Optical imaging of electrically evoked visual signals in cats: II. ICA "harmonic filtering" noise reduction.

Spencer C. Chen, Yan T. Wong, Luke E. Hallum, Norbert B. Dommel, Shaun L. Cloherty, John W. Morley, Gregg J. Suaning, Nigel H. Lovell

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

6 Citations (Scopus)


Optical imaging of intrinsic signals (OIS) is a tool for visualizing differential areas in the primary visual cortex devoted to visual functions such as ocular dominance and spatial orientation preferences. The OIS methodology was employed to verify visual cortical response to a retinal vision prosthesis whereby electrical stimulation is applied to the neural retina in order to elicit visual percepts. However, OIS recording is quite susceptible to cardiac and respiratory artifact, and inherent noise related to the measurement process. This complicates the identification of evoked signals using standard ensemble averaging based image processing. We therefore developed an independent component analysis (ICA) "harmonic filtering" technique to improve the signal-to-noise ratio. This technique is capable of reducing noise components, highlighting response signals to visual and electrical stimuli. Particularly, we demonstrated extraction of an ocular dominance map due to corneal stimulation and localized cortical activation due to intravitreal stimulation.

Original languageEnglish
Title of host publicationAnnual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2007
Number of pages4
Publication statusPublished - 2007
Externally publishedYes
EventInternational Conference of the IEEE Engineering in Medicine and Biology Society 2007 - Centre de Congres, Lyon, France
Duration: 22 Aug 200726 Aug 2007
Conference number: 29th


ConferenceInternational Conference of the IEEE Engineering in Medicine and Biology Society 2007
Abbreviated titleEMBC 2007
Otherin conjunction with the Biennial Conference of the French society of Biological and Medical Engineering (SFGBM)

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