June 2023
Volume 64, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2023
Anesthetic disruption of visual evoked feedforward and feedback signaling in the mouse brain
Author Affiliations & Notes
  • Adeeti Aggarwal
    Neuroscience, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States
  • Jennifer Luo
    University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Diego Contreras
    Neuroscience, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States
  • Max Kelz
    Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Alex Proekt
    Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Footnotes
    Commercial Relationships   Adeeti Aggarwal None; Jennifer Luo None; Diego Contreras None; Max Kelz None; Alex Proekt None
  • Footnotes
    Support  F30 EY029931-01A1
Investigative Ophthalmology & Visual Science June 2023, Vol.64, 40. doi:
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    • Get Citation

      Adeeti Aggarwal, Jennifer Luo, Diego Contreras, Max Kelz, Alex Proekt; Anesthetic disruption of visual evoked feedforward and feedback signaling in the mouse brain. Invest. Ophthalmol. Vis. Sci. 2023;64(8):40.

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

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Abstract

Purpose : Feedforward and feedback signaling are critical for sensory information processing across the cortical hierarchy. In awake mice, simple visual stimuli evoke two traveling waves that span much of a cortical hemisphere: a fast (30-50Hz) feedforward wave and a slow (3-6 Hz) feedback wave. If these waves denote critical elements of visual processing, the delivery of hypnotic doses of anesthesia should impair their propagation patterns.

Methods : To explore how arousal state affects the spatiotemporal properties of visual evoked responses, we performed high density electrocorticography recordings (128 channels) in mice (n = 32) during wakefulness or under mechanistically distinct anesthetics.

Results : We demonstrate that simple visual stimuli evoke fast oscillations over the cortical surface in all mice, regardless of anesthetic state. However, attributes of fast feedforward waves including single trial reliability, signal to noise, and spatial activation pattern, are disrupted in drug specific manner. Conversely, visual stimuli fail to evoke large amplitude slow oscillations in animals under any of the anesthetics tested. Moreover, evoked slow waves observed in anesthetized animals resemble those elicited from weak stimuli in awake animals.

Conclusions : We find that while feedforward waves are affected by the anesthesia in a drug specific manner, feedback waves are abolished by all anesthetic agents tested. Thus, the ability to generate feedback waves might be a unifying signaling pathway necessary for visual perception.

This abstract was presented at the 2023 ARVO Annual Meeting, held in New Orleans, LA, April 23-27, 2023.

 

A. ECoG grid records local field potentials (LFP) from the cortical surface, and laminar probes placed in primary visual cortex (V1) and the Posterior Parietal Area (PPA); stimuli were 10ms LED flashes B. 5 s of LFP traces of spontaneous activity at the V1 electrode C. Single trials and average visual evoked potentials (VEPs) D. Intertrial phase coherence at the V1 electrode averaged over animals E. Average ITPC over the first 100ms of the VEP at V1 in mice with 95% confidence intervals around the mean. E. Average CSD

A. ECoG grid records local field potentials (LFP) from the cortical surface, and laminar probes placed in primary visual cortex (V1) and the Posterior Parietal Area (PPA); stimuli were 10ms LED flashes B. 5 s of LFP traces of spontaneous activity at the V1 electrode C. Single trials and average visual evoked potentials (VEPs) D. Intertrial phase coherence at the V1 electrode averaged over animals E. Average ITPC over the first 100ms of the VEP at V1 in mice with 95% confidence intervals around the mean. E. Average CSD

 

A. Probability of the SVD mode rank of the most visually responsive wave identified on each trial across animals for fast oscillations. B. Fraction of trials in which at least one visually responsive wave was found across mouse under each behavioral state for fast oscillations. C. Same as A for slow oscillations D. Same as B for slow oscillations

A. Probability of the SVD mode rank of the most visually responsive wave identified on each trial across animals for fast oscillations. B. Fraction of trials in which at least one visually responsive wave was found across mouse under each behavioral state for fast oscillations. C. Same as A for slow oscillations D. Same as B for slow oscillations

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