Artigo Revisado por pares

Reduced Functional Connectivity in Brain Networks Underlying Paired Associates Memory Encoding in Schizophrenia

2021; Elsevier BV; Volume: 8; Issue: 1 Linguagem: Inglês

10.1016/j.bpsc.2021.07.003

ISSN

2451-9030

Autores

Meighen Roes, Abhijit Chinchani, Todd S. Woodward,

Tópico(s)

Mental Health Research Topics

Resumo

Deficits in relational episodic memory encoding are characteristic of schizophrenia (SZ), but whole-brain multivariate analyses of these deficits have been lacking. Open science has provided task-based functional magnetic resonance imaging (fMRI) data investigating paired associate encoding in SZ, but it has not yet been mobilized to address this gap in the literature. Therefore, in this study, we use previously unpublished task fMRI data to conduct the first network-level investigation of impaired relational episodic encoding in SZ. Using fMRI data acquired from 40 healthy control participants and 40 age- and sex-matched persons with SZ, we examined the networks involved in successful versus unsuccessful encoding of verbal paired associates using an associative semantic strategy. Constrained principal component analysis for fMRI revealed 3 distinct functional networks recruited during encoding: a responding network, a linguistic processing/attention network, and the default mode network. Relative to the healthy control group, the SZ group exhibited aberrant activity in all 3 networks during successful encoding; namely, hypoactivation in the linguistic processing/attention network, lower peak activation in the responding network, and weaker suppression in the default mode network. Independent of group effects, a pattern of stronger anticorrelating linguistic processing/attention–default mode network activity during successful encoding significantly predicted subsequent retrieval of paired associates. Together with previous observations of language network hypoactivation during controlled semantic processes, these results suggest that abnormalities in networks representing language and meaning may contribute to difficulties employing deep semantic strategies during relational episodic encoding in SZ.

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