Josh obtained his Doctoral degree in Psychology at the University of Illinois at Urbana-Champaign, USA. In his graduate research, he investigated how aging brain biology and culture-related life experiences are associated with object, scene, and object-scene binding neural activity during perceptual processing in young and older Westerners and East Asians. He then further did his postdoctoral fellowship with the Laboratory of Behavioral Neuroscience in the National Institute on Aging, Intramural Research Program, USA. There, he continued his work on age-related effects on the brain and mind with the Baltimore Longitudinal Study of Aging (BLSA), investigating individual differences in age-related changes in executive processing and the corresponding structural and functional neural correlates, as well as initiating studies on value-based decision-making in older adults.

Josh is now the Principal Investigator of the Brain and Mind Laboratory at the Graduate Institute of Brain and Mind Sciences, National Taiwan University. He continues to work on a better understanding of intelligent systems like the human brain and mind, and how they are affected by biological and experiential factors. Specifically, his interests include the cognitive neuroscience of aging, individual differences and cross-cultural neuroscience, information theory, and decision-making.

Our lab is located at the Graduate Institute of Brain and Mind Sciences (GIBMS), College of Medicine, National Taiwan University (NTU), Taiwan. Our personnel include postdocs, PhD and MA graduate students, research assistants (RAs), and undergraduate interns. We primarily work with brain imaging data collected at the Taiwan Mind and Brain Imaging Center (TMBIC), National Cheng-Chi University (NCCU), the National Taiwan University Hospital (NTUH) research MRI facility, the Imaging Center for Integrated Body, Mind, and Culture Research (ICIBMC) at NTU, the Mind Research and Imaging Center (MRIC) at National Cheng Kung University (NCKU), as well as imaging data from collaborators. In addition, we also work with human behavioral testing and neuropsychological assessments, electroencephalograph (EEG) data, and also collect blood samples. We implement various experimental psychological designs and apply data analysis methods that include statistical and computational modeling as well as machine learning.

Our lab conducts many studies with different approaches that are jointly geared to understand how intelligent systems encode and retrieve environmental information. At present, we use the human brain as well as artificial neural networks that implement neural-based cognitive operations as our key models of intelligent systems. Our current pet theory is to consider intelligent systems as Bayesian inference machines. In this light, we view the brain as a physical system that dynamically interacts with the environment in which it is embedded, so that it modulates its structure and function in some definable association with environmental variations in information.

We have three project aims. 1) To develop models of how the brain-environment cycle operates. 2) To obtain empirical proof-of-concept evidence in support of the above theory. 3) To evaluate factors that modulate how a primary neurocognitive mechanism works such as in individual differences in neural processing and cognition.

The bulk of these studies focuses on normative human young and older adult data, with some inclusion of clinical human data where relevant. In addition to deepening our understanding of neural mechanisms, where practical, we also develop applications and interventions that address related human neurocognitive issues.