Using brain potentials to understand prism adaptation: the error-related negativity and the P300

Abstract

Prism adaptation (PA) is both a perceptual-motor learning task as well as a promising rehabilitation tool for visuo-spatial neglect (VSN)—a spatial attention disorder often experienced after stroke resulting in slowed and/or inaccurate motor responses to contralesional targets. During PA, individuals are exposed to prism-induced shifts of the visual-field while performing a visuo-guided reaching task. After adaptation, with goggles removed, visuomotor responding is shifted to the opposite direction of that initially induced by the prisms. This visuomotor aftereffect has been used to study visuomotor learning and adaptation and has been applied clinically to reduce VSN severity by improving motor responding to stimuli in contralesional (usually left-sided) space. In order to optimize PA's use for VSN patients, it is important to elucidate the neural and cognitive processes that alter visuomotor function during PA. In the present study, healthy young adults underwent PA while event-related potentials (ERPs) were recorded at the termination of each reach (screen-touch), then binned according to accuracy (hit vs. miss) and phase of exposure block (early, middle, late). Results show that two ERP components were evoked by screen-touch: an error-related negativity (ERN), and a P300. The ERN was consistently evoked on miss trials during adaptation, while the P300 amplitude was largest during the early phase of adaptation for both hit and miss trials. This study provides evidence of two neural signals sensitive to visual feedback during PA that may sub-serve changes in visuomotor responding. Prior ERP research suggests that the ERN reflects an error processing system in medial-frontal cortex, while the P300 is suggested to reflect a system for context updating and learning. Future research is needed to elucidate the role of these ERP components in improving visuomotor responses among individuals with VSN.

Neural Signatures of Reward and Sensory Prediction Error in Motor Learning

“…Although 618 the FRN is classically associated with reinforcement learning, recent work has identified the FRN 619 or the closely related error-related negativity (ERN) in various motor learning and execution tasks 620 involving sensory error signals. These studies either concluded that reinforcement and sensory er-621 ror based learning processes share common neural resources, or they simply do not distinguish 622 between these two processes (Krigolson et al 2008;Torrecillos et al 2014;MacLean et al 2015). 623 We argue that the brain processes reward and sensory error feedback through distinct mechanisms, 624 but that the two processes can be confounded when perturbations causing sensory error are also 625 evaluated as an implicit failure to meet task goals.…”

“…25 29 Nikooyan and Ahmed 2015). Electroencephalography (EEG) has been used to identify neural sig-30 natures of error processing in various motor learning and movement execution tasks, but it remains 31 unclear how these neural responses relate to distinct reward and sensory-error based motor learning 32 mechanisms (Krigolson et al 2008;Torrecillos et al 2014;MacLean et al 2015). Here we identified 33 neural signatures of sensory error and reward feedback processing in motor learning using separate 34 learning paradigms that produce comparable changes in behavior.…”

“…It has been proposed that the 75 P300 reflects the updating of a model of stimulus context (Donchin and Coles 1988). Both the FRN 76 and the P300 have been observed in response to errors in motor tasks (Krigolson et al 2008; Torrecil-77 los et al 2014;MacLean et al 2015;Reuter et al 2018;Savoie et al 2018) . In this paper we describe 78 experiments in which we isolated and compared EEG responses to both reward and sensory error 79 feedback using separate adaptation paradigms that produced comparable changes in behavior.…”

A solution to the learning dilemma for recurrent networks of spiking neurons

“…Interestingly some of these signals are of a predictive nature, e.g. they predict upcoming rewards in the case of dopamine or movement errors in the case of the error-related negativity (ERN), see MacLean et al (2015). Furthermore both dopamine signals (Engelhard et al, 2019;Roeper, 2013) and ERN-related neural firing (Sajad et al, 2019) are reported to be specific for a target population of neurons, rather than global.…”

Older adults display diminished error processing and response in a continuous tracking task

“…Thus, for simplicity's sake we have chosen to use the error-related negativity label from our original work. See MacLean et al (2015) and our original work, Krigolson and Holroyd (2006), for more detail. 450 [20.20, 20.64], p 5 .001 (see Figure 3).…”