Electrophysiological correlates of impending multitasking performance

968 

Abstract Submission 

Jee Eun Park^1,2,3,4,5, Wan-Yu Hsu^4,5, Kevin Jones^4,5, Elizabeth Johnson⁶, Adam Gazzaley^4,5, Theodore Zanto^4,5

¹Department of Psychiatry, Seoul National University College of Medicine, Seoul, Korea, Republic of, ²Department of Psychiatry, Seoul National University Hospital, Seoul, Korea, Republic of, ³Medical Research Center, Institute of Human Behavioral Medicine, Seoul, Korea, Republic of, ⁴Department of Neurology, University of California, San Francisco, San Francisco, CA, USA, ⁵Neuroscape, University of California, San Francisco, San Francisco, CA, USA, ⁶Departments of Medical Social Sciences, Pediatrics, and Psychology, Northwestern University, Evanston, IL, USA

Jee Eun Park  
Department of Psychiatry, Seoul National University College of Medicine|Department of Psychiatry, Seoul National University Hospital|Medical Research Center, Institute of Human Behavioral Medicine|Department of Neurology, University of California, San Francisco|Neuroscape, University of California, San Francisco
Seoul, Korea, Republic of|Seoul, Korea, Republic of|Seoul, Korea, Republic of|San Francisco, CA, USA|San Francisco, CA, USA

Wan-Yu Hsu  
Department of Neurology, University of California, San Francisco|Neuroscape, University of California, San Francisco
San Francisco, CA, USA|San Francisco, CA, USA

Kevin Jones  
Department of Neurology, University of California, San Francisco|Neuroscape, University of California, San Francisco
San Francisco, CA, USA|San Francisco, CA, USA

Elizabeth Johnson  
Departments of Medical Social Sciences, Pediatrics, and Psychology, Northwestern University
Evanston, IL, USA

Adam Gazzaley  
Department of Neurology, University of California, San Francisco|Neuroscape, University of California, San Francisco
San Francisco, CA, USA|San Francisco, CA, USA

Theodore Zanto  
Department of Neurology, University of California, San Francisco|Neuroscape, University of California, San Francisco
San Francisco, CA, USA|San Francisco, CA, USA

This study investigated brain activity related to the preparatory state for multitasking. We aimed to uncover electroencephalography (EEG) predictors of impending multitasking performance as indexed by response times. EEG data were analyzed while participants engaged in visuomotor tracking, in anticipation of (prior to) multitasking (visuomotor tracking + target discrimination). Data was also analyzed to assess the effects of longitudinal theta-band (6 Hz) transcranial alternating current stimulation (tACS) on the potential for these EEG measures to predict performance.

EEGs from 133 healthy adults (young, n=80; old, n=53) were obtained from three studies conducted by the same research group (Anguera et al., 2013; Hsu et al., 2017; Hsu et. al., 2019; Zanto et. al., 2021; Jones et al., 2022). Among them, 98 people participated in clinical trials to examine the effects of theta tACS on cognitive performance. All participants performed a game-based multitasking paradigm, Neuroracer, which consisted of repeated multitasking (visuomotor tracking + target discrimination) with adaptive difficulty. Only the participants who performed the tasks at least 20 trials were included in this study (mean = 47.94). The mean-centered response time (mcRT) of each performance per individual was calculated as the time difference from the individual's mean response time. Theta and beta oscillations were mainly examined as possible correlates of the preparatory state for multitasking performance based on the results of these previous studies. For the first analysis, the response time (mcRT), age (young vs. old), and their interaction were included as fixed factors in a linear mixed model to predict one's theta and beta band power. For the second analysis, we added two more factors into the models, stimulation (tACS vs. control) and time (pre- vs. post-tACS), as well as their interactions. Post-hoc analyses focused on the mean difference in band power according to the binary response group: each response was categorized as fast or slow compared to the individual median response time.

Theta power showed a significant association with response times (frontal theta, F=20.642, p<0.001; posterior theta, F=19.750, p<0.001). Furthermore, this relationship was affected by age group (mcRT x age interaction on frontal theta, F=6.071, p=0.014; posterior theta, F=6.744, p=0.009). Post-hoc analyses demonstrated that theta power and response time were more strongly associated in younger adults. When the effect of tACS application was included in the analysis, tACS had an influence on beta power during the preparatory state in accordance with individual response time (stimulation x time x mcRT interaction on frontal beta, F=3.898, p=0.048; posterior beta, F=4.469, p=0.035). This association was also affected by age (stimulation x time x mcRT interaction on frontal beta, F=3.950, p=0.047; posterior beta, F=5.395, p=0.020): in older adults, the effect of tACS on beta power was more associated with faster responses.

We investigated the association of EEG spectral power with individual multitasking performance. Theta power was related to a highly attentive state in multitasking performance, especially in younger adults. After applying tACS, increased beta power was associated with improved response times, which was most prominent in older adults. Together, these results identify EEG measures associated with the preparatory state of multitasking. Moreover, results showed that tACS can affect the preparatory state of multitasking, which may occur in frequencies outside the applied stimulation frequency.

Non-invasive Electrical/tDCS/tACS/tRNS

Higher Cognitive Functions Other ¹

Aging

EEG/MEG Modeling and Analysis ²

Aging

Cognition

Electroencephaolography (EEG)

Other - Multitasking; Non-invasive brain stimulation