By Meenakshi Khosla explores data-driven modeling in large-scale naturalistic neuroscience, focusing on brain activity representation and computational models.
By Tatjana Tchumatchenko explores dynamical response functions in neuroscience, emphasizing the role of linear response functions in understanding neural activity.
Covers the heterogeneous neuroscience data, techniques like microarrays and gene sequencing, data integration, and the importance of metadata in organizing and sharing data.
Delves into simulating network dynamics in in silico neuroscience, covering spontaneous and evoked activity, in-vitro and in-vivo simulations, and sensitivity analysis.
