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

Roes, Meighen; Chinchani, Abhijit; Woodward, Todd S.

doi:10.1016/j.bpsc.2021.07.003

Cited by 3 publications

(6 citation statements)

References 86 publications

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“…components and the data-driven networks they estimated. The HDRs are also presented in Figure 4; the temporal features of the modeled networks were also confirmed, and all Group, Time, and Encoding effects were reproduced exactly (omitted here for brevity -see Roes et al, 2021). Finally, as predicted, the 𝑃 % predictor weights specifying the relation of each data-driven network in 𝐻 and its 𝐺𝑀𝐻 !…”

Section: Test Case 1 (All Data-driven Network In H)supporting

confidence: 61%

“…Combining temporal and spatial constraints in task-based fMRI Constrained Principal Component Analysis for fMRI (fMRI-CPCA) has emerged as a reliable data-driven method for extraction of task-based brain networks from fMRI data, including their associated hemodynamic response shapes, which are interpreted to determine cognitive functions (e.g., Damascelli et al, 2021;Larivière et al, 2017;Lavigne, Menon, Moritz, & Woodward, 2020;Metzak et al, 2011;Metzak et al, 2012;Roes, Chinchani, & Woodward, 2021;Sanford, Whitman, & Woodward, 2020;Whitman, Metzak, Lavigne, & Woodward, 2013;Wong et al, 2020;Woodward et al, 2006;. In its standard application, prior to dimension reduction, variability in blood oxygen level dependent (BOLD) signal is constrained to that portion which is predictable from task timing for the specific task under study.…”

Section: Impact Statementmentioning

confidence: 99%

“…The test case data matrix 𝑍 and design matrix 𝐺 have already been described in Roes et al, (2021). Briefly, the 𝑍 matrix contained BOLD intensity values for 76470 voxels over RESP, a language/attention network; LANG/ATTN, and the default mode network; DMN) accounted for 18.50%, 12.97%, and 8.02% of the task-timing related variance in BOLD signal, respectively.…”

Section: Test Case Datamentioning

confidence: 99%

“…The analyses reported in this manuscript make secondary use of data originally collected as part of the UCLA Consortium for Neuropsychiatric Phenomics LA5c Study (Poldrack et al, 2016). The fMRI task data were obtained from the OpenfMRI database (https://openfmri.org/dataset/ds000030, accession number ds000030), as reported in Roes et al, (2021).…”

Section: Acknowledgmentsmentioning

confidence: 99%

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Combining temporal and spatial constraints in task-based fMRI

Roes¹,

Takane²,

Woodward

2022

Preprint

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Constrained principal component analysis for fMRI (fMRI-CPCA) is carried out in two main steps: (1) blood-oxygen-level dependent (BOLD) signal is row (time)-constrained to variance predictable from a finite impulse response (FIR) model, and (2) task-based networks and their associated estimated hemodynamic response shapes (HDR) are extracted through dimension reduction. In the current study, we introduce a novel methodology that additionally employs anatomical patterns as constraints on columns (voxels). We refer to this as spatiotemporal fMRI-CPCA (ST-fMRI-CPCA). In a series of analyses, we demonstrate that ST-fMRI-CPCA accurately portions the row (time)-constrained variance into that which is predictable (and not) from network-level constraints on columns (voxels). This method can be used to compare spatial models (e.g., competing network sets) on their ability to account for the task-timing-related brain networks measurable by fMRI.

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Section: Test Case 1 (All Data-driven Network In H)supporting

confidence: 61%

Section: Impact Statementmentioning

confidence: 99%

Section: Test Case Datamentioning

confidence: 99%

Section: Acknowledgmentsmentioning

confidence: 99%

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Combining temporal and spatial constraints in task-based fMRI

Roes¹,

Takane²,

Woodward

2022

Preprint

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“…Notably, individuals with SZ exhibited hypoactivity within the semantic network and inefficiency in suppressing the DMN. The author suggests that the patient’s capacity to employ semantic strategies during episodic memory encoding may be limited ( 23 ).…”

Section: Resultsmentioning

confidence: 99%

Aberrant brain language network in schizophrenia spectrum disorder: a systematic review of its relation to language signs beyond symptoms

Alonso-Sanchez,

Z-Rivera,

Otero

et al. 2024

Front. Psychiatry

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BackgroundLanguage disturbances are a core feature of schizophrenia, often studied as a formal thought disorder. The neurobiology of language in schizophrenia has been addressed within the same framework, that language and thought are equivalents considering symptoms and not signs. This review aims to systematically examine published peer-reviewed studies that employed neuroimaging techniques to investigate aberrant brain-language networks in individuals with schizophrenia in relation to linguistic signs.MethodsWe employed a language model for automatic data extraction. We selected our studies according to the PRISMA recommendations, and we conducted the quality assessment of the selected studies according to the STROBE guidance.ResultsWe analyzed the findings from 37 studies, categorizing them based on patient characteristics, brain measures, and language task types. The inferior frontal gyrus (IFG) and superior temporal gyrus (STG) exhibited the most significant differences among these studies and paradigms.ConclusionsWe propose guidelines for future research in this field based on our analysis. It is crucial to investigate larger networks involved in language processing, and language models with brain metrics must be integrated to enhance our understanding of the relationship between language and brain abnormalities in schizophrenia

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