Basic stimulus processing alterations from top-down cognitive control in depression drive independent temporal components of multi-echo naturalistic fMRI data

Abstract

Perceptual changes in major depressive disorder (MDD) may extend beyond emotional content and include the processing of basic stimulus features. These alterations may ultimately contribute to perceptual bias and anhedonia. To characterize blood oxygen level-dependent (BOLD) signal of perceptual processing, we investigated temporally independent fMRI signal components related to naturalistic stimulus processing in 39 patients with MDD and 36 healthy subjects. Leveraging the capability of multi-echo data to detect BOLD activity changes, we extracted physiologically meaningful group temporal components. For each component that exhibited a significant correlation with the movie content, we localized its underlying brain network and assessed MDD-associated alterations. Two components exhibited significant group differences; one was associated with auditory features (sound pressure level) and one with visual features (temporal contrast of intensity). Notably, these deficits in MDD localized primarily to higher-order processing areas, such as the dorsal prefrontal cortex and insula, rather than primary sensory cortices. For the visual feature component, additional group differences emerged in non-visual primary sensory cortices (auditory and somatosensory) as well as major hubs of the motor system. Our findings support the hypothesis that basic sensory processing deficits represent an inherent feature of MDD which may contribute to anhedonia and negative perceptual bias. These deficits are primarily confined to higher-order processing units, as well as cross-modal primary sensory cortices indicating predominant dysfunction of top-down control and multisensory integration. Therapeutic effects of interventions targeting the prefrontal cortex may be partially mediated by restoring prefrontal control not only over emotional but also sensory processing hubs.

Fig. 1. Schematic overview of this study.

A Multi-echo EPI data were collected during a 20-minute movie clip viewing session (“Lola Rennt”). B Individual BOLD fluctuations identification based on three-way decomposition of the ME-EPI data. The data were first decomposed into spatial, temporal, and TE domains. Components exhibiting BOLD patterns (bell-shaped) across TEs were identified as BOLD changes. C Extraction of group temporal components using ICA. The BOLD fluctuations from all subjects were concatenated, forming a matrix of all BOLD time series. ICA was then utilized to decompose the group time series and derive the underlying shared responses at the group level. D Further analyses contained in the context of the group temporal components in this study.

Fig. 2. Representative group components (GTC) with significant stimulus correlations and their underlying brain maps (t-value).

A GTC #1 (blue line: normalized time course over the 20 min video) correlated significantly (cc = 0.677, p < 0.001) with the manually annotated presence of language after convolution with hemodynamic response function (red line). The statistical map projected on the brain surface reflects a linear regression with this GTC. B GTC #8 correlated with the presence of faces (cc = 0.480, p < 0.001). C and D Two GTCs yielded significant ccs with basic stimulus features extracted from the video (red line) and audio signal (yellow line; see text for details). (GTC: group temporal components; cc: correlation coefficient).

Fig. 3. Group differences emerged in the mapping of two shared responses (p < 0.05 FWE-corrected).

Both these GTCs were characterized by sensory processing. A GTC #4 correlated with sound pressure level and revealed group differences in the left dorsal prefrontal dominant area between HC and MDD groups. B GTC #15 correlated with a visual stimulus feature and with group differences in four left hemispheric clusters around the SFG, pre- and postcentral gyrus, insula, and thalamus.

Fig. 4. Brain alterations and relationship with clinical symptom severity.

A Beta values from clusters with significant group differences (error bar is the standard error of the mean). B Significant correlations between peaks from group differences and depression severity (BDI-II score).