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Shanahan, M.

Publications and source records attributed to Shanahan, M..

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Assessing Selectivity in the Basal Ganglia: The "Gearbox" Hypothesis

A plethora of evidence and theoretical work indicates that the basal ganglia (BG) might be the locus where conflicts between prospective motor programs, or actions, are being resolved. Similarly to the majority of brain regions, oscillations in this subcortical group are ubiquitous, largely driven by the cortex and associated with a number of motor symptoms in neurodegenerative diseases. However, the literature so far contains no systematic attempt to address the impact of cortical oscillations on the ability of the BG to select. In this study, we employed a state of the art spiking neural model of the BG circuitry and investigated the effectiveness of the BG as an action selection device. We found that cortical frequency, phase, dopamine and the examined time scale, all have a very important impact on the models ability to select. Our simulations resulted n a canonical profile of selectivity, termed selectivity portraits, which suggests that the cortex is the structure that determines whether selection will be performed in the BG and what strategy will be utilized. Some frequency ranges promote the exploitation of highly salient actions, others promote the exploration of alternative options, while the remaining frequencies simply halt the selection process. Based on this behaviour, we propose that the BG circuitry can be viewed as the \"gearbox\" of action selection. Coalitions of rhythmic cortical areas are able to switch between a repertoire of available BG modes which, in turn, change the course of information flow within the Cortico BG thalamo cortical loop. Dopamine, akin to \"control pedals\", either stops or initiates a decision, while cortical frequencies, as a \"gear lever\", determine whether a decision can be triggered and what type of decision this will be. Finally, we identified a selection cycle with a period of around 200ms, which was used to assess the biological plausibility of the popular cognitive architectures.

neuroscience

A functioning model of human time perception

Despite being a fundamental dimension of experience, how the human brain generates the perception of time remains unknown. Here, we provide a novel explanation for how human time perception might be accomplished, based on non-temporal perceptual clas-sification processes. To demonstrate this proposal, we built an artificial neural system centred on a feed-forward image classification network, functionally similar to human visual processing. In this system, input videos of natural scenes drive changes in network activation, and accumulation of salient changes in activation are used to estimate duration. Estimates produced by this system match human reports made about the same videos, replicating key qualitative biases, including differentiating between scenes of walking around a busy city or sitting in a cafe or office. Our approach provides a working model of duration perception from stimulus to estimation and presents a new direction for examining the foundations of this central aspect of human experience.

neuroscience