Yael Jacob

Gray matter atrophy distinguishes between Parkinson disease motor subtypes

Objective: To assess differences in gray matter (GM) atrophy between 2 Parkinson disease (PD) subtypes: the tremor dominant (TD) subtype and the postural instability gait difficulty (PIGD) subtype. Methods: Patients were classified as belonging to the predominately PIGD (n = 30) or predominately TD (n = 29) subtype. Voxel-based morphometry was used to compare GM in these 2 subtypes and to evaluate correlations between predefined regions of interest and the degree of symptoms. In the regions where GM atrophy was associated with symptoms, the relationship between GM volumes and functional connectivity was examined. Results: GM was reduced in the predominately PIGD group, compared with the predominately TD group, in areas that involve motor, cognitive, limbic, and associative functions (p < 0.05, false discovery rate corrected). Lower GM volumes in the pre–supplementary motor area (SMA) and in the primary motor area were associated with increased severity of PIGD symptoms (r = −0.42, p < 0.001; r = −0.38, p < 0.003, respectively). Higher GM volumes within the pre-SMA were associated with stronger functional connectivity between the pre-SMA and the putamen (r = 0.415, p < 0.025) in the patients with predominately PIGD. Conclusions: In patients with PD, PIGD symptoms are apparently associated with GM atrophy in motor-related regions and decreased functional connectivity. GM degeneration and a related decrease in spontaneous coactivation between cortical and subcortical motor-planning areas may partially account for the unique clinical characteristics of a subset of patients with PD.

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.

White Matter Hyperintensities in Parkinson’s Disease: Do They Explain the Disparity between the Postural Instability Gait Difficulty and Tremor Dominant Subtypes?

Background Brain white matter hyperintensities (WMHs) commonly observed on brain imaging of older adults are associated with balance and gait impairment and have also been linked to cognitive deficits. Parkinson’s disease (PD) is traditionally sub-classified into the postural instability gait difficulty (PIGD) sub-type, and the tremor dominant (TD) sub-type. Considering the known association between WMHs and axial symptoms like gait disturbances and postural instability, one can hypothesize that WMHs might contribute to the disparate clinical sub-types of patients with PD. Methods 110 patients with PD underwent a clinical evaluation and a 3T MRI exam. Based on the Unified Parkinson Disease Rating Scale, the patients were classified into motor sub-types, i.e., TD or PIGD, and scores reflecting PIGD and TD symptoms were computed. We compared white matter burden using three previously validated methods: one using a semi-quantitative visual rating scale in specific brain regions and two automated methods. Results Overall, MRI data were obtained in 104 patients. The mean WMHs scores and the percent of subjects with lesions in specific brain regions were similar in the two subtypes, p = 0.678. The PIGD and the TD scores did not differ even when comparing patients with a relatively high burden of WMHs to patients with a relatively low burden. Across most of the brain regions, mild to moderate correlations between WMHs and age were found (r = 0.23 to 0.41; p<0.021). Conversely, no significant correlations were found between WMHs and the PIGD score or disease duration. In addition, depressive symptoms and cerebro-vascular risk factors were similar among the two subtypes. Conclusions In contrast to what has been reported previously among older adults, the present study could not demonstrate any association between WMHs and the PIGD or TD motor sub-types in patients with PD.

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.

A Voxel-Based Morphometry and Diffusion Tensor Imaging Analysis of Asymptomatic Parkinson's Disease-Related G2019S LRRK2 Mutation Carriers

Patients with Parkinsons 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.

Altered brain activation in complex walking conditions in patients with Parkinson's disease

INTRODUCTION Behavioral studies suggest that deficits in cognitive domains and sensory-motor processes associated with Parkinsons disease (PD) impair the ability to walk in complex environments. However, the neural correlates of locomotion in complex environments are still unclear. METHODS Twenty healthy older adults (mean age 69.7 ± 1.3 yrs) and 20 patients with PD (mean age 72.9 ± 1.6 yrs; disease duration: 6.8 ± 1.3 yrs; UPDRSIII: 29.8 ± 2.4) were asked to imagine themselves walking while in the MRI scanner. Three imagined walking tasks, i.e., usual walking, obstacle negotiation, and navigation were performed. Watching the same virtual scenes without imagining walking served as control tasks. Whole brain analyses were used. RESULTS Compared to usual walking, both groups had increased activation during obstacle negotiation in middle occipital gyrus (MOG) (pFWEcorr<0.001), middle frontal gyrus (MFG) (pFWEcorr<0.005), and cerebellum (pFWEcorr<0.001). Healthy older adults had higher activation in precuneus and MOG (pFWEcorr<0.023) during navigation, while no differences were observed in patients with PD. Between group comparisons revealed that patients with PD had a significantly higher activation in usual walking and obstacle negotiation (pFWEcorr<0.039) while during navigation task, healthy older adults had higher activation (pFWEcorr<0.047). CONCLUSIONS Patients with PD require greater activation during imagined usual walking and obstacle negotiation than healthy older adults. This increased activation may reflect a compensatory attempt to overcome inefficient neural activation in patients with PD. This increased activation may reduce the functional reserve needed during more demanding tasks such as during navigation which may contribute to the high prevalence of falls and dual tasking difficulties among patients with PD.

Disparate effects of training on brain activation in Parkinson disease

Objective: To compare the effects of 2 forms of exercise, i.e., a 6-week trial of treadmill training with virtual reality (TT + VR) that targets motor and cognitive aspects of safe ambulation and a 6-week trial of treadmill training alone (TT), on brain activation in patients with Parkinson disease (PD). Methods: As part of a randomized controlled trial, patients were randomly assigned to 6 weeks of TT (n = 17, mean age 71.5 ± 1.5 years, disease duration 11.6 ± 1.6 years; 70% men) or TT + VR (n = 17, mean age 71.2 ± 1.7 years, disease duration 7.9 ± 1.4 years; 65% men). A previously validated fMRI imagery paradigm assessed changes in neural activation pretraining and post-training. Participants imagined themselves walking in 2 virtual scenes projected in the fMRI: (1) a clear path and (2) a path with virtual obstacles. Whole brain and region of interest analyses were performed. Results: Brain activation patterns were similar between training arms before the interventions. After training, participants in the TT + VR arm had lower activation than the TT arm in Brodmann area 10 and the inferior frontal gyrus (cluster level familywise error–corrected [FWEcorr] p < 0.012), while the TT arm had lower activation than TT + VR in the cerebellum and middle temporal gyrus (cluster level FWEcorr p < 0.001). Changes in fall frequency and brain activation were correlated in the TT + VR arm. Conclusions: Exercise modifies brain activation patterns in patients with PD in a mode-specific manner. Motor-cognitive training decreased the reliance on frontal regions, which apparently resulted in improved function, perhaps reflecting increased brain efficiency.

Dependency Network Analysis (DEPNA) Reveals Context Related Influence of Brain Network Nodes

Communication between and within brain regions is essential for information processing within functional networks. The current methods to determine the influence of one region on another are either based on temporal resolution, or require a predefined model for the connectivity direction. However these requirements are not always achieved, especially in fMRI studies, which have poor temporal resolution. We thus propose a new graph theory approach that focuses on the correlation influence between selected brain regions, entitled Dependency Network Analysis (DEPNA). Partial correlations are used to quantify the level of influence of each node during task performance. As a proof of concept, we conducted the DEPNA on simulated datasets and on two empirical motor and working memory fMRI tasks. The simulations revealed that the DEPNA correctly captures the network’s hierarchy of influence. Applying DEPNA to the functional tasks reveals the dynamics between specific nodes as would be expected from prior knowledge. To conclude, we demonstrate that DEPNA can capture the most influencing nodes in the network, as they emerge during specific cognitive processes. This ability opens a new horizon for example in delineating critical nodes for specific clinical interventions.

Towards emotional regulation through neurofeedback

This paper discusses the potential of Brain-Computer Interfaces based on neurofeedback methods to support emotional control and pursue the goal of emotional control as a mechanism for human augmentation in specific contexts. We illustrate this discussion through two proof-of-concept, fully-implemented experiments: one controlling disposition towards virtual characters using pre-frontal alpha asymmetry, and the other aimed at controlling arousal through activity of the amygdala. In the first instance, these systems are intended to explore augmentation technologies that would be incorporated into various media-based systems rather than permanently affect user behaviour.

Breakdown of Inter-Hemispheric Connectivity Is Associated with Posttraumatic Symptomatology and Memory Impairment

Altered brain anatomy in specific gray-matter regions has been shown in patients with posttraumatic stress disorder (PTSD). Recently, white-matter tracts have become a focus of research in PTSD. The corpus callosum (CC) is the principal white-matter fiber bundle, crucial in relaying sensory, motor and cognitive information between hemispheres. Alterations in CC fibers have been reported in PTSD and might be assumed to underlie substantial behavioral and cognitive sequelae; however most diffusion tensor imaging (DTI) studies in adult-onset PTSD failed to address the clinical correlates between imaging and PTSD symptoms severity, behavioral manifestation and cognitive functions. In the current study we examined (a) to what extent microstructural integrity of the CC is associated with memory performance and (b) whether imaging and cognitive parameters are associated with PTSD symptom severity. DTI data were obtained and fractional anisotropy (FA) values were computed for 16 patients and 14 controls. PTSD symptom severity was assessed by employing the clinician administered PTSD scale (CAPS) and memory was tested using a task probing item and associative memory for words and pictures. Significant correlations were found between PTSD symptoms severity, memory accuracy and reaction-time to CC FA values in the PTSD group. This study demonstrates meaningful clinical and cognitive correlates of microstructural connectivity. These results have implications for diagnostic tools and future studies aimed at identifying individuals at risk for PTSD.