An Overview on Electrophysiological and Neuroimaging Findings in Dyslexia

Objective: Dyslexia is a prevalent neurodevelopmental condition that is characterized by inaccurate and slow word recognition. This article reviews neural correlates of dyslexia from both electrophysiological and neuroimaging studies. Method : In this brief review, we provide electrophysiological and neuroimaging evidence from electroencephalogram (EEG) and magnetic resonance imaging (MRI) studies in dyslexia to understand functional and structural brain changes in this condition. Results: In both electrophysiological and neuroimaging studies, the most frequently reported functional impairments in dyslexia include aberrant activation of the left hemisphere occipito-temporal cortex (OTC), temporo-parietal cortex (TPC), inferior frontal gyrus (IFG), and cerebellar areas. EEG studies have mostly highlighted the important role of lower frequency bands in dyslexia, especially theta waves. Furthermore, neuroimaging studies have suggested that dyslexia is related to functional and structural impairments in the left hemisphere regions associated with reading and language, including reduced grey matter volume in the left TPC, decreased white matter connectivity between reading networks, and hypo-activation of the left OTC and TPC. In addition, neural evidence from pre-reading children and infants at risk for dyslexia show that there are abnormalities in the dyslexic brain before learning to read begins. Conclusion: Advances in comprehending the neural correlates of dyslexia could bring closer translation from basic to clinical neuroscience and effective rehabilitation for individuals who struggle to read. However, neuroscience still has great potential for clinical translation that requires further research.

A cognitive psychological approach for tooth identification based on brain event-related potentials

BACKGROUND

When perceiving a tooth, visual information, such as the tooth's morphology and feature areas, are projected onto the retina. The projected visual information is organized and transferred through the thalamus to the visual cortex, where shapes, colors, and sizes are analyzed. Thereafter, the information is contrasted with previous memories and experiences and finally recognized as the tooth. A variety of approaches, including cerebral physiology, psychology, and cognitive science are useful to understand how the brain recognizes and differentiates the teeth. Our research group has been studying event-related potentials (ERPs), which are known to be affected by psychological factors such as attention, retrieval, and memory. Herein, we describe the use of a cognitive psychological approach for tooth identification using the P300 latency, amplitude, and appearance patterns of ERP waveform components as indicators.

CONCLUSION

Tooth identification is based on the characteristic parameters of the object, which are matched with the knowledge stored in the brain, and the last steps of tooth identification are made through various cognitive activities.

Developing a Multi-channel Beamformer by Enhancing Spatially Constrained ICA for Recovery of Correlated EEG Sources

Background:

Brain source imaging based on electroencephalogram (EEG) data aims to recover the neuron populations’ activity producing the scalp potentials. This procedure is known as the EEG inverse problem. Recently, beamformers have gained a lot of consideration in the EEG inverse problem.

Objective:

Beamformers lack acceptable performance in the case of correlated brain sources. These sources happen when some regions of the brain have simultaneous or correlated activities such as auditory stimulation or moving left and right extremities of the body at the same time. In this paper, we have developed a multichannel beamformer robust to correlated sources.

Material and Methods:

In this simulation study, we have looked at the problem of brain source imaging and beamforming from a blind source separation point of view. We focused on the spatially constraint independent component analysis (scICA) algorithm, which generally benefits from the pre-known partial information of mixing matrix, and modified the steps of the algorithm in a way that makes it more robust to correlated sources. We called the modified scICA algorithm Multichannel ICA based EEG Beamformer (MIEB).

Results:

We evaluated the proposed algorithm on simulated EEG data and compared its performance quantitatively with three algorithms scICA, linearly-constrained minimum-variance (LCMV) and Dual-Core beamformers; it is considered that the latter is specially designed to reconstruct correlated sources.

Conclusion:

The MIEB algorithm has much better performance in terms of normalized mean squared error in recovering the correlated/uncorrelated sources both in noise free and noisy synthetic EEG signals. Therefore, it could be used as a robust beamformer in recovering correlated brain sources.

Brain Oscillations and Their Implications for Neurorehabilitation

Neural oscillation is rhythmic or repetitive neural activities, which can be observed at all levels of the central nervous system (CNS). The large-scale oscillations measured by electroencephalography have long been used in clinical practice and may have a potential for the usage in neurorehabilitation for people with various CNS disorders. The recent advancement of computational neuroscience has opened up new opportunities to explore clinical application of the results of neural oscillatory activity analysis to evaluation and diagnosis; monitoring the rehab progress; prognostication; and personalized rehabilitation planning in neurorehabilitation. In addition, neural oscillation is catching more attention to its role as a target of noninvasive neuromodulation in neurological disorders.

Investigating the Effects of Chiropractic Spinal Manipulation on EEG in Stroke Patients

: Objective: The purpose of this study was to evaluate the impact of chiropractic spinal manipulation on the early somatosensory evoked potentials (SEPs) and resting-state electroencephalography (EEG) recorded from chronic stroke patients. Methods: Seventeen male patients (53 ± 12 years old) participated in this randomized cross-over study. The patients received chiropractic spinal manipulation and control intervention, in random order, separated by at least 24 hours. EEG was recorded before and after each intervention during rest and stimulation of the non-paretic median nerve. For resting-state EEG, the delta-alpha ratio, brain-symmetry index, and power-spectra were calculated. For SEPs, the amplitudes and latencies of N20 and N30 peaks were assessed. Source localization was performed on the power-spectra of resting-state EEG and the N30 SEP peak. Results: Following spinal manipulation, the N30 amplitude increased by 39%, which was a significant increase compared to the control intervention (p < 0.01). The latency and changes to the strength of the cortical sources underlying the N30 peak were not significant. The N20 peak, the resting-state power-spectra, delta-alpha ratio, brain-symmetry index, and resting-state source localization showed no significant changes after either intervention. Conclusion: A single session of chiropractic spinal manipulation increased the amplitude of the N30 SEP peak in a group of chronic stroke patients, which may reflect changes to early sensorimotor function. More research is required to investigate the long-term effects of chiropractic spinal manipulation, to better understand what impact it may have on the neurological function of stroke survivors.

Modulatory Effect of Association of Brain Stimulation by Light and Binaural Beats in Specific Brain Waves

Introduction

One of the positive effects of brain stimulation is interhemispheric modulation as shown in some scientific studies. This study examined if a type of noninvasive stimulation using binaural beats with led-lights and sound would show different modulatory effects upon Alfa and SMR brain waves of elderlies and children with some disease types.

Subjects

The sample included 75 individuals of both genders, being, randomly, divided in 6 groups. Groups were named elderly without dementia diagnosis (EWD), n=15, 76±8 years, elderly diagnosed with Parkinson's disease (EDP), n=15, 72±7 years, elderly diagnosed with Alzheimer's disease (EDA), n=15, 81±6 years. The other groups were named children with Autism (CA), n=10, 11±4 years, children with Intellectual Impairment (CII), n=10, 12 ±5 years and children with normal cognitive development (CND), n=10, 11±4 years.

Instruments and procedure

Instruments were the Mini Mental State Examination Test (MMSE), EEG-Neurocomputer instrument for brain waves registration, brain stimulator, Digit Span Test and a Protocol for working memory training. Data collection followed a pre and post-conjugated stimulation version.

Results

The results of the inferential statistics showed that the stimulation protocol had different effects on Alpha and SMR brain waves of the patients. Also, indicated gains in memory functions, for both, children and elderlies as related to gains in brain waves modulation.

Conclusion

The results may receive and provide support to a range of studies examining brain modulation and synaptic plasticity. Also, it was emphasized in the results discussion that there was the possibility of the technique serving as an accessory instrument to alternative brain therapies.