Petitet, P. | bioRxiv Science

bioRxiv2018

Causal explanation of individual differences in human sensorimotor memory formation

Sensorimotor cortex mediates the formation of adaptation memory. Individuals differ in the rate at which they acquire, retain, and generalize adaptation. We present a mechanistic explanation of the neurochemical and computational causes of this variation in humans. Neuroimaging identified structural, functional and neurochemical covariates of a computational parameter that determines memory persistence. To establish causality, we increased sensorimotor cortex excitability during adaptation, using transcranial direct current stimulation. As predicted, this increased retention. Inter-individual variance in the stimulation-induced E:I increase predicted the computational change, which predicted the memory gain. These relations did not hold, and memory was unchanged, with stimulation applied before adaptation. This cognitive state dependent effect was modulated by the BDNF val66met genetic polymorphism. Memory was enhanced by stimulation in Val/Val carriers only, implicating a mechanistic role for activity-dependent BDNF secretion. Sensorimotor cortex E:I causally determines the time constant of memory persistence, explaining phenotypic variation in adaptation decay.

neuroscience↗

bioRxiv2017

Towards a neuro-computational account of prism adaptation

Prism adaptation has a long history as an experimental paradigm used to investigate the functional and neural processes that underlie sensorimotor control. In the neuropsychology literature, functional explanations of prism adaptation are typically framed within a traditional cognitive psychology box-and-arrow framework that distinguishes putative component functions thought to give rise to behaviour (i.e. strategic control versus spatial realignment). However, this kind of theoretical framework lacks precision and explanatory power. Here, we advocate for a computational framework that offers several advantages: 1) an algorithmic explanatory account of the computations and operations that drive behaviour; 2) expressed in quantitative mathematical terms; 3) embedded within a principled theoretical framework (Bayesian decision theory, state-space modelling); 4) that offers a means to generate and test quantitative behavioural predictions. This computational framework offers a route toward mechanistic explanations of prism adaptation behaviour. Thus it constitutes a conceptual advance compared to the traditional theoretical framework. In this paper, we illustrate how Bayesian decision theory and state-space models offer principled explanations for a range of behavioural phenomena in the field of prism adaptation (e.g. visual capture, magnitude of visual versus proprioceptive realignment, spontaneous recovery and dynamics of adaptation memory). We argue that this explanatory framework offers to advance understanding of the functional and neural mechanisms that implement prism adaptation behaviour, by enabling quantitative tests of hypotheses that go beyond mere descriptive mapping claims that brain area X is (somehow) involved in psychological process Y.

neuroscience↗