Multimodal Neuroimaging Study of Visual Plasticity in Schizophrenia.
Ontology highlight
ABSTRACT:
SUBMITTER: Wijtenburg SA
PROVIDER: S-EPMC8046908 | biostudies-literature | 2021
REPOSITORIES: biostudies-literature
Publications
Multimodal Neuroimaging Study of Visual Plasticity in Schizophrenia.
Wijtenburg S Andrea SA West Jeffrey J Korenic Stephanie A SA Kuhney Franchesca F Gaston Frank E FE Chen Hongji H Rowland Laura M LM
Frontiers in psychiatry 20210401
Schizophrenia is a severe mental illness with visual learning and memory deficits, and reduced long term potentiation (LTP) may underlie these impairments. Recent human fMRI and EEG studies have assessed visual plasticity that was induced with high frequency visual stimulation, which is thought to mimic an LTP-like phenomenon. This study investigated the differences in visual plasticity in participants with schizophrenia and healthy controls. An fMRI visual plasticity paradigm was implemented, a ...[more]
Similar Datasets
Project description:In this paper we describe an open-access collection of multimodal neuroimaging data in schizophrenia for release to the community. Data were acquired from approximately 100 patients with schizophrenia and 100 age-matched controls during rest as well as several task activation paradigms targeting a hierarchy of cognitive constructs. Neuroimaging data include structural MRI, functional MRI, diffusion MRI, MR spectroscopic imaging, and magnetoencephalography. For three of the hypothesis-driven projects, task activation paradigms were acquired on subsets of ~200 volunteers which examined a range of sensory and cognitive processes (e.g., auditory sensory gating, auditory/visual multisensory integration, visual transverse patterning). Neuropsychological data were also acquired and genetic material via saliva samples were collected from most of the participants and have been typed for both genome-wide polymorphism data as well as genome-wide methylation data. Some results are also presented from the individual studies as well as from our data-driven multimodal analyses (e.g., multimodal examinations of network structure and network dynamics and multitask fMRI data analysis across projects). All data will be released through the Mind Research Network's collaborative informatics and neuroimaging suite (COINS).
| S-EPMC5671541 | biostudies-literature
Project description:Prefrontal-parietal networks are essential to many cognitive processes, including the ability to differentiate new from previously presented items. As patients with schizophrenia exhibit structural abnormalities in these areas along with well documented decrements in recognition memory, we hypothesized that these patients would demonstrate memory-related abnormalities in prefrontal and parietal physiology as measured by both functional magnetic resonance imaging and magnetoencephalography (MEG). Medicated outpatients with schizophrenia (n = 18) and age-matched healthy control subjects (n = 18) performed an old-new recognition memory task while physiological data were obtained. Whereas controls exhibited strong, bilateral activation of prefrontal and posterior parietal regions during successful identification of old versus new items, patients exhibited greatly attenuated activation of the right prefrontal and parietal cortices. However, within the patient group, there was strong correlation between memory performance and activation of these right-sided regions as well as a tight correlation between old-new effect-related activations in frontal and parietal regions, a pattern not seen in control subjects. Using MEG, control subjects-but not patients-exhibited a sequential pattern of old > new activity in the left posterior parietal cortex and then right prefrontal cortex; however, patients uniquely exhibited old > new activity in right temporal cortex. Collectively, these findings point to markedly different distributions of regional specialization necessary to complete the old-new item recognition task in patients versus controls. Inefficient utilization of prefrontal-parietal networks, with compensatory activation in temporal regions, may thus contribute to deficient old-new item recognition in schizophrenia.
| S-EPMC2768128 | biostudies-other
Project description:BackgroundThe cognitive deficits of schizophrenia are largely resistant to current treatments and thus are a lifelong illness burden. The Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery (MCCB) provides a reliable and valid assessment of cognition across major cognitive domains; however, the multimodal brain alterations specifically associated with MCCB in schizophrenia have not been examined.MethodsThe interrelationships between MCCB and the abnormalities seen in three types of neuroimaging-derived maps-fractional amplitude of low-frequency fluctuations (fALFF) from resting-state functional magnetic resonance imaging (MRI), gray matter (GM) density from structural MRI, and fractional anisotropy from diffusion MRI-were investigated by using multiset canonical correlation analysis in data from 47 schizophrenia patients treated with antipsychotic medications and 50 age-matched healthy control subjects.ResultsOne multimodal component (canonical variant 8) was identified as both group differentiating and significantly correlated with the MCCB composite. It demonstrated 1) increased cognitive performance associated with higher fALFF (intensity of regional spontaneous brain activity) and higher GM volumes in thalamus, striatum, hippocampus, and the mid-occipital region, with co-occurring fractional anisotropy changes in superior longitudinal fascicules, anterior thalamic radiation, and forceps major; 2) higher fALFF but lower GM volume in dorsolateral prefrontal cortex related to worse cognition in schizophrenia; and 3) distinct domains of MCCB might exhibit dissociable multimodal signatures, e.g., increased fALFF in inferior parietal lobule particularly correlated with decreased social cognition. Medication dose did not relate to these findings in schizophrenia.ConclusionsOur results suggest linked functional and structural deficits in distributed cortico-striato-thalamic circuits may be closely related to MCCB-measured cognitive impairments in schizophrenia.
| S-EPMC4547923 | biostudies-literature
Project description:Background and hypothesisSchizophrenia is a multidimensional disease. This study proposes a new research framework that combines multimodal meta-analysis and genetic/molecular architecture to solve the consistency in neuroimaging biomarkers of schizophrenia and whether these link to molecular genetics.Study designWe systematically searched Web of Science, PubMed, and BrainMap for the amplitude of low-frequency fluctuations (ALFF) or fractional ALFF, regional homogeneity, regional cerebral blood flow, and voxel-based morphometry analysis studies investigating schizophrenia. The pooled-modality, single-modality, and illness duration-dependent meta-analyses were performed using the activation likelihood estimation algorithm. Subsequently, Spearman correlation and partial least squares regression analyses were conducted to assess the relationship between identified reliable convergent patterns of multimodality and neurotransmitter/transcriptome, using prior molecular imaging and brain-wide gene expression.Study resultsIn total, 203 experiments comprising 10 613 patients and 10 461 healthy controls were included. Multimodal meta-analysis showed that brain regions of significant convergence in schizophrenia were mainly distributed in the frontotemporal cortex, anterior cingulate cortex, insula, thalamus, striatum, and hippocampus. Interestingly, the analyses of illness-duration subgroups identified aberrant functional and structural evolutionary patterns: Lines from the striatum to the cortical core networks to extensive cortical and subcortical regions. Subsequently, we found that these robust multimodal neuroimaging abnormalities were associated with multiple neurobiological abnormalities, such as dopaminergic, glutamatergic, serotonergic, and GABAergic systems.ConclusionsThis work links transcriptome/neurotransmitters with reliable structural and functional signatures of brain abnormalities underlying disease effects in schizophrenia, which provides novel insight into the understanding of schizophrenia pathophysiology and targeted treatments.
| S-EPMC10686354 | biostudies-literature
Project description:This work proposes a novel generative multimodal approach to jointly analyze multimodal data while linking the multimodal information to colors. We apply our proposed framework, which disentangles multimodal data into private and shared sets of features from pairs of structural (sMRI), functional (sFNC and ICA), and diffusion MRI data (FA maps). With our approach, we find that heterogeneity in schizophrenia is potentially a function of modality pairs. Results show (1) schizophrenia is highly multimodal and includes changes in specific networks, (2) non-linear relationships with schizophrenia are observed when interpolating among shared latent dimensions, and (3) we observe a decrease in the modularity of functional connectivity and decreased visual-sensorimotor connectivity for schizophrenia patients for the FA-sFNC and sMRI-sFNC modality pairs, respectively. Additionally, our results generally indicate decreased fractional corpus callosum anisotropy, and decreased spatial ICA map and voxel-based morphometry strength in the superior frontal lobe as found in the FA-sFNC, sMRI-FA, and sMRI-ICA modality pair clusters. In sum, we introduce a powerful new multimodal neuroimaging framework designed to provide a rich and intuitive understanding of the data which we hope challenges the reader to think differently about how modalities interact.
| S-EPMC10619380 | biostudies-literature
Project description:Previous studies have observed impairments in both brain function and neurometabolite levels in schizophrenia. In this study, we investigated the relationship between brain activity and neurochemistry in off-medication patients with schizophrenia and if this relationship is altered following antipsychotic medication by combining proton magnetic resonance spectroscopy (1H-MRS) with functional magnetic resonance imaging (fMRI). We used single voxel MRS acquired in the bilateral dorsal anterior cingulate cortex (ACC) and fMRI during performance of a Stroop color-naming task in 22 patients with schizophrenia (SZ), initially off-medication and after a 6-week course of risperidone, and 20 matched healthy controls (HC) twice, 6 weeks apart. We observed a significant decrease in ACC glutamate + glutamine (Glx)/Creatine (Cr) levels in medicated SZ patients compared to HC but not compared to their off-medication baseline. In off-medication SZ, the relationship between ACC Glx/Cr levels and the blood oxygen level-dependent (BOLD) response in regions of the salience network (SN) and posterior default mode network (DMN) was opposite than of HC. After 6 weeks, the relationship between Glx and the BOLD response was still opposite between the groups; however for both groups the direction of the relationship changed from baseline to week 6. These results suggest a mechanism whereby alterations in the relationship between cortical glutamate and BOLD response is disrupting the modulation of major neural networks subserving cognitive processes, potentially affecting cognition. While these relationships appear to normalize with treatment in patients, the interpretations of the results are confounded by significant group differences in Glx levels, as well as the variability of the relationship between Glx and BOLD response in HC over time, which may be driven by factors including habituation to task or scanner environment.
| S-EPMC6281980 | biostudies-literature
Project description:Visual perceptual learning (VPL) is long-term performance improvement as a result of perceptual experience. It is unclear whether VPL is associated with refinement in representations of the trained feature (feature-based plasticity), improvement in processing of the trained task (task-based plasticity), or both. Here, we provide empirical evidence that VPL of motion detection is associated with both types of plasticity which occur predominantly in different brain areas. Before and after training on a motion detection task, subjects' neural responses to the trained motion stimuli were measured using functional magnetic resonance imaging. In V3A, significant response changes after training were observed specifically to the trained motion stimulus but independently of whether subjects performed the trained task. This suggests that the response changes in V3A represent feature-based plasticity in VPL of motion detection. In V1 and the intraparietal sulcus, significant response changes were found only when subjects performed the trained task on the trained motion stimulus. This suggests that the response changes in these areas reflect task-based plasticity. These results collectively suggest that VPL of motion detection is associated with the 2 types of plasticity, which occur in different areas and therefore have separate mechanisms at least to some degree.
| S-EPMC5004756 | biostudies-literature
Project description:BackgroundThis research is a one-site neuroimaging component of a two-site genetic study involving patients with schizophrenia at early and later stages of illness. Studies support a role for the neuronal Per-Arnt-Sim 3 (NPAS3) gene in processes that are essential for normal brain development. Specific NPAS3 variants have been observed at an increased frequency in schizophrenia. In humans, NPAS3 protein was detected in the hippocampus from the first trimester of gestation. In addition, NPAS3 protein levels were reduced in the dorsolateral prefrontal cortex of some patients with schizophrenia. Npas3 knockout mice display behavioural, neuroanatomical and structural changes with associated severe reductions in neural precursor cell proliferation in the hippocampal dentate gyrus. This study will evaluate the hypothesis that the severe reductions in neural precursor cell proliferation in the dentate gyrus will be present to some degree in patients carrying schizophrenia-associated NPAS3 variants and less so in other patients.Methods/designPatients enrolled in the larger genetic study (n = 150) will be invited to participate in this neuroimaging arm. The genetic data will be used to ensure a sample size of 45 participants in each genetic subgroup of patients (with and without NPAS3 variants). In addition, we will recruit 60 healthy controls for acquisition of normative data. The following neuroimaging measures will be acquired from the medial temporal region: a) an index of the microcellular environment; b) a macro-structural volumetric measure of the hippocampus; and c) concentration levels of N-acetylaspartate, a marker of neuronal health.DiscussionThis study will help to establish the contribution of the NPAS3 gene and its variants to brain tissue abnormalities in schizophrenia. Given the genetic and phenotypic heterogeneity of the disorder and the large variation in outcomes, the identification of biological subgroups may in future support tailoring of treatment approaches in order to optimize recovery.
| S-EPMC3986669 | biostudies-literature
Project description:It has been hypothesized that schizophrenia is characterized by overly broad automatic activity within lexico-semantic networks. We used two complementary neuroimaging techniques, Magnetoencephalography (MEG) and functional Magnetic Resonance Imaging (fMRI), in combination with a highly automatic indirect semantic priming paradigm, to spatiotemporally localize this abnormality in the brain. Eighteen people with schizophrenia and 20 demographically-matched control participants viewed target words ("bell") preceded by directly related ("church"), indirectly related ("priest"), or unrelated ("hammer") prime words in MEG and fMRI sessions. To minimize top-down processing, the prime was masked, the target appeared only 140 ms after prime onset, and participants simply monitored for words within a particular semantic category that appeared in filler trials. Both techniques revealed a significantly larger automatic indirect priming effect in people with schizophrenia than in control participants. MEG temporally localized this enhanced effect to the N400 time window (300-500 ms) - the critical stage of accessing meaning from words. fMRI spatially localized the effect to the left temporal fusiform cortex, which plays a role in mapping of orthographic word-form on to meaning. There was no evidence of an enhanced automatic direct semantic priming effect in the schizophrenia group. These findings provide converging neural evidence for abnormally broad highly automatic lexico-semantic activity in schizophrenia. We argue that, rather than arising from an unconstrained spread of automatic activation across semantic memory, this broader automatic lexico-semantic activity stems from looser mappings between the form and meaning of words.
| S-EPMC6453534 | biostudies-literature
Project description:In many clinical and scientific situations the optimal neuroimaging sequence may not be known prior to scanning and may differ for each individual being scanned, depending on the exact nature and location of abnormalities. Despite this, the standard approach to data acquisition, in such situations, is to specify the sequence of neuroimaging scans prior to data acquisition and to apply the same scans to all individuals. In this paper, we propose and illustrate an alternative approach, in which data would be analysed as it is acquired and used to choose the future scanning sequence: Active Acquisition. We propose three Active Acquisition scenarios based around multiple MRI modalities. In Scenario 1, we propose a simple use of near-real time analysis to decide whether to acquire more or higher resolution data, or acquire data with a different field -of -view. In Scenario 2, we simulate how multimodal MR data could be actively acquired and combined with a decision tree to classify a known outcome variable (in the simple example here, age). In Scenario 3, we simulate using Bayesian optimisation to actively search across multiple MRI modalities to find those which are most abnormal. These simulations suggest that by actively acquiring data, the scanning sequence can be adapted to each individual. We also consider the many outstanding practical and technical challenges involving normative data acquisition, MR physics, statistical modelling and clinical relevance. Despite these, we argue that Active Acquisition allows for potentially far more powerful, sensitive or rapid data acquisition, and may open up different perspectives on individual differences, clinical conditions, and biomarker discovery.
| S-EPMC6807153 | biostudies-literature