Cognitive Resting State Networks Research Articles

Amplitudes of resting-state functional networks – investigation into their correlates and biophysical properties

Resting-state fMRI studies have shown that multiple functional networks, which consist of distributed brain regions that share synchronised spontaneous activity, co-exist in the brain. As these resting-state networks (RSNs) have been thought to reflect the brain's intrinsic functional organization, intersubject variability in the networks’ spontaneous fluctuations may be associated with individuals’ clinical, physiological, cognitive, and genetic traits. Here, we investigated resting-state fMRI data along with extensive clinical, lifestyle, and genetic data collected from 37,842 UK Biobank participants, with the object of elucidating intersubject variability in the fluctuation amplitudes of RSNs. Functional properties of the RSN amplitudes were first examined by analyzing correlations with the well-established between-network functional connectivity. It was found that a network amplitude is highly correlated with the mean strength of the functional connectivity that the network has with the other networks. Intersubject clustering analysis showed the amplitudes are most strongly correlated with age, cardiovascular factors, body composition, blood cell counts, lung function, and sex, with some differences in the correlation strengths between sensory and cognitive RSNs. Genome-wide association studies (GWASs) of RSN amplitudes identified several significant genetic variants reported in previous GWASs for their implications in sleep duration. We provide insight into key factors determining RSN amplitudes and demonstrate that intersubject variability of the amplitudes primarily originates from differences in temporal synchrony between functionally linked brain regions, rather than differences in the magnitude of raw voxelwise BOLD signal changes. This finding additionally revealed intriguing differences between sensory and cognitive RSNs with respect to sex effects on temporal synchrony and provided evidence suggesting that synchronous coactivations of functionally linked brain regions, and magnitudes of BOLD signal changes, may be related to different genetic mechanisms. These results underscore that intersubject variability of the amplitudes in health and disease need to be interpreted largely as a measure of the sum of within-network temporal synchrony and amplitudes of BOLD signals, with a dominant contribution from the former.

The impact of dopaminergic treatment over cognitive networks in Parkinson's disease: Stemming the tide?

Dopamine‐replacing therapies are an effective treatment for the motor aspects of Parkinson's disease. However, its precise effect over the cognitive resting‐state networks is not clear; whether dopaminergic treatment normalizes their functional connectivity‐as in other networks‐ and the links with cognitive decline are presently unknown. We recruited 35 nondemented PD patients and 16 age‐matched controls. Clinical and neuropsychological assessments were performed at baseline, and conversion to dementia was assessed in a 10 year follow‐up. Structural and functional brain imaging were acquired in both the ON and practical OFF conditions. We assessed functional connectivity in both medication states compared to healthy controls, connectivity differences within participants related to the ON/OFF condition, and baseline connectivity of PD participants that converted to dementia compared to those who did not convert. PD participants showed and increased frontoparietal connectivity compared to controls: a pattern of higher connectivity between salience (SN) and default‐mode (DMN) networks both in the ON and OFF states. Within PD patients, this higher SN‐DMN connectivity characterized the participants in the ON state, while within‐DMN connectivity prevailed in the OFF state. Interestingly, participants who converted to dementia also showed higher SN‐DMN connectivity in their baseline ON scans compared to nonconverters. To conclude, PD patients showed higher frontoparietal connectivity in cognitive networks compared to healthy controls, irrespective of medication status, but dopaminergic treatment specifically promoted SN‐DM hyperconnectivity.

Cognitive Networks Disarrangement in Patients With Migraine Predicts Cutaneous Allodynia.

Two-thirds of patients with migraine without aura (MwoA) complain ictal cutaneous allodynia (CA), clinical sign of central nociceptive pathway sensitization, and independent predictor for migraine chronification. We aimed to investigate whether functional abnormalities, structural, or microstructural changes of the main cognitive networks (default mode network [DMN], salience network [SN], and central executive network [CEN]) could predict the development of CA in patients with MwoA. Baseline 3-Tesla MRI images of 50 patients with MwoA were analyzed between 2009 and 2015. Over a three-year period, patients were then stratified into 2 groups based on CA development and compared with matched healthy controls (HC). Group-level independent components analysis was used to investigate intrinsic functional connectivity (FC) differences within the cognitive resting-state networks. Voxel-based morphometry (VBM) was used to assess whether group differences in cognitive network FC were related to structural differences. Tract-based spatial statistical analyses (TBSS) were conducted to assess the microstructural properties of white matter tracts. We also compared internetwork connectivity between patients. Finally, a logistic regression analysis was used to investigate baseline imaging predictors of CA development. We observed a significantly reduced FC of both DMN and CEN in patients with MwoA developing CA (MwoA d CA) when compared with both patients with MwoA not developing CA (MwoA nd CA) and HC. Within the DMN, the PCC/precuneus is a key hub aimed to anti-nociception and multisensory integration. The reduced intrinsic PCC/precuneus FC observed in patients with MwoA d CA could subtend abnormal inputs integration, from different sensory modalities, allowing the development of CA. On the other hand, within the CEN, a central role in pain modulation as well as in executive functions is played by ACC and MFG. Our finding of reduced ACC and MFG FC in MwoA d CA may represent the neuronal substrate of both subclinical impairment of complex executive functions and dysfunctional anti-nociceptive pathway, making these patients more prone to migraine chronification. TBSS analyses showed a statistically significant reduced corpus callosum (CC) FA in patients with MwoA d CA as previously demonstrated in migraine patients with other chronification factors such as medication overuse or affective disorders. No VBM differences in both global and local volumes were revealed between groups. No significant correlations have been found between the observed functional and microstructural changes and clinical parameters of disease severity. Logistic regression analysis indicated that the full model containing all predictors was statistically significant while the decreased ACC-FC was significantly associated with CA development. We suggest that DMN and CEN FC abnormalities as well as CC microstructural changes could represent a prognostic imaging biomarker able to identify migraine patients more prone to experiencing CA and therefore, more inclined to chronic migraine. In the new pharmacological scenario, it would be useful to address therapeutic resources to specific migraine populations with a high risk of more severe clinical phenotype.

Frontotemporal degeneration in amyotrophic lateral sclerosis (ALS): a longitudinal MRI one-year study.

Advanced neuroimaging techniques may offer the potential to monitor disease progression in amyotrophic lateral sclerosis (ALS), a neurodegenerative, multisystem disease that still lacks therapeutic outcome measures. We aim to investigate longitudinal functional and structural magnetic resonance imaging (MRI) changes in a cohort of patients with ALS monitored for one year after diagnosis. Resting state functional MRI, diffusion tensor imaging (DTI), and voxel-based morphometry analyses were performed in 22 patients with ALS examined by six-monthly MRI scans over one year. During the follow-up period, patients with ALS showed reduced functional connectivity only in some extramotor areas, such as the middle temporal gyrus in the left frontoparietal network after six months and in the left middle frontal gyrus in the default mode network after one year without showing longitudinal changes of cognitive functions. Moreover, after six months, we reported in the ALS group a decreased fractional anisotropy (P=.003, Bonferroni corrected) in the right uncinate fasciculus. Conversely, we did not reveal significant longitudinal changes of functional connectivity in the sensorimotor network, as well as of gray matter (GM) atrophy or of DTI metrics in motor areas, although clinical measures of motor disability showed significant decline throughout the three time points. Our findings highlighted that progressive impairment of extramotor frontotemporal networks may precede the appearance of executive and language dysfunctions and GM changes in ALS. Functional connectivity changes in cognitive resting state networks might represent candidate radiological markers of disease progression.

Altered functional connectivity between emotional and cognitive resting state networks in euthymic bipolar I disorder patients.

Bipolar disorder is characterized by a functional imbalance between hyperactive ventral/limbic areas and hypoactive dorsal/cognitive brain regions potentially contributing to affective and cognitive symptoms. Resting-state studies in bipolar disorder have identified abnormal functional connectivity between these brain regions. However, most of these studies used a seed-based approach, thus restricting the number of regions that were analyzed. Using data-driven approaches, researchers identified resting state networks whose spatial maps overlap with frontolimbic areas such as the default mode network, the frontoparietal networks, the salient network, and the meso/paralimbic network. These networks are specifically engaged during affective and cognitive tasks and preliminary evidence suggests that functional connectivity within and between some of these networks is impaired in bipolar disorder. The present study used independent component analysis and functional network connectivity approaches to investigate functional connectivity within and between these resting state networks in bipolar disorder. We compared 30 euthymic bipolar I disorder patients and 35 age- and gender-matched healthy controls. Inter-network connectivity analysis revealed increased functional connectivity between the meso/paralimbic and the right frontoparietal network in bipolar disorder. This abnormal connectivity pattern did not correlate with variables related to the clinical course of the disease. The present finding may reflect abnormal integration of affective and cognitive information in ventral-emotional and dorsal-cognitive networks in euthymic bipolar patients. Furthermore, the results provide novel insights into the role of the meso/paralimbic network in bipolar disorder.

Motor Imagery Learning Modulates Functional Connectivity of Multiple Brain Systems in Resting State

BackgroundLearning motor skills involves subsequent modulation of resting-state functional connectivity in the sensory-motor system. This idea was mostly derived from the investigations on motor execution learning which mainly recruits the processing of sensory-motor information. Behavioral evidences demonstrated that motor skills in our daily lives could be learned through imagery procedures. However, it remains unclear whether the modulation of resting-state functional connectivity also exists in the sensory-motor system after motor imagery learning.Methodology/Principal FindingsWe performed a fMRI investigation on motor imagery learning from resting state. Based on previous studies, we identified eight sensory and cognitive resting-state networks (RSNs) corresponding to the brain systems and further explored the functional connectivity of these RSNs through the assessments, connectivity and network strengths before and after the two-week consecutive learning. Two intriguing results were revealed: (1) The sensory RSNs, specifically sensory-motor and lateral visual networks exhibited greater connectivity strengths in precuneus and fusiform gyrus after learning; (2) Decreased network strength induced by learning was proved in the default mode network, a cognitive RSN.Conclusions/SignificanceThese results indicated that resting-state functional connectivity could be modulated by motor imagery learning in multiple brain systems, and such modulation displayed in the sensory-motor, visual and default brain systems may be associated with the establishment of motor schema and the regulation of introspective thought. These findings further revealed the neural substrates underlying motor skill learning and potentially provided new insights into the therapeutic benefits of motor imagery learning.

Functional Connectivity Abnormalities and Cognitive Impairment in Relapse-Onset MS Patients: A Whole-Brain Functional Network Connectivity Analysis (P03.072)

Objective: To explore abnormalities of functional connectivity (FC) and of functional interaction among cognitive resting state networks (RSNs) in patients with relapsing remitting (RR) and secondary progressive (SP) MS, and their correlation with cognitive impairment and damage to selected white matter (WM) tracts. Background Previous studies showed abnormal RS FC of the default mode network (DMN) in progressive MS patients. Design/Methods: RS fMRI and diffusion tensor (DT) MRI were acquired from 30 RRMS, 30 SPMS patients and 30 matched controls. Maps of the corpus callosum (CC) and cingulum were produced using DT tractography. Independent component analysis (ICA) and a template-matching procedure identified the DMN, the executive control network (ECN) and the salience network (SN). Within-group and between-group RS FC comparisons were performed with SPM8. The Functional network connectivity (FNC) toolbox was used to assess changes of interactions among RSNs. In MS patients, correlations between network abnormalities, cognitive impairment and structural damage were also assessed. Results: Significant RS FC abnormalities, which were more pronounced in SPMS vs. RRMS, were detected in the three RSNs, and were characterized by a decreased FC in the frontal, temporal, parahippocampal gyri, and the cerebellum, as well as an increased FC in the anterior cingulate cortex. FC abnormalities were more severe in cognitively impaired vs. cognitively preserved patients, and were correlated moderately with DT MRI indexes of damage to the CC and cingulum. FNC analysis detected a decreased connection between the DMN and ECN, and an increased connection between the SN and ECN in both RRMS and SPMS patients. SPMS also showed an increased FC between the SN and DMN. Altered connectivity among RSNs was correlated moderately with cognitive and structural MRI variables. Conclusions: Intra-network and inter-network dysfunction at rest is associated to more severe cognitive deficits in MS patients. Supported by: The study was partially supported by a grant from FISM/2008/R/13. Disclosure: Ms. Rocca has received personal compensation for activities with Bayer Schering Pharma and Biogen Idec as a consultant. Dr. Valsasina has nothing to disclose. Dr. Preziosa has nothing to disclose. Dr. Riccitelli has nothing to disclose. Dr. Martinelli has received personal compensation for activities with Biogen Dompe, Merck Serono, Bayer Schering, Teva, and Sanofi Aventis as a speaker. Dr. Falini has nothing to disclose. Dr. Comi has received personal compensation for activities with Novartis, Teva Neuroscience, Sanofi-Aventis Pharmaceuticals, Inc., Merck Serono, Bayer Schering, and Biogen Dompe. Dr. Filippi has received personal compensation for activities with ECTRIMS, MSIF, MS Ireland, US NMSS, Bayer-Schering, Biogen-Dompe AG, Genmab, Merck Serono, Pepgen Corporation, Teva, and Sanofi-Aventis. Dr. Filippi has received research support from Teva, Bayer-Schering and Genmab.