معرفی
Professor Marios Philiastides is a faculty member at the University of Glasgow's School of Psychology & Neuroscience, specializing in Decision Neuroscience. His work integrates EEG, fMRI, and computational models to study perceptual and value-based decisions, particularly focusing on neural mechanisms underlying reward learning and decision-making.
- Affiliations: School of Psychology & Neuroscience (University of Glasgow), Principal Investigator of the Decision Neuroscience Lab.
- Education: Not explicitly listed in the text; however, extensive publication history suggests advanced training in Neuroscience, Psychology, and related fields.
Research Interests:
His research explores the neural principles guiding human decision-making, including:
- Perceptual decision-making processes using EEG/MEG/fMRI
- Reward-based learning and prediction error signaling
- Computational modeling of neural evidence accumulation
- Clinical applications in psychiatry (e.g., depression treatment prediction)
- Multimodal neuroimaging fusion techniques (EEG-fMRI/TRIUX)
Research Trends in Articles:
Recent work emphasizes:
- Dynamic neural mechanisms in reward/punishment contexts
- Age-related changes in multisensory decision-making
- Inflammation's impact on reward processing
- Social vs. non-social decision neural commonalities
Scientific Awards & Grants
- Wellcome Trust (2025-2030): Investigating punishment's role in reward learning
- European Research Council (2020-2025): Multimodal neuroimaging fusion research
- Multiple grants from BBSRC, ESRC, and MRC for neural decision confidence studies
Advising & Collaborations
Supervised postgraduate students include Kitti Ban, Li Cheng, and Nicole Lai. Collaborators include experts in computational neuroscience (e.g., Tarryn Balsdon, Jessica Diaz) and clinical researchers (e.g., Rajeev Krishnadas).
Labs & Teams
Directs the Decision Neuroscience Lab, focusing on translational research bridging basic neuroscience and clinical applications.
Marios Philiastides در سایتهای دیگر
جستوجوهای مرتبط
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