A hidden Markov model reliably characterizes ketamine-induced spectral dynamics in macaque local field potentials and human electroencephalograms
Sourish Chakravarty, Indie C. Garwood, S. Chakravarty, Jacob Donoghue, Meredith Mahnke, Pegah Kahali, Shubham Chamadia, Oluwaseun Akeju, Earl K. Miller, Emery N Brown
PLoS Computational Biology August 18, 2021 DOI: 10.1371/journal.pcbi.1009280 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Observational study with statistical modeling Peer reviewed |
|---|---|
| Sample size | 11 |
| Population | Non-human primates and human subjects receiving anesthetic doses of ketamine |
| Intervention | Ketamine |
| Dose | anesthetic doses |
| Topics | Ketamine Esketamine |
| Keywords | Local field potential Hidden markov model Electroencephalography Beta programming language Beta rhythm Artificial intelligence Pattern recognition psychology Statistical physics |
| Citations | 32 |
| Key findings | Ketamine-induced neural dynamics consist of alternating gamma and slow-delta oscillations with characteristic durations and five sequentially transitioning sub-states. |
Abstract
Ketamine is an NMDA receptor antagonist commonly used to maintain general anesthesia. At anesthetic doses, ketamine causes high power gamma (25-50 Hz) oscillations alternating with slow-delta (0.1-4 Hz) oscillations. These dynamics are readily observed in local field potentials (LFPs) of non-human primates (NHPs) and electroencephalogram (EEG) recordings from human subjects. However, a detailed statistical analysis of these dynamics has not been reported. We characterize ketamine's neural dynamics using a hidden Markov model (HMM). The HMM observations are sequences of spectral power in seven canonical frequency bands between 0 to 50 Hz, where power is averaged within each band and scaled between 0 and 1. We model the observations as realizations of multivariate beta probability distributions that depend on a discrete-valued latent state process whose state transitions obey Markov dynamics. Using an expectation-maximization algorithm, we fit this beta-HMM to LFP recordings from 2 NHPs, and separately, to EEG recordings from 9 human subjects who received anesthetic doses of ketamine. Our beta-HMM framework provides a useful tool for experimental data analysis. Together, the estimated beta-HMM parameters and optimal state trajectory revealed an alternating pattern of states characterized primarily by gamma and slow-delta activities. The mean duration of the gamma activity was 2.2s([1.7,2.8]s) and 1.2s([0.9,1.5]s) for the two NHPs, and 2.5s([1.7,3.6]s) for the human subjects. The mean duration of the slow-delta activity was 1.6s([1.2,2.0]s) and 1.0s([0.8,1.2]s) for the two NHPs, and 1.8s([1.3,2.4]s) for the human subjects. Our characterizations of the alternating gamma slow-delta activities revealed five sub-states that show regular sequential transitions. These quantitative insights can inform the development of rhythm-generating neuronal circuit models that give mechanistic insights into this phenomenon and how ketamine produces altered states of arousal.
Comparable studies
Other preclinical and animal studies on ketamine, most cited first.
| Study | Year | Design | Participants |
|---|---|---|---|
| mTOR-Dependent Synapse Formation Underlies the Rapid Antidepressant Effects of NMDA Antagonists Rats | 2010 | Observational study | |
| Activation of Glutamatergic Neurotransmission by Ketamine: A Novel Step in the Pathway from NMDA Receptor Blockade to Dopaminergic and Cognitive Disruptions Associated with the Prefrontal Cortex Conscious rats | 1997 | Dose-response study with microdialysis and behavioral testing | |
| NMDAR inhibition-independent antidepressant actions of ketamine metabolites Mice | 2016 | Preclinical study | |
| The dissociative anaesthetics, ketamine and phencyclidine, selectively reduce excitation of central mammalian neurones by N‐methyl‐aspartate Spinal neurons in decerebrate or pentobarbitone-anaesthetized cats and rats | 1983 | Experimental study | |
| R-ketamine: a rapid-onset and sustained antidepressant without psychotomimetic side effects Mice | 2015 | Experimental study |
Citations in the library
Cited by 6
- Ketamine can produce oscillatory dynamics by engaging mechanisms dependent on the kinetics of NMDA receptors. Proceedings of the National Academy of Sciences May 28, 2024
- Dynamic reconfiguration of frequency-specific cortical coactivation patterns during psychedelic and anesthetized states induced by ketamine Neuroimage January 7, 2022
- Anesthetics as Treatments for Depression: Clinical Insights and Underlying Mechanisms. Annual Review of Neuroscience February 19, 2025
- Convergent effects of different anesthetics on changes in phase alignment of cortical oscillations. Cell Reports May 27, 2025
- Cortical high-frequency oscillations (≈ 110 Hz) in cats are state-dependent and enhanced by a subanesthetic dose of ketamine. Behavioural Brain Research January 5, 2025
and 1 more in the library
Cites 12
- A Randomized Trial of an N-methyl-D-aspartate Antagonist in Treatment-Resistant Major Depression Archives of General Psychiatry August 1, 2006
- Ketamine and Ketamine Metabolite Pharmacology: Insights into Therapeutic Mechanisms Pharmacological Reviews June 26, 2018
- Taming the Ketamine Tiger Anesthesiology August 6, 2010
- Reviewing the ketamine model for schizophrenia Journal of Psychopharmacology November 20, 2013
- Deep posteromedial cortical rhythm in dissociation Nature September 16, 2020
and 7 more in the library