Scientific Understanding of Consciousness
Consciousness as an Emergent Property of Thalamocortical Activity

Basal Ganglia loops for Action Selection


Philos Trans R Soc Lond B Biol Sci. 2007 September 29; 362(1485): 1573–1583.

Action selection and refinement in subcortical loops through basal ganglia and cerebellum

J.C Houk, C Bastianen, D Fansler, A Fishbach, D Fraser, P.J Reber, S.A Roy, and L.S Simo

Northwestern University Medical School, Chicago, IL 60208, USA


Subcortical loops through the basal ganglia and the cerebellum form computationally powerful distributed processing modules (DPMs). This paper relates the computational features of a DPM's loop through the basal ganglia to experimental results for two kinds of natural action selection. First, functional imaging during a serial order recall task was used to study human brain activity during the selection of sequential actions from working memory. Second, microelectrode recordings from monkeys trained in a step-tracking task were used to study the natural selection of corrective submovements. Our DPM-based model assisted in the interpretation of puzzling data from both of these experiments. We come to posit that the many loops through the basal ganglia each regulate the embodiment of pattern formation in a given area of cerebral cortex. This operation serves to instantiate different kinds of action (or thought) mediated by different areas of cerebral cortex. We then use our findings to formulate a model of the aetiology of schizophrenia.


The higher-order circuitry of the brain comprises a large-scale network of cerebral cortical areas that are individually regulated by loops through subcortical structures, particularly through the basal ganglia and the cerebellum. These subcortical loops form distributed processing modules (DPMs) that have powerful computational architectures. The final outcome of all of the computations in a given DPM is a spatio-temporal pattern of activity in the module's output vector, representing the activity in its set of cortical output neurons. This allows a given DPM to participate in the computations taking place in other areas of cerebral cortex or in the brainstem or spinal cord.


The loop through the basal ganglia is thought to regulate the selection and/or initiation of pattern formation. The term embodiment is used in to capture both possibilities, i.e. selection and initiation, the former occurring when disinhibition allows other cortical inputs to initiate and the latter when the selection is strong and does its own initiation. Embodiment is critically dependent on the refined, neuromodulated pattern classification operations that take place in the input layer of the basal ganglia, the striatum. According to most contemporary models, bursts of striatal spiny neurons, via the direct pathway through the basal ganglia, disinhibit their targets in thalamus, allowing thalamo-cortical loops to embody patterns of activity that represent a ballpark estimate of an action or a thought. There are also mechanisms, via less direct pathways through the basal ganglia, for inhibiting the embodiment of patterns that would represent poor choices in action selection.


Once a tentative pattern has been selected and initiated through the operation of the loops through the basal ganglia,   the loops through the cerebellum   amplify and sculpt that pattern into a refined output vector. The amplification step appears to be implemented by the loop through the cerebellar nuclei. Regenerative positive feedback in this loop    amplifies the output's intensity, duration and spatial extent. The restraint of this amplification process and, more importantly, sculpting it into an accurate representation of an action (or thought) is implemented by the loop through the cerebellar cortex. The cerebellar cortex is considered to be an exceptional neuronal architecture for learning difficult computations and so is well suited to this refinement task.


Although many authors have suggested that the loop through the basal ganglia plays an important role in action selection, there are diverse views concerning the mechanism by which this might occur. Most authors agree that action selection occurs in the input nucleus of the basal ganglia loop, namely the striatum. There are different views about the mechanisms for preventing actions, which will not be discussed here.


The dorsal part of the striatum, the neostriatum, comprises two divisions, the caudate nucleus and the putamen. The principal neurons of both the caudate and the putamen, the medium spiny neurons, are inhibitory GABAergic projection neurons. They emit an elaborate array of collaterals to neighbouring spiny neurons before they project to output stages of the basal ganglia, namely to either globus pallidus or substantia nigra pars reticulataSpiny neurons with collaterals that inhibit each other gives rise to an inhibitory feedback network entirely within the neostriatum. This local feedback network mediates a competitive pattern classification operation. Collateral inhibition is deemed an effective mechanism for competition by some authors and ineffective by others, the latter believing that feed-forward inhibition regulates the pattern classification operation.


Tracking movements that require both speed and accuracy consist of a primary movement that is often off-target, in which case it is accompanied by one or more corrective submovements. The corrective submovements often occur before the primary movement is completed, which suggests that the neural control system uses a forward model to predict the movement endpoint based on a copy of the neural command (efference copy) and delayed sensory feedback.


Whether the update of motor commands is continuous or intermittent is still under debate. Our findings from a statistical analysis of the properties of submovements under conditions in which perturbations of target location were introduced at movement onset strongly support the hypothesis that the neural controller predicts the need for a correction and selects an appropriate one intermittently.


The DPM model posits that practice in a task allows regularly rehearsed processing steps to be exported from the basal ganglia and/or cerebellum to the area of cerebral cortex to which the channel projects. The control of primary movements can be exported to the motor cortex since they are rehearsed in every trial. In contrast, the corrective submovements vary substantially from trial to trial, so nothing regular is rehearsed. This model of knowledge transfer from the basal ganglia to the cerebral cortex is supported by combined recordings of single cell activity from the neostriatum and frontal cortex. It is also supported by simulations of dopamine modulation in the basal ganglia and by imaging data


Comprehension of brain dynamics may require an understanding of the assembly language of the brain, its machine language so to speak. The model used here assumes that the brain's assembly language is the firing rate of its individual neurons. The output of each DPM is a vector of firing rates in its population of output neurons. Although population discharge contains some information in addition to its rate code, due to the tendency for population activity to become synchronized, the evidence that synchronization is actually used to control actions is meagre. The key issue for us concerns whether or not there exists a biophysical mechanism for decoding a synchronicity signal into a selected action. Since thus far none have been documented, we treated synchronicity as an epiphenomenon and decided to focus our modelling efforts on firing rate, ignoring the detailed timing of action potentials.


Our model of action selection is motivated by the existence of powerful computational features in the loops through the basal ganglia. The pattern classification operation takes place in the striatal layer of a DPM. Computationally powerful pattern classification derives from several unique features of striatal medium spiny neurons. These features include (i) a high convergence ratio that presents nearly 20,000 different cortical inputs to any given spiny neuron, (ii) a three-factor learning rule that uses reward-predicting training signals from dopamine neurons to consolidate long-term potentiation learning, (iii) an attentional neuromodulatory factor that induces bistability and nonlinear amplification in spiny neurons, and (iv) competition among spiny neurons mediated by presynaptic and postsynaptic collateral inhibition.


The anatomically demonstrated projections that loop back to the same area of cortex from which they derive allow cortical-basal ganglionic modules to perform serial order processing. This feature allows them in principle to implement immediate serial order recall from working memories of a sequence. Long-term memories of serial order could be stored in cortico-cortical synapses or in the synapses between cortical neurons and striatal spiny neurons. The latter storage mechanism is thought to have a larger memory capacity for salient information. The recall of previously learned sequences should also be efficient because cortical-basal ganglionic modules implement parallel searches through a vast repertoire of past experiences stored in the synapses of spiny neurons.


We posit that both serial order recall and online error correction are prime examples of natural action selection. They appear to use analogous mechanisms for signal processing in their respective DPMs. Models comprising networks of DPMs may provide a useful substrate for studying complex behaviours and for exploring the underlying dynamics of the mind. Such simulations may help us to understand the aetiology and treatment of Parkinson's disease, ADHD and schizophrenia.

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