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. Author manuscript; available in PMC: 2019 May 1.
Published in final edited form as: Depress Anxiety. 2018 Feb 27;35(5):440–447. doi: 10.1002/da.22734

Depression is associated with dimensional and categorical effects on white matter pathways

Daniel G Dillon 1,*, Atilla Gonenc 2,*, Emily Belleau 1, Diego A Pizzagalli 1,2
PMCID: PMC5934303  NIHMSID: NIHMS939856  PMID: 29486093

Abstract

Background

Diffusion tensor imaging (DTI) studies report reduced fractional anisotropy (FA) in Major Depressive Disorder (MDD). However, whether FA covaries with key depressive symptoms, such as anhedonia, is unclear.

Methods

Magnetic resonance imaging data were acquired from 38 unmedicated adults with MDD and 52 healthy controls. DTI metrics were extracted from regions of interest that have consistently shown reduced FA in MDD. Analyses focused first on identifying group differences, and then determining whether reduced FA in depressed adults was related to individual differences in anhedonia and depressive severity. To establish specificity to depression, these analyses controlled for symptoms of anxiety.

Results

Relative to controls, depressed adults showed reduced FA in the genu of the corpus callosum, the anterior limb of the internal capsule (ALIC), the cingulum bundle near the anterior cingulate cortex, and the uncinate fasciculus (UF). In the depressed group, anhedonia negatively correlated with FA in the genu, cingulum, and UF, but positively correlated with radial diffusivity (RD)—a metric previously linked to demyelination—in the genu and ALIC. Depressive severity positively correlated with RD in the ALIC. These relationships remained significant after accounting for anxiety.

Conclusion

Anhedonia was positively correlated with reduced FA and increased RD in white matter pathways that connect regions critical for value coding, representing stimulus-reward associations, and guiding value-based action selection. Thus, a cardinal symptom of MDD—anhedonia—was lawfully related to abnormalities in reward network connectivity.

Keywords: depression, anhedonia, white matter, corpus callosum, anxiety

Introduction

Meta-analyses of the diffusion tensor imaging (DTI) literature report reduced fractional anisotropy (FA) in Major Depressive Disorder (MDD) (Chen et al., 2016; Jiang et al., 2016; Liao et al., 2013; Wise et al., 2016). FA reflects the tendency for water to diffuse in one direction, and FA increases in white matter because axons constrain diffusion to occur parallel to fibers (Alexander et al., 2007). Consequently, reduced FA suggests white matter abnormalities. In MDD, FA is consistently reduced in the genu of the corpus callosum, the uncinate fasciculus (UF), and the anterior limb of the internal capsule (ALIC) (Bracht et al., 2015b; Chen et al., 2016). These tracts connect the frontal lobes to each other, to anterior temporal regions (e.g., amygdala), and to subcortical structures (e.g., striatum). Given the importance of these connections for cognition, emotion regulation, and motivated behavior, their disruption may contribute to MDD (Liao et al., 2013).

It would be useful to know whether FA covaries with anhedonia. Anhedonia is a cardinal symptom of MDD (APA, 2013) that may be related to reduced FA in reward networks. Functional neuroimaging has linked anhedonia to abnormal reward responses in the striatum and ventromedial prefrontal cortex (Keedwell et al., 2005), and DTI studies (see Bracht et al., 2015b) have linked anhedonia to decreased FA in the cingulum and medial forebrain bundle (MFB), a pathway that connects the ventral tegmental area and nucleus accumbens (Coenen et al., 2011; in many DTI studies, data from the ALIC may include overlapping fibers from the MFB, Bracht et al., 2015b). For instance, Bracht et al. (2014) found a negative correlation between loss of pleasure and MFB FA, while cingulum FA was positively correlated with hedonic tone and reduced in women with a family history of depression (Keedwell et al., 2012).

Thus, anhedonia has been associated with reduced FA in the MFB/ALIC and cingulum. Whether anhedonia is related to FA in other regions is less clear. Furthermore, whether reduced FA in the MFB/ALIC and cingulum specifically reflects anhedonia or involves a contribution from comorbid symptoms, such as anxiety, has not been established. The Mood and Anxiety Symptoms Questionnaire (MASQ: Watson et al., 1995) is ideal for addressing this issue, as it includes scales particularly relevant for depression (anhedonic depression: MASQ-AD) versus anxiety (anxious arousal: MASQ-AA), with other scales capturing general distress due to depression (MASQ-GDD) and anxiety (MASQ-GDA). Keedwell et al. (2012) reported a correlation between cingulum FA and MASQ-AD scores but did not test whether this relationship held when controlling for anxiety, which is critical for establishing specificity. Finally, because antidepressants may affect DTI variables (Sijens et al., 2008; Taylor et al., 2011), use of unmedicated samples is critical.

Therefore, we examined MASQ and DTI data from unmedicated adults with MDD and healthy controls who completed functional magnetic resonance imaging (fMRI) studies (Dillon, Dobbins, & Pizzagalli, 2014; Dillon & Pizzagalli, 2013). Guided by recent meta-analyses, we extracted FA values from a priori regions of interest (ROIs): the genu of the corpus callosum, the cingulum bundle near the anterior cingulate cortex (ACC) and hippocampus, the UF, ALIC, and MFB. We also extracted FA values from the anterior corona radiata, as reduced FA in this region has been reported in depression (Cole et al., 2012).

We also extracted estimates of radial diffusivity (RD), axial diffusivity (AD), and mean diffusivity (MD) from each ROI. In rodents, demyelination is correlated with increased RD, which corresponds to diffusivity perpendicular to white matter, but is less strongly related to AD, corresponding to diffusivity parallel to white matter, or MD, corresponding to overall diffusivity (Budde et al., 2007; Song et al., 2005). Research in humans with multiple sclerosis has also linked demyelination to increased RD (Klawiter et al., 2011). Thus, if MDD is associated with decreased FA and increased RD, this would suggest an association between MDD and demyelination. Interpretation of RD can be difficult, especially where crossing fibers are present (Wheeler-Kingshott & Cercignani, 2009). Nevertheless, we predicted that depressed adults would show reduced FA, and that anhedonia and depressive severity would be negatively related to FA but positively related to RD, even after controlling for anxiety.

Materials and Methods

Participants

DTI data were collected from 38 unmedicated adults who met DSM-IV criteria for current MDD and 52 healthy controls (Dillon et al., 2014; Dillon & Pizzagalli, 2013). Psychiatric history was assessed with the Structured Clinical Interview for DSM-IV (First, Spitzer, Gibbon, & Williams, 2002). Depressed participants had to meet criteria for current MDD with no history of psychosis and had to be unmedicated, although past use of psychotropic compounds was allowed (no use in the preceding two weeks for benzodiazepines, six weeks for selective serotonin reuptake inhibitors, six months for dopaminergic drugs). Comorbid anxiety was allowed if secondary to depression. Controls reported no current or past Axis I diagnosis, and no participant presented with neurological conditions or significant medical history, or met criteria for lifetime substance dependence or substance abuse in the past year. The studies were approved by the Harvard University Committee on the Use of Human Subjects in Research and the Partners HealthCare Human Research Committee. Participants were right handed and 18–64 years old; they provided informed consent and were paid $25/hour.

Data Acquisition

Diffusion tensor imaging

DTI data were collected on a Siemens 3T Tim Trio scanner using a protocol (Holmes et al., 2015) that began with a localizer scan, an auto-align scout (van der Kouwe et al., 2005), and collection of T1-weighted (van der Kouwe et al., 2008) and T2-weighted anatomical data. Diffusion tensor imaging was conducted next (TE = 85 ms, FOV = 220 x 220 mm, voxels = 1.4 x 1.4 x 3.0 mm, b value = 1,000 s/mm2, 6 directions). During data collection, the TR used during DTI acquisition changed from 5,960 ms to 6,110 ms; there was no group difference on this variable (5960 ms: 15 MDD, 29 controls; 6110 ms: 23 MDD, 23 controls; χ2(1) = 1.73, p = 0.19).

Questionnaires

Participants completed the Beck Depression Inventory-II (BDI-II; Beck et al., 1996) and the MASQ. MASQ data were not collected for one control and one depressed participant. For correlations with DTI metrics, only MASQ scores were considered because they allowed us to test whether relationships with anhedonia and depression severity remained when accounting for anxiety.

Data Analysis

DTI

Preprocessing was conducted using FSL (Smith et al., 2004) and included skull-stripping, motion correction, and eddy correction with reorientation of the b matrix. The method used to correct for EPI/susceptibility distortions has been described (Irfanoglu et al., 2012). To avoid inclusion of gray matter and cerebrospinal fluid, DTI values were extracted from voxels with FA values > 0.2. After correction of the diffusion-weighted images, FA values were obtained with non-linear least squares tensor fitting as it provides accurate noise modeling. Participant maps were registered to a study-specific template constructed using a subset of 20 participants and the Diffusion Tensor Imaging Toolkit (DTI-TK; Wang et al., 2011; Zhang et al., 2006), an optimized tensor-based registration tool that yields better results than scalar-based registration (Adluru et al., 2012). All diffusion tensor maps were normalized to this template with rigid, affine, and diffeomorphic alignments and interpolated to 1.4 mm3 voxels. Finally, the Johns Hopkins International Consortium for Brain Mapping FA template was warped to the study-specific template space using Advanced Normalization Tools (Avants et al., 2011). Images were visually inspected to ensure adequate registrations.

Regions of Interest

We extracted FA, RD, AD, and MD data from six ROIs in the Johns Hopkins University ICBM-DTI-81 atlas (Hua et al., 2008): the genu of the corpus callosum, ALIC, cingulum of the ACC, cingulum of the hippocampus, anterior corona radiata, and UF (Figure 1). To assess the MFB, we used 3-mm radius spheres around published MNI coordinates (±6, −14, −8; Schlaepfer et al., 2013); the spheres did not overlap with any other ROI. ROIs were bilateral (2 hemispheres x 7 ROIs = 14 values). DTI data were available from the CC for all participants, but in the other ROIs we excluded poor quality data from two healthy and three depressed participants.

Figure 1.

Figure 1

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FA, RD, AD, and MD were extracted from ROIs in (from left to right) the cingulum of the hippocampus (cyan), uncinate fasciculus (blue), median forebrain bundle (white), corpus callosum (yellow), anterior limb of the internal capsule (ALIC; red), anterior corona radiata (purple), and cingulum of the anterior cingulate cortex (ACC; green). The ROI for the median forebrain bundle appears rectangular in this plane but was actually a 3-mm sphere.

Statistics

First, we computed a Group x Gender x ROI x Hemisphere ANCOVA on mean FA values, with SNR and age as covariates. The Greenhouse-Geisser correction was applied in case of violations of sphericity. A separate Group x Gender x Hemisphere ANCOVA was run for the genu as more data were available for this structure than for the other ROIs. Second, for ROIs showing reduced FA in MDD, we computed Group x Gender x ROI x Hemisphere ANCOVAs for AD, RD, and MD. Third, in ROIs that revealed group differences in DTI metrics, we computed partial correlations with MASQ-GDD or MASQ-AD scores in the depressed participants, again regressing out SNR and age. To test specificity, we performed hierarchical multiple regressions in which MASQ-GDA and MASQ-AA scores were entered first and MASQ-GDD or MASQ-AD scores were entered second. For these exploratory analyses, we did not correct for multiple comparisons. Alpha was set to 0.05, and all tests were two-tailed.

Results

Demographics and Clinical Data

There were no group differences in gender, age, or education (Table 1). The MASQ showed that, relative to controls, depressed adults were experiencing more distress, anxious arousal, and anhedonia.

Table 1.

Mean (SD) Demographic and Self-Report Data

Variable Controls
n = 52		 Depressed
n = 38		 P-value Effect size
Gender 25 f, 27 m 21 f, 17 m 0.65 0.07
Age 33.75 (13.46) 33.45 (10.44) 0.12 0.03
Education (years) 16.00 (1.83) 15.97 (2.27) 0.95 0.01
BDI-II 1.51 (2.10) 23.97 (9.10) 0.001 3.68
MASQ-GDA 13.47 (3.30) 25.03 (6.00) 0.001 2.50
MASQ-AA 18.37 (1.85) 25.00 (8.36) 0.001 1.18
MASQ-GDD 13.76 (2.57) 38.41 (10.23) 0.001 3.56
MASQ-AD 46.41 (11.36) 82.89 (8.77) 0.001 3.53
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Note. f = female, m = male. p-values reflect two sample t-tests except for Gender (chi-square). Effect size is given as absolute value of Hedges’ g (Cramer’s V for Gender). The mean BDI-II score in the MDD group indicates moderate depression.

As shown in Table 2, 29% of depressed participants were in their first episode, with the rest in recurrence. Depressed participants were unmedicated; 61% reported no prior psychotropic medication. Of 38 depressed participants, 42% met full criteria for a comorbid anxiety disorder, including social phobia (n = 10), panic disorder (n = 2), specific phobia (n = 1), social phobia and panic disorder (n = 1), or social phobia, specific phobia, and panic disorder (n = 2). Current binge eating disorder was diagnosed in two depressed participants.

Table 2.

Clinical Information for Depressed Participants

Clinical variable Value
N (%) in first MDE 11 (29%)
N (%) in recurrent MDE 27 (71%)
Mean (SD) past MDEs in recurrent group 4.67 (2.86)
Mean (SD) years since onset of first MDE 14.03 (10.02)
N (%) reporting past psychotropic use 15 (39%)
N (%) reporting no past psychotropic use 23 (61%)
N (%) with comorbid anxiety disorder 16 (42%)
N (%) with no comorbid anxiety disorder 22 (58%)
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FA

Mean (±SD) SNR was similar in the MDD (7.45±0.87) and control (7.25±0.66) groups, t(88) = −1.26, p = 0.21, Hedges’ g = −0.27. The ANCOVA on genu FA revealed an effect of Group, F(1, 83) = 4.26, p = 0.04, ηp2 = 0.05. As shown in Figure 2, this reflected reduced FA in MDD. The ANCOVA on the remaining ROIs also yielded an effect of Group, F(1, 79) = 20.61, p < 0.001, ηp2 = 0.21, which was qualified by a Group x Gender interaction, F(1, 79) = 3.97, p < 0.05, ηp2 = 0.05. Post-hoc Tukey tests revealed lower FA values in depressed vs. healthy males (mean±SE: controls = 0.55±0.07, MDD = 0.52±0.07, p < 0.001); the effect was not significant in females (controls = 0.53±0.07, MDD = 0.52±0.07, p = 0.28). Importantly, there was also a Group x ROI interaction, F(4, 277) = 11.62, p < 0.001, ηp2 = 0.13. Follow-up ANCOVAs yielded no effect of Group in the MFB, cingulum near the hippocampus, or corona radiata, Fs < 1. However, there were Group effects in the ALIC, F(1, 79) = 9.78, p = 0.002, ηp2 = 0.11, cingulum near the ACC, F(1, 79) = 8.91, p = 0.004, ηp2 = 0.10, and UF, F(1, 79) = 29.50, p < 0.001, ηp2 = 0.27, all reflecting reduced FA in MDD (Figure 2). The difference in the cingulum remained after removing an outlier from the controls, F(1, 80) = 8.66, p = 0.004, ηp2 = 0.10.

Figure 2.

Figure 2

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FA was reduced in the MDD group relative to the control group in four of seven ROIs: the genu of corpus callus, the anterior limb of the internal capsule (ALIC), the cingulum bundle near the ACC, and the uncinate fasciculus. The group difference in the cingulum remained significant after removal of the extreme outlier in the control group. Boxes show quartiles (center line indicates the median), with whiskers extending to 1.5 times the interquartile range.

MD, AD, and RD

In the ROIs that showed group differences in FA, we conducted Group x Gender x ROI x Hemisphere ANCOVAs on MD, AD, and RD. For all three measures, the Group x Hemisphere interaction was significant, Fs > 4.30, ps < 0.05. In controls, follow-up Tukey tests revealed lower values in the left versus right hemisphere for MD (mean±SE: left = 0.70±0.01, right = 0.73±0.01, p < 0.001), AD (left = 1.03±0.01, right = 1.05±0.01, p < 0.03), and RD (left = 0.54±0.01, right = 0.57±0.01, p < 0.001). None of these measures differed by hemisphere in the MDD group (MD: left = 0.73±0.01, right = 0.74±0.01, p = 0.61; AD: left = 1.05±0.01, right = 1.04±0.01, p = 0.99; RD: left = 0.57±0.01, right = 0.58±0.01, p = 0.17). Left hemisphere RD values were lower in healthy versus depressed participants, t(109) = −2.76, p = 0.03. No other effects involving Group were significant.

Relationships with Anhedonia and Depressive Severity

FA

There was a negative relationship between depressive severity (MASQ-GDD) and FA in the genu (r = −0.44, p < 0.01). Anhedonia (MASQ−AD) was negatively related with FA in the genu (r = −0.42, p = 0.01), the cingulum near the ACC (r = −0.43, p = 0.01), and the UF (r = −0.42, p = 0.02). Hierarchical regressions indicated that the association between depressive severity and genu FA was not significant after accounting for anxiety (MASQ-GDA and MASQ-AA), β = −.31, p = 0.10. By contrast, higher anhedonia remained related to lower FA in the genu, cingulum near the ACC, and UF after accounting for anxiety, βs < −0.36, ps < 0.03. Moreover, adding MASQ-AD scores improved the models in each ROI, Fs > 5.69, ps < 0.03, ΔR2s > 0.13. These relationships are shown in Figure 3.

Figure 3.

Figure 3

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Individual differences in anhedonia are related to variation in FA in the genu of the corpus callosum, the cingulum bundle near the ACC, and the uncinate fasciculus.

RD

RD was positively associated with depressive severity and anhedonia in the genu (severity: r = 0.36, p = 0.04; anhedonia: r = 0.44, p = 0.01) and ALIC (severity: r = 0.37, p = 0.04; anhedonia: r = 0.36, p = 0.04). The relationship between severity and RD in the genu did not remain significant after accounting for anxiety, β = 0.20, p = 0.29. However, the link between anhedonia and genu RD did, β = 0.41, p < 0.01, as did both relationships with RD in the ALIC (anhedonia: β = 0.39, p = 0.02; severity: β = 0.54, p = 0.005), all Fs > 5.7, all ΔR2 > 0.14. These associations are shown in Figure 4.

Figure 4.

Figure 4

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Individual differences in anhedonia are related to variation in RD in the genu of the corpus callosum (left) and the anterior limb of the internal capsule (ALIC) (middle); individual differences in depressive severity are also related to variation in RD in the ALIC (right).

Clinical Heterogeneity

We repeated the ANCOVAs on FA after excluding both participants with binge eating disorder. This reduced the group difference in the genu to a trend, F(1, 81) = 3.08, p = 0.08, ηp2 = 0.04, but all other findings were unchanged. Next, we omitted data from controls and re-ran the ANCOVA on FA values three times, dichotomizing the MDD group to capture important clinical phenomena. First, we grouped depressed participants based on the presence (n = 16) vs. absence (n = 22) of comorbid Anxiety. This yielded an Anxiety x ROI x Hemisphere interaction, F(4, 109) = 4.12, p = 0.005, ηp2 = 0.12, but follow-up ANCOVAs in each ROI revealed no main effects of Anxiety and only a trend-level (p = 0.06) Anxiety x Hemisphere interaction in the cingulum near the ACC. Next, we grouped the depressed adults based on whether they did (n = 15) vs. did not (n = 23) report a history of Prior Psychotropics; no effects involving this factor were significant (Fs < 1.42, ps > 0.23). Finally, we grouped depressed adults according to whether they were (n = 11) vs. were not (n = 27) in their first episode. This yielded an Episode x Gender interaction, F(1, 29) = 4.59, p = 0.04, ηp2 = 0.14; follow-up t-tests revealed a gender difference for individuals in their first episode (females = 0.43±0.01, males = 0.45±0.01, t(9) = −2.60, p = 0.03, g = 1.76), but not for those in recurrence (females = 0.43±0.01, males = 0.43±0.01, t(22) < 1, p = 0.83, g = 0.09).

Discussion

This analysis yielded two main results. First, relative to controls, depressed adults showed reduced FA in the genu of the corpus callosum, the ALIC, the cingulum near the ACC, and the UF. This pattern is consistent with prior studies (Bracht et al., 2015; Chen et al., 2016). Second, partial correlations revealed negative relationships between anhedonia and FA in the genu, cingulum near the ACC, and the UF, as well as positive relationships between (1) anhedonia and RD in the genu and ALIC, and (2) depressive severity and RD in the ALIC. Critically, these relationships remained significant after accounting for anxiety. This second set of findings is noteworthy because few studies have examined the relationship between FA and anhedonia, and none have demonstrated that such relationships persist after controlling for anxiety. These results strengthen the case for a negative effect of anhedonia (and depressive severity) on the structural integrity of white matter pathways in depressed adults, with effects again emerging in the genu, cingulum, UF, and ALIC (Bracht et al., 2015b).

The cause of reduced FA in the depressed sample is unclear, but the associations with increased RD are striking as they suggest an underlying mechanism (for additional evidence of reduced FA and increased RD in depression, see Henderson et al., 2013). Specifically, several rodent studies have linked increased RD to reduced myelination. For example, Song et al. (2002) reported that, compared to wild-type mice, shiverer mice—who lack myelin due to a genetic mutation (Readhead & Hood, 1990)—showed normal AD and MD values but significantly elevated RD in several brain regions. Similarly, experimentally manipulating the myelination status of the corpus callosum in wild-type mice caused corresponding changes in RD, not AD (Song et al., 2005). By contrast, inducing ischemia to damage axons caused rapid reductions in AD and MD but not RD, indicating that RD is not particularly sensitive to nerve damage (Song et al., 2003). Therefore, increased RD appears to reflect demyelination, not nerve damage. Consistent with this hypothesis, RD was a sensitive marker of demyelination in spinal cord samples taken from humans with multiple sclerosis (Klawiter et al., 2011). Therefore, demyelination may contribute to lowered FA in the MDD group. This account is speculative, and because of technical complexities (Wheeler-Kingshott & Cercignani, 2009), a definitive account of reduced FA in MDD awaits future studies. However, supporting our interpretation, a post-mortem study found reduced myelination of deep white matter tracts in adults with unipolar or bipolar depression vs. healthy controls (Regenold et al., 2007).

The cause of an association between depression and disrupted myelination is unknown, but Sacchet and Gotlib (2017) highlighted two candidate mechanisms. In a quantitative MRI study, they used the longitudinal relaxation rate R1 (1/T1) as a proxy for myelination status, and found that myelination was reduced in depressed vs. healthy adults at the whole-brain level and particularly in the nucleus accumbens. Because myelination is dynamic and changes with experience (Fields, 2008), one possibility is that brain activity is reduced overall in depressed adults, which leads to broad reductions in myelination. A second possibility is that psychosocial stress—a potent risk factor for initial depressive episodes (Monroe & Harkness, 2005)—induces inflammation, which produces cytokines that degrade myelin. It is unclear whether either of these accounts is correct, but they offer testable accounts of reduced myelination in depression.

Finally, the fact that Sacchet and Gotlib (2017) detected reduced nucleus accumbens myelination in MDD suggests that white matter changes may contribute to anhedonia in depression. The current findings strengthen this argument. As reviewed by Haber and Behrens (2014), the cingulum bundle and the UF are major dorsal and ventral “limbic” white matter tracts that connect the frontal, temporal, and parietal lobes, while the internal capsule—including the ALIC—connects the PFC with subcortical structures. These pathways join regions that contribute directly to reinforcement learning by coding reward value (ventromedial PFC), maintaining stimulus-reward associations (orbitofrontal cortex), and guiding action selection (dorsal ACC). Therefore, the observation of reliable correlations between anhedonia and both FA and RD in these tracts supports the hypothesis that structural abnormalities in reward network connections contribute to the pathophysiology of anhedonic depression. In this context, it is noteworthy that the cingulum bundle, UF, and ALIC are all targeted by deep brain stimulation or psychosurgery for depression and anxiety (Haber & Behrens, 2014).

This study is strengthened by the well-characterized and unmedicated depressed sample. However, there are several limitations. First, with only six diffusion-encoding gradient directions, we cannot perform probabilistic tractography or tract-based spatial statistics. Additional research using improved DTI methodologies is clearly warranted. Second, partial volume effects may have occurred during resampling, although we limited this by extracting DTI from voxels with FA values > 0.2. Third, the partial correlations were exploratory and would not survive Bonferroni correction. Finally, there was clinical heterogeneity in our MDD sample, although our analysis of comorbid anxiety, past psychotropic use, and first episode vs. recurrence suggested limited effects of these factors.

Conclusion

This study contributes to the literature on structural connectivity in depression. In addition to replicating previously observed group differences in FA, we related reduced FA and increased RD to variation in anhedonia and depressive severity, controlling for anxiety. It would be valuable to investigate the physiological basis for these effects (Wheeler-Kingshott & Cercignani, 2009). Given the heterogeneity of MDD and evidence that FA may be sensitive to MDD chronicity (Chen et al., 2016), it would also be useful to compare depressive subtypes (melancholic vs. atypical) in larger samples (Bracht et al., 2014).

Acknowledgments

This work was supported by the National Institute of Mental Health (D.D., grant numbers F32MH081394, K99MH094438, R00MH094438), (D.P., grant numbers R01MH068376, R01MH101521), and the Brain and Behavior Research Foundation (D.D., Young Investigator Award). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. In the last three years, Dr. Dillon has received consulting fees from Pfizer Inc., and Dr. Pizzagalli has received consulting fees from Akili Interactive Lab, BlackThorn Therapeutics, Boehreinger Ingelheim, Pfizer Inc. and Posit Science, for activities unrelated to the current research. All other authors report no biomedical financial interests.

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