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Updated: Jul 10, 2026

Electroencephalography Measurements in Awake Marmosets Listening to Conspecific Vocalizations
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Multiday electrophysiological recordings from freely behaving primates.

Vikash Gilja1, Michael D Linderman, Gopal Santhanam

  • 1Department of Computer Science, Stanford University, California, USA. gilja@stanford.edu

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
|October 20, 2007
PubMed
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Continuous neural recordings reveal distinct brain activity patterns during physical activity. Researchers identified specific changes in local field potential power and firing rates, enabling accurate classification of active versus inactive periods.

Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Signal Processing

Background:

  • Continuous neural recordings offer insights into brain function over extended durations.
  • Understanding neural correlates of behavior is crucial for advancing neuroscience and brain-computer interfaces.

Purpose of the Study:

  • To analyze continuous neural data to identify neural correlates of physical activity.
  • To develop methods for classifying active versus inactive periods using neural signals.

Main Methods:

  • Acquisition of continuous multiday broadband neural data.
  • Analysis of local field potential (LFP) power, firing rate variability, and temporal correlation.
  • Utilizing head-mounted accelerometer data to define physical activity states.
  • Classification of active/inactive periods based on LFP power thresholds.

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Last Updated: Jul 10, 2026

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Electroencephalography Measurements in Awake Marmosets Listening to Conspecific Vocalizations

Published on: July 26, 2024

Electrophysiology of Laminar Cortical Activity in the Common Marmoset
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Electrophysiology of Laminar Cortical Activity in the Common Marmoset

Published on: August 4, 2023

The TD Drive: A Parametric, Open-Source Implant for Multi-Area Electrophysiological Recordings in Behaving and Sleeping Rats
08:51

The TD Drive: A Parametric, Open-Source Implant for Multi-Area Electrophysiological Recordings in Behaving and Sleeping Rats

Published on: April 26, 2024

Main Results:

  • Significant reduction in 5-25 Hz LFP power during active periods.
  • Increased firing rate variability and temporal correlation in neural activity during activity.
  • Achieved 93% accuracy in classifying 5-minute blocks as active or inactive using LFP power.

Conclusions:

  • Continuous neural data can reliably differentiate between active and inactive behavioral states.
  • Identified neural signatures associated with physical activity.
  • These findings support the use of such data for testing neural prosthetics and studying natural behaviors.