Decoding human spontaneous spiking activity in medial temporal lobe from scalp EEG

Hagar G Yamin; Guy Gurevitch; Tomer Gazit; Lavi Shpigelman; Itzhak Fried; Yuval Nir; Yoav Benjamini; Talma Hendler

doi:10.1016/j.isci.2023.106391

Decoding human spontaneous spiking activity in medial temporal lobe from scalp EEG

iScience. 2023 Mar 11;26(4):106391. doi: 10.1016/j.isci.2023.106391. eCollection 2023 Apr 21.

Authors

Hagar G Yamin¹, Guy Gurevitch^{1

2}, Tomer Gazit^{1

2}, Lavi Shpigelman³, Itzhak Fried^{2

4

5}, Yuval Nir^{2

6

7

8}, Yoav Benjamini^{6

9}, Talma Hendler^{1

2

6

10}

Affiliations

¹ Sagol Brain Institute, Wohl Institute for Advanced Imaging, Tel-Aviv Sourasky Medical Center, Tel-Aviv 6423906, Israel.
² Department of Physiology & Pharmacology, Sackler School of Medicine, Tel-Aviv University, Tel-Aviv 6997801, Israel.
³ IBM Research, Haifa 3498825, Israel.
⁴ Department of Psychiatry and Biobehavioral Sciences, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA 90024, USA.
⁵ Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA.
⁶ Sagol School of Neuroscience, Tel-Aviv University, Tel-Aviv 6997801, Israel.
⁷ Department of Biomedical Engineering, Faculty of Engineering, Tel Aviv University, Tel Aviv 6997801, Israel.
⁸ The Sieratzki-Sagol Center for Sleep Medicine, Tel Aviv Sourasky Medical Center, Tel Aviv 6423906, Israel.
⁹ Department of Statistics and Operations Research, Tel-Aviv University, Tel-Aviv 6997801, Israel.
¹⁰ School of Psychological Sciences, Faculty of Social Sciences, Tel-Aviv University, Tel-Aviv 6997801, Israel.

Abstract

Linking scalp electroencephalography (EEG) signals and spontaneous firing activity from deep nuclei in humans is not trivial. To examine this, we analyzed simultaneous recordings of scalp EEG and unit activity in deeply located sites recorded overnight from patients undergoing pre-surgical invasive monitoring. We focused on modeling the within-subject average unit activity of two medial temporal lobe areas: amygdala and hippocampus. Linear regression model correlates the units' average firing activity to spectral features extracted from the EEG during wakefulness or non-REM sleep. We show that changes in mean firing activity in both areas and states can be estimated from EEG (Pearson r > 0.2, p≪0.001). Region specificity was shown with respect to other areas. Both short- and long-term fluctuations in firing rates contributed to the model accuracy. This demonstrates that scalp EEG frequency modulations can predict changes in neuronal firing rates, opening a new horizon for non-invasive neurological and psychiatric interventions.

Keywords: Biological sciences; Clinical neuroscience; Neuroscience.