Propagated infra-slow intrinsic brain activity reorganizes across wake and slow wave sleep

Propagation of slow intrinsic brain activity has been widely observed in electrophysiogical studies of slow wave sleep (SWS). However, in human resting state fMRI (rs-fMRI), intrinsic activity has been understood predominantly in terms of zero-lag temporal synchrony (functional connectivity) within systems known as resting state networks (RSNs). Prior rs-fMRI studies have found that RSNs are generally preserved across wake and sleep. Here, we use a recently developed analysis technique to study propagation of infra-slow intrinsic blood oxygen level dependent (BOLD) signals in normal adults during wake and SWS. This analysis reveals marked changes in propagation patterns in SWS vs. wake. Broadly, ordered propagation is preserved within traditionally defined RSNs but lost between RSNs. Additionally, propagation between cerebral cortex and subcortical structures reverses directions, and intra-cortical propagation becomes reorganized, especially in visual and sensorimotor cortices. These findings show that propagated rs-fMRI activity informs theoretical accounts of the neural functions of sleep

Network-Targeted Approach and Postoperative Resting-State Functional Magnetic Resonance Imaging Are Associated with Seizure Outcome

Objective Postoperative resting‐state functional magnetic resonance imaging (MRI) in children with intractable epilepsy has not been quantified in relation to seizure outcome. Therefore, its value as a biomarker for epileptogenic pathology is not well understood. Methods In a sample of children with intractable epilepsy who underwent prospective resting‐state seizure onset zone (SOZ)‐targeted epilepsy surgery, postoperative resting‐state functional MRI (rs‐fMRI) was performed 6 to 12 months later. Graded normalization of the postoperative resting‐state SOZ was compared to seizure outcomes, patient, surgery, and anatomical MRI characteristics. Results A total of 64 cases were evaluated. Network‐targeted surgery, followed by postoperative rs‐fMRI normalization was significantly (p < 0.001) correlated with seizure reduction, with a Spearman rank correlation coefficient of 0.83. Of 39 cases with postoperative rs‐fMRI SOZ normalization, 38 (97%) became completely seizure free. In contrast, of the 25 cases without complete rs‐fMRI SOZ normalization, only 3 (5%) became seizure free. The accuracy of rs‐fMRI as a biomarker predicting seizure freedom is 94%, with 96% sensitivity and 93% specificity. Interpretation Among seizure localization techniques in pediatric epilepsy, network‐targeted surgery, followed by postoperative rs‐fMRI normalization, has high correlation with seizure freedom. This study shows that rs‐fMRI SOZ can be used as a biomarker of the epileptogenic zone, and postoperative rs‐fMRI normalization is a biomarker for SOZ quiescence

A Generative-Discriminative Basis Learning Framework to Predict Clinical Severity from Resting State Functional MRI Data

We propose a matrix factorization technique that decomposes the resting state fMRI (rs-fMRI) correlation matrices for a patient population into a sparse set of representative subnetworks, as modeled by rank one outer products. The subnetworks are combined using patient specific non-negative coefficients; these coefficients are also used to model, and subsequently predict the clinical severity of a given patient via a linear regression. Our generative-discriminative framework is able to exploit the structure of rs-fMRI correlation matrices to capture group level effects, while simultaneously accounting for patient variability. We employ ten fold cross validation to demonstrate the predictive power of our model on a cohort of fifty eight patients diagnosed with Autism Spectrum Disorder. Our method outperforms classical semi-supervised frameworks, which perform dimensionality reduction on the correlation features followed by non-linear regression to predict the clinical scores

fMRI biomarkers of social cognitive skills training in psychosis: Extrinsic and intrinsic functional connectivity.

Social cognitive skills training interventions for psychotic disorders have shown improvement in social cognitive performance tasks, but little was known about brain-based biomarkers linked to treatment effects. In this pilot study, we examined whether social cognitive skills training could modulate extrinsic and intrinsic functional connectivity in psychosis using functional magnetic resonance imaging (fMRI). Twenty-six chronic outpatients with psychotic disorders were recruited from either a Social Cognitive Skills Training (SCST) or an activity- and time-matched control intervention. At baseline and the end of intervention (12 weeks), participants completed two social cognitive tasks: a Facial Affect Matching task and a Mental State Attribution Task, as well as resting-state fMRI (rs-fMRI). Extrinsic functional connectivity was assessed using psychophysiological interaction (PPI) with amygdala and temporo-parietal junction as a seed region for the Facial Affect Matching Task and the Mental State Attribution task, respectively. Intrinsic functional connectivity was assessed with independent component analysis on rs-fMRI, with a focus on the default mode network (DMN). During the Facial Affect Matching task, we observed stronger PPI connectivity in the SCST group after intervention (compared to baseline), but no treatment-related change in the Control group. Neither group showed treatment-related changes in PPI connectivity during the Mental State Attribution task. During rs-fMRI, we found treatment-related changes in the DMN in the SCST group, but not in Control group. This study found that social cognitive skills training modulated both extrinsic and intrinsic functional connectivity in individuals with psychotic disorders after a 12-week intervention. These findings suggest treatment-related changes in functional connectivity as a potential brain-based biomarker of social cognitive skills training

Motor and language resting state functional magnetic resonance imaging in brain tumor patients

Background and purpose: Resting state functional magnetic resonance (RS-fMRI) correlation with pre-surgical functional status in patients with brain tumors is scarcely documented in the present literature. Aim of the present study was to investigate the validity of RS-fMRI as potential preoperative functional mapping tool in tumor brain surgery by exploring the association of motor and language RS-fMRI networks with subjects’ preoperative performance on motor and language clinical assessment respectively in patients with brain tumor. Materials and methods: 85 patients presented with brain tumor entities and 27 healthy controls were prospectively recruited for the present study. Clinical sample was subdivided into two groups according to mass localization: patients with tumors in proximity to motor cortex (n=59) underwent clinical examination for gross (paresis- muscle weakness) and fine (finger tapping) motor deficits. Patients harboring tumors in proximity to the left inferior frontal gyrus (n=35) were clinically assessed for apparent (expressive aphasia) and subtle language function (phonological verbal fluency) disturbances. All patients and healthy subjects underwent RS-fMRI with motor and language resting networks being derived by Independent Component Analysis (ICA). Results: In the motor group, patients with paresis demonstrated significantly (p=<0.01) reduced resting state BOLD-signal intensity in ipsilesional motor cortex in comparison to the respective one in contralesional-intact motor cortex. Significantly (p<0.01) decreased BOLD-signal intensity was additionally noticed in ipsilesional motor cortex of patients with paresis in comparison to patients with normal muscle strength. Furthermore, in patients with intact muscle strength, a strong positive correlation (r=0.70, p<0.01) between ipsilesional pre-central gyrus BOLD-signal and performance on finger tapping task was demonstrated. Compared to the healthy group, clinical motor group showed reduced resting state network activity, with patients’ ipsilesional pre- central gyrus BOLD-signal intensity to be significantly (p<0.01) lower than normals’ left and right pre-central gyri BOLD-signal intensities. Concerning language group, patients presented with expressive aphasia exhibited significantly (p=<0.01) reduced RS-fMRI BOLD-signal intensity in left inferior frontal gyrus (Broadmann area 44) when compared with patients without aphasia. In non-aphasic patients, a strong positive correlation (r=0.70, P<0.01) between left inferior frontal gyrus’ BOLD-signal intensity and phonological fluency scoring was demonstrated. Similarly with the motor group, language group also showed significantly (p=<0.01) reduced left inferior gyrus RS- fMRI BOLD-signal when compared to healthy controls. Finally, RS-fMRI BOLD signal was not observed to have an association with demographic parameters (age, gender) for both clinical and healthy groups and with tumor histopathological grading for both motor and language clinical groups. Conclusions: Our findings show a significant affection of motor and language RS-fMRI networks’ BOLD-signal intensity by the presence of a tumor and a correlation with clinical performance of patients providing thus evidence for the functional validity of RS-fMRI in brain tumor patients; our results indicate therefore, that RS-fMRI may be a valuable complementary tool for preoperative mapping of eloquent areas, at least in patients who cannot cooperate satisfactory in a traditional task-based motor and language fMRI