Titile：Statistical Learning of Distractor Suppression Downregulates Prestimulus Neural Excitability in Early Visual Cortex

Speaker：Dr. Oscar Ferrante, University of Birmingham

Time： 2023-9-22, 10:00am.

Venue：Room1115 Wankezhen Building

Host：Huan Luo

Abstract:

Visual attention is significantly influenced by prior experiences. Recent behavioral studies have revealed that implicit learning of spatial distractor expectations within a search array results in reduced interference from anticipated distractors. However, the neural mechanisms underlying this form of statistical learning remain poorly understood. In this study, magnetoencephalography (MEG) was employed to examine human brain activity and investigate whether pre-stimulus mechanisms of attention play a role in the statistical learning of distractor locations. Specifically, a novel technique called rapid invisible frequency tagging (RIFT) was utilized to assess neural excitability in the early visual cortex during the process of statistical learning for distractor suppression, while concurrently exploring the modulation of posterior alpha band activity. The findings suggest that proactive attention mechanisms are indeed implicated in predictive distractor suppression, and these mechanisms are associated with altered neural excitability in the early visual cortex but not alpha band activity.

Bio:

Oscar Ferrante holds a Master's degree in Cognitive Psychology from D'Annunzio University in Chieti–Pescara, Italy. In 2017, he successfully completed his Ph.D. in Neuroscience, Psychological, and Psychiatric Sciences at the University of Verona, Italy. His doctoral research focused on investigating the influence of past experiences with task-relevant and interfering items on visual attention. Currently, he is employed at the Centre for Human Brain Health, University of Birmingham, United Kingdom. In this role, he utilizes magnetoencephalography (MEG) to conduct research on visual attention and brain oscillations within the laboratory of Professor Ole Jensen. Oscar is also a significant contributor to the FLUX pipeline, a standardized MEG data analysis tool. Additionally, he is an active member of the Cogitate adversarial collaboration, where his responsibilities include the collection and analysis of MEG-EEG data. Oscar's primary research interests lie in the field of visual attention, with a specific focus on enhancing target identification and distractor rejection through statistical learning techniques, and consciousness.