Faculty Bibliography

PURPOSE: The proposed reconstruction framework addresses the reconstruction accuracy, noise propagation and computation time for magnetic resonance fingerprinting. METHODS: Based on a singular value decomposition of the signal evolution, magnetic resonance fingerprinting is formulated as a low rank (LR) inverse problem in which one image is reconstructed for each singular value under consideration. This LR approximation of the signal evolution reduces the computational burden by reducing the number of Fourier transformations. Also, the LR approximation improves the conditioning of the problem, which is further improved by extending the LR inverse problem to an augmented Lagrangian that is solved by the alternating direction method of multipliers. The root mean square error and the noise propagation are analyzed in simulations. For verification, in vivo examples are provided. RESULTS: The proposed LR alternating direction method of multipliers approach shows a reduced root mean square error compared to the original fingerprinting reconstruction, to a LR approximation alone and to an alternating direction method of multipliers approach without a LR approximation. Incorporating sensitivity encoding allows for further artifact reduction. CONCLUSION: The proposed reconstruction provides robust convergence, reduced computational burden and improved image quality compared to other magnetic resonance fingerprinting reconstruction approaches evaluated in this study. Magn Reson Med, 2017. (c) 2017 International Society for Magnetic Resonance in Medicine.

Modeling self-organization of neural networks for unsupervised learning using Hebbian and anti-Hebbian plasticity has a long history in neuroscience. Yet derivations of single-layer networks with such local learning rules from principled optimization objectives became possible only recently, with the introduction of similarity matching objectives. What explains the success of similarity matching objectives in deriving neural networks with local learning rules? Here, using dimensionality reduction as an example, we introduce several variable substitutions that illuminate the success of similarity matching. We show that the full network objective may be optimized separately for each synapse using local learning rules in both the offline and online settings. We formalize the long-standing intuition of the rivalry between Hebbian and anti-Hebbian rules by formulating a min-max optimization problem. We introduce a novel dimensionality reduction objective using fractional matrix exponents. To illustrate the generality of our approach, we apply it to a novel formulation of dimensionality reduction combined with whitening. We confirm numerically that the networks with learning rules derived from principled objectives perform better than those with heuristic learning rules.

There is common agreement that many disorders of the central nervous system are 'complex', that is, there are many potential factors that influence the development of the disease, underlying mechanisms, and successful treatment. Most of these disorders, unfortunately, have no cure at the present time, and therapeutic strategies often have debilitating side effects. Interestingly, some of the 'complexities' of one disorder are found in another, and the similarities are often network defects. It seems likely that more discussions of these commonalities could advance our understanding and, therefore, have clinical implications or translational impact. With this in mind, the Fourth International Halifax Epilepsy Conference and Retreat was held as described in the prior paper, and this companion paper focuses on the second half of the meeting. Leaders in various subspecialties of epilepsy research were asked to address aging and dementia or psychosis in people with epilepsy (PWE). Commonalities between autism, depression, aging and dementia, psychosis, and epilepsy were the focus of the presentations and discussion. In the last session, additional experts commented on new conceptualization of translational epilepsy research efforts. Here, the presentations are reviewed, and salient points are highlighted.

OBJECTIVE:To test the hypothesis that localization-related epilepsy is associated with widespread neuronal dysfunction beyond the ictal focus, reflected by a decrease in patients' global concentration of their proton MR spectroscopy (1H-MRS) observed marker, N-acetyl-aspartate (NAA). METHODS:Thirteen patients with localization-related epilepsy (7 men, 6 women) 40±13 (mean±standard-deviation)years old, 8.3±13.4years of disease duration; and 14 matched controls, were scanned at 3 T with MRI and whole-brain (WB) 1H MRS. Intracranial fractions of brain volume, gray and white matter (fBV, fGM, fWM) were segmented from the MRI, and global absolute NAA creatine (Cr) and choline (Cho) concentrations were estimated from their WB 1H MRS. These metrics were compared between patients and controls using an unequal variance t test. RESULTS:Patients' fBV, fGM and fWM: 0.81±0.07, 0.47±0.04, 0.31±0.04 were not different from controls' 0.79±0.05, 0.48±0.04, 0.32±0.02; nor were their Cr and Cho concentrations: 7.1±1.1 and 1.3±0.2 millimolar (mM) versus 7.7±0.7 and 1.4±0.1mM (p>0.05 all). Patients' global NAA concentration: 11.5±1.5 mM, however, was 12% lower than controls' 13.0±0.8mM (p=0.004). CONCLUSIONS:These findings indicate that neuronal dysfunction in localization-related epilepsy extends globally, beyond the ictal zone, but without atrophy or spectroscopic evidence of other pathology. This suggests a diffuse decline in the neurons' health, rather than their number, early in the disease course. WB 1H-MRS assessment, therefore, may be a useful tool for quantification of global neuronal dysfunction load in epilepsy.

Important tools in the study of prefrontal cortical-dependent executive functions are cross-species behavioural tasks with translational validity. A widely used test of executive function and attention in humans is the continuous performance task (CPT). Optimal performance in variations of this task is associated with activity along the medial wall of the prefrontal cortex, including the anterior cingulate cortex (ACC), for its essential components such as response control, target detection and processing of false alarm errors. We assess the validity of a recently developed rodent touchscreen continuous performance task (rCPT) that is analogous to typical human CPT procedures. Here we evaluate the performance of mice with quinolinic acid-induced lesions centred on the ACC in the rCPT following a range of task parameter manipulations designed to challenge attention and impulse control. Lesioned mice showed a disinhibited response profile expressed as a decreased response criterion and increased false alarm rates. ACC lesions also resulted in a milder increase in inter-trial interval responses ('ITI touches') and hit rate. Lesions did not affect discriminative sensitivity d'. The disinhibited behaviour of ACC lesioned animals was stable and not affected by the manipulation of variable task parameter manipulations designed to increase task difficulty. The results are in general agreement with human studies implicating the ACC in the processing of inappropriate responses. We conclude that the rCPT may be useful for studying prefrontal cortex function in mice and has the capability of providing meaningful links between animal and human cognitive tasks.