User profiles for C. Clopath
Prof. Claudia ClopathBioengineering, Imperial College London Verified email at imperial.ac.uk Cited by 14078 |
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 …
[HTML][HTML] Catalyzing next-generation artificial intelligence through neuroai
Neuroscience has long been an essential driver of progress in artificial intelligence (AI). We
propose that to accelerate progress in AI, we must invest in fundamental research in NeuroAI…
propose that to accelerate progress in AI, we must invest in fundamental research in NeuroAI…
[HTML][HTML] AI for social good: unlocking the opportunity for positive impact
Advances in machine learning (ML) and artificial intelligence (AI) present an opportunity to
build better tools and solutions to help address some of the world’s most pressing challenges, …
build better tools and solutions to help address some of the world’s most pressing challenges, …
Overcoming catastrophic forgetting in neural networks
…, D Hassabis, C Clopath… - Proceedings of the …, 2017 - National Acad Sciences
… When moving to a third task, task C, EWC will try to keep the network parameters close to
the learned parameters of both tasks A and B. This can be enforced either with two separate …
the learned parameters of both tasks A and B. This can be enforced either with two separate …
Inhibitory plasticity balances excitation and inhibition in sensory pathways and memory networks
… (C) Schematic of a step stimulus delivered with large and small step sizes (solid and dotted
black lines respectively); Sample PSTHs for nonpreferred (red) and preferred (blue) stimuli to …
black lines respectively); Sample PSTHs for nonpreferred (red) and preferred (blue) stimuli to …
Connectivity reflects coding: a model of voltage-based STDP with homeostasis
… (c) Step current injection made the postsynaptic neuron fire at 50 Hz in the absence of
presynaptic … (c,d) Data are presented as in a and b, but we used a standard STDP rule 12,14,19 . …
presynaptic … (c,d) Data are presented as in a and b, but we used a standard STDP rule 12,14,19 . …
The emergence of functional microcircuits in visual cortex
… Gaussian function parameterized by A (amplitude), c x and c y (centre of the Gaussian), and
σ x … ), the centre of the Gabor fit to the RF is at (c x , c y , d), and the angle of orientation of the …
σ x … ), the centre of the Gabor fit to the RF is at (c x , c y , d), and the angle of orientation of the …
[HTML][HTML] Firing patterns in the adaptive exponential integrate-and-fire model
For simulations of large spiking neuron networks, an accurate, simple and versatile single-neuron
modeling framework is required. Here we explore the versatility of a simple two-…
modeling framework is required. Here we explore the versatility of a simple two-…
A triplet spike-timing–dependent plasticity model generalizes the Bienenstock–Cooper–Munro rule to higher-order spatiotemporal correlations
J Gjorgjieva, C Clopath, J Audet… - Proceedings of the …, 2011 - National Acad Sciences
… (C) Same as B except for the 10 correlated inputs in each … triplet STDP were performed in B
and C. (D) The average weight … scenario as C, but for different correlation time constants τ c . …
and C. (D) The average weight … scenario as C, but for different correlation time constants τ c . …
[HTML][HTML] Supervised learning in spiking neural networks with FORCE training
… c This allows the network to represent a 5 Hz sinusoidal input (black). After learning, the
network (blue) still displays the 5 Hz sinusoidal oscillation as its macroscopic dynamics and the …
network (blue) still displays the 5 Hz sinusoidal oscillation as its macroscopic dynamics and the …