June 2022
Volume 63, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2022
Brain responsivity in visual cortex is linked to visual field deficits in acute stroke patients
Author Affiliations & Notes
  • Christian Grefkes
    Department of Neurology, University Hospital Cologne, Cologne, Germany
    Institute of Neuroscience and Medicine, Jülich Research Center, Juelich, Germany
  • Manuel M Hermann
    Department of Ophthalmology, University Hospital Cologne, Cologne, Germany
  • Caroline Tscherpel
    Department of Neurology, University Hospital Cologne, Cologne, Germany
  • Footnotes
    Commercial Relationships   Christian Grefkes None; Manuel Hermann None; Caroline Tscherpel None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2022, Vol.63, 2615 – F0498. doi:
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Christian Grefkes, Manuel M Hermann, Caroline Tscherpel; Brain responsivity in visual cortex is linked to visual field deficits in acute stroke patients. Invest. Ophthalmol. Vis. Sci. 2022;63(7):2615 – F0498.

      Download citation file:


      © ARVO (1962-2015); The Authors (2016-present)

      ×
  • Supplements
Abstract

Purpose : Neural reorganization following lesions of the central visual system and the mechanisms enabling recovery of visual function are still poorly understood. We here combined transcranial magnetic stimulation (TMS) and electroencephalography (EEG) to directly assess visual cortex function in stroke patients in order to non-invasively capture lesion-induced alterations in neural signal processing as well as their associations to visual field deficits.

Methods : We employed neuronavigated TMS-EEG over primary visual cortex (V1) of the lesioned and the intact hemisphere (120 single TMS pulses per hemisphere at 80% maximal stimulator output) in 10 patients with hemi- or quadrantanopia due to ischemic stroke in occipital cortex. TMS-evoked EEG potentials were recorded using a TMS-compatible 64-channel EEG system. Preprocessing and data analyses, i.e., global mean field power, time-frequency analysis, and phase locking value, were performed using in-house MATLAB scripts based on functions of the open-source toolbox EEGLAB.
Visual field deficits were quantified using an Octopus 900 perimeter and PeriData. Mean defects (MD) were computed for each visual hemifield averaged across both eyes to quantify the homonymic deficit, and subsequently correlated with TMS-EEG parameters.

Results : TMS-EEG revealed signal alterations in the time and time-frequency-domain of ipsilesional as well as contralesional V1 in the acute phase after stroke. This indicates not only changes of neuronal processing in the ischemic area but also in contralateral brain regions that are functionally connected, yet structurally intact. Interestingly, when analyzing the local spreading of induced activity, we found a shorter time course of significant coupling in the contralesional hemisphere (p=0.029), which was directly linked to visual field deficit (r=-0.771 p=0.036). Moreover, stronger alterations of the TMS-evoked oscillatory activity in both hemispheres were associated with more pronounced visual field deficits (ipsilesional: r=0.78, p=0.033; contralesional: r=0.829 p=0.021).

Conclusions : Brain responsivity parameters as assessed by TMS-EEG are linked to visual field deficits in stroke patients. Hence, TMS-EEG does not only present a novel tool to assess central visual system integrity, but may also help to uncover brain mechanisms driving functional compensation following lesions to the visual system.

This abstract was presented at the 2022 ARVO Annual Meeting, held in Denver, CO, May 1-4, 2022, and virtually.

 

TMS-evoked potential time series

TMS-evoked potential time series

×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×