Browse
Submit Data
Databases
API
Help

Dataset Information

42 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

A structural and functional magnetic resonance imaging dataset of brain tumour patients.

ABSTRACT: We collected high resolution structural (T1, T2, DWI) and several functional (BOLD T2*) MRI data in 22 patients with different types of brain tumours. Functional imaging protocols included a motor task, a verb generation task, a word repetition task and resting state. Imaging data are complemented by demographics (age, sex, handedness, and pathology), behavioural results to motor and cognitive tests and direct cortical electrical stimulation data (pictures of stimulation sites with outcomes) performed during surgery. Altogether, these data are suited to test functional imaging methods for single subject analyses, in particular methods that focus on locating eloquent cortical areas, critical functional and/or structural network hubs, and predict patient status based on imaging data (presurgical mapping).

SUBMITTER: Pernet CR

PROVIDER: S-EPMC4736501 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

A structural and functional magnetic resonance imaging dataset of brain tumour patients.

Pernet Cyril R CR Gorgolewski Krzysztof J KJ Job Dominic D Rodriguez David D Whittle Ian I Wardlaw Joanna J

Scientific data 20160202

We collected high resolution structural (T1, T2, DWI) and several functional (BOLD T2*) MRI data in 22 patients with different types of brain tumours. Functional imaging protocols included a motor task, a verb generation task, a word repetition task and resting state. Imaging data are complemented by demographics (age, sex, handedness, and pathology), behavioural results to motor and cognitive tests and direct cortical electrical stimulation data (pictures of stimulation sites with outcomes) per ...[more]

PMID: 26836205

Similar Datasets

Brain functional and structural magnetic resonance imaging of obesity and weight loss interventions.

Project description:Obesity has tripled over the past 40 years to become a major public health issue, as it is linked with increased mortality and elevated risk for various physical and neuropsychiatric illnesses. Accumulating evidence from neuroimaging studies suggests that obesity negatively affects brain function and structure, especially within fronto-mesolimbic circuitry. Obese individuals show abnormal neural responses to food cues, taste and smell, resting-state activity and functional connectivity, and cognitive tasks including decision-making, inhibitory-control, learning/memory, and attention. In addition, obesity is associated with altered cortical morphometry, a lowered gray/white matter volume, and impaired white matter integrity. Various interventions and treatments including bariatric surgery, the most effective treatment for obesity in clinical practice, as well as dietary, exercise, pharmacological, and neuromodulation interventions such as transcranial direct current stimulation, transcranial magnetic stimulation and neurofeedback have been employed and achieved promising outcomes. These interventions and treatments appear to normalize hyper- and hypoactivations of brain regions involved with reward processing, food-intake control, and cognitive function, and also promote recovery of brain structural abnormalities. This paper provides a comprehensive literature review of the recent neuroimaging advances on the underlying neural mechanisms of both obesity and interventions, in the hope of guiding development of novel and effective treatments.

| S-EPMC10208984 | biostudies-literature

Bimodal electroencephalography-functional magnetic resonance imaging dataset for inner-speech recognition.

Project description:The recognition of inner speech, which could give a 'voice' to patients that have no ability to speak or move, is a challenge for brain-computer interfaces (BCIs). A shortcoming of the available datasets is that they do not combine modalities to increase the performance of inner speech recognition. Multimodal datasets of brain data enable the fusion of neuroimaging modalities with complimentary properties, such as the high spatial resolution of functional magnetic resonance imaging (fMRI) and the temporal resolution of electroencephalography (EEG), and therefore are promising for decoding inner speech. This paper presents the first publicly available bimodal dataset containing EEG and fMRI data acquired nonsimultaneously during inner-speech production. Data were obtained from four healthy, right-handed participants during an inner-speech task with words in either a social or numerical category. Each of the 8-word stimuli were assessed with 40 trials, resulting in 320 trials in each modality for each participant. The aim of this work is to provide a publicly available bimodal dataset on inner speech, contributing towards speech prostheses.

| S-EPMC10264396 | biostudies-literature

Calgary Preschool magnetic resonance imaging (MRI) dataset.

Project description:The Calgary Preschool MRI Dataset in the Developmental Neuroimaging Lab at the University of Calgary uses magnetic resonance imaging (MRI) techniques to study brain structure and function in early childhood [1-3]. The dataset aims to characterise brain development in early childhood (2-8 years), and to understand links to cognitive and behavioral development, as well as provide a baseline from which to identify atypical development in children with diseases, disorders, or brain injuries. MRI data are provided for 126 children (61 males, 65 females). Children ranged from 1.95 to 6.22 years (mean = 3.98 ± 1.06 years) at the time of their first scan and were initially scanned at six month intervals, and now continue to be followed annually (1-20 scans per child, 431 total datasets; datasets do not always have all scan modalities available). All MRI scans were acquired on the same General Electric 3T MR750w system and 32-channel head coil (GE, Waukesha, WI) at the Alberta Children's Hospital in Calgary, Canada. The MRI protocols provided in this dataset include: T1-weighted images acquired using a FSPGR BRAVO sequence; arterial spin labeling (ASL) images acquired with the vendor supplied pseudo continuous 3D ASL sequence; diffusion tensor imaging data acquired using single shot spin echo echo-planar imaging; and passive viewing resting state functional MRI data acquired with a gradient-echo echo-planar imaging sequence.

| S-EPMC7016255 | biostudies-literature

Discriminative Analysis of Schizophrenia Patients Using Topological Properties of Structural and Functional Brain Networks: A Multimodal Magnetic Resonance Imaging Study.

Project description:Interest in the application of machine learning (ML) techniques to multimodal magnetic resonance imaging (MRI) data for the diagnosis of schizophrenia (SZ) at the individual level is growing. However, a few studies have applied the features of structural and functional brain networks derived from multimodal MRI data to the discriminative analysis of SZ patients at different clinical stages. In this study, 205 normal controls (NCs), 61 first-episode drug-naive SZ (FESZ) patients, and 79 chronic SZ (CSZ) patients were recruited. We acquired their structural MRI, diffusion tensor imaging, and resting-state functional MRI data and constructed brain networks for each participant, including the gray matter network (GMN), white matter network (WMN), and functional brain network (FBN). We then calculated 3 nodal properties for each brain network, including degree centrality, nodal efficiency, and betweenness centrality. Two classifications (SZ vs. NC and FESZ vs. CSZ) were performed using five ML algorithms. We found that the SVM classifier with the input features of the combination of nodal properties of both the GMN and FBN achieved the best performance to discriminate SZ patients from NCs [accuracy, 81.2%; area under the receiver operating characteristic curve (AUC), 85.2%; p < 0.05]. Moreover, the SVM classifier with the input features of the combination of the nodal properties of both the GMN and WMN achieved the best performance to discriminate FESZ from CSZ patients (accuracy, 86.2%; AUC, 92.3%; p < 0.05). Furthermore, the brain areas in the subcortical/cerebellum network and the frontoparietal network showed significant importance in both classifications. Together, our findings provide new insights to understand the neuropathology of SZ and further highlight the potential advantages of multimodal network properties for identifying SZ patients at different clinical stages.

| S-EPMC8787107 | biostudies-literature

Chemotherapy-induced functional brain abnormality in colorectal cancer patients: a resting-state functional magnetic resonance imaging study.

Project description:IntroductionChemotherapy-induced cognitive impairment (i.e., "chemobrain") is a common neurotoxic side-effect experienced by many cancer survivors who undergone chemotherapy. However, the central mechanism underlying chemotherapy-related cognitive impairment is still unclear. The purpose of this study was to investigate the changes of intrinsic brain activity and their associations with cognitive impairment in colorectal cancer (CRC) patients after chemotherapy.MethodsResting-state functional magnetic resonance imaging data of 29 CRC patients following chemotherapy and 29 matched healthy controls (HCs) were collected in this study, as well as cognitive test data including Mini Mental State Exam (MMSE), Montreal Cognitive Assessment (MoCA) and Functional Assessment of Cancer Therapy-Cognitive Function (FACT-Cog). The measure of fractional amplitude of low-frequency fluctuation (fALFF) was calculated and compared between groups. The correlations between the fALFF of impaired brain region and cognitive performance were also analyzed.ResultsCompared with HCs, CRC patients following chemotherapy showed decreased fALFF values in the left anterior cingulate gyrus (ACG) and middle frontal gyrus, as well as increased fALFF values in the left superior frontal gyrus (orbital part) and middle occipital gyrus. Moreover, positive associations were identified between fALFF values of the left ACG and the total scores of MMSE, MoCA and FACT-Cog in the patient group.ConclusionThese findings indicated that CRC patients after chemotherapy had decreased intrinsic brain activity in the left ACG, which might be vulnerable to the neurotoxic side-effect of chemotherapeutic drugs and related to chemotherapy-induced cognitive impairment.

| S-EPMC9339615 | biostudies-literature

Measuring brain beats: Cardiac-aligned fast functional magnetic resonance imaging signals.

Project description:Blood and cerebrospinal fluid (CSF) pulse and flow throughout the brain, driven by the cardiac cycle. These fluid dynamics, which are essential to healthy brain function, are characterized by several noninvasive magnetic resonance imaging (MRI) methods. Recent developments in fast MRI, specifically simultaneous multislice acquisition methods, provide a new opportunity to rapidly and broadly assess cardiac-driven flow, including CSF spaces, surface vessels and parenchymal vessels. We use these techniques to assess blood and CSF flow dynamics in brief (3.5 min) scans on a conventional 3 T MRI scanner in five subjects. Cardiac pulses are measured with a photoplethysmography (PPG) on the index finger, along with functional MRI (fMRI) signals in the brain. We, retrospectively, align the fMRI signals to the heartbeat. Highly reliable cardiac-gated fMRI temporal signals are observed in CSF and blood on the timescale of one heartbeat (test-retest reliability within subjects R2 > 50%). In blood vessels, a local minimum is observed following systole. In CSF spaces, the ventricles and subarachnoid spaces have a local maximum following systole instead. Slower resting-state scans with slice timing, retrospectively, aligned to the cardiac pulse, reveal similar cardiac-gated responses. The cardiac-gated measurements estimate the amplitude and phase of fMRI pulsations in the CSF relative to those in the arteries, an estimate of the local intracranial impedance. Cardiac aligned fMRI signals can provide new insights about fluid dynamics or diagnostics for diseases where these dynamics are important.

| S-EPMC9783469 | biostudies-literature

Brain-based correlates of depression and traumatic brain injury: a systematic review of structural and functional magnetic resonance imaging studies.

Project description:IntroductionDepression is prevalent after traumatic brain injury (TBI). However, there is a lack of understanding of the brain-based correlates of depression post-TBI. This systematic review aimed to synthesize findings of structural and functional magnetic resonance imaging (MRI) studies to identify consistently reported neural correlates of depression post-TBI.MethodsA search for relevant published studies was conducted through OVID (MEDLINE, APA PsycINFO, and Embase), with an end date of August 3rd, 2023. Fourteen published studies were included in this review.ResultsTBI patients with depression exhibited distinct changes in diffusion- based white matter fractional anisotropy, with the direction of change depending on the acuteness or chronicity of TBI. Decreased functional connectivity (FC) of the salience and default mode networks was prominent alongside the decreased volume of gray matter within the insular, dorsomedial prefrontal, and ventromedial prefrontal cortices. Seven studies reported the correlation between observed neuroimaging and depression outcomes. Of these studies, 42% indicated that FC of the bilateral medial temporal lobe subregions was correlated with depression outcomes in TBI.DiscussionThis systematic review summarizes existing neuroimaging evidence and reports brain regions that can be leveraged as potential treatment targets in future studies examining depression post-TBI.

| S-EPMC11573519 | biostudies-literature

Brain Structural Alterations in Left-Behind Children: A Magnetic Resonance Imaging Study.

Project description:Parental migration has caused millions of children left behind, especially in China and India. Left-behind children (LBC) have a high risk of mental disorders and may present negative life outcomes in the future. However, little is known whether there are cerebral structural alterations in LBC in relative to those with parents. This study is to explore the effect of parental migration on brain maturation by comparing gray matter volume (GMV) and fractional anisotropy (FA) of LBC with well-matched non-LBC. Thirty-eight LBC (21 boys, age = 9.60 ± 1.8 years) and 30 non-LBC (19 boys, age = 10.00 ± 1.95 years) were recruited and underwent brain scans in 3.0 T MR. Intelligence quotient and other factors including family income, guardians' educational level and separation time were also acquired. GMV and FA were measured for each participant and compared between groups using 2-sample t-tests with atlas-based analysis. Compared to non-LBC, LBC exhibited greater GMV in emotional and cortico-striato-thalamo-cortical circuits, and altered FA in bilateral superior occipitofrontal fasciculi and right medial lemniscus (p < 0.05, Cohen's d > 0.89, corrected for false-discovery rate). Other factors including family income, guardians' educational level and separation time were not associated with these brain changes. Our study provides empirical evidence of altered brain structure in LBC compared to non-LBC, responsible for emotion regulation and processing, which may account for mental disorders and negative life outcome of LBC. Our study suggests that absence of direct biological parental care may impact children's brain development. Therefore, public health efforts may be needed to provide additional academic and social/emotional supports to LBC when their parents migrate to seeking better economic circumstances, which has become increasingly common in developing countries.

| S-EPMC6517480 | biostudies-literature

Brain Structural and Functional Connectivity: A Review of Combined Works of Diffusion Magnetic Resonance Imaging and Electro-Encephalography.

Project description:Implications of structural connections within and between brain regions for their functional counterpart are timely points of discussion. White matter microstructural organization and functional activity can be assessed in unison. At first glance, however, the corresponding findings appear variable, both in the healthy brain and in numerous neuro-pathologies. To identify consistent associations between structural and functional connectivity and possible impacts for the clinic, we reviewed the literature of combined recordings of electro-encephalography (EEG) and diffusion-based magnetic resonance imaging (MRI). It appears that the strength of event-related EEG activity increases with increased integrity of structural connectivity, while latency drops. This agrees with a simple mechanistic perspective: the nature of microstructural white matter influences the transfer of activity. The EEG, however, is often assessed for its spectral content. Spectral power shows associations with structural connectivity that can be negative or positive often dependent on the frequencies under study. Functional connectivity shows even more variations, which are difficult to rank. This might be caused by the diversity of paradigms being investigated, from sleep and resting state to cognitive and motor tasks, from healthy participants to patients. More challenging, though, is the potential dependency of findings on the kind of analysis applied. While this does not diminish the principal capacity of EEG and diffusion-based MRI co-registration, it highlights the urgency to standardize especially EEG analysis.

| S-EPMC8529047 | biostudies-literature

Right-hemispheric language reorganization in patients with brain arteriovenous malformations: A functional magnetic resonance imaging study.

Project description:Brain arteriovenous malformation (AVM), a presumed congenital lesion, may involve traditional language areas but usually does not lead to language dysfunction unless it ruptures. The objective of this research was to study right-hemispheric language reorganization patterns in patients with brain AVMs using functional magnetic resonance imaging (fMRI). We prospectively enrolled 30 AVM patients with lesions involving language areas and 32 age- and sex-matched healthy controls. Each subject underwent fMRI during three language tasks: visual synonym judgment, oral word reading, and auditory sentence comprehension. The activation differences between the AVM and control groups were investigated by voxelwise analysis. Lateralization indices (LIs) for the frontal lobe, temporal lobe, and cerebellum were compared between the two groups, respectively. Results suggested that the language functions of AVM patients and controls were all normal. Voxelwise analysis showed no significantly different activations between the two groups in visual synonym judgment and oral word reading tasks. In auditory sentence comprehension task, AVM patients had significantly more activations in the right precentral gyrus (BA 6) and right cerebellar lobule VI (AAL 9042). According to the LI results, the frontal lobe in oral word reading task and the temporal lobe in auditory sentence comprehension task were significantly more right-lateralized in the AVM group. These findings suggest that for patients with AVMs involving language cortex, different language reorganization patterns may develop for different language functions. The recruitment of brain areas in the right cerebral and cerebellar hemispheres may play a compensatory role in the reorganized language network of AVM patients.

| S-EPMC8596961 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data