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The symptoms of bipolar disorder suggest dysfunction of emotion regulatory networks. In healthy control populations, down-regulation of emotional responses activates the ventral lateral prefrontal cortex (vlPFC) and dampens amygdala activation. This study investigated frontal and limbic function and connectivity during emotion down-regulation in euthymic subjects with bipolar I disorder (BPI) and healthy control subjects.
30 BPI and 26 control subjects underwent fMRI scanning while performing an emotion processing task with passive viewing and emotion down-regulation conditions. Contrasts were made for each group comparing the down-regulation and passive viewing conditions and these were entered into a between-group random effects analysis to assess group differences in activation. Psychophysiological Interaction (PPI) analyses were conducted to test for significant group differences in functional connectivity between the amygdala and inhibitory frontal regions (i.e., vlPFC).
Control subjects showed the expected robust bilateral activation of frontal and limbic regions during passive viewing and emotion down-regulation tasks. Between-group analyses revealed similar activation of BP and control subjects during passive viewing but significantly decreased activation in bilateral vlPFC, bilateral anterior and posterior cingulate, medial frontal gyrus and bilateral dlPFC during emotion down-regulation in subjects with BP. Connectivity analysis demonstrated that control subjects had significantly greater negative functional connectivity between the left amygdala and bilateral vlPFC compared to subjects with BP.
This study provides evidence that dysfunction in the neural networks responsible for emotion regulation, including the prefrontal cortex, cingulate and subcortical structures, are present in BPI subjects even in euthymia.
Emotion processing involves detection and evaluation of salient stimuli as well as regulation of affective response to these stimuli (1). Dysregulated emotional responses can lead to pathological mood states (2, 3). This is exemplified by bipolar disorder, a mood disorder characterized by symptoms of dysregulated emotional states that include mania and depression. This mood instability suggests possible dysfunction of neural networks involved in emotion regulation. Despite the fact that emotion dysregulation is its defining criteria, neural network connectivity remains understudied in bipolar disorder.
The amygdala, insula, anterior cingulate cortex (ACC), medial prefrontal cortex (mPFC) and ventral lateral prefrontal cortex (vlPFC) are considered key neural substrates of an emotion processing and regulation circuit (1). Neuroimaging studies have demonstrated a role for the amygdala and insula in normal emotion processing, and for the medial and lateral regions of the vlPFC in mood regulation (4, 5) and associative emotional memory functions (6, 7). Functional neuroimaging studies involving the simple viewing of emotion stimuli in healthy subjects demonstrate reliable amygdala and vlPFC activation (8-10). Functional MRI (fMRI) studies requiring subjects to modify their emotions by down-regulating their normal emotional responses typically show activation of the vlPFC and other frontal regions and reduced amygdala activation (8-11). The vlPFC plays a role in integrating emotional information and regulating the intensity of emotional responses (12, 13), and regulating emotion through pathways between itself and autonomic systems governing visceral responses associated with affective stimuli (14). VlPFC dysfunction may explain the failure to modulate regions underlying affect, such as the amygdala, and may correlate with the mood shifts characteristic of bipolar disorder.
In cognitive reappraisal, one emotion regulation technique, subjects attempt to consciously reframe the context of disturbing emotional stimuli to reduce (down-regulate) their emotional effect. In behavioral studies, down-regulation of emotion via cognitive reappraisal has been shown to decrease physiological arousal (15-17) and subjective reports of distress (18). Emotion down-regulation studies in healthy subjects demonstrate reliable activation in the vlPFC, pre-SMA and less frequently in the ACC (18-23). These studies demonstrate reduced amygdala activity during cognitive reappraisal, consistent with the vlPFC’s putative role in inhibiting limbic activity. The amygdala has extensive reciprocal connections with the frontal lobe, including direct connections to the medial and vlPFC (24).
Several neuroimaging studies have demonstrated attenuated vlPFC function and /or heightened amygdala activation in manic compared to healthy subjects (25-28). fMRI studies during mania specifically probing emotion processing demonstrate hypoactivation of the vlPFC during processing of negative faces (27), fear perception (29) and negatively captioned pictures (30). Furthermore, hypoactivation of frontal regions, including dlPFC and medial PFC, have been reported during mania (29, 31). Few network connectivity studies have been performed during mania. Reports of decreased negative connectivity between vlPFC and amygdala (32) and between amygdala and anterior cingulate (33) suggest deficient prefrontal modulation over limbic structures during mania.
Most bipolar disorder neuroimaging studies have evaluated subjects during acute mood states. To date, no studies have investigated emotion down-regulation and functional connectivity in subjects with bipolar disorder during euthymia, which could elucidate trait-level dysfunction in key neural circuitry. One recent study demonstrated that euthymic bipolar disorder subjects did not differ in amygdala activation during emotion processing compared to control subjects, but had vlPFC hypoactivation during an emotion labeling condition (34). Persistent dysfunction in prefrontal regions involved in emotion regulation during euthymia might contribute to an abnormal inhibitory vlPFC-amygdala network, and might contribute to the vulnerability of patients with bipolar disorder to shift into acute mood states. The primary aim of this fMRI study was to assess regional activation and functional connectivity between the amygdala and frontal lobe in healthy control and euthymic bipolar I subjects. We hypothesized that during emotion regulation, euthymic bipolar I disorder subjects would show 1.) vlPFC hypoactivation and 2.) reduced functional connectivity in the frontolimbic network (specifically vlPFC-amygdala) compared to healthy subjects.
The study protocol was approved by the institutional review board at the University of California, Los Angeles; each participant gave written consent before initiating the study. Subjects with a DSM-IV diagnosis of bipolar I disorder, currently euthymic, were recruited through the UCLA Outpatient Clinic, local advertising, or other research projects of the UCLA Mood Disorders Research Program. Control subjects were recruited by advertisement. All subjects were interviewed using the Structured Clinical Interview for DSM-IV (SCID) (35) to confirm a bipolar diagnosis or absence thereof. Subjects with bipolar I disorder were excluded if they met criteria for any other current Axis I disorder. Twenty subjects with bipolar I disorder met criteria for past history of substance abuse or dependency, with a minimum of 3 months free from substance abuse (mean=4.2 yrs ± 5.9 yrs). Control subjects were medication-free and excluded for current or past psychiatric diagnoses. Exclusions for all subjects included left-handedness, hypertension, neurological illness, metal implants and history of head trauma with loss of consciousness > 5 minutes.
Mood symptoms were evaluated on the day of the scan using the Young Mania Rating Scale (YMRS) and the 21-item Hamilton Depression Rating Scale (HDRS). Bipolar I disorder subjects were eligible if they had been euthymic by self-report and SCID for > 1 month prior to scanning (YMRS score ≤ 7 and HDRS score ≤ 7).
Subjects underwent fMRI scanning on a 3-Tesla Siemens Allegra. Blood Oxygenation Level Dependent (BOLD) contrast was evaluated using a T2-weighted echo-planar image (EPI) gradient-echo pulse sequence (TR=2500 ms, TE=35 ms, Flip-Angle=90°, Matrix 64×64, FOV=24cm, 28 axial slices, in-plane voxel size 3.75mm × 3.75mm, slice thickness= 3mm, 1mm gap). EPI high-resolution structural images (spin-echo; TR=5000, TE=33 ms, Matrix 128× 128; FOV=24 cm, 28 axial slices, 3 mm thick, 1 mm gap) were obtained co-planar to functional scans.
Subjects performed a validated emotion reactivity and regulation task that required viewing neutral or negative images and either reacting normally or reducing their emotional response through cognitive reappraisal. Images were taken from the IAPS set (36). Images were chosen (negative: 0-3 and neutral 4-5) based on a valence rating (0-8 scale with 0 the most negative). Image types (animal, faces, scene), valence (mean=2.8; ANOVA: F=0.10, df=45,2, p=0.91) and arousal (mean=6.5; ANOVA: F=0.17, df=45,2, p=0.84) ratings were balanced across blocks.
Subjects passively viewed neutral (“Observe Neutral”) or negative (“Observe Negative”) images. For these two blocks, subjects were instructed to attend to and naturally experience the emotional state elicited by the images. During the emotion down-regulation block (“Decrease Emotion”), subjects were instructed to cognitively re-evaluate the image. (Sample instructions: “If you see an image of a snake you might think, ‘That snake isn’t poisonous -- it can’t hurt me”). All subjects were trained to ensure they could perform this cognitive reappraisal in the given time. Finally, to ensure participation and attention, in a final block, subjects selected the word that best described the image using a button box (“Scene Description”), (e.g., with an image of a snake, subjects selected between “venom” and “wreck”). Images were presented for 4 sec., with instructions (3 sec.) beginning each block. Each experimentation block (“Observe Negative,” “Decrease Negative” and “Scene Description”) contained 8 images and was repeated twice (35 sec. per block). Experimental blocks were interleaved with control blocks (“Observe Neutral”), containing 3 neutral images (15 sec. per block). Experimental conditions were counter-balanced across subjects.
To assess group differences in response times and accuracy, performance data from the “Scene Description” condition was analyzed using a mixed effects analysis of variance model (unconstrained covariance matrix) with diagnosis as a grouping variable and task as a repeated measure. Two subjects (1 from each group) were missing behavioral data.
Functional images were examined for severe motion or spike artifacts, and scans with >1.5mm of motion were excluded. fMRI data was processed using FEAT (FMRI Expert Analysis Tool), part of FSL 4.0 (FMRIB’s Software Library, www.fmrib.ox.ac.uk/fsl). Pre-processing steps included: motion correction; non-brain removal using BET (37, 38); spatial smoothing using a 5mm Gaussian kernel; grand-mean intensity normalization; and high-pass temporal filtering (Gaussian-weighted least-squares fitting, sigma=65.0s). Time-series statistical analysis used FMRIB’s Improved Linear Model (FILM) with local autocorrelation correction (38). Registration to standard space was performed with a 2-step transformation of registering subjects’ functional images to their structural image and then to a standard space template.
First, contrasts were made for “Observe Negative vs. Observe Neutral,” as this has been shown to robustly activate amygdalae (22). This contrast enables the comparison of simple passive viewing and emotion reactivity between bipolar and control groups. Next, “Decrease” vs. “Observe Negative” contrasts were created to investigate regions involved in emotion down-regulation. This process has been shown to activate lateral and medial prefrontal cortices, and decreases amygdala activation in healthy subjects (20-23). These outputs were entered into second-level analyses, with subject as a random factor, to determine regions that were significantly different between groups (cluster threshold Z>2.0, p=0.05 corrected).
For task validation, ROI analyses were conducted in the bilateral amygdala, using Pick Atlas structural masks (fMRI Laboratory, Wake Forest University School of Medicine, http://www.fmri.wfubmc.edu). We used structural amygdala ROIs to avoid issues of bias inherent with using functionally-based ROIs in non-independent tasks [(39) for review of this issue]. The time course from each ROI was extracted and used to calculate the mean percent signal change per subject. We fit a 2×2×2 repeated measure ANOVA with group (control and bipolar) as the between-subjects factor and condition (observe and decrease) and hemisphere (left and right) as within-subject factors, along with all possible interactions, to investigate patterns of amygdala activation during these conditions.
To assess functional connectivity, we performed a psychophysiological interaction (PPI) analysis (40) with SPM8 (www.fil.ion.ucl.ac.uk/spm) using the preprocessing steps described above. PPI analyses use regionally specific activation to identify statistical interactions between brain activity and a psychological process (40), reporting differential correlations between regions in one task compared to another. Context-specific changes in functional connectivity are generally interpreted as contributory when the correlation in activity between two regions is either positive or negative (i.e. activity in X suppresses activation in Y). It should be noted that PPI cannot determine the causal direction of connectivity.
Our PPI procedure was adapted from previous studies (32, 41-43). Three time-series were used: 1. The physiological variable represents the time-series activity taken from the “seed” region (L/R amygdala structural ROIs), with the first principal component adjusted for effects of interest (i.e. de-spiked and de-noised). 2. The psychological regressor represents task condition and is used to determine condition-specific changes in functional connectivity between regions. 3. The PPI variable is formed by deconvolving the BOLD physiological time-series to represent the interaction at the neuronal level, computing the element by element product of the first two variables, and reconvolving this time-series to create a regressor for the PPI analysis (44).
To determine which areas reflected this PPI, a general linear model was formed that incorporated these interaction terms. Applying a t-contrast of −1 for the PPI regressor and 0 elsewhere produced statistical images revealing voxels having a significant negative regression slope with activity in the left or right amygdalae during emotion down-regulation vs. passive viewing conditions. Subject-specific PPI statistical images were taken to a second-level random effects analysis to evaluate within- and between- group differences using one- and two-sample t tests, respectively. Given our a priori hypothesis, PPIs between amygdala seed regions and vlPFC were identified (using an uncorrected statistical threshold of p=0.005 and an extent threshold of k=5). For other regions, we used a more conservative threshold (p=0.005, k=20).
Table 1 provides demographic information. 36 subjects with bipolar I disorder and 32 control subjects met inclusion criteria, while data from 6 subjects in each group were excluded due to excessive motion. Thus, the final analysis included 30 euthymic bipolar disorder and 26 control subjects. There were no significant differences between groups in gender (χ2=0.19, p=0.66) or age (T=0.72, p=0.47). Nine (30%) bipolar disorder subjects were medication-free when scanned. The rest were on a range of medications to treat bipolar disorder including anticonvulsants (n=14) (valproic acid, lamotrigine, carbamazepine or oxcarbazepine), antipsychotics (n=13) (aripiprazole, olanzapine, quetiapine, ziprasidone or risperidone) or antidepressants (n=9) (bupropion, trazedone or SSRIs).
Behavioral data analyses revealed no significant differences between bipolar and control groups in accuracy (T=0.63, p=0.53) or reaction time (T=0.57, p=0.57) during the scene description condition, indicating subjects were attentive during the task.
Amygdala ROI results showed a significant main effect of condition (ANOVA: F=5.77, df=1, 54, p=0.02), with a significant decrease in amygdala activation during the “Decrease” vs. “Observe” conditions. There were no other significant main effects of either group (ANOVA: F=1.34, df=1, 54, p=0.25) or hemisphere (ANOVA: F=0.63, df=1, 54, p=0.43), nor were there any significant interactions (all p > 0.44) (Figure 1). In addition, there were no significant correlations between ROI results and any clinical variable.
In our reactivity contrast (“Observe Negative” vs. “Observe Neutral”), bipolar disorder and control subjects extensively activated frontolimbic regions, including bilateral vlPFC (BA44/45 and 47), bilateral insula, medial PFC, anterior cingulate (ACC), and bilateral amygdala (Figure 2). There were no significant differences between bipolar disorder and control subjects (Z>2.0, p=0.05 corrected) in any frontal or limbic regions of interest.
In the emotion down-regulation contrast (“Decrease Negative” - “Observe Negative), control subjects activated frontolimbic regions reported in previous reappraisal studies, including bilateral vlPFC (BA44/45 and 47), insula, dorsomedial PFC (BA8) and ACC (BA32/24). Thus, there was significantly greater activation in the vlPFC during emotion down-regulation than during passive viewing. Additional regions of activation included bilateral insula, bilateral superior frontal gyrus (SFG: BA9/10), bilateral pre-SMA, bilateral hippocampal gyrus (BA28/36), bilateral inferior parietal lobule (IPL: BA40), left middle temporal gyrus (MTG), bilateral superior temporal gyrus (STG), occipital regions (BA17/18/19) and cerebellum (Figure 3A).
Bipolar disorder subjects also activated frontolimbic regions, including left vlPFC (BA45/47), dorsomedial PFC (BA8) and ACC (BA32/24). Other regions of significant activation included bilateral insula, bilateral SFG (BA9/10), left pre-SMA, left MTG (BA20/21) and left cerebellum (Figure 3B).
Between-group analysis revealed significantly greater activation in control compared to bipolar disorder subjects in the frontal lobe, including bilateral vlPFC (BA47/44/45), insula, bilateral MFG (BA 46/9), bilateral cingulate (BA24 and BA23) and pre-SMA (BA6). Other regions of greater activation in the control subjects were seen in the right IPL (BA40), bilateral MTG (BA18), bilateral lingual gyri, bilateral caudate and right thalamus (Figure 4 and Table 2). There were no areas of significantly greater activation in bipolar vs. control subjects. An exploratory analysis of unmedicated bipolar disorder subjects (n=9) showed a similar trend of reduced bilateral vlPFC activation compared to control subjects, but did not reach significance as the sample size was small and underpowered.
In the within-group analysis, control subjects showed significant negative functional connectivity between left amygdala and left vlPFC (BA44/45). Control subjects showed significant negative functional connectivity between right amygdala and right vlPFC (BA44/47), left fusiform gyri (BA18) and left occipital gyrus (BA18/19).
Bipolar disorder subjects showed significant negative functional connectivity between left amygdala and right vlPFC (BA47) as well as significant negative functional connectivity between right amygdala and left vlPFC (BA44).
Between-group analyses using the left amygdala as a seed region revealed significantly greater negative functional connectivity in control > bipolar disorder (BP) in left vlPFC (BA44/45), left occipital gyrus (BA19) and right posterior cingulate (BA23/31) (Figure 5 and Table 3). The BP > control comparison showed no significantly greater negative connectivity between the left amygdala and any regions. For confirmation, we ran additional connectivity analyses using main effect of task to functionally define amygdala seeds; the main results did not change significantly.
Using the right amygdala as a seed region, there were no regions of significantly greater connectivity between control > BP. The BP > control comparison showed significantly greater negative connectivity between right amygdala and right MFG (BA9).
This is the first functional connectivity study exploring neural network functioning during emotion down-regulation in euthymic subjects with bipolar I disorder. During emotion regulation using cognitive reappraisal, which recruits vlPFC, significant group differences emerged. Consistent with our hypothesis, control subjects showed significantly greater engagement of prefrontal structures, including bilateral vlPFC, compared to bipolar disorder subjects. PPI analysis revealed subjects with bipolar disorder had significantly less negative functional connectivity between left amygdala and bilateral vlPFC during down-regulation. These findings support our second hypothesis that during emotion regulation, there are specific neural network frontal-amygdala functional connectivity difference in bipolar disorder.
During passive viewing of emotional images, both groups demonstrated significant bilateral amygdala activation consistent with prior studies (10, 45) of control subjects. No differences in frontolimbic functioning were present between euthymic bipolar and control groups during passive viewing, consistent with some (34, 46), but not all (47), prior studies. Differences in the type of emotional stimuli used (valence and salience) as well as sample size may explain some of these inconsistencies. However, tasks requiring simple emotion reactivity (bottom-up processing, as in passive viewing) consistently show greater amygdala activation than tasks requiring emotion regulation (top-down, as in cognitive reappraisal) (10, 32, 48); we replicate these findings in both groups. Similar amygdala activation between control and bipolar groups suggests no amygdala dysfunction during euthymia at least with these stimuli, while persistent vlPFC hypoactivation in euthymic subjects may suggest a trait abnormality.
Our results are consistent with prior emotion regulation studies demonstrating healthy controls engage frontal regions, including vlPFC and anterior cingulate (32, 49, 50), significantly more during regulation than passive emotion conditions, and down-regulate limbic regions via vlPFC activation (10, 45). During emotion down-regulation, control subjects show increased activation in vlPFC, medial PFC and anterior cingulate (18, 51). These regions have extensive anatomical connectivity to the amygdala (13, 14, 52). Human (53) and non-human (54) primate anatomical studies show reciprocal connections between amygdalae and PFC, and neurochemical studies in animals suggest an inhibitory amygdala-PFC connection (55, 56). Studies of control subjects report significant effective connectivity between amygdala, vlPFC, insula and anterior cingulate (57), and significant negative functional connectivity between amygdala and frontal regions during emotion regulation (10, 32). These latter findings of significant negative connectivity between limbic and frontal regions are consistent with our results of control subjects.
Studies of mania report amygdala hyperactivation (27, 58) and bilateral vlPFC hypoactivation (27, 29, 59). Manic subjects have shown significantly reduced negative functional connectivity between left amygdala, and bilateral vlPFC and anterior cingulate (32), suggesting neural network differences of emotion down-regulation in bipolar disorder subjects during mania. Such results are consistent with the present study and suggest these connectivity differences persist in euthymia. A recent effective connectivity study of euthymic subjects implicated a dysfunctional ventromedial neural system in automatic emotion regulation (60). While amygdala function may vary as a function of mood state (27, 58), vlPFC hypoactivation have been reported in euthymia (29, 61, 62), mania and depression (63, 64). Lesion studies support the vlPFC’s role in emotion regulation, as impairment here is associated with manic and depressive symptoms (65, 66). In the present study, vlPFC hypoactivation in bipolar disorder subjects was more prominent in the left hemisphere, perhaps due to the verbal nature of this cognitive reappraisal paradigm. Most emotion studies in euthymia found hypoactivation of bilateral vlPFC or left vlPFC, depending on paradigm specifics (32, 62, 67). The current functional connectivity results are consistent with another study of bipolar euthymia that reported abnormal frontolimbic connectivity while viewing emotional faces (68). Furthermore, resting state studies support decreased corticolimbic functional connectivity in unmedicated subjects with bipolar disorder (69). A second resting state study found reduced negative functional connectivity specifically in vPFC-amygdala activity between BP vs control groups (70). These studies, using BP subjects in acute and euthymic mood states, are consistent with the present study’s results in BP euthymia. Thus, vlPFC hypoactivation may represent a trait neural marker of bipolar disorder that endures across mood states (71).
Neuropsychological studies suggest bipolar disorder patients continue to display mood instability and increased mood reactivity in the absence of an acute episode (72, 73). Chronic vlPFC hypoactivation and/or reduced modulatory control of limbic structures may explain these findings. The vlPFC may act as a brake on extreme emotion through its inhibitory connections with limbic structures. It is possible that abnormal PFC function and the resultant fronto-limbic circuit alterations may create dysregulation of emotional reactions and increase the vulnerability of patients to lapse into mood episodes [(74) for review].
Although our hypothesis focused on amygdala and vlPFC activation, other areas showed significant group differences. Control subjects showed significantly increased activation in bilateral insula and bilateral anterior cingulate and increased negative connectivity between left amygdala and posterior cingulate compared to bipolar disorder subjects. The anterior insula is part of the salience-emotion network (75) and is integral in introspection (76). Extensive reciprocal connections exist between the insula and amygdala (77), and decreased amygdala-insula connectivity in bipolar euthymia suggests another emotion network difference that may contribute to the presentation of bipolar disorder. The ACC, particularly the rostral portion that shows hypoactivation in bipolar disorder subjects during down regulation, is also part of the emotional salience network and has extensive frontal and limbic connections (78). The posterior cingulate is important for internal awareness, processing spontaneous thought and is part of the default mode network (79), engaged in the absence of task-specific challenges and suppressed during task demands (80). In primates, the posterior cingulate receives direct efferent connections from the amygdala (81). The amygdala and posterior cingulate may be part of two functionally-distinct networks that are “on” and “off” at different times (i.e., have significant anti-correlations) (82). The decreased negative (or equivalently, increased positive) connectivity between these regions in bipolar disorder suggests less functional segregation between networks, findings reported in other psychiatric populations (83, 84). We are currently conducting studies investigating these networks in bipolar disorder.
While this is the first study of emotion regulation in euthymic subjects with bipolar I disorder and has the largest sample size of a functional connectivity study in this population, this study has several limitations. First, while ~30% bipolar disorder subjects were unmedicated, this sample remained underpowered to provide meaningful sub-analyses into medication effects on frontolimbic functioning. However, an exploratory analysis suggested similar patterns of vlPFC hypoactivation in unmedicated and medicated subjects. Also, as bipolar and control groups showed similar activation of many structures (e.g., amygdala) during passive emotion reactivity, it is doubtful that medication per se caused selective vlPFC hypoactivation during emotion regulation in the bipolar group. A review study (85) found medication either had no significant or ameliorative effects on abnormal functional neuroimaging results, suggesting medication alone likely does not explain the current findings. Second, this study utilized a paradigm previously used in healthy controls, but in subjects with bipolar disorder. As such, these results require replication. Future studies may determine whether amygdala differences emerge between bipolar and control subjects as demands for emotion regulation increase beyond the relatively simple condition used in this study. Finally, as subjective ratings were not collected at the time of scanning, we were unable to make direct conclusions regarding neural responses and subjective affective experiences. However, we spent considerable time training subjects to complete cognitive reappraisal of images during the timeframe. Future studies that collect subjective and physiological measures simultaneously during fMRI can provide a more complete picture of the success of emotion regulation strategies used in bipolar disorder and control subjects.
This study provides evidence of decreased vlPFC activation, decreased vlPFC-amygdala connectivity, and amygdala-posterior cingulate abnormalities, during emotion down-regulation in bipolar I disorder. vlPFC hypoactivation in bipolar I disorder is consistent with several studies in this population and suggests that these abnormalities persist in the absence of acute mood episodes. Reduced frontolimbic connectivity in euthymia may underlie the decreased ability of bipolar disorder subjects to regulate emotions and the proclivity to relapse into acute mood states. vlPFC inhibitory inputs to the amygdalae may be abnormal in bipolar disorder due to local alterations (e.g., neuronal) and/or disrupted connections (e.g., white matter tracts) between regions. Follow-up studies tracking subjects longitudinally across mood states may help determine whether the degree of vlPFC hypoactivation and decreased frontolimbic connectivity can help predict future mood episodes.
For their financial support of this study, the authors gratefully acknowledge the Furlotti Family Foundation, the Swift Family Foundation and the following two components of the National Institutes of Health (NIH): the National Institute of Mental Health [R01 MH084955 (LLA), K24 MH001848 (LA), R21 MH075944 (LA)] and the National Center for Research Resources (NCRR) (RR012169, RR013642 and RR00865). Contents of this report are solely the responsibility of the authors and do not necessarily represent the official views of any sponsoring organization. For generous support the authors also wish to thank the Brain Mapping Medical Research Organization, Brain Mapping Support Foundation, Pierson-Lovelace Foundation, The Ahmanson Foundation, William M. and Linda R. Dietel Philanthropic Fund at the Northern Piedmont Community Foundation, Tamkin Foundation, Jennifer Jones-Simon Foundation, Capital Group Companies Charitable Foundation, Robson Family and Northstar Fund. The sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript. Dr. Altshuler, Dr. Bookheimer, Dr. Lieberman, Mr. Torrisi, Dr. Sugar and Ms. Townsend had full access to all study data and take responsibility for its integrity and the accuracy of data analysis.
Dr. Altshuler has received past (and potential future) funding from Abbott Laboratories (research support and consulting honoraria); Forest Laboratories (consulting and speakers bureau honoraria); GlaxoSmithKline (speakers bureau honoraria); and no past, but potential future honoraria from Astra-Zeneca (speakers bureau) and Merck and Co. (consulting). Ms. Townsend, Mr. Torrisi, Dr. Lieberman, Dr. Sugar and Dr. Bookheimer report no biomedical financial interests or potential conflicts of interest.
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