Goto

Collaborating Authors

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.


News Detail - Research in Germany

#artificialintelligence

Tourette's syndrome is a neuro-psychiatric disease defined by the occurrence of so-called "tics". Tics are sudden, fast and recurring non-rhythmic movements or sound expressions. The development of tics is associated with specific abnormalities of brain activity. Basal ganglia in particular are attributed a role in the development of tics. The underlying mechanisms are still largely unexplored.


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.


An Integrated Computational Framework for Attention, Reinforcement Learning, and Working Memory

AAAI Conferences

This paper proposes a reinterpretation of selective attention as a form of control of working memory based on self-generated reward signals and model-free reinforcement learning. In addition to being simple and parsimonious, this approach systematizes a number of classic psychological constructs without calling for additional, specific mechanisms. Finally, the papers presents the results of an empirical test of this framework, and elaborates on the implications of our findings for general models of control and intelligent behavior, as well as neurobiological models of the basal ganglia.