23 citations · 26 across the 4 of their papers we have counts for
7 papers
Multi-Objective Optimisation of Cortical Spiking Neural Networks With Genetic Algorithms
James Fitzgerald, KongFatt Wong-Lin
Spiking neural networks (SNNs) communicate through the all-or-none spiking activity of neurons. However, fitting the large number of SNN model parameters to observed neural activit…
Predicting feature imputability in the absence of ground truth
Niamh McCombe, Xuemei Ding, Girijesh Prasad +4
Data imputation is the most popular method of dealing with missing values, but in most real life applications, large missing data can occur and it is difficult or impossible to eva…
Opportunities for multiscale computational modelling of serotonergic drug effects in Alzheimer's disease
Alok Joshi, Da-Hui Wang, Steven Watterson +4
Alzheimer's disease (AD) is an age-specific neurodegenerative disease that compromises cognitive functioning and impacts the quality of life of an individual. Pathologically, AD is…
Computational neurology: Computational modeling approaches in dementia
KongFatt Wong-Lin, Jose M. Sanchez-Bornot, Niamh McCombe +14
Dementia is a collection of symptoms associated with impaired cognition and impedes everyday normal functioning. Dementia, with Alzheimer's disease constituting its most common typ…
Genetic Algorithmic Parameter Optimisation of a Recurrent Spiking Neural Network Model
Ifeatu Ezenwe, Alok Joshi, KongFatt Wong-Lin
Neural networks are complex algorithms that loosely model the behaviour of the human brain. They play a significant role in computational neuroscience and artificial intelligence.…
Optimality and limitations of audio-visual integration for cognitive systems
W. Paul Boyce, Tony Lindsay, Arkady Zgonnikov +2
Multimodal integration is an important process in perceptual decision-making. In humans, this process has often been shown to be statistically optimal, or near optimal: sensory inf…