An investigation into the causal relationship between sensory attenuation and motor initiation: a novel hypothesis for motor control & movement disorders
Prior to and during movement afferent input to the cortex is reduced (Cohen and Starr, 1987; Hughes et al., 2013; Hughes and Waszak, 2011; Starr and Cohen, 1985). This robust phenomenon of sensory attenuation has been proposed to distinguish between biologically salient external sensations and our highly predictable self-generated sensory input. However, a recent theoretical framework, active inference, posits that this sensory gating may actually represent a necessary mechanism for movement initiation. Brown et al (2013) hypothesise that sensory attenuation “is a necessary consequence of reducing the precision of sensory evidence during movement to allow the expression of proprioceptive predictions that incite movement” (Brown et al., 2013; K. Friston et al., 2011; Friston et al., 2010). This theory predicts that estimates of the gain, or precision (inverse uncertainty), surrounding the ascending afferent input to sensorimotor cortex must be reduced in order to allow movements to be initiated (Brown et al., 2013). The mechanism underlying this theory comes from applying the ideas of predictive coding and Bayesian inference, that have been readily used to describe perception in multiple sensory modalities, to the sensorimotor system. However, this theory is grounded in computational and theoretical work, which is lacking empirical evidence. In this PhD, I conducted a series of experiments using behavioural tasks and electroencephalography (EEG) in humans to test specific predictions from this overarching hypothesis. More specifically, I aimed to better characterise somatosensory attenuation, determine the neurophysiological correlate of sensory precision in the cortex and determine the consequences of modulating sensory precision on behaviour and cortical oscillatory activity. As well as offering new insights into how we control movements, this PhD offers novel avenues for understanding movement disorders, in particular Parkinson’s disease (PD), and generates a number of testable hypotheses for future clinical work
