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Inhibiting Human Aversive Memory by Transcranial Theta-Burst Stimulation to the Primary Sensory Cortex

  • Author Footnotes
    1 KEO and MS contributed equally to this work.
    Karita E. Ojala
    Correspondence
    Address correspondence to Karita E. Ojala, Ph.D.
    Footnotes
    1 KEO and MS contributed equally to this work.
    Affiliations
    Computational Psychiatry Research, Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zürich, Zürich, Switzerland

    Neuroscience Centre Zurich, University of Zürich, Zürich, Switzerland
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  • Author Footnotes
    1 KEO and MS contributed equally to this work.
    Matthias Staib
    Footnotes
    1 KEO and MS contributed equally to this work.
    Affiliations
    Computational Psychiatry Research, Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zürich, Zürich, Switzerland

    Neuroscience Centre Zurich, University of Zürich, Zürich, Switzerland
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  • Samuel Gerster
    Affiliations
    Computational Psychiatry Research, Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zürich, Zürich, Switzerland
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  • Christian C. Ruff
    Affiliations
    Neuroscience Centre Zurich, University of Zürich, Zürich, Switzerland

    Zurich Center for Neuroeconomics, Department of Economics, University of Zürich, Zürich, Switzerland
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  • Dominik R. Bach
    Correspondence
    Dominik R. Bach, Ph.D.
    Affiliations
    Computational Psychiatry Research, Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zürich, Zürich, Switzerland

    Neuroscience Centre Zurich, University of Zürich, Zürich, Switzerland

    Wellcome Centre for Human Neuroimaging and Max-Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom
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  • Author Footnotes
    1 KEO and MS contributed equally to this work.
Open AccessPublished:February 09, 2022DOI:https://doi.org/10.1016/j.biopsych.2022.01.021

      Abstract

      Background

      Predicting adverse events from past experience is fundamental for many biological organisms. However, some individuals suffer from maladaptive memories that impair behavioral control and well-being, e.g., after psychological trauma. Inhibiting the formation and maintenance of such memories would have high clinical relevance. Previous preclinical research has focused on systemically administered pharmacological interventions, which cannot be targeted to specific neural circuits in humans. Here, we investigated the potential of noninvasive neural stimulation on the human sensory cortex in inhibiting aversive memory in a laboratory threat conditioning model.

      Methods

      We build on an emerging nonhuman literature suggesting that primary sensory cortices may be crucially required for threat memory formation and consolidation. Immediately before conditioning innocuous somatosensory stimuli (conditioned stimuli [CS]) to aversive electric stimulation, healthy human participants received continuous theta-burst transcranial magnetic stimulation (cTBS) to individually localized primary somatosensory cortex in either the CS-contralateral (experimental) or CS-ipsilateral (control) hemisphere. We measured fear-potentiated startle to infer threat memory retention on the next day, as well as skin conductance and pupil size during learning.

      Results

      After overnight consolidation, threat memory was attenuated in the experimental group compared with the control cTBS group. There was no evidence that this differed between simple and complex CS or that CS identification or initial learning were affected by cTBS.

      Conclusions

      Our results suggest that cTBS to the primary sensory cortex inhibits threat memory, likely by an impact on postlearning consolidation. We propose that noninvasive targeted stimulation of the sensory cortex may provide a new avenue for interfering with aversive memories in humans.

      Keywords

      Memory for aversive events allows learning from past experience, adaptive behavior, and survival in ever-changing environments. However, in anxiety and stress-related disorders, such memories can become maladaptive and impairing (
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      Discriminative auditory fear learning requires both tuned and nontuned auditory pathways to the amygdala.
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      A non-canonical reticular-limbic central auditory pathway via medial septum contributes to fear conditioning.
      )]. Specifically, disrupting neural transmission in the auditory cortex during learning impairs threat memory acquisition of complex stimuli (
      • Dalmay T.
      • Abs E.
      • Poorthuis R.B.
      • Hartung J.
      • Pu D.L.
      • Onasch S.
      • et al.
      A critical role for neocortical processing of threat memory.
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      ), and blocking protein synthesis impairs postlearning consolidation but leaves acquisition unaffected (
      • Kraus M.
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      • Wetzel W.
      • Ohl F.
      • Staak S.
      • Tischmeyer W.
      Memory consolidation for the discrimination of frequency-modulated tones in Mongolian gerbils is sensitive to protein-synthesis inhibitors applied to the auditory cortex.
      ). Finally, disrupting neural transmission in the auditory cortex during cue presentation in a postconditioning test impairs complex discriminative but not nondiscriminative threat memory retrieval (
      • Gillet S.N.
      • Kato H.K.
      • Justen M.A.
      • Lai M.
      • Isaacson J.S.
      Fear learning regulates cortical sensory representations by suppressing habituation.
      ).
      In humans, CS+ associated with threat US and CS− associated with safety elicit differential evoked-potential amplitude, oscillatory synchrony, and univariate functional magnetic resonance imaging (fMRI) blood oxygen level–dependent amplitude in the visual cortex (
      • Keil A.
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      Aversive learning enhances perceptual and cortical discrimination of indiscriminable odor cues.
      ), and univariate blood oxygen level–dependent amplitude and multivariate patterns in the auditory cortex, with no difference between simple and complex CS (
      • Apergis-Schoute A.M.
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      ,
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      ). Recent evidence has also shown that the visual cortex is involved in long-term threat memory in humans (
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      Human sensory cortex contributes to the long-term storage of aversive conditioning.
      ). However, the precise function of these areas in the acquisition and retention of threat memories remains unresolved. In particular, it is unclear whether activity in these areas is in fact required for threat memoires to be formed and/or consolidated.
      To elucidate the role of the primary sensory cortex for discriminative conditioning to simple and complex CS in humans, we used continuous theta-burst TMS (cTBS) as a technique that can transiently downregulate cortical excitability and synaptic plasticity in the targeted area (
      • Huang Y.Z.
      • Edwards M.J.
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      • Bhatia K.P.
      • Rothwell J.C.
      Theta burst stimulation of the human motor cortex.
      ). We selected somatosensation as our model system because the primary somatosensory cortex (S1) is well accessible to cTBS and stimulus representation is strictly contralateral, unlike in the auditory system or in foveal vision (
      • Gazzaniga M.S.
      Cerebral specialization and interhemispheric communication: Does the corpus callosum enable the human condition?.
      ). Somatosensory threat conditioning in humans has been demonstrated previously (
      • Harvie D.S.
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      ), including a study from our own laboratory with the same CS as in this work (
      • Korn C.W.
      • Staib M.
      • Tzovara A.
      • Castegnetti G.
      • Bach D.R.
      A pupil size response model to assess fear learning.
      ). To examine the role of complex stimulus features, we used simple CS defined by stimulus location (finger) and complex CS defined by a temporal pattern of alternating locations. S1 was localized individually with fMRI.
      We expected reduced threat memory retention after overnight memory consolidation when cTBS had been applied to the stimulus–contralateral sensory cortex (experimental group) as compared with the stimulus–ipsilateral cortex (control group). We measured threat memory retention by potentiation of the startle eye-blink reflex to CS+ versus CS−. Studies in rodents suggest that cTBS exerts effects at multiple timescales: it can elicit action potentials immediately during stimulation, lead to a period of reduced cortical excitability in the direct aftermath of the stimulation, and induce longer-term changes in learning and memory at different timescales through synaptic long-term depression (LTD) and by modulating neurotransmitters, neural growth factors, and gene expression (
      • Polanía R.
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      Studying and modifying brain function with non-invasive brain stimulation.
      ,
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      ). In humans, there is evidence that the inhibitory LTD-like effect of cTBS (
      • Huang Y.Z.
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      • Rounis E.
      • Bhatia K.P.
      • Rothwell J.C.
      Theta burst stimulation of the human motor cortex.
      ) may be mediated by effects on both GABAergic (gamma-aminobutyric acidergic) interneurons and glutamate (NMDA) receptors that are involved in synaptic long-term potentiation (LTP) and LTD (
      • Huang Y.Z.
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      The after-effect of human theta burst stimulation is NMDA receptor dependent.
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      ,
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      ).
      However, the timescales of these effects are not precisely known, and neither is the time course of memory consolidation, which starts immediately after a CS-US coupling. Synaptic plasticity independent of protein synthesis (early LTP) may last up to 1 to 3 hours, synaptic consolidation dependent on protein synthesis starts soon after the first instance of learning and may last up to 24 hours (late LTP), and systems consolidation takes place over days and weeks (
      • Baltaci S.B.
      • Mogulkoc R.
      • Baltaci A.K.
      Molecular mechanisms of early and late LTP.
      ,
      • Dudai Y.
      The neurobiology of consolidations, or, how stable is the engram?.
      ). To maximize the sensitivity of our study to answer whether S1 is causally involved in threat memory formation and/or retention, we conducted cTBS before learning and measured threat memory recall on the next day as the primary outcome. By analyzing conditioned responses during initial learning, we additionally sought to disentangle whether a possible effect on memory retention was primarily driven by learning deficits already measurable during conditioning or consolidation deficits only measurable during the recall test.

      Methods and Materials

      Participants

      A total of 68 participants (34 women and 34 men; mean ± SD age = 23.7 ± 4.2 years) recruited from the general and student population completed the cTBS and threat conditioning session on test day 1 according to protocol. After exclusions due to data collection and quality issues (detailed in Figure S1 in Supplement 1), the final sample for skin conductance analyses was 62 participants (28 experimental, 34 control) and 34 participants (18 experimental, 16 control) for pupil size analyses. A total of 52 participants were included in our analyses of startle eye-blink responses in the threat memory recall test (25 experimental, 27 control). All recruited participants stated no history of neurological and psychiatric disorders or contraindications for TMS and MRI and gave written informed consent. The study protocol, including the form of taking consent, was in accordance with the Declaration of Helsinki and approved by a governmental research ethics committee (Kantonale Ethikkommission Zürich, KEH-ZH 2013-0383).

      Primary Sensory Cortex Localization and Transcranial Stimulation Protocol

      Participants took part in an fMRI experiment to individually localize the S1 representation of the index and middle fingers of both hands for later targeting with cTBS. After the fMRI localizer, participants were invited to the laboratory on 2 consecutive days (Figure 1). On the first day, cTBS was administered before the experimental task. We used a protocol that has been shown to decrease cortical excitability for up to an hour (
      • Huang Y.Z.
      • Edwards M.J.
      • Rounis E.
      • Bhatia K.P.
      • Rothwell J.C.
      Theta burst stimulation of the human motor cortex.
      ). For the experimental group, cTBS was applied to the left hemisphere S1, and for the control group, it was applied to the right hemisphere S1. The protocol consisted of 600 pulses administered continuously for 40 seconds in bursts of three pulses at 50 Hz (every 20 ms) at 5-Hz intervals (every 200 ms) (
      • Huang Y.Z.
      • Edwards M.J.
      • Rounis E.
      • Bhatia K.P.
      • Rothwell J.C.
      Theta burst stimulation of the human motor cortex.
      ), applied with a figure-of-eight coil. Immediately after cTBS, participants underwent 20 minutes of classical threat conditioning, which is well within the estimated duration of the cTBS effect (
      • Huang Y.Z.
      • Edwards M.J.
      • Rounis E.
      • Bhatia K.P.
      • Rothwell J.C.
      Theta burst stimulation of the human motor cortex.
      ). Details of the localizer and cTBS protocols are described in Supplement 1.
      Figure thumbnail gr1
      Figure 1Structure of the study and the experimental paradigm. First, participants underwent functional magnetic resonance imaging (fMRI) and somatosensory stimulation to functionally localize the primary somatosensory cortex (S1) for the second digits of index and middle fingers (d1: left middle finger, d2: left index finger, d3: right index finger, d4: right middle finger). On the first test day, participants received continuous theta-burst transcranial magnetic stimulation (TMS) targeted on S1. Experimental group received continuous theta-burst stimulation (cTBS) on the right hemisphere, contralateral to the somatosensory conditioned stimuli (CS) on the left hand. Control group received cTBS on the ipsilateral hemisphere. Immediately after cTBS, participants underwent threat conditioning with aversive electric shock unconditioned stimuli (US) with a 50% reinforcement rate. US was delivered to the foot ipsilateral to the cTBS site. Simple CS were electric pulses to either index or middle finger of the left hand whereas complex CS were pulses alternating between fingers. Simple and complex CS blocks alternated in all sessions. Each CS lasted for 4 s, and 50% of CS+ trials co-terminated with the 0.5-s US, whereas CS− trials never co-terminated with the US. On each trial, participants saw a fixation cross in the center of the screen and were asked to press a button as fast as possible to indicate which of the two possible stimulus patterns they perceived. Pupil size and skin conductance from the ring and little fingers were recorded during conditioning. On the next day, participants came back for a test of threat memory retention in a recall session and a relearning session, which were both conducted without cTBS. The recall session was conducted under extinction (no US), and eye-blink reflex to an acoustic startle probe was recorded. Relearning was conducted afterward with 50% reinforcement. Pupil size responses and skin conductance responses were recorded also during relearning. At the end of the conditioning and relearning sessions, participants rated each CS for how likely they thought it had co-terminated with the US during the experiment.

      CS and US of the Threat Conditioning Protocol

      There were four different CS in the experiment: 1) simple CS+ paired with an electric shock US in 50% of trials, 2) simple CS− never paired with the US, 3) complex CS+ paired with an electric shock US in 50% of trials, and 4) complex CS− never paired with the shock. Simple and complex CS trials were presented in separate, alternating conditioning blocks in all conditioning and recall sessions. The intensity for the CS was set for each finger separately and to a subjectively clear but not unpleasant level by incremental increases of the current. CS were 4-second electric pulses to the middle and index fingers of the left hand delivered with a Digitimer DS7A stimulator through a pin-cathode/ring-anode electrode. Simple CS were short pulses either on the middle or index finger whereas complex stimuli alternated between the two fingers. Aversive US was an electric shock of 500-ms duration delivered with a Digitimer DS7A stimulator to the top of the foot. The US was delivered ipsilateral to the cTBS site to exclude possible cTBS effects on sensory processing of the US. Intensity of the US was individually calibrated for each participant.

      Day 1: Training, cTBS, and Threat Conditioning

      Participants trained the experimental task without US before cTBS. They received each of the four somatosensory CS three times in random order (i.e., 12 trials) and were asked to indicate which CS pattern they perceived by pressing the left/right arrow button. The training block was repeated until 75% accuracy was achieved for both simple and complex stimuli and served also as habituation to the CS alone. After cTBS, the threat conditioning protocol followed, consisting of eight blocks of 12 trials each, for a total of 96 trials. The intertrial interval was between 7 and 11 seconds. The order of simple and complex blocks (simple first or complex first) was randomized.

      Day 2: Threat Memory Retention and Relearning

      The next day, participants returned for a recall and relearning session to assess memory savings from the conditioning session of the previous day. Recall was measured in the absence of US in four blocks of six trials each, i.e., two blocks of simple and two blocks of complex stimuli, for a total of 24 trials (12 CS+, 12 CS−). Before the recall session, the experiment was set up the same way as the previous day, including the US electrode on the foot. To retain expectation of US, participants were instructed that they may experience US during the session, including the possibility of only one US at the very end. During the recall session, participants were exposed to auditory startle probes (50 ms, 100-dB white noise via headphones) on every trial at CS offset. The relearning session was identical to the learning session of the previous day, except for the cTBS.

      Dependent Variables

      Our primary index of memory retention was fear-potentiated startle, which has been suggested as the most sensitive conditioned response across various psychophysiological indices (
      • Bach D.R.
      • Melinscak F.
      Psychophysiological modelling and the measurement of fear conditioning.
      ) as well as in a head-to-head comparison with skin conductance responses (SCRs) (
      • Khemka S.
      • Tzovara A.
      • Gerster S.
      • Quednow B.B.
      • Bach D.R.
      Modeling startle eyeblink electromyogram to assess fear learning.
      ). Different from other conditioned responses, it is also assumed to unambiguously relate to US expectation (
      • Ojala K.E.
      • Bach D.R.
      Measuring learning in human classical threat conditioning: Translational, cognitive and methodological considerations.
      ). We did not use fear-potentiated startle during acquisition, because this has been shown to alter and delay the learning process (
      • Sjouwerman R.
      • Niehaus J.
      • Kuhn M.
      • Lonsdorf T.B.
      Don’t startle me—Interference of startle probe presentations and intermittent ratings with fear acquisition.
      ) and might therefore reduce the sensitivity of the paradigm. To index acquisition of conditioning, we used SCRs and pupil size responses (PSRs) estimated with a model-based approach (
      • Korn C.W.
      • Staib M.
      • Tzovara A.
      • Castegnetti G.
      • Bach D.R.
      A pupil size response model to assess fear learning.
      ,
      • Staib M.
      • Castegnetti G.
      • Bach D.R.
      Optimising a model-based approach to inferring fear learning from skin conductance responses.
      ). These were not analyzed in the recall session because the presence of startle probes produces artefacts and makes the responses difficult to interpret. Details of the psychophysiological methods are found in Supplement 1.

      CS-US Contingency Ratings

      Immediately after the conditioning and relearning sessions, participants were presented with each CS alone without US. Participants were asked to indicate what they thought was the probability of the US occurring together with this CS, from a choice of 0%, 25%, 50%, 75%, or 100%.

      Statistical Analysis

      The estimated startle eye-blink, SCRs and PSRs, and postexperiment contingency ratings, accuracies, and reaction times for each participant were analyzed in R (
      R Core Team
      R: A language and environment for statistical computing.
      ). For SCRs and PSRs in both learning and relearning sessions, only trials without US were included in the analyses to avoid confounding of the conditioned responses with unconditioned responses. Psychophysiological response estimates, CS-US contingency ratings, reaction times, and accuracy percentages were entered into three-way repeated-measures analyses of variance of the form DV ∼ group × CS type × CS complexity + error (subject/[CS type × CS complexity]). Post hoc tests were conducted with emmeans R package (
      • Lenth R.V.
      • Buerkner P.
      • Herve M.
      • Love J.
      • Miguez F.
      • Riebl H.
      • Singmann H.
      emmeans: Estimated marginal means, aka least-squares means.
      ) and effect sizes were approximated with the t_to_d function of effect size package (
      • Ben-Shachar M.S.
      • Lüdecke D.
      • Makowski D.
      effectsize: Estimation of effect size indices and standardized parameters.
      ). Further specific tests were conducted with Student’s paired t tests for within-subject effects and Welch’s two-sample t tests for comparing groups with unequal sample sizes. One-tailed p values were used for a priori hypotheses for CS+ > CS− and control > experimental group; two-tailed tests were used for all other comparisons.

      Results

      Threat Memory Retention: Startle Eye-Blink Responses

      The primary focus of our study was to investigate the cTBS effect on memory retention on test day 2. Consistent with a cTBS-induced reduction of threat memory retention, we found a significant group × CS type interaction (Table 1 and Figure 2), with an overall smaller CS+/CS− difference in the experimental group compared with the control group. There was no evidence that this effect depended on CS complexity (Table 1). Post hoc t tests suggested a difference in fear-potentiated startle elicited by CS+ versus CS− (collapsing across CS complexity) in the control group (t50 = 3.76, p = .0002, Cohen’s d = 0.53) but not in the experimental group (t50 = 0.25, p = .60, d = 0.04).
      Table 1Statistical Test Results for Conditionwise Startle Eye-Blink Responses During Threat Memory Recall Test on Test Day 2
      Repeated-Measures ANOVAF1,50pη2
      Group7.71.0080.024
      CS Type6.39.0150.020
      CS Complexity5.48.0230.049
      Group × CS Type7.71.0080.024
      Group × CS Complexity0.00.99<0.001
      CS Type × CS Complexity0.30.59<0.001
      Group × CS Type × CS Complexity2.56.120.006
      η2 represents the explained variance.
      ANOVA, analysis of variance; CS, conditioned stimulus.
      Figure thumbnail gr2
      Figure 2Startle eye-blink responses (SEBRs) during threat memory recall test on test day 2. (A) Trial-by-trial responses for each condition show the time course of the responses, with little differentiation of CS+ and CS− for the experimental group and overall quick decline in amplitude across trials (habituation). (B) The CS+/CS− difference was smaller for the experimental group than for the control group across simple and complex conditioned stimuli (CS), indicating that the fear-potentiated startle was inhibited by continuous theta-burst transcranial magnetic stimulation as measured in the threat memory recall test the next day. Error bars are 95% within-subject standard errors of the mean reflecting paired, one-tailed CS+ > CS− comparison (
      • Morey R.D.
      Confidence intervals from normalized data: A correction to Cousineau (2005).
      ). a.u., arbitrary units.
      The analysis included all trials of the recall test and may thus potentially reflect group differences in extinction learning due to repeated presentations of CS without US. However, the group difference in CS+/CS− discrimination was already present during the first six trials of the recall test (t49.71 = 2.16, p = .036, d = 0.598). Moreover, the size of the group difference in CS+/CS− discrimination did not differ between the first and last half of the recall test (t47.17 = 1.58, p = .12, d = 0.435).

      Threat Conditioning on the Day Before Recall Test: SCRs and PSRs

      Our finding of reduced memory retention after cTBS could be due to impairments in synaptic consolidation after the threat conditioning or due to impairments in neural processing and synaptic transmission during acquisition of conditioning. To assess the latter possibility, we analyzed SCRs and PSRs to CS during conditioning on test day 1. In line with our previous somatosensory threat conditioning data (
      • Korn C.W.
      • Staib M.
      • Tzovara A.
      • Castegnetti G.
      • Bach D.R.
      A pupil size response model to assess fear learning.
      ), participants learned to discriminate CS+ and CS− as evidenced by SCRs (Table 2 and Figure 3A, C) and PSRs (Table 2 and Figure 3B, D). There was no evidence that learning differed between control or experimental cTBS groups. Pairwise comparisons within the groups showed a different constellation of results for SCRs and PSRs, with stronger learning in the control group than in the experimental group for SCRs but the opposite pattern for PSRs (Figure 3C, D; Table S3 in Supplement 1), while the interaction term for learning difference between the groups was not close to significant for either SCRs or PSRs (Table 2). There was no significant interaction of learning and CS complexity for either SCR or PSR (Table 2).
      Table 2Statistical Test Results for Conditionwise SCRs and PSRs During Threat Learning on Test Day 1
      Repeated-Measures ANOVAFpη2
      SCRs
       GroupF1,60 = 0.45.510.001
       CS typeF1,60 = 7.82.0070.02
       CS complexityF1,60 = 1.25.270.01
       Group × CS typeF1,60 = 0.39.53<0.001
       Group × CS complexityF1,60 = 0.06.82<0.001
       CS type × CS complexityF1,60 = 1.68.200.004
       Group × CS type × CS complexityF1,60 = 0.19.67<0.001
      PSRs
       GroupF1,35 = 1.36.250.021
       CS typeF1,35 = 5.33.0270.015
       CS complexityF1,35 = 33.2<.0010.002
       Group × CS typeF1,35 = 0.85.360.119
       Group × CS complexityF1,35 = 2.29.140.008
       CS type × CS complexityF1,35 = 1.53.230.003
       Group × CS type × CS complexityF1,35 = 0.05.82<0.001
      η2 represents the explained variance.
      ANOVA, analysis of variance; CS, conditioned stimulus; PSRs, pupil size responses; SCRs, skin conductance responses.
      Figure thumbnail gr3
      Figure 3Skin conductance responses (SCRs) and pupil size responses (PSRs) during threat conditioning on test day 1. (A, B) Averaged trial time courses of skin conductance and pupil size changes from baseline for the different stimuli, separately for control and experimental groups. Shaded areas represent within-subject SEM; dashed gray line marks unconditioned stimulus onset (only no unconditioned stimulus trials were included). (C, D) SCR amplitudes and PSR estimates showed that the participants learned the CS+/CS− difference overall (main effect of conditioned stimulus [CS] type for both modalities) (), evidencing threat conditioning. There was no evidence for a significant difference in learning between the control and experimental groups (interaction of group and CS type) or between the simple and complex stimuli (interaction of CS complexity and CS type). Error bars show 95% within-subject SEM reflecting paired, one-tailed CS+ > CS− comparison (
      • Morey R.D.
      Confidence intervals from normalized data: A correction to Cousineau (2005).
      ). a.u., arbitrary units; μS, microsiemens.

      Threat Relearning After Recall Test: SCRs and PCRs

      To assess memory savings carried over from the conditioning session of the previous day, we conducted a second learning session directly after the threat memory recall test. PSRs discriminated between CS+ and CS− overall, with no difference between experimental and control cTBS groups (Figure S3 and Table S5 in Supplement 1). No significant differences in CS+/CS− responses were found in condition-wise SCRs (Figure S3 and Table S5 in Supplement 1) while a small difference was found in trialwise responses (F1,3886 = 5.83, p = .02) but no group × CS type interaction (Table S6 in Supplement 1).

      CS-US Contingency Learning

      Participants learned to explicitly distinguish CS+/CS− (F1,50 = 18.1, p < .001, η2 = 0.121) (Figure S4A in Supplement 1) after day 1 and on day 2 after relearning (F1,50 = 83.3, p < .001, η2 = 0.356) (Figure S4B in Supplement 1). There was no difference between ratings for simple and complex stimuli on either test day or between cTBS groups on test day 1 (all p values > .30). Further results can be found in Supplement 1.

      Discussion

      Growing evidence from rodent studies suggests that sensory cortices are important for processing complex stimuli during auditory threat conditioning, but their role for simple CS, and for human threat conditioning in general, remains unclear. We addressed this question in a TMS study with the goal of inducing temporary inhibition of neural processing in the sensory cortex. We applied cTBS in healthy human participants over S1, either ipsilateral (control) or contralateral (experimental) to somatosensory stimuli, immediately prior to a threat conditioning protocol where the somatosensory stimuli were paired with painful shocks (CS+) or not (CS−). We found that after overnight consolidation, differential fear-potentiated startle to CS+/CS− was smaller in the experimental (contralateral cTBS) group compared with the control (ipsilateral cTBS) group. Detailed analyses confirmed the robustness of this finding and showed that it was not due to group differences in extinction learning or in the random trial sequence. We found no evidence for an inhibitory cTBS effect during the initial learning session. Moreover, contralateral cTBS did not impair CS identification, excluding the possibility that our results merely reflect a cTBS-induced deficit in immediate somatosensory processing unrelated to the threat conditioning. Taken together, these results suggest that cTBS did not interfere with basic sensory processing and activity-dependent short-term plasticity, but rather with synaptic structural reconfiguration required for memory consolidation (
      • Baltaci S.B.
      • Mogulkoc R.
      • Baltaci A.K.
      Molecular mechanisms of early and late LTP.
      ).
      As a caveat, cTBS was conducted before threat conditioning. The lack of a significant effect of cTBS on learning cannot conclusively rule out that there was no impact on learning, particularly so because distinct and not directly comparable conditioned responses were assessed during learning and during recall. Future work could conduct cTBS after conditioning to conclusively confirm that cTBS impacts on consolidation. This could also be useful to explore the possibility of using cTBS clinically in a post-trauma prevention setting. Recently, it was shown that repetitive TMS over the dorsolateral prefrontal cortex administered after visual threat memory retrieval was successful in reducing physiological threat responses during the so-called reconsolidation period and preventing return of threat responding after reinstatement, while leaving declarative CS-US learning intact (
      • Borgomaneri S.
      • Battaglia S.
      • Garofalo S.
      • Tortora F.
      • Avenanti A.
      • di Pellegrino G.
      State-dependent TMS over prefrontal cortex disrupts fear-memory reconsolidation and prevents the return of fear.
      ). The authors speculate that this effect may be due to the role of the dorsolateral prefrontal cortex in memory retrieval and potentially due to long-range connections to the amygdala (
      • Borgomaneri S.
      • Battaglia S.
      • Garofalo S.
      • Tortora F.
      • Avenanti A.
      • di Pellegrino G.
      State-dependent TMS over prefrontal cortex disrupts fear-memory reconsolidation and prevents the return of fear.
      ). Therefore, there may be several putative time windows and neural pathways through which to influence threat memories with TMS. Beyond TMS studies, there is very little data from clinical lesion samples to address the role of sensory cortices in threat conditioning. One lesion case study suggested that the visual cortex is not required for nondiscriminative visual conditioning in humans (
      • Hamm A.O.
      • Weike A.I.
      • Schupp H.T.
      • Treig T.
      • Dressel A.
      • Kessler C.
      Affective blindsight: Intact fear conditioning to a visual cue in a cortically blind patient.
      ), in line with nondiscriminative auditory conditioning in rodents (
      • Sacco T.
      • Sacchetti B.
      Role of secondary sensory cortices in emotional memory storage and retrieval in rats.
      ,
      • Campeau S.
      • Davis M.
      Involvement of subcortical and cortical afferents to the lateral nucleus of the amygdala in fear conditioning measured with fear-potentiated startle in rats trained concurrently with auditory and visual conditioned stimuli.
      ,
      • Romanski L.M.
      • LeDoux J.E.
      Equipotentiality of thalamo-amygdala and thalamo-cortico-amygdala circuits in auditory fear conditioning.
      ,
      • Peter M.
      • Scheuch H.
      • Burkard T.R.
      • Tinter J.
      • Wernle T.
      • Rumpel S.
      Induction of immediate early genes in the mouse auditory cortex after auditory cued fear conditioning to complex sounds.
      ,
      • Moczulska K.E.
      • Tinter-Thiede J.
      • Peter M.
      • Ushakova L.
      • Wernle T.
      • Bathellier B.
      • Rumpel S.
      Dynamics of dendritic spines in the mouse auditory cortex during memory formation and memory recall.
      ).
      While we selected somatosensory threat conditioning as a model system for methodological reasons, somatosensation is an important sensory modality to investigate next to the more commonly investigated auditory and visual modalities. Clinically, somatosensation is affected in posttraumatic stress disorder (
      • Badura-Brack A.S.
      • Becker K.M.
      • McDermott T.J.
      • Ryan T.J.
      • Becker M.M.
      • Hearley A.R.
      • et al.
      Decreased somatosensory activity to non-threatening touch in combat veterans with posttraumatic stress disorder.
      ), a psychiatric disorder that has been proposed to develop partly as a result of maladaptive conditioning mechanisms such as threat overgeneralization and impaired safety learning (
      • Duits P.
      • Cath D.C.
      • Lissek S.
      • Hox J.J.
      • Hamm A.O.
      • Engelhard I.M.
      • et al.
      Updated meta-analysis of classical fear conditioning in the anxiety disorders.
      ,
      • Dunsmoor J.E.
      • Paz R.
      Fear generalization and anxiety: Behavioral and neural mechanisms.
      ). In rodents, somatosensory threat conditioning with whisker touch as CS is suggested to induce increased neural response strength, sparse coding (
      • Gdalyahu A.
      • Tring E.
      • Polack P.O.
      • Gruver R.
      • Golshani P.
      • Fanselow M.S.
      • et al.
      Associative fear learning enhances sparse network coding in primary sensory cortex.
      ), dendritic spine plasticity (
      • Joachimsthaler B.
      • Brugger D.
      • Skodras A.
      • Schwarz C.
      Spine loss in primary somatosensory cortex during trace eyeblink conditioning.
      ), and inhibitory postsynaptic potentials (
      • Tokarski K.
      • Urban-Ciecko J.
      • Kossut M.
      • Hess G.
      Sensory learning-induced enhancement of inhibitory synaptic transmission in the barrel cortex of the mouse.
      ) in the primary somatosensory barrel cortex, somewhat similar to postconsolidation changes in the auditory cortex (
      • Weinberger N.M.
      Associative representational plasticity in the auditory cortex: A synthesis of two disciplines.
      ). Our study adds to the scarce literature on somatosensory threat conditioning in humans (
      • Harvie D.S.
      • Meulders A.
      • Madden V.J.
      • Hillier S.L.
      • Peto D.K.
      • Brinkworth R.
      • Moseley G.L.
      When touch predicts pain: Predictive tactile cues modulate perceived intensity of painful stimulation independent of expectancy.
      ,
      • Harvie D.S.
      • Meulders A.
      • Reid E.
      • Camfferman D.
      • Brinkworth R.S.A.
      • Moseley G.L.
      Selectivity of conditioned fear of touch is modulated by somatosensory precision.
      ). In line with our previous work (
      • Korn C.W.
      • Staib M.
      • Tzovara A.
      • Castegnetti G.
      • Bach D.R.
      A pupil size response model to assess fear learning.
      ), we have shown that somatosensory threat learning is possible from simple and complex patterned electric pulses on fingers, but now we additionally demonstrate that the associative memory is retained at least overnight.
      We found that S1 is required at least for consolidation of associative somatosensory threat memories in humans, in line with previous findings in rodent auditory threat conditioning to complex cues. It has been suggested that primary sensory cortices are involved in stimulus identification and are specifically needed for processing complex stimuli, such as frequency sweeps and tone pips, which necessitate the binding together of different stimulus elements into a unitary representation (
      • Dalmay T.
      • Abs E.
      • Poorthuis R.B.
      • Hartung J.
      • Pu D.L.
      • Onasch S.
      • et al.
      A critical role for neocortical processing of threat memory.
      ,
      • Kholodar-Smith D.B.
      • Allen T.A.
      • Brown T.H.
      Fear conditioning to discontinuous auditory cues requires perirhinal cortical function.
      ). However, we did not find evidence that the role of S1 in threat conditioning and threat memory retention differed between simple and complex somatosensory stimuli (here differentiated by the temporal pattern of the stimulus across one or two fingers). Indeed, the role of the sensory cortex in rodent discriminant conditioning with simple cues has not been conclusively established or falsified. Our results are more in line with studies suggesting that primary sensory cortices are important for discriminant simple-cue conditioning as well (
      • Banerjee S.B.
      • Gutzeit V.A.
      • Baman J.
      • Aoued H.S.
      • Doshi N.K.
      • Liu R.C.
      • Ressler K.J.
      Perineuronal nets in the adult sensory cortex are necessary for fear learning.
      ,
      • Yang Y.
      • Liu D.Q.
      • Huang W.
      • Deng J.
      • Sun Y.
      • Zuo Y.
      • Poo M.M.
      Selective synaptic remodeling of amygdalocortical connections associated with fear memory [published correction appears in Nat Neurosci 2018; 21:1137.
      ). They are also in line with human neuroimaging studies that found equal CS+/CS− neural pattern discriminability for simple and complex CS in the auditory cortex (
      • Staib M.
      • Bach D.R.
      Stimulus-invariant auditory cortex threat encoding during fear conditioning with simple and complex sounds.
      ,
      • Staib M.
      • Abivardi A.
      • Bach D.R.
      Primary auditory cortex representation of fear-conditioned musical sounds.
      ) and that were able to cross-decode simple CS threat predictions from complex threat predictions and vice versa (
      • Staib M.
      • Bach D.R.
      Stimulus-invariant auditory cortex threat encoding during fear conditioning with simple and complex sounds.
      ). However, it is possible that experiments with larger sample sizes may detect effects of complexity (
      • Bach D.R.
      • Tzovara A.
      • Vunder J.
      Blocking human fear memory with the matrix metalloproteinase inhibitor doxycycline.
      ,
      • Bach D.R.
      • Melinščak F.
      • Fleming S.M.
      • Voelkle M.C.
      Calibrating the experimental measurement of psychological attributes.
      ). Finally, as of yet, there is no direct evidence from neuroimaging studies that somatosensory cortices are associated with threat learning and memory processes in humans irrespective of stimulus complexity.
      The neural effects of theta-burst TMS are multifaceted (
      • Polanía R.
      • Nitsche M.A.
      • Ruff C.C.
      Studying and modifying brain function with non-invasive brain stimulation.
      ). They may reflect synaptic LTP and LTD at excitatory glutamatergic (
      • Huang Y.Z.
      • Chen R.S.
      • Rothwell J.C.
      • Wen H.Y.
      The after-effect of human theta burst stimulation is NMDA receptor dependent.
      ,
      • Vlachos A.
      • Müller-Dahlhaus F.
      • Rosskopp J.
      • Lenz M.
      • Ziemann U.
      • Deller T.
      Repetitive magnetic stimulation induces functional and structural plasticity of excitatory postsynapses in mouse organotypic hippocampal slice cultures.
      ) and inhibitory GABAergic neurons (
      • Stagg C.J.
      • Wylezinska M.
      • Matthews P.M.
      • Johansen-Berg H.
      • Jezzard P.
      • Rothwell J.C.
      • Bestmann S.
      Neurochemical effects of theta burst stimulation as assessed by magnetic resonance spectroscopy [published correction appears in J Neurophysiol 2011; 105:3114].
      ,
      • Nitsche M.A.
      • Müller-Dahlhaus F.
      • Paulus W.
      • Ziemann U.
      The pharmacology of neuroplasticity induced by non-invasive brain stimulation: Building models for the clinical use of CNS active drugs.
      ), neurotrophic factors (
      • Fritsch B.
      • Reis J.
      • Martinowich K.
      • Schambra H.M.
      • Ji Y.
      • Cohen L.G.
      • Lu B.
      Direct current stimulation promotes BDNF-dependent synaptic plasticity: Potential implications for motor learning.
      ,
      • Cheeran B.
      • Talelli P.
      • Mori F.
      • Koch G.
      • Suppa A.
      • Edwards M.
      • et al.
      A common polymorphism in the brain-derived neurotrophic factor gene (BDNF) modulates human cortical plasticity and the response to rTMS.
      ), and neurogenesis (
      • Ueyama E.
      • Ukai S.
      • Ogawa A.
      • Yamamoto M.
      • Kawaguchi S.
      • Ishii R.
      • Shinosaki K.
      Chronic repetitive transcranial magnetic stimulation increases hippocampal neurogenesis in rats.
      ). It has been proposed that the LTD-like effect of continuous theta-burst TMS used here is based on an initial facilitatory LTP-like effect, as seen with intermittent theta-burst TMS, which reverses and becomes inhibitory with continuing stimulation (
      • Suppa A.
      • Huang Y.Z.
      • Funke K.
      • Ridding M.C.
      • Cheeran B.
      • Di Lazzaro V.
      • et al.
      Ten years of theta burst stimulation in humans: Established knowledge, unknowns and prospects.
      ). However, at this moment, it is not yet known whether these mechanisms truly underlie the observed inhibitory effect of continuous theta-burst TMS observed in humans. The best evidence comes from a study where an NMDA receptor antagonist blocked both the LTP-like excitatory and LTD-like inhibitory effects of theta-burst TMS in 6 healthy human participants (
      • Huang Y.Z.
      • Chen R.S.
      • Rothwell J.C.
      • Wen H.Y.
      The after-effect of human theta burst stimulation is NMDA receptor dependent.
      ). Finally, the efficacy of repetitive TMS is strongly influenced by baseline cortical excitability as well as individual and contextual factors (
      • Polanía R.
      • Nitsche M.A.
      • Ruff C.C.
      Studying and modifying brain function with non-invasive brain stimulation.
      ,
      • Li C.T.
      • Huang Y.Z.
      • Bai Y.M.
      • Tsai S.J.
      • Su T.P.
      • Cheng C.M.
      Critical role of glutamatergic and GABAergic neurotransmission in the central mechanisms of theta-burst stimulation.
      ,
      • Silvanto J.
      • Bona S.
      • Marelli M.
      • Cattaneo Z.
      On the mechanisms of transcranial magnetic stimulation (TMS): How brain state and baseline performance level determine behavioral effects of TMS.
      ). Crucially, rodent studies suggest also longer-lasting effects of cTBS via modulating neurotransmitters, neural growth factors, and gene expression (
      • Polanía R.
      • Nitsche M.A.
      • Ruff C.C.
      Studying and modifying brain function with non-invasive brain stimulation.
      ,
      • Siebner H.R.
      • Rothwell J.
      Transcranial magnetic stimulation: New insights into representational cortical plasticity.
      ). This may have contributed to the results we observe here, a hypothesis that could be tested by future extensions of our approach in rodents.
      TMS is known to influence wide functional networks in the human brain, with potential effects on even distant brain regions through long-range connections (
      • Siebner H.R.
      • Rothwell J.
      Transcranial magnetic stimulation: New insights into representational cortical plasticity.
      ,
      • Bestmann S.
      • Feredoes E.
      Combined neurostimulation and neuroimaging in cognitive neuroscience: Past, present, and future.
      ). This has also been shown for cTBS of S1 at rest, which led to reductions in functional connectivity of S1 with a variety of distant brain regions, including regions important for threat conditioning such as the amygdala, striatum, and anterior cingulate cortex (
      • Valchev N.
      • Curčić-Blake B.
      • Renken R.J.
      • Avenanti A.
      • Keysers C.
      • Gazzola V.
      • Maurits N.M.
      cTBS delivered to the left somatosensory cortex changes its functional connectivity during rest.
      ). Therefore, without concurrent fMRI measurement, we cannot confirm or exclude possible downstream influences of our cTBS protocol on other brain areas.
      Taken together, we found that inhibitory cTBS over S1 led to reduced threat memory retention after overnight consolidation, with no clear influence of CS complexity. This finding extends the rodent and human literature on the function of primary sensory cortices in threat learning and memory by suggesting that primary sensory cortices are involved in stimulus representation for threat conditioning and play a role in consolidation of threat memories. Further studies may investigate the neurophysiological mechanisms underlying these effects with concurrent neuroimaging and TMS, examine whether cTBS on S1 could be used as a method to modify threat memories through a reconsolidation update mechanism (
      • Kroes M.C.W.
      • Schiller D.
      • LeDoux J.E.
      • Phelps E.A.
      Translational approaches targeting reconsolidation.
      ), and attempt to establish whether intervening with (re)consolidation of threat memories may have clinical relevance for patients with fear and anxiety disorders.

      Acknowledgments and Disclosures

      This work was funded by the Swiss National Science Foundation (Grant No. 320030_149586/1 [to DRB]) and Wellcome Centre for Human Neuroimaging (University College London, UK) core funding (Grant No. 203147/Z/16/Z ). DRB and CCR are supported by funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (Grant No. ERC-2018 CoG-816564 ActionContraThreat [to DRB] and Grant No. ERC-2016 CoG-725355 BRAINCODES [to CCR]). DRB receives support from the National Institute for Health Research UCLH Biomedical Research Centre. CCR receives support from the Swiss National Science Foundation (Grant No. 100019L_173248 ).
      DRB, MS, and CCR designed the experiment; SG and CCR provided methodological expertise, training, and access to equipment; SG and MS piloted the experiment; KEO and MS acquired the data; KEO analyzed the data; KEO wrote the original draft of the article; MS, CCR and DRB contributed to the editing and revising of the paper; and DRB supervised work at all stages.
      We thank Marius Moisa, Karl Treiber, Jennifer Hueber, Rosa Bohlender, Athina Tzovara, and Filip Melinščak for assistance.
      A previous version of this article was published as a preprint on bioRxiv: http://doi.org/10.1101/2021.06.09.447685.
      Summary data to reproduce the figures and tables in the article and in Supplement 1 are included in Supplement 2. Original psychophysiological data files are available at https://doi.org/10.5281/zenodo.6377103, and supplementary MRI data are available at https://doi.org/10.5281/zenodo.6373554. Within the limits of data protection laws, individual original MR images are available from the authors upon request for academic purposes. The code for the experiment and the analyses presented in the article are available publicly on GitLab: https://gitlab.com/kojala/tms_somatosensory_fc.
      The authors report no biomedical financial interests or potential conflicts of interest.

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      Linked Article

      • The High Road to Inhibiting Fear Memories
        Biological PsychiatryVol. 92Issue 2
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          In an elegant study in the current issue of Biological Psychiatry, Ojala et al. (1) interrupt the consolidation of an acquired aversive memory via careful stimulation of sensory cortex—an approach that holds promise as a novel avenue of attenuating disruptive memories in clinical populations in the future.
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      • Erratum
        Biological Psychiatry
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          Erratum to: “Inhibiting Human Aversive Memory by Transcranial Theta-Burst Stimulation to the Primary Sensory Cortex”, by Ojala et al. (Biol Psychiatry 2022; 92:149-157); https://doi.org/10.1016/j.biopsych.2022.01.021 .
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