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By Tatjana Tchumatchenko explores dynamical response functions in neuroscience, emphasizing the role of linear response functions in understanding neural activity.
Delves into simulating network dynamics in in silico neuroscience, covering spontaneous and evoked activity, in-vitro and in-vivo simulations, and sensitivity analysis.
Explores decoding techniques for neural signals using invasive interfaces, regenerative electrodes, and intraneural electrodes to improve prosthesis control and reduce neuroma pain.
Explores machine learning models for neuroscience, focusing on understanding brain function and core object recognition through convolutional neural networks.
