Reading Group on Integrative Systems Approaches in Computational Cognitive Neuroscience
Reading group course (2024) focused on integrative systems approaches across cognitive neuroscience, network science, and computational modeling.
Understanding the timing of interactions between visual areas during context-based object recognition using TMS and behavior.
Modeling multitasking and cognitive-task structure in neural networks to probe candidate neural substrates of flexible behavior.
Characterizing distinct contributions of control-related brain networks in working memory using MEG.
Studying thalamic (pulvinar) orchestration of cognitive functions with a pulvino-cortical computational model.
Studying how information routing can emerge and reconfigure in complex nonlinear network dynamics.
Linking large-scale functional connectivity dynamics to learning with network-level fMRI analyses.
Identifying neural correlates of predictive factors in language comprehension by combining fMRI and computational linguistics.
Neural evidence supporting binding-by-synchrony accounts of memory via widespread cortical ripple coordination in humans (SEEG).
A computational hippocampal-formation model unifying spatial and relational learning through generalization.
Assessing synergy-dominated computation in human brain organization through integrative analyses spanning MRI, genetics, and molecular evidence.
Showing cerebellar contributions to motor planning via cortico-cerebellar-thalamic loops, beyond execution-only accounts.
Examining basal ganglia-frontal neurochemical interactions under nucleus accumbens DBS using in vivo microdialysis.