Spinal cord of Lamprey: generation of locomotor patterns
The handbook of brain theory and neural networks
Sharing the cost of multicast transmissions
Journal of Computer and System Sciences - Special issue on Internet algorithms
Localization of function via lesion analysis
Neural Computation
High-dimensional analysis of evolutionary autonomous agents
Artificial Life
ADUS: Indirect Generation of User Interfaces on Wireless Devices
DEXA '04 Proceedings of the Database and Expert Systems Applications, 15th International Workshop
Neurocontroller Analysis via Evolutionary Network Minimization
Artificial Life
Distinguishing Causal Interactions in Neural Populations
Neural Computation
Feature Selection via Coalitional Game Theory
Neural Computation
A Cooperative Game Theoretic Approach to Prototype Selection
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
Feature selection based on the Shapley value
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Evolving modular neural-networks through exaptation
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
An Efficient Explanation of Individual Classifications using Game Theory
The Journal of Machine Learning Research
An overview of recent applications of Game Theory to bioinformatics
Information Sciences: an International Journal
Searching for emergent representations in evolved dynamical systems
SAB'06 Proceedings of the 9th international conference on From Animals to Animats: simulation of Adaptive Behavior
Incremental evolution of target-following neuro-controllers for flapping-wing animats
SAB'06 Proceedings of the 9th international conference on From Animals to Animats: simulation of Adaptive Behavior
The evolution of imitation and mirror neurons in adaptive agents
Cognitive Systems Research
Adaptive attribute selection for configurator design via shapley value
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
| Hi-index | 0.00 |
This letter presents the multi-perturbation Shapley value analysis (MSA), an axiomatic, scalable, and rigorous method for deducing causal function localization from multiple perturbations data. The MSA, based on fundamental concepts from game theory, accurately quantifies the contributions of network elements and their interactions, overcoming several shortcomings of previous function localization approaches. Its successful operation is demonstrated in both the analysis of a neurophysiological model and of reversible deactivation data. The MSA has a wide range of potential applications, including the analysis of reversible deactivation experiments, neuronal laser ablations, and transcranial magnetic stimulation "virtual lesions," as well as in providing insight into the inner workings of computational models of neurophysiological systems.