Extraction of robust functional connectivity patterns across psychiatric disorders using principal component analysis-based feature selection.

Background and objectivesGlaucoma is one of the leading irreversible causes of blindness worldwide, and previous studies have shown that there is abnormal functional connectivity (FC) in the visual cortex of glaucoma patients. The thalamus is a relay nucleus for visual signals; however, it is not yet clear how the FC of the thalamus is altered in glaucoma. This study investigated the alterations in thalamic FC in patients with primary angle-closure glaucoma (PACG) by using resting-state functional MRI (rs-fMRI). We hypothesized that PACG patients have abnormal FC between the thalamus and visual as well as extravisual brain regions.MethodsClinically confirmed PACG patients and age- and gender-matched healthy controls (HCs) were evaluated by T1 anatomical and functional MRI on a 3 T scanner. Thirty-four PACG patients and 33 HCs were included in the rs-fMRI analysis. All PACG patients underwent complete ophthalmological examinations; included retinal nerve fiber layer thickness (RNFLT), intraocular pressure (IOP), average cup-to-disc ratio (A-C/D), and vertical cup-to-disc ratio (V-C/D). After the MRI data were preprocessed, the bilateral thalamus was chosen as the seed point; and the differences in resting-state FC between groups were evaluated. The brain regions that significantly differed between PACG patients and HCs were identified, and the correlations were then evaluated between the FC coefficients of these regions and clinical variables.ResultsCompared with the HCs, the PACG patients showed decreased FC between the bilateral thalamus and right transverse temporal gyrus, between the bilateral thalamus and left anterior cingulate cortex, and between the left thalamus and left insula. Concurrently, increased FC was found between the bilateral thalamus and left superior frontal gyrus in PACG patients. The FC between the bilateral thalamus and left superior frontal gyrus was positively correlated with RNFLT and negatively correlated with the A-C/D and V-C/D. The FC between the left thalamus and left insula was negatively correlated with IOP.ConclusionExtensive abnormal resting-state functional connections between the thalamus and visual and extravisual brain areas were found in PACG patients, and there were certain correlations with clinical variables, suggesting that abnormal thalamic FC plays an important role in the progression of PACG.

Objective To study the resting-state functional connectivity(FC) changes of anterior cingulate cortex(ACC) and amygdala in adolescent patients with medication-naive first-episode major depressive disorder(MDD). Methods Medication-naive first-episode MDD adolescents(n=30) and pair-wise matched healthy controls(HCs, n=29) underwent resting-state functional magnetic resonance images(fMRI). To study whether there were different in FC changes between amygdala and ACC and whole brain regions, and whether abnormal FC was related to clinical characteristics. Results Compared with HCs, the adolescent MDD patients showed decreased FC between the left amygdala and right thalamus(MNI x, y, z: 15, -21, 18)(t=-2.85)and increased FC between the left amygdala and the bilateral temporal middle gyrus, left occipital gyrus, right medial prefrontal cortex(MPFC)(MNI x, y, z: 9, 66, 15)(t=2.80). The right amygdale showed decreased FC with bilateral middle frontal gyrus, left caudate(MNI x, y, z: -15, -9, 21)(t=-2.53), right thalamus(MNI x, y, z: 12, -36, 12)(t=-3.01), right cerebellum(MNI x, y, z: 3, -84, -33)(t=-2.45) and increased FC with right temporal middle gyrus, right MPFC(MNI x, y, z: 6, 69, 12)(t=2.41). The left ACC showed decreased FC with left cerebellum(MNI x, y, z: 12, -87, -24)(t=-2.36), left frontal inferior triangle gyrus, right frontal inferior orbital gyrus and increased FC with right frontal middle orbital gyrus.The right ACC showed decreased FC with left caudate(MNI x, y, z: -15, 21, 6)(t=-2.29), right temporal middle gyrus, right MPFC(MNI x, y, z: 9, 54, 36)(t=-2.29), right frontal inferior orbital gyrus, right angular(MNI x, y, z: 45, -51, 21)(t=-3.01), left dorsolateral prefrontal cortex(MNI x, y, z: -21, 33, 36)(t=-2.61). The increased FC between the left amygdale and bilateral temporal middle gyrus showed positive correlation with the score of HAMD(r=0.50, P<0.05; r=0.45, P<0.05). And the FC between the right amygdale and right middle frontal gyrus was positive correlation with duration of disease(r=0.63, P<0.05). Conclusion There is widespread FC disorder in amygdala and ACC in adolescents patients with first-episode depression.Abnormal FC changes may be the neuropathological mechanism of depression. Key words: Adolescent major depressive disorder; Resting-state fMRI; Functional connectivity; Amygdala; Anterior cingulated cortex

The whole-brain functional connectivity (FC) pattern obtained from resting-state functional magnetic resonance imaging data are commonly applied to study neuropsychiatric conditions such as autism spectrum disorder (ASD) by using different machine learning models. Recent studies indicate that both hyper- and hypo- aberrant ASD-associated FCs were widely distributed throughout the entire brain rather than only in some specific brain regions. Deep neural networks (DNN) with multiple hidden layers have shown the ability to systematically extract lower-to-higher level information from high dimensional data across a series of neural hidden layers, significantly improving classification accuracy for such data. In this study, a DNN with a novel feature selection method (DNN-FS) is developed for the high dimensional whole-brain resting-state FC pattern classification of ASD patients vs. typical development (TD) controls. The feature selection method is able to help the DNN generate low dimensional high-quality representations of the whole-brain FC patterns by selecting features with high discriminating power from multiple trained sparse auto-encoders. For the comparison, a DNN without the feature selection method (DNN-woFS) is developed, and both of them are tested with different architectures (i.e., with different numbers of hidden layers/nodes). Results show that the best classification accuracy of 86.36% is generated by the DNN-FS approach with 3 hidden layers and 150 hidden nodes (3/150). Remarkably, DNN-FS outperforms DNN-woFS for all architectures studied. The most significant accuracy improvement was 9.09% with the 3/150 architecture. The method also outperforms other feature selection methods, e.g., two sample t-test and elastic net. In addition to improving the classification accuracy, a Fisher's score-based biomarker identification method based on the DNN is also developed, and used to identify 32 FCs related to ASD. These FCs come from or cross different pre-defined brain networks including the default-mode, cingulo-opercular, frontal-parietal, and cerebellum. Thirteen of them are statically significant between ASD and TD groups (two sample t-test p < 0.05) while 19 of them are not. The relationship between the statically significant FCs and the corresponding ASD behavior symptoms is discussed based on the literature and clinician's expert knowledge. Meanwhile, the potential reason of obtaining 19 FCs which are not statistically significant is also provided.

Secular Mindfulness-Based Interventions: Efficacy and Neurobiology.

The abnormal brain functional connectivity (FC) of patients with mental diseases is closely linked to the transition features among brain states. However, the current research on state transition will produce certain division deviations in the measurement method of state division, and also ignore the transition features among multiple states that contain more abundant information for analyzing brain diseases. To investigate the potential of the proposed method based on coarse-grained similarity measurement to solve the problem of state division, and consider the transition features among multiple states to analyze the FC abnormalities of autism spectrum disorder (ASD) patients. We used resting-state functional magnetic resonance imaging to examine 45 ASD and 47 healthy controls (HC). The FC between brain regions was calculated by the sliding window and correlation algorithm, and a novel coarse-grained similarity measure method was used to cluster the FC networks into five states, and then extract the features both of the state itself and the transition features among multiple states for analysis and diagnosis. (1) The state as divided by the coarse-grained measurement method improves the diagnostic performance of individuals with ASD compared with previous methods. (2) The transition features among multiple states can provide complementary information to the features of the state itself in the ASD analysis and diagnosis. (3) ASD individuals have different brain state transitions than HC. Specifically, the abnormalities in intra- and inter-network connectivity of ASD patients mainly occur in the default mode network, the visual network, and the cerebellum. Such results demonstrate that our approach with new measurements and new features is effective and promising in brain state analysis and ASD diagnosis.

Sensory processing dysfunction not only affects most individuals with autism spectrum disorder (ASD), but at least 5% of children without ASD also experience dysfunctional sensory processing. Our understanding of the relationship between sensory dysfunction and resting state brain activity is still emerging. This study compared long-range resting state functional connectivity of neural oscillatory behavior in children aged 8–12 years with autism spectrum disorder (ASD; N=18), those with sensory processing dysfunction (SPD; N=18) who do not meet ASD criteria, and typically developing control participants (TDC; N=24) using magnetoencephalography (MEG). Functional connectivity analyses were performed in the alpha and beta frequency bands, which are known to be implicated in sensory information processing. Group differences in functional connectivity and associations between sensory abilities and functional connectivity were examined. Distinct patterns of functional connectivity differences between ASD and SPD groups were found only in the beta band, but not in the alpha band. In both alpha and beta bands, ASD and SPD cohorts differed from the TDC cohort. Somatosensory cortical beta-band functional connectivity was associated with tactile processing abilities, while higher-order auditory cortical alpha-band functional connectivity was associated with auditory processing abilities. These findings demonstrate distinct long-range neural synchrony alterations in SPD and ASD that are associated with sensory processing abilities. Neural synchrony measures could serve as potential sensitive biomarkers for ASD and SPD.

We examined the functional connectivity of subcallosal cingulate gyrus (SCG), nucleus accumbens (NAc), and ventral caudate (VCa), the main target areas for the treatment of major depression disorder (MDD), using deep brain stimulation (DBS). MDD is one of the most common diseases in the world, and approximately 30% of MDD patients do not respond to common therapies, including psychotherapy and antidepressant medications. Alternatively, DBS has been recently used to treat MDD. Resting state fMRI was obtained from seventeen healthy subjects and seven MDD patients. The functional connectivity network of the brain was constructed for all subjects and measured by the `degree' value for each SCG, NAc, and VCa regions using the graph theory analysis. The results show that the degree values of VCa and the left SCG are higher in the MDD group than the healthy group. Furthermore, the patterns of the degree values were different for the right and left hemispheres in MDD patients. Our findings suggest that degree values and their patterns have a potential to be used as diagnosis tools to detect the brain areas with abnormal functional connectivity.

To investigate the functional connectivity of the default-mode network (DMN) in patients with end-stage renal disease (ESRD) by using independent component analysis of resting-state functional magnetic resonance (MR) imaging and to correlate these DMN connectivity changes with neuropsychological test results and clinical biomarkers. Medical research ethics committee approval and written informed consent were obtained. Forty-six patients with ESRD, including 22 with minimal nephrotic encephalopathy (MNE) and 24 without nephrotic encephalopathy, and 23 healthy control subjects underwent resting-state functional MR imaging. All patients were asymptomatic and without history of neurologic or psychiatric disease. Independent component analysis was used to isolate the DMN. To display the voxels that contributed most strongly to an independent component, the intensity values in each spatial map were converted to z scores, which indirectly provided a measurement of functional connectivity in the DMN. Maps of the DMN were compared among the groups. Pearson correlation analysis was performed to correlate abnormal DMN functional connectivity with serum urea, creatinine, duration of dialysis, duration of disease, and neuropsychological test scores. Patients with ESRD showed significantly less functional connectivity in the posterior cingulate cortex, precuneus, and medial prefrontal cortex (MPFC) (P < .01) than did control subjects. Comparison of the two patient groups showed significantly reduced functional connectivity in the superior and MPFC in the MNE group (P < .01). The functional connectivity of the MPFC was positively correlated with digital symbol test score (R = 0.293, P = .048). Serum creatinine level was negatively correlated with functional connectivity of the posterior cingulate cortex and precuneus in patients with ESRD (R = -0.51, P = .002). Functional connectivity in the DMN was impaired in patients with ESRD, with further reduction in the MPFC with the development of MNE, which might explain the reduced performance of these patients on neurocognitive tests. Serum creatinine level might be associated with impairment of the DMN in patients with ESRD.

Is schizophrenia a spatiotemporal disorder of the brain's resting state?

2. Muller RA, Shih P, Keehn B, Deyoe JR, Leyden KM, Shukla DK. Underconnected, but how? A survey of functional connectivity MRI studies in autism spectrum disorders. Cereb Cortex. 2011 Oct;21(10):2233-43. 3. Just MA, Cherkassky VL, Keller TA, Kana RK, Minshew NJ. Functional and anatomical cortical underconnectivity in autism: evidence from an FMRI study of an executive function task and corpus callosum morphometry. Cereb Cortex 2007;17:951–61. 4. Kleinhans NM, Richards T, Sterling L, Stegbauer KC, Mahurin R, Johnson LC, Greenson J, Dawson G, Aylward E. Abnormal functional connectivity in autism spectrum disorders during face processing. Brain 2008;131:1000–12. 5. Raichle ME, MacLeod AM, Snyder AZ, Powers WJ, Gusnard DA, Shulman GL. 2001. A default mode of brain function. Proc. Natl. Acad. Sci. USA 98:676–82 6. Weng SJ, Wiggins JL, Peltier SJ, Carrasco M, Risi S, Lord C, Monk CS. Alterations of resting state functional connectivity in the default network in adolescents with autism spectrum disorders. Brain Res. 2010 Feb 8;1313:202-14. 7. Monk CS, Peltier SJ, Wiggins JL, Weng SJ, Carrasco M, Risi S, Lord C. Abnormalities of intrinsic functional connectivity in autism spectrum disorders. Neuroimage 2009;47:764–772. 8. Dalton KM, BM Nacewicz, T Johnstone, HS Schaefer, MA Gernsbacher, HH Goldsmith, AL Alexander, and RJ Davidson. Gaze fixation and the neural circuitry of face processing in autism. Nat Neurosci; 2005. 8(4): p. 519-26 9. Wechsler D, Wechsler Abbreviated Scale of Intelligence (WASI). 4th ed. 1999, San Antonio, Tx: The Psychological Corporation. 10. Thesen, S., O. Heid, E. Mueller, and L.R. Schad, Prospective acquisition correction for head motion with image-based tracking for real-time fMRI. Magn Reson Med, 2000. 44(3): p. 457-65. 11. Behzadi, Y., Restom, K., Liau, J. and Liu, T.T. (2007) A component based noise correction method (CompCor) for BOLD and perfusion based fMRI. NeuroImage, 37: 90-101. Resting State Functional Connectivity in Autism Spectrum Disorders: An fMRI Study!

Mainero C, Boshyan J, Hadjikhani N. Altered functional magnetic resonance imaging resting-state connectivity in periaqueductal gray networks in migraine. Annals of Neurology 2011;70:838-845. Objective: The periaqueductal gray matter (PAG), a known modulator of somatic pain transmission, shows evidence of interictal functional and structural abnormalities in migraineurs, which may contribute to hyperexcitability along spinal and trigeminal nociceptive pathways, and lead to the migraine attack. The aim of this study was to examine functional connectivity of the PAG in migraine. Methods: Using resting-state functional MRI, we compared functional connectivity between PAG and a subset of brain areas involved in nociceptive/somatosensory processing and pain modulation in 17 subjects with migraine, during a pain-free state, versus 17 genderand age-matched controls. We also assessed the relation between intrinsic resting-state correlations within PAG networks and the average monthly frequency of migraine attacks, as well as allodynia. Results: Our findings show stronger connectivity between the PAG and several brain areas within nociceptive and somatosensory processing pathways in migraineurs versus controls. In addition, as the monthly frequency of migraine attacks worsens, the strength of the connectivity in some areas within these pathways increases, whereas a significant decrease in functional resting-state connectivity between the PAG and brain regions with a predominant role in pain modulation (prefrontal cortex, anterior cingulate, amygdala) can be evidenced. Finally, migraineurs with a history of allodynia exhibit significantly reduced connectivity between PAG, prefrontal regions, and anterior cingulate compared to migraineurs without allodynia. Interpretation: These data reveal interictal dysfunctional dynamics within pain pathways in migraine manifested as an impairment of the descending pain modulatory circuits, likely leading to loss of pain inhibition, and hyperexcitability primarily in nociceptive areas. Comments: Functional neuroimaging techniques have helped elucidate the underlying physiology of migraines. Unlike traditional functional magnetic resonance imaging scans done during a task, resting state functional connectivity is a relatively new neuroimaging technique in which participants are scanned at rest, and the lowfrequency spontaneous fluctuations found to be highly correlated are thought to represent brain areas that are functionally connected at baseline. Mainero et al recently conducted this study to assess the functional connectivity of the periaqueductal gray (PAG) (a region previously implicated in the pathogenesis of migraine) to other brain regions in 17 migraineurs interictally compared with 17 age-/gendermatched controls. They found that compared with the controls, the migraineurs had increased resting state functional connectivity between the PAG, and somatosensory and nociceptive processing pathways. The connections between the PAG and the supramarginal gyrus, anterior insula, and hypothalamus were increased in migraineurs with more frequent attacks, while the connections between PAG and the prefrontal cortex, anterior cingulate, amygdala, and medial thalamus were decreased in migraineurs with more frequent attacks. The 5 migraineurs with allodynia also had significantly reduced connectivity between the PAG and the anterior insula, anterior cingulate, and prefrontal cortex vs genderand age-matched migraineurs without allodynia. This study is one of the first to use resting state functional connectivity analyses to compare the intrinsic neural connections in migraineurs vs controls. As expected, many of the connections between the PAG, and nociceptive and sensory processing pathways were increased in the migraineurs, and some of those connections were stronger in those with more frequent attacks. However, unexpectedly, those with more frequent migraines and those with allodynia had decreased connections between the PAG and areas involved in the cognitive modulation of pain. This suggests that From the Graham Headache Center, Faulkner/Brigham and Women’s Hospital, Boston, MA,

Objective: To study resting-state functional connectivity (FC) of default mode network (DMN) in adolescent patients with first-episode drug-naive major depressive disorder (MDD). Methods: We enrolled thirty first-episode and drug-naive adolescent MDD patients and twenty-nine adolescent healthy control (HC) participants in the First Affiliated Hospital of Zhengzhou University. There were no differences in age, sex, and education between the MDD and HC group. Resting-state functional magnetic resonance images (fMRI) was performed. We selected posterior cingulate cortex (PCC) and medial prefrontal cortex (MPFC) of DMN as regions of interests (ROI). The differences of these regions from the whole brain functional connectivity were analyzed. The relations between abnormalities in FCs of DMN and clinical variables were further investigated. Results: Compared to the HCs, the MDD patients had congruently reduced FCs between the PCC and cerebellum, temporal cortices, occipital cortices, fusiform, dorsolateral prefrontal cortex. MPFC not only had reduced FCs with fusiform, temporal cortices, anterior cingulate cortex, but also had enhanced FCs with occipital cortices, parietal cortices, and precentral gyrus. In addition, the increased FC between the right MPFC and right precentral gyrus was positive correlated with Hamilton Rating Scale for Depression (HAMD) scores (r=0.38, P=0.04). The reduced FC between the left middle temporal gyrus and left PCC as well as the enhanced FC between the right middle cingulum and right MPFC were positive correlated with the duration of depression since onset (r=0.39, P=0.03; r=0.38, P=0.04). Conclusions: These findings show dysfunctional DMN connectivity of adolescent MDD patients. Neurodevelopmental abnormalities in DMN may present in adolescent MDD.

Background and PurposeTemporomandibular disorders (TMD), especially pain-related TMD, are closely related to social and psychological factors. We aimed to measure changes in spontaneous brain activity and its related functional connectivity (FC), as well as FC characteristics within the mood-regulating circuits (MRC) in TMD patients by resting-state functional magnetic resonance imaging (RS-fMRI), and to analyze the relationship between these parameters and emotional symptoms.Materials and MethodsTwenty-one adult TMD patients and thirty demographically matched healthy controls (HCs) underwent clinical scale evaluation and RS-fMRI scanning. After processing RS-fMRI data, the values of the amplitude of low-frequency fluctuation (ALFF) between the two groups were compared. Regions with abnormal ALFF values were selected as areas of interest (ROIs) to compare the differences of whole-brain seed-based FC between groups. The FCs between regions within MRC were also analyzed and compared. In addition, the relationships between RS-fMRI characteristics and pain and mood were explored by correlation and mediation analyses.ResultsCompared with HCs, TMD patients showed increased ALFF in the right parahippocampal gyrus (PHG), the right supplementary motor area, and the bilateral precentral gyrus, with decreased ALFF in the right cerebelum_crus2. Patients showed enhanced right PHG-related FC in the vermis and posterior cingulate cortex, orbitofrontal cortex (OFC)-related FC in the striatal-frontal regions, while decreased dorsolateral prefrontal cortex-related FC in the amygdala. In TMD patients, ALFF values in the right PHG and FC values between the right PHG and the vermis were positively correlated with depressive symptoms. Abnormal FCs in the left striatal-orbitofrontal pathway were correlated with pain and depressive symptoms. More importantly, mediation analysis revealed that chronic pain mediates the relationship between FC of right PHG with vermis and depressive symptoms, and abnormal FC in the left striatal-orbitofrontal pathway can mediate the association between pain and depressive symptoms.ConclusionTMD patients have dysregulated spontaneous activity and FC in the default mode network, sensorimotor network and pain-related regions, as well as dysfunction of the fronto-striatal-limbic circuits. The development of negative emotions in TMD may be related to the dysfunction of components within the reward system (especially hippocampus complex, OFC, striatum) due to chronic pain.

Numerous resting-state functional magnetic resonance imaging studies have revealed that major depressive disorder (MDD) is associated with abnormal functional connectivity (FC) within and between large-scale functional networks such as the default mode network (DMN), cognitive control network (CCN) and affective network (AN). Compared with healthy controls, individuals with MDD usually show (i) increased FC within the anterior DMN and decreased FC within the posterior DMN, (ii) decreased FC within the CCN and (iii) increased FC within limbic system and decreased FC in the reward system in the AN. Depression related interactive changes between networks have also been reported: (i) decreased FC between DMN and CCN, (ii) increased FC between DMN and AN, and (iii) decreased FC between CCN and AN. These findings on network interaction may represent impaired resource allocation and information integration in MDD. Major weakness in the present rfMRI studies of depression resides in small sample and lack of multidimensional features. Meanwhile, as several brain disorders may show commonly disrupted functional architectures, depression-related specific alterations are typically lacking. We suggest that future studies may advance by combining multidimensional big data and individualized characterization, as well as examining shared and distinct functional network mechanisms of MDD in the spectrum of psychiatric disorders.

Fatigue is commonly observed in pediatric multiple sclerosis (pedMS) patients, but its underlying mechanisms remain largely unexplored. We evaluated whether resting-state (RS) functional connectivity (FC) abnormalities in monoaminergic networks contributed to explain fatigue in pedMS. Fifty-five pedMS and twenty-three matched healthy controls (HC) underwent clinical and RS functional MRI assessment. Patients with Fatigue Severity Scale (FSS) score ≥ 4 were classified as fatigued (F). Patterns of dopamine-, noradrenaline- and serotonin-related RS FC were derived by constrained independent component analysis, using PET atlases for dopamine, noradrenaline, and serotonin transporters obtained in HCs' brain. Compared to non-fatigued (NF)-pedMS patients and HC, F-pedMS patients (15/55, 27.3%) showed decreased dopamine-related RS FC in the right postcentral gyrus. They also showed decreased dopamine-related RS FC in the left insula vs. HC and increased dopamine-related RS FC in the left middle temporal gyrus and cerebellum (lobule VI) vs. NF patients. In the noradrenaline-related network, F-pedMS patients showed decreased RS FC in the left superior parietal lobule and increased RS FC in the right thalamus vs. HC and NF-pedMS. Compared to HC, F-pedMS patients also showed decreased RS FC in the right calcarine cortex and increased RS FC in the right middle frontal gyrus. In the serotonin-related network, F-pedMS patients showed decreased RS FC in the right angular gyrus and increased RS FC in the right postcentral gyrus vs. NF-pedMS patients. In pedMS, fatigue is associated with specific monoaminergic network abnormalities, providing pathological markers for this bothersome symptom and putative targets for its treatment.