Classification of bipolar disorder using basal-ganglia-related functional connectivity in the resting state

2013 ◽  
Author(s):  
Shin Teng ◽  
Chia-Feng Lu ◽  
Po-Shan Wang ◽  
Chih-I Hung ◽  
Cheng-Ta Li ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Basal Ganglia ◽  
Functional Connectivity ◽  
Resting State

scholarly journals Evolutionary optimization in classification of early-MCI patients from healthy controls using graph measures of resting-state fMRI

2021 ◽  
Author(s):  
Jafar Zamani ◽  
Ali Sadr ◽  
Amir-Homayoun Javadi
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Functional Connectivity ◽  
Evolutionary Algorithms ◽  
Resting State ◽  
Optimization Methods ◽  
Resting State Fmri ◽  
Optimization Method ◽  
Effective Parameters

AbstractsIdentifying individuals with early mild cognitive impairment (EMCI) can be an effective strategy for early diagnosis and delay the progression of Alzheimer’s disease (AD). Many approaches have been devised to discriminate those with EMCI from healthy control (HC) individuals. Selection of the most effective parameters has been one of the challenging aspects of these approaches. In this study we suggest an optimization method based on five evolutionary algorithms that can be used in optimization of neuroimaging data with a large number of parameters. Resting-state functional magnetic resonance imaging (rs-fMRI) measures, which measure functional connectivity, have been shown to be useful in prediction of cognitive decline. Analysis of functional connectivity data using graph measures is a common practice that results in a great number of parameters. Using graph measures we calculated 1155 parameters from the functional connectivity data of HC (n=36) and EMCI (n=34) extracted from the publicly available database of the Alzheimer’s disease neuroimaging initiative database (ADNI). These parameters were fed into the evolutionary algorithms to select a subset of parameters for classification of the data into two categories of EMCI and HC using a two-layer artificial neural network. All algorithms achieved classification accuracy of 94.55%, which is extremely high considering single-modality input and low number of data participants. These results highlight potential application of rs-fMRI and efficiency of such optimization methods in classification of images into HC and EMCI. This is of particular importance considering that MRI images of EMCI individuals cannot be easily identified by experts.

scholarly journals Resting-state functional connectivity in individuals with bipolar disorder during clinical remission: a systematic review

2018 ◽  
Vol 43 (5) ◽  
pp. 298-316 ◽  
Author(s):  
Sabrina K. Syan ◽  
Mara Smith ◽  
Benicio N. Frey ◽  
Raheem Remtulla ◽  
Flavio Kapczinski ◽  
...  
Keyword(s):  
Systematic Review ◽  
Bipolar Disorder ◽  
Functional Connectivity ◽  
Resting State ◽  
Clinical Remission ◽  
Resting State Functional Connectivity

scholarly journals Resting-state functional connectivity of emotion regulation networks in euthymic and non-euthymic bipolar disorder patients

2016 ◽  
Vol 34 ◽  
pp. 56-63 ◽  
Author(s):  
G. Rey ◽  
C Piguet ◽  
A Benders ◽  
S Favre ◽  
SB Eickhoff ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Functional Connectivity ◽  
Resting State ◽  
Clinical Symptoms ◽  
Mood State ◽  
A Priori ◽  
Emotion Processing ◽  
Population Sample ◽  
Small Population ◽  
Resting State Functional Connectivity

AbstractBackgroundPrevious functional magnetic resonance imaging studies in bipolar disorder (BD) have evidenced changes in functional connectivity (FC) in brain areas associated with emotion processing, but how these changes vary with mood state and specific clinical symptoms is not fully understood.MethodsWe investigated resting-state FC between a priori regions of interest (ROIs) from the default-mode network and key structures for emotion processing and regulation in 27 BD patients and 27 matched healthy controls. We further compared connectivity patterns in subgroups of 15 euthymic and 12 non-euthymic patients and tested for correlations of the connectivity strength with measures of mood, anxiety, and rumination tendency. No correction for multiple comparisons was applied given the small population sample and pre-defined target ROIs.ResultsOverall, regardless of mood state, BD patients exhibited increased FC of the left amygdala with left sgACC and PCC, relative to controls. In addition, non-euthymic BD patients showed distinctive decrease in FC between right amygdala and sgACC, whereas euthymic patients showed lower FC between PCC and sgACC. Euthymic patients also displayed increased FC between sgACC and right VLPFC. The sgACC–PCC and sgACC–left amygdala connections were modulated by rumination tendency in non-euthymic patients, whereas the sgACC-VLPFC connection was modulated by both the current mood and tendency to ruminate.ConclusionsOur results suggest that sgACC-amygdala coupling is critically affected during mood episodes, and that FC of sgACC play a pivotal role in mood normalization through its interactions with the VLPFC and PCC. However, these preliminary findings require replication with larger samples of patients.

Brain activity at rest: a multiscale hierarchical functional organization

2011 ◽  
Vol 105 (6) ◽  
pp. 2753-2763 ◽  
Author(s):  
Gaëlle Doucet ◽  
Mikaël Naveau ◽  
Laurent Petit ◽  
Nicolas Delcroix ◽  
Laure Zago ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Functional Organization ◽  
Brain Activity ◽  
Correlation Coefficients ◽  
Temporal Correlation ◽  
Hierarchical Level ◽  
Spontaneous Brain Activity ◽  
Dorsal Attentional Network

Spontaneous brain activity was mapped with functional MRI (fMRI) in a sample of 180 subjects while in a conscious resting-state condition. With the use of independent component analysis (ICA) of each individual fMRI signal and classification of the ICA-defined components across subjects, a set of 23 resting-state networks (RNs) was identified. Functional connectivity between each pair of RNs was assessed using temporal correlation analyses in the 0.01- to 0.1-Hz frequency band, and the corresponding set of correlation coefficients was used to obtain a hierarchical clustering of the 23 RNs. At the highest hierarchical level, we found two anticorrelated systems in charge of intrinsic and extrinsic processing, respectively. At a lower level, the intrinsic system appears to be partitioned in three modules that subserve generation of spontaneous thoughts (M1a; default mode), inner maintenance and manipulation of information (M1b), and cognitive control and switching activity (M1c), respectively. The extrinsic system was found to be made of two distinct modules: one including primary somatosensory and auditory areas and the dorsal attentional network (M2a) and the other encompassing the visual areas (M2b). Functional connectivity analyses revealed that M1b played a central role in the functioning of the intrinsic system, whereas M1c seems to mediate exchange of information between the intrinsic and extrinsic systems.

Structural and functional changes in the somatosensory cortex in euthymic females with bipolar disorder

2017 ◽  
Vol 52 (11) ◽  
pp. 1075-1083 ◽  
Author(s):  
Luciano Minuzzi ◽  
Sabrina K Syan ◽  
Mara Smith ◽  
Alexander Hall ◽  
Geoffrey BC Hall ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Functional Connectivity ◽  
Somatosensory Cortex ◽  
Resting State ◽  
Healthy Controls ◽  
Voxel Based Morphometry ◽  
Resting State Functional Connectivity ◽  
Functional Changes ◽  
Morphometry Analysis ◽  
And Function

Objective: Current evidence from neuroimaging data suggests possible dysfunction of the fronto-striatal-limbic circuits in individuals with bipolar disorder. Somatosensory cortical function has been implicated in emotional recognition, risk-taking and affective responses through sensory modalities. This study investigates anatomy and function of the somatosensory cortex in euthymic bipolar women. Methods: In total, 68 right-handed euthymic women (bipolar disorder = 32 and healthy controls = 36) between 16 and 45 years of age underwent high-resolution anatomical and functional magnetic resonance imaging during the mid-follicular menstrual phase. The somatosensory cortex was used as a seed region for resting-state functional connectivity analysis. Voxel-based morphometry was used to evaluate somatosensory cortical gray matter volume between groups. Results: We found increased resting-state functional connectivity between the somatosensory cortex and insular cortex, inferior prefrontal gyrus and frontal orbital cortex in euthymic bipolar disorder subjects compared to healthy controls. Voxel-based morphometry analysis showed decreased gray matter in the left somatosensory cortex in the bipolar disorder group. Whole-brain voxel-based morphometry analysis controlled by age did not reveal any additional significant difference between groups. Conclusion: This study is the first to date to evaluate anatomy and function of the somatosensory cortex in a well-characterized sample of euthymic bipolar disorder females. Anatomical and functional changes in the somatosensory cortex in this population might contribute to the pathophysiology of bipolar disorder.

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