Ventral tegmental area integrity measured with high-resolution 7-Tesla MRI relates to motivation across depression and anxiety diagnoses.

The ventral tegmental area (VTA) is one of the major sources of dopamine in the brain and has been associated with reward prediction, error-based reward learning, volitional drive and anhedonia. However, precise anatomical investigations of the VTA have been prevented by the use of standard-resolution MRI, reliance on subjective manual tracings, and lack of quantitative measures of dopamine-related signal. Here, we combine ultra-high field 400 µm3 quantitative MRI with dopamine-related signal mapping, and a mixture of machine learning and supervised computational techniques to delineate the VTA in a transdiagnostic sample of subjects with and without depression and anxiety disorders. Subjects also underwent cognitive testing to measure intrinsic and extrinsic motivational tone. Fifty-one subjects were scanned in total, including healthy control (HC) and mood/anxiety (MA) disorder subjects. MA subjects had significantly larger VTA volumes compared to HC but significantly lower signal intensity within VTA compared to HC, indicating reduced structural integrity of the dopaminergic VTA. Interestingly, while VTA integrity did not significantly correlate with self-reported depression or anxiety symptoms, it was correlated with an objective cognitive measure of extrinsic motivation, whereby lower VTA integrity was associated with lower motivation. This is the first study to demonstrate a computational pipeline for detecting and delineating the VTA in human subjects with 400 µm3 resolution. We highlight the use of objective transdiagnostic measures of cognitive function that link neural integrity to behavior across clinical and non-clinical groups.

Lateralisation of subcortical functional connectivity during and after general anaesthesia.

BACKGROUND: Arousal and awareness are two important components of consciousness states. Functional neuroimaging has furthered our understanding of cortical and thalamocortical mechanisms of awareness. Investigating the relationship between subcortical functional connectivity and arousal has been challenging owing to the relatively small size of brainstem structures and thalamic nuclei, and their depth in the brain. METHODS: Resting state functional MRI scans of 72 healthy volunteers were acquired before, during, 1 h after, and 1 day after sevoflurane general anaesthesia. Functional connectivity of subcortical regions of interest vs whole brain and homotopic functional connectivity for assessment of left-right symmetry analyses of both cortical and subcortical regions of interest were performed. Both analyses used high resolution atlases generated from deep brain stimulation applications. RESULTS: Functional connectivity in subcortical loci within the thalamus and of the ascending reticular activating system was sharply restricted under anaesthesia, featuring a general lateralisation of connectivity. Similarly, left-right homology was sharply reduced under anaesthesia. Subcortical bilateral functional connectivity was not fully restored after emergence from anaesthesia, although greater restoration was seen between ascending reticular activating system loci and specific thalamic nuclei thought to be involved in promoting and maintaining arousal. Functional connectivity was fully restored to baseline by the following day. CONCLUSIONS: Functional connectivity in the subcortex is sharply restricted and lateralised under general anaesthesia. This restriction may play a part in loss and return of consciousness. CLINICAL TRIAL REGISTRATION: NCT02275026.

Leveraging high-resolution 7-tesla MRI to derive quantitative metrics for the trigeminal nerve and subnuclei of limbic structures in trigeminal neuralgia.

BACKGROUND: Trigeminal Neuralgia (TN) is a chronic neurological disease that is strongly associated with neurovascular compression (NVC) of the trigeminal nerve near its root entry zone. The trigeminal nerve at the site of NVC has been extensively studied but limbic structures that are potentially involved in TN have not been adequately characterized. Specifically, the hippocampus is a stress-sensitive region which may be structurally impacted by chronic TN pain. As the center of the emotion-related network, the amygdala is closely related to stress regulation and may be associated with TN pain as well. The thalamus, which is involved in the trigeminal sensory pathway and nociception, may play a role in pain processing of TN. The objective of this study was to assess structural alterations in the trigeminal nerve and subregions of the hippocampus, amygdala, and thalamus in TN patients using ultra-high field MRI and examine quantitative differences in these structures compared with healthy controls. METHODS: Thirteen TN patients and 13 matched controls were scanned at 7-Tesla MRI with high resolution, T1-weighted imaging. Nerve cross sectional area (CSA) was measured and an automated algorithm was used to segment hippocampal, amygdaloid, and thalamic subregions. Nerve CSA and limbic structure subnuclei volumes were compared between TN patients and controls. RESULTS: CSA of the posterior cisternal nerve on the symptomatic side was smaller in patients (3.75 mm2) compared with side-matched controls (5.77 mm2, p = 0.006). In TN patients, basal subnucleus amygdala volume (0.347 mm3) was reduced on the symptomatic side compared with controls (0.401 mm3, p = 0.025) and the paralaminar subnucleus volume (0.04 mm3) was also reduced on the symptomatic side compared with controls (0.05 mm3, p = 0.009). The central lateral thalamic subnucleus was larger in TN patients on both the symptomatic side (0.033 mm3) and asymptomatic side (0.035 mm3), compared with the corresponding sides in controls (0.025 mm3 on both sides, p = 0.048 and p = 0.003 respectively). The inferior and lateral pulvinar thalamic subnuclei were both reduced in TN patients on the symptomatic side (0.2 mm3 and 0.17 mm3 respectively) compared to controls (0.23 mm3, p = 0.04 and 0.18 mm3, p = 0.04 respectively). No significant findings were found in the hippocampal subfields analyzed. CONCLUSIONS: These findings, generated through a highly sensitive 7 T MRI protocol, provide compelling support for the theory that TN neurobiology is a complex amalgamation of local structural changes within the trigeminal nerve and structural alterations in subnuclei of limbic structures directly and indirectly involved in nociception and pain processing.

Resting-state functional connectivity in early postanaesthesia recovery is characterised by globally reduced anticorrelations.

BACKGROUND: A growing body of literature addresses the possible long-term cognitive effects of anaesthetics, but no study has delineated the normal trajectory of neural recovery attributable to anaesthesia alone in adults. We obtained resting-state functional MRI scans on 72 healthy human volunteers between ages 40 and 80 (median: 59) yr before, during, and after general anaesthesia with sevoflurane, in the absence of surgery, as part of a larger study on cognitive function postanaesthesia. METHODS: Region-of-interest analysis, independent component analysis, and seed-to-voxel analysis were used to characterise resting-state functional connectivity and to differentiate between correlated and anticorrelated connectivity before, during, and after general anaesthesia. RESULTS: Whilst positively correlated functional connectivity remained essentially unchanged across these perianaesthetic states, anticorrelated functional connectivity decreased globally by 35% 1 h after emergence from general anaesthesia compared with baseline, as seen by the region-of-interest analysis. This decrease corresponded to a consistent reduction in expression of canonical resting-state networks, as seen by independent component analysis. All measures returned to baseline 1 day later. CONCLUSIONS: The normal perianaesthesia trajectory of resting-state connectivity in healthy adults is characterised by a transient global reduction in anticorrelated activity shortly after emergence from anaesthesia that returns to baseline by the following day. CLINICAL TRIAL REGISTRATION: NCT02275026.

Network abnormalities among non-manifesting Parkinson disease related LRRK2 mutation carriers.

Non-manifesting carriers (NMC) of the G2019S mutation in the LRRK2 gene represent an "at risk" group for future development of Parkinson's disease (PD) and have demonstrated task related fMRI changes. However, resting-state networks have received less research focus, thus this study aimed to assess the integrity of the motor, default mode (DMN), salience (SAL), and dorsal attention (DAN) networks among this unique population by using two different connectivity measures: interregional functional connectivity analysis and Dependency network analysis (DEP NA). Machine learning classification methods were used to distinguish connectivity between the two groups of participants. Forty-four NMC and 41 non-manifesting non-carriers (NMNC) participated in this study; while no behavioral differences on standard questionnaires could be detected, NMC demonstrated lower connectivity measures in the DMN, SAL, and DAN compared to NMNC but not in the motor network. Significant correlations between NMC connectivity measures in the SAL and attention were identified. Machine learning classification separated NMC from NMNC with an accuracy rate above 0.8. Reduced integrity of non-motor networks was detected among NMC of the G2019S mutation in the LRRK2 gene prior to identifiable changes in connectivity of the motor network, indicating significant non-motor cerebral changes among populations "at risk" for future development of PD.

Psychophysiological whole-brain network clustering based on connectivity dynamics analysis in naturalistic conditions.

We introduce a novel method for delineating context-dependent functional brain networks whose connectivity dynamics are synchronized with the occurrence of a specific psychophysiological process of interest. In this method of context-related network dynamics analysis (CRNDA), a continuous psychophysiological index serves as a reference for clustering the whole-brain into functional networks. We applied CRNDA to fMRI data recorded during the viewing of a sadness-inducing film clip. The method reliably demarcated networks in which temporal patterns of connectivity related to the time series of reported emotional intensity. Our work successfully replicated the link between network connectivity and emotion rating in an independent sample group for seven of the networks. The demarcated networks have clear common functional denominators. Three of these networks overlap with distinct empathy-related networks, previously identified in distinct sets of studies. The other networks are related to sensorimotor processing, language, attention, and working memory. The results indicate that CRNDA, a data-driven method for network clustering that is sensitive to transient connectivity patterns, can productively and reliably demarcate networks that follow psychologically meaningful processes. Hum Brain Mapp 37:4654-4672, 2016. © 2016 Wiley Periodicals, Inc.

Functional connectivity dynamics during film viewing reveal common networks for different emotional experiences.

Recent theoretical and empirical work has highlighted the role of domain-general, large-scale brain networks in generating emotional experiences. These networks are hypothesized to process aspects of emotional experiences that are not unique to a specific emotional category (e.g., "sadness," "happiness"), but rather that generalize across categories. In this article, we examined the dynamic interactions (i.e., changing cohesiveness) between specific domain-general networks across time while participants experienced various instances of sadness, fear, and anger. We used a novel method for probing the network connectivity dynamics between two salience networks and three amygdala-based networks. We hypothesized, and found, that the functional connectivity between these networks covaried with the intensity of different emotional experiences. Stronger connectivity between the dorsal salience network and the medial amygdala network was associated with more intense ratings of emotional experience across six different instances of the three emotion categories examined. Also, stronger connectivity between the dorsal salience network and the ventrolateral amygdala network was associated with more intense ratings of emotional experience across five out of the six different instances. Our findings demonstrate that a variety of emotional experiences are associated with dynamic interactions of domain-general neural systems.

Portraying the unique contribution of the default mode network to internally driven mnemonic processes.

Numerous neuroimaging studies have implicated default mode network (DMN) involvement in both internally driven processes and memory. Nevertheless, it is unclear whether memory operations reflect a particular case of internally driven processing or alternatively involve the DMN in a distinct manner, possibly depending on memory type. This question is critical for refining neurocognitive memory theorem in the context of other endogenic processes and elucidating the functional significance of this key network. We used functional MRI to examine DMN activity and connectivity patterns while participants overtly generated words according to nonmnemonic (phonemic) or mnemonic (semantic or episodic) cues. Overall, mnemonic word fluency was found to elicit greater DMN activity and stronger within-network functional connectivity compared with nonmnemonic fluency. Furthermore, two levels of functional organization of memory retrieval were shown. First, across both mnemonic tasks, activity was greater mainly in the posterior cingulate cortex, implying selective contribution to generic aspects of memory beyond its general involvement in endogenous processes. Second, parts of the DMN showed distinct selectivity for each of the mnemonic conditions; greater recruitment of the anterior prefrontal cortex, retroesplenial cortex, and hippocampi and elevated connectivity between anterior and posterior medial DMN nodes characterized the semantic condition, whereas increased recruitment of posterior DMN components and elevated connectivity between them characterized the episodic condition. This finding emphasizes the involvement of DMN elements in discrete aspects of memory retrieval. Altogether, our results show a specific contribution of the DMN to memory processes, corresponding to the specific type of memory retrieval.

Gray matter atrophy and freezing of gait in Parkinson's disease: Is the evidence black-on-white?

OBJECTIVES: The pathophysiology underlying freezing of gait (FOG) in Parkinson's disease (PD) is poorly understood. We tested whether gray matter (GM) atrophy contributes to FOG in PD. METHODS: Voxel-based morphometry quantified GM atrophy in 106 patients who were classified as freezers (n = 30) or nonfreezers (n = 76). Well-matched smaller subgroups were also studied. Balance, gait, and cognitive function were assessed, and we evaluated the relationship between GM, FOG severity, and symptoms associated with FOG. RESULTS: GM was significantly reduced in the inferior parietal lobe and angular gyrus in the matched freezers (n = 22), compared to nonfreezers (n = 22; P < 0.015, cluster-level corrected). In the entire cohort, FOG severity was related to bilateral caudate volumes. CONCLUSIONS: GM atrophy in cortical (i.e., parietal lobe and angular gyrus) and subcortical areas (i.e., caudate) are related to FOG. Disparities among the existing findings suggest that inferences regarding specific brain regions should be made with caution.

A voxel-based morphometry and diffusion tensor imaging analysis of asymptomatic Parkinson's disease-related G2019S LRRK2 mutation carriers.

BACKGROUND: Patients with Parkinson's disease have reduced gray matter volume and fractional anisotropy in both cortical and sub-cortical structures, yet changes in the pre-motor phase of the disease are unknown. METHODS: A comprehensive imaging study using voxel-based morphometry and diffusion tensor imaging tract-based spatial statistics analysis was performed on 64 Ashkenazi Jewish asymptomatic first degree relatives of patients with Parkinson's disease (30 mutation carriers), who carry the G2019S mutation in the leucine-rich repeat kinase 2 (LRRK2) gene. RESULTS: No between-group differences in gray matter volume could be noted in either whole-brain or volume-of-interest analysis. Diffusion tensor imaging analysis did not identify group differences in white matter areas, and volume-of-interest analysis identified no differences in diffusivity parameters in Parkinson's disease-related structures. CONCLUSIONS: G2019S carriers do not manifest changes in gray matter volume or diffusivity parameters in Parkinson's disease-related structures prior to the appearance of motor symptoms.

White-matter correlates of anxiety: The contribution of the corpus-callosum to the study of anxiety and stress-related disorders.

OBJECTIVES: Traumatic stress has been associated with increased risk for brain alterations and development of anxiety disorders. Studies conducted in posttraumatic patients have shown white-mater volume and diffusion alterations in the corpus-callosum. Decreased cognitive performance has been demonstrated in acute stress disorder and posttraumatic patients. However, whether cognitive alterations result from stress related neuropathology or reflect a predisposition is not known. In the current study, we examined in healthy controls, whether individual differences in anxiety are associated with those cognitive and brain alterations reported in stress related pathologies. METHODS: Twenty healthy volunteers were evaluated for anxiety using the state-trait inventory (STAI), and were tested for memory performance. Brain imaging was employed to extract volumetric and diffusion characteristics of the corpus-callosum. RESULTS: Significant correlations were found between trait anxiety and all three diffusion parameters (fractional-anisotropy, mean and radial-diffusivity). Associative-memory performance and corpus-callosum volume were also significantly correlated. CONCLUSION: We suggest that cognitive and brain alterations, as tested in the current work and reported in stress related pathologies, are present early and possibly persist throughout life. Our findings support the hypothesis that individual differences in trait anxiety predispose individuals towards negative cognitive outcomes and brain alterations, and potentially to stress related disorders.

Stress-related reduction of hippocampal subfield volumes in major depressive disorder: A 7-Tesla study.

Background: Major depressive disorder (MDD) is a prevalent health problem with complex pathophysiology that is not clearly understood. Prior work has implicated the hippocampus in MDD, but how hippocampal subfields influence or are affected by MDD requires further characterization with high-resolution data. This will help ascertain the accuracy and reproducibility of previous subfield findings in depression as well as correlate subfield volumes with MDD symptom scores. The objective of this study was to assess volumetric differences in hippocampal subfields between MDD patients globally and healthy controls (HC) as well as between a subset of treatment-resistant depression (TRD) patients and HC using automatic segmentation of hippocampal subfields (ASHS) software and ultra-high field MRI. Methods: Thirty-five MDD patients and 28 HC underwent imaging using 7-Tesla MRI. ASHS software was applied to the imaging data to perform automated hippocampal segmentation and provide volumetrics for analysis. An exploratory analysis was also performed on associations between symptom scores for diagnostic testing and hippocampal subfield volumes. Results: Compared to HC, MDD and TRD patients showed reduced right-hemisphere CA2/3 subfield volume (p = 0.01, η 2 = 0.31 and p = 0.3, η 2 = 0.44, respectively). Additionally, negative associations were found between subfield volumes and life-stressor checklist scores, including left CA1 (p = 0.041, f 2 = 0.419), left CA4/DG (p = 0.010, f 2 = 0.584), right subiculum total (p = 0.038, f 2 = 0.354), left hippocampus total (p = 0.015, f 2 = 0.134), and right hippocampus total (p = 0.034, f 2 = 0.110). Caution should be exercised in interpreting these results due to the small sample size and low power. Conclusion: Determining biomarkers for MDD and TRD pathophysiology through segmentation on high-resolution MRI data and understanding the effects of stress on these regions can enable better assessment of biological response to treatment selection and may elucidate the underlying mechanisms of depression.

Portraying emotions at their unfolding: a multilayered approach for probing dynamics of neural networks.

Dynamic functional integration of distinct neural systems plays a pivotal role in emotional experience. We introduce a novel approach for studying emotion-related changes in the interactions within and between networks using fMRI. It is based on continuous computation of a network cohesion index (NCI), which is sensitive to both strength and variability of signal correlations between pre-defined regions. The regions encompass three clusters (namely limbic, medial prefrontal cortex (mPFC) and cognitive), each previously was shown to be involved in emotional processing. Two sadness-inducing film excerpts were viewed passively, and comparisons between viewer's rated sadness, parasympathetic, and inter-NCI and intra-NCI were obtained. Limbic intra-NCI was associated with reported sadness in both movies. However, the correlation between the parasympathetic-index, the rated sadness and the limbic-NCI occurred in only one movie, possibly related to a "deactivated" pattern of sadness. In this film, rated sadness intensity also correlated with the mPFC intra-NCI, possibly reflecting temporal correspondence between sadness and sympathy. Further, only for this movie, we found an association between sadness rating and the mPFC-limbic inter-NCI time courses. To the contrary, in the other film in which sadness was reported to commingle with horror and anger, dramatic events coincided with disintegration of these networks. Together, this may point to a difference between the cinematic experiences with regard to inter-network dynamics related to emotional regulation. These findings demonstrate the advantage of a multi-layered dynamic analysis for elucidating the uniqueness of emotional experiences with regard to an unguided processing of continuous and complex stimulation.

The Future of Medicine Is Digital: Exploring the Ethics of Digital Pills.

Digital Pills are a drug-device technology that allow for the combination of traditional medications with a monitoring system that automatically records data about medication adherence and patients' physiological data. They are a promising innovation in digital medicine; however, their use has raised a number of ethical concerns. In this paper, we outline some of the main Digital Pills technologies and explore key ethical challenges surrounding their use. In this paper, we introduce educational materials we have developed that provide an insight into the technologies and ethical aspects that underpin Digital Pills.

Altered hippocampus and amygdala subregion connectome hierarchy in major depressive disorder.

The hippocampus and amygdala limbic structures are critical to the etiology of major depressive disorder (MDD). However, there are no high-resolution characterizations of the role of their subregions in the whole brain network (connectome). Connectomic examination of these subregions can uncover disorder-related patterns that are otherwise missed when treated as single structures. 38 MDD patients and 40 healthy controls (HC) underwent anatomical and diffusion imaging using 7-Tesla MRI. Whole-brain segmentation was performed along with hippocampus and amygdala subregion segmentation, each representing a node in the connectome. Graph theory analysis was applied to examine the importance of the limbic subregions within the brain network using centrality features measured by node strength (sum of weights of the node's connections), Betweenness (number of shortest paths that traverse the node), and clustering coefficient (how connected the node's neighbors are to one another and forming a cluster). Compared to HC, MDD patients showed decreased node strength of the right hippocampus cornu ammonis (CA) 3/4, indicating decreased connectivity to the rest of the brain, and decreased clustering coefficient of the right dentate gyrus, implying it is less embedded in a cluster. Additionally, within the MDD group, the greater the embedding of the right amygdala central nucleus (CeA) in a cluster, the greater the severity of depressive symptoms. The altered role of these limbic subregions in the whole-brain connectome is related to diagnosis and depression severity, contributing to our understanding of the limbic system involvement in MDD and may elucidate the underlying mechanisms of depression.

Quantification of brain age using high-resolution 7 tesla MR imaging and implications for patients with epilepsy.

Purpose: Epilepsy patients exhibit morphological differences on neuroimaging compared to age-matched healthy controls, including cortical and sub-cortical volume loss and altered gray-white matter ratios. The objective was to develop a model of normal aging using the 7T MRIs of healthy controls. This model can then be used to determine if the changes in epilepsy patients resemble the changes seen in aging, and potentially give a marker for the severity of those changes. Methods: Sixty-nine healthy controls (24F/45M, mean age 36.5 ± 10.5 years) and forty-four epilepsy patients (24F/20M, 33.2 ± 9.9 years) non-lesional at 3T were scanned with volumetric T1-MPRAGE at 7T. These images were segmented and quantified using FreeSurfer. A linear regression-based model trained on healthy controls was developed to predict ages using derived imaging features among the epilepsy patient cohort. The model used 114 features with significant linear correlation with age. Results: The regression-based model estimated brain age with mean absolute error (MAE) of 6.6 years among controls. Comparable prediction accuracy of 6.9 years MAE was seen epilepsy patients. T-test of mean absolute error showed no difference in the prediction accuracy with controls and epilepsy patients (p = 0.68). However, average signed error showed elevated (+5.0 years, p = 0.0007) predicted age differences (PAD; brain-PAD=, predicted minus biological age) among epilepsy patients. Morphological metrics in the medial temporal lobe were major contributors to PAD. Additionally, patients with seizure frequency greater than once a week showed significantly elevated brain-PAD (+8.2 ± 5.3 years, n = 13) compared to patients with lower seizure frequency (3.7 ± 6.5 years, n = 31, p = 0.033). Major conclusions: Morphological patterns suggestive of premature aging were observed in non-lesional epilepsy patients vs. controls and in high seizure frequency patients vs. low frequency patients. Modeling brain age with 7T MRI may provide a sensitive imaging marker to assess the differential effects of the aging process in diseases such as epilepsy.

The neural correlates of falls: Alterations in large-scale resting-state networks in elderly fallers.

INTRODUCTION: Falls are associated with numerous risk factors, such as motor and cognitive impairments. However, the neural correlates of falls are poorly understood. OBJECTIVES: Here, we aimed to assess patterns of structural, and resting-state functional connectivity (FC) alterations related to falls in a group of older adults with a history of falls compared to non-fallers. METHODS: Fourteen elderly fallers (mean age = 78.1 ± 1.5 yrs, >2 falls previous six months), and 20 healthy controls (mean age = 69.6 ± 1.3 yrs) were examined. All participants underwent a 3T MRI scan obtaining 3D T1-weighted images, and eyes-open resting-state (rs)-fMRI. Voxel-based morphometry was conducted to detect grey matter differences between the groups. Independent component analysis was conducted based on rs-fMRI and number of attention-and-motor related functional networks was identified and compared between groups using an independent-sample T-test. RESULTS: No differences were observed in grey matter between the groups after correcting for age and gender (p > 0.01, FWEc). Compared with non-fallers, the fallers had lower FC in cerebellar, frontal and parietal cortical nodes within the sensorimotor network (SMN), lateral motor network (M1), Cerebellar network (CBL), frontal-striatal network (FSN), executive control network (ECN), and dorsal attention network (DAN). Moreover, fallers had increased FC in the basal ganglia network (BGN), Left paracentral in M1 and SMN, and right hippocampus in DAN (p < 0.01, FWEc). CONCLUSIONS: Among fallers, reduced connectivity was observed in areas that relate to integration of information, while increased connectivity was found in areas associated with motor and sensory information processing. Together, these results provide evidence to the complex multidimensionality of the neural underpinnings of falls. Furthermore, these findings may help emphasize the importance of interventions that target both motor and cognitive aspects.

Distinct Effects of Motor Training on Resting-State Functional Networks of the Brain in Parkinson's Disease.

Background. Nigrostriatal dopaminergic loss is a hallmark of Parkinson's disease (PD) pathophysiology, leading to motor Parkinsonism. Different intervention protocols have shown that motor and cognitive functions improvement in PD occur via the modulation of distinct motor and cognitive pathways. Objective. To investigate the effects of two motor training programs on the brains' functional networks in PD patients. Methods. Thirty-seven PD patients were prospectively studied. All enrolled patients underwent either treadmill training (TT) (n = 19) or treadmill with virtual reality (TT + VR) (n = 18) for 6 weeks. Magnetic resonance imaging (MRI) scans (3 T) acquiring 3-dimensional T1-weighted and resting-state functional MRI (rs-fMRI) data sets were performed at baseline and after 6 weeks. Independent component analysis (ICA) was conducted, and functional connectivity (FC) changes within large-scale functional brain networks were examined. Results. In both groups, significant post-training FC decrease in striatal, limbic, and parietal regions within the basal ganglia network, executive control network, and frontal-striatal network, and significant FC increase in the caudate, and cingulate within the sensorimotor network (SMN) were observed. Moreover, a significant time × group interaction was detected where TT + VR training had greater effects on FC levels in the supplementary motor area (SMA) and right precentral gyrus within the SMN, and in the right middle frontal gyrus (MFG) within the cerebellar network. These FC alterations were associated with improved usual and dual-task walking performance. Conclusions. These results suggest that TT with-and-without the addition of a VR component affects distinct neural pathways, highlighting the potential for beneficial neural plasticity in PD. Such distinctive task-specific pathways may foster the facilitation of interventions tailored to the individual needs of PD patients. Registered at Clinicaltrials.gov number: NCT01732653.

Neural correlates of rumination in major depressive disorder: A brain network analysis.

Patients with major depressive disorder (MDD) exhibit higher levels of rumination, i.e., repetitive thinking patterns and exaggerated focus on negative states. Rumination is known to be associated with the cortical midline structures / default mode network (DMN) region activity, although the brain network topological organization underlying rumination remains unclear. Implementing a graph theoretical analysis based on ultra-high field 7-Tesla functional MRI data, we tested whether whole brain network connectivity hierarchies during resting state are associated with rumination in a dimensional manner across 20 patients with MDD and 20 healthy controls. Applying this data-driven approach we found a significant correlation between rumination tendency and connectivity strength degree of the right precuneus, a key node of the DMN. In order to interrogate this region further, we then applied the Dependency Network Analysis (DEPNA), a recently developed method used to quantify the connectivity influence of network nodes. This revealed that rumination was associated with lower connectivity influence of the left medial orbito-frontal cortex (MOFC) cortex on the right precuneus. Lastly, we used an information theory entropy measure that quantifies the cohesion of a network's correlation matrix. We show that subjects with higher rumination scores exhibit higher entropy levels within the DMN i.e. decreased overall connectivity within the DMN. These results emphasize the general DMN involvement during self-reflective processing related to maladaptive rumination in MDD. This work specifically highlights the impact of the MOFC on the precuneus, which might serve as a target for clinical neuromodulation treatment.

Altered organization of the dorsal attention network is associated with freezing of gait in Parkinson's disease.

INTRODUCTION: Deficits in executive function and attention have been associated with freezing of gait (FOG) in patients with Parkinson's disease (PD). However, the exact changes in the ventral and dorsal attentional networks that may contribute to FOG are unknown. Our aim was to examine the changes in connectivity of the attentional networks in patients with PD and their role in FOG. METHODS: Resting-state fMRI was obtained in 20 healthy controls (age: 69.7 ±â€¯1.3yrs), 11 patients without FOG (age: 74.1 ±â€¯1.2yrs), and 26 patients with FOG (age: 72.3 ±â€¯1.3yrs). Graph theory analysis was used to examine differences in previously defined attention networks between groups. RESULTS: We found differences between the groups in the dorsal attentional network (Global Efficiency: p = 0.007, Local Efficiency: p = 0.017, Between Centrality: p = 0.010). Global efficiency was lower in patients with FOG compared to healthy controls (p = 0.003) and patients without FOG (p = 0.025). Local efficiency was higher in patients with FOG compared to healthy controls (p = 0.014) but not compared to patients without FOG (p = 0.109). In contrast, no differences were found in the ventral attentional network between the groups (Global Efficiency: p = 0.258, Local Efficiency: p = 0.114, Between Centrality: p = 0.130). CONCLUSIONS: Altered organization of the dorsal attention network in patients with FOG may explain the higher risk for FOG during complex walking situations. In contrast, the lack of changes in the ventral attention network may partially explain the effectiveness of external cues on gait in patients with PD. Our findings support the idea that attentional networks play an important role in FOG.