An open problem in the cognitive dimensions of navigation concerns how previous exploratory experience is reorganized in order to allow the creation of novel efficient navigation trajectories. This behavior is revealed in the "traveling salesrat prob...
Neural networks : the official journal of the International Neural Network Society
Feb 6, 2020
Recent findings suggest that acetylcholine mediates uncertainty-seeking behaviors through its projection to dopamine neurons - another neuromodulatory system known for its major role in reinforcement learning and decision-making. In this paper, we pr...
Biological psychiatry. Cognitive neuroscience and neuroimaging
Oct 22, 2019
BACKGROUND: Theoretical models have emphasized systems-level abnormalities in major depressive disorder (MDD). For unbiased yet rigorous evaluations of pathophysiological mechanisms underlying MDD, it is critically important to develop data-driven ap...
Neural networks : the official journal of the International Neural Network Society
Jun 4, 2019
We seek to (i) characterize the learning architectures exploited in biological neural networks for training on very few samples, and (ii) port these algorithmic structures to a machine learning context. The moth olfactory network is among the simples...
Reservoir computing is a biologically inspired class of learning algorithms in which the intrinsic dynamics of a recurrent neural network are mined to produce target time series. Most existing reservoir computing algorithms rely on fully supervised l...
Mental effort is an elementary notion in our folk psychology and a familiar fixture in everyday introspective experience. However, as an object of scientific study, mental effort has remained rather elusive. Cognitive psychology has provided some too...
The Journal of neuroscience : the official journal of the Society for Neuroscience
Jul 13, 2018
Animals successfully thrive in noisy environments with finite resources. The necessity to function with resource constraints has led evolution to design animal brains (and bodies) to be optimal in their use of computational power while being adaptabl...
Cyborg insects have attracted great attention as the flight performance they have is incomparable by micro aerial vehicles and play a critical role in supporting extensive applications. Approaches to construct cyborg insects consist of two major issu...
Synaptic connections between neurons in the brain are dynamic because of continuously ongoing spine dynamics, axonal sprouting, and other processes. In fact, it was recently shown that the spontaneous synapse-autonomous component of spine dynamics is...
Computational intelligence and neuroscience
Aug 14, 2017
We use both reinforcement learning and deep learning to simultaneously extract entities and relations from unstructured texts. For reinforcement learning, we model the task as a two-step decision process. Deep learning is used to automatically captur...