Probing new targets for movement disorders

Science

Two Parkinson's patients receive deep brain stimulation (DBS) in their subthalamic nuclei. Despite accurate electrode placement, one patient is able to stand up and walk effortlessly around the room while the other breaks down into uncontrolled sobbing that only stops once the stimulator is turned off. This paradox exposes one of the major roadblocks in developing therapies for brain disorders: the elaborate and diffuse nature of neural circuits. Physically proximal neurons are often engaged in functionally different pathways; whereas modulation of one pathway might be therapeutic, modulation of those surrounding it may produce debilitating side effects. The problem with high-amplitude electrical stimulation, as applied during DBS, is that it affects not only the activity of neurons around the electrode, but also the activity of neurons whose long extensions happen to pass by the electrode.


Stocco

AAAI Conferences

One of the open issues in developing large-scale computational models of the brain is how the transfer of information between communicating cortical regions is controlled. Here, we present a model where the basal ganglia implement such a conditional information routing system. The basal ganglia are a set of subcortical nuclei that play a central role in cognition. Like a switchboard, the model basal ganglia direct the communication between cortical regions by alerting the destination regions to the presence of important signals coming from the source regions. This way, they can impose serial control on the massive parallel communication between cortical areas. The model also incorporates a possible mechanism by which subsequent transfers of information control the release of dopamine. This signal is used to produce novel stimulus-response associations by internalizing the representation being transferred in the striatum. We discuss how this neural circuit can be seen as a biological implementation of a production system. This comparison highlights the basal ganglia as bridge between computational models of small-size brain circuits and high-level characterizations of complex cognition, such as cognitive architectures.


Different Cortico-Basal Ganglia Loops Specialize in Reward Prediction at Different Time Scales

Neural Information Processing Systems

To understand the brain mechanisms involved in reward prediction on different time scales, we developed a Markov decision task that requires prediction of both immediate and future rewards, and analyzed subjects'brain activities using functional MRI. We estimated the time course of reward prediction and reward prediction error on different time scales from subjects' performance data, and used them as the explanatory variables for SPM analysis. We found topographic mapsof different time scales in medial frontal cortex and striatum. The result suggests that different cortico-basal ganglia loops are specialized for reward prediction on different time scales.


FS04-01-007.pdf

AAAI Conferences

Engines of the brain: the computational "instruction set" of perception and cognition Abstract Cognition is the action and interaction of multiple brain regions, and these are becoming understood computationally. Simulation and analysis has led to derivation of a set of elemental operations that emerge from individual and combined brain circuits, such that each circuit contributes a particular algorithm, and pairs and larger groups interact to compose further algorithms. We forward the hypothesis that these operations constitute the "instruction set" of the brain, i.e., that these are the most basic mental operations, from which all other behavioral and cognitive operations are constructed, constructing a unified formalism for description of operations ranging from perceptual to cognitive, including vision, language, learning and reasoning. Figure 1 depicts the primary elements of the mammalian forebrain (telencephalon), shared across all mammalian species. Whereas posterior neocortex receives sensory inputs (via dorsal thalamus), anterior neocortex produces motor outputs and, in so doing, interacts closely with the basal ganglia, a more ancient structure that dominates reptilian brains. Mammalian brains scale across several orders of magnitude (e.g., from milligrams to kilograms), yet overwhelmingly retain their structural design characteristics. As the ratio of brain size to body size grows, particular allometric changes occur, defining differences between bigger and smaller brain designs. Figure 1b illustrates the three largest changes: 1) Connection pathways between anterior and posterior cortex (fasciculi) grow large 2) Output pathways from striatal complex change relative size: the recurrent pathway back to cortex via thalamus increases relative to the descending motor pathway 3) Descending output from anterior cortex to motor systems (pyramidal tract) grows large These changes grow disproportionately with increased brain-body ratio, becoming notably outsized in humans.


Dopamine, Learning, and Production Rules: The Basal Ganglia and the Flexible Control of Information Transfer in the Brain

AAAI Conferences

One of the open issues in developing large-scale computational models of the brain is how the transfer of information between communicating cortical regions is controlled. Here, we present a model where the basal ganglia implement such a conditional information routing system. The basal ganglia are a set of subcortical nuclei that play a central role in cognition. Like a switchboard, the model basal ganglia direct the communication between cortical regions by alerting the destination regions to the presence of important signals coming from the source regions. This way, they can impose serial control on the massive parallel communication between cortical areas. The model also incorporates a possible mechanism by which subsequent transfers of information control the release of dopamine. This signal is used to produce novel stimulus-response associations by internalizing the representation being transferred in the striatum. We discuss how this neural circuit can be seen as a biological implementation of a production system. This comparison highlights the basal ganglia as bridge between computational models of small-size brain circuits and high-level characterizations of complex cognition, such as cognitive architectures.