Neural heterogeneity promotes robust learning
The brain is a hugely diverse, heterogeneous structure. Whether or not heterogeneity at the
neural level plays a functional role remains unclear, and has been relatively little explored in …
neural level plays a functional role remains unclear, and has been relatively little explored in …
Bottom-up and top-down approaches for the design of neuromorphic processing systems: tradeoffs and synergies between natural and artificial intelligence
While Moore's law has driven exponential computing power expectations, its nearing end
calls for new avenues for improving the overall system performance. One of these avenues …
calls for new avenues for improving the overall system performance. One of these avenues …
Brain-inspired methods for achieving robust computation in heterogeneous mixed-signal neuromorphic processing systems
D Zendrikov, S Solinas, G Indiveri - … Computing and Engineering, 2023 - iopscience.iop.org
Neuromorphic processing systems implementing spiking neural networks with mixed signal
analog/digital electronic circuits and/or memristive devices represent a promising …
analog/digital electronic circuits and/or memristive devices represent a promising …
Neural heterogeneity controls computations in spiking neural networks
The brain is composed of complex networks of interacting neurons that express
considerable heterogeneity in their physiology and spiking characteristics. How does this …
considerable heterogeneity in their physiology and spiking characteristics. How does this …
Bottom-up and top-down neural processing systems design: Neuromorphic intelligence as the convergence of natural and artificial intelligence
While Moore's law has driven exponential computing power expectations, its nearing end
calls for new avenues for improving the overall system performance. One of these avenues …
calls for new avenues for improving the overall system performance. One of these avenues …
Neural learning rules for generating flexible predictions and computing the successor representation
The predictive nature of the hippocampus is thought to be useful for memory-guided
cognitive behaviors. Inspired by the reinforcement learning literature, this notion has been …
cognitive behaviors. Inspired by the reinforcement learning literature, this notion has been …
Predictive coding is a consequence of energy efficiency in recurrent neural networks
Predictive coding is a promising framework for understanding brain function. It postulates
that the brain continuously inhibits predictable sensory input, ensuring preferential …
that the brain continuously inhibits predictable sensory input, ensuring preferential …
Heterogeneous recurrent spiking neural network for spatio-temporal classification
B Chakraborty, S Mukhopadhyay - Frontiers in Neuroscience, 2023 - frontiersin.org
Spiking Neural Networks are often touted as brain-inspired learning models for the third
wave of Artificial Intelligence. Although recent SNNs trained with supervised …
wave of Artificial Intelligence. Although recent SNNs trained with supervised …
Neuromorphic bioelectronic medicine for nervous system interfaces: from neural computational primitives to medical applications
E Donati, G Indiveri - Progress in Biomedical Engineering, 2023 - iopscience.iop.org
Bioelectronic medicine treats chronic diseases by sensing, processing, and modulating the
electronic signals produced in the nervous system of the human body, labeled'neural …
electronic signals produced in the nervous system of the human body, labeled'neural …
Intrinsic neural diversity quenches the dynamic volatility of neural networks
Heterogeneity is the norm in biology. The brain is no different: Neuronal cell types are
myriad, reflected through their cellular morphology, type, excitability, connectivity motifs, and …
myriad, reflected through their cellular morphology, type, excitability, connectivity motifs, and …