Biology subjects

Chanpornpakdi, I.

Publications and source records attributed to Chanpornpakdi, I..

3 recordsLinked to original sources

bioRxiv2023

Partial Face Visibility and Facial Cognition: An Electroencephalography and Eye-Tracking Investigation

Face masks became a part of everyday life in the SARS-CoV-2 pandemic. Previous studies showed that the face cognition mechanism involves holistic face processing, and the absence of face features could lower cognition ability. This is opposed to the experience during the pandemic, when people were able to correctly recognize faces, although the mask covered a part of the face. This paper shows a strong correlation in face cognition based on the EEG and eye-tracking data between the full and partial faces. We observed two event-related potentials, P3a in the frontal lobe and P3b in the parietal lobe, as subcomponents of P300. Both P3a and P3b were lowered when the eyes were invisible, and P3a evoked by the nose covered was larger than the full face. The eye-tracking data showed that 16 out of 18 participants focused on the eyes associated with the EEG results. Our results demonstrate that the eyes are the most crucial feature of facial cognition. Moreover, the face with the nose covered might enhance cognition ability due to the visual working memory capacity. Our experiment shows the possibility of people recognizing faces using both holistic face processing and structural face processing. Furthermore, people can recognize the masked face as well as the full face in similar cognition patterns due to the high correlation in the cognition mechanism.

neuroscience↗

bioRxiv2023

The Role of the Eyes: Investigating Face Cognition Mechanisms Using Machine Learning and Partial Face Stimuli

Face cognition plays a significant role in social interaction. The typical stimulus used to study face cognition mechanisms is a rapid serial visual presentation (RSVP). During the RSVP task, the brain response called event-related potential (ERP) is evoked when a person recognizes a target image. Many trials are required to average and obtain a clean ERP to interpret the cognitive mechanism behind the ERP response. However, increasing the trial number can cause fatigue and affect evoked ERP amplitude. This paper adopts a different perspective; machine learning might extract a meaningful cognitive result that reveals the face cognition mechanism without directly focusing on the characteristic of the ERP. We implemented an xDAWN covariance matrix method to enhance the data quality and a support vector machine classification model to predict the participants event of interest using ERP components evoked in the partial face cognition task. The effect of face components and the physical response was also investigated to explore the role of each component and find the possibility of reducing fatigue caused during the experiment. We found that the eyes were the most effective component. Similar statistical results were obtained from full face and partial face with eyes visible in both behavioral response and classification performance. From these results, the eye component could be the most crucial in face cognition. So, there could be some similarities in the face cognition mechanism of the full face and the partial face with eyes visible, which should be further investigated using ERP characteristics.

neuroscience↗

bioRxiv2023

Effect of predicting familiar melodies on alpha power

The processing of music and language share similar characteristics. Previous studies indicated that the similarity between language and melody was observed in event-related potentials to the deviation of a word and tone, respectively. We focused on a language study that demonstrated strong suppression of the alpha power in the presence of easily predictable words. Motivated by the physiological similarity between language and music, this study hypothesized that predictable music might suppress the alpha power. We measured electroencephalogram (EEG) signals while a melody followed by silence was presented for a participant who imagined the melody during the silent part of the music. The participants scored the melodys familiarity to quantify the ease of prediction and imagination. We observed similarity to language processing. For familiar melodies, alpha power suppression was observed in the left frontal and left central regions. Further, we observed Bereitschaftspotential (a negative slope) in both familiar and unfamiliar conditions before the silent interval. Moreover, a network analysis revealed that information flow from the right sensory-motor cortex to the right auditory cortex in the beta band was stronger for familiar music than for unfamiliar music. Considering the previous findings that motor preparation and execution suppress the alpha power in the left frontal and left central regions, the alpha band suppression under music prediction suggests a motor interaction during music processing in the prediction of melodies.

neuroscience↗