scholarly journals CHANGES OF THE LOCAL FUNCTIONAL BRAIN ACTIVITY ASSOCIATED WITH SPEECH DISORDERS IN CHILDREN WITH EPILEPSY AND DEVELOPMENTAL DELAY (PET STUDY)

2019 ◽  
pp. 39-43
Author(s):  
Yu. G. Khomenko ◽  
G. V. Kataeva ◽  
V. I. Kolomiec
Keyword(s):  
Cerebral Metabolism ◽  
Brain Activity ◽  
Brain Structures ◽  
Speech Disorders ◽  
Speech Development ◽  
Metabolism Rate ◽  
Local Functional ◽  
Left And Right ◽  
Functional Brain Activity ◽  
The Brain

PET study of cerebral glucose metabolism was performed in 73 children with epilepsy and mental retardation. Expressive speech disorders were associated with decrease of cerebral metabolism rate of glucose (CMRglu) in the upper frontal gyrus, caudate nucleus and thalamus of the left and right hemispheres. In the group with combined expressive and impressive speech disorders the significant CMRglu reduction in the middle temporal and supramarginal gyrus of the left hemisphere was observed. The obtained results confirm that the brain structures associated with the executive functions and complex association processes have a great significance in the speech development.

scholarly journals Consciousness, decision making, and volition: freedom beyond chance and necessity

2021 ◽  
Author(s):  
Hans Liljenström
Keyword(s):  
Decision Making ◽  
Free Will ◽  
Brain Activity ◽  
Brain Structures ◽  
Complex Process ◽  
Neural Information ◽  
Neural Information Processing ◽  
Stochastic Population Model ◽  
The Brain

AbstractWhat is the role of consciousness in volition and decision-making? Are our actions fully determined by brain activity preceding our decisions to act, or can consciousness instead affect the brain activity leading to action? This has been much debated in philosophy, but also in science since the famous experiments by Libet in the 1980s, where the current most common interpretation is that conscious free will is an illusion. It seems that the brain knows, up to several seconds in advance what “you” decide to do. These studies have, however, been criticized, and alternative interpretations of the experiments can be given, some of which are discussed in this paper. In an attempt to elucidate the processes involved in decision-making (DM), as an essential part of volition, we have developed a computational model of relevant brain structures and their neurodynamics. While DM is a complex process, we have particularly focused on the amygdala and orbitofrontal cortex (OFC) for its emotional, and the lateral prefrontal cortex (LPFC) for its cognitive aspects. In this paper, we present a stochastic population model representing the neural information processing of DM. Simulation results seem to confirm the notion that if decisions have to be made fast, emotional processes and aspects dominate, while rational processes are more time consuming and may result in a delayed decision. Finally, some limitations of current science and computational modeling will be discussed, hinting at a future development of science, where consciousness and free will may add to chance and necessity as explanation for what happens in the world.

scholarly journals Neuronal pathway and signal modulation for motor communication

2019 ◽  
pp. 106-113 ◽  
Author(s):  
Parth Chholak ◽  
Alexander N. Pisarchik ◽  
Semen A. Kurkin ◽  
Vladimir A. Maksimenko ◽  
Alexander E. Hramov
Keyword(s):  
Brain Activity ◽  
Dominant Role ◽  
Motor Command ◽  
Gamma Activity ◽  
Frequency Range ◽  
Inferior Parietal Cortex ◽  
Left And Right ◽  
Gamma Frequencies ◽  
Phase Amplitude ◽  
The Brain

The knowledge of the mechanisms of motor imagery (MI) is very important for the development of braincomputer interfaces. Depending on neurophysiological cortical activity, MI can be divided into two categories: visual imagery (VI) and kinesthetic imagery (KI). Our magnetoencephalography (MEG) experiments with ten untrained subjects provided evidences that inhibitory control plays a dominant role in KI. We found that communication between inferior parietal cortex and frontal cortex is realised in the mu-frequency range. We also pinpointed three gamma frequencies to be used for motor command communication. The use of artificial intelligence allowed us to classify MI of left and right hands with maximal classification accuracy using the brain activity encoded in the identified gamma frequencies which were then proposed to be used for communication of specifics. Mu-activity was identified as the carrier of gamma-activity between these areas by means of phase-amplitude coupling similar to the modern day radio wave transmission.

scholarly journals Peculiarities of organization of bioelectric brain activity in subclinical stage of epilepsy

2017 ◽  
Vol 25 (3) ◽  
pp. 399-403
Author(s):  
V. V. Sychev ◽  
V. N. Sychev ◽  
N. V. Shatrova
Keyword(s):  
Fourier Analysis ◽  
Right Hemisphere ◽  
Brain Activity ◽  
Epileptiform Activity ◽  
Clinical Manifestations ◽  
Bioelectric Activity ◽  
Left And Right ◽  
Electroencephalogram Eeg ◽  
The Brain

According to some authors, changes in the electroencephalogram (EEG) in the absence of clinical paroxysmal manifestations should be considered as subclinical epileptic manifestations. Verification of this hypothesis on the basis of the auto-spectral Fourier analysis of the EEG was the purpose of this work. Were examined in 27 women, mean age of 35.4±2.48 years, right-handed, without paroxysmal clinical and EEG manifestations (first group) and 25 women, mean age of 36.2±2.17 years, right-handed, without paroxysmal clinical manifestations, but with epileptiform activity on EEG (second group). In the second group were registered the increase in faverage of the brain EEG (p<0.001), while was increased faverage both of the left and right hemisphere (p<0.01). Zonal peculiarities of bioelectric activity of a brain of the second group surveyed was a significant increase in faverage EEG in all investigated leads (p<0.01), resulting in total liquidation of zonal differences (p>0.05). The results of the analysis allowed to conclude that the registration of the EEG epileptiform paroxysmal phenomena without clinical manifestations should be considered as a subclinical stage of epilepsy.

scholarly journals TRANSDISCIPLINARY APPROACH TO SPEECH THERAPY WITH CHILDREN WITH ALALIA

2020 ◽  
Vol 3 (8) ◽  
pp. 238-241
Author(s):  
Karimova Shoira Tursunovna
Keyword(s):  
Alpha Rhythm ◽  
Speech Therapy ◽  
Physiological Activity ◽  
Brain Structures ◽  
Speech Disorders ◽  
Time Interval ◽  
Transdisciplinary Approach ◽  
Correction Program ◽  
The Brain ◽  
Neuropsychological Methods

The article discloses the practical side of the transdisciplinary approach in speech therapy work and rehabilitation of children with alalia. In diagnosing speech disorders, the author believes that the behavior of children with alalia is closely related to the physiological activity of the brain, that diagnosis of speech disorders based on EEG and neuropsychological methods, as well as knowledge of the insufficiency of individual brain structures, which is supported by data from electroencephalographic research, are important for speech therapists in complex rehabilitation. Binaural therapy (individual alpha balance correction program) was used for children after EEG diagnosis of their dominant alpha rhythm, which matched their dominant rhythm in the selected time interval.

Word Learning in 6-Month-Olds: Fast Encoding–Weak Retention

2011 ◽  
Vol 23 (11) ◽  
pp. 3228-3240 ◽  
Author(s):  
Manuela Friedrich ◽  
Angela D. Friederici
Keyword(s):  
Semantic Memory ◽  
Word Learning ◽  
Declarative Memory ◽  
Brain Activity ◽  
Brain Structures ◽  
Memory Formation ◽  
Fast Encoding ◽  
Frequent Exposure ◽  
The Brain ◽  
Lexical Mapping

There has been general consensus that initial word learning during early infancy is a slow and time-consuming process that requires very frequent exposure, whereas later in development, infants are able to quickly learn a novel word for a novel meaning. From the perspective of memory maturation, this shift in behavioral development might represent a shift from slow procedural to fast declarative memory formation. Alternatively, it might be caused by the maturation of specific brain structures within the declarative memory system that may support lexical mapping from the very first. Here, we used the neurophysiological method of ERPs to watch the brain activity of 6-month-old infants, when repeatedly presented with object–word pairs in a cross-modal learning paradigm. We report first evidence that infants as young as 6 months are able to associate objects and words after only very few exposures. A memory test 1 day later showed that infants did not fully forget this newly acquired knowledge, although the ERP effects indicated it to be less stable than immediately after encoding. The combined results suggest that already at 6 months the encoding process of word learning is based on fast declarative memory formation, but limitations in the consolidation of declarative memory diminish the long lasting effect in lexical-semantic memory at that age.

scholarly journals A Comprehensive Review on Brain-Computer Interface Controlled Movements

2019 ◽  
Vol 5 (6) ◽  
pp. 3
Author(s):  
Kulsheet Kaur Virdi ◽  
Satish Pawar
Keyword(s):  
Brain Activity ◽  
Brain Computer Interface ◽  
Low Cost ◽  
Neuromuscular Disorders ◽  
Research Work ◽  
Brain Structures ◽  
Computer Interface ◽  
Body Parts ◽  
Machine Interface ◽  
The Brain

A brain-computer interface (BCI), also referred to as a mind-machine interface (MMI) or a brain-machine interface (BMI), provides a non-muscular channel of communication between the human brain and a computer system. With the advancements in low-cost electronics and computer interface equipment, as well as the need to serve people suffering from disabilities of neuromuscular disorders, a new field of research has emerged by understanding different functions of the brain. The electroencephalogram (EEG) is an electrical activity generated by brain structures and recorded from the scalp surface through electrodes. Researchers primarily rely on EEG to characterize the brain activity, because it can be recorded noninvasively by using portable equipment. The EEG or the brain activity can be used in real time to control external devices via a complete BCI system. For these applications there is need of such machine learning application which can be efficiently applied on these EEG signals. The aim of this research is review different research work in the field of brain computer interface related to body parts movements.

scholarly journals Review of Computational Methods on Brain Symmetric and Asymmetric Analysis from Neuroimaging Techniques

2016 ◽  
Author(s):  
P. Kalavathi ◽  
K. Senthamilselvi ◽  
V. B. Surya Prasath
Keyword(s):  
Right Hemisphere ◽  
Sagittal Plane ◽  
Correct Diagnosis ◽  
Brain Structures ◽  
Diagnostic Tools ◽  
Computational Techniques ◽  
Brain Images ◽  
Left And Right ◽  
The Brain ◽  
Neuroimaging Techniques

Brain is the most complex organ in the human body and it is divided into two hemispheres - left and right hemispheres. Left hemisphere is responsible for control of right side of our body whereas right hemisphere is responsible for control of left side of our body. Brain image segmentation from different neuroimaging modalities is one of the important parts in clinical diagnostic tools. Neuroimaging based digital imagery generally contain noise, inhomogeneity, aliasing artifacts, and orientational deviations. Therefore, accurate segmentation of brain images is a very difficult task. However, the development of accurate segmentation of brain images is very important and crucial for a correct diagnosis of any brain related diseases. One of the fundamental segmentation tasks is to identify and segment inter-hemispheric fissure/mid-sagittal plane, which separate the two hemispheres of the brain. Moreover, the symmetric/asymmetric analyses of left and right hemispheres of brain structures are important for radiologists to analyze diseases such as Alzheimer's, Autism, Schizophrenia, Lesions and Epilepsy. Therefore, in this paper we have analyzed the existing computational techniques used to find brain symmetric/asymmetric analysis in various neuroimaging techniques (MRI/CT/PET/SPECT), which are utilized for detecting various brain related disorders.

scholarly journals COMPLEX DIAGNOSTICS OF GIFTED CHILDREN OF PRESCHOOL AGE

2019 ◽  
Vol 11 (1) ◽  
pp. 40-47
Author(s):  
Lydia Konstantinovna Mazunova ◽  
Marat Irecovich Gubaidullin ◽  
Lilia Rashitovna Khalikova
Keyword(s):  
Quantitative Data ◽  
Brain Activity ◽  
Total Sample ◽  
Speech Development ◽  
Preschool Age ◽  
Diagnostic Tools ◽  
Gifted Children ◽  
Empirical Methods ◽  
Successful Development ◽  
The Brain

The article describes a set of diagnostic tools to identify the natural potential of a gifted preschooler, it presents the results of diagnosing children and their parents using these tools, as well as their interpretation. The relevance of the formation of a comprehensive diagnosis of giftedness of preschool children is determined by the task of promoting preservation and development of child giftedness, the national gene pool of gifted people in Russia. The novelty of the considered approach to solving the problem of diagnosing children’s giftedness lies in the use of an original set of techniques for determining the profile of the dominant hemispheres of the brain, a psychotype and natural inclinations of the child. The aim of the study is to find an answer to the question concerning the potential of giftedness with which a person is born and the percentage of children endowed with it. Among the research methods employed were such empirical methods as observation and testing with the help of a set of questionnaires and tests, as well as a statistical method for the initial collection and primary processing of quantitative data on natural inclinations, psychotypes, dominant profiles of hemispheric brain activity. The following diagnostic tools were applied: A. I. Savenkov’s questionnaire “Palette of interests” - to determine the natural inclinations of preschoolers,” Psychogeometric test of S. Dellinger (in the adaptation of G. I. Kolesnikova) - to determine a psychotype and the technique of Carla Hannaford - to determine the dominant profile of hemispheric activity of the brain. Among the results obtained, the most significant conclusion is the possibility of identifying a diverse and rich palette of natural inclinations in each child, which will allow individualizing the content aspect of the program and serve as a basic condition for the successful development of natural inclinations of each child. In the total sample of children (1669 questionnaires) more than 82% demonstrated inclinations to 3-4 types of human activity. Also revealed are more poorly developed areas, such as the communicative sphere, which is associated with the lack of live interaction (communication) of the child with adults and peers, and humanitarian, requiring more attention to the speech development of the child. Thus, children of 4-7 years old of both sexes with a dominant profile were characterized by a weak interest in the communicative sphere, the most preferred area for girls was art, and for boys - mathematics and technology

scholarly journals Correspondence between resting state activity and brain gene expression

2015 ◽  
Author(s):  
Guang-Zhong Wang ◽  
T. Grant Belgard ◽  
Deng Mao ◽  
Leslie Chen ◽  
Stefano Berto ◽  
...  
Keyword(s):  
Gene Expression ◽  
Resting State ◽  
Brain Activity ◽  
Low Frequency ◽  
Population Level ◽  
Rna Seq ◽  
Brain Gene Expression ◽  
Functional Brain Activity ◽  
The Relationship ◽  
The Brain

The relationship between functional brain activity and gene expression has not been fully explored in the human brain. Here, we identify significant correlations between gene expression in the brain and functional activity by comparing fractional Amplitude of Low Frequency Fluctuations (fALFF) from two independent human fMRI resting state datasets to regional cortical gene expression from a newly generated RNA-seq dataset and two additional gene expression datasets to obtain robust and reproducible correlations. We find significantly more genes correlated with fALFF than expected by chance, and identify specific genes correlated with the imaging signals in multiple expression datasets in the default mode network. Together, these data support a population-level relationship between regional steady state brain gene expression and resting state brain activity.

scholarly journals The Role of Neurolinguistics for Language and Speech Disorders

2019 ◽  
Vol 6 (2) ◽  
pp. 147
Author(s):  
Gusdi Sastra ◽  
Mohamad Saiful Haq ◽  
Handoko Handoko
Keyword(s):  
Human Life ◽  
Speech Disorders ◽  
Brain Science ◽  
Language Capacity ◽  
Left And Right ◽  
Analytical Procedures ◽  
The Individual ◽  
The Brain

This paper explains the significance of neurolinguistics as one of interdisciplinary fields of linguistics encompassing the analytical procedures on individual speech disorders in producing and using language. The result of analysis is used for designing a model and strategy to improve their language capacity.  Neurolinguistics roadmap covers some previous researches done by Sastra et all since 2006. Those studies investigate language and speech disorders including thinking ailments, and answer the inherent question on neurolinguistics contribution for addressing the individual problems to express themselves. Those problems are caused by some disorders on the left and right hemispheres of the brain. Science wise, neurolinguistics will always develop because the language phenomena always happen in human life through thinking and speech.

Sign in / Sign up

Export Citation Format

Share Document