Cikkek nyilvánosan hozzáférhető megbízással - Murray ShanahanTovábbi információ
Valahol hozzáférhető: 19
The entropic brain: a theory of conscious states informed by neuroimaging research with psychedelic drugs
RL Carhart-Harris, R Leech, PJ Hellyer, M Shanahan, A Feilding, ...
Frontiers in human neuroscience 8, 55875, 2014
Megbízások: UK Medical Research Council
Large-Scale Network Organisation in the Avian Forebrain: A Connectivity Matrix and Theoretical Analysis
M Shanahan, VP Bingman, T Shimizu, M Wild, O Güntürkün
Frontiers in Computational Neuroscience 7, 89, 2013
Megbízások: German Research Foundation
The control of global brain dynamics: opposing actions of frontoparietal control and default mode networks on attention
PJ Hellyer, M Shanahan, G Scott, RJS Wise, DJ Sharp, R Leech
Journal of Neuroscience 34 (2), 451-461, 2014
Megbízások: UK Medical Research Council, UK Research & Innovation
Cognitive flexibility through metastable neural dynamics is disrupted by damage to the structural connectome
PJ Hellyer, G Scott, M Shanahan, DJ Sharp, R Leech
Journal of Neuroscience 35 (24), 9050-9063, 2015
Megbízások: UK Medical Research Council, National Institute for Health Research, UK …
NeMo: a platform for neural modelling of spiking neurons using GPUs
AK Fidjeland, EB Roesch, MP Shanahan, W Luk
2009 20th IEEE international conference on application-specific systems …, 2009
Megbízások: Swiss National Science Foundation
Effects of lesions on synchrony and metastability in cortical networks
F Váša, M Shanahan, PJ Hellyer, G Scott, J Cabral, R Leech
Neuroimage 118, 456-467, 2015
Megbízások: Bill & Melinda Gates Foundation, UK Medical Research Council, European …
Feature control as intrinsic motivation for hierarchical reinforcement learning
N Dilokthanakul, C Kaplanis, N Pawlowski, M Shanahan
IEEE transactions on neural networks and learning systems 30 (11), 3409-3418, 2019
Megbízások: UK Engineering and Physical Sciences Research Council
Learning to combine top-down and bottom-up signals in recurrent neural networks with attention over modules
S Mittal, A Lamb, A Goyal, V Voleti, M Shanahan, G Lajoie, M Mozer, ...
International Conference on Machine Learning, 6972-6986, 2020
Megbízások: Natural Sciences and Engineering Research Council of Canada
Rethink reporting of evaluation results in AI
R Burnell, W Schellaert, J Burden, TD Ullman, F Martinez-Plumed, ...
Science 380 (6641), 136-138, 2023
Megbízások: US Department of Defense
Integrated information as a common signature of dynamical and information-processing complexity
PAM Mediano, FE Rosas, JC Farah, M Shanahan, D Bor, AB Barrett
Chaos: An Interdisciplinary Journal of Nonlinear Science 32 (1), 2022
Megbízások: Wellcome Trust
The role of cortical oscillations in a spiking neural network model of the basal ganglia
Z Fountas, M Shanahan
PLoS One 12 (12), e0189109, 2017
Megbízások: UK Engineering and Physical Sciences Research Council
Metastability and inter-band frequency modulation in networks of oscillating spiking neuron populations
D Bhowmik, M Shanahan
PloS one 8 (4), e62234, 2013
Megbízások: UK Engineering and Physical Sciences Research Council
Direct human-AI comparison in the animal-AI environment
K Voudouris, M Crosby, B Beyret, J Hernández-Orallo, M Shanahan, ...
Frontiers in Psychology 13, 711821, 2022
Megbízások: US Department of Defense, UK Economic and Social Research Council
Phase offset between slow oscillatory cortical inputs influences competition in a model of the basal ganglia
Z Fountas, M Shanahan
2014 International Joint Conference on Neural Networks (IJCNN), 2407-2414, 2014
Megbízások: UK Engineering and Physical Sciences Research Council
Three tools for the real-time simulation of embodied spiking neural networks using GPUs
AK Fidjeland, D Gamez, MP Shanahan, E Lazdins
Neuroinformatics 11, 267-290, 2013
Megbízások: UK Engineering and Physical Sciences Research Council
GPU-based fast parameter optimization for phenomenological spiking neural models
Z Fountas, M Shanahan
2015 International Joint Conference on Neural Networks (IJCNN), 1-8, 2015
Megbízások: UK Engineering and Physical Sciences Research Council
A reservoir computing model of episodic memory
D Bhowmik, K Nikiforou, M Shanahan, M Maniadakis, P Trahanias
2016 international joint conference on neural networks (IJCNN), 5202-5209, 2016
Megbízások: UK Engineering and Physical Sciences Research Council
An investigation of the dynamical transitions in harmonically driven random networks of firing-rate neurons
K Nikiforou, PAM Mediano, M Shanahan
Cognitive Computation 9 (3), 351-363, 2017
Megbízások: UK Engineering and Physical Sciences Research Council
The Propensity for Density in Feed-forward Models
N Schoots, A Jackson, A Kholmovia, P McBurney, M Shanahan
ECAI 2024, 2830-2837, 2024
Megbízások: UK Research & Innovation
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