The Neural Reckoning Group is led by Dan Goodman. It is part of the Intelligent Systems and Networks group in the Department of Electrical and Electronic Engineering at Imperial College London. Follow us on Twitter @neuralreckoning.
We aim to understand the brain, and intelligent behaviour more widely, via theoretical and computational models.
We are particularly interested in sensory processing, primarily the auditory system, where our goal is to understand how we make sense of complex, natural environments.
One of the most striking operating principles of the brain is the use of highly connected, parallel networks of neurons communicating via precisely timed, discrete neural impulses (called "spikes"). This spike-based form of computation is specific to the brain, being radically different to conventional digital and analogue computation. We wish to uncover the principles underlying spike-based neuronal computation, both as a fundamental research problem and with an eye to wider applications in intelligent systems.
Underlying much of our work is neuroinformatics, or the application of computational methods in neuroscience. We are particularly interested in the simulation of spiking neural networks and the analysis of experimentally recorded spiking data (see Software).
We maintain a short list of resources for learning computational neuroscience that might be useful to students and people new to the field.
Weerts L, Rosen S, Clopath C, Goodman DFM
The Psychometrics of Automatic Speech Recognition.
Su Y, Chung Y, Goodman DFM, Hancock KE, Delgutte B (2021)
Rate and Temporal Coding of Regular and Irregular Pulse Trains in Auditory Midbrain of Normal‑Hearing and Cochlear‑Implanted Rabbits.
Journal of the Association for Research in Otolaryngology
Zenke F, et al. (2021)
Visualizing a joint future of neuroscience and neuromorphic engineering.
Achakulvisut T, et al. (2021)
Towards democratizing and automating online conferences: lessons from the Neuromatch conferences.
Trends in Cognitive Sciences
Stimberg M, Brette R, Goodman DFM (2019)
Brian 2, an intuitive and efficient neural simulator.
Rossant C, et al. (2016)
Spike sorting for large, dense electrode arrays.
Goodman DFM, Benichoux V, Brette R (2013)
Decoding neural responses to temporal cues for sound localization.