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Since its revelation over 14 centuries ago, the Holy Quran is considered as scriptural divine words of Islam, and it is believed to promote psycho-spiritual therapeutic benefits to its reciter and/or listener. In this context, the listening of rhythmic Quranic verses among Muslims is often viewed as a form of unconventional melodic vocals, with accompanied anecdotal claims of the 'Quranic chills' pleasing effect. However, compared to music, rhythm, and meditation therapy, information on the neural basis of the anecdotal healing effects of the Quran remain largely unexplored. Current studies in this area took the leads from the low-frequency neuronal oscillations (i.e., alpha and theta) as the neural correlates, mainly using electroencephalography (EEG) and/or magnetoencephalography (MEG). In this narrative review, we present and discuss recent work related to these neural correlates and highlight several methodical issues and propose recommendations to progress this emerging transdisciplinary research. Collectively, evidence suggests that listening to rhythmic Quranic verses activates similar brain regions and elicits comparable therapeutic effects reported in music and rhythmic therapy. Notwithstanding, further research are warranted with more concise and standardized study designs to substantiate these findings, and opens avenue for the listening to Quranic verses as an effective complementary psycho-spiritual therapy.

Bone marrow-derived mesenchymal stem cells (BMSCs) have therapeutic potential for spinal cord injury (SCI). We have shown that insulin-like growth factor 1 (IGF-1) enhances the cellular proliferation and survivability of BMSCs-derived neural progenitor cells (NPCs) by downregulating miR-22-3p. However, the functional application of BMSCs-derived NPCs has not been investigated fully. In this study, we demonstrate that knockdown of endogenous miR-22-3p in BMSCs-derived NPCs upregulates

Functional neuroimaging modalities play an important role in deciding the diagnosis and course of treatment of neuronal dysfunction and degeneration. This article presents an analytical tool with visualization by exploiting the strengths of the MEG (magnetoencephalographic) neuroimaging technique. The tool automates MEG data import (in tSSS format), channel information extraction, time/frequency decomposition, and circular graph visualization (connectogram) for simple result inspection. For advanced users, the tool also provides magnitude squared coherence (MSC) values allowing personalized threshold levels, and the computation of default model from MEG data of control population. Default model obtained from healthy population data serves as a useful benchmark to diagnose and monitor neuronal recovery during treatment. The proposed tool further provides optional labels with international 10-10 system nomenclature in order to facilitate comparison studies with EEG (electroencephalography) sensor space. Potential applications in epilepsy and traumatic brain injury studies are also discussed.

To evaluate the correlations between memory function and intelligence and event-related potential, the P300 component for different tasks was studied for 30 post-traumatic brain injury patients (mean age 31.6 +/- 13.7 years; 23 male and 7 female). Memory function, intelligence, and depression were measured by using the Mini-Mental State Examination, the revised Wechsler Adult Intelligence Scale and the Self-Rating Depression Scale, respectively. P300 latency was measured during silent-count and button-press tests at three midline scalp (Fz, Cz, and Pz) sites for all subjects by using an auditory 'odd-ball' paradigm. Neuropsychological memory score was predicted by intelligence score, but neurophysiological P300 latency was predicted by memory score for the silent-count test and by intelligence score for the button-press test. These results show that the P300 event-related potential component is sensitive to the diverse nature of cognitive deficits in post-traumatic brain injury patients during different types of discrimination tasks. However, future research is necessary to replicate and extend these findings.

Transcranial magnetic stimulation (TMS) elicits short latency excitatory responses in the target muscles, termed motor evoked potential (MEP). When TMS is delivered during a voluntary contraction, the MEP is followed by a period of silence called silent period (SP). These MEP parameters are in general recordable by electromyography (EMG). Mechanomyography (MMG) on the other hand is the mechanical counterpart of EMG. Thus, this study has been conducted to observe whether the MEP parameters from MMG signals showed similar trait of EMG recordings. Five normal healthy male subjects were included in this study. The subjects were required to perform right biceps brachii muscles contraction at diverse graded of load level at 5, 10, 20, 30, 40, 60, and 100% maximum voluntary contraction (MVC). MEPs by single pulse TMS on left hemisphere were obtained from both EMG electrode and MMG accelerometer at rest and at different levels of predetermined load level. MEP amplitude and area obtained both from EMG and MMG record were increased with the increase of muscle contraction with a maximum of 60% MVC. With increasing the level of contraction there was a shortening of onset latency and decreasing in the length of silent period in both EMG and MMG signals. We also recorded the EMG- and MMG-MEP from the right extensor carpi radialis muscle during transcutaneous electric nerve stimulation in order to observe neural changes in sensory stimulation from both EMG and MMG responses. The EMG-MEP was not visible in electrical artifact whereas it was obvious in MMG responses. In accordance with other study, this study showed that the voluntary contraction of biceps brachii muscle influenced the MEP parameter which are moreover obtainable by MMG even in electrical noise may provide insight for future study.