If deep learning is the answer, what is the question?
Neuroscience research is undergoing a minor revolution. Recent advances in machine
learning and artificial intelligence research have opened up new ways of thinking about …
learning and artificial intelligence research have opened up new ways of thinking about …
Deep neural networks in computational neuroscience
The goal of computational neuroscience is to find mechanistic explanations of how the
nervous system processes information to support cognitive function and behaviour. At the …
nervous system processes information to support cognitive function and behaviour. At the …
[HTML][HTML] Analyzing biological and artificial neural networks: challenges with opportunities for synergy?
Highlights•Artificial and biological neural networks can be analyzed using similar
methods.•Neural analysis has revealed similarities between the representations in artificial …
methods.•Neural analysis has revealed similarities between the representations in artificial …
Deep learning for cognitive neuroscience
KR Storrs, N Kriegeskorte - arXiv preprint arXiv:1903.01458, 2019 - arxiv.org
Neural network models can now recognise images, understand text, translate languages,
and play many human games at human or superhuman levels. These systems are highly …
and play many human games at human or superhuman levels. These systems are highly …
A deep learning framework for neuroscience
Abstract Systems neuroscience seeks explanations for how the brain implements a wide
variety of perceptual, cognitive and motor tasks. Conversely, artificial intelligence attempts to …
variety of perceptual, cognitive and motor tasks. Conversely, artificial intelligence attempts to …
Principles for models of neural information processing
KN Kay - NeuroImage, 2018 - Elsevier
The goal of cognitive neuroscience is to understand how mental operations are performed
by the brain. Given the complexity of the brain, this is a challenging endeavor that requires …
by the brain. Given the complexity of the brain, this is a challenging endeavor that requires …
Deep neural network models of sensory systems: windows onto the role of task constraints
AJE Kell, JH McDermott - Current opinion in neurobiology, 2019 - Elsevier
Highlights•Deep neural networks (DNNs) now reach human-level performance on some
perceptual tasks.•They show human-like error patterns and predict sensory cortical …
perceptual tasks.•They show human-like error patterns and predict sensory cortical …
[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 …
Deep neural networks as scientific models
Artificial deep neural networks (DNNs) initially inspired by the brain enable computers to
solve cognitive tasks at which humans excel. In the absence of explanations for such …
solve cognitive tasks at which humans excel. In the absence of explanations for such …
Artificial neural networks as models of neural information processing
M Van Gerven, S Bohte - Frontiers in computational neuroscience, 2017 - frontiersin.org
Conclusion Neural networks are experiencing a revival that not only transforms AI but also
provides new insights about neural computation in biological systems. The contributions in …
provides new insights about neural computation in biological systems. The contributions in …