Decreased default-mode network homogeneity in unaffected siblings of schizophrenia patients at rest.
Psychiatry Res. 2014 Sep 1;
Authors: Guo W, Liu F, Yao D, Jiang J, Su Q, Zhang Z, Zhang J, Yu L, Zhai J, Xiao C
The dysconnectivity hypothesis proposes that abnormal resting state connectivity within the default-mode network (DMN) plays a key role in schizophrenia. Little is known, however, about alterations of the network homogeneity (NH) of the DMN in unaffected siblings of patients with schizophrenia. Unaffected siblings have unique advantages as subjects of neuroimaging studies independent of the clinical and treatment issues that complicate studies of the patients themselves. In the present study, we investigated NH of the DMN in unaffected siblings of schizophrenia. Participants comprised 46 unaffected siblings of schizophrenia patients and 50 age-, sex-, and education-matched healthy controls who underwent resting state functional magnetic resonance imaging (fMRI). Automated NH and group independent component analysis (ICA) approaches were used to analyze the data. Compared with healthy controls, the unaffected siblings of schizophrenia patients showed decreased DMN homogeneity in the left precuneus. No significantly increased DMN homogeneity was found in the sibling group relative to the control group. Our results suggest that there is decreased NH of the DMN in unaffected siblings of schizophrenia patients and indicate that the alternative perspective of examining the DMN NH in patients׳ siblings may improve understanding of the nature of schizophrenia.
PMID: 25242670 [PubMed - as supplied by publisher]
Alteration of Default Mode Network in High School Football Athletes Due to Repetitive Sub-concussive mTBI - A resting state fMRI study.
Brain Connect. 2014 Sep 22;
Authors: Abbas K, Shenk TE, Poole VN, Breedlove EL, Leverenz LJ, Nauman EA, Talavage TM, Robinson ME
Long-term neurological damage as a result of head trauma while playing sports is a major concern for football athletes today. Repetitive concussions have been linked to many neurological disorders. Recently, it has been reported that repetitive sub-concussive events can be a significant source of accrued damage. Since football athletes can experience hundreds of sub-concussive hits during a single season, it is of utmost importance to understand their effect on brain health in the short- and long-term. In this study, resting state functional magnetic resonance imaging (rs-fMRI) was used to study changes in the Default Mode Network (DMN) after repetitive sub-concussive mTBI. Twenty-two high school American football athletes, clinically asymptomatic, were scanned using rs-fMRI for a single season. Baseline scans were acquired before the start of the season, and follow-up scans were obtained during and after the season to track the potential changes in the DMN as a result of experienced trauma. Ten non-collision-sport athletes were scanned over two sessions as controls. Overall, football athletes had significantly different functional connectivity measures than controls for most of the year. The presence of this deviation of football athletes from their healthy peers even before the start of the season suggests a neurological change that has accumulated over the years of playing the sport. Football athletes also demonstrate short-term changes relative to their own baseline at start of the season. Football athletes exhibited hyper-connectivity in the DMN compared to controls for most of the sessions, which indicates that, despite the absence of symptoms typically associated with concussion, the repetitive trauma accrued produced long-term brain changes compared to their healthy peers.
PMID: 25242171 [PubMed - as supplied by publisher]
Lateralization of Resting State Networks and Relationship to Age and Gender.
Neuroimage. 2014 Sep 17;
Authors: Agcaoglu O, Miller R, Mayer AR, Hugdahl K, Calhoun VD
Brain lateralization is a widely studied topic, however there has been little work focused on lateralization of intrinsic networks (regions showing similar patterns of covariation among voxels) in the resting brain. In this study, we evaluate resting state network lateralization in an age and gender-balanced functional magnetic resonance imaging (fMRI) dataset comprising over 600 healthy subjects ranging in age from 12 to 71. After establishing sample-wide network lateralization properties, we continue with an investigation of age and gender effects on network lateralization. All data was gathered on the same scanner and preprocessed using an automated pipeline (Scott et al., 2011). Networks were extracted via group independent component analysis (gICA) (Calhoun et al., 2001). Twenty-eight resting state networks discussed in previous (Allen et al., 2011) work were re-analyzed with a focus on lateralization. We calculated homotopic voxelwise measures of laterality in addition to a global lateralization measure, called the laterality cofactor, for each network. As expected, many of the intrinsic brain networks were lateralized. For example, the visual network was strongly right lateralized, auditory network and default mode networks were mostly left lateralized. Attentional and frontal networks included nodes that were left lateralized and other nodes that were right lateralized. Age was strongly related to lateralization in multiple regions including sensorimotor network regions precentral gyrus, postcentral gyrus and supramarginal gyrus; and visual network regions lingual gyrus; attentional network regions inferior parietal lobule, superior parietal lobule and middle temporal gyrus; and frontal network regions including the inferior frontal gyrus. Gender showed significant effects mainly in two regions, including visual and frontal networks. For example, the inferior frontal gyrus was more right lateralized in males. Significant effects of age were found in sensorimotor and visual networks on the global measure. In summary, we report a large-sample of lateralization study that finds intrinsic functional brain networks to be highly lateralized, with regions that are strongly related to gender and age locally, and with age a strong factor in lateralization, and gender exhibiting a trend-level effect on global measures of laterality.
PMID: 25241084 [PubMed - as supplied by publisher]
Neural substrates of rumination tendency in non-depressed individuals.
Biol Psychol. 2014 Sep 18;
Authors: Piguet C, Desseilles M, Sterpenich V, Cojan Y, Bertschy G, Vuilleumier P
The tendency to ruminate, experienced by both healthy individuals and depressed patients, can be quantified by the Ruminative Response Scale (RRS). We hypothesized that brain activity associated with rumination tendency might not only occur at rest but also persist to some degree during a cognitive task. We correlated RRS with whole-brain fMRI data of 20 healthy subjects during rest and during a face categorization task with different levels of cognitive demands (easy or difficult conditions). Our results reveal that the more subjects tend to ruminate, the more they activate the left entorhinal region, both at rest and during the easy task condition, under low attentional demands. Conversely, lower tendency to ruminate correlates with greater activation of visual cortex during rest and activation of insula during the easy task condition. These results indicate a particular neural marker of the tendency to ruminate, corresponding to increased spontaneous activity in memory-related areas, presumably reflecting more internally driven trains of thoughts even during a concomitant task. Conversely, people who are not prone to ruminate show more externally driven activity.
PMID: 25240323 [PubMed - as supplied by publisher]
Decreased connectivity of the default mode network in pathological gambling: A resting state functional MRI study.
Neurosci Lett. 2014 Sep 18;
Authors: Jung MH, Kim JH, Shin YC, Jung WH, Jang JH, Choi JS, Kang DH, Yi JS, Choi CH, Kwon JS
The default mode network (DMN) represents neuronal activity that is intrinsically generated during a resting state. The present study used resting-state fMRI to investigate whether functional connectivity is altered in pathological gambling (PG). Fifteen drug-naive male patients with PG and 15 age-matched male control subjects participated in the present study. The pathological gambling modification of the Yale-Brown Obsessive Compulsive Scale (PG-YBOCS), the Beck Depression Inventory, and the Beck Anxiety Inventory were used to determine symptom severity in all participants. Participants were instructed to keep their eyes closed and not to focus on any particular thoughts during the 4.68-min resting-state functional scan. The patients with PG displayed decreased default mode connectivity in the left superior frontal gyrus, right middle temporal gyrus, and precuneus compared with healthy controls. The severity of PG symptoms in patients with PG was negatively associated with connectivity between the posterior cingulate cortex seed region and the precuneus (r=-0.599, p=0.018). Decreased functional connectivity within DMN suggests that PG may share similar neurobiological abnormalities with other addictive disorders. Moreover, the severity of PG symptoms was correlated with decreased connectivity in the precuneus, which may be important in the response to treatment in patients with PG.
PMID: 25238959 [PubMed - as supplied by publisher]
Modafinil Alters Intrinsic Functional Connectivity of the Right Posterior Insula: A Pharmacological Resting State fMRI Study.
PLoS One. 2014;9(9):e107145
Authors: Cera N, Tartaro A, Sensi SL
BACKGROUND: Modafinil is employed for the treatment of narcolepsy and has also been, off-label, used to treat cognitive dysfunction in neuropsychiatric disorders. In a previous study, we have reported that single dose administration of modafinil in healthy young subjects enhances fluid reasoning and affects resting state activity in the Fronto Parietal Control (FPC) and Dorsal Attention (DAN) networks. No changes were found in the Salience Network (SN), a surprising result as the network is involved in the modulation of emotional and fluid reasoning. The insula is crucial hub of the SN and functionally divided in anterior and posterior subregions.
METHODOLOGY: Using a seed-based approach, we have now analyzed effects of modafinil on the functional connectivity (FC) of insular subregions.
PRINCIPAL FINDINGS: Analysis of FC with resting state fMRI (rs-FMRI) revealed increased FC between the right posterior insula and the putamen, the superior frontal gyrus and the anterior cingulate cortex in the modafinil-treated group.
CONCLUSIONS: Modafinil is considered a putative cognitive enhancer. The rs-fMRI modifications that we have found are consistent with the drug cognitive enhancing properties and indicate subregional targets of action.
TRIAL REGISTRATION: ClinicalTrials.gov NCT01684306.
PMID: 25237810 [PubMed - as supplied by publisher]
Opioid modulation of resting-state anterior cingulate cortex functional connectivity.
J Psychopharmacol. 2014 Sep 18;
Authors: Gorka SM, Fitzgerald DA, de Wit H, Angstadt M, Phan KL
Individuals misuse oxycodone, a widely prescribed opioid analgesic, in part to self-medicate physical and emotional pain. Physical and emotional pain is thought to be represented in the brain by a 'pain matrix,' consisting of the insula, thalamus, and somatosensory cortices, with processing of the affective dimension of pain in the dorsal and rostral anterior cingulate cortex (ACC). The current study examined oxycodone's effects on resting-state functional connectivity between the dorsal ACC, rostral ACC, and other regions of the pain matrix using functional magnetic resonance imaging (fMRI). In a within-subjects, randomized, double-blind, placebo-controlled, dose-response design, 14 healthy subjects completed a resting-state scan following ingestion of placebo, 10 mg, or 20 mg of oxycodone. Functional correlations between the dorsal and rostral ACC seed regions and the pain matrix were examined and compared across sessions. Both doses of oxycodone reduced functional coupling between the dorsal ACC and bilateral anterior insula/putamen and the rostral ACC and right insula relative to placebo (no differences between doses). The findings do not withstand correction for multiple comparisons, and thus should be considered preliminary. However, they are consistent with the idea that oxycodone may produce its physical and emotional 'analgesic' effects through disruption of ACC-insula and ACC-putamen connectivity.
PMID: 25237122 [PubMed - as supplied by publisher]
Prediction of post-earthquake depressive and anxiety symptoms: a longitudinal resting-state fMRI study.
Sci Rep. 2014;4:6423
Authors: Long J, Huang X, Liao Y, Hu X, Hu J, Lui S, Zhang R, Li Y, Gong Q
Neurobiological markers of stress symptom progression for healthy survivors from a disaster (e.g., an earthquake) would greatly help with early intervention to prevent the development of stress-related disorders. However, the relationship between the neurobiological alterations and the symptom progression over time is unclear. Here, we examined 44 healthy survivors of the Wenchuan earthquake in China in a longitudinal resting-state fMRI study to observe the alterations of brain functions related to depressive or anxiety symptom progression. Using multi-variate pattern analysis to the fMRI data, we successfully predicted the depressive or anxiety symptom severity for these survivors in short- (25 days) and long-term (2 years) and the symptom severity changes over time. Several brain areas (e.g., the frontolimbic and striatal areas) and the functional connectivities located within the fronto-striato-thalamic and default-mode networks were found to be correlated with the symptom progression and might play important roles in the adaptation to trauma.
PMID: 25236674 [PubMed - in process]
Short-term Cortical Plasticity Associated With Feedback-Error Learning After Locomotor Training in an Individual With Incomplete Spinal Cord Injury.
Phys Ther. 2014 Sep 18;
Authors: Chisholm AE, Peters S, Borich MR, Boyd LA, Lam T
BACKGROUND AND PURPOSE: For rehabilitation strategies to be effective, training should be based on principles of motor learning, such as feedback-error learning, that facilitate adaptive processes in the nervous system by inducing errors and recalibration of sensory and motor systems. This case report suggests that locomotor-resistance training can enhance somatosensory and corticospinal excitability, and modulate resting-state brain functional connectivity in a person with motor-incomplete spinal cord injury (iSCI).
CASE DESCRIPTION: Short-term cortical plasticity of a 31-year old man who had sustained an iSCI 9.5 years ago was examined in response to body-weight support treadmill training with a velocity-dependent resistance applied by the Lokomat robotic gait orthosis. The following neurophysiologic and neuroimaging measures were recorded before and after training. Sensory-evoked potentials were elicited by electrical stimulation of the tibial nerve, and recorded from the somatosensory cortex. Motor-evoked potentials were generated using transcranial magnetic stimulation applied over the tibialis anterior representation within the primary motor cortex. Resting-state functional magnetic resonance imaging (fMRI) was collected to evaluate short-term changes in patterns of brain activity associated with locomotor training.
OUTCOMES: Somatosensory and corticospinal excitability were observed to increase following the locomotor-resistance training. Motor-evoked potentials were increased (particularly at higher stimulation intensities), and seed-based resting-state fMRI analyses revealed increased functional connectivity strength within the motor cortex associated with the less affected side following training.
DISCUSSION: Our observations suggest evidence of short-term cortical plasticity after one session of locomotor-resistance training in three complementary neurophysiologic measures. Future investigation in a sample of individuals with iSCI will enhance our understanding of potential neural mechanisms underlying behavioral response to locomotor-resistance training.
PMID: 25234276 [PubMed - as supplied by publisher]
Increased functional connectivity within mesocortical networks in open people.
Neuroimage. 2014 Sep 16;
Authors: Passamonti L, Terracciano A, Riccelli R, Donzuso G, Cerasa A, Vaccaro MG, Novellino F, Fera F, Quattrone A
Openness is a personality trait reflecting absorption in sensory experience, preference for novelty, and creativity, and is thus considered a driving force of human evolution. At the brain level, a relation between openness and dopaminergic circuits has been proposed, although evidence to support this hypothesis is lacking. Recent behavioral research has also found that people with mania, a psychopathological condition linked to dopaminergic dysfunctions, may display high levels of openness. However, whether openness is related to dopaminergic circuits has not been determined thus far. We addressed this issue via three functional magnetic resonance imaging (fMRI) experiments in n=46 healthy volunteers. In the first experiment participants lied at rest in the scanner while in the other two experiments they performed active tasks that included the presentation of pleasant odors and pictures of food. Individual differences in openness and other personality traits were assessed via the NEO-PI-R questionnaire (NEO-Personality Inventory-Revised), a widely employed measure of the five-factor model personality traits. Correlation between fMRI and personality data was analyzed via state-of-art methods assessing resting-state and task-related functional connectivity within specific brain networks. Openness was positively associated with the functional connectivity between the right substantia nigra/ventral tegmental area, the major source of dopaminergic inputs in the brain, and the ipsilateral dorsolateral prefrontal cortex (DLPFC), a key region in encoding, maintaining, and updating information that is relevant for adaptive behaviors. Of note, the same connectivity pattern was consistently found across all of the three fMRI experiments. Given the critical role of dopaminergic signal in gating information in DLPFC, the increased functional connectivity within mesocortical networks in open people may explain why these individuals display a wide "mental permeability" to salient stimuli and an increased absorption in sensory experience.
PMID: 25234120 [PubMed - as supplied by publisher]
On spurious and real fluctuations of dynamic functional connectivity during rest.
Neuroimage. 2014 Sep 15;
Authors: Leonardi N, Van De Ville D
Functional brain networks reconfigure spontaneously during rest. Such network dynamics can be studied by dynamic functional connectivity (dynFC); i.e., sliding-window correlations between regional brain activity. Key parameters-such as window length and cut-off frequencies for filtering-are not yet systematically studied. In this letter we provide the fundamental theory from signal processing to address these parameter choices when estimating and interpreting dynFC. We guide the reader through several illustrative cases, both simple analytical models and experimental fMRI BOLD data. First, we show how spurious fluctuations in dynFC can arise due to the estimation method when the window length is shorter than the largest wavelength present in both signals, even for deterministic signals with a fixed relationship. Second, we study how real fluctuations of dynFC can be explained using a frequency-based view, which is particularly instructive for signals with multiple frequency components such as fMRI BOLD, demonstrates that fluctuations in sliding-window correlation emerge by interaction between frequency components similar to the phenomenon of beat frequencies. We conclude with practical guidelines for the choice and impact of the window length.
PMID: 25234118 [PubMed - as supplied by publisher]
Altered spontaneous neural activity in first-episode, unmedicated patients with major depressive disorder.
Neuroreport. 2014 Sep 16;
Authors: Shen T, Qiu M, Li C, Zhang J, Wu Z, Wang B, Jiang K, Peng D
Abnormal brain function is presumed to be a pathophysiological aspect of major depressive disorder (MDD). However, the underlying patterns of spontaneous neural activity have been poorly characterized and replicated to date. In this study, we applied a novel approach of fractional amplitude of low-frequency fluctuation (fALFF) to investigate the alteration of spontaneous neural activity in MDD. Sixteen first-episode, unmedicated patients with MDD and 16 healthy controls were recruited and subjected to resting-state fMRI scans to measure the fALFF across the whole brain. Compared with healthy controls, MDD patients exhibited decreased fALFF in the right angular gyrus, left middle temporal gyrus, left superior temporal gyrus, right putamen, right precuneus, and the right superior temporal gyrus. Differences in fALFF between MDD patients and controls indicated that altered spontaneous neural activity was distributed across a number of specific brain regions among MDD patients. These atypical functional regions may help explain some of the neural processes underlying the clinical symptoms accompanying MDD.
PMID: 25229945 [PubMed - as supplied by publisher]
Corrigendum: The quest for EEG power band correlation with ICA derived fMRI resting state networks.
Front Hum Neurosci. 2014;8:539
Authors: Meyer MC, Janssen RJ, Van Oort ES, Beckmann CF, Barth M
[This corrects the article on p. 315 in vol. 7, PMID: 23805098.].
PMID: 25228866 [PubMed - as supplied by publisher]
Resting state fMRI feature-based cerebral glioma grading by support vector machine.
Int J Comput Assist Radiol Surg. 2014 Sep 17;
Authors: Wu J, Qian Z, Tao L, Yin J, Ding S, Zhang Y, Yu Z
PURPOSE : Tumor grading plays an essential role in the optimal selection of solid tumor treatment. Noninvasive methods are needed for clinical grading of tumors. This study aimed to extract parameters of resting state blood oxygenation level-dependent functional magnetic resonance imaging (RS-fMRI) in the region of glioma and use the extracted features for tumor grading. METHODS : Tumor segmentation was performed with both conventional MRI and RS-fMRI. Four typical parameters, signal intensity difference ratio, signal intensity correlation (SIC), fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity (ReHo), were defined to analyze tumor regions. Mann-Whitney [Formula: see text] test was employed to identify statistical difference of these four parameters between low-grade glioma (LGG) and high-grade glioma (HGG), respectively. Support vector machine (SVM) was employed to assess the diagnostic contributions of these parameters. RESULTS : Compared with LGG, HGG had more complex anatomical morphology and BOLD-fMRI features in the tumor region. SIC [Formula: see text], fALFF ([Formula: see text]) and ReHo ([Formula: see text]) were selected as features for classification according to the test [Formula: see text] value. The accuracy, sensitivity and specificity of SVM classification were better than 80, where SIC had the best classification accuracy (89). CONCLUSION : Parameters of RS-fMRI are effective to classify the tumor grade in glioma cases. The results indicate that this technique has clinical potential to serve as a complementary diagnostic tool.
PMID: 25227532 [PubMed - as supplied by publisher]
Insights into the mechanisms of absence seizure generation provided by EEG with functional MRI.
Front Neurol. 2014;5:162
Authors: Carney PW, Jackson GD
Absence seizures (AS) are brief epileptic events characterized by loss of awareness with subtle motor features. They may be very frequent, and impact on attention, learning, and memory. A number of pathophysiological models have been developed to explain the mechanism of absence seizure generation, which relies heavily on observations from animal studies. Studying the structural and functional relationships between large-scale brain networks in humans is only practical with non-invasive whole brain techniques. EEG with functional MRI (EEG-fMRI) is one such technique that provides an opportunity to explore the interactions between brain structures involved in AS generation. A number of fMRI techniques including event-related analysis, time-course analysis, and functional connectivity (FC) have identified a common network of structures involved in AS. This network comprises the thalamus, midline, and lateral parietal cortex [the default mode network (DMN)], caudate nuclei, and the reticular structures of the pons. The main component displaying an increase in blood oxygen level dependent (BOLD) signal relative to the resting state, in group studies, is the thalamus while the most consistent cortical change is reduced BOLD signal in the DMN. Time-course analysis shows that, rather than some structures being activated or inactivated during AS, there appears to be increase in activity across components of the network preceding or following the electro-clinical onset of the seizure. The earliest change in BOLD signal occurs in the DMN, prior to the onset of epileptiform events. This region also shows altered FC in patients with AS. Hence, it appears that engagement of this network is central to AS. In this review, we will explore the insights of EEG-fMRI studies into the mechanisms of AS and consider how the DMN is likely to be the major large-scale brain network central to both seizure generation and seizure manifestations.
PMID: 25225491 [PubMed]
Denoising the Speaking Brain: Toward a Robust Technique for Correcting Artifact-Contaminated fMRI Data under Severe Motion.
Neuroimage. 2014 Sep 12;
Authors: Xu Y, Tong Y, Liu S, Chow HM, AbdulSabur NY, Mattay GS, Braun AR
A comprehensive set of methods based on spatial independent component analysis (sICA) is presented as a robust technique for artifact removal, applicable to a broad range of functional magnetic resonance imaging (fMRI) experiments that have been plagued by motion-related artifacts. Although the applications of sICA for fMRI denoising have been studied previously, three fundamental elements of this approach have not been established: 1) a mechanistically-based ground truth for component classification; 2) a general framework for evaluating the performance and generalizability of automated classifiers; 3) a reliable method for validating the effectiveness of denoising. Here we perform a thorough investigation of these issues and demonstrate the power of our technique by resolving the problem of severe imaging artifacts associated with continuous overt speech production. As a key methodological feature, a dual-mask sICA method is proposed to isolate a variety of imaging artifacts by directly revealing their extracerebral spatial origins. It also plays an important role for understanding the mechanistic properties of noise components in conjunction with temporal measures of physical or physiological motion. The potentials of a spatially-based machine learning classifier and the general criteria for feature selection have both been examined, in order to maximize the performance and generalizability of automated component classification. The effectiveness of denoising is quantitatively validated by comparing the activation maps of fMRI with those of positron emission tomography acquired under the same task conditions. The general applicability of this technique is further demonstrated by the successful reduction of distance-dependent effect of head motion on resting-state functional connectivity.
PMID: 25225001 [PubMed - as supplied by publisher]
Understanding Human Original Actions Directed at Real-Worls Goals: The Role of the Lateral Prefrontal Cortex.
Neuroimage. 2014 Sep 12;
Authors: Sitnikova T, Rosen BR, Lord LD, Caroline West W
Adaptive, original actions, which can succeed in multiple contextual situations, require understanding of what is relevant to a goal. Recognizing what is relevant may also help in predicting kinematics of observed, original actions. During action observation, comparisons between sensory input and expected action kinematics have been argued critical to accurate goal inference. Experimental studies with laboratory tasks, both in humans and nonhuman primates, demonstrated that the lateral prefrontal cortex (LPFC) can learn, hierarchically organize, and use goal-relevant information. To determine whether this LPFC capacity is generalizable to real-world cognition, we recorded functional magnetic resonance imaging (fMRI) data in the human brain during comprehension of original and usual object-directed actions embedded in video-depictions of real-life behaviors. We hypothesized that LPFC will contribute to forming goal-relevant representations necessary for kinematic predictions of original actions. Additionally, resting-state fMRI was employed to examine functional connectivity between the brain regions delineated in the video fMRI experiment. According to behavioral data, original videos could be understood by identifying elements relevant to real-life goals at different levels of abstraction. Patterns of enhanced activity in four regions in the left LPFC, evoked by original, relative to usual, video scenes, were consistent with previous neuroimaging findings on representing abstract and concrete stimuli dimensions relevant to laboratory goals. In the anterior left LPFC, the activity increased selectively when representations of broad classes of objects and actions, which could achieve the perceived overall behavioral goal, were likely to bias kinematic predictions of original actions. In contrast, in the more posterior regions, the activity increased even when concrete properties of the target object were more likely to bias the kinematic prediction. Functional connectivity was observed between contiguous regions along the rostro-caudal LPFC axis, but not between the regions that were not immediately adjacent. These findings generalize the representational hierarchy account of LPFC function to diverse core principles that can govern both production and comprehension of flexible real-life behavior.
PMID: 25224997 [PubMed - as supplied by publisher]
Optimizing affinity measures for parcellating brain structures based on resting state fMRI data: a validation on medial superior frontal cortex.
J Neurosci Methods. 2014 Sep 12;
Authors: Cheng H, Wu H, Fan Y
BACKGROUND: Parcellating brain structures into functionally homogeneous subregions based on resting state fMRI data could be achieved by grouping image voxels using clustering algorithms, such as normalized cut. The affinity between brain voxels adopted in the clustering algorithms is typically characterized by a combination of the similarity of their functional signals and their spatial distance with parameters empirically specified. However, improper parameter setting of the affinity measure may result in parcellation results biased to spatial smoothness.
NEW METHOD: To obtain a functionally homogeneous and spatially contiguous brain parcellation result, we propose to optimize the affinity measure of image voxels using a constrained bi-level programming optimization method. Particularly, we first identify the space of all possible parameters that are able to generate spatially contiguous brain parcellation results. Then, within the constrained parameter space we search those leading to the brain parcellation results with optimal functional homogeneity and spatial smoothness.
RESULTS AND COMPARISON WITH EXISTING METHODS: The method has successfully parcellated medial superior frontal cortex into supplementary motor area (SMA) and pre-SMA for 106 subjects based on their resting state fMRI data. These results have been validated through functional connectivity analysis and meta-analysis of existing functional imaging studies and compared with those obtained by state-of-the-art brain parcellation methods.
CONCLUSIONS: The validation results have demonstrated that our method could obtain brain parcellation results consistent with the existing functional anatomy knowledge, and the comparison results have further demonstrated that optimizing affinity measure could improve the brain parcellation's robustness and functional homogeneity.
PMID: 25224735 [PubMed - as supplied by publisher]
Exploring variations in functional connectivity of the resting state default mode network in mild traumatic brain injury.
Brain Connect. 2014 Sep 15;
Authors: Nathan DE, Yeh PH, French LM, Harper JF, Liu W, Wolfowitz RD, Wang BQ, Graner JL, Oakes T, Riedy G
A definitive diagnosis of mTBI is difficult due to the absence of biomarkers in standard clinical imaging. The brain is a complex network of interconnected neurons and subtle changes can modulate key networks of cognitive function. The resting state default mode network (DMN) has been shown to be sensitive to changes induced by pathology. This study seeks to determine if quantitative measures of the DMN are sensitive in distinguishing mTBI subjects. Resting state fMRI data were obtained for healthy (N=12) and mTBI subjects (N=15). DMN maps were computed using dual-regression independent component analysis (ICA). A goodness-of-fit index (GOF) was calculated to assess the degree of spatial specificity and sensitivity between healthy controls and mTBI subjects. DMN regions and neuropsychological assessments were examined to identify potential relationships. The resting state DMN maps indicate an increase in spatial co-activity in mTBI subjects within key regions of the DMN. Significant co-activity within the cerebellum and supplementary motor areas of mTBI subjects were also observed. This has not been previously reported in seed-based resting state network analysis. The GOF suggested the presence of high variability within the mTBI subject group, with poor sensitivity and specificity. The neuropsychological data showed correlations between areas of co-activity within the resting state network in the brain with a number of measures of emotion and cognitive functioning. The poor performance of the GOF highlights the key challenge associated with mTBI injury: the high variability in injury mechanisms and subsequent recovery. However, the quantification of the DMN using dual regression ICA has potential to distinguish mTBI from healthy subjects, and provide information on the relationship of aspects of cognitive and emotional functioning with their potential neural correlates.
PMID: 25222050 [PubMed - as supplied by publisher]
Microstructure, length, and connection of limbic tracts in normal human brain development.
Front Aging Neurosci. 2014;6:228
Authors: Yu Q, Peng Y, Mishra V, Ouyang A, Li H, Zhang H, Chen M, Liu S, Huang H
The cingulum and fornix play an important role in memory, attention, spatial orientation, and feeling functions. Both microstructure and length of these limbic tracts can be affected by mental disorders such as Alzheimer's disease, depression, autism, anxiety, and schizophrenia. To date, there has been little systematic characterization of their microstructure, length, and functional connectivity in normally developing brains. In this study, diffusion tensor imaging (DTI) and resting state functional MRI (rs-fMRI) data from 65 normally developing right-handed subjects from birth to young adulthood was acquired. After cingulate gyrus part of the cingulum (cgc), hippocampal part of the cingulum (cgh) and fornix (fx) were traced with DTI tractography, absolute and normalized tract lengths and DTI-derived metrics including fractional anisotropy, mean, axial, and radial diffusivity were measured for traced limbic tracts. Free water elimination (FWE) algorithm was adopted to improve accuracy of the measurements of DTI-derived metrics. The role of these limbic tracts in the functional network at birth and adulthood was explored. We found a logarithmic age-dependent trajectory for FWE-corrected DTI metric changes with fast increase of microstructural integrity from birth to 2 years old followed by a slow increase to 25 years old. Normalized tract length of cgc increases with age, while no significant relationship with age was found for normalized tract lengths of cgh and fx. Stronger microstructural integrity on the left side compared to that of the right side was found. With integrated DTI and rs-fMRI, the key connectional role of cgc and cgh in the default mode network was confirmed as early as birth. Systematic characterization of length and DTI metrics after FWE correction of limbic tracts offers insight into their morphological and microstructural developmental trajectories. These trajectories may serve as a normal reference for pediatric patients with mental disorders.
PMID: 25221509 [PubMed]