scholarly journals Regional brain activation/deactivation during word generation in schizophrenia: fMRI study

2011 ◽  
Vol 198 (3) ◽  
pp. 213-222 ◽  
Author(s):  
John P. John ◽  
Harsha N. Halahalli ◽  
Mandapati K. Vasudev ◽  
Peruvumba N. Jayakumar ◽  
Sanjeev Jain
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Brain Regions ◽  
Repetition Condition ◽  
Healthy Individuals ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Word Generation ◽  
The Brain

BackgroundExamination of the brain regions that show aberrant activations and/or deactivations during semantic word generation could pave the way for a better understanding of the neurobiology of cognitive dysfunction in schizophrenia.AimsTo examine the pattern of functional magnetic resonance imaging blood oxygen level dependent activations and deactivations during semantic word generation in schizophrenia.MethodFunctional magnetic resonance imaging was performed on 24 participants with schizophrenia and 24 matched healthy controls during an overt, paced, ‘semantic category word generation’ condition and a baseline ‘word repetition’ condition that modelled all the lead-in/associated processes involved in the performance of the generation task.ResultsThe brain regions activated during word generation in healthy individuals were replicated with minimal redundancies in participants with schizophrenia. The individuals with schizophrenia showed additional activations of temporo-parieto-occipital cortical regions as well as subcortical regions, despite significantly poorer behavioural performance than the healthy participants. Importantly, the extensive deactivations in other brain regions during word generation in healthy individuals could not be replicated in those with schizophrenia.ConclusionsMore widespread activations and deficient deactivations in the poorly performing participants with schizophrenia may reflect an inability to inhibit competing cognitive processes, which in turn could constitute the core information-processing deficit underlying impaired word generation in schizophrenia.

scholarly journals Functional magnetic resonance imaging in schizophrenia

2010 ◽  
Vol 12 (3) ◽  
pp. 333-343 ◽  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Neural Substrates ◽  
Brain Regions ◽  
Affective Neuroscience ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Behavioral Deficits ◽  
The Brain

The integration of functional magnetic resonance imaging (fMRI) with cognitive and affective neuroscience paradigms enables examination of the brain systems underlying the behavioral deficits manifested in schizophrenia; there have been a remarkable increase in the number of studies that apply fMRI in neurobiological studies of this disease. This article summarizes features of fMRI methodology and highlights its application in neurobehavioral studies in schizophrenia. Such work has helped elucidate potential neural substrates of deficits in cognition and affect by providing measures of activation to neurobehavioral probes and connectivity among brain regions. Studies have demonstrated abnormalities at early stages of sensory processing that may influence downstream abnormalities in more complex evaluative processing. The methodology can help bridge integration with neuropharmacologic and genomic investigations.

scholarly journals Applying 3DPCANet and Functional Magnetic Resonance Imaging to Aided Diagnosis of Alzheimer’s Disease

2021 ◽  
Author(s):  
Yu Wang ◽  
Hongfei Jia ◽  
Yifan Duan ◽  
Hongbing Xiao
Keyword(s):  
Magnetic Resonance Imaging ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Brain Regions ◽  
Support Vector ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Public Data

Abstract Alzheimer's disease (AD) is a progressive neurodegenerative disease, which changes the structure of brain regions by some hidden causes. In this paper for assisting doctors to make correct judgments, an improved 3DPCANet method is proposed to classify AD by combining the mean (mALFF) of the whole brain. The main idea includes that firstly, the functional magnetic resonance imaging (fMRI) data is pre-processed, and mALFF is calculated to get the corresponding matrix. Then the features of mALFF images are extracted via the improved 3DPCANet network. Finally, AD patients with different stages are classified using support vector machine (SVM). Experiments results based on public data from the Alzheimer’s disease neuroimaging initiative (ADNI) show that the proposed approach has better performance compared with state-of-the-art methods. The accuracies of AD vs. significant memory concern (SMC), SMC vs. late mild cognitive impairment (LMCI), and normal control (NC) vs. SMC reach respectively 92.42%, 91.80%, and 89.50%, which testifies the feasibility and effectiveness of the proposed method.

scholarly journals Resting-State Functional Magnetic Resonance Imaging Connectivity Between Semantic and Phonological Regions of Interest May Inform Language Targets in Aphasia

2020 ◽  
Vol 63 (9) ◽  
pp. 3051-3067
Author(s):  
Amy E. Ramage ◽  
Semra Aytur ◽  
Kirrie J. Ballard
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Resting State ◽  
Brain Regions ◽  
Regions Of Interest ◽  
Healthy Controls ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Language Performance

Purpose Brain imaging has provided puzzle pieces in the understanding of language. In neurologically healthy populations, the structure of certain brain regions is associated with particular language functions (e.g., semantics, phonology). In studies on focal brain damage, certain brain regions or connections are considered sufficient or necessary for a given language function. However, few of these account for the effects of lesioned tissue on the “functional” dynamics of the brain for language processing. Here, functional connectivity (FC) among semantic–phonological regions of interest (ROIs) is assessed to fill a gap in our understanding about the neural substrates of impaired language and whether connectivity strength can predict language performance on a clinical tool in individuals with aphasia. Method Clinical assessment of language, using the Western Aphasia Battery–Revised, and resting-state functional magnetic resonance imaging data were obtained for 30 individuals with chronic aphasia secondary to left-hemisphere stroke and 18 age-matched healthy controls. FC between bilateral ROIs was contrasted by group and used to predict Western Aphasia Battery–Revised scores. Results Network coherence was observed in healthy controls and participants with stroke. The left–right premotor cortex connection was stronger in healthy controls, as reported by New et al. (2015) in the same data set. FC of (a) connections between temporal regions, in the left hemisphere and bilaterally, predicted lexical–semantic processing for auditory comprehension and (b) ipsilateral connections between temporal and frontal regions in both hemispheres predicted access to semantic–phonological representations and processing for verbal production. Conclusions Network connectivity of brain regions associated with semantic–phonological processing is predictive of language performance in poststroke aphasia. The most predictive connections involved right-hemisphere ROIs—particularly those for which structural adaptions are known to associate with recovered word retrieval performance. Predictions may be made, based on these findings, about which connections have potential as targets for neuroplastic functional changes with intervention in aphasia. Supplemental Material https://doi.org/10.23641/asha.12735785

Resting state functional magnetic resonance imaging processing techniques in stroke studies

2016 ◽  
Vol 27 (8) ◽  
pp. 871-885 ◽  
Author(s):  
Golrokh Mirzaei ◽  
Hojjat Adeli
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Resting State ◽  
Brain Connectivity ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Stroke Patients ◽  
Processing Techniques ◽  
The Brain

AbstractIn recent years, there has been considerable research interest in the study of brain connectivity using the resting state functional magnetic resonance imaging (rsfMRI). Studies have explored the brain networks and connection between different brain regions. These studies have revealed interesting new findings about the brain mapping as well as important new insights in the overall organization of functional communication in the brain network. In this paper, after a general discussion of brain networks and connectivity imaging, the brain connectivity and resting state networks are described with a focus on rsfMRI imaging in stroke studies. Then, techniques for preprocessing of the rsfMRI for stroke patients are reviewed, followed by brain connectivity processing techniques. Recent research on brain connectivity using rsfMRI is reviewed with an emphasis on stroke studies. The authors hope this paper generates further interest in this emerging area of computational neuroscience with potential applications in rehabilitation of stroke patients.

Sign in / Sign up

Export Citation Format

Share Document