Visual short-term memory deficits associated with GBA mutation and Parkinson's disease.

Individuals with mutation in the lysosomal enzyme glucocerebrosidase (GBA) gene are at significantly high risk of developing Parkinson's disease with cognitive deficit. We examined whether visual short-term memory impairments, long associated with patients with Parkinson's disease, are also present in GBA-positive individuals-both with and without Parkinson's disease. Precision of visual working memory was measured using a serial order task in which participants observed four bars, each of a different colour and orientation, presented sequentially at screen centre. Afterwards, they were asked to adjust a coloured probe bar's orientation to match the orientation of the bar of the same colour in the sequence. An additional attentional 'filtering' condition tested patients' ability to selectively encode one of the four bars while ignoring the others. A sensorimotor task using the same stimuli controlled for perceptual and motor factors. There was a significant deficit in memory precision in GBA-positive individuals-with or without Parkinson's disease-as well as GBA-negative patients with Parkinson's disease, compared to healthy controls. Worst recall was observed in GBA-positive cases with Parkinson's disease. Although all groups were impaired in visual short-term memory, there was a double dissociation between sources of error associated with GBA mutation and Parkinson's disease. The deficit observed in GBA-positive individuals, regardless of whether they had Parkinson's disease, was explained by a systematic increase in interference from features of other items in memory: misbinding errors. In contrast, impairments in patients with Parkinson's disease, regardless of GBA status, was explained by increased random responses. Individuals who were GBA-positive and also had Parkinson's disease suffered from both types of error, demonstrating the worst performance. These findings provide evidence for dissociable signature deficits within the domain of visual short-term memory associated with GBA mutation and with Parkinson's disease. Identification of the specific pattern of cognitive impairment in GBA mutation versus Parkinson's disease is potentially important as it might help to identify individuals at risk of developing Parkinson's disease

Independent Component Analysis of the Effect of L-dopa on fMRI of Language Processing

L-dopa, which is a precursor for dopamine, acts to amplify strong signals, and dampen weak signals as suggested by previous studies. The effect of L-dopa has been demonstrated in language studies, suggesting restriction of the semantic network. In this study, we aimed to examine the effect of L-dopa on language processing with fMRI using Independent Component Analysis (ICA). Two types of language tasks (phonological and semantic categorization tasks) were tested under two drug conditions (placebo and L-dopa) in 16 healthy subjects. Probabilistic ICA (PICA), part of FSL, was implemented to generate Independent Components (IC) for each subject for the four conditions and the ICs were classified into task-relevant source groups by a correlation threshold criterion. Our key findings include: (i) The highly task-relevant brain regions including the Left Inferior Frontal Gyrus (LIFG), Left Fusiform Gyrus (LFUS), Left Parietal lobe (LPAR) and Superior Temporal Gyrus (STG) were activated with both L-dopa and placebo for both tasks, and (ii) as compared to placebo, L-dopa was associated with increased activity in posterior regions, including the superior temporal area (BA 22), and decreased activity in the thalamus (pulvinar) and inferior frontal gyrus (BA 11/47) for both tasks. These results raise the possibility that L-dopa may exert an indirect effect on posterior regions mediated by the thalamus (pulvinar)

CVD growth of carbon nanostructures from zirconia: mechanisms and a method for enhancing yield.

By excluding metals from synthesis, growth of carbon nanostructures via unreduced oxide nanoparticle catalysts offers wide technological potential. We report new observations of the mechanisms underlying chemical vapor deposition (CVD) growth of fibrous carbon nanostructures from zirconia nanoparticles. Transmission electron microscope (TEM) observation reveals distinct differences in morphological features of carbon nanotubes and nanofibers (CNTs and CNFs) grown from zirconia nanoparticle catalysts versus typical oxide-supported metal nanoparticle catalysts. Nanofibers borne from zirconia lack an observable graphitic cage consistently found with nanotube-bearing metal nanoparticle catalysts. We observe two distinct growth modalities for zirconia: (1) turbostratic CNTs 2-3 times smaller in diameter than the nanoparticle localized at a nanoparticle corner, and (2) nonhollow CNFs with approximately the same diameter as the nanoparticle. Unlike metal nanoparticle catalysts, zirconia-based growth should proceed via surface-bound kinetics, and we propose a growth model where initiation occurs at nanoparticle corners. Utilizing these mechanistic insights, we further demonstrate that preannealing of zirconia nanoparticles with a solid-state amorphous carbon substrate enhances growth yield.This material is based upon work supported by the National Science Foundation under Grant No. 1007793 and was also supported by Airbus group, Boeing, Embraer, Lockheed Martin, Saab AB, Hexcel, and TohoTenax through MIT’s Nano- Engineered Composite aerospace STructures (NECST) Consortium. This research was supported (in part) by the U.S. Army Research Office under Contract W911NF-13-D-0001. This work was performed in part at the Center for Nanoscale Systems (CNS), a member of the National Nanotechnology Infrastructure Network (NNIN), which is supported by the National Science Foundation under NSF Award No. ECS-0335765. CNS is part of Harvard University. This work was carried out in part through the use of MIT Microsystems Technology Laboratories. Stephan Hofmann acknowledges funding from EPSRC under grant EP/H047565/1. Piran Kidambi acknowledges the Lindemann Trust Fellowship.This is the final published version. It first appeared at http://pubs.acs.org/doi/abs/10.1021/ja509872y

Pseudotumoural soft tissue lesions of the hand and wrist: a pictorial review

Mimickers of soft tissue tumours in the hand and wrist are more frequent than true neoplastic lesions. Pseudotumours belong to a large and heterogeneous group of disorders, varying from normal anatomical variants, cystic lesions, post-traumatic lesions, skin lesions, inflammatory and infectious lesions, non-neoplastic vascular lesions, metabolic disorders (crystal deposition disease and amyloidosis) and miscellaneous disorders. Although the imaging approach to pseudotumoural lesions is often very similar to the approach to “true” soft tissue tumoral counterparts, further management of these lesions is different. Biopsy should be performed only in doubtful cases, when the diagnosis is unclear. Therefore, the radiologist plays a pivotal role in the diagnosis of these lesions. Awareness of the normal anatomy and existence and common imaging presentation of these diseases, in combination with relevant clinical findings (clinical history, age, location and skin changes), enables the radiologist to make the correct diagnosis in most cases, thereby limiting the need for invasive procedures

EEG Biofeedback as a Treatment for Substance Use Disorders: Review, Rating of Efficacy, and Recommendations for Further Research

Electroencephalographic (EEG) biofeedback has been employed in substance use disorder (SUD) over the last three decades. The SUD is a complex series of disorders with frequent comorbidities and EEG abnormalities of several types. EEG biofeedback has been employed in conjunction with other therapies and may be useful in enhancing certain outcomes of therapy. Based on published clinical studies and employing efficacy criteria adapted by the Association for Applied Psychophysiology and Biofeedback and the International Society for Neurofeedback and Research, alpha theta training—either alone for alcoholism or in combination with beta training for stimulant and mixed substance abuse and combined with residential treatment programs, is probably efficacious. Considerations of further research design taking these factors into account are discussed and descriptions of contemporary research are given

Dopamine, affordance and active inference.

The role of dopamine in behaviour and decision-making is often cast in terms of reinforcement learning and optimal decision theory. Here, we present an alternative view that frames the physiology of dopamine in terms of Bayes-optimal behaviour. In this account, dopamine controls the precision or salience of (external or internal) cues that engender action. In other words, dopamine balances bottom-up sensory information and top-down prior beliefs when making hierarchical inferences (predictions) about cues that have affordance. In this paper, we focus on the consequences of changing tonic levels of dopamine firing using simulations of cued sequential movements. Crucially, the predictions driving movements are based upon a hierarchical generative model that infers the context in which movements are made. This means that we can confuse agents by changing the context (order) in which cues are presented. These simulations provide a (Bayes-optimal) model of contextual uncertainty and set switching that can be quantified in terms of behavioural and electrophysiological responses. Furthermore, one can simulate dopaminergic lesions (by changing the precision of prediction errors) to produce pathological behaviours that are reminiscent of those seen in neurological disorders such as Parkinson's disease. We use these simulations to demonstrate how a single functional role for dopamine at the synaptic level can manifest in different ways at the behavioural level

Resting-State Quantitative Electroencephalography Reveals Increased Neurophysiologic Connectivity in Depression

Symptoms of Major Depressive Disorder (MDD) are hypothesized to arise from dysfunction in brain networks linking the limbic system and cortical regions. Alterations in brain functional cortical connectivity in resting-state networks have been detected with functional imaging techniques, but neurophysiologic connectivity measures have not been systematically examined. We used weighted network analysis to examine resting state functional connectivity as measured by quantitative electroencephalographic (qEEG) coherence in 121 unmedicated subjects with MDD and 37 healthy controls. Subjects with MDD had significantly higher overall coherence as compared to controls in the delta (0.5–4 Hz), theta (4–8 Hz), alpha (8–12 Hz), and beta (12–20 Hz) frequency bands. The frontopolar region contained the greatest number of “hub nodes” (surface recording locations) with high connectivity. MDD subjects expressed higher theta and alpha coherence primarily in longer distance connections between frontopolar and temporal or parietooccipital regions, and higher beta coherence primarily in connections within and between electrodes overlying the dorsolateral prefrontal cortical (DLPFC) or temporal regions. Nearest centroid analysis indicated that MDD subjects were best characterized by six alpha band connections primarily involving the prefrontal region. The present findings indicate a loss of selectivity in resting functional connectivity in MDD. The overall greater coherence observed in depressed subjects establishes a new context for the interpretation of previous studies showing differences in frontal alpha power and synchrony between subjects with MDD and normal controls. These results can inform the development of qEEG state and trait biomarkers for MDD