Based on recent experimental data, we have developed a conductance-based computational network model of the subthalamic nucleus and the external segment of the globus pallidus in the indirect pathway of the basal ganglia. Computer simulations and analysis of this model illuminate the roles of the coupling architecture of the network, and associated synaptic conductances, in modulating the activity patterns displayed by this network. Depending on the relationships of these coupling parameters, the network can support three general classes of sustained firing patterns: clustering, propagating waves, and repetitive spiking that may show little regularity or correlation. Each activity pattern can occur continuously or in discrete episodes. We characterize the mechanisms underlying these rhythms, as well as the influence of parameters on details such as spiking frequency and wave speed. These results suggest that the subthalamopallidal circuit is capable both of correlated rhythmic activity and of irregular autonomous patterns of activity that block rhythmicity. Increased striatal input to, and weakened intrapallidal inhibition within, the indirect pathway can switch the behavior of the circuit from irregular to rhythmic. This may be sufficient to explain the emergence of correlated oscillatory activity in the subthalamopallidal circuit after destruction of dopaminergic neurons in Parkinson's disease and in animal models of parkinsonism. Key words: basal ganglia; subthalamic nucleus; globus pallidus; computational models; oscillations; synchrony; Parkinson's diseaseMost current models of the basal ganglia are static models, in that they represent the inputs and outputs of the component nuclei as firing rates. For example, the Albin et al. (1989) model, commonly used to explain the symptoms of Parkinsonism, views the interactions of the direct and indirect pathway as constant in time and explains the symptoms of Parkinson's disease in terms of changes in mean rate of the basal ganglia output (Wichmann and DeLong, 1996). In contrast, recent experimental studies have not strongly confirmed the predicted changes in mean rate in these structures under dopamine depletion, but have instead revealed prominent low-frequency periodicity (4 -30 Hz) of firing and dramatically increased correlations among neurons in the external segment of the globus pallidus (GPe) and the subthalamic nucleus (STN) (Bergman et al., 1994;Nini et al., 1995;Magnin et al., 2000;Raz et al., 2000;Brown et al., 2001). It is remarkable that the changes in firing pattern seen in those structures do not appear to be attributable to comparable changes in the firing patterns of striatal output cells, although cholinergic striatal interneurons show changes comparable with those seen in the globus pallidus (Raz et al., 1996). The authors of those studies have proposed that a rate model of the basal ganglia is inadequate to capture the dynamic interaction of the STN and GPe that may generate these pathological changes.In particular, such dynamic interactions ma...

The basal ganglia (BG) play an important role in motor control, reinforcement learning, and perceptual decision making. Modeling and experimental evidence suggest that, in a speed-accuracy tradeoff, the corticostriatal pathway can adaptively adjust a decision threshold (the amount of information needed to make a choice). In this study, we go beyond the focus of previous works on the direct and hyperdirect pathways to examine the contribution of the indirect pathway of the BG system to decision making in a biophysically based spiking network model. We find that the mechanism of adjusting the decision threshold by plasticity of the corticostriatal connections is effective, provided that the indirect pathway counterbalances the direct pathway in their projections to the output nucleus. Furthermore, in our model, changes within basal ganglia connections similar to those that arise in parkinsonism give rise to strong beta oscillations. Specifically, beta oscillations are produced by an abnormal enhancement of the interactions between the subthalamic nucleus (STN) and the external segment of globus pallidus (GPe) in the indirect pathway, with an oscillation frequency that depends on the excitatory cortical input to the STN and the inhibitory input to the GPe from the striatum. In a parkinsonian state characterized by pronounced beta oscillations, the mean reaction time and range of threshold variation (a measure of behavioral flexibility) are significantly reduced compared with the normal state. Our work thus reveals a specific circuit mechanism for impairments of perceptual decision making associated with Parkinson's disease.

To survive, organisms must extract information from the past that is relevant for their future. How this process is expressed at the neural level remains unclear. We address this problem by developing a novel approach from first principles. We show here how to generate low-complexity representations of the past that produce optimal predictions of future events. We then illustrate this framework by studying the coding of ‘oddball’ sequences in auditory cortex. We find that for many neurons in primary auditory cortex, trial-by-trial fluctuations of neuronal responses correlate with the theoretical prediction error calculated from the short-term past of the stimulation sequence, under constraints on the complexity of the representation of this past sequence. In some neurons, the effect of prediction error accounted for more than 50% of response variability. Reliable predictions often depended on a representation of the sequence of the last ten or more stimuli, although the representation kept only few details of that sequence.

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