3T hippocampal glutamate-glutamine complex reflects verbal memory decline in aging.
Neurobiol Aging. 2017 Mar 18;54:103-111
Authors: Nikolova S, Stark SM, Stark CE
The hippocampus is a critical site for alterations that are responsible for age-related changes in memory. Here, we present a relatively novel approach of examining the relationship between memory performance and glutamate-glutamine levels using short echo time magnetic resonance spectroscopy. Specifically, we investigated the relationship between Glx (a composite of glutamate and glutamine) levels in the hippocampus, performance on a word-recall task, and resting-state functional connectivity. While there was no overall difference in Glx intensity between young and aging adults, we identified a positive correlation between delayed word-list recall and Glx, bilaterally in older adults, but not in young adults. Collapsed across age, we also discovered a negative relationship between Glx intensity and resting-state functional connectivity between the anterior hippocampus and regions in the subcallosal gyrus. These findings demonstrate the possible utility of Glx in identifying age-related changes in the brain and behavior and provide encouragement that magnetic resonance spectroscopy can be useful in predicting age-related decline before any physical abnormalities are present.
PMID: 28363111 [PubMed - as supplied by publisher]
Associations between Daily Affective Instability and Connectomics in Functional Subnetworks in Remitted Patients with Recurrent Major Depressive Disorder.
Neuropsychopharmacology. 2017 Mar 31;:
Authors: Servaas MN, Riese H, Renken RJ, Wichers M, Bastiaansen JA, Figueroa CA, Geugies H, Mocking RJ, Geerligs L, Marsman JB, Aleman A, Schene AH, Schoevers RA, Ruhé HG
Remitted patients with major depressive disorder (rMDD) often report more fluctuations in mood as residual symptomatology. It is unclear how this affective instability is associated with information processing related to the default mode (DMS), salience/reward (SRS) and fronto-parietal (FPS) subnetworks in rMDD patients at high risk of recurrence (rrMDD). Sixty-two unipolar, drug-free rrMDD patients (⩾2 MDD-episodes) and 41 HC (HC) were recruited. We used Experience Sampling Methodology (ESM) to monitor mood/cognitions (10 times a day for 6 days) and calculated affective instability using the mean adjusted absolute successive difference. Subsequently, we collected resting-state functional Magnetic Resonance Imaging data and performed graph theory to obtain network metrics of integration within (local efficiency) the DMS, SRS and FPS, and between (participation coefficient) these subnetworks and others. In rrMDD patients compared to HC, we found that affective instability was increased in most negative mood/cognition variables and that the DMS had less connections with other subnetworks. Furthermore, we found that rrMDD patients, who showed more instability in feeling down and irritated, had less connections between the SRS and other subnetworks and higher local efficiency coefficients in the FPS, respectively. In conclusion, rrMDD patients, compared to HC, are less stable in their negative mood and these dynamics are related to differences in information processing within and between specific functional subnetworks. These results are a first step to gain a better understanding of how mood fluctuations in real-life are represented in the brain and provide insights in the vulnerability profile of MDD.Neuropsychopharmacology accepted article preview online, 31 March 2017. doi:10.1038/npp.2017.65.
PMID: 28361870 [PubMed - as supplied by publisher]
Memory performance-related dynamic brain connectivity indicates pathological burden and genetic risk for Alzheimer's disease.
Alzheimers Res Ther. 2017 Mar 31;9(1):24
Authors: Quevenco FC, Preti MG, van Bergen JM, Hua J, Wyss M, Li X, Schreiner SJ, Steininger SC, Meyer R, Meier IB, Brickman AM, Leh SE, Gietl AF, Buck A, Nitsch RM, Pruessmann KP, van Zijl PC, Hock C, Van De Ville D, Unschuld PG
BACKGROUND: The incidence of Alzheimer's disease (AD) strongly relates to advanced age and progressive deposition of cerebral amyloid-beta (Aβ), hyperphosphorylated tau, and iron. The purpose of this study was to investigate the relationship between cerebral dynamic functional connectivity and variability of long-term cognitive performance in healthy, elderly subjects, allowing for local pathology and genetic risk.
METHODS: Thirty seven participants (mean (SD) age 74 (6.0) years, Mini-Mental State Examination 29.0 (1.2)) were dichotomized based on repeated neuropsychological test performance within 2 years. Cerebral Aβ was measured by (11)C Pittsburgh Compound-B positron emission tomography, and iron by quantitative susceptibility mapping magnetic resonance imaging (MRI) at an ultra-high field strength of 7 Tesla (7T). Dynamic functional connectivity patterns were investigated by resting-state functional MRI at 7T and tested for interactive effects with genetic AD risk (apolipoprotein E (ApoE)-ε4 carrier status).
RESULTS: A relationship between low episodic memory and a lower expression of anterior-posterior connectivity was seen (F(9,27) = 3.23, p < 0.008), moderated by ApoE-ε4 (F(9,27) = 2.22, p < 0.005). Inherent node-strength was related to local iron (F(5,30) = 13.2; p < 0.022).
CONCLUSION: Our data indicate that altered dynamic anterior-posterior brain connectivity is a characteristic of low memory performance in the subclinical range and genetic risk for AD in the elderly. As the observed altered brain network properties are associated with increased local iron, our findings may reflect secondary neuronal changes due to pathologic processes including oxidative stress.
PMID: 28359293 [PubMed - in process]
Predictors and brain connectivity changes associated with arm motor function improvement from intensive robotic practice in chronic stroke.
Authors: Wittenberg GF, Richards LG, Jones-Lush LM, Roys SR, Gullapalli RP, Yang S, Guarino PD, Lo AC
Background and Purpose: The brain changes that underlie therapy-induced improvement in motor function after stroke remain obscure. This study sought to demonstrate the feasibility and utility of measuring motor system physiology in a clinical trial of intensive upper extremity rehabilitation in chronic stroke-related hemiparesis. Methods: This was a substudy of two multi-center clinical trials of intensive robotic arm therapy in chronic, significantly hemiparetic, stroke patients. Transcranial magnetic stimulation was used to measure motor cortical output to the biceps and extensor digitorum communus muscles. Magnetic resonance imaging (MRI) was used to determine the cortical anatomy, as well as to measure fractional anisotropy, and blood oxygenation (BOLD) during an eyes-closed rest state. Region-of-interest time-series correlation analysis was performed on the BOLD signal to determine interregional connectivity. Functional status was measured with the upper extremity Fugl-Meyer and Wolf Motor Function Test. Results: Motor evoked potential (MEP) presence was associated with better functional outcomes, but the effect was not significant when considering baseline impairment. Affected side internal capsule fractional anisotropy was associated with better function at baseline. Affected side primary motor cortex (M1) activity became more correlated with other frontal motor regions after treatment. Resting state connectivity between affected hemisphere M1 and dorsal premotor area (PMAd) predicted recovery. Conclusions: Presence of motor evoked potentials in the affected motor cortex and its functional connectivity with PMAd may be useful in predicting recovery. Functional connectivity in the motor network shows a trends towards increasing after intensive robotic or non-robotic arm therapy. Clinical Trial Registration URL: http://www.clinicaltrials.gov. Unique identifiers: CT00372411 & NCT00333983.
PMID: 28357039 [PubMed - in process]
J Geriatr Psychiatry Neurol. 2017 Jan 01;:891988717700509
Authors: Cieri F, Esposito R, Cera N, Pieramico V, Tartaro A, di Giannantonio M
Late-life depression (LLD) is a common emotional and mental disability in the elderly population characterized by the presence of depressed mood, the loss of interest or pleasure in daily activities, and other depression symptoms. It has a serious effect on the quality of life of elderly individuals and increases their risk of developing physical and mental diseases. It is an important area of research, given the growing elderly population. Brain functional connectivity modifications represent one of the neurobiological biomarker for LLD even if to date remains poorly understood. In our study, we enrolled 10 elderly patients with depressive symptoms compared to 11 age-matched healthy controls. All participants were evaluated by means of neuropsychological tests and underwent the same functional magnetic resonance imaging (fMRI) protocol to evaluate modifications of brain resting state functional connectivity. Between-group differences were observed for the Geriatric Depression Scale and Hamilton Depression Rating Scale, with higher scores for patients with LLD. Voxel-wise, 1-way analysis of variance revealed between-group differences in left frontoparietal network (lFPN) and sensory motor network (SMN): Increased intrinsic connectivity in the LLD group was observed in the left dorsolateral prefrontal cortex and in the left superior parietal lobule of the lFPN and increased intrinsic connectivity in the LLD group was observed in the bilateral primary somatosensory cortex of the SMN. Our findings support the use of resting state fMRI as a potential biomarker for LLD; even if to confirm the relationship between brain changes and the pathophysiology of LLD, longitudinal neuroimaging studies are required.
PMID: 28355945 [PubMed - as supplied by publisher]
Hyperactivity of the default-mode network in first-episode, drug-naive schizophrenia at rest revealed by family-based case-control and traditional case-control designs.
Medicine (Baltimore). 2017 Mar;96(13):e6223
Authors: Guo W, Liu F, Chen J, Wu R, Li L, Zhang Z, Chen H, Zhao J
Abnormal regional activity and functional connectivity of the default-mode network (DMN) have been reported in schizophrenia. However, previous studies may have been biased by unmatched case-control design. To limit such bias, the present study used both the family-based case-control design and the traditional case-control design to investigate abnormal regional activity of the DMN in patients with schizophrenia at rest.Twenty-eight first-episode, drug-naive patients with schizophrenia, 28 age-, sex-matched unaffected siblings of the patients (family-based controls, FBC), and 40 healthy controls (HC) underwent resting-state functional magnetic resonance imaging (fMRI) scans. The group-independent component analysis and fractional amplitude of low-frequency fluctuation (fALFF) methods were used to analyze the data.Patients with schizophrenia show increased fALFF in an overlapped region of the right superior medial prefrontal cortex (MPFC) relative to the FBC and the HC. Compared with the HC, the patients and the FBC exhibit increased fALFF in an overlapped region of the left posterior cingulate cortex/precuneus (PCC/PCu). Furthermore, the z values of the 2 overlapped regions can separate the patients from the FBC/HC, and separate the patients/FBC from the HC with relatively high sensitivity and specificity.Both the family-based case-control and traditional case-control designs reveal hyperactivity of the DMN in first-episode, drug-naive patients with paranoid schizophrenia, which highlights the importance of the DMN in the neurobiology of schizophrenia. Family-based case-control design can limit the confounding effects of environmental factors in schizophrenia. Combination of the family-based case-control and traditional case-control designs may be a viable option for the neuroimaging studies.
PMID: 28353559 [PubMed - in process]
Resting state fMRI: A review on methods in resting state connectivity analysis and resting state networks.
Neuroradiol J. 2017 Jan 01;:1971400917697342
Authors: Smitha KA, Akhil Raja K, Arun KM, Rajesh PG, Thomas B, Kapilamoorthy TR, Kesavadas C
The inquisitiveness about what happens in the brain has been there since the beginning of humankind. Functional magnetic resonance imaging is a prominent tool which helps in the non-invasive examination, localisation as well as lateralisation of brain functions such as language, memory, etc. In recent years, there is an apparent shift in the focus of neuroscience research to studies dealing with a brain at 'resting state'. Here the spotlight is on the intrinsic activity within the brain, in the absence of any sensory or cognitive stimulus. The analyses of functional brain connectivity in the state of rest have revealed different resting state networks, which depict specific functions and varied spatial topology. However, different statistical methods have been introduced to study resting state functional magnetic resonance imaging connectivity, yet producing consistent results. In this article, we introduce the concept of resting state functional magnetic resonance imaging in detail, then discuss three most widely used methods for analysis, describe a few of the resting state networks featuring the brain regions, associated cognitive functions and clinical applications of resting state functional magnetic resonance imaging. This review aims to highlight the utility and importance of studying resting state functional magnetic resonance imaging connectivity, underlining its complementary nature to the task-based functional magnetic resonance imaging.
PMID: 28353416 [PubMed - as supplied by publisher]
Negative functional brain networks.
Brain Imaging Behav. 2017 Mar 29;:
Authors: Parente F, Frascarelli M, Mirigliani A, Di Fabio F, Biondi M, Colosimo A
The anticorrelations in fMRI measurements are still not well characterized, but some new evidences point to a possible physiological role. We explored the topology of functional brain networks characterized by negative edgess and their possible alterations in schizophrenia, using functional images of 8 healthy subjects and 8 schizophrenic patients in a resting state condition. In order to minimize the insertion of artifactual negative correlations, the preprocessing of images was carried out by the CompCorr procedure, and the results compared with the Global Signal Regression (GSR) procedure. The degree distribution, the centrality, the efficiency and the rich-club behavior were used to characterize the functional brain network with negative links of healthy controls in comparison with schizophrenic patients. The results show that functional brain networks with both positive and negative values have a truncated power-law degree distribution. Moreover, although functional brain networks characterized by negative values have not small-world topology, they show a specific disassortative configuration: the more connected nodes tend to have fewer connections between them. This feature is lost using the GSR procedure. Finally, the comparison with schizophrenic patients showed a decreased (local and global) efficiency associated to a decreased connectivity among central nodes. As a conclusion, functional brain networks characterized by negative values, despite lacking a well defined topology, show specific features, different from random, and indicate an implication in the alterations associated to schizophrenia.
PMID: 28353136 [PubMed - as supplied by publisher]
Functional insights into aberrant brain responses and integration in patients with lifelong premature ejaculation.
Sci Rep. 2017 Mar 28;7(1):460
Authors: Zhang B, Lu J, Xia J, Wang F, Li W, Chen F, Han Y, Chen Y, Zhu B, Qing Z, Zhang X, Dai Y
Even though lifelong premature ejaculation (PE) is highly prevalent, few studies have investigated the neural mechanisms underlying PE. The extent and pattern of brain activation can be determined through a version of functional magnetic resonance imaging (fMRI) with erotic picture stimuli (task fMRI) and a resting-state fMRI (rs fMRI). We showed that the brain activity in the left inferior frontal gyrus and left insula was decreased both during the task and in the resting state, while there was higher activation in the right middle temporal gyrus during the task. Higher functional connectivity was found in PE between those three brain areas and the bilateral middle cingulate cortex, right middle frontal gyrus and supplementary motor area. Moreover, the brain activity had positive correlation with clinical rating scales, such as intravaginal ejaculatory latency time (IELT) and the Chinese Index of Premature Ejaculation (CIPE). These findings revealed that brain responses and functional integration in certain brain areas are impaired in cases of PE, which was consistently supported by multiple measurements obtained using a task and rs fMRI approach.
PMID: 28352072 [PubMed - in process]
Resting-State Functional Connectivity Changes Associated with Visuospatial Cognitive Deficits in Patients with Mild Alzheimer Disease.
Dement Geriatr Cogn Disord. 2017 Mar 29;43(5-6):229-236
Authors: Balachandar R, Bharath S, John JP, Joshi H, Sadanand S, Saini J, Kumar KJ, Varghese M
BACKGROUND/AIMS: Alzheimer disease (AD) is a neurodegenerative disorder characterized by progressive disconnection of various brain networks leading to neuropsychological impairment. Pathology in the visual association areas has been documented in presymptomatic AD and therefore we aimed at examining the relationship between brain connectivity and visuospatial (VS) cognitive deficits in early AD.
METHODS: Tests for VS working memory, episodic memory and construction were used to classify patients with AD (n = 48) as having severe VS deficits (n = 12, female = 4) or mild deficits (n = 11, female = 4). Resting-state functional magnetic resonance imaging and structural images were acquired as per the standard protocols. Between-group differences in resting-state functional connectivity (rsFC) were examined by dual regression analysis correcting for age, gender, and total brain volume.
RESULTS: Patients with AD having severe VS deficits exhibited significantly reduced rsFC in bilateral lingual gyri of the visual network compared to patients with mild VS deficits.
CONCLUSION: Reduced rsFC in the visual network in patients with more severe VS deficits may be a functional neuroimaging biomarker reflecting hypoconnectivity of the brain with progressive VS deficits during early AD.
PMID: 28351035 [PubMed - as supplied by publisher]
Discriminating cognitive status in Parkinson's disease through functional connectomics and machine learning.
Sci Rep. 2017 Mar 28;7:45347
Authors: Abós A, Baggio HC, Segura B, García-Díaz AI, Compta Y, Martí MJ, Valldeoriola F, Junqué C
There is growing interest in the potential of neuroimaging to help develop non-invasive biomarkers in neurodegenerative diseases. In this study, connection-wise patterns of functional connectivity were used to distinguish Parkinson's disease patients according to cognitive status using machine learning. Two independent subject samples were assessed with resting-state fMRI. The first (training) sample comprised 38 healthy controls and 70 Parkinson's disease patients (27 with mild cognitive impairment). The second (validation) sample included 25 patients (8 with mild cognitive impairment). The Brainnetome atlas was used to reconstruct the functional connectomes. Using a support vector machine trained on features selected through randomized logistic regression with leave-one-out cross-validation, a mean accuracy of 82.6% (p < 0.002) was achieved in separating patients with mild cognitive impairment from those without it in the training sample. The model trained on the whole training sample achieved an accuracy of 80.0% when used to classify the validation sample (p = 0.006). Correlation analyses showed that the connectivity level in the edges most consistently selected as features was associated with memory and executive function performance in the patient group. Our results demonstrate that connection-wise patterns of functional connectivity may be useful for discriminating Parkinson's disease patients according to the presence of cognitive deficits.
PMID: 28349948 [PubMed - in process]
Connectivity patterns during music listening: Evidence for action-based processing in musicians.
Hum Brain Mapp. 2017 Mar 28;:
Authors: Alluri V, Toiviainen P, Burunat I, Kliuchko M, Vuust P, Brattico E
Musical expertise is visible both in the morphology and functionality of the brain. Recent research indicates that functional integration between multi-sensory, somato-motor, default-mode (DMN), and salience (SN) networks of the brain differentiates musicians from non-musicians during resting state. Here, we aimed at determining whether brain networks differentially exchange information in musicians as opposed to non-musicians during naturalistic music listening. Whole-brain graph-theory analyses were performed on participants' fMRI responses. Group-level differences revealed that musicians' primary hubs comprised cerebral and cerebellar sensorimotor regions whereas non-musicians' dominant hubs encompassed DMN-related regions. Community structure analyses of the key hubs revealed greater integration of motor and somatosensory homunculi representing the upper limbs and torso in musicians. Furthermore, musicians who started training at an earlier age exhibited greater centrality in the auditory cortex, and areas related to top-down processes, attention, emotion, somatosensory processing, and non-verbal processing of speech. We here reveal how brain networks organize themselves in a naturalistic music listening situation wherein musicians automatically engage neural networks that are action-based while non-musicians use those that are perception-based to process an incoming auditory stream. Hum Brain Mapp, 2017. © 2017 Wiley Periodicals, Inc.
PMID: 28349620 [PubMed - as supplied by publisher]
Intrinsic Brain Activity Responsible for Sex Differences in Shyness and Social Anxiety.
Front Behav Neurosci. 2017;11:43
Authors: Yang X, Zhou M, Lama S, Chen L, Hu X, Wang S, Chen T, Shi Y, Huang X, Gong Q
Male and female show significant differences in important behavioral features such as shyness, yet the neural substrates of these differences remain poorly understood. Previous neuroimaging studies have demonstrated that both shyness and social anxiety in healthy subjects are associated with increased activation in the fronto-limbic and cognitive control areas. However, it remains unknown whether these brain abnormalities would be shared by different genders. Therefore, in the current study, we used resting-state fMRI (r-fMRI) to investigate sex differences in intrinsic cerebral activity that may contribute to shyness and social anxiety. Sixty subjects (28 males, 32 females) participated in r-fMRI scans, and the amplitude of low-frequency fluctuations (ALFF) and fractional ALFF (fALFF) were used to measure the spontaneous regional cerebral activity in all subjects. We first compared the differences between male and female both in the ALFF and fALFF and then we also examined the whole brain correlation between the ALFF/fALFF and the severity of shyness as well as social anxiety by genders. Referring to shyness measure, we found a significant positive correlation between shyness scores (CBSS) and ALFF/fALFF value in the frontoparietal control network and a negative correlation in the cingulo-insular network in female; while in male, there is no such correlation. For the social anxiety level, we found positive correlations between Leibowitz Social Anxiety Scale (LSAS) scores and spontaneous activity in the frontal-limbic network in male and negative correlation between the frontal-parietal network; however, such correlation was not prominent in female. This pattern suggests that shy female individuals engaged a proactive control process, driven by a positive association with activity in frontoparietal network and negative association in cingulo-insular network, whereas social anxiety males relied more on a reactive control process, driven by a positive correlation of frontal-limbic network and negative correlation of frontoparietal network. Our results reveal that shyness or social anxiety is associated with disrupted spontaneous brain activity patterns and that these patterns are influenced by sex.
PMID: 28348521 [PubMed - in process]
Commentary: Microstructure, length, and connection of limbic tracts in normal human brain development.
Front Neurosci. 2017;11:117
Authors: Oishi K
PMID: 28348513 [PubMed - in process]
Using Dual Regression to Investigate Network Shape and Amplitude in Functional Connectivity Analyses.
Front Neurosci. 2017;11:115
Authors: Nickerson LD, Smith SM, Öngür D, Beckmann CF
Independent Component Analysis (ICA) is one of the most popular techniques for the analysis of resting state FMRI data because it has several advantageous properties when compared with other techniques. Most notably, in contrast to a conventional seed-based correlation analysis, it is model-free and multivariate, thus switching the focus from evaluating the functional connectivity of single brain regions identified a priori to evaluating brain connectivity in terms of all brain resting state networks (RSNs) that simultaneously engage in oscillatory activity. Furthermore, typical seed-based analysis characterizes RSNs in terms of spatially distributed patterns of correlation (typically by means of simple Pearson's coefficients) and thereby confounds together amplitude information of oscillatory activity and noise. ICA and other regression techniques, on the other hand, retain magnitude information and therefore can be sensitive to both changes in the spatially distributed nature of correlations (differences in the spatial pattern or "shape") as well as the amplitude of the network activity. Furthermore, motion can mimic amplitude effects so it is crucial to use a technique that retains such information to ensure that connectivity differences are accurately localized. In this work, we investigate the dual regression approach that is frequently applied with group ICA to assess group differences in resting state functional connectivity of brain networks. We show how ignoring amplitude effects and how excessive motion corrupts connectivity maps and results in spurious connectivity differences. We also show how to implement the dual regression to retain amplitude information and how to use dual regression outputs to identify potential motion effects. Two key findings are that using a technique that retains magnitude information, e.g., dual regression, and using strict motion criteria are crucial for controlling both network amplitude and motion-related amplitude effects, respectively, in resting state connectivity analyses. We illustrate these concepts using realistic simulated resting state FMRI data and in vivo data acquired in healthy subjects and patients with bipolar disorder and schizophrenia.
PMID: 28348512 [PubMed - in process]
Driving human motor cortical oscillations leads to behaviourally relevant changes in local GABAA inhibition: a tACS-TMS study.
J Neurosci. 2017 Mar 27;:
Authors: Nowak M, Hinson E, van Ede F, Pogosyan A, Guerra A, Quinn A, Brown P, Stagg CJ
Beta and gamma oscillations are the dominant oscillatory activity in the human motor cortex (M1). However, their physiological basis and precise functional significance remain poorly understood. Here, we employed Transcranial Magnetic Stimulation (TMS) to examine the physiological basis and behavioural relevance of driving beta and gamma oscillatory activity in the human M1 using transcranial alternating current stimulation (tACS). tACS was applied using a sham-controlled cross-over design at individualised intensity for 20 min, and TMS was performed at rest (before, during and after tACS) and during movement preparation (before and after tACS). We demonstrated that driving gamma frequency oscillations using tACS led to a significant, duration-dependent decrease in local resting-state GABAA inhibition, as quantified by short interval intracortical inhibition (SICI). The magnitude of this effect was positively correlated with the magnitude of GABAA decrease during movement preparation, when gamma activity in motor circuitry is known to increase. In addition, gamma tACS-induced change in GABAA inhibition was closely related to performance in a motor learning task, such that subjects who demonstrated a greater increase in GABAA inhibition also showed faster short-term learning. The findings presented here contribute to our understanding of the neurophysiological basis of motor rhythms, and suggest that tACS may have similar physiological effects to endogenously driven local oscillatory activity. Moreover, the ability to modulate local interneuronal circuits by tACS in a behaviourally relevant manner provides a basis for tACS as a putative therapeutic intervention.SIGNIFICANCE STATEMENTGamma oscillations have a vital role in motor control. Using a combined tACS-TMS approach, we demonstrate that driving gamma-frequency oscillations modulates GABAA inhibition in the human motor cortex. Moreover, there is a clear relationship between the change in magnitude of GABAA inhibition induced by tACS and the magnitude of GABAA inhibition observed during task-related synchronisation of oscillations in inhibitory interneuronal circuits, supporting the hypothesis that tACS engages endogenous oscillatory circuits. We also show that an individual's physiological response to tACS is closely related to their ability to learn a motor task. These findings contribute to our understanding of the neurophysiological basis of motor rhythms and their behavioural relevance, and offer the possibility of developing tACS as a potential therapeutic tool.
PMID: 28348136 [PubMed - as supplied by publisher]
Higher interference susceptibility in reaction time task is accompanied by weakened functional dissociation between salience and default mode network.
Neurosci Lett. 2017 Mar 24;:
Authors: Götting FN, Borchardt V, Demenescu LR, Teckentrup V, Dinica K, Lord AR, Rohe T, Hausdörfer DI, Li M, Metzger CD, Walter M
BACKGROUND: The relationship between task-positive and task-negative components of brain networks has repeatedly been shown to be characterized by dissociated fluctuations of spontaneous brain activity. We tested whether the interaction between task-positive and task-negative brain areas during resting-state predicts higher interference susceptibility, i.e. increased reaction times (RTs), during an Attention Modulation by Salience Task (AMST).
METHODS: 29 males underwent 3 Tesla resting-state Magnetic Resonance Imaging scanning. Subsequently, they performed the AMST, which measures RTs to early- and late-onset auditory stimuli while perceiving high- or low-salient visual distractors. We conducted seed-based resting-state functional connectivity (rsFC) analyses using global signal correction. We assessed general responsiveness and salience related interference in the AMST and set this into context of the resting-state functional connectivity (rsFC) between a key salience network region (dACC; task-positive region) and a key default mode network region (precuneus; task-negative region).
RESULTS: With increasing RTs to high- but not low-salient pictures dACC shows significantly weakened functional dissociation to a cluster in precuneus. This cluster overlaps with a cluster that correlates in its dACC rsFC with subjects' interference, as measured of high-salient RTs relative to low-salient RTs.
CONCLUSION: Our findings suggest that the interaction between salience network (SN) and default mode network (DMN) at rest predicts susceptibility to distraction. Subjects, that are more susceptible to high-salient stimuli - task-irrelevant external information - showed increased dACC rsFC towards precuneus. This is consistent with prior work in individuals with impaired attentional focus. Future studies might help to conclude whether an increased rsFC between a SN region and DMN region may serve as a predictor for clinical syndromes characterized by attentional impairments, e.g. ADHD. This could lead to an alternative, objective diagnosis and treatment of such disorders by decreasing the rsFC of these regions.
PMID: 28347858 [PubMed - as supplied by publisher]
Attenuated intrinsic connectivity within cognitive control network among individuals with remitted depression: Temporal stability and association with negative cognitive styles.
Hum Brain Mapp. 2017 Mar 27;:
Authors: Stange JP, Bessette KL, Jenkins LM, Peters AT, Feldhaus C, Crane NA, Ajilore O, Jacobs RH, Watkins ER, Langenecker SA
Many individuals with major depressive disorder (MDD) experience cognitive dysfunction including impaired cognitive control and negative cognitive styles. Functional connectivity magnetic resonance imaging studies of individuals with current MDD have documented altered resting-state connectivity within the default-mode network and across networks. However, no studies to date have evaluated the extent to which impaired connectivity within the cognitive control network (CCN) may be present in remitted MDD (rMDD), nor have studies examined the temporal stability of such attenuation over time. This represents a major gap in understanding stable, trait-like depression risk phenotypes. In this study, resting-state functional connectivity data were collected from 52 unmedicated young adults with rMDD and 47 demographically matched healthy controls, using three bilateral seeds in the CCN (dorsolateral prefrontal cortex, inferior parietal lobule, and dorsal anterior cingulate cortex). Mean connectivity within the entire CCN was attenuated among individuals with rMDD, was stable and reliable over time, and was most pronounced with the right dorsolateral prefrontal cortex and right inferior parietal lobule, results that were corroborated by supplemental independent component analysis. Attenuated connectivity in rMDD appeared to be specific to the CCN as opposed to representing attenuated within-network coherence in other networks (e.g., default-mode, salience). In addition, attenuated connectivity within the CCN mediated relationships between rMDD status and cognitive risk factors for depression, including ruminative brooding, pessimistic attributional style, and negative automatic thoughts. Given that these cognitive markers are known predictors of relapse, these results suggest that attenuated connectivity within the CCN could represent a biomarker for trait phenotypes of depression risk. Hum Brain Mapp, 2017. © 2017 Wiley Periodicals, Inc.
PMID: 28345197 [PubMed - as supplied by publisher]
Trait-based food-cravings are encoded by regional homogeneity in the parahippocampal gyrus.
Appetite. 2017 Mar 23;:
Authors: Chen S, Dong D, Jackson T, Zhuang Q, Chen H
Food cravings can reflect an intense trait-like emotional-motivational desire to eat palatable food, often resulting in the failure of weight loss efforts. Studies have linked trait-based food-cravings to increased risk of overeating. However, little is known about resting-state neural mechanisms that underlie food cravings. We investigated this issue using resting-state functional magnetic resonance imaging (fMRI) to test the extent to which spontaneous neural activity occurs in regions implicated in emotional memory and reward motivation associated with food cravings. Spontaneous regional activity patterns correlating to food cravings were assessed among 65 young healthy women using regional homogeneity analysis to assess temporal synchronization of spontaneous activity. Analyses indicated that women with higher scores on the Food Cravings Questionnaire displayed increased local functional homogeneity in brain regions involved in emotional memory and visual attention processing (i.e., parahippocampal gyrus and fusiform gyrus) but not reward. In view of parahippocampal gyrus involvement in hedonic learning and incentive memory encoding, this study suggests that trait-based food cravings are encoded by emotional memory circuits.
PMID: 28344152 [PubMed - as supplied by publisher]
Functional Reorganization in Obstructive Sleep Apnoea and Insomnia: A Systematic Review of the Resting-State fMRI.
Neurosci Biobehav Rev. 2017 Mar 23;:
Authors: Khazaie H, Veronese M, Noori K, Emamian F, Zarei M, Ashkan K, Leschziner GD, Eickhoff CR, Eickhoff SB, Morrell MJ, Osorio RS, Spiegelhalder K, Tahmasian M, Rosenzweig I
Functional neuroimaging techniques have accelerated progress in the study of sleep disorders. Considering the striking prevalence of these disorders in the general population, however, as well as their strong bidirectional relationship with major neuropsychiatric disorders, including major depressive disorder, their numbers are still surprisingly low. This review examines the contribution of resting state functional MRI to current understanding of two major sleep disorders, insomnia disorder and obstructive sleep apnoea. An attempt is made to learn from parallels of previous resting state functional neuroimaging findings in major depressive disorder. Moreover, shared connectivity biomarkers are suggested for each of the sleep disorders. Taken together, despite some inconsistencies, the synthesis of findings to date highlights the importance of the salience network in hyperarousal and affective symptoms in insomnia. Conversely, dysfunctional connectivity of the posterior default mode network appears to underlie cognitive and depressive symptoms of obstructive sleep apnoea.
PMID: 28344075 [PubMed - as supplied by publisher]