Clinical, cognitive, and functional connectivity correlations of resting-state intrinsic brain activity alterations in unmedicated depression

Human performance, alertness, and most biological functions express rhythmic fluctuations across a 24-hour-period. This phenomenon is believed to originate from differences in both circadian and homeostatic sleep-wake regulatory processes. Interactions between these processes result in time-of-day modulations of behavioral performance as well as brain activity patterns. Although the basic mechanism of the 24-hour clock is conserved across evolution, there are interindividual differences in the timing of sleep-wake cycles, subjective alertness and functioning throughout the day. The study of circadian typology differences has increased during the last few years, especially research on extreme chronotypes, which provide a unique way to investigate the effects of sleep-wake regulation on cerebral mechanisms. Using functional magnetic resonance imaging (fMRI), we assessed the influence of chronotype and time-of-day on resting-state functional connectivity. 29 extreme morning- and 34 evening-type participants underwent two fMRI sessions: about one hour after wake-up time (morning) and about ten hours after wake-up time (evening), scheduled according to their declared habitual sleep-wake pattern on a regular working day. Analysis of obtained neuroimaging data disclosed only an effect of time of day on resting-state functional connectivity; there were different patterns of functional connectivity between morning and evening sessions. The results of our study showed no differences between extreme morning-type and evening-type individuals. We demonstrate that circadian and homeostatic influences on the resting-state functional connectivity have a universal character, unaffected by circadian typology.

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Computerized physical and cognitive training improves the functional architecture of the brain in adults with Down syndrome: A network science EEG study

Network Neuroscience ◽

10.1162/netn_a_00177 ◽

2020 ◽

pp. 1-21

Author(s):

Alexandra Anagnostopoulou ◽

Charis Styliadis ◽

Panagiotis Kartsidis ◽

Evangelia Romanopoulou ◽

Vasiliki Zilidou ◽

...

Keyword(s):

Down Syndrome ◽

Functional Connectivity ◽

Cognitive Training ◽

Resting State ◽

Network Architecture ◽

Right Hemisphere ◽

Random Network ◽

Brain Activity ◽

Hierarchical Organization ◽

The Brain

Understanding the neuroplastic capacity of people with Down syndrome (PwDS) can potentially reveal the causal relationship between aberrant brain organization and phenotypic characteristics. We used resting-state EEG recordings to identify how a neuroplasticity-triggering training protocol relates to changes in the functional connectivity of the brain’s intrinsic cortical networks. Brain activity of 12 PwDS before and after a 10-week protocol of combined physical and cognitive training was statistically compared to quantify changes in directed functional connectivity in conjunction with psychosomatometric assessments. PwDS showed increased connectivity within the left hemisphere and from left-to-right hemisphere, as well as increased physical and cognitive performance. Our findings reveal a strong adaptive neuroplastic reorganization as a result of the training that leads to a less-random network with a more pronounced hierarchical organization. Our results go beyond previous findings by indicating a transition to a healthier, more efficient, and flexible network architecture, with improved integration and segregation abilities in the brain of PwDS. Resting-state electrophysiological brain activity is used here for the first time to display meaningful relationships to underlying Down syndrome processes and outcomes of importance in a translational inquiry. This trial is registered with ClinicalTrials.gov Identifier NCT04390321.

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Brain activity at rest: a multiscale hierarchical functional organization

Journal of Neurophysiology ◽

10.1152/jn.00895.2010 ◽

2011 ◽

Vol 105 (6) ◽

pp. 2753-2763 ◽

Cited By ~ 187

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.

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Mental rotation task specifically modulates functional connectivity strength of intrinsic brain activity in low frequency domains: A maximum uncertainty linear discriminant analysis

Behavioural Brain Research ◽

10.1016/j.bbr.2016.12.017 ◽

2017 ◽

Vol 320 ◽

pp. 233-243 ◽

Cited By ~ 4

Author(s):

Mengxia Gao ◽

Delong Zhang ◽

Zengjian Wang ◽

Bishan Liang ◽

Yuxuan Cai ◽

...

Keyword(s):

Discriminant Analysis ◽

Functional Connectivity ◽

Linear Discriminant Analysis ◽

Brain Activity ◽

Low Frequency ◽

Linear Discriminant ◽

Frequency Domains ◽

Functional Connectivity Strength ◽

Intrinsic Brain Activity ◽

Connectivity Strength

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Altered Intra- and Interregional Synchronization in Resting-State Cerebral Networks Associated with Chronic Tinnitus

Neural Plasticity ◽

10.1155/2015/475382 ◽

2015 ◽

Vol 2015 ◽

pp. 1-11 ◽

Cited By ~ 20

Author(s):

Yu-Chen Chen ◽

Jian Zhang ◽

Xiao-Wei Li ◽

Wenqing Xia ◽

Xu Feng ◽

...

Keyword(s):

Functional Connectivity ◽

Resting State ◽

Brain Activity ◽

Inferior Frontal Gyrus ◽

Resting State Fmri ◽

Brain Regions ◽

Chronic Tinnitus ◽

Healthy Controls ◽

Tinnitus Distress ◽

The Right

Objective. Subjective tinnitus is hypothesized to arise from aberrant neural activity; however, its neural bases are poorly understood. To identify aberrant neural networks involved in chronic tinnitus, we compared the resting-state functional magnetic resonance imaging (fMRI) patterns of tinnitus patients and healthy controls.Materials and Methods. Resting-state fMRI measurements were obtained from a group of chronic tinnitus patients (n=29) with normal hearing and well-matched healthy controls (n=30). Regional homogeneity (ReHo) analysis and functional connectivity analysis were used to identify abnormal brain activity; these abnormalities were compared to tinnitus distress.Results. Relative to healthy controls, tinnitus patients had significant greater ReHo values in several brain regions including the bilateral anterior insula (AI), left inferior frontal gyrus, and right supramarginal gyrus. Furthermore, the left AI showed enhanced functional connectivity with the left middle frontal gyrus (MFG), while the right AI had enhanced functional connectivity with the right MFG; these measures were positively correlated with Tinnitus Handicap Questionnaires (r=0.459,P=0.012andr=0.479,P=0.009, resp.).Conclusions. Chronic tinnitus patients showed abnormal intra- and interregional synchronization in several resting-state cerebral networks; these abnormalities were correlated with clinical tinnitus distress. These results suggest that tinnitus distress is exacerbated by attention networks that focus on internally generated phantom sounds.

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Longitudinal Spatial Patterns of Intrinsic Brain Activity and Functional Connectivity in Upper Limb Amputees Patients

10.21203/rs.2.21498/v1 ◽

2020 ◽

Author(s):

bingbo bao ◽

xuyun hua ◽

haifeng wei ◽

pengbo luo ◽

hongyi zhu ◽

...

Keyword(s):

Functional Connectivity ◽

Spatial Patterns ◽

Brain Plasticity ◽

Brain Activity ◽

Low Frequency ◽

Resting State Fmri ◽

Brain Regions ◽

Brain Network ◽

Intrinsic Connectivity ◽

Intrinsic Brain Activity

Abstract Background: Amputation in adults is a serious condition and most patients were associated with the remapping of representations in motor and sensory brain network. Methods: The present study includes 8 healthy volunteers and 16 patients with amputation. We use resting-state fMRI to investigate the local and extent brain plasticity in patients suffering from amputation simultaneously. Both the amplitude of low-frequency fluctuations (ALFF) and degree centrality (DC) were used for the assessment of neuroplasticity in central level. Results: We described changes in spatial patterns of intrinsic brain activity and functional connectivity in amputees in the present study and we found that not only the sensory and motor cortex, but also the related brain regions involved in the functional plasticity after upper extremity deafferentation. Conclusion: Our findings showed local and extensive cortical changes in the sensorimotor and cognitive-related brain regions, which may imply the dysfunction in not only sensory and motor function, but also sensorimotor integration and motor plan. The activation and intrinsic connectivity in the brain changed a lot showed correlation with the deafferentation status.

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Abnormal Spontaneous Brain Activity and Functional Connectivity of the Default Mode Network in Patients with Bipolar Disorder

10.21203/rs.3.rs-194210/v1 ◽

2021 ◽

Author(s):

Lei Zhao ◽

Qijing Bo ◽

Zhifang Zhang ◽

Feng Li ◽

Yuan Zhou ◽

...

Keyword(s):

Bipolar Disorder ◽

Functional Connectivity ◽

Default Mode Network ◽

Resting State ◽

Brain Activity ◽

Seed Region ◽

Potential Candidate ◽

Neural Basis ◽

Default Mode ◽

Spontaneous Brain Activity

Abstract Background: No consistent evidence on the specific brain regions is available in the default mode network (DMN), which show abnormal spontaneous activity in bipolar disorder (BD). We aim to identify this region that is particularly impaired in patients with BD by using several different indices measuring spontaneous brain activity and then investigate its functional connectivity (FC).Methods: A total of 56 patients with BD and 71 healthy controls (HC) underwent resting-state functional magnetic resonance imaging. Three commonly used functional indices were used to identify the brain region showing abnormal spontaneous brain activity in BD. Then, this region served as the seed region for resting-state FC analysis to identify its functional networks altered in BD.Results: The BD group exhibited decreased fALFF, ReHo, and DC values in the left precuneus. The BD group had decreased rsFC within the DMN, indicated by decreased resting-state FC within the left precuneus and between the left precuneus and the medial prefrontal cortex. The BD group had decreased negative connectivity between the left precuneus and the left putamen, extending to the left insula.Conclusions: The findings provide convergent evidence for the abnormalities in the DMN of BD, particularly located in the left precuneus. Decreased FC within the DMN and the disruptive anticorrelation between the DMN and the salience network are found in BD. These findings suggest that the DMN is a key aspect for understanding the neural basis of BD, and the altered functional patterns of DMN may be a potential candidate biomarker of BD.

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Neuronal noise to identity confusion - association between long-range temporal correlations in intrinsic EEG activity and subjective sense of identity

10.31234/osf.io/fxw3c ◽

2020 ◽

Author(s):

Kazumi Sugimura ◽

Yasuhiro Iwasa ◽

Ryota Kobayashi ◽

Tatsuru Honda ◽

Junya Hashimoto ◽

...

Keyword(s):

Long Range ◽

Resting State ◽

Noise Suppression ◽

Brain Activity ◽

Random Noise ◽

Temporal Correlation ◽

Temporal Consistency ◽

Identity Confusion ◽

Sense Of Identity ◽

Intrinsic Brain Activity

The long-range temporal correlation (LRTC) in resting-state intrinsic brain activity is known to be associated with temporal behavioral patterns, including decision making based on internal criteria such as self-knowledge. However, the association between the neuronal LRTC and the subjective sense of identity remains to be explored; in other words, whether our subjective sense of consistent self across time relates to the temporal consistency of neural activity. The present study examined the relationship between the LRTC of resting-state scalp electroencephalography (EEG) and a subjective sense of identity measured by the Erikson Psychosocial Stage Inventory (EPSI). Consistent with our prediction based on previous studies of neuronal-behavioral relationships, the frontocentral alpha LRTC correlated negatively with identity confusion. Moreover, from the descriptive analyses, centroparietal beta LRTC showed negative correlations with identity confusion, and frontal theta LRTC showed positive relationships with identity synthesis. These results suggest that more temporal consistency (reversely, less random noise) in intrinsic brain activity is associated with less confused and better-synthesized identity. Our data provide further evidence that the LRTC of intrinsic brain activity might serve as a noise suppression mechanism at the psychological level.

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Predicting Individual Variability in Task-Evoked Brain Activity in Schizophrenia

10.1101/2020.05.25.114603 ◽

2020 ◽

Author(s):

Niv Tik ◽

Abigail Livny ◽

Shachar Gal ◽

Karny Gigi ◽

Galia Tsarfaty ◽

...

Keyword(s):

Functional Connectivity ◽

Prediction Model ◽

Resting State ◽

Brain Activity ◽

Strong Association ◽

Brain Activation ◽

Individual Variability ◽

Resting State Functional Connectivity ◽

Successful Prediction ◽

And Task

AbstractBACKGROUNDPatients suffering from schizophrenia demonstrate abnormal brain activity, as well as alterations in patterns of functional connectivity assessed by functional magnetic resonance imaging (fMRI). Previous studies in healthy participants suggest a strong association between resting-state functional connectivity and task-evoked brain activity that could be detected at an individual level, and show that brain activation in various tasks could be predicted from task-free fMRI scans. In the current study we aimed to predict brain activity in patients diagnosed with schizophrenia, using a prediction model based on healthy individuals exclusively. This offers novel insights regarding the interrelations between brain connectivity and activity in schizophrenia.METHODSWe generated a prediction model using a group of 80 healthy controls that performed the well-validated N-back task, and used it to predict individual variability in task-evoked brain activation in 20 patients diagnosed with schizophrenia.RESULTSWe demonstrated a successful prediction of individual variability in the task-evoked brain activation based on resting-state functional connectivity. The predictions were highly sensitive, reflected by high correlations between predicted and actual activation maps (Median = 0.589, SD = 0.193) and specific, evaluated by a Kolomogrov-Smirnov test (D = 0.25, p < 0.0001).CONCLUSIONSA Successful prediction of brain activity from resting-state functional connectivity highlights the strong coupling between the two. Moreover, our results support the notion that even though resting-state functional connectivity and task-evoked brain activity are frequently reported to be altered in schizophrenia, the relations between them remains unaffected. This may allow to generate task activity maps for clinical populations without the need the actually perform the task.

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