General anesthesia dissociates discrete components of ketamine neurophysiology

General anesthesia dissociates discrete components of ketamine neurophysiology | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search General anesthesia dissociates discrete components of ketamine neurophysiology Ben Deverett , Duan Li , Theresa Lii , Phillip E. Vlisides , Vijay Tarnal , Anna Forsyth , Rachael Sumner , View ORCID Profile Pilleriin Sikka , Alan F. Schatzberg , Suresh Muthukumaraswamy , George A. Mashour , View ORCID Profile Boris D. Heifets doi: https://doi.org/10.1101/2025.08.05.25333019 Ben Deverett 1 Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University , Stanford CA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Duan Li 2 Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School , Ann Arbor, Michigan Find this author on Google Scholar Find this author on PubMed Search for this author on this site Theresa Lii 1 Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University , Stanford CA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Phillip E. Vlisides 2 Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School , Ann Arbor, Michigan Find this author on Google Scholar Find this author on PubMed Search for this author on this site Vijay Tarnal 2 Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School , Ann Arbor, Michigan Find this author on Google Scholar Find this author on PubMed Search for this author on this site Anna Forsyth 4 School of Pharmacy, University of Auckland , New Zealand Find this author on Google Scholar Find this author on PubMed Search for this author on this site Rachael Sumner 4 School of Pharmacy, University of Auckland , New Zealand Find this author on Google Scholar Find this author on PubMed Search for this author on this site Pilleriin Sikka 1 Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University , Stanford CA 6 Department of Psychology, Stanford University , Stanford CA 7 Department of Cognitive Neuroscience and Philosophy, School of Bioscience, University of Skövde , Sweden 8 Department of Psychology, University of Turku , Turku, Finland Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Pilleriin Sikka Alan F. Schatzberg 5 Department of Psychiatry and Behavioral Sciences, Stanford University , Stanford CA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Suresh Muthukumaraswamy 4 School of Pharmacy, University of Auckland , New Zealand Find this author on Google Scholar Find this author on PubMed Search for this author on this site George A. Mashour 3 Center for Consciousness Science, Departments of Anesthesiology and Pharmacology, Neuroscience Graduate Program, University of Michigan Medical School , Ann Arbor, Michigan Find this author on Google Scholar Find this author on PubMed Search for this author on this site Boris D. Heifets 1 Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University , Stanford CA 4 School of Pharmacy, University of Auckland , New Zealand Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Boris D. Heifets For correspondence: bheifets{at}stanford.edu Abstract Full Text Info/History Metrics Data/Code Preview PDF Structured Abstract Importance Ketamine has well known dissociative, analgesic, and antidepressant properties, but it is unknown whether the neurophysiologic effects that are associated with these properties can be modulated separately from one another. Given prior studies that link specific cortical oscillations with specific therapeutic effects, it is likely that modulating selective aspects of ketamine neurophysiology can inform efforts to develop more targeted therapies. Objective To determine how the neurophysiologic signatures of ketamine are influenced by removal of conscious awareness using general anesthesia. Design Observational cohort study from trials spanning 2017 to 2023. Setting Multicenter study using data from two study cohorts (U-Michigan and Stanford) and supplementary analysis of a third cohort (U-Auckland). Participants 52 participants in primary analysis and 27 additional participants in supplementary analyses. Study cohorts included healthy volunteers, patients undergoing elective surgery, and patients with a diagnosis of depression. Intervention Participants received a subanesthetic infusion of ketamine (0.5 mg/kg) or placebo with or without general anesthesia (GA). Main Outcome and Measure Changes in electroencephalographic (EEG) band power during medication infusion. Results GA differentially alters EEG features commonly associated with ketamine. In comparison to awake administration, ketamine during GA preserves its high-frequency power modulation but lacks its characteristic low-frequency augmentation. Conclusions and Relevance Co-administration of ketamine with GA selectively modulates the high- and low-frequency neurophysiological correlates of ketamine, suggesting a method to explore these components’ role in ketamine’s behavioral effects. Introduction Ketamine is a widely used anesthetic, analgesic, and antidepressant 1 , 2 . Low doses produce connected consciousness with dissociative experiences and high doses produce a state of disconnected dissociative anesthesia. These subanesthetic and anesthetic states are characterized by elevations in βγ (high-frequency) and θ (low-frequency) power on electroencephalography (EEG) 3 – 9 . Ketamine’s antidepressant mechanisms have been attributed to high-frequency oscillations 10 while its dissociative properties have been linked to low-frequency oscillations 5 , 11 . However, there are no known methods to independently modulate these aspects of ketamine-induced neurophysiology in humans. Separating these mechanisms can inform efforts to develop ketamine-like antidepressant therapies without inducing dissociation. We hypothesized that removal of conscious awareness, and therefore removal of dissociative experience, could be used to study which features of ketamine neurophysiology are related to experience. We predicted that ketamine administered under general anesthesia (GA; induced by non-dissociative GABAergic agents) would exhibit different EEG features compared to ketamine administered awake. Preclinical studies suggest that anesthetics disrupt ketamine-evoked neurotransmission in frontal regions 12 and its associated γ oscillations 10 , 13 , 14 , and θ oscillations have been associated with subjective experiences of ketamine dissociation 11 . We therefore hypothesized that ketamine administered under GA would lack these high- and low-frequency oscillatory modulations. We compared EEG recorded from patients receiving ketamine under GA or receiving ketamine only. Methods We analyzed data from two studies utilizing a standardized ketamine infusion: 0.5 milligrams per kilogram body weight over 40 minutes. In Study 1 (U-Michigan) 4 , 15 , 15 healthy participants received ketamine in a laboratory session (“ketamine-only”). In Study 2 (Stanford) 16 , from which EEG data have not been published, 37 patients under steady-state GA for elective surgery were administered ketamine (n=18) or placebo (n=19) intraoperatively (“ketamine-GA” and “placebo-GA” respectively) while anesthetized using standard regimens ( Table S1 ). Data from an additional Study 3, (U-Auckland) 17 , 18 in which 27 participants with depression were administered ketamine, were used to assess the impact of depression on the EEG effects of ketamine. Study 1 data were collected using a 128-channel HydroCel Geodesic sensor, Study 2 data were collected intraoperatively using the SedLine frontal EEG monitor, and Study 3 data were collected using a 64-channel BrainCap MR. Data were preprocessed with downsampling, filtering, and artifact removal as described in the original studies and Supplementary Methods. To compare frontal EEG across datasets, channels corresponding to the SedLine electrode locations (Fp1=L1, Fp2=R1, F7=L2, F8=R2) were extracted and re-referenced to Fz, and all subsequent analyses were performed in an identical manner across datasets. We separately confirmed the consistency of EEG cap and SedLine data using simultaneous recordings from the same individual, which showed comparable spectral profiles ( Fig. S1 ). Spectrograms were computed using the multitaper method described in Supplementary Methods. For spectral analyses in Fig. 1 , spectral power was extracted individually for each participant in the bands θ (theta, 4-8 Hz), Lβ (low-beta, 15-22 Hz), and βγ (beta-gamma, 23-40 Hz) using the median power within the band. Fold-Δ power was computed as above on a per-subject basis then averaged across subjects for display. Decibel power values were displayed in the positive range using a constant additive offset applied uniformly to all datasets. Download figure Open in new tab Figure 1: EEG spectral profiles during ketamine/placebo infusions. (a-c) Left: spectral power time courses for placebo-GA (n=19), ketamine-only (n=15), and ketamine-GA (n=18), median across participants, normalized from 0 to 1. Middle: fold spectral power change relative to Start of infusion, normalized from -1 to 1. Fold Δ power is computed as (p-p0)/p0 where p0 is the baseline power in the first 3 minutes of infusion on a per-subject and per-frequency basis. Right: power spectral density at the Start and End of infusion, median across participants. Start and End times correspond to the median values within the 3 first minutes and final minutes of the infusion, respectively. (d-f) Time course of fold power change relative to Start of infusion, mean ± SEM over participants, in three frequency bands (left: βγ, middle: Lβ, right: θ). (g-i) Mean power at Start and End of infusion for all experimental conditions and frequency bands. Lines denote individual participants. * : p<0.05; ** : p<0.01; two-tailed Wilcoxon signed-rank test. Results Under GA-only, patients exhibited stereotypical anesthetized EEG profiles ( Figure 1a ) characterized by α (8-14 Hz) and Δ (0.5-4 Hz) oscillations. In contrast, the ketamine-only group exhibited typical signatures of subanesthetic ketamine: increases in βγ and θ power 3 , 4 ( Fig. 1b , middle; Fig. 1d,f ), rising within 10 minutes and remaining elevated throughout the infusion. Contrary to our hypothesis, the ketamine-GA group showed robust βγ enhancement ( Fig. 1c, 1d ). A moderate early enhancement of Lβ occurred in both ketamine-only and ketamine-GA but persisted in a significant manner by the end of infusion only in the ketamine-GA group ( Fig. 1e ). Finally, as predicted, in the ketamine-GA group we observed a total absence of the θ modulation seen with subanesthetic ketamine infusions ( Fig. 1f ). To quantify these effects, we compared absolute power values across the start and end of the infusion. The following spectral power changes were observed ( Fig. 1g-i ): in βγ, the placebo-GA group exhibited a decrease (9.6 ± 5.5 vs 8.5 ± 5.3 dB), while the ketamine-only and ketamine-GA groups exhibited increases (6.3 ± 11.3 vs 11.6 ± 2.2 dB and 8.5 ± 2.9 vs 11.2 ± 3.8 dB, respectively). In Lβ, placebo-GA exhibited a decrease (21.4 ± 6.4 vs 20.5 ± 6.5 dB), ketamine-only exhibited an upward but non-significant trend (10.9 ± 11.3 vs 14.0 ± 2.3 dB), and ketamine-GA exhibited an increase (20.1 ± 3.2 vs 22.6 ± 3.5 dB). Finally, in θ, placebo-GA showed no change (29.2 ± 6.3 vs 29.5 ± 6.7 dB), ketamine-only exhibited an increase (17.3 ± 10.5 vs 22.9 ± 3.1 dB), and ketamine-GA exhibited a small decrease (29.0 ± 3.0 vs 27.8 ± 3.5 dB). High-frequency modulation could be an artifact of ketamine-induced EMG activity even under anesthesia, however 27 of 37 anesthetized patients had received a neuromuscular blocking drug within an hour of ketamine infusion. To address whether the diagnosis of depression in Study 2 could account for these results, we compared data from Study 3 (U-Auckland) 18 in which patients with depression were administered a subanesthetic bolus of ketamine without GA. These EEG data recapitulated key features of our findings, demonstrating that subanesthetic ketamine causes a rise in βγ and θ power even in the presence of depression ( Fig. S2 ). Discussion We demonstrate that ketamine delivered during GA preserves the enhancement of frontal high-frequency but not low-frequency power, compared to ketamine delivered when awake. The absence of low-frequency modulation on a background of GA was predictable, as dissociative experiences associated with ketamine are presumably absent under GABA-mediated unconsciousness. Together these findings raise the possibility that the ketamine-GA EEG signature reflects the absence of subjective experience (absence of θ increase), alongside the maintenance of other biological effects (persistence of βγ increase). This interpretation is supported by several studies demonstrating that ketamine retains antidepressant efficacy when delivered during surgical anesthesia 16 , 19 – 21 , though we note an exception from a secondary analysis of patients receiving ketamine to prevent postoperative delirium 22 . We therefore propose that some, but not all, of ketamine’s biological activity is preserved under GA, and that the mechanisms underlying ketamine’s effects may be separable with targeted perturbations. Depression was present in the two GA groups but not in the ketamine-only group, however patients with depression exhibit clear θ and βγ modulation ( Fig. S2 ) demonstrating that depression cannot account for the present results. Surgery involving other concomitant medications was also occurring in the two GA groups but not in the ketamine-only group, but these factors do not explain the altered response to ketamine since previous findings in surgical settings where ketamine was delivered without GA demonstrated the same increases in low- and high-frequency power observed in the ketamine-only group of this study 3 . We therefore interpret the observed differences between the ketamine-only and ketamine-GA groups as resulting from the GABA-mediated unconsciousness rather than from differences in patient population. In summary, we demonstrate that the typical EEG signature of ketamine (elevated βγ and θ power) is selectively altered when ketamine is administered under general anesthesia, preserving high-frequency (βγ) modulations while lacking low-frequency (θ) augmentation. This result suggests that the neuronal mechanisms underlying ketamine’s effects can be selectively altered, which may give way to more precise characterization and usage of ketamine. Data Availability All data produced in the present study are available upon reasonable request to the authors Competing Interests Statement B.D.H. is on the scientific advisory boards of Osmind and Journey Clinical and is a consultant for Arcadia Medicine, Inc., Tactogen, LLC, and Vida Ventures, LLC. Dr. Schatzberg has served as a consultant to Alto Neuroscience, ANeurotech, Compass, Magnus, NeuraWell, Parexal, Sage and Signant. He holds equity in Alto Neuroscience, Corcept, Delpor, Madrigal, Magnus, Seattle Genetics, Titan and Xhale. SM has previously received research funding from atai Life Sciences and MindBio Therapeutics for research in psychedelic medicines. A.F. has previously consulted for atai Life Sciences and Mindbio Therapeutics for research in psychedelic medicines. R.S. has previously received research funding from MindBio Therapeutics for research in psychedelic medicines. These interests had no role in the referenced trials. The other authors declare no competing interests. Supplementary Materials Supplementary Methods Analyses were performed in Python 3.12.1 using numpy 1.26.4, scipy 1.11.4, and pandas 2.2.3. In the Stanford cohort, the SedLine device was a Masimo Root v2.1.2.4 with SedLine firmware 2343, and data were exported in EDF format at the conclusion of each surgery. EEG data were collected for 37 of the 40 subjects in the original study (the remaining three had no EEG data collected). Raw data for each patient consisted of four frontal EEG traces sampled at 178 Hz. For four datasets, signal sampling rate and amplitude were adjusted prior to analyses to account for variations in device data output. The two edge channels on the device output frequently exceeded the dynamic range of the measurement device and exhibited clipping, so we excluded these channels from analyses. For each patient, the remaining channels were averaged. Data were bandpass filtered between 0.1 and 50 Hz with a Butterworth filter of order three and notch filtered at 60 Hz. We applied a custom artifact rejection algorithm which excluded data points whose amplitude deviated significantly from the baseline distribution: for each subject we excluded any contiguous 1-second period during which greater than 10% of data points had amplitudes that differed by greater than 2.5 standard deviations from the mean of the entire dataset. Additionally, we excluded any contiguous 100-millisecond period during which greater than 5% of data points had amplitudes that differed by greater than 4 standard deviations from a 3-second rolling average of the dataset. This resulted in 4.2 ± 2% (mean ± s.d.) of samples rejected from further analyses. Data from the U-Michigan and U-Auckland studies were processed as described in the original publications using standard downsampling, filtering, and artifact rejection. To compute spectrograms, data from raw preprocessed time series were processed using the multitaper method 23 with a non-overlapping window size of 15 seconds, frequency resolution 1 Hz, time half bandwidth 7.5, and 14 tapers. Download figure Open in new tab Supplementary Figure 1: EEG data obtained from SedLine are comparable to those obtained from high-channel EEG cap. These data were captured during a separate experiment involving propofol infusions in healthy participants and are displayed as a general comparison of cap data and SedLine data. The left panel shows data obtained from a 32-channel BrainVision BrainCap. The right panel shows data obtained from the SedLine device. The two signals were simultaneously recorded and processed in the same manner as the present study. Download figure Open in new tab Supplementary Figure 2: Subjects with and without major depression exhibit the same EEG trends with subanesthetic ketamine. Top row: ketamine-only data from the U-Michigan study as shown in the analyses in Figure 1 . Bottom row: data from a separate study (U-Auckland) of 27 participants with major depression receiving a 0.25 mg/kg ketamine bolus. Data were analyzed at time zero (Start) and at 2 minutes after ketamine administration (End), which for a 70-kilogram 40-year-old person corresponds to a ketamine effect-site concentration of 0.2 mcg/ml; this is comparable to the level reached at the End time point of the 0.5 mg/kg infusions analyzed in this study (0.2-0.21 mcg/ml). Conventions are as in Fig. 1g-i . View this table: View inline View popup Download powerpoint Supplementary Table 1: Maintenance general anesthesia agents and dosages used during ketamine infusions View this table: View inline View popup Download powerpoint Supplementary Table 2: Participant demographics Acknowledgements This work was supported by a grant awarded to B.D.H. by the Society for Neuroscience in Anesthesia and Critical Care. T.R.L. received salary support through a T32 grant from the NIH National Institute on Drug Abuse (3T32DA035165-02S1). B.D. received support from the Research in Anesthesia Training Program (ReAP, NIH T32GM089626). The U-Michigan study was funded by NIH grant R01GM111293. The funding bodies supporting this study had no influence on the conduct of the trial, analysis of the data, or reporting of the results. References 1. ↵ Li L , Vlisides PE . Ketamine: 50 Years of Modulating the Mind . Front Hum Neurosci . 2016 ; 10 . doi: 10.3389/fnhum.2016.00612 OpenUrl CrossRef PubMed 2. ↵ Zarate CA Jr . , Singh JB , Carlson PJ , et al. A Randomized Trial of an N-methyl-D-aspartate Antagonist in Treatment-Resistant Major Depression . Arch Gen Psychiatry . 2006 ; 63 ( 8 ): 856 – 864 . doi: 10.1001/archpsyc.63.8.856 OpenUrl CrossRef PubMed Web of Science 3. ↵ Akeju O , Song AH , Hamilos AE , et al. Electroencephalogram signatures of ketamine anesthesia-induced unconsciousness . Clin Neurophysiol . 2016 ; 127 ( 6 ): 2414 – 2422 . doi: 10.1016/j.clinph.2016.03.005 OpenUrl CrossRef PubMed 4. ↵ Vlisides PE , Bel-Bahar T , Lee U , et al. Neurophysiologic Correlates of Ketamine Sedation and Anesthesia: A High-density Electroencephalography Study in Healthy Volunteers . Anesthesiology . 2017 ; 127 ( 1 ): 58 . doi: 10.1097/ALN.0000000000001671 OpenUrl CrossRef 5. ↵ Tian F , Lewis LD , Zhou DW , et al. Characterizing brain dynamics during ketamine-induced dissociation and subsequent interactions with propofol using human intracranial neurophysiology . Nat Commun . 2023 ; 14 ( 1 ): 1748 . doi: 10.1038/s41467-023-37463-3 OpenUrl CrossRef PubMed 6. Schüttler J , Stanski DR , White PF , et al. Pharmacodynamic modeling of the EEG effects of ketamine and its enantiomers in man . J Pharmacokinet Biopharm . 1987 ; 15 ( 3 ): 241 – 253 . doi: 10.1007/BF01066320 OpenUrl CrossRef PubMed Web of Science 7. Kochs E , Scharein E , Mollenberg O , Bromm B , Schulte am Esch J. Analgesic Efficacy of Low-dose Ketamine: Somatosensory-evoked Responses in Relation to Subjective Pain Ratings . Anesthesiology . 1996 ; 85 ( 2 ): 304 . doi: 10.1097/00000542-199608000-00012 OpenUrl CrossRef PubMed Web of Science 8. Muthukumaraswamy SD , Shaw AD , Jackson LE , Hall J , Moran R , Saxena N. Evidence that Subanesthetic Doses of Ketamine Cause Sustained Disruptions of NMDA and AMPA-Mediated Frontoparietal Connectivity in Humans . J Neurosci . 2015 ; 35 ( 33 ): 11694 – 11706 . doi: 10.1523/JNEUROSCI.0903-15.2015 OpenUrl Abstract / FREE Full Text 9. ↵ Rivolta D , Heidegger T , Scheller B , et al. Ketamine Dysregulates the Amplitude and Connectivity of High-Frequency Oscillations in Cortical–Subcortical Networks in Humans: Evidence From Resting-State Magnetoencephalography-Recordings . Schizophr Bull . 2015 ; 41 ( 5 ): 1105 – 1114 . doi: 10.1093/schbul/sbv051 OpenUrl CrossRef PubMed 10. ↵ Adam E , Kowalski M , Akeju O , et al. Ketamine can produce oscillatory dynamics by engaging mechanisms dependent on the kinetics of NMDA receptors . Proc Natl Acad Sci . 2024 ; 121 ( 22 ): e2402732121 . doi: 10.1073/pnas.2402732121 OpenUrl CrossRef PubMed 11. ↵ Vesuna S , Kauvar IV , Richman E , et al. Deep posteromedial cortical rhythm in dissociation . Nature . 2020 ; 586 ( 7827 ): 87 – 94 . doi: 10.1038/s41586-020-2731-9 OpenUrl CrossRef PubMed 12. ↵ Moghaddam B , Adams B , Verma A , Daly D. 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 . J Neurosci Off J Soc Neurosci . 1997 ; 17 ( 8 ): 2921 – 2927 . doi: 10.1523/JNEUROSCI.17-08-02921.1997 OpenUrl Abstract / FREE Full Text 13. ↵ Hambrecht-Wiedbusch VS , Li D , Mashour GA . Paradoxical Emergence: Administration of Subanesthetic Ketamine during Isoflurane Anesthesia Induces Burst Suppression but Accelerates Recovery . Anesthesiology . 2017 ; 126 ( 3 ): 482 – 494 . doi: 10.1097/ALN.0000000000001512 OpenUrl CrossRef PubMed 14. ↵ Duan WY , Peng K , Qin HM , et al. Esketamine accelerates emergence from isoflurane general anaesthesia by activating the paraventricular thalamus glutamatergic neurones in mice . Br J Anaesth . 2024 ; 132 ( 2 ): 334 – 342 . doi: 10.1016/j.bja.2023.10.038 OpenUrl CrossRef 15. ↵ Li D , Mashour GA . Cortical dynamics during psychedelic and anesthetized states induced by ketamine . NeuroImage . 2019 ; 196 : 32 – 40 . doi: 10.1016/j.neuroimage.2019.03.076 OpenUrl CrossRef PubMed 16. ↵ Lii TR , Smith AE , Flohr JR , et al. Randomized trial of ketamine masked by surgical anesthesia in patients with depression . Nat Ment Health . 2023 ; 1 ( 11 ): 876 – 886 . doi: 10.1038/s44220-023-00140-x OpenUrl CrossRef PubMed 17. ↵ McMillan R , Sumner R , Forsyth A , et al. Simultaneous EEG/fMRI recorded during ketamine infusion in patients with major depressive disorder . Prog Neuropsychopharmacol Biol Psychiatry . 2020 ; 99 : 109838 . doi: 10.1016/j.pnpbp.2019.109838 OpenUrl CrossRef 18. ↵ Sumner RL , McMillan R , Spriggs MJ , et al. Ketamine Enhances Visual Sensory Evoked Potential Long-term Potentiation in Patients With Major Depressive Disorder . Biol Psychiatry Cogn Neurosci Neuroimaging . 2020 ; 5 ( 1 ): 45 – 55 . doi: 10.1016/j.bpsc.2019.07.002 OpenUrl CrossRef PubMed 19. ↵ Liu P , Li P , Li Q , et al. Effect of Pretreatment of S-Ketamine On Postoperative Depression for Breast Cancer Patients . J Investig Surg Off J Acad Surg Res . 2021 ; 34 ( 8 ): 883 – 888 . doi: 10.1080/08941939.2019.1710626 OpenUrl CrossRef PubMed 20. Zhou Y , Sun W , Zhang G , et al. Ketamine Alleviates Depressive Symptoms in Patients Undergoing Intracranial Tumor Resection: A Randomized Controlled Trial . Anesth Analg . 2021 ; 133 ( 6 ): 1588 – 1597 . doi: 10.1213/ANE.0000000000005752 OpenUrl CrossRef PubMed 21. ↵ Zhang Z , Zhang WH , Lu YX , et al. Intraoperative Low-Dose S-Ketamine Reduces Depressive Symptoms in Patients with Crohn’s Disease Undergoing Bowel Resection: A Randomized Controlled Trial . J Clin Med . 2023 ; 12 ( 3 ): 1152 . doi: 10.3390/jcm12031152 OpenUrl CrossRef PubMed 22. ↵ Mashour GA , Abdallah AB , Pryor KO , et al. Intraoperative ketamine for prevention of depressive symptoms after major surgery in older adults: an international, multicentre, double-blind, randomised clinical trial . Br J Anaesth . 2018 ; 121 ( 5 ): 1075 – 1083 . doi: 10.1016/j.bja.2018.03.030 OpenUrl CrossRef PubMed 23. ↵ Babadi B , Brown EN . A review of multitaper spectral analysis . IEEE Trans Biomed Eng . 2014 ; 61 ( 5 ): 1555 – 1564 . doi: 10.1109/TBME.2014.2311996 OpenUrl CrossRef PubMed View the discussion thread. Back to top Previous Next Posted August 07, 2025. Download PDF Data/Code Email Thank you for your interest in spreading the word about medRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following General anesthesia dissociates discrete components of ketamine neurophysiology Message Subject (Your Name) has forwarded a page to you from medRxiv Message Body (Your Name) thought you would like to see this page from the medRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share General anesthesia dissociates discrete components of ketamine neurophysiology Ben Deverett , Duan Li , Theresa Lii , Phillip E. Vlisides , Vijay Tarnal , Anna Forsyth , Rachael Sumner , Pilleriin Sikka , Alan F. Schatzberg , Suresh Muthukumaraswamy , George A. Mashour , Boris D. Heifets medRxiv 2025.08.05.25333019; doi: https://doi.org/10.1101/2025.08.05.25333019 Share This Article: Copy Citation Tools General anesthesia dissociates discrete components of ketamine neurophysiology Ben Deverett , Duan Li , Theresa Lii , Phillip E. Vlisides , Vijay Tarnal , Anna Forsyth , Rachael Sumner , Pilleriin Sikka , Alan F. Schatzberg , Suresh Muthukumaraswamy , George A. Mashour , Boris D. Heifets medRxiv 2025.08.05.25333019; doi: https://doi.org/10.1101/2025.08.05.25333019 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Psychiatry and Clinical Psychology Subject Areas All Articles Addiction Medicine (567) Allergy and Immunology (863) Anesthesia (297) Cardiovascular Medicine (4411) Dentistry and Oral Medicine (443) Dermatology (380) Emergency Medicine (606) Endocrinology (including Diabetes Mellitus and Metabolic Disease) (1505) Epidemiology (15205) Forensic Medicine (30) Gastroenterology (1119) Genetic and Genomic Medicine (6574) Geriatric Medicine (666) Health Economics (994) Health Informatics (4511) Health Policy (1365) Health Systems and Quality Improvement (1608) Hematology (537) HIV/AIDS (1263) Infectious Diseases (except HIV/AIDS) (15903) Intensive Care and Critical Care Medicine (1103) Medical Education (620) Medical Ethics (144) Nephrology (666) Neurology (6573) Nursing (345) Nutrition (998) Obstetrics and Gynecology (1139) Occupational and Environmental Health (954) Oncology (3319) Ophthalmology (968) Orthopedics (369) Otolaryngology (420) Pain Medicine (435) Palliative Medicine (129) Pathology (662) Pediatrics (1689) Pharmacology and Therapeutics (691) Primary Care Research (710) Psychiatry and Clinical Psychology (5422) Public and Global Health (9205) Radiology and Imaging (2191) Rehabilitation Medicine and Physical Therapy (1367) Respiratory Medicine (1191) Rheumatology (593) Sexual and Reproductive Health (709) Sports Medicine (529) Surgery (709) Toxicology (99) Transplantation (288) Urology (265) (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'9fe99a8ecaeb0db4',t:'MTc3OTI2MTg4Nw=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();