scholarly journals Handedness and the Brain: A Review of Brain-imaging Techniques

2007 ◽  
Vol 6 (2) ◽  
pp. 99-112 ◽  
Author(s):  
Takeshi HATTA
2018 ◽  
Vol 16 (2) ◽  
pp. 201-212
Author(s):  
Bożydar L.J. Kaczmarek ◽  
Katarzyna Markiewicz

The present paper argues that the development of a new methodology in studying the brain has resulted in a change of our views on the way it works, has seen the emergence of new ideas, and a considerable modification of traditionally accepted theories. The most significant are neuroplasticity, negative activity network (NAT), the nature of aphasic disorders, and the approach to the localization of brain functions. New brain imaging techniques have confirmed also the ability to change the neuronal circuits by mental force. Moreover, new techniques have brought about a rise in new methods for both the diagnosis and rehabilitation of individuals with various brain disorders. Most valuable in this respect has proved to be neurofeedback. We have concentrated on the most important contributions of Prof. Pąchalska in the implementation and development of these new ideas on brain functioning. We also emphasize the fact that her theoretical considerations are firmly based upon her extensive (forty years) work with brain damaged patients.


2008 ◽  
Vol 2008 ◽  
pp. 1-8 ◽  
Author(s):  
Serguei Y. Semenov ◽  
Douglas R. Corfield

There is a need for a medical imaging technology, that supplements current clinical brain imaging techniques, for the near-patient and mobile assessment of cerebral vascular disease. Microwave tomography (MWT) is a novel imaging modality that has this potential. The aim of the study was to assess the feasibility, and potential performance characteristics, of MWT for brain imaging with particular focus on stroke detection. The study was conducted using MWT computer simulations and 2D head model with stroke. A nonlinear Newton reconstruction approach was used. The MWT imaging of deep brain tissues presents a significant challenge, as the brain is an object of interest that is located inside a high dielectric contrast shield, comprising the skull and CSF. However, high performance, nonlinear MWT inversion methods produced biologically meaningful images of the brain including images of stroke. It is suggested that multifrequency MWT has the potential to significantly improve imaging results.


Author(s):  
Katarína Neomániová ◽  
Jakub Berčík ◽  
Elena Horská

In addition to advanced brain imaging techniques and growing interest in the study of consumer reactions with influence of marketing stimuli a new interdisciplinary study has developed on a borderland of neuroscience, economic and psychological studies – neuromarketing. Despite a certain form of insecurity whether the brain imaging technologies provide useful information for control of marketing, more and more marketers identify with their application in conventional market research. The main aim of this contribution is to clarify the influence of a selected advertising spot on the final emotional state of consumers by researching a brain activity of respondents and activity of somatic nervous system, specifically the face expressions. Cortical brain activity was detected by 16channel wireless electroencephalograph by Epoc and changes of mimic muscles were monitored by a biometric device the Facereader by Noldus. The subject of the research is the dissonance of the selected neuroscience techniques with influence of chosen advertising emotional appeals like fear, disgust and sadness. In the end of our contribution, the way of using the neuroscience technology and psychology for detection of consumer emotional involvement of consumers is explained.


2011 ◽  
Vol 4 (2) ◽  
Author(s):  
Manuel Martín-Loeches

AbstractThis article presents an overview of the contribution of brain imaging techniques to the study of human language by first reviewing previous historical approaches to the study of the relationships between language and the brain. A brief introduction to modern brain imaging techniques follows, thereafter describing several concrete examples of contributions of these techniques to better know the human language, as well as to vivid debates into the linguistic and the psycholinguistic disciplines. This overview finishes with a comment on the present and the future of studying language with brain imaging techniques. It is concluded that these techniques are playing an essential role in the understanding of human language.


2020 ◽  
Vol 246 (2) ◽  
pp. R33-R50 ◽  
Author(s):  
Pauline Campos ◽  
Jamie J Walker ◽  
Patrice Mollard

In most species, survival relies on the hypothalamic control of endocrine axes that regulate critical functions such as reproduction, growth, and metabolism. For decades, the complexity and inaccessibility of the hypothalamic–pituitary axis has prevented researchers from elucidating the relationship between the activity of endocrine hypothalamic neurons and pituitary hormone secretion. Indeed, the study of central control of endocrine function has been largely dominated by ‘traditional’ techniques that consist of studying in vitro or ex vivo isolated cell types without taking into account the complexity of regulatory mechanisms at the level of the brain, pituitary and periphery. Nowadays, by exploiting modern neuronal transfection and imaging techniques, it is possible to study hypothalamic neuron activity in situ, in real time, and in conscious animals. Deep-brain imaging of calcium activity can be performed through gradient-index lenses that are chronically implanted and offer a ‘window into the brain’ to image multiple neurons at single-cell resolution. With this review, we aim to highlight deep-brain imaging techniques that enable the study of neuroendocrine neurons in awake animals whilst maintaining the integrity of regulatory loops between the brain, pituitary and peripheral glands. Furthermore, to assist researchers in setting up these techniques, we discuss the equipment required and include a practical step-by-step guide to performing these deep-brain imaging studies.


2021 ◽  
Vol 2 ◽  
Author(s):  
Chen Song

Structure shapes function. Understanding what is structurally special about the brain that allows it to generate consciousness remains a fundamental scientific challenge. Recently, advances in brain imaging techniques have made it possible to measure the structure of human brain, from the morphology of neurons and neuronal connections to the gross anatomy of brain regions, in-vivo and non-invasively. Using advanced brain imaging techniques, it was discovered that the structural diversity between neurons and the topology of neuronal connections, as opposed to the sheer number of neurons or neuronal connections, are key to consciousness. When the structural diversity is high and the connections follow a modular topology, neurons will become functionally differentiable and functionally integrable with one another. The high levels of differentiation and integration, in turn, enable the brain to produce the richest conscious experiences from the smallest number of neurons and neuronal connections. Consequently, across individuals, those with a smaller brain volume but a higher structural diversity tend to have richer conscious experiences than those with a larger brain volume but a lower structural diversity. Moreover, within individuals, a reduction in neuronal connections, if accompanied by an increase in structural diversity, will result in richer conscious experiences, and vice versa. These findings suggest that having a larger number of neurons and neuronal connections is not necessarily beneficial for consciousness; in contrast, an optimal brain architecture for consciousness is one where the richest conscious experiences are generated from the smallest number of neurons and neuronal connections, at the minimal cost of biological material, physical space, and metabolic energy.


Author(s):  
Aaishwarya Sanjay Bajaj ◽  
Usha Chouhan

Background: This paper endeavors to identify an expedient approach for the detection of the brain tumor in MRI images. The detection of tumor is based on i) review of the machine learning approach for the identification of brain tumor and ii) review of a suitable approach for brain tumor detection. Discussion: This review focuses on different imaging techniques such as X-rays, PET, CT- Scan, and MRI. This survey identifies a different approach with better accuracy for tumor detection. This further includes the image processing method. In most applications, machine learning shows better performance than manual segmentation of the brain tumors from MRI images as it is a difficult and time-consuming task. For fast and better computational results, radiology used a different approach with MRI, CT-scan, X-ray, and PET. Furthermore, summarizing the literature, this paper also provides a critical evaluation of the surveyed literature which reveals new facets of research. Conclusion: The problem faced by the researchers during brain tumor detection techniques and machine learning applications for clinical settings have also been discussed.


Author(s):  
Shoaib Amin Banday ◽  
Mohammad Khalid Pandit

Introduction: Brain tumor is among the major causes of morbidity and mortality rates worldwide. According to National Brain Tumor Foundation (NBTS), the death rate has nearly increased by as much as 300% over last couple of decades. Tumors can be categorized as benign (non-cancerous) and malignant (cancerous). The type of the brain tumor significantly depends on various factors like the site of its occurrence, its shape, the age of the subject etc. On the other hand, Computer Aided Detection (CAD) has been improving significantly in recent times. The concept, design and implementation of these systems ascend from fairly simple ones to computationally intense ones. For efficient and effective diagnosis and treatment plans in brain tumor studies, it is imperative that an abnormality is detected at an early stage as it provides a little more time for medical professionals to respond. The early detection of diseases has predominantly been possible because of medical imaging techniques developed from past many decades like CT, MRI, PET, SPECT, FMRI etc. The detection of brain tumors however, has always been a challenging task because of the complex structure of the brain, diverse tumor sizes and locations in the brain. Method: This paper proposes an algorithm that can detect the brain tumors in the presence of the Radio-Frequency (RF) inhomoginiety. The algorithm utilizes the Mid Sagittal Plane as a landmark point across which the asymmetry between the two brain hemispheres is estimated using various intensity and texture based parameters. Result: The results show the efficacy of the proposed method for the detection of the brain tumors with an acceptable detection rate. Conclusion: In this paper, we have calculated three textural features from the two hemispheres of the brain viz: Contrast (CON), Entropy (ENT) and Homogeneity (HOM) and three parameters viz: Root Mean Square Error (RMSE), Correlation Co-efficient (CC), and Integral of Absolute Difference (IAD) from the intensity distribution profiles of the two brain hemispheres to predict any presence of the pathology. First a Mid Sagittal Plane (MSP) is obtained on the Magnetic Resonance Images that virtually divides brain into two bilaterally symmetric hemispheres. The block wise texture asymmetry is estimated for these hemispheres using the above 6 parameters.


Biosensors ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 255
Author(s):  
Ziyi Luo ◽  
Hao Xu ◽  
Liwei Liu ◽  
Tymish Y. Ohulchanskyy ◽  
Junle Qu

Alzheimer’s disease (AD) is a multifactorial, irreversible, and incurable neurodegenerative disease. The main pathological feature of AD is the deposition of misfolded β-amyloid protein (Aβ) plaques in the brain. The abnormal accumulation of Aβ plaques leads to the loss of some neuron functions, further causing the neuron entanglement and the corresponding functional damage, which has a great impact on memory and cognitive functions. Hence, studying the accumulation mechanism of Aβ in the brain and its effect on other tissues is of great significance for the early diagnosis of AD. The current clinical studies of Aβ accumulation mainly rely on medical imaging techniques, which have some deficiencies in sensitivity and specificity. Optical imaging has recently become a research hotspot in the medical field and clinical applications, manifesting noninvasiveness, high sensitivity, absence of ionizing radiation, high contrast, and spatial resolution. Moreover, it is now emerging as a promising tool for the diagnosis and study of Aβ buildup. This review focuses on the application of the optical imaging technique for the determination of Aβ plaques in AD research. In addition, recent advances and key operational applications are discussed.


Sign in / Sign up

Export Citation Format

Share Document