Ryan Thomas Philips
Areas of Interest & Expertise
- Fear and Anxiety
- Mood Disorders
- Mental Health
- Emotions & Motivations
- Neuroimaging: fMRI, EEG
- Neuron-Astrocyte-Vessel coupling
- Neural Networks
- Reinforcement Learning
- Self-organizing maps
- Machine Learning
Biography
Ryan is a computational neuroscientist by training, working at the intersection of models, algorithms, neuroscience, affect and psychiatry. His broad research goal is to design theoretical model-inspired experiments that probe brain function, particularly in mood and anxiety disorders.
He builds computational models and tools to study brain function and behaviour, and then uses these insights to design better experiments and treatments, thus completing the loop. His two major interrelated research directions are to build a robust computation-driven understanding of decision-making and metacognition in anxiety, specifically by isolating the influence of independent parameters; and to investigate brain networks involved in fear and anxiety and their connectivity, specifically the Bed Nucleus of the Stria Terminals (BNST) and the Central Extended Amygdala (CEA) and associated circuits.
Ryan completed his doctoral studies at the Indian Institute of Technology Madras (IITM), with V Srinivasa Chakravarthy as his thesis guide. His most recent postdoctoral training was at the Section on Neurobiology of Fear and Anxiety, at the National Institute of Mental Health (NIMH/NIH) with Christian Grillon and Monique Ernst as his mentors.
His current projects include exploration-exploitation under anxiety, functional connectivity of BNST & CEA using resting state 7T fMRI, the role of mental fatigue in threat biases, investigating valence and uncertainty circuits using task-based fMRI.
Courses
Introduction to Psychology
A foundational course in Psychology
Publications
Journal Articles
- Gorka, A.X., Philips, R.T., Torrisi, S., Manbeck, A., Goodwin, M., Ernst, M., & Grillon, C. (2023). Periaqueductal gray matter and medial prefrontal cortex reflect negative prediction errors during differential conditioning. Social Cognitive and Affective Neuroscience, 18(1). 10.1093/scan/nsad025
- Gorka, A. X., Philips, R.T., Torrisi, S., Claudino, L., Foray, K., Ernst, M., & Grillon, C. (2022). The posterior cingulate cortex reflects the impact of anxiety on drift rates during cognitive processing. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 8(4), 445 – 451. https:// doi.org/10.1016/j.bpsc.2022.03.010
- Philips, R.T., Torrisi, S., Gorka, A.X., Grillon, C.,& Ernst, M. (2022). Dynamic time warping identifies functionally distinct fMRI resting state cortical networks specific to VTA and SNc: a proof of concept. Cerebral Cortex, 32(6), 1142 – 1151. https://doi.org/10.1093/cercor…
- Ernst, M., Gowin, J.L., Gaillard, C., Philips, R.T., & Grillon, C. (2019). Sketching the power of machine learning to decrypt a neural systems model of behavior. Brain Sciences, 9 (3).https://doi.org/10.3390/brains…
- Philips, R.T., Sur, M., & Chakravarthy, V. S. (2017). The influence of astrocytes on the width of orientation hypercolumns in visual cortex: A computational perspective. PLoS Computational Biology, 13(10). https://doi.org/10.1371/journa…
- Philips, R.T., & Chakravarthy, V. S. (2017). A global orientation map in the primary visual cortex (V1): Could a self organizing model reveal its hidden bias? Frontiers in Neural Circuits, 10. https://doi.org/10.3389/fncir.…
- Philips, R.T., Chhabria, K., & Chakravarthy, V. S. (2016). Vascular dynamics aid a coupled neurovascular network learn sparse independent features: A computational model. Frontiers in Neural Circuits, 10. https://doi.org/10.3389/fncir.…
- Philips, R.T., & Chakravarthy, V. S. (2015). The mapping of eccentricity and meridional angle onto orthogonal axes in the primary visual cortex: An activity-dependent developmental model. Frontiers in Computational Neuroscience, 9. https://doi.org/10.3389/fncom.…