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A prediction model of working memory across health and psychiatric disease using whole-brain functional connectivity.

ABSTRACT: Working memory deficits are present in many neuropsychiatric diseases with diagnosis-related severity. However, it is unknown whether this common behavioral abnormality is a continuum explained by a neural mechanism shared across diseases or a set of discrete dysfunctions. Here, we performed predictive modeling to examine working memory ability (WMA) as a function of normative whole-brain connectivity across psychiatric diseases. We built a quantitative model for letter three-back task performance in healthy participants, using resting state functional magnetic resonance imaging (rs-fMRI). This normative model was applied to independent participants (N = 965) including four psychiatric diagnoses. Individual's predicted WMA significantly correlated with a measured WMA in both healthy population and schizophrenia. Our predicted effect size estimates on WMA impairment were comparable to previous meta-analysis results. These results suggest a general association between brain connectivity and working memory ability applicable commonly to health and psychiatric diseases.

SUBMITTER: Yamashita M

PROVIDER: S-EPMC6324880 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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A prediction model of working memory across health and psychiatric disease using whole-brain functional connectivity.

Yamashita Masahiro M Yoshihara Yujiro Y Hashimoto Ryuichiro R Yahata Noriaki N Ichikawa Naho N Sakai Yuki Y Yamada Takashi T Matsukawa Noriko N Okada Go G Tanaka Saori C SC Kasai Kiyoto K Kato Nobumasa N Okamoto Yasumasa Y Seymour Ben B Takahashi Hidehiko H Kawato Mitsuo M Imamizu Hiroshi H

eLife 20181210

Working memory deficits are present in many neuropsychiatric diseases with diagnosis-related severity. However, it is unknown whether this common behavioral abnormality is a continuum explained by a neural mechanism shared across diseases or a set of discrete dysfunctions. Here, we performed predictive modeling to examine working memory ability (WMA) as a function of normative whole-brain connectivity across psychiatric diseases. We built a quantitative model for letter three-back task performan ...[more]

PMID: 30526859

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Project description:Brain connectivity analysis plays an essential role in the research of working memory that involves complex coordination of various brain regions. In this research, we present a comprehensive view of trans-states brain connectivity variation based on continuous scalp EEG, extending beyond traditional stimuli-lock averaging or restriction to short time scales of hundreds of milliseconds after stimulus onset. The scalp EEG was collected under three conditions: quiet, memory, and control. The only difference between the memory and control conditions was that in the memory condition, subjects made an effort to retain information. We started our investigation with calibrations of Pearson correlation in EEG analysis and then derived two indices, link strength and node connectivity, to make comparisons between different states. Finally, we constructed and studied trans-state brain connectivity variation topography. Comparing memory and control states with quiet state, we found that the beta topography highlights links between T5/T6 and O1/O2, which represents the visual ventral stream, and the gamma topography conveys strengthening of inter-hemisphere links and weakening of intra-hemisphere frontal-posterior links, implying parallel inter-hemisphere coordination combined with sequential intra-hemisphere coordination when subjects are confronted with visual stimuli and a motor task. For comparison between memory and control states, we also found that the node connectivity of T6 stands out in gamma topography, which provides strong proof from scalp EEG for the information binding or relational processing function of the temporal lobe in memory formation. To our knowledge, this is the first time for any method to effectively capture brain connectivity variation associated with working memory from a relatively large scale both in time (from a second to a minute) and in space (from the scalp). The method can track brain activity continuously with minimal manual interruptions; therefore, it has promising potential in applications such as brain computer interfaces and brain training.

Project description:ObjectiveWorking memory (WM) deficits are consistently reported in schizophrenia and are related to poor functional outcomes. Functional magnetic resonance imaging studies of adult-onset schizophrenia have reported decreased functional activations and connectivity in the WM network, but no prior functional magnetic resonance imaging study has examined WM in childhood-onset schizophrenia (COS). The aim of this study was to examine the neural correlates of WM in COS.MethodAdult patients with COS (n = 32, 21.3 ± 1.1 years), nonpsychotic siblings of patients with COS (n = 30, 19.4 ± 0.8 years), and healthy controls (n = 39, 20.0 ± 0.7 years) completed 1- and 2-back WM tasks during 3-T functional magnetic resonance imaging. Functional activation and connectivity analyses were conducted. A separate group of 23 younger patients with COS (17.9 ± 7.4 years) could not perform the tasks after twice completing a standard training and are not included in this report.ResultsPatients with COS who were included scored significantly lower than controls on all tasks (p < .001). Patients with COS showed significantly lower activations in the dorsolateral prefrontal cortices, posterior parietal cortices, cerebellum, and caudate and decreased frontoparietal and corticostriatal functional connectivity compared with controls (p < .05, corrected). Siblings had functional activations and connectivity intermediate between those of patients and controls in a similar set of regions (p < .05, corrected). In patients, functional connectivity strength in the left frontoparietal network correlated positively with accuracy scores during the 1-back task (p = .0023, corrected).ConclusionDecreased functional activation and connectivity in the WM network in COS supports pathophysiologic continuity with adult-onset schizophrenia. The low participation rate and accuracy of the patients highlights the disease severity of COS. Hypo-activations and hypo-connectivity were shared by siblings of patients with COS, suggesting COS as a potential endophenotype.Clinical trial registration informationEvaluating Genetic Risk Factors for Childhood-Onset Schizophrenia; http://ClinicalTrials.gov;NCT00001198.

Project description:Obstructive sleep apnea (OSA) is characterized by the frequent presence of neuro-cognitive impairment. Recent studies associate cognitive dysfunction with altered resting-state brain connectivity between key nodes of the executive and default-mode networks, two anti-correlated functional networks whose strength of activation increases or decreases with cognitive activity, respectively. To date no study has investigated a relationship between cognitive impairment in OSA and brain connectivity during an active working-memory challenge. We thus investigated the effect of OSA on working-memory performance and underlying brain connectivity. OSA patients and matched healthy controls underwent functional magnetic resonance imaging (fMRI) scanning while performing a 2-back working-memory task. Standard fMRI analyses highlighted the brain regions activated at increasing levels of working-memory load, which were used as seeds in connectivity analyses. The latter were based on a multiregional Psycho-Physiological-Interaction (PPI) approach, to unveil group differences in effective connectivity underlying working-memory performance. Compared with controls, in OSA patients normal working-memory performance reflected in: a) reduced interhemispheric effective connectivity between the frontal "executive" nodes of the working-memory network, and b) increased right-hemispheric connectivity among regions mediating the "salience-based" switch from the default resting-state mode to the effortful cognitive activity associated with the executive network. The strength of such connections was correlated, at increasing task-demands, with executive (Stroop test) and memory (Digit Span test) performance in neuro-cognitive evaluations. The analysis of effective connectivity changes during a working-memory challenge provides a complementary window, compared with resting-state studies, on the mechanisms supporting preserved performance despite functional and structural brain modifications in OSA.

Dataset Information

A prediction model of working memory across health and psychiatric disease using whole-brain functional connectivity.

Publications

A prediction model of working memory across health and psychiatric disease using whole-brain functional connectivity.

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