-based basal ganglia sub-circuits are well placed to generate the phasic burst and dip responses of dopaminergic neurons. We detail dopamine's modulation of ventral basal ganglia's inputs by its actions on pre-synaptic terminals and post-synaptic membranes in the striatum, arguing that the complexity of these effects hint at computational roles for dopamine beyond current ideas. The ventral basal ganglia are revealed as a constellation of multiple functional systems for the learning and selection of flexible behaviours and of behavioural strategies, sharing the common operations of selection-by-disinhibition and of dopaminergic modulation.

Unexpected stimuli which are behaviourally significant have the capacity to evoke a short latency, short duration burst of firing in mesencephalic dopamine neurones. An influential interpretation of the experimental data characterising this response proposes that dopamine neurones play a critical role in reinforcement learning by signalling errors in the prediction of future reward. In the present viewpoint we propose a different functional role for the short latency dopamine response in the mechanisms of associative learning.We suggest that the initial burst of dopaminergic firing may represent an essential component in the process of switching attentional and behavioural selections to unexpected, behaviourally important stimuli. This switching response could be a critical prerequisite for associative learning and may be part of a general short latency reaction, mediated by catecholamines, which prepares the organism to react appropriately to biologically significant events. Introduction:ÒAny 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 alsoÓ. Although the effects of positive and negative reinforcement on behaviour have been known for centuries, Thorndike 1 in this statement formalised the linking of action to situation on the basis of outcome. It also emphasises two of the principal functions of rewarding or appetitive stimuli: to produce satisfaction (hedonia) and to adjust the probabilities of selecting immediately preceding actions. A third, often recognised function of rewarding stimuli is to elicit approach and consummatory behaviour 2 . While the neural mechanisms mediating any of these processes have yet to be identified in detail, much evidence points to the vertebrate basal ganglia playing a central role 3 . Numerous investigations of this system using a wide range of experimental techniques suggest that ascending dopaminergic projections from the ventral midbrain (substantia nigra pars compacta (SNc) and the ventral tegmental area (VTA)) to the striatum (caudate, putamen and nucleus accumbens) provide essential signals for reinforcement learning 2, 4, 5 . Currently, a popular view is that dopaminergic input to the striatum provides the reinforcement signal required to adjust the probabilities of subsequent action selection [4][5][6][7] . A particularly important and influential part of the evidence supporting this view concerns the short latency, short duration response of dopamine cells observed after the unexpected presentation of a behaviourally significant stimulus 2,8 . This response has been widely interpreted as providing the system with a reinforcement prediction error signal 5, 9 . We will, however, argue that the short latency burst of dopamine activity could have a rather different functional role. Specifically, we suggest that the short latency response may represent an important component of the processes responsible for re-allocating attentional and behavioural re...