Effect of Lithium Administration on Brain Activity Under an Emotion Regulation Paradigm in Healthy Participants: A Functional Magnetic Resonance Imaging Study

doi:10.21203/rs.3.rs-2246522/v1

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Effect of Lithium Administration on Brain Activity Under an Emotion Regulation Paradigm in Healthy Participants: A Functional Magnetic Resonance Imaging Study

https://doi.org/10.21203/rs.3.rs-2246522/v1

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Rationale:

Emotion Regulation (ER) difficulties have been previously described in bipolar disorder (BD). Whilst lithium has been shown to be effective in the treatment of BD, the mechanisms underlying lithium’s effect on mood stabilisation remain unclear.

Objectives

Unravelling lithium’s effect on psychological processes impaired in BD, such as ER, could address this translational gap and inform the development of new treatments.

Methods

This study investigated the neural effects of lithium on ER in 36 healthy volunteers in a double-blind between-groups design, with randomised administration of lithium or placebo for 11 days. At treatment completion, participants underwent 3- Tesla functional magnetic resonance imaging while performing an ER task. Participants viewed negative images and were instructed to maintain or reappraise the elicited emotions and rate the negative affect experienced.

Results

During reappraisal (versus maintain), lithium increased activity in the right middle temporal gyrus (MTG, Z > 3.1, p < 0.05 corrected) and decreased activation in the left angular gyrus, the left anterior prefrontal cortex (or rostral PFC, BA10) and right superior frontal gyrus (Z > 2.3, p < 0.05 corrected). In addition, greater connectivity was found between the right MTG and left middle frontal gyrus for the lithium group compared to placebo, during reappraisal (versus maintain) (Z > 2.3, p < 0.05 corrected). Further effects of lithium were found in response to negative picture presentation, whereby decreased connectivity was found between the left amygdala and the frontal cortex, and greater connectivity between the right MTG and the bilateral medial prefrontal cortex extending into the paracingulate gyrus, compared to placebo (Z > 2.3, p < 0.05 corrected).

Conclusions

These results show a potential effect of lithium on ER through its effects on activity and connectivity, and further elaborate the neural underpinnings of cognitive reappraisal. Future work should investigate more extended effects of lithium on ER, ultimately benefitting the development of novel and more effective treatments for BD.

Psychiatry

Cognitive Neuroscience

Lithium

Emotional Regulation

task fMRI

emotional processing

Bipolar disorder (BD) is characterised by recurrent episodes of depression and mania/hypomania, affecting not only mood, but motivation, cognition, and behaviour (APA, 2013). Lithium has shown to be effective in reducing the occurrence of such episodes (Licht 2012; Won and Kim 2017) in addition to having anti-suicidal, neurotrophic, and neuroprotective effects, making it the main treatment for BD since its effects were reported 60 years ago (Alda 2015). Recent efforts to understand its neurochemical properties have yielded several pharmacological pathways whereby lithium exerts its mood-stabilising effects including inositol depletion and GSK inhibition. However, the translation of these neurochemical effects to mood-stabilisation remains unclear. Understanding this translational gap is motivated by a desire to further elaborate on the underlying pathogenesis of BD; assist in the prediction of patients’ response to lithium treatment (Licht 2012); and an imperative need to develop novel and more effective treatments for the disorder, given that two out of three patients show a poor response (Hui et al. 2019), or do not respond at all (Won and Kim 2017).

Theoretical models of bipolar disorder propose emotional regulation (ER) difficulties to contribute to its underlying psychopathology. These difficulties are proposed to lead to emotional extremes and mood dysregulation, ultimately giving rise to its characteristic pathological mood states (i.e., mania and/or depression; (Townsend and Altshuler 2012; Johnson et al. 2016; Brady et al. 2016; Li et al. 2019). ER allows the modulation of one’s response to emotional stimuli (Townsend and Altshuler 2012), with the fronto-limbic network implicated in such an effort (Dixon et al. 2017). This network comprises cortical regions including the anterior cingulate cortex (ACC), medial prefrontal cortex (mPFC), ventrolateral prefrontal cortex (vlPFC) and insula; and limbic regions including the amygdala and striatum (Townsend and Altshuler 2012; Zhang et al. 2018b). Evidence from structural and functional neuroimaging studies suggest a disruption in the fronto-limbic network may underly ER difficulties in BD (Benedetti et al. 2011; Strakowski et al. 2012; Radaelli et al. 2015). Structurally, greater amygdala volumes (Phillips et al. 2008; Townsend et al. 2013), grey matter (GM) reductions in cortical areas such as the ACC (Malhi et al. 2013; Won and Kim 2017; Chen et al. 2018; Kato 2019), and disruption of superior white matter (Zhang et al. 2018b) have been described in BD when compared to healthy controls. Functionally, ER difficulties in BD have been studied employing an ER paradigm that uses reappraisal as a strategy to regulate one’s emotions to disturbing stimuli. This strategy, whereby an individual consciously attempts to reinterpret the processed stimulus to reduce its emotional effect, is one of the most common and successful strategies for ER (Buhle et al. 2014). In healthy individuals, reappraisal recruits domain-general cognitive control areas, namely anterior PFC, dlPFC, vlPFC, and the dorsomedial prefrontal cortex (dmPFC); in addition to posterior parietal areas involved in attentional processes (Ochsner et al. 2002; Phan et al. 2005; Buhle et al. 2014). These areas are then hypothesized to either (1) recruit the ventromedial prefrontal cortex (vmPFC) to modulate regions involved in emotional processing, such as the amygdala (Diekhof et al. 2011), or (2) engage lateral temporal regions, associated with language processing, to alter the semantic and perceptual meaning of the stimulus, ultimately changing its emotional significance (Ochsner et al. 2012; Buhle et al. 2014). In BD patients, reappraisal of negative stimuli is characterised by decreased bilateral activation in vlPFC, anterior and posterior cingulate cortex, dlPFC, as well as medial frontal gyrus when compared to healthy controls (Townsend et al. 2013). Additional evidence shows weaker dlPFC-amygdala connectivity, which might reflect failure of prefrontal areas to engage in effective ER (Zhang et al. 2018a, 2020). Overall, authors have linked structural deficits to ER-related functional impairments in BD (Benedetti et al. 2011).

Unravelling lithium’s effect on core psychological processes impaired in BD (i.e., ER) can further elaborate on the mechanisms whereby lithium leads to mood stabilization in the disorder. Here we used an experimental medicine approach with healthy volunteers to explore direct effects of lithium compared to indirect effects on symptomology. The present study therefore assessed brain activity and connectivity during ER in healthy participants administered either lithium or placebo for 10–12 days in a double-blind randomised design. On the assumption that lithium reverses ER difficulties in unmedicated BD patients, it was hypothesised that a stronger activation would be seen in prefrontal regions of the fronto-limbic network in those receiving lithium when asked to reappraise compared to participants on placebo.

Participants

36 healthy participants (18 males, aged 18–31) were recruited through advertising. Following the local ethics committee guidelines (NRES committee South central – Oxford REC B 10/H0605/71), written and oral consent was obtained. Participants had a body mass index of 19–30, were physically fit as assessed by a medical doctor, and had normal laboratory values of thyroid and renal function. Additionally, females tested negative on a pregnancy test and were taking two forms of contraception. Participants were excluded if they took any psychotropic medication, had any past or current Axis 1 psychiatric disorder on DSM-IV, had any medical contra-indication, had current or past history of drug or alcohol dependency, smoked more than 5 cigarettes a day, had dyslexia, had any contra-indication to magnetic resonance imaging (MRI) scanning or were left-handed. A total of 3 participants were further excluded from the experiment and/or analysis due to treatment non-compliance (1x), unexpected adverse effect (1x) and incomplete MRI session (1x), leaving a total of 33 participants for analysis.

Experimental Design And Procedure

The present study followed a double-blind randomised design (as previously reported in Volman et al. 2021). An independent qualified researcher performed the randomisation on a 1:1 ratio for treatment (placebo/lithium) and gender (male/female). Lithium (“Priadel” prolonged release tablet) or placebo were administered orally at night for 11 days (± 1 day) on identical capsules. Lithium dosage was increased on a gradual fashion (day 1:400 mg, day 2:600 mg; days 3–11:800 mg) following previous procedures (Kohno et al. 2007; Monkul et al. 2007).

As previously described in Volman and colleagues (2021), participants visited the lab on three occasions. The initial assessment comprised a medical and psychiatric screening, as well as a blood drawing for testing thyroid stimulating hormone and creatine. Eligible participants were then asked to return for a baseline assessment in which the Beck Depression Inventory (BDI) (Beck et al. 1961), State-Trait Anxiety Inventory (STAI; (Spielberger 1983), Mood Disorder Questionnaire (MDQ; Hirschfeld et al. 2000), National Adult Reading Test (NART) IQ Scale (Nelson and Willison 1982), Eysenck Personality Questionnaire (EPQ; Eysenck and Eysenck 1984) and Emotion Regulation Questionnaire (ERQ; Gross and John 2003) were completed. Females were additionally required to take a pregnancy test at this stage. Upon completion, participants received the full treatment (lithium/placebo), the Befindlichskeit scale (BFS; Pichot & Olivier-Martin, 1974), the Positive and Negative Affect Scale (PANAS; Tran, 2013), the Bond and Lader Visual Analogue Scales (Bond and Lader 1974) and side-effects questionnaires, which had to be filled each day during treatment. Participants were contacted on days three and five to ensure no treatment side-effects and check appropriate compliance of the dosage regimen. Following the last treatment day, participants returned for testing. Blood was drawn to monitor lithium levels and participants underwent a behavioural and MRI session that lasted approximately 120 minutes. In the behavioural session, the BDI, STAI-state and MDQ as well as a battery of tasks (reported elsewhere) were completed. In the MRI session, functional and structural data were acquired while participants completed the ER task, the monetary incentive delay task (Volman et al. 2021), the checkerboard control task (Volman et al., 2021) and an MR spectroscopy scan (not included here).

Tasks

An adaptation of the original ER paradigm (Phan et al. 2005), previously used by Reinecke and colleagues (2015) was employed. In the task, participants were presented with 8 blocks of 5 negatively valanced images in each block (mean valence rating of 2.8 ± 1.7, mean arousal ratings of 6.0 ± 2.2 on 9-point Likert scales from 1 = unpleasant/low arousal to 9 = pleasant/high arousal) to which they were instructed to alternatively maintain (naturally experience the emotional state evoked), or reappraise (downregulate the provoked negative affect) through cognitive reappraisal. Employment of cognitive reappraisal was trained prior to the scan session. Following each block, participants had to rate on a 4-point rating scale (1 = neutral; 4 = negative) the intensity of the negative affect experienced. A more detailed description of the task as well as an illustrative figure can be found in supplementary material (Figure S1 supplementary material). Valence, arousal ratings and scene content matched between conditions and the order of the pictures within each condition remaining constant across all participants. The total duration of the task was of approximately 10 minutes.

A checkerboard control task (CCT: see Volman et al., 2021) was used to control for treatment-related possible cofounders on brain activation.

Mri Acquisition

Bold-oxygenation-level-dependent (BOLD) functional MRI (fMRI) data was acquired on a 3-Tesla MRI scanner (Magnetom, Siemens Medical systems) with a 32-channel head coil. Functional images during the ER task consisted of 45 T2-weighted echoplanar imaging (EPI) slices (TR = 3000ms, TE = 30ms, flip angle = 90°, field of view = 192 mm, voxel size = 3*3*3mm, 200 volumes, acquisition time (TA) = 10 minutes, 6 seconds). Functional images during the CCT consisted of 45 T2-weighted EPI slices (TR = 3000 ms, TE = 30 ms, flip angle = 87°, field of view = 192 mm, voxel size = 3*3*3mm, 120 volumes, TA = 6 minutes, 6 seconds). Additionally, fieldmaps volumes (magnitude and phase difference images) were acquired (echos at 5.19 and 7.65 ms, TR = 488, flip angle = 60°) to capture the inhomogeneities in the magnitude field. Structural scans were acquired via T1-weighted MR images (TR = 2040 ms, TE = 4.7 ms, flip angle = 8°, field of view = 192 mm, voxel size = 1*1*1 isotropic, TA = 5 minutes, 56 seconds).

Analysis Of Fmri Data

Data were analysed using FSL (FMRIB Software Library v6.05; www.fmrib.ox.ac.uk/fsl). Structural anatomical scans were brain extracted using FSL’s Brain Extraction Tool BET (Smith 2002). Fieldmap magnitude images were brain extracted by first registering these to their high-resolution structural images, inversing the created matrix, applying such matrix to the brain extracted structural mask with FMRIB’s Linear Registration Tool (FLIRT) (Jenkinson and Smith 2001; Jenkinson et al. 2002), and applying this mask to the whole brain magnitude image. These were then used to create a fieldmap rads image with the fieldmap phase difference image using the fsl_fieldmap_prepare tool.

Pre-processing of each participant’s functional data was done with FEAT (FMRI Expert Analysis Tool), part of FSL. This included motion correction using MCFLIRT (Jenkinson et al. 2002); spatial smoothing using Gaussian kernel of full width at half maximum (FWHM) 5mm; grand-mean intensity normalisation of the entire 4D dataset by a single multiplicative factor; high-pass temporal filtering of the functional timeseries at 90s; fieldmap distortion correction (Jenkinson 2003, 2004); registration of the functional images to their high-resolution structural images with Boundary-Based Registration (BBR) using FLIRT (Jenkinson and Smith 2001); and registration of the structural images to Montreal Neurological Institute (MNI)-152 standard space using linear registration with 12 degrees of freedom (DOFs), further refined using FNIRT non-linear registration with 10mm resolution (Andersson et al. 2007a, b).

Regarding the ER task, lower-level analysis was carried out to observe within-subject differences in brain activity across the two conditions by including the following contrasts: (1) Maintain vs. Baseline (M > B) to identify brain regions active when asked to naturally experience the emotion elicited; (2) Reappraise vs. Baseline (R > B) to identify brain regions active during voluntary suppression of negative affect using reappraisal techniques; (3) Reappraise vs. Maintain (R > M) to identify brain regions with greater activation when reappraising as compared to maintain; (4) Maintain vs. Reappraise (M > R) to identify brain regions with greater activation while maintaining as compared to reappraise; and (3) overall Picture Blocks vs. Baseline (M + R > B), to identify brain regions activated in response to negative images.

A custom 3-column format convolved with a gamma haemodynamic response function, and its temporal derivative were used to model the data. Time-series statistical analysis was carried out using FILM with local autocorrelation correction (Woolrich et al. 2001). Motion traces detected by MCFLIRT were included in the model as nuisance regressors to account for motion. Differences between groups in absolute and relative motion were tested for using Mann-Whitney non-parametric analysis. Groups did not differ in absolute nor relative motion (all U’s > 94, all p’s > 0.130).

In the higher-level analysis for the ER task, the contrast of parameter estimates (COPEs), their variance (VARCOPEs) and DOFs from the lower-level analysis were introduced into the analysis. Using a mixed-effects analysis with FLAME1 + 2 across the whole-brain, the following contrasts were analysed: (1) Placebo > Lithium (1, -1); (2) Lithium > Placebo (-1, 1); and (3) mean activation and deactivation across both treatment groups (1, 1; -1, -1). Due to lithium’s potential to promote GM changes, GM images of each participant were extracted using FMRIB’s Automated Segmentation tool (FAST; Zhang et al. 2001). These were then registered to standard space, smoothed to match the intrinsic smoothness of the fMRI data (2.63mm), voxel-wise demeaned across all subjects and added to the general linear model (GLM) of the ER task to remove any potential structural differences explaining the BOLD contrast differences. Significant activations were identified using cluster-based thresholding of statistical images with a height threshold of Z > 3.1 and a family wise error (FWE)-corrected cluster significance threshold of p < 0.05. Clusters thesholded at Z > 2.3 p < 0.05 were also reported for completeness and to compare the present results with previous studies using this less stringent statistical threshold (Worsley 2001). See Volman and colleagues (2021) for details on CCT analysis.

Small volume correction (SVC) analysis was performed using several regions of interests (ROIs), namely the bilateral amygdala, due to its implication in emotional processing; and bilateral vmPFC and middle temporal gyrus (MTG), key areas hypothesized to exert ER through cognitive reappraisal. Bilateral amygdala’s anatomical masks were created using the probabilistic map thresholded at 50 provided by the Harvard-Oxford Structural Atlas in FSL. Spherical masks of 10mm radius were created for the right and left vmPFC and MTG using coordinates previously reported (Buhle et al., 2014; right vmPFC: x = 6, y = 40, z=-20; left vmPFC; x=-6, Y = 40, z=-20; right MTG: x = 56, y=-32, z = 0; left MTG: x=-56, y=-32, z = 0). Significant activations were identified using cluster-based thresholding of statistical images with a height threshold of Z > 3.1 and a FWE-corrected cluster significance threshold of p < 0.05.

Connectivity analysis was performed to investigate a seed ROIs’ relationship with other brain areas throughout the task using psychophysiological interactions analysis in FSL (O’Reilly et al. 2012). Previously created masks for the bilateral amygdala were used as above. Bilateral vmPFC and MTG masks were obtained using the Talairach atlas (Talairach et al., 1988). Standard masks were transformed into individual’s standard space, thresholded and binarized. Time-series of each mask were extracted and entered in the lower-level analysis as a regressor to identify voxels where a significant effect is explained by such regressor. Task regressors were added (maintain, reappraise and instructions), in addition to the interaction between the masks’ time-series and the task conditions (maintain x mask time-series and reappraise x mask time-series). Contrast images were introduced in the higher-level analysis to identify brain differences in connectivity across treatment groups. Significant activations were identified using cluster-based thresholding of statistical images with a height threshold of Z > 3.1 and Z > 2.3 and a FWE-corrected cluster significance threshold of p < 0.05. BOLD parameter estimates of significant whole-brain or ROIs interactions were further explored plotted for visual inspection.

Statistical Analysis

Statistical analysis was performed with IBM SPSS 22 Software, with significant levels set at p < 0.05. Between group-differences on the sample’s tendency for ER (ERQ questionnaire) were analysed with an independent samples T-test after testing for normality. Treatment-derived differences on self-reported ratings of negative affect experienced throughout the task were further analysed with a mixed-model ANOVA, within-subject factor condition (maintain vs. reappraise) and between-subject factor treatment (lithium vs. placebo). Post-hoc analysis of the ANOVAs was carried out with pairwise comparisons.

Demographical Characteristics and Questionnaire Measures

Sociodemographic, clinical, and personality characteristics of participants of the final sample (n = 33) can be found in Volman and colleagues (2021). Both groups had higher scores in the ERQ-reappraise, indicating that reappraisal was their usual technique for ER in daily life. As previously reported in Volman et al., (2021) no significant time by treatment interactions were identified in the BDI, STAI-state and MDQ questionnaires. Similarly, no significant group differences in the change in side-effects, visual-analogue scale, PANAS and BFS scores were found.

Lithium Levels

Participants in the lithium group had significantly higher levels of lithium in their serum (reported in Volman et al., 2021). This ensures treatment compliance in this group and was within the optimal serum levels of lithium in BD maintenance treatment (Volkmann et al. 2020).

Affective Ratings

Analysis of the affect ratings showed a significant condition effect (F(1) = 37.629, p < 0.001, ηp2 = 0.565). That is, during maintain blocks (Mean = 2.545, SD = 0.113), negative affect ratings were significantly higher than during reappraisal blocks (Mean = 1.849, SD = 0.112; M-R difference = 0.697) across treatment groups. These results show that participants successfully implemented cognitive reappraisal, reducing the negative affect elicited by negative stimuli. No significant effect of treatment nor treatment by condition interaction arose (all F’s > 1.5, p’s < 0.250).

Fmri

Whole-brain Analysis

Main Effect of Task (Reappraise vs. Maintain, across groups). In order to identify which brain regions were differentially activated between conditions, maintain and reappraise conditions were compared across both groups. Significant brain activations were observed in a network of areas reported previously (Ochsner et al. 2002; Phan et al. 2005; Reinecke et al. 2015). Reappraisal increased activation in bilateral ACC, anterior PFC, supplementary motor cortex, dmPFC, dlPFC, vlPFC, lateral orbitofrontal cortex (OFC), insular cortex, temporoparietal junction, superior and middle temporal gyrus, lateral occipital cortex, occipital cortex, cerebellum, thalamus, pallidum, caudate and left supramarginal gyrus (Table S1 supplementary material; Fig. 1A + B). Together, these findings confirm this task engaged brain regions pertaining to a network implicated in ER.

Group x Task interaction (Reappraise vs. Maintain; Placebo vs. Lithium). A preliminary whole brain analysis at Z > 2.3, p < 0.05 corrected, revealed greater BOLD activation in three separate clusters: the left angular gyrus (AG) extending towards supramarginal gyrus (421 voxels, Zmax = 3.84, MNI x=-46, y=-52, z = 40, p = 0.002); the left anterior PFC (303 voxels, Zmax = 4.45, MNI x=-24, y = 58, z=-8, p = 0.019) and the right superior frontal gyrus (269 voxels, Zmax = 3.89, MNI x = 20, y = 26, z = 60, p = 0.038), in those receiving placebo compared to lithium, when cognitive strategies of reappraisal were implemented compared to passively viewing the pictures (maintain condition; Fig. 1C, D and E). There were no significant differences between the placebo and lithium group any of the other contrasts (maintain greater than baseline, suppress greater than baseline and mean of maintain and suppress = aversive picture blocks greater than baseline).

SVC Analysis

Main effect of task (Z > 3.1, p < 0.05 corrected; Reappraise vs. Maintain; across groups). Across groups, the reappraisal condition increased activity in bilateral amygdala and bilateral MTG (Table S2 supplementary material) compared to maintain. No significant findings in bilateral vmPFC were seen.

Group x Task interaction (Z > 3.1, p < 0.05 corrected; Reappraise vs. Maintain; Lithium vs. Placebo). There was a significant Group x Task interaction in the right MTG (cluster: 19 voxels, MNI x = 52, y=-32, z = 4, Zmax = 4.33, p = 0.0058). That is, participants in the lithium group showed significant increased activation in the right MTG when reappraising relative to maintain, compared to placebo (Table S2 supplementary material). No significant findings in other ROIs arose.

Connectivity Analysis

Main effect of task (Z > 2.3, p < 0.05 corrected; Reappraise vs. Maintain, across groups; Fig. 2). Activity in the right amygdala during reappraisal significantly correlated with deactivation (negative mean maintain and suppress) in the left lateral occipital cortex (cluster: 1821 voxels, MNI x=-24, y=-84, z = 30, Z = 3.75, p < .001), right lateral occipital cortex extending into bilateral intracalcarine cortex and left precuneous cortex (cluster 1455 voxels, MNI x = 40, y=-76, z = 24, Z = 3.99, p < 0.001), right precentral gyrus extending into middle frontal gyrus (Brodmann area (BA) 6 + 9) (cluster: 302 voxels, MNI x = 40, y=-4, z = 46, Z = 3.22, p = 0.0099).

In addition, activity in the left amygdala was significantly correlated with deactivation in the right lateral occipital cortex (cluster: 285 voxels, MNI x = 34, y=-78, z = 28, Zmax = 3.18, p = 0.0213) and left lateral occipital cortex, extending into the occipital pole (cluster: 257 voxels, MNI x=-24, y=-86, z = 34, Zmax = 3.46, p = 0.0389). Activity in the right vmPFC was significantly correlated with deactivation in the left medial PFC to the vmPFC and paracingulate gyrus during reappraisal (cluster: 620 voxels, MNI x=-16, y = 62, z = 12, Z = 3.61, p < .001). Similarly, activity in the left vmPFC significantly correlated with deactivation of the left vmPFC towards the medial PFC and paracingulate gyrus (cluster: 316 voxels, MNI x=-10, y = 58, z = 12, Z = 3.74, p = 0.007) during reappraisal.

Group x Task interaction (Z > 2.3, p < 0.05 corrected; Reappraise vs. Maintain; Lithium vs. Placebo; Fig. 3). There was significantly greater coupling between the right MTG and the left middle frontal gyrus (covering BA 8, 6 and 9) in the lithium group compared to placebo during reappraisal versus maintain (cluster 264 voxels, Zmax = 3.46, MNI x = -36, y = 20, z = 46, p = 0.0213; Fig. 3).

Main effect of group (Z > 2.3, p < 0.05 corrected, Placebo > Lithium, during picture blocks (M + R > B); Fig. 4). Greater connectivity was found between the left amygdala and bilateral frontal cortex for the placebo group compared to the lithium group in response to aversive pictures (cluster 1 (left): 834 voxels, MNI x=-18, y = 30, z = 24, Z = 4.37, p < 0.001; cluster 2 (right): 519 voxels, MNI x = 20, y = 38, z = 0, Z = 4.13, p < 0.001). Additionally, again during negative picture blocks, the lithium group showed greater right MTG and bilateral PFC extending towards paracingulate gyrus connectivity than the placebo group (cluster: 326 voxels, Zmax = 3.58, MNI x=-2, y = 56, z = 10, p = 0.006).

Sensitivity Analyses

Grey matter. Results for the task fMRI analysis remained similar when GM maps were not added into the GLM as a nuisance regressor.

Checkerboard Control Task. As reported in Volman and colleagues (2021), across groups, visual stimulation was associated with a large and highly significant activation cluster in the occipital cortex, among others. However, there were no significant group differences in brain activity during visual stimulation, suggesting that the observed effects during the ER task did not reflect haemodynamic changes due to lithium treatment.

This study is, to the best of the researchers’ knowledge, the first to evaluate the effects of lithium on ER in healthy participants. With this, the present research aimed to understand lithium’s mood-stabilizing properties in BD.

Neural effects of reappraisal, compared to naturally experiencing the negative stimuli, across groups were expectedly seen in frontal, temporal, parietal, and occipital regions, and were associated with lower self-reported negative affect ratings. This evidence therefore confirms participant’s ability to successfully complete the task, which ultimately translates into successful ER. During reappraisal of negative stimuli, compared to maintain, lithium significantly decreased activation in the left AG, left anterior prefrontal cortex (rostralateral PFC) and right superior frontal gyrus, as shown by whole-brain analysis; and significantly increased activation in the right MTG, as shown by SVC analysis. Furthermore, connectivity analysis revealed activity in the right MTG to be significantly more correlated with the left middle frontal gyrus during reappraisal (vs. maintain) in the lithium group compared to placebo. Across negative picture blocks as a whole those receiving placebo displayed a greater coupling between the amygdala and prefrontal cortex. Consistently, there was greater connectivity between the right MTG and medial PFC extending to the paracingulate gyrus across picture blocks in the lithium group compared to placebo. These results, although preliminary, show that lithium may have impacted ER, which could enlighten its underlying mechanisms leading to mood-stabilisation.

Lithium-derived effects on ER

Results from whole-brain analysis showed an effect of lithium on the left AG, left anterior prefrontal cortex and right superior frontal gyrus during reappraisal. The AG can be regarded as a cross-modal integrative hub, and has been linked to multiple functions (Seghier 2013). Previous research in the context of ER has elucidated its implication in cognitive reappraisal through the allocation attentional resources, monitoring the emotional experience (Picó-Pérez et al. 2017), and imagination of scenes that might facilitate ER (Kohn et al. 2014). Similar to the proposed effect of lithium on the left AG, a recent meta-analysis on cognitive reappraisal studies in mood and anxiety disorders has reported a decrease in the AG’s activation during reappraisal in this clinical population (Picó-Pérez et al. 2017). The anterior prefrontal cortex is a high-level integrative area receiving information from somatosensory networks (Peng et al. 2018) and connecting the limbic system with medial prefrontal regions (Gilbert et al. 2006; Mitchell 2011). Contributing to sensory and emotion detection, emotional processing, and regulation strategies (Gilbert et al. 2006; Mitchell 2011; Peng et al. 2018), this region is key in the top-down modulation of the emotional response (Phan et al. 2002; Mitchell 2011). The right superior frontal gyrus has previously shown to be active during tasks involving introspection or self-reflection, where participants were asked to analyse their feelings after being exposed to emotional stimuli (Briggs et al. 2020). Considering this evidence, lithium’s effect on the abovementioned areas could suggest a potential action of the mood-stabilizer in ER. Although hypo-activation in prefrontal areas has generally been observed in BD during emotional processing (Townsend and Altshuler 2012), more recent neurobiological frameworks have suggested that some prefrontal areas may also be hyperactive during emotional regulation, at least in anxiety disorders (Reinecke et al. 2015). This prefrontal hyperactivation might reflect increased utilisation of dysfunctional regulation attempts (Hofmann et al. 2012). Although essential to fully understand the role of lithium in ER, establishing the directionality or valence of these effects might be challenging given the lack of treatment-derived behavioural findings on the ER task, and the healthy volunteer sample in this study.

During reappraisal, as compared to maintain, those in the lithium group showed increased activation in the right MTG, and a significantly greater connectivity between this region and the left middle frontal gyrus. Involvement of the superior and the middle temporal gyrus in emotional downregulation through cognitive reappraisal has previously been reported (Kohn et al. 2014; Buhle et al. 2014; Picó-Pérez et al. 2017; Nguyen et al. 2019). Cognitive control regions engaging medial temporal structures (namely MTG) to alter the semantic meaning and perceptual representation of negative stimuli is thought to mediate emotion downregulation (Buhle et al. 2014). In line with this, posterior areas of the prefrontal cortex, including middle frontal gyrus, are implicated in ER by directing the attention to reappraisal-relevant stimulus features and holding in mind reappraisal goals, as well as the content of one’s appraisal (Ochsner et al. 2012). Additionally, activation in MTG has been reported to affect amygdala’s activity (Kanske et al. 2011; Kohn et al. 2014). Lithium’s effect on the right MTG, and its connectivity with cognitive control regions might be enhancing the MTG’s ability to alter the emotional significance of the presented stimuli, ultimately leading to a heightened capacity to regulate one’s emotions. Further connectivity findings showed correlated activation between the right MTG and bilateral medial PFC, including the paracingulate cortex and the dmPFC, during negative picture stimuli in the lithium group. Both dmPFC and paracingulate areas of the prefrontal cortex have been involved in emotion processing, with the former involved in appraising other’s mental states and traits, and the latter appraising viscero-sensory signals related to subjective emotional feelings (Dixon et al. 2017). Possibly, connectivity between MTG and prefrontal regions could reflect the former making use of information pertaining to the individual and other’s (stimulus related) emotional states to effectively process and/or alter the stimuli’s meaning.

In line with prefrontal connectivity findings, there was a significantly greater connectivity for the placebo group compared to lithium between the left amygdala and bilateral prefrontal regions during negative picture blocks. It has been established that during successful ER a negative correlation between prefrontal and limbic regions is expected (Kanske et al. 2011; Paschke et al. 2016; Sarkheil et al. 2019), with BD patients showing a weaker modulatory effect of prefrontal regions, compared to healthy controls (Zhang et al. 2018a). Moreover, antidepressant treatment (with chronotherapy) in BD increased these regions’ functional connectivity (Vai et al. 2015), which Vai and colleagues (2015) proposed it to be a potential biomarker for treatment efficacy in BD. However, due to the lack of treatment-derived behavioural findings on the ER task and the healthy volunteer sample it is difficult to determine the directionality of our finding. Whether the lithium derived decreased connectivity between the amygdala and bilateral PFC found in this study is beneficial for ER will need to be further investigated.

Task-related Findings And General Implication For Emotional Regulation

Increased activation of prefrontal regions, including bilateral dlPFC, vlPFC, lateral OFC, ACC, and supplementary motor area; temporal, parietal, and occipital regions, as well as subcortical structures was observed during reappraisal of negative stimuli across groups. This task activation is consistent with previous literature investigating ER through reappraisal (Ochsner et al. 2002; Phan et al. 2005; Frank et al. 2014; Buhle et al. 2014; Reinecke et al. 2015; Paschke et al. 2016; Morawetz et al. 2017; Picó-Pérez et al. 2017; Nguyen et al. 2019; Hassa et al. 2021). Behaviourally, reappraisal successfully decreased self-reported negative affect experienced throughout the task, which adds to the existing body of literature on cognitive reappraisal as an effective strategy to downregulate the experience of negative affect (Paschke et al. 2016; Ma et al. 2017; Cao et al. 2020; Yang et al. 2020; Anand et al. 2020).

However, and contrary to previous studies (Ochsner et al. 2002; Phan et al. 2005; Kanske et al. 2011; Frank et al. 2014; Buhle et al. 2014; Picó-Pérez et al. 2017), no decreased activation of limbic structures was observed during reappraisal compared to maintain across groups. SVC analysis of the bilateral amygdala showed increased activation during reappraisal compared to maintain, across groups and hemispheres. With the use of the same task (Reinecke et al. 2015), or similar (Sarkheil et al. 2019; Hassa et al. 2021), Reinecke and colleagues (2015) did not report amygdala deactivation during reappraisal of negative stimuli across their sample, with Sarkeil (2019) and Hassa and colleagues (2021) reporting an overactivation. Post-hoc analysis implemented by Sarkeil (2019) investigated this unexpected effect by dividing the reappraisal period into early and late to observe when the activation was occurring. Results showed that during late periods of reappraisal, amygdala activation was most increased and amygdala-prefrontal connectivity most reduced. Similar to the present study, numerous images were presented consecutively in each block, with reappraisal needing to be implemented with each individual image. The author proposed that this could have increased the cognitive load during the reappraisal block, leading to poor efficacy of frontal regions downregulating amygdala’s activation, ultimately heightening its activation during reappraisal. Given the similarity between the task used in the present study and in Sarkeil’s (2019), this could explain amygdala’s activity during reappraisal. Alternatively, Wager and colleagues’ meta-analysis (2003) found a left lateralization of the amygdala for processing negative emotions. Given the negative nature of the stimuli, it is proposed that prefrontal efforts to downregulate amygdala activity might have been lateralised to the left amygdala, leading to a higher right amygdala activation during reappraisal. Further evidence showed the right amygdala to be negatively correlated with areas of the occipital cortex, including the lateral occipital cortex (bilaterally), and right precentral gyrus towards frontal gyrus (BA6 + 9) during reappraisal across groups. Taken within the hypervigilance model (Hofmann et al. 2012), which proposes that hyperactivation of the amygdala towards threat facilitates visual processing in the occipital cortex, reappraisal of negative stimuli could have decreased the connectivity between the amygdala and occipital regions in an effort to discontinue the feed of visual information to the amygdala. Additionally, a negative connectivity between the right amygdala and right precentral gyrus towards frontal gyrus (BA6 + 9) might reflect the latter motor planning areas (Briggs et al. 2020) planning to remove oneself from the fearful situation, thus decreasing amygdala’s activation. However, reasons behind the lateralisation of this effect to the right amygdala are not clearly understood.

Consistent with previous literature (Ochsner et al. 2012; Buhle et al. 2014), and contrary to others (Diekhof et al. 2011, p. 201), during reappraisal of negative stimuli the vmPFC (bilaterally) was not found to be active neither at whole-brain nor SVC. This was opposite to the MTG, which was shown to be active in both analyses. Additionally, during reappraisal the vmPFC was bilaterally correlated with a deactivation of the left vmPFC towards rostral mPFC. This possibly indicates a null involvement of this region during reappraisal. It has been previously conjectured that given the vmPFC involvement during both maintain and reappraisal, the nature of the contrast (reappraise vs. maintain) might not be specific enough to show its involvement during reappraisal (Buhle et al. 2014). The correlation of the bilateral vmPFC ROI with deactivation in regions mainly including the left vmPFC, however, might indicate that its involvement in reappraisal is potentially absent, or that given its role in self-related emotion generation (Dixon et al. 2017), it might not be involved in reappraisal due to the non-self-related nature of the negative stimuli of the present task. Altogether, this evidence contradicts previous hypothesis assigning the vmPFC a role as the key link between frontal and parietal regions in emotion downregulation (Diekhof et al. 2011), and further supports the hypothesis that reappraisal engages temporal structures (namely MTG) to alter the meaning of the perceived stimuli and therefore downregulate negative emotions (Buhle et al. 2014).

Study’s Strengths, Limitations, And Future Directions

Notably, and to the best of the researchers’ knowledge, this study is the first to evaluate the effects of lithium on ER in healthy participants. This is considered to aid the understanding of the mechanisms behind lithium treatment due to the lack of interactions between treatment and disorder-related factors (i.e., disorder severity, duration, state and/or history of medication).

The lack of treatment-derived differential effects in self-reported negative affect however, limits the establishment of whether lithium’s neural effects were beneficial or detrimental to the overall ER process. Importantly, the absence of treatment-derived self-reported effects does not necessarily imply that differences do not exist, but perhaps that the measurement was not sensitive enough to detect them. Establishing the directionality of these effects is of importance to further understand lithium’s mood-stabilising properties. Additionally, we had a relatively small sample size (n = 33) which may have impacted the statistical power of the study for both type 1 and 2 errors. Despite being able to compare the study findings with previous literature, the lenient statistical significance threshold of Z > 2.3 could have resulted in false positive findings. These findings therefore need to be replicated in larger sample sizes to confirm. Lastly, we used a short treatment administration period, which may have hindered lithium’s potential to impact ER in healthy participants.

Considering the study’s limitations and the potential implications of these results for research in BD treatment, future work should validate the present evidence in a larger sample size, with a longer treatment administration, and including the assessment of physiological measurements (i.e., heart rate and/or arousal) that could inform if the implementation of reappraisal in any group is more successful. Moreover, prospective work should consider the inclusion of a condition involving the downregulation of positive stimuli. Altogether, these future recommendations could broaden the understanding of how lithium achieves mood-stabilisation in BD through ER. Lastly, and of general clinical implication is the AG’s role in ER. Given lithium’s downregulating effect in the left AG during reappraisal and considering similar downregulation patterns observed in clinical populations (Picó-Pérez et al. 2017), further attention should be drawn to the AG’s role in ER and how its downregulation might be related to symptomatology in different mood, including BD, and anxiety disorders.

The present research examined the neural effects of an 11-day lithium administration on ER in healthy participants. Lithium-derived differences in brain activation during reappraisal (vs. maintain) were (1) decreased activation in the left AG, left anterior prefrontal cortex and right superior frontal gyrus; (2) increased activation in the right MTG; and (3) greater correlated activation between the right MTG and the left middle frontal gyrus. During negative picture blocks, lithium-derived differences in brain activity were (1) decreased amygdala-prefrontal connectivity; and (2) enhanced MTG-prefrontal connectivity. These results provide preliminary support for the involvement of lithium in emotional processing and regulation in healthy participants, and potentially benefit future work in the development of more effective treatments for BD.

Of general implications for ER and, specifically for cognitive reappraisal, the present research replicated previous findings. Consistently, enhanced activation in prefrontal, including cognitive control regions, temporal, parietal, and occipital regions was found. Contrary to leading evidence, but in line with a small number of studies, no decreased in amygdala’s activity was found, with the right amygdala observing an increase during reappraisal, compared to maintain. Lastly, the present research shows support for Buhle and colleagues’ (2014) hypothesis implicating temporal structures, as opposed to the vmPFC, in the downregulation of negative stimuli through reappraisal.

Taken together, these results show an effect of lithium in emotional processing and regulation, and further elaborate the neural underpinnings of cognitive reappraisal. Although, limitations should be considering when interpreting these results, a call for future research to investigate more extended effects of lithium on ER is made, which ultimately may benefit the development of novel and more effective treatments for BD.

Acknowledgements/funding

This study was funded by the Medical Research Council (funders ref no: G0801432) and supported by the NIHR Oxford Health Biomedical Research Centre. The views expressed here are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health.

Conﬂict of interest

CJH has received consultancy fees from P1vital Ltd., Janssen Pharmaceuticals, Sage Therapeutics, Pfizer, Zogenix, Compass Pathways, and Lundbeck. CJH holds grant income from Zogenix, UCB Pharma, Pfizer, Janssen Pharmaceuticals.

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Effect of Lithium Administration on Brain Activity Under an Emotion Regulation Paradigm in Healthy Participants: A Functional Magnetic Resonance Imaging Study

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Abstract

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Introduction

Methods

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Experimental Design And Procedure

Tasks

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Analysis Of Fmri Data

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Results

Demographical Characteristics and Questionnaire Measures

Lithium Levels

Affective Ratings

Fmri

Whole-brain Analysis

SVC Analysis

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Lithium-derived effects on ER

Task-related Findings And General Implication For Emotional Regulation

Study’s Strengths, Limitations, And Future Directions

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