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Original Investigation |

Behavioral and Neurophysiological Correlates of Autobiographical Memory Deficits in Patients With Depression and Individuals at High Risk for Depression FREE

Kymberly D. Young, PhD1; Patrick S. F. Bellgowan, PhD1,2; Jerzy Bodurka, PhD1,4; Wayne C. Drevets, MD1,3,5
[+] Author Affiliations
1Laureate Institute for Brain Research, Tulsa, Oklahoma
2School of Community Medicine, The University of Tulsa, Tulsa, Oklahoma
3Department of Psychiatry, The University of Oklahoma College of Medicine, Tulsa
4College of Engineering, The University of Oklahoma, Norman
5Janssen Pharmaceuticals LLC, Johnson & Johnson Inc, Titusville, New Jersey
JAMA Psychiatry. 2013;70(7):698-708. doi:10.1001/jamapsychiatry.2013.1189.
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Published online

Importance  Individuals with major depressive disorder (MDD) compared with healthy control subjects (HCs) consistently recall fewer specific and more categorical autobiographical memories (AMs). This effect is most pronounced for positive AMs and persists into remission.

Objectives  To determine whether individuals at high familial risk for developing MDD (HR group) also show an AM overgenerality bias and to use functional magnetic resonance imaging to assess differences in functional correlates of AM recall across HR, currently depressed MDD, and HC groups.

Design  While recalling AMs in response to emotionally valenced cue words, study participants underwent functional magnetic resonance imaging. Control tasks involved generating examples from a given category and counting the number of risers in a letter string.

Setting  Testing was conducted at the Laureate Institute for Brain Research, Tulsa, Oklahoma.

Participants  Participants included 16 unmedicated patients with MDD, 16 HR participants, and 16 HCs.

Main Outcomes and Measures  Percentage of specific and categorical AMs recalled and brain regions in which hemodynamic activity changed during specific and positive AM recall compared with example generation.

Results  Both the MDD and HR groups generated fewer specific, more categorical, and fewer positive AMs than the HC group (P ≤ .02 for all). During specific AM recall compared with example generation, neuroimaging results showed between-group differences in the left cuneus (Talairach space coordinates x, y, z = −7, −71, 18; F = 7.55), right medial frontal cortex (x, y, z = 7, 59, 12; F = 8.53), right frontal operculum (x, y, z = 23, 23, 12; F = 8.25), and right and left pregenual anterior cingulate cortex (x, y, z = 9, 37, 10 and x, y, z = −3, 43, 6; F = 6.84 and F = 7.13, respectively).

Conclusions and Relevance  Autobiographic memory deficits exist in HR individuals, suggesting that these impairments constitute traitlike abnormalities in MDD. We also found distinct patterns of hemodynamic activity for each group as they recalled specific AMs. Specifically, the HR and MDD groups showed differential hemodynamic activity from HCs in medial prefrontal and occipital regions, suggesting that these groups may use different self-referential focus during successful retrieval of specific memories.

Figures in this Article

The tendency of individuals with major depressive disorder (MDD) to recall fewer specific and more categorical autobiographical memories (AMs) compared with healthy control subjects (HCs) is a consistently replicated finding.1,2 Despite remission of depressive symptoms,35 this abnormality persists and seems unrelated to symptom severity,6,7 suggesting that a pathogenetic construct beyond disturbed mood underlies overgeneral AM in MDD. These data further suggest the hypothesis that this deficit reflects a trait marker of depression. Moreover, overgeneral AM may have an antecedent, facilitatory role in the development of MDD. Researchers have shown that an overgeneral AM response style coupled with a major environmental stressor increases the likelihood of depressive symptoms at follow-up assessment.79 In addition, studies focusing on adolescents have found AM overgenerality in adolescents deemed at risk for developing MDD by virtue of high neuroticism scores or a history of MDD10 and noted that overgeneral AM at age 11 years predicted depressive symptoms at age 12 years in girls.11 These studies either assessed populations already experiencing significant pathologic conditions or those who are healthy. To date, no study has examined whether individuals with a hereditary risk for depression might also demonstrate overgeneral AM retrieval. Therefore, one objective of the present study was to determine whether healthy participants at high familial risk for developing MDD (HR group) based on having a first-degree family relative with MDD also show an AM overgenerality bias.

A second objective of the present study was to examine whether the functional correlates of AM recall would differ across participants drawn from HR, MDD, and HC samples. Delineating the functional correlates of AM deficits in HR and MDD samples holds the potential to identify an endophenotype of MDD.

A substantial amount of research has examined depressive deficits and biases during memory encoding. For example, MDD samples compared with HC samples show increased amygdala activity during encoding of negative pictures12 and words,13 as well as increased anterior cingulate cortex (ACC) and decreased hippocampal activity when encoding positive words.13 Furthermore, increased prefrontal and medial temporal activity is evident during encoding of positive words in individuals with remitted MDD,14 while increased hemodynamic activity within the ventrolateral prefrontal cortex, hippocampus, and amygdala is evident during encoding of both positive and negative stimuli in individuals at risk for developing MDD.15 These results indicate that individuals with MDD show altered activity in the network recruited for encoding affective stimuli and that this abnormality persists into remission and extends to individuals at risk for developing MDD.

Although neurobiological differences during encoding suggest differences during recall, no study to date has used functional magnetic resonance (fMR) imaging to examine AM recall in HR populations, and only 3 studies1618 have used fMR imaging to examine AM in MDD. Two studies16,17 used a recognition paradigm in which participants were shown AM prompts based on preimaging interviews. These studies found that activity within the ventrolateral prefrontal cortex decreased in MDD vs HC samples during negative AM recognition16,17 and that activity within the ventrolateral prefrontal cortex increased in MDD vs HC samples during positive recognition. Those results should be interpreted with caution because a recognition paradigm may change the properties of the memories.19,20 To date, only one study18 has used neuroimaging to examine AM recall in MDD and found decreased activity in the ACC, hippocampus, anterior insula, and parahippocampal gyrus in MDD vs HC samples as they engaged in AM recall.

We aimed to assess differences in hemodynamic correlates of AM recall across HR, currently depressed MDD, and HC samples. We predicted that the HR sample would behaviorally show the same pattern of AM deficits as the MDD sample (fewer specific and more categorical AMs), while the HR sample and the MDD sample would neurophysiologically show decreased hemodynamic activity in temporal and prefrontal components of the AM network compared with HCs.

Participants

Medically healthy, right-handed individuals aged 18 to 55 years were evaluated for their eligibility to be included in 1 of the following 3 groups: psychiatrically HCs, psychiatrically healthy participants having a first-degree relative with MDD, and unmedicated individuals with MDD in a current major depressive episode according to the DSM-IV-TR.21 Recruitment continued until each group had 16 participants who underwent imaging and satisfied exclusion criteria for movement during imaging (described in detail in the next subsection). The total sample sizes entered to reach this recruitment goal were 18 MDD, 17 HC, and 17 HR. Volunteers, recruited from the community via advertisements, underwent medical and psychiatric screening evaluations at the Laureate Institute for Brain Research, which included the Structural Clinical Interview for DSM-IV-TR Axis I Disorders.22 Family history was established via the Family Interview for Genetic Studies.23

Exclusion criteria included psychosis, current pregnancy, serious suicidal ideation, general MR imaging exclusions, major medical or neurological disorders, and exposure to any medication likely to influence cerebral function or blood flow within 3 weeks, as well as meeting DSM-IV criteria for drug or alcohol abuse within the previous year or for alcohol or drug dependence (except nicotine) within the lifetime. Additional exclusion criteria applied to the HC and HR groups were current or past Axis I psychiatric conditions and a history of psychotropic medication use. After receiving a complete explanation of the study procedures, all participants provided written informed consent as approved by the Western Institutional Review Board. Participants received financial compensation for their participation. Participant data were dropped from analysis if absolute movement during fMR imaging exceeded 3 mm in any direction.

Intelligence testing was performed using the 2-subtest version of the Wechsler Abbreviated Scale of Intelligence.24 Anxiety and depressive symptoms were rated on imaging day using the State-Trait Anxiety Inventory,25 the 21-item Hamilton Scale for Depression,26 the Montgomery-Åsberg Depression Rating Scale,27 the Snaith-Hamilton Pleasure Scale,28 and the Profile of Mood States.29

Image Acquisition

Functional MR imaging was performed using a 3-T MR imaging system (GE 750; GE Healthcare) and an 8-channel receiver coil array. Gradient-recalled echoplanar imaging with sensitivity (SENSE) was used for fMR imaging with the following parameters: 40 × 3-mm sections acquired axially; repetition time, 2000 milliseconds; echo time, 25 milliseconds; SENSE acceleration, 2; flip angle, 90°; 96 × 96-pixel matrix; field of view, 24 cm; and voxel size, 3 × 2.5 × 2.5 mm3. A total of 211 echoplanar images were acquired in each of ten 7-minute runs during the AM task. The first 4 images of each run were discarded to allow for steady-state tissue magnetization. Also acquired for coregistration with the echoplanar imaging series were high-resolution T1-weighted anatomical MR images with the following parameters: 120 × 1.2-mm sections acquired axially; repetition time, 5 milliseconds; echo time, 1.93 milliseconds; flip angle, 8°; 256 × 256-pixel matrix; field of view, 24 cm; and in-plane resolution, 0.94 mm2.

AM Task

Before imaging, participants were instructed as to the different types of AMs that they might retrieve (according to conventional definitions used in the literature)2,30,31 and were informed that their goal was to recall a specific AM, defined as a memory for an event that occurred at an identified place and lasted up to 1 day. A categorical memory referred to a category of events containing several episodes without reference to one specific event (eg, all examinations failed without reference to one particular examination). An extended memory referred to an extended period without reference to a specific event within the time frame (eg, a weeklong vacation). A semantic memory was defined as a statement of fact without an associated event (eg, “I’ve never been dancing.”). Participants were provided these definitions and examples verbally before entering the imaging system and immediately before the start of each fMR imaging run.

A computerized version of the AM task32 was developed for use during fMR imaging. Using available software (E-Prime; Psychology Software Tools Inc), participants were presented with 60 words, including 20 positive (eg, success), 20 negative (eg, danger), and 20 neutral (eg, journal).33 During fMR imaging, participants were presented with a cue word for 12 seconds and were instructed to recall a past experience. Following the cue, participants rated the retrieved memory on the specificity (specific, categorical, extended, semantic, repeat, or no memory) and the valence (negative, somewhat negative, neutral, somewhat positive, positive, or no memory). Participants had 10 seconds to assign each rating by scrolling to the relevant option and making their selection using a scroll wheel (Current Designs Inc).

The AM recall condition was compared with a semantic example generation condition to control for abstract or general knowledge retrieval.34 Participants were presented with an example generation cue word for 12 seconds and were instructed to think of at least 7 examples from the presented category. Selected from the same word pool as the memory cue words, 10 positive categories (eg, flowers), 10 negative categories (eg, villains), and 10 neutral categories (eg, instruments) were presented. Following an example generation cue word, participants rated the ease with which they were able to generate examples (very easy, easy, somewhat easy, somewhat difficult, difficult, or very difficult) and the number of examples they generated (0, 1-2, 3-4, 5-6, 7, or ≥8). Participants had 10 seconds to select each rating.

Following the presentation of each cue and each set of ratings, participants engaged in a riser detection task as a control for visual input and attention. All example generation and memory cue words were scrambled into lowercase nonword letter strings, and participants were instructed to count the number of risers in the string, defined as a letter with a part rising above the tops of the other letters (eg, “gulmnh” has the risers l and h). The presentation of each letter string was jittered with a mean presentation time of 6 seconds. For a randomly selected one-half of these strings, a 2-second period followed during which participants selected whether the number of risers in the previous string was even or odd.

The order of memory and example cue word presentations was pseudorandomized, with restrictions on order presentation to prevent sequential presentations of a particular valence. Within each of 10 runs, participants were presented with 6 memory cue words, 3 example generation cue words, and 18 riser letter strings in the following order: cue word, riser (one-half, followed by even or odd question), ratings, and riser (one-half, followed by even or odd question). Two computers time-linked to the image acquisition of the MR imaging system controlled stimulus presentation and behavioral response collection. Participants observed the stimuli using a mirror system attached to the head coil.

Following the imaging, the experimenter (K.D.Y.) presented participants with all the AM cue words again in the same order as during imaging. Participants were asked to describe the memory for the experimenter to corroborate participants’ specificity ratings. The experimenter was blind to diagnosis at the time of rating. In addition to the definitions provided, a memory was categorized as “can’t recall” if the participant was unable to recall the memory retrieved during fMR imaging or the memory provided did not match the participant’s specificity rating (indicating that he or she had not reported the same memory as during the imaging). Participants also rated each memory on the following 3 additional properties: arousal (5-point scale ranging from very low to very high), vividness (5-point scale ranging from not at all vivid to perfectly clear and vivid), and age when the memory occurred (childhood, adolescence, >18 years but >1 year before imaging, 6 months to >1 year before imaging, or within 6 months).

Assessment of Behavioral Performance

Behavioral data were analyzed using available software (SYSTAT 13; Systat Software Inc). Potential group differences in age, IQ, symptom ratings, performance on the riser detection and example generation control tasks, and percentage of memories recalled at each specificity level (specific, categorical, extended, semantic, repeat, no memory, and can’t recall after imaging) were assessed using a 1-way analysis of variance (ANOVA) (entering diagnosis as the independent variable and mood, demographic, and specificity variables as the dependent variables), as well as follow-up independent t tests.

Our a priori hypothesis was that HR participants would exhibit the same AM defects as previously reported in individuals with MDD using a similar paradigm.18 We expected that both the HR and MDD groups compared with HCs would have fewer positive AMs, fewer highly arousing AMs, fewer specific and more categorical AMs, and fewer AMs from the most recent period examined. A priori hypothesis testing focused on the properties of the specific and categorical memories because too few exemplars of other types of AMs were retrieved to allow sufficient power to detect group differences. To increase power, the following variables were collapsed: somewhat positive and positive were considered together to create a positive variable, somewhat negative and negative were considered together to create a negative variable, low and very low (arousal and vividness) were considered together to generate low arousal and vividness variables, and high and very high (arousal and vividness) were considered together to generate high arousal and vividness variables,

Four repeated-measures ANOVAs were performed to examine group differences in the properties of the recalled AMs. In each case, the between-group variable was diagnosis, and the repeated measure was type (specific or categorical). The other repeated measure entered for each ANOVA was arousal (low, medium, or high), vividness (low, medium, or high), valence (positive, negative, or neutral), or age when the memory occurred (childhood, adolescence, >18 years but >1 year before imaging, 6 months to >1 year before imaging, or within 6 months) for the dependent variable percentage of memories recalled. Follow-up independent samples t tests were conducted for significant results within the ANOVAs. The threshold criterion for significance was set at P < .05, and post hoc tests were corrected for multiple comparisons (Bonferroni).

Because participants underwent 90 minutes of fMR imaging, we performed additional behavioral analyses that ruled out fatigue as a significant factor contributing to the observed results. Further details are given in the eMethods in Supplement.

Image Processing and Analysis

Image preprocessing and analysis were performed using available software (AFNI; http://afni.nimh.nih.gov/afni) and consisted of within-group realignment, section acquisition time correction, coregistration between anatomical and functional images, spatial normalization to the stereotaxic array by Talairach and Tournoux,35 and smoothing using a 4-mm full-width at half maximum gaussian kernel. Using AFNI 3dDeconvolve for each participant, the evoked hemodynamic response to each event type was modeled as a boxcar function convolved with a synthetic hemodynamic response function. Regressors modeling task and motion parameters were used in the model. The main effects of interest were cue word presentations that prompted specific AM recall and example generation. In addition to regressors modeling main effects, each design matrix included regressors modeling rating selection, even or odd riser question presentations, cue presentation in which nonspecific memories were recalled, and cue presentation in which the retrieved memory was not recalled. The nonword letter strings used as stimuli for the riser detection task were modeled as the baseline.

At the group level, AFNI 3dANOVA was used to identify regional differences in the blood oxygen level–dependent (BOLD) signal between groups for specific memories vs example generation and example generation vs riser baseline. Because the only behavioral difference found between groups was for the valence model, additional contrasts of positive memories (specific and categorical) vs positive example generation and negative memories (specific and categorical) vs negative example generation also were performed. An additional test was performed to compare the BOLD response for each contrast for all 3 groups combined. Because the mean number of neutral memories recalled was fewer than 10 and because the number of categorical AMs recalled by HCs was low, we lacked statistical sensitivity to justify group comparisons involving these parameters. The significance criterion for detecting differences was set at corrected P < .05, determined using AFNI 3dClustSim (cluster size >30 voxels, thresholded at voxel P < .005). A final analysis indicated that neither the temporal signal to noise ratio nor motion statistics differed between groups (eMethods in Supplement).

Behavioral Findings

Table 1 gives the demographic and clinical characteristics for each group (eTable 4 in Supplement summarizes additional clinical characteristics of the individuals with MDD). A 1-way ANOVA with diagnosis as the independent variable showed no significant difference across groups in age or IQ (F2,45 < 1.92, P > .20 for all) but differed in the mean results on the Profile of Mood States, State-Trait Anxiety Inventory, Hamilton Scale for Depression, Snaith-Hamilton Pleasure Scale, and Montgomery-Åsberg Depression Rating Scale (F2,45 > 19.5, P < .001 for all). The MDD group had higher scores on all ratings compared with the HC group (t30 > 5.04, P < .001 for all) and the HR group (t30 > 4.50, P < .001 for all), while the HC group and the HR group did not differ on any rating (t30 < 1.06, P > .60 for all).

Table Graphic Jump LocationTable 1.  Participant Characteristics by Diagnostic Group1

The groups did not differ in performance on the riser baseline task, the ratings of ease at generating the examples, or the number of examples generated for the differently valenced categories on the example generation task (F2,45 < 2.27, P > .11 for all). These results are summarized in Table 1.

The percentage of memories recalled for each memory type (Table 1) were assessed using ANOVA with the independent variable diagnosis. The groups differed in the percentage of memories coded as specific (F2,45 = 11.1) and categorical (F2,45 = 16.2) (P < .001 for both). The HC group had more specific and fewer categorical AMs than both the HR group and the MDD group (t30 > 3.75, P < .001 for all), while the HR group and the MDD group did not differ significantly from each other (t30 < 1.59, P > .24 for all). The groups did not differ significantly in the percentage of memories coded as extended, semantic, no memory, or unable to recall after imaging (F2,45 < 1.30, P > .28 for all).

We examined the properties of the specific and categorical memories by performing repeated-measures ANOVAs with the between-group factor of diagnosis and the repeated measures of type (specific or categorical) and either valence, arousal, vividness, or age when the memory occurred. Table 2 gives the percentage of memories recalled, separated by these properties.

Table Graphic Jump LocationTable 2.  Properties of Specific and Categorical AMs by Diagnostic Group1

The valence × diagnosis interaction was significant (F2,44 = 3.23, P < .02). Follow-up t tests revealed that the HC group had more positive memories than both the HR group and the MDD group (t30 > 2.91, P < .02 for all), while the HR group and the MDD group did not differ from each other (t30 < 1.83, P > .23 for all). The interaction with diagnosis was nonsignificant for arousal and for vividness (F2,44 < 0.65, P > .63 for all), indicating that the groups did not differ on these ratings. The diagnosis × memory age × type interaction was significant (F8,42 = 5.67, P = .002). Follow-up t tests revealed that the MDD group had fewer specific AMs from the most recent 6 months compared with the HC group and the HR group (t30 > 2.58, P < .05 for all), whereas the HR group and the HC group did not differ from each other on this parameter (t30 = 1.03, P = .99).

fMR Imaging Findings

eTable 5 in Supplement lists regions where BOLD activity increased across the entire sample (all groups combined), and Table 3 summarizes group differences in regional BOLD activity. Comparing example generation with riser baseline in the entire sample, BOLD activity increased in the caudate, precentral gyrus, parahippocampus, orbitofrontal cortex, inferior temporal gyrus, left posterior cingulate cortex, and right dorsolateral prefrontal cortex. No significant group difference in regional BOLD activity was identified for this contrast, suggesting that performance on the control tasks was similar across groups.

Table Graphic Jump LocationTable 3.  Regions Where Hemodynamic Activity Differed Significantly Across the Diagnostic Groups for the Different Contrasts Performed

Comparing specific AM recall with example generation in the entire sample, BOLD activity increased in the ACC, amygdala, hippocampus, left precuneus, parahippocampus, temporoparietal cortex, medial prefrontal cortex, bilateral middle temporal gyrus, bilateral postcentral gyrus and cerebellum, and left ventrolateral prefrontal cortex and dorsolateral prefrontal cortex. BOLD activity differed across groups on this contrast (ie, the diagnosis × specific AM recall × example generation interaction was significant [Figure]), such that the mean BOLD response was higher in the MDD group than in the HC group and the HR group in the right medial frontal gyrus and bilateral pregenual ACC. The BOLD response was higher in the HR group than in the MDD group and HC group in the left cuneus (Brodmann area [BA] 17). Finally, in the right frontal operculum (intrasulcal lateral orbitofrontal cortex [BA 47s]36), the BOLD activity decreased in the HR group, did not change significantly in the HC group, and increased in the MDD group.

Place holder to copy figure label and caption
Figure.
Hemodynamic Activity During Autobiographical Memory (AM) Recall Group Differences in AM and Regions Where Groups Had Differential Activation During Specific AM Recall vs Example Generation (Corrected P < .05)

Using the significant clusters in Table 3 as regions of interest, β weights were extracted for specific AMs vs riser baseline and example generation vs riser baseline. ACC indicates anterior cingulate cortex; BA, Brodmann area; HC, healthy control subjects; HR, individuals at high familial risk for developing MDD; L, left; MDD, major depressive disorder; and R, right.

Graphic Jump Location

In the entire sample, positive AM recall vs positive example generation was associated with increased BOLD activity in the left precuneus, right parahippocampus and orbitofrontal cortex, and bilateral temporoparietal cortex, caudate, and cerebellum. During recall of negative AMs vs negative example generation, the combined sample also showed increased BOLD activity in the right orbitofrontal cortex, occipital cortex and cerebellum, parahippocampus and precuneus, left dorsolateral prefrontal cortex, and bilateral amygdala, temporoparietal cortex, and caudate. During positive AM recall, BOLD activity increased in the right middle temporal gyrus of the HR group but decreased in the MDD group and the HC group. No significant group difference was identified in BOLD response during negative AM recall vs negative example generation.

We replicated previous behavioral findings of fewer specific and more categorical AMs in MDD1 and for the first time to date demonstrate that these deficits exist in individuals at risk for developing MDD. Despite the similarity in depression, anxiety, and anhedonia ratings between the HR group and HC group, HR participants showed the same pattern of AM deficits seen in the MDD group. We also observed fewer overall positive AMs in both the HR participants and the MDD group vs the HC group, as well as differential hemodynamic response in regions recruited during recall of positive AMs in HR participants vs the HC group. In contrast, these groups showed no significant difference in BOLD activity during recall of negative AMs. These data support the hypothesis that MDD is associated with impaired recall of positive information rather than a diathesis toward recalling negative information.37 The extension of this finding to HR participants further supports the role of alterations in positive processing in the underlying pathology of MDD.

We also replicated previous findings that individuals with MDD had fewer specific AMs from the most recent 6-month epoch compared with HCs.18 In contrast, HR participants generated significantly more memories from this epoch than the individuals with MDD and did not differ significantly from HCs. It remains unclear whether the reduction in recent memories recalled by individuals with MDD reflects an encoding deficit38 or a paucity of salient life experiences to draw on due to nonspecific factors, such as inactivity or social isolation.39 The finding that HR participants do not share the impairment in recent specific AMs manifest in individuals with MDD raises questions as to whether this abnormality results from recurrent depressive episodes.

The neuroimaging data demonstrated both common and distinct functional correlates of AM recall between groups. Across groups, BOLD activity changed in core components of the AM network,40 including the amygdala, hippocampus, parahippocampus, temporoparietal cortex and cerebellum, and ventrolateral, dorsolateral, and medial prefrontal cortex, as participants recalled specific AMs vs example generation. Differences in BOLD activity between groups were evident in the ACC, occipital cortex, frontal operculum, and medial prefrontal cortex.

In the pregenual ACC, BOLD activity increased to a greater extent in the MDD group than in the HC group or HR group. This ACC subdivision has been implicated in emotional processing associated with both positively and negatively valenced stimuli4144 and seems overactive at rest in MDD.45 The MDD group also had increased BOLD activity during specific AM recall compared with the other groups in the frontal polar cortex adjacent to the pregenual ACC. This area is involved in self-referential processing,46 and increased activity here when watching sad film clips predicts later rumination and depression relapse.47 The elevated BOLD response in this area in MDD conceivably may indicate greater self-referential and emotional processing, as well as depressive rumination. The absence of this abnormal pattern in BOLD activity in the HR group suggests that these alterations in prefrontal cortex function in the MDD group may relate more to pathologic emotional processing than specifically to AM recall deficits.

In the right frontal operculum, the HR group had decreased BOLD activity, while the HC group and MDD group had increased BOLD activity when recalling specific AMs. This area is implicated in self-focus and rumination and is active during induced sadness.48 Notably, individuals with MDD who have completed cognitive therapy do not manifest higher BOLD activity in this region during sadness induction.49

Finally, in the occipital cortex, both the MDD group and HR group had increased activity during specific AM recall, with the HR group showing the greatest increase in BOLD activity. Neuroimaging studies5052 of AM recall demonstrated occipital activation, and this area has been implicated in visuospatial processing.53 A recent study47 also found that activity in BA 17 correlated with tolerance of distress in both HC and remitted MDD samples, and increased activity in this area was associated with a lower risk for depression relapse. This may be particularly relevant to the present study because BOLD activity was higher in the HR group than in the MDD group.

Despite showing similar behavioral differences during AM recall, the HR group and the MDD group had distinct neuroimaging profiles. In BA 47s, the BOLD response in the MDD group seemed more similar to that in the HC group than to that in the HR group. In other regions (BA 10 and the ACC), BOLD activity in the MDD group differed from that in both the HC group and the HR group. Notably, the analysis focused on specific AMs, and the properties of these memories (other than age when the memory occurred) did not differ across groups. Distinct neuroimaging results across groups may be attributable to different cognitive strategies used by each group to achieve a specific memory. Conceivably, such strategies may differentially engage self-referential and ruminative processing, with the MDD group using these processes to a greater extent than the other groups (as suggested by increased activity in BA 10 and the ACC), while the HR group avoided ruminative processing. Lower BOLD response in the HR group in BA 47s may reflect a protective mechanism whereby emotions are interpreted as information associated with a memory rather than as impetus for rumination. In addition, the ability to recall specific AMs, leading to an increase in BOLD activity of BA 17, conceivably may aid HR individuals and patients with MDD as they encounter distressing situations. Previous behavioral studies support this hypothesis by showing that, in remitted patients with MDD, overgeneral AM recall is more likely manifest when interpersonally relevant content is accessed before memory recall54 and by demonstrating that increased exposure to self-relevant AM cues is associated with decreased AM specificity.55

Our results support the assertion that AM overgenerality constitutes a traitlike marker of MDD.56 However, we hypothesize that this overgenerality may only become dysfunctional and lead to pathology when coupled with increased rumination or self-focus. Because the mean age at onset for MDD is the mid-20s57 and because the mean age in our HR group was early 30s, it is likely that our HR sample predominantly represented a resilient group beyond the age of peak susceptibility. Therefore, understanding how these participants differ from those with MDD may provide insight into how to prevent MDD from developing in those at risk. Because several regions where the MDD group manifested increased BOLD activity compared with the HC or HR group are involved in self-referential processing, it is conceivable that focusing less on self during AM retrieval provides a protective mechanism for HR individuals. To our knowledge, assessing whether AMs focus more on self or others has not been characterized in previous studies of AM in MDD but may prove informative in future studies.

One limitation of our study design is the lack of experimental control over the properties of recalled AMs and the processes triggered that are unrelated to memory recall or depression vulnerability. This limitation is inherent to neuroimaging studies of AM recall, which we attempted to mitigate by carefully selecting relevant control tasks. Although some portion of the response during memory recall would be attributable to affective processing, this type of processing presumably occurred for both example generation and memory conditions because both cue words were matched for valence, arousal, vividness, and frequency of use. The lack of group differences during the example generation condition supports the conclusion that observed differences during AM recall relate to different processes of searching for and recalling a memory.

The use of this new control task also may explain why our fMR imaging results did not replicate some of the neuroimaging findings from a previous study,18 despite the successful replication of the previous behavioral results. The control task used in the present study (example generation) differed from that used in the previous study (solving subtraction problems). The strength of the present design is that, by comparing BOLD activity during recall of specific AMs with activity during example generation, we more specifically characterized the BOLD response to episodic, sensory, and perceptual representations of the memory.

Overgeneral AM is associated with impaired problem solving both generally58,59 and following negative mood induction,60 impaired executive control,61 and difficulty imagining the future.62 In addition, AM deficits interfere with the generation of adaptive responses to social interactions and stressful circumstances.63 Illuminating the neural mechanisms underlying AM deficits in MDD and HR samples ultimately may lead to the development of interventions that enhance the effectiveness of cognitive-based treatments for depression. Existing cognitive therapies target overgeneralization in patients’ beliefs and perspectives, often accomplished by having patients keep a diary of significant events and associated feelings.64 Targeting overgeneral AM recall and shifting the focus of AMs from self to others in cognitive therapy may prove beneficial for treating MDD and preventing those at risk from developing the disorder.

Corresponding Author: Kymberly D. Young, PhD, Laureate Institute for Brain Research, 6655 S Yale Ave, Tulsa, OK (kyoung@laureateinstitute.org).

Submitted for Publication: April 24, 2012; final revision received November 1, 2012; accepted November 3, 2012.

Published Online: May 15, 2013. doi:10.1001/jamapsychiatry.2013.1189.

Author Contributions: Dr Young takes responsibility for the integrity of the data and accuracy of the data analysis. All authors had full access to all the data in the study.

Conflict of Interest Disclosures: None reported.

Funding/Support: Funding for this work was provided by the Laureate Institute for Brain Research through The William K. Warren Foundation.

Role of the Sponsors: None reported.

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PubMed   |  Link to Article
Mackinger  HF, Pachinger  MM, Leibetseder  MM, Fartacek  RR.  Autobiographical memories in women remitted from major depression. J Abnorm Psychol. 2000;109(2):331-334.
PubMed   |  Link to Article
Spinhoven  P, Bockting  CL, Schene  AH, Koeter  MW, Wekking  EM, Williams  JM.  Autobiographical memory in the euthymic phase of recurrent depression. J Abnorm Psychol. 2006;115(3):590-600.
PubMed   |  Link to Article
Nandrino  JL, Pezard  L, Posté  A, Réveillère  C, Beaune  D.  Autobiographical memory in major depression: a comparison between first-episode and recurrent patients. Psychopathology. 2002;35(6):335-340.
PubMed   |  Link to Article
Wessel  I, Meeren  M, Peeters  F, Arntz  A, Merckelbach  H.  Correlates of autobiographical memory specificity: the role of depression, anxiety and childhood trauma. Behav Res Ther. 2001;39(4):409-421.
PubMed   |  Link to Article
Gibbs  B, Rude  S.  Overgeneral autobiographical memory as depression vulnerability. Cognit Ther Res. 2004;28(4):511-526.
Link to Article
van Minnen  A, Wessel  I, Verhaak  C, Smeenk  J.  The relationship between autobiographical memory specificity and depressed mood following a stressful life event: a prospective study. Br J Clin Psychol. 2005;44(pt 3):405-415.
PubMed
Kleim  B, Ehlers  A.  Reduced autobiographical memory specificity predicts depression and posttraumatic stress disorder after recent trauma. J Consult Clin Psychol. 2008;76(2):231-242.
PubMed   |  Link to Article
Kuyken  W, Dalgleish  T.  Overgeneral autobiographical memory in adolescents at risk for depression. Memory. 2011;19(3):241-250.
PubMed   |  Link to Article
Hipwell  AE, Sapotichne  B, Klostermann  S, Battista  D, Keenan  K.  Autobiographical memory as a predictor of depression vulnerability in girls. J Clin Child Adolesc Psychol. 2011;40(2):254-265.
PubMed   |  Link to Article
Hamilton  JP, Gotlib  IH.  Neural substrates of increased memory sensitivity for negative stimuli in major depression. Biol Psychiatry. 2008;63(12):1155-1162.
PubMed   |  Link to Article
van Tol  MJ, Demenescu  LR, van der Wee  NJ,  et al.  Functional magnetic resonance imaging correlates of emotional word encoding and recognition in depression and anxiety disorders. Biol Psychiatry. 2012;71(7):593-602.
PubMed   |  Link to Article
Arnold  JF, Fitzgerald  DA, Fernández  G,  et al.  Rose or black–coloured glasses? altered neural processing of positive events during memory formation is a trait marker of depression. J Affect Disord. 2011;131(1-3):214-223.
PubMed   |  Link to Article
Wolfensberger  SP, Veltman  DJ, Hoogendijk  WJ, De Ruiter  MB, Boomsma  DI, de Geus  EJ.  The neural correlates of verbal encoding and retrieval in monozygotic twins at low or high risk for depression and anxiety. Biol Psychol. 2008;79(1):80-90.
PubMed   |  Link to Article
Whalley  MG, Rugg  MD, Brewin  CR.  Autobiographical memory in depression: an fMRI study. Psychiatry Res. 2012;201(2):98-106.
PubMed   |  Link to Article
Keedwell  PA, Andrew  C, Williams  SC, Brammer  MJ, Phillips  ML.  A double dissociation of ventromedial prefrontal cortical responses to sad and happy stimuli in depressed and healthy individuals. Biol Psychiatry. 2005;58(6):495-503.
PubMed   |  Link to Article
Young  KD, Erickson  K, Nugent  AC,  et al.  Functional anatomy of autobiographical memory recall deficits in depression. Psychol Med. 2011;42:1-13.
PubMed
Ryan  L, Nadel  L, Keil  K,  et al.  Hippocampal complex and retrieval of recent and very remote autobiographical memories: evidence from functional magnetic resonance imaging in neurologically intact people. Hippocampus. 2001;11(6):707-714.
PubMed   |  Link to Article
Conway  M, Pleydell-Pearce  C, Whitecross  S, Sharpe  H.  Brain imaging autobiographical memory. Psychol Learn Motiv. 2002;41:229-263.
American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders.4th ed, text revision. Washington, DC: American Psychiatric Association; 2000.
First  MB, Spitzer  RL, Gibbon  M, Williams  JBW. Structured Clinical Interview for DSM-IV-TR Axis I Disorders, Research Version, Patient Edition (SCID-I/P). New York, NY: New York State Psychiatric Institute, Biometrics Research; 2002.
Maxwell  E. Family Interview for Genetic Studies (FIGS): A Manual for FIGS. Bethesda, MD: Clinical Neurogenetics Branch, Intramural Research Program, National Institute of Mental Health; 1992.
Wechsler  D. Wechsler Abbreviated Scale of Intelligence (WASI). San Antonio, TX: Harcourt Assessment; 1999.
Spielberger  CD, Gorsuch  RL, Lushene  RE. Manual for the State-Trait Anxiety Inventory. Palo Alto, CA: Consulting Psychologists Press; 1970.
Hamilton  M.  A rating scale for depression. J Neurol Neurosurg Psychiatry. 1960;23:56-62.
PubMed   |  Link to Article
Montgomery  SA, Åsberg  M.  A new depression scale designed to be sensitive to change. Br J Psychiatry. 1979;134:382-389.
PubMed   |  Link to Article
Snaith  RP, Hamilton  M, Morley  S, Humayan  A, Hargreaves  D, Trigwell  P.  A scale for the assessment of hedonic tone: the Snaith-Hamilton Pleasure Scale. Br J Psychiatry. 1995;167(1):99-103.
PubMed   |  Link to Article
McNair  D, Lorr  M, Dropplemen  L, eds. Manual: Profile of Mood States. San Diego, CA: Educational and Industrial Testing Services; 1971.
Williams  JM, Scott  J.  Autobiographical memory in depression. Psychol Med. 1988;18(3):689-695.
PubMed   |  Link to Article
Anderson  R, Goddard  L, Powell  J.  Reduced specificity of autobiographical memory as a moderator of the relationship between daily hassles and depression. Cogn Emotion. 2010;24(4):702-709.
Link to Article
Williams  JM, Broadbent  K.  Autobiographical memory in suicide attempters. J Abnorm Psychol. 1986;95(2):144-149.
PubMed   |  Link to Article
Bradley  MM, Lang  PJ. Affective Norms for English Words (ANEW). Gainesville, FL: NIMH Center for the Study of Emotion and Attention, University of Florida; 1999.
Conway  M. A Structural Model of Autobiographical Memory. Dordrecht, the Netherlands: Kluwer Academic Publishers; 1992.
Talairach  J, Tournoux  P. Co-planar Stereotaxic Atlas of the Human Brain: 3-Dimensional Proportional System: An Approach to Cerebral Imaging. New York, NY: Thieme Medical Publishers; 1988.
Ongür  D, Ferry  AT, Price  JL.  Architectonic subdivision of the human orbital and medial prefrontal cortex. J Comp Neurol. 2003;460(3):425-449.
PubMed   |  Link to Article
Suslow  T, Junghanns  K, Arolt  V.  Detection of facial expressions of emotions in depression. Percept Mot Skills. 2001;92(3, pt 1):857-868.
PubMed
Ottowitz  WE, Dougherty  DD, Savage  CR.  The neural network basis for abnormalities of attention and executive function in major depressive disorder: implications for application of the medical disease model to psychiatric disorders. Harv Rev Psychiatry. 2002;10(2):86-99.
PubMed   |  Link to Article
Peeters  F, Nicolson  NA, Berkhof  J, Delespaul  P, deVries  M.  Effects of daily events on mood states in major depressive disorder. J Abnorm Psychol. 2003;112(2):203-211.
PubMed   |  Link to Article
Svoboda  E, McKinnon  MC, Levine  B.  The functional neuroanatomy of autobiographical memory: a meta-analysis. Neuropsychologia. 2006;44(12):2189-2208.
PubMed   |  Link to Article
Bush  G, Luu  P, Posner  MI.  Cognitive and emotional influences in anterior cingulate cortex. Trends Cogn Sci. 2000;4(6):215-222.
PubMed   |  Link to Article
Rolls  ET, Grabenhorst  F, Parris  BA.  Warm pleasant feelings in the brain. Neuroimage. 2008;41(4):1504-1513.
PubMed   |  Link to Article
Grabenhorst  F, Rolls  ET, Bilderbeck  A.  How cognition modulates affective responses to taste and flavor: top-down influences on the orbitofrontal and pregenual cingulate cortices. Cereb Cortex. 2008;18(7):1549-1559.
PubMed   |  Link to Article
Pizzagalli  DA.  Frontocingulate dysfunction in depression: toward biomarkers of treatment response. Neuropsychopharmacology. 2011;36(1):183-206.
PubMed   |  Link to Article
Drevets  WC, Videen  TO, Price  JL, Preskorn  SH, Carmichael  ST, Raichle  ME.  A functional anatomical study of unipolar depression. J Neurosci. 1992;12(9):3628-3641.
PubMed
Lemogne  C, Gorwood  P, Bergouignan  L, Pélissolo  A, Lehéricy  S, Fossati  P.  Negative affectivity, self-referential processing and the cortical midline structures. Soc Cogn Affect Neurosci. 2011;6(4):426-433.
PubMed   |  Link to Article
Farb  NA, Anderson  AK, Bloch  RT, Segal  ZV.  Mood-linked responses in medial prefrontal cortex predict relapse in patients with recurrent unipolar depression. Biol Psychiatry. 2011;70(4):366-372.
PubMed   |  Link to Article
Gillihan  SJ, Farah  MJ.  Is self special? a critical review of evidence from experimental psychology and cognitive neuroscience. Psychol Bull. 2005;131(1):76-97.
PubMed   |  Link to Article
Farb  NA, Anderson  AK, Mayberg  H, Bean  J, McKeon  D, Segal  ZV.  Minding one’s emotions: mindfulness training alters the neural expression of sadness. Emotion. 2010;10(1):25-33.
PubMed   |  Link to Article
Cabeza  R, Prince  SE, Daselaar  SM,  et al.  Brain activity during episodic retrieval of autobiographical and laboratory events: an fMRI study using a novel photo paradigm. J Cogn Neurosci. 2004;16(9):1583-1594.
PubMed   |  Link to Article
Conway  MA, Turk  DJ, Miller  SL,  et al.  A positron emission tomography (PET) study of autobiographical memory retrieval. Memory. 1999;7(5-6):679-702.
PubMed   |  Link to Article
Addis  DR, McIntosh  AR, Moscovitch  M, Crawley  AP, McAndrews  MP.  Characterizing spatial and temporal features of autobiographical memory retrieval networks: a partial least squares approach. Neuroimage. 2004;23(4):1460-1471.
PubMed   |  Link to Article
Renier  LA, Anurova  I, De Volder  AG, Carlson  S, VanMeter  J, Rauschecker  JP.  Preserved functional specialization for spatial processing in the middle occipital gyrus of the early blind. Neuron. 2010;68(1):138-148.
PubMed   |  Link to Article
Barnhofer  T, Crane  C, Spinhoven  P, Williams  JM.  Failures to retrieve specific memories in previously depressed individuals: random errors or content-related? Behav Res Ther. 2007;45(8):1859-1869.
PubMed   |  Link to Article
Crane  C, Barnhofer  T, Mark  J, Williams  G.  Cue self-relevance affects autobiographical memory specificity in individuals with a history of major depression. Memory. 2007;15(3):312-323.
PubMed   |  Link to Article
Brittlebank  AD, Scott  J, Williams  JM, Ferrier  IN.  Autobiographical memory in depression: state or trait marker? Br J Psychiatry. 1993;162:118-121.
PubMed   |  Link to Article
Zisook  S, Lesser  I, Stewart  JW,  et al.  Effect of age at onset on the course of major depressive disorder. Am J Psychiatry. 2007;164(10):1539-1546.
PubMed   |  Link to Article
Evans  J, Williams  JM, O’Loughlin  S, Howells  K.  Autobiographical memory and problem-solving strategies of parasuicide patients. Psychol Med. 1992;22(2):399-405.
PubMed   |  Link to Article
Goddard  L, Dritschel  B, Burton  A.  Role of autobiographical memory in social problem solving and depression. J Abnorm Psychol. 1996;105(4):609-616.
PubMed   |  Link to Article
Williams  JM, Barnhofer  T, Crane  C, Beck  AT.  Problem solving deteriorates following mood challenge in formerly depressed patients with a history of suicidal ideation. J Abnorm Psychol. 2005;114(3):421-431.
PubMed   |  Link to Article
Dalgleish  T, Williams  JM, Golden  AM,  et al.  Reduced specificity of autobiographical memory and depression: the role of executive control. J Exp Psychol Gen. 2007;136(1):23-42.
PubMed   |  Link to Article
Williams  JM, Ellis  NC, Tyers  C, Healy  H, Rose  G, MacLeod  AK.  The specificity of autobiographical memory and imageability of the future. Mem Cognit. 1996;24(1):116-125.
PubMed   |  Link to Article
Williams  JM, Conway  MA, Cohen  G. Autobiographical Memory.3rd ed. Hove, UK: Psychology Press; 2008.
Beck  A. Cognitive Therapy and Emotional Disorders. New York, NY: Penguin; 1993.

Figures

Place holder to copy figure label and caption
Figure.
Hemodynamic Activity During Autobiographical Memory (AM) Recall Group Differences in AM and Regions Where Groups Had Differential Activation During Specific AM Recall vs Example Generation (Corrected P < .05)

Using the significant clusters in Table 3 as regions of interest, β weights were extracted for specific AMs vs riser baseline and example generation vs riser baseline. ACC indicates anterior cingulate cortex; BA, Brodmann area; HC, healthy control subjects; HR, individuals at high familial risk for developing MDD; L, left; MDD, major depressive disorder; and R, right.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1.  Participant Characteristics by Diagnostic Group1
Table Graphic Jump LocationTable 2.  Properties of Specific and Categorical AMs by Diagnostic Group1
Table Graphic Jump LocationTable 3.  Regions Where Hemodynamic Activity Differed Significantly Across the Diagnostic Groups for the Different Contrasts Performed

References

Van Vreeswijk  MF, De Wilde  EJ.  Autobiographical memory specificity, psychopathology, depressed mood and the use of the Autobiographical Memory Test: a meta-analysis. Behav Res Ther. 2004;42(6):731-743.
PubMed   |  Link to Article
Williams  JM, Barnhofer  T, Crane  C,  et al.  Autobiographical memory specificity and emotional disorder. Psychol Bull. 2007;133(1):122-148.
PubMed   |  Link to Article
Mackinger  HF, Pachinger  MM, Leibetseder  MM, Fartacek  RR.  Autobiographical memories in women remitted from major depression. J Abnorm Psychol. 2000;109(2):331-334.
PubMed   |  Link to Article
Spinhoven  P, Bockting  CL, Schene  AH, Koeter  MW, Wekking  EM, Williams  JM.  Autobiographical memory in the euthymic phase of recurrent depression. J Abnorm Psychol. 2006;115(3):590-600.
PubMed   |  Link to Article
Nandrino  JL, Pezard  L, Posté  A, Réveillère  C, Beaune  D.  Autobiographical memory in major depression: a comparison between first-episode and recurrent patients. Psychopathology. 2002;35(6):335-340.
PubMed   |  Link to Article
Wessel  I, Meeren  M, Peeters  F, Arntz  A, Merckelbach  H.  Correlates of autobiographical memory specificity: the role of depression, anxiety and childhood trauma. Behav Res Ther. 2001;39(4):409-421.
PubMed   |  Link to Article
Gibbs  B, Rude  S.  Overgeneral autobiographical memory as depression vulnerability. Cognit Ther Res. 2004;28(4):511-526.
Link to Article
van Minnen  A, Wessel  I, Verhaak  C, Smeenk  J.  The relationship between autobiographical memory specificity and depressed mood following a stressful life event: a prospective study. Br J Clin Psychol. 2005;44(pt 3):405-415.
PubMed
Kleim  B, Ehlers  A.  Reduced autobiographical memory specificity predicts depression and posttraumatic stress disorder after recent trauma. J Consult Clin Psychol. 2008;76(2):231-242.
PubMed   |  Link to Article
Kuyken  W, Dalgleish  T.  Overgeneral autobiographical memory in adolescents at risk for depression. Memory. 2011;19(3):241-250.
PubMed   |  Link to Article
Hipwell  AE, Sapotichne  B, Klostermann  S, Battista  D, Keenan  K.  Autobiographical memory as a predictor of depression vulnerability in girls. J Clin Child Adolesc Psychol. 2011;40(2):254-265.
PubMed   |  Link to Article
Hamilton  JP, Gotlib  IH.  Neural substrates of increased memory sensitivity for negative stimuli in major depression. Biol Psychiatry. 2008;63(12):1155-1162.
PubMed   |  Link to Article
van Tol  MJ, Demenescu  LR, van der Wee  NJ,  et al.  Functional magnetic resonance imaging correlates of emotional word encoding and recognition in depression and anxiety disorders. Biol Psychiatry. 2012;71(7):593-602.
PubMed   |  Link to Article
Arnold  JF, Fitzgerald  DA, Fernández  G,  et al.  Rose or black–coloured glasses? altered neural processing of positive events during memory formation is a trait marker of depression. J Affect Disord. 2011;131(1-3):214-223.
PubMed   |  Link to Article
Wolfensberger  SP, Veltman  DJ, Hoogendijk  WJ, De Ruiter  MB, Boomsma  DI, de Geus  EJ.  The neural correlates of verbal encoding and retrieval in monozygotic twins at low or high risk for depression and anxiety. Biol Psychol. 2008;79(1):80-90.
PubMed   |  Link to Article
Whalley  MG, Rugg  MD, Brewin  CR.  Autobiographical memory in depression: an fMRI study. Psychiatry Res. 2012;201(2):98-106.
PubMed   |  Link to Article
Keedwell  PA, Andrew  C, Williams  SC, Brammer  MJ, Phillips  ML.  A double dissociation of ventromedial prefrontal cortical responses to sad and happy stimuli in depressed and healthy individuals. Biol Psychiatry. 2005;58(6):495-503.
PubMed   |  Link to Article
Young  KD, Erickson  K, Nugent  AC,  et al.  Functional anatomy of autobiographical memory recall deficits in depression. Psychol Med. 2011;42:1-13.
PubMed
Ryan  L, Nadel  L, Keil  K,  et al.  Hippocampal complex and retrieval of recent and very remote autobiographical memories: evidence from functional magnetic resonance imaging in neurologically intact people. Hippocampus. 2001;11(6):707-714.
PubMed   |  Link to Article
Conway  M, Pleydell-Pearce  C, Whitecross  S, Sharpe  H.  Brain imaging autobiographical memory. Psychol Learn Motiv. 2002;41:229-263.
American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders.4th ed, text revision. Washington, DC: American Psychiatric Association; 2000.
First  MB, Spitzer  RL, Gibbon  M, Williams  JBW. Structured Clinical Interview for DSM-IV-TR Axis I Disorders, Research Version, Patient Edition (SCID-I/P). New York, NY: New York State Psychiatric Institute, Biometrics Research; 2002.
Maxwell  E. Family Interview for Genetic Studies (FIGS): A Manual for FIGS. Bethesda, MD: Clinical Neurogenetics Branch, Intramural Research Program, National Institute of Mental Health; 1992.
Wechsler  D. Wechsler Abbreviated Scale of Intelligence (WASI). San Antonio, TX: Harcourt Assessment; 1999.
Spielberger  CD, Gorsuch  RL, Lushene  RE. Manual for the State-Trait Anxiety Inventory. Palo Alto, CA: Consulting Psychologists Press; 1970.
Hamilton  M.  A rating scale for depression. J Neurol Neurosurg Psychiatry. 1960;23:56-62.
PubMed   |  Link to Article
Montgomery  SA, Åsberg  M.  A new depression scale designed to be sensitive to change. Br J Psychiatry. 1979;134:382-389.
PubMed   |  Link to Article
Snaith  RP, Hamilton  M, Morley  S, Humayan  A, Hargreaves  D, Trigwell  P.  A scale for the assessment of hedonic tone: the Snaith-Hamilton Pleasure Scale. Br J Psychiatry. 1995;167(1):99-103.
PubMed   |  Link to Article
McNair  D, Lorr  M, Dropplemen  L, eds. Manual: Profile of Mood States. San Diego, CA: Educational and Industrial Testing Services; 1971.
Williams  JM, Scott  J.  Autobiographical memory in depression. Psychol Med. 1988;18(3):689-695.
PubMed   |  Link to Article
Anderson  R, Goddard  L, Powell  J.  Reduced specificity of autobiographical memory as a moderator of the relationship between daily hassles and depression. Cogn Emotion. 2010;24(4):702-709.
Link to Article
Williams  JM, Broadbent  K.  Autobiographical memory in suicide attempters. J Abnorm Psychol. 1986;95(2):144-149.
PubMed   |  Link to Article
Bradley  MM, Lang  PJ. Affective Norms for English Words (ANEW). Gainesville, FL: NIMH Center for the Study of Emotion and Attention, University of Florida; 1999.
Conway  M. A Structural Model of Autobiographical Memory. Dordrecht, the Netherlands: Kluwer Academic Publishers; 1992.
Talairach  J, Tournoux  P. Co-planar Stereotaxic Atlas of the Human Brain: 3-Dimensional Proportional System: An Approach to Cerebral Imaging. New York, NY: Thieme Medical Publishers; 1988.
Ongür  D, Ferry  AT, Price  JL.  Architectonic subdivision of the human orbital and medial prefrontal cortex. J Comp Neurol. 2003;460(3):425-449.
PubMed   |  Link to Article
Suslow  T, Junghanns  K, Arolt  V.  Detection of facial expressions of emotions in depression. Percept Mot Skills. 2001;92(3, pt 1):857-868.
PubMed
Ottowitz  WE, Dougherty  DD, Savage  CR.  The neural network basis for abnormalities of attention and executive function in major depressive disorder: implications for application of the medical disease model to psychiatric disorders. Harv Rev Psychiatry. 2002;10(2):86-99.
PubMed   |  Link to Article
Peeters  F, Nicolson  NA, Berkhof  J, Delespaul  P, deVries  M.  Effects of daily events on mood states in major depressive disorder. J Abnorm Psychol. 2003;112(2):203-211.
PubMed   |  Link to Article
Svoboda  E, McKinnon  MC, Levine  B.  The functional neuroanatomy of autobiographical memory: a meta-analysis. Neuropsychologia. 2006;44(12):2189-2208.
PubMed   |  Link to Article
Bush  G, Luu  P, Posner  MI.  Cognitive and emotional influences in anterior cingulate cortex. Trends Cogn Sci. 2000;4(6):215-222.
PubMed   |  Link to Article
Rolls  ET, Grabenhorst  F, Parris  BA.  Warm pleasant feelings in the brain. Neuroimage. 2008;41(4):1504-1513.
PubMed   |  Link to Article
Grabenhorst  F, Rolls  ET, Bilderbeck  A.  How cognition modulates affective responses to taste and flavor: top-down influences on the orbitofrontal and pregenual cingulate cortices. Cereb Cortex. 2008;18(7):1549-1559.
PubMed   |  Link to Article
Pizzagalli  DA.  Frontocingulate dysfunction in depression: toward biomarkers of treatment response. Neuropsychopharmacology. 2011;36(1):183-206.
PubMed   |  Link to Article
Drevets  WC, Videen  TO, Price  JL, Preskorn  SH, Carmichael  ST, Raichle  ME.  A functional anatomical study of unipolar depression. J Neurosci. 1992;12(9):3628-3641.
PubMed
Lemogne  C, Gorwood  P, Bergouignan  L, Pélissolo  A, Lehéricy  S, Fossati  P.  Negative affectivity, self-referential processing and the cortical midline structures. Soc Cogn Affect Neurosci. 2011;6(4):426-433.
PubMed   |  Link to Article
Farb  NA, Anderson  AK, Bloch  RT, Segal  ZV.  Mood-linked responses in medial prefrontal cortex predict relapse in patients with recurrent unipolar depression. Biol Psychiatry. 2011;70(4):366-372.
PubMed   |  Link to Article
Gillihan  SJ, Farah  MJ.  Is self special? a critical review of evidence from experimental psychology and cognitive neuroscience. Psychol Bull. 2005;131(1):76-97.
PubMed   |  Link to Article
Farb  NA, Anderson  AK, Mayberg  H, Bean  J, McKeon  D, Segal  ZV.  Minding one’s emotions: mindfulness training alters the neural expression of sadness. Emotion. 2010;10(1):25-33.
PubMed   |  Link to Article
Cabeza  R, Prince  SE, Daselaar  SM,  et al.  Brain activity during episodic retrieval of autobiographical and laboratory events: an fMRI study using a novel photo paradigm. J Cogn Neurosci. 2004;16(9):1583-1594.
PubMed   |  Link to Article
Conway  MA, Turk  DJ, Miller  SL,  et al.  A positron emission tomography (PET) study of autobiographical memory retrieval. Memory. 1999;7(5-6):679-702.
PubMed   |  Link to Article
Addis  DR, McIntosh  AR, Moscovitch  M, Crawley  AP, McAndrews  MP.  Characterizing spatial and temporal features of autobiographical memory retrieval networks: a partial least squares approach. Neuroimage. 2004;23(4):1460-1471.
PubMed   |  Link to Article
Renier  LA, Anurova  I, De Volder  AG, Carlson  S, VanMeter  J, Rauschecker  JP.  Preserved functional specialization for spatial processing in the middle occipital gyrus of the early blind. Neuron. 2010;68(1):138-148.
PubMed   |  Link to Article
Barnhofer  T, Crane  C, Spinhoven  P, Williams  JM.  Failures to retrieve specific memories in previously depressed individuals: random errors or content-related? Behav Res Ther. 2007;45(8):1859-1869.
PubMed   |  Link to Article
Crane  C, Barnhofer  T, Mark  J, Williams  G.  Cue self-relevance affects autobiographical memory specificity in individuals with a history of major depression. Memory. 2007;15(3):312-323.
PubMed   |  Link to Article
Brittlebank  AD, Scott  J, Williams  JM, Ferrier  IN.  Autobiographical memory in depression: state or trait marker? Br J Psychiatry. 1993;162:118-121.
PubMed   |  Link to Article
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Evans  J, Williams  JM, O’Loughlin  S, Howells  K.  Autobiographical memory and problem-solving strategies of parasuicide patients. Psychol Med. 1992;22(2):399-405.
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Supplement.

eMethods. Supplemental Methods

eFigure. tSNR Maps for Each Participant Group

eTable 1. Group Motion Statistics

eTable 2. Difference Scores for Fatigue Measures for Each Participant Group

eTable 3. Percentage of Specific and Positive AMs Recalled for Each Group and Task Half

eTable 4. Clinical Characteristics of the MDD Participants

eTable 5. Increases in the BOLD Response for the Different Contrasts Across all Diagnostic Groups

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