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Published on: August 1, 2018
State dependence of noise correlations in macaque primary visual cortex
Alexander S Ecker1, Philipp Berens2, R James Cotton3
1Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA; Werner Reichardt Centre for Integrative Neuroscience and Institute of Theoretical Physics, University of Tübingen, Germany; Bernstein Center for Computational Neuroscience, Tübingen, Germany; Max Planck Institute for Biological Cybernetics, Tübingen, Germany.
Anesthesia significantly impacts neuronal population activity and noise correlations in the brain. Accounting for these anesthesia-induced fluctuations reconciles differing correlation estimates between awake and anesthetized states.
Area of Science:
- Neuroscience
- Computational Neuroscience
- Systems Neuroscience
Background:
- Shared variability in neuronal populations, known as noise correlations, influences brain information processing accuracy.
- Existing estimates of noise correlations vary widely (0.01–0.4), lacking consensus on contributing factors.
Purpose of the Study:
- To investigate the impact of anesthesia on population activity structure in the macaque primary visual cortex.
- To determine if anesthesia explains discrepancies in noise correlation estimates across studies.
Main Methods:
- Recorded neuronal population activity in the primary visual cortex of macaque monkeys.
- Compared neural activity patterns during opioid anesthesia versus awake, fixating states.
- Analyzed coordinated fluctuations and noise correlations under different brain states.
Main Results:
- Opioid anesthesia induced strong, low-frequency (1–2 Hz) coordinated fluctuations in neural activity.
- These global fluctuations were largely absent in awake monkeys.
- Accounting for these fluctuations under anesthesia reduced noise correlations to levels comparable to those in awake animals.
Conclusions:
- Anesthesia-induced internal signals can significantly alter population activity structure and induce noise correlations.
- The identified fluctuations provide a reconcilable factor for differing noise correlation estimates between studies.
- Noise correlations can be accurately estimated by accounting for global neural signals related to brain state.
