Biology subjects

Corbett, E. A.

Publications and source records attributed to Corbett, E. A..

4 recordsLinked to original sources

bioRxiv2025

Optimizing Electrotactile Stimulation Parameters for Responses Under Cognitive Load

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSProsthetic users mainly rely on their vision for feedback during control of the device in absence of the tactile and proprioceptive modalities. Overreliance on vision increases cognitive load during prosthesis use, resulting in reduced control performance. Provision of additional feedback through other modalities could reduce this overreliance on vision and improve closed-loop prosthetic control. Fast and accurate recognition of feedback is particularly important when we consider that both delays and inaccuracies can destabilize closed-loop control environments. Transcutaneous electrotactile stimulation is a promising technology with advantages including non-invasiveness and simplicity. It is not yet clear, however, which parameters influence the speed and accuracy of response to electrotactile stimuli. In this study, we set out to investigate how we can influence response characteristics to an instantaneous change in stimulation intensity by manipulating both stimulus-related and environmental variables. Methods20 participants completed a randomized reaction time test to both visual and electrotactile stimulation. Participants were asked to respond to incoming stimuli with a button press on a controller as fast as possible, without discriminating between modality of stimulation. In a second experiment, 20 participants completed an intensity discrimination task for electrotactile stimulation. Participants had to prioritize either speed or accuracy during specific blocks, while cognitive load, magnitude of intensity shift and direction of shift were manipulated. ResultsThe results of the reaction time experiment confirmed lower average response times for electrotactile stimuli compared to visual stimuli by a median of ~50ms (p=0.008). In the intensity discrimination experiment, increased shift intensities led to increased response accuracies and decreased response times (p<0.001 in both cases). The presence of cognitive load increased average response times (p=0.005), but did not affect response accuracies (p=0.420). ConclusionsThe results of the intensity discrimination experiment imply that the magnitude of intensity shift needs to be provided via steps multiple times larger than the just noticeable difference to ensure fast and accurate responses to electrotactile stimulation. Moreover, results from the reaction time experiment confirmed faster average response times for electrotactile stimuli over visual stimuli. We argue that providing electrotactile stimulation using bigger steps in perceived intensity could result in the supplementary feedback making closed-loop control of prosthetic devices more reliable.

neuroscience↗

bioRxiv2024

Regressing Away Common Neural Choice Signals does not make them Artifacts. Comment on Frömer et al (2024, Nature Human Behaviour)

Fromer et al (2024, Nature Human Behaviour) apply a deconvolution method to correct for component overlap in the event-related potential. They report that this method eliminates signatures of sensory evidence accumulation from response-aligned measurements of the centro-parietal positivity (CPP), suggesting that these signatures arise artifactually.. Here, we argue that the analysis and interpretation of their perceptual choice data are critically flawed. We demonstrate with simulations that the deconvolution analyses used by the authors are not designed to reliably test for the presence or absence of bounded accumulation signals.

neuroscience↗

bioRxiv2021

Multiphasic value biases in fast-paced decisions

Perceptual decisions are biased toward higher-value options when overall gains can be improved. When stimuli demand immediate reactions, the neurophysiological decision process dynamically evolves through distinct phases of growing anticipation, detection and discrimination, but how value biases are exerted through these phases remains unknown. Here, by parsing motor preparation dynamics in human electrophysiology, we uncovered a multiphasic pattern of countervailing biases operating in speeded decisions. Anticipatory preparation of higher-value actions began earlier, conferring a "starting point"-advantage at stimulus onset, but the delayed preparation of lower-value actions was steeper, conferring a value-opposed buildup rate bias. This, in turn, was countered by a transient deflection toward the higher value action evoked by stimulus detection. A neurally-constrained process model featuring anticipatory urgency, biased detection, and accumulation of growing stimulus-discriminating evidence, successfully captured both behavior and motor preparation dynamics. Thus, an intricate interplay of distinct biasing mechanisms serves to prioritise time-constrained perceptual decisions.

neuroscience↗

bioRxiv2019

Multifaceted adaptation of the neural decision process with prior knowledge of time constraints and stimulus probability

When selecting actions in response to noisy sensory stimuli, the brain can exploit prior knowledge of time constraints, stimulus discriminability and stimulus probability to hone the decision process. Although behavioral models typically explain such effects through adjustments to decision criteria only, the full range of underlying neural process adjustments remains to be established. Here, we draw on human neurophysiological signals reflecting decision formation to construct and constrain a multi-tiered model of prior-informed motion discrimination, in which a motor-independent representation of cumulative evidence feeds build-to-threshold motor signals that receive additional dynamic urgency and bias signal components. The neurally-informed model not only provides a superior quantitative fit to prior-biased behavior across three distinct task regimes (easy, time-pressured and weak evidence), but also reveals adjustments to evidence accumulation rate, urgency rate, and the timing of accumulation onset and motor execution which go undetected or are discrepant in more standard diffusion-model analysis of behavior.

neuroscience↗