[HTML][HTML] Recent advances in physical reservoir computing: A review
Reservoir computing is a computational framework suited for temporal/sequential data
processing. It is derived from several recurrent neural network models, including echo state …
processing. It is derived from several recurrent neural network models, including echo state …
Recurrent neural networks as versatile tools of neuroscience research
O Barak - Current opinion in neurobiology, 2017 - Elsevier
Highlights•Recurrent neural networks (RNNs) are powerful models of neural systems.•RNNs
can be either designed or trained to perform a task.•In both cases, low dimensional …
can be either designed or trained to perform a task.•In both cases, low dimensional …
Prefrontal cortex as a meta-reinforcement learning system
Over the past 20 years, neuroscience research on reward-based learning has converged on
a canonical model, under which the neurotransmitter dopamine 'stamps in'associations …
a canonical model, under which the neurotransmitter dopamine 'stamps in'associations …
[HTML][HTML] Toward an integration of deep learning and neuroscience
AH Marblestone, G Wayne, KP Kording - Frontiers in computational …, 2016 - frontiersin.org
Neuroscience has focused on the detailed implementation of computation, studying neural
codes, dynamics and circuits. In machine learning, however, artificial neural networks tend …
codes, dynamics and circuits. In machine learning, however, artificial neural networks tend …
Thalamic regulation of switching between cortical representations enables cognitive flexibility
Interactions between the prefrontal cortex (PFC) and mediodorsal thalamus are critical for
cognitive flexibility, yet the underlying computations are unknown. To investigate …
cognitive flexibility, yet the underlying computations are unknown. To investigate …
Distributive dynamic spectrum access through deep reinforcement learning: A reservoir computing-based approach
Dynamic spectrum access (DSA) is regarded as an effective and efficient technology to
share radio spectrum among different networks. As a secondary user (SU), a DSA device …
share radio spectrum among different networks. As a secondary user (SU), a DSA device …
Stable and dynamic coding for working memory in primate prefrontal cortex
Working memory (WM) provides the stability necessary for high-level cognition. Influential
theories typically assume that WM depends on the persistence of stable neural …
theories typically assume that WM depends on the persistence of stable neural …
Supervised learning in spiking neural networks with FORCE training
Populations of neurons display an extraordinary diversity in the behaviors they affect and
display. Machine learning techniques have recently emerged that allow us to create …
display. Machine learning techniques have recently emerged that allow us to create …
Mixed selectivity morphs population codes in prefrontal cortex
A Parthasarathy, R Herikstad, JH Bong… - Nature …, 2017 - nature.com
The prefrontal cortex maintains working memory information in the presence of distracting
stimuli. It has long been thought that sustained activity in individual neurons or groups of …
stimuli. It has long been thought that sustained activity in individual neurons or groups of …
Physical reservoir computing with emerging electronics
Physical reservoir computing is a form of neuromorphic computing that harvests the dynamic
properties of materials for high-efficiency computing. A wide range of physical systems can …
properties of materials for high-efficiency computing. A wide range of physical systems can …