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Predicting individual variability in task-evoked brain activity in schizophrenia.

ABSTRACT: What goes wrong in a schizophrenia patient's brain that makes it so different from a healthy brain? In this study, we tested the hypothesis that the abnormal brain activity in schizophrenia is tightly related to alterations in brain connectivity. Using functional magnetic resonance imaging (fMRI), we demonstrated that both resting-state functional connectivity and brain activity during the well-validated N-back task differed significantly between schizophrenia patients and healthy controls. Nevertheless, using a machine-learning approach we were able to use resting-state functional connectivity measures extracted from healthy controls to accurately predict individual variability in the task-evoked brain activation in the schizophrenia patients. The predictions were highly accurate, sensitive, and specific, offering novel insights regarding the strong coupling between brain connectivity and activity in schizophrenia. On a practical perspective, these findings may allow to generate task activity maps for clinical populations without the need to actually perform any tasks, thereby reducing patients inconvenience while saving time and money.

SUBMITTER: Tik N

PROVIDER: S-EPMC8288090 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature

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Predicting individual variability in task-evoked brain activity in schizophrenia.

Tik Niv N Livny Abigail A Gal Shachar S Gigi Karny K Tsarfaty Galia G Weiser Mark M Tavor Ido I

Human brain mapping 20210522 12

What goes wrong in a schizophrenia patient's brain that makes it so different from a healthy brain? In this study, we tested the hypothesis that the abnormal brain activity in schizophrenia is tightly related to alterations in brain connectivity. Using functional magnetic resonance imaging (fMRI), we demonstrated that both resting-state functional connectivity and brain activity during the well-validated N-back task differed significantly between schizophrenia patients and healthy controls. Neve ...[more]

PMID: 34021674

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Project description:Investigations of between-person variability are enjoying a recent resurgence in functional magnetic resonance imaging (fMRI) research. Several recent studies have found persistent between-person differences in blood-oxygenated-level dependent (BOLD) activation patterns and resting-state functional connectivity. Conflicting findings have been reported regarding the extent to which (a) between-person or (b) within-person cognitive state differences explain differences in BOLD activation patterns. These discrepancies may arise due to statistical analysis choices, parcellation resolution, and limited sampling of task-fMRI datasets. We attempt to address these issues in a large-scale analysis of several task-fMRI paradigms. Using a novel application of multivariate distance matrix regression, we examine between-person and task-condition variability estimates across varying levels of "resolution", from a coarse region-of-interest level to the vertex-level, and across different distance metrics. These analyses revealed that under most circumstances, differences in task conditions explained a greater amount of variance in activation map differences than between-person differences. However, this finding was reversed when comparing activation maps at a "high-resolution" vertex level. More generally, we observed that when moving from "low" to "high" resolutions, the variance explained by between-person differences increased while variance explained by task conditions decreased. We further analyzed the relationships among subject-level activation maps across all task-conditions using an unsupervised clustering approach and identified a superordinate task structure. This structure went beyond conventional task labels and highlighted those experimental manipulations across task conditions that produce contrasting versus similar whole-brain activation patterns. Overall, these analyses suggest that the question of the subject- versus task-effects on BOLD activation patterns is nontrivial, and depends on the comparison "resolution," choice of distance metric, and the coding of task-conditions.

Project description:ObjectivesPeople with Schizophrenia (SZ) show deficits in auditory and audiovisual speech recognition. It is possible that these deficits are related to aberrant early sensory processing, combined with an impaired ability to utilize visual cues to improve speech recognition. In this electroencephalography study we tested this by having SZ and healthy controls (HC) identify different unisensory auditory and bisensory audiovisual syllables at different auditory noise levels.MethodsSZ (N = 24) and HC (N = 21) identified one of three different syllables (/da/, /ga/, /ta/) at three different noise levels (no, low, high). Half the trials were unisensory auditory and the other half provided additional visual input of moving lips. Task-evoked mediofrontal N1 and P2 brain potentials triggered to the onset of the auditory syllables were derived and related to behavioral performance.ResultsIn comparison to HC, SZ showed speech recognition deficits for unisensory and bisensory stimuli. These deficits were primarily found in the no noise condition. Paralleling these observations, reduced N1 amplitudes to unisensory and bisensory stimuli in SZ were found in the no noise condition. In HC the N1 amplitudes were positively related to the speech recognition performance, whereas no such relationships were found in SZ. Moreover, no group differences in multisensory speech recognition benefits and N1 suppression effects for bisensory stimuli were observed.ConclusionOur study suggests that reduced N1 amplitudes reflect early auditory and audiovisual speech processing deficits in SZ. The findings that the amplitude effects were confined to salient speech stimuli and the attenuated relationship with behavioral performance in patients compared to HC, indicates a diminished decoding of the auditory speech signals in SZs. Our study also revealed relatively intact multisensory benefits in SZs, which implies that the observed auditory and audiovisual speech recognition deficits were primarily related to aberrant processing of the auditory syllables.

Dataset Information

Predicting individual variability in task-evoked brain activity in schizophrenia.

Publications

Predicting individual variability in task-evoked brain activity in schizophrenia.

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