Evidence for an optimal algorithm underlying signal combination in human visual cortex

Research output: Contribution to journalArticlepeer-review


How does the cortex combine information from multiple sources? We tested several computational models against data from steady-state EEG experiments in humans, using periodic visual stimuli combined across either retinal location or eye-of-presentation. A model in which signals are raised to an exponent before being summed in both the numerator and the denominator of a gain control nonlinearity gave the best account of the data. This model also predicted the pattern of responses in a range of additional conditions accurately and with no free parameters, as well as predicting responses at harmonic and intermodulation frequencies between 1 and 30Hz. We speculate that this model implements the optimal algorithm for combining multiple noisy inputs, in which responses are proportional to the weighted sum of both inputs. This suggests a novel purpose for cortical gain control: implementing optimal signal combination via mutual inhibition, perhaps explaining its ubiquity as a neural computation.
Original languageEnglish
Pages (from-to)254-264
Number of pages11
JournalCerebral Cortex
Issue number1
Early online date28 Dec 2016
Publication statusPublished - 1 Jan 2017

Bibliographical note

© The Author 2016. Published by Oxford University Press.


  • gain control
  • signal combination
  • visual cortex
  • Kalman filter
  • Visual Perception/physiology
  • Humans
  • Information Storage and Retrieval/methods
  • Male
  • Models, Statistical
  • Evidence-Based Medicine
  • Neural Inhibition/physiology
  • Young Adult
  • Visual Cortex/physiology
  • Algorithms
  • Photic Stimulation/methods
  • Computer Simulation
  • Evoked Potentials, Visual/physiology
  • Brain Mapping
  • Adult
  • Female
  • Models, Neurological
  • Nerve Net/physiology
  • Synaptic Transmission/physiology

Cite this