ePoster · Computational Neuroscience
Critical organisation for complex temporal tasks in neural networks
Gayathri Ramesan, Akhilesh Nandan, Daniel Koch, Aneta Koseska · Bernstein Conference 2024
Current theoretical frameworks in neuroscience focus on attractor-based formalism, where the neural dynamics asymptotically converge to one of the system’s stable states, and these states are subsequently associated with the behavioral states of the system [1,2]. Although this framework explains a wide range of phenomena, it cannot explicitly account for transiently stable sequential neuronal activity dynamics, generated for example in olfactory encoding [3]. Recently, we have proposed a complementary theoretical framework that does not rely on (un)stable attractors, but rather on transiently