Computational models of basal-ganglia pathway functions: focus on functional neuroanatomy

By Henning Schroll, Fred Henrik Hamker. 2013

139 citations recorded by the source corpus.

Over the past 15 years, computational models have had a considerable impact on basal-ganglia research. Most of these models implement multiple distinct basal-ganglia pathways and assume them to fulfill different functions. As there is now a multitude of different models, it has become complex to keep track of their various, sometimes just marginally different assumptions on pathway functions. Moreover, it has become a challenge to oversee to what extent individual assumptions are corroborated or challenged by empirical data. Focusing on computational, but also considering non-computational models, we review influential concepts of pathway functions and show to what extent they are compatible with or contradict each other. Moreover, we outline how empirical evidence favors or challenges specific model assumptions and propose experiments that allow testing assumptions against each other.

Subfields: Cellular and Molecular Neuroscience, Neurology

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Citations in the corpus

Born to Learn: the Inspiration, Progress, and Future of Evolved Plastic Artificial Neural Networks (2017, background): “Computational models of, e.g., the basal ganglia and modulatory systems may propose plasticity mechanisms and aim to demonstrate the computational relations among various nuclei, pathways, and learning processes (Krichmar, 2008; Vitay and Hamker, 2010; Schroll and Hamker, 2015).”