Frontiers in neuroscience
-
Frontiers in neuroscience · Jan 2015
Magnetic resonance imaging biomarkers for the early diagnosis of Alzheimer's disease: a machine learning approach.
Determination of sensitive and specific markers of very early AD progression is intended to aid researchers and clinicians to develop new treatments and monitor their effectiveness, as well as to lessen the time and cost of clinical trials. Magnetic Resonance (MR)-related biomarkers have been recently identified by the use of machine learning methods for the in vivo differential diagnosis of AD. However, the vast majority of neuroimaging papers investigating this topic are focused on the difference between AD and patients with mild cognitive impairment (MCI), not considering the impact of MCI patients who will (MCIc) or not convert (MCInc) to AD. ⋯ CN, 66% MCIc vs. MCInc (nested 20-fold cross validation). Our data encourage the application of computer-based diagnosis in clinical practice of AD opening new prospective in the early management of AD patients.
-
Frontiers in neuroscience · Jan 2015
Segmentation of brain magnetic resonance images based on multi-atlas likelihood fusion: testing using data with a broad range of anatomical and photometric profiles.
We propose a hierarchical pipeline for skull-stripping and segmentation of anatomical structures of interest from T1-weighted images of the human brain. The pipeline is constructed based on a two-level Bayesian parameter estimation algorithm called multi-atlas likelihood fusion (MALF). In MALF, estimation of the parameter of interest is performed via maximum a posteriori estimation using the expectation-maximization (EM) algorithm. ⋯ As a result, we demonstrate subject-level differences in the performance of the proposed pipeline, which may be accounted for by age, diagnosis, or the imaging parameters (particularly the field strength). For the subcortical and ventricular structures of the two datasets, the hierarchical pipeline is capable of producing automated segmentations with Dice overlaps ranging from 0.8 to 0.964 when compared with the gold standard. Comparisons with other representative segmentation algorithms are presented, relative to which the proposed hierarchical pipeline demonstrates comparative or superior accuracy.
-
Frontiers in neuroscience · Jan 2015
Transcranial random noise stimulation-induced plasticity is NMDA-receptor independent but sodium-channel blocker and benzodiazepines sensitive.
Application of transcranial random noise stimulation (tRNS) between 0.1 and 640 Hz of the primary motor cortex (M1) for 10 min induces a persistent excitability increase lasting for at least 60 min. However, the mechanism of tRNS-induced cortical excitability alterations is not yet fully understood. ⋯ In contrast to transcranial direct current stimulation (tDCS), aftereffects of tRNS are seem to be not NMDA receptor dependent and can be suppressed by benzodiazepines suggesting that tDCS and tRNS depend upon different mechanisms.
-
Frontiers in neuroscience · Jan 2015
Case ReportsNeuroplastic Effects of Transcranial Direct Current Stimulation on Painful Symptoms Reduction in Chronic Hepatitis C: A Phase II Randomized, Double Blind, Sham Controlled Trial.
Pegylated Interferon Alpha (Peg-IFN) in combination with other drugs is the standard treatment for chronic hepatitis C infection (HCV) and is related to severe painful symptoms. The aim of this study was access the efficacy of transcranial direct current stimulation (tDCS) in controlling the painful symptoms related to Peg-IFN side effects. ⋯ Five sessions of tDCS were effective in reducing the painful symptoms in HCV patients undergoing Peg-IFN treatment. These findings support the efficacy of tDCS as a promising therapeutic tool to improve the tolerance of the side effects related to the use of Peg-IFN. Future larger studies (phase III and IV trials) are needed to confirm the clinical use of the therapeutic effects of tDCS in such condition.
-
Frontiers in neuroscience · Jan 2015
ReviewGlycolysis and the significance of lactate in traumatic brain injury.
In traumatic brain injury (TBI) patients, elevation of the brain extracellular lactate concentration and the lactate/pyruvate ratio are well-recognized, and are associated statistically with unfavorable clinical outcome. Brain extracellular lactate was conventionally regarded as a waste product of glucose, when glucose is metabolized via glycolysis (Embden-Meyerhof-Parnas pathway) to pyruvate, followed by conversion to lactate by the action of lactate dehydrogenase, and export of lactate into the extracellular fluid. In TBI, glycolytic lactate is ascribed to hypoxia or mitochondrial dysfunction, although the precise nature of the latter is incompletely understood. ⋯ This suggests that where neurons are too damaged to utilize the lactate produced from glucose by astrocytes, i.e., uncoupling of neuronal and glial metabolism, high extracellular levels of lactate would accumulate, explaining the association between high lactate and poor outcome. Recently, an intravenous exogenous lactate supplementation study in TBI patients revealed evidence for a beneficial effect judged by surrogate endpoints. Here we review the current state of knowledge about glycolysis and lactate in TBI, how it can be measured in patients, and whether it can be modulated to achieve better clinical outcome.