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SO247

Examining moment-to-moment neural variability in treatment-resistant depression

INVESTIGATING MOMENT-TO-MOMENT NEURAL VARIABILITY IN TREATMENT-RESISTANT DEPRESSION

In treatment-resistant depression, lower resting-state neural variability, particularly in the putamen and anterior cingulate cortex, is associated with greater depressive symptom severity.

The study aimed to determine whether resting-state neural variability is associated with depressive symptom severity in treatment-resistant depression (TRD). Resting-state functional magnetic resonance imaging (fMRI) data were acquired at 3T from forty-eight patients with TRD (n=48; 56.2% male, mean age 39), with a scan duration of 6 minutes and 41 seconds. Neural variability was defined as the temporal standard deviation of voxelwise blood oxygen level-dependent (BOLD) signals (SDBOLD, k=56,025 voxels); depression severity was measured using the Hamilton Depression Rating Scale (HDRS), and whole-brain voxelwise data were analyzed using partial least squares (PLS), with 1,000 bootstrap samples and 1,000 permutations, at a BSR threshold of ±3. Lower resting-state neural variability, particularly in the putamen and anterior cingulate cortex (ACC), was associated with greater depressive symptom severity (Pearson r=0.45; permutation p=0.03; BSR=±3); the model remained significant after adjustment for age and sex (R2=0.17; p=0.01). At the regional level, negative correlations were identified in the left subgenual ACC (r=0.49), right subgenual ACC (r=0.49), left putamen (r=0.45), and right putamen (r=0.50) (all p<0.01). No fluctuations in neural variability were observed within the resting-state session (permutation p=0.086); HDRS scores decreased significantly from pretreatment (19.3) to after the first ketamine infusion (12.7) and after the fourth infusion (8.7) (T1 to T2: t(47)=9.18, p<0.001; T2 to T3: t(43)=4.48, p<0.001). The authors conclude that neural variability associated with the reward network may capture individual differences in depressive symptom severity and plan to investigate whether pretreatment neural variability can predict treatment response as a next step.

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