Touch-driven advantages in reaction time but not in performance in a cross-sensory comparison of reinforcement learning
Year: 2024
Type: article
Abstract: Recent research has highlighted a notable confidence bias in the haptic sense, yet its impact on learning relative to other senses remains unexplored. This online study investigated learning behaviour across visual, auditory, and haptic modalities using a probabilistic selection task on computers and mobile devices, employing dynamic and ecologically valid stimuli to enhance generalisability. We analysed reaction time as an indicator of confidence, alongside learning speed and task accuracy. Our results revealed the fastest reaction times with haptic stimuli, suggesting heightened perceptual confidence, whereas visual stimuli were the slowest, and auditory stimuli were intermediate. Despite these differences, all modalities demonstrated consistent learning speeds and accuracies. These findings support the 'common currency' hypothesis of perceptual confidence, facilitating modality-independent meta-representations for efficient decision-making. Additionally, reaction times were significantly faster on touch-based mobile devices compared to computers, underscoring the metacognitive efficiency of haptic feedback in technology-enhanced environments. The combination of faster reaction time in the haptic modality without sacrificing accuracy and the enhanced efficiency of touch-based interfaces advocates for the integration of haptics in technological designs to boost efficiency while maintaining a high level of precision.
Source: Heliyon
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,100
Awards: G1305463392, G1314256473, EXC 2050: Centre for Tactile Internet with HumanintheLoop (CeTI), G1407243695, G1933938177, Verbundprojekt: Digitale Transformation und Souveränität künftiger Kommunikationsnetze - 6G-life -, Teilvorhaben: Forschung für künftige 6G-Kommunikationsnetze mit dem Fokus Mensch-Maschine-Kollaboration, G4021765181, G5154814024, G5628759018, G6270499413, G7491412026, G7827343235
OpenAlex ID: W4405651027
