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The combination of an in-plane B1 sensitivity encoding (SENSE) technique with a simultaneous multiple-slice B0 field step technique (multiple-acquisition micro B0 array (MAMBA)) has produced high scan time reduction factors (R ≤ 8). In this study, two slices were acquired simultaneously in combination with ×2 and ×4 SENSE in-plane encoding using a MAMBA stepped B0 field coil inside a four-channel phased-array coil system. Experiments were performed on a 1.5 T Infinion system (Philips Medical Systems, Cleveland, OH). The signal-to-noise ratio (SNR) was reduced with higher R factors, as was expected from the reduced number of acquisitions used to create the unaliased images. The combination of SENSE and MAMBA offers great promise for reducing scan times through parallel acquisition while at the same time reducing the number of RF channels required by a factor equal to the number of field steps employed. The B1 array combined with MAMBA (B1AC-MAMBA) technique is applicable when the length of an object is much greater than its diameter, as in scanning limbs or in whole-body screening for disease. Magn Reson Med 49:1196–1200, 2003. © 2003 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

Cognitive impairments are commonly observed in patients with multiple sclerosis and are associated with lower levels of quality of life. No consensus has been reached on how to tackle effectively cognitive decline in this clinical population non-pharmacologically. This exploratory case-control study aims to investigate the effectiveness of a hypothesis-based cognitive training designed to target multiple domains by promoting the synchronous co-activation of different brain areas and thereby improve cognition and induce changes in functional connectivity in patients with relapsing-remitting multiple sclerosis. Forty-five patients (36 females and 9 males, mean age 44.62 ± 8.80 years) with clinically stable relapsing-remitting multiple sclerosis were assigned to either a standard cognitive training or to control groups (sham training and non-active control). The standard training included twenty sessions of computerized exercises involving various cognitive functions supported by distinct brain networks. The sham training was a modified version of the standard training that comprised the same exercises and number of sessions but with increased processing speed load. The non-active control group received no cognitive training. All patients underwent comprehensive neuropsychological and magnetic resonance imaging assessments at baseline and after 5 weeks. Cognitive and resting-state magnetic resonance imaging data were analyzed using repeated measures models. At reassessment, the standard training group showed significant cognitive improvements compared to both control groups in memory tasks not specifically targeted by the training: the Buschke Selective Reminding Test and the Semantic Fluency test. The standard training group showed reductions in functional connectivity of the salience network, in the anterior cingulate cortex, associated with improvements on the Buschke Selective Reminding Test. No changes were observed in the sham training group. These findings suggest that multi-domain training that stimulates multiple brain areas synchronously may improve cognition in people with relapsing-remitting multiple sclerosis if sufficient time to process training material is allowed. The associated reduction in functional connectivity of the salience network suggests that training-induced neuroplastic functional reorganization may be the mechanism supporting performance gains. This study was approved by the Regional Ethics Committee of Yorkshire and Humber (approval No. 12/YH/0474) on November 20, 2013.

One of the fundamental challenges when dealing with medical imaging datasets is class imbalance. Class imbalance happens where an instance in the class of interest is relatively low, when compared to the rest of the data. This study aims to apply oversampling strategies in an attempt to balance the classes and improve classification performance. We evaluated four different classifiers from k-nearest neighbors (k-NN), support vector machine (SVM), multilayer perceptron (MLP) and decision trees (DT) with 73 oversampling strategies. In this work, we used imbalanced learning oversampling techniques to improve classification in datasets that are distinctively sparser and clustered. This work reports the best oversampling and classifier combinations and concludes that the usage of oversampling methods always outperforms no oversampling strategies hence improving the classification results.

Clinical methods of detecting diabetic peripheral neuropathy (DPN) are not objective and reproducible. We therefore evaluated if SUDOSCAN, a new method developed to provide a quick, non-invasive and quantitative assessment of sudomotor function can reliably screen for DPN. 70 subjects (45 with type 1 diabetes and 25 healthy volunteers [HV]) underwent detailed assessments including clinical, neurophysiological and 5 standard cardiovascular reflex tests (CARTs). Using the American Academy of Neurology criteria subjects were classified into DPN and No-DPN groups. Based on CARTs subjects were also divided into CAN, subclinical-CAN and no-CAN. Sudomotor function was assessed with measurement of hand and foot Electrochemical Skin Conductance (ESC) and calculation of the CAN risk score. Foot ESC (μS) was significantly lower in subjects with DPN [n = 24; 53.5(25.1)] compared to the No-DPN [77.0(7.9)] and HV [77.1(14.3)] groups (ANCOVA p

Several studies have investigated the neural basis of effortful emotion regulation (ER) but the neural basis of automatic ER has been less comprehensively explored. The present study investigated the neural basis of automatic ER supported by 'implementation intentions'. 40 healthy participants underwent fMRI while viewing emotion-eliciting images and used either a previously-taught effortful ER strategy, in the form of a goal intention (e.g., try to take a detached perspective), or a more automatic ER strategy, in the form of an implementation intention (e.g., "If I see something disgusting, then I will think these are just pixels on the screen!"), to regulate their emotional response. Whereas goal intention ER strategies were associated with activation of brain areas previously reported to be involved in effortful ER (including dorsolateral prefrontal cortex), ER strategies based on an implementation intention strategy were associated with activation of right inferior frontal gyrus and ventro-parietal cortex, which may reflect the attentional control processes automatically captured by the cue for action contained within the implementation intention. Goal intentions were also associated with less effective modulation of left amygdala, supporting the increased efficacy of ER under implementation intention instructions, which showed coupling of orbitofrontal cortex and amygdala. The findings support previous behavioural studies in suggesting that forming an implementation intention enables people to enact goal-directed responses with less effort and more efficiency.

The neural basis of progress monitoring has received relatively little attention compared to other sub-processes that are involved in goal directed behavior such as motor control and response inhibition. Studies of error-monitoring have identified the dorsal anterior cingulate cortex (dACC) as a structure that is sensitive to conflict detection, and triggers corrective action. However, monitoring goal progress involves monitoring correct as well as erroneous events over a period of time. In the present research, 20 healthy participants underwent fMRI while playing a game that involved monitoring progress towards either a numerical or a visuo-spatial target. The findings confirmed the role of the dACC in detecting situations in which the current state may conflict with the desired state, but also revealed activations in the frontal and parietal regions, pointing to the involvement of processes such as attention and working memory in monitoring progress over time. In addition, activation of the cuneus was associated with monitoring progress towards a specific target presented in the visual modality. This is the first time that activation in this region has been linked to higher-order processing of goal-relevant information, rather than low-level anticipation of visual stimuli. Taken together, these findings identify the neural substrates involved in monitoring progress over time, and how these extend beyond activations observed in conflict and error monitoring.

Life expectancy in multiple myeloma has significantly increased. However, a high incidence of chemotherapy induced peripheral neuropathy (CIPN) can negatively influence quality of life during this period. This study applied functional magnetic resonance imaging (fMRI) to compare areas associated with central pain processing in patients with multiple myeloma who had chemotherapy induced peripheral neuropathy (MM-CIPN) with those from healthy volunteers (HV). Twenty-four participants (n = 12 MM-CIPN, n = 12 HV) underwent Blood Oxygen Level-Dependent (BOLD) fMRI at 3T whilst noxious heat-pain stimuli were applied to the foot and then thigh. Patients with MM-CIPN demonstrated greater activation during painful stimulation in the precuneus compared to HV (p = 0.014, FWE-corrected). Patients with MM-CIPN exhibited hypo-activation of the right superior frontal gyrus compared to HV (p = 0.031, FWE-corrected). Significant positive correlation existed between the total neuropathy score (reduced version) and activation in the frontal operculum (close to insular cortex) during foot stimulation in patients with MM-CIPN (p = 0.03, FWE-corrected; adjusted R2 = 0.87). Painful stimuli delivered to MM-CIPN patients evoke differential activation of distinct cortical regions, reflecting a unique pattern of central pain processing compared with healthy volunteers. This characteristic activation pattern associated with pain furthers the understanding of the pathophysiology of painful chemotherapy induced peripheral neuropathy. Functional MRI provides a tool for monitoring cerebral changes during anti-cancer and analgesic treatment.