scholarly journals Microwave Tomography for Brain Imaging: Feasibility Assessment for Stroke Detection

2008 ◽  
Vol 2008 ◽  
pp. 1-8 ◽  
Author(s):  
Serguei Y. Semenov ◽  
Douglas R. Corfield
Keyword(s):  
Brain Imaging ◽  
High Performance ◽  
Imaging Modality ◽  
Imaging Techniques ◽  
Head Model ◽  
Microwave Tomography ◽  
Feasibility Assessment ◽  
Imaging Results ◽  
High Dielectric ◽  
The Brain

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.

CURRENT AND TRADITIONAL VIEWS ON THE BRAIN WORKS

2018 ◽  
Vol 16 (2) ◽  
pp. 201-212
Author(s):  
Bożydar L.J. Kaczmarek ◽  
Katarzyna Markiewicz
Keyword(s):  
Brain Imaging ◽  
Imaging Techniques ◽  
Brain Disorders ◽  
New Techniques ◽  
Brain Functioning ◽  
Brain Functions ◽  
New Methods ◽  
New Ideas ◽  
Theoretical Considerations ◽  
The Brain

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.

scholarly journals Evidence for Bias of Genetic Ancestry in Resting State Functional MRI

2018 ◽  
Author(s):  
Andre Altmann ◽  
Janaina Mourao-Miranda
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
High Performance ◽  
Imaging Modality ◽  
Genetic Ancestry ◽  
Connectivity Pattern ◽  
Functional Magnetic Resonance ◽  
Performance Area ◽  
The Brain ◽  
Very High

ABSTRACTResting state functional magnetic resonance imaging (rs-fMRI) is a popular imaging modality for mapping the functional connectivity of the brain. Rs-fMRI is, just like other neuroimaging modalities, subject to a series of technical and subject level biases that change the inferred connectivity pattern. In this work we predicted genetic ancestry from rs-fMRI connectivity data at very high performance (area under the ROC curve of 0.93). Thereby, we demonstrated that genetic ancestry is encoded in the functional connectivity pattern of the brain at rest. Consequently, genetic ancestry constitutes a bias that should be accounted for in the analysis of rs-fMRI data.

scholarly journals BrainIAK: The Brain Imaging Analysis Kit

2020 ◽  
Author(s):  
Manoj Kumar ◽  
Michael Anderson ◽  
James Antony ◽  
Christopher Baldassano ◽  
Paula Pacheco Brooks ◽  
...  
Keyword(s):  
Brain Imaging ◽  
High Performance ◽  
Markov Models ◽  
Real Data ◽  
Matrix Analysis ◽  
Imaging Analysis ◽  
Neural Basis ◽  
Noise Characteristics ◽  
Fmri Analysis ◽  
The Brain

Functional magnetic resonance imaging (fMRI) offers a rich source of data for studying the neural basis of cognition. Here, we describe the Brain Imaging Analysis Kit (BrainIAK), an open-source, free Python package that provides computationally-optimized solutions to key problems in advanced fMRI analysis. A variety of techniques are presently included in BrainIAK: intersubject correlation (ISC) and intersubject functional connectivity (ISFC), functional alignment via the shared response model (SRM), full correlation matrix analysis (FCMA), a Bayesian version of representational similarity analysis (BRSA), event segmentation using hidden Markov models, topographic factor analysis (TFA), inverted encoding models (IEM), an fMRI data simulator that uses noise characteristics from real data (fmrisim), and some emerging methods. These techniques have been optimized to leverage the efficiencies of high performance compute (HPC) clusters, and the same code can be seamlessly transferred from a laptop to a cluster. For each of the aforementioned techniques, we describe the data analysis problem that the technique is meant to solve, and how it solves that problem; we also include an example Jupyter notebook for each technique and an annotated bibliography of papers that have used and/or described that technique. In addition to the sections describing various analysis techniques in BrainIAK, we have included sections describing the future applications of BrainIAK to real-time fMRI, tutorials that we have developed and shared online to facilitate learning the techniques in BrainIAK, computational innovations in BrainIAK, and how to contribute to BrainIAK. We hope that this manuscript helps readers to understand how BrainIAK might be useful in their research.

scholarly journals Dissonance of Selected Neuroscience Techniques at Detection of Emotions in Advertising Spots

2018 ◽  
Vol 66 (4) ◽  
pp. 969-977
Author(s):  
Katarína Neomániová ◽  
Jakub Berčík ◽  
Elena Horská
Keyword(s):  
Brain Imaging ◽  
Imaging Techniques ◽  
Brain Activity ◽  
Emotional Involvement ◽  
Emotional Appeals ◽  
The Face ◽  
The Subject ◽  
Somatic Nervous System ◽  
Interdisciplinary Study ◽  
The Brain

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.

scholarly journals Brain imaging before and after COVID-19 in UK Biobank

2021 ◽  
Author(s):  
Gwenaëlle Douaud ◽  
Soojin Lee ◽  
Fidel Alfaro-Almagro ◽  
Christoph Arthofer ◽  
Chaoyue Wang ◽  
...  
Keyword(s):  
Brain Imaging ◽  
Grey Matter ◽  
Cingulate Cortex ◽  
Anterior Cingulate ◽  
Uk Biobank ◽  
Hospitalised Patients ◽  
Imaging Results ◽  
Before And After ◽  
The Impact ◽  
The Brain

There is strong evidence for brain-related pathologies in COVID-19, some of which could be a consequence of viral neurotropism. The vast majority of brain imaging studies so far have focused on qualitative, gross pathology of moderate to severe cases, often carried out on hospitalised patients. It remains unknown however whether the impact of COVID-19 can be detected in milder cases, in a quantitative and automated manner, and whether this can reveal a possible mechanism for the spread of the disease. UK Biobank scanned over 40,000 participants before the start of the COVID-19 pandemic, making it possible to invite back in 2021 hundreds of previously-imaged participants for a second imaging visit. Here, we studied the effects of the disease in the brain using multimodal data from 782 participants from the UK Biobank COVID-19 re-imaging study, with 394 participants having tested positive for SARS- CoV-2 infection between their two scans. We used structural and functional brain scans from before and after infection, to compare longitudinal brain changes between these 394 COVID- 19 patients and 388 controls who were matched for age, sex, ethnicity and interval between scans. We identified significant effects of COVID-19 in the brain with a loss of grey matter in the left parahippocampal gyrus, the left lateral orbitofrontal cortex and the left insula. When looking over the entire cortical surface, these results extended to the anterior cingulate cortex, supramarginal gyrus and temporal pole. We further compared COVID-19 patients who had been hospitalised (n=15) with those who had not (n=379), and while results were not significant, we found comparatively similar findings to the COVID-19 vs control group comparison, with, in addition, a greater loss of grey matter in the cingulate cortex, central nucleus of the amygdala and hippocampal cornu ammonis (all |Z|>3). Our findings thus consistently relate to loss of grey matter in limbic cortical areas directly linked to the primary olfactory and gustatory system. Unlike in post hoc disease studies, the availability of pre- infection imaging data helps avoid the danger of pre-existing risk factors or clinical conditions being mis-interpreted as disease effects. Since a possible entry point of the virus to the central nervous system might be via the olfactory mucosa and the olfactory bulb, these brain imaging results might be the in vivo hallmark of the spread of the disease (or the virus itself) via olfactory and gustatory pathways.

The Contribution of Brain Imaging to the Study of Human Language

2011 ◽  
Vol 4 (2) ◽  
Author(s):  
Manuel Martín-Loeches
Keyword(s):  
Brain Imaging ◽  
Essential Role ◽  
Imaging Techniques ◽  
Human Language ◽  
The Future ◽  
The Brain

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.

scholarly journals Diving into the brain: deep-brain imaging techniques in conscious animals

2020 ◽  
Vol 246 (2) ◽  
pp. R33-R50 ◽  
Author(s):  
Pauline Campos ◽  
Jamie J Walker ◽  
Patrice Mollard
Keyword(s):  
Brain Imaging ◽  
Ex Vivo ◽  
Imaging Techniques ◽  
Hormone Secretion ◽  
Endocrine Function ◽  
Neuron Activity ◽  
Pituitary Hormone ◽  
Conscious Animals ◽  
The Brain ◽  
Deep Brain

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.

Conceptual, methodological, and statistical challenges in brain imaging studies of developmentally based psychopathologies

2003 ◽  
Vol 15 (3) ◽  
pp. 811-832 ◽  
Author(s):  
BRADLEY S. PETERSON
Keyword(s):  
Brain Imaging ◽  
Functional Imaging ◽  
Developmental Disorders ◽  
Imaging Modality ◽  
Effective Connectivity ◽  
Imaging Data ◽  
Scaling Effects ◽  
Imaging Studies ◽  
Brain Functions ◽  
The Brain

Brain imaging studies in developmentally based psychopathologies most often use magnetic resonance imaging (MRI) to study regional volumes, task-related activity, neurometabolite concentrations, or the paths of fiber tracts within the brain. Methodological challenges for the use of MRI in studying these disorders include understanding the ultrastructural correlates of brain structure and function that are below the limits of resolution of this imaging modality and developing better methods for approximating the anatomical boundaries of the cytoarchitectonic units that are defined by those ultrastructural characteristics. Conceptual challenges include distinguishing findings that represent pathophysiologically central causes from compensatory and epiphenomenal effects, a difficulty that stems directly from the inherently correlational nature of imaging data. The promise of functional imaging studies must capitalize on the specificity of the cognitive and behavioral probes that are used to illuminate core features of the pathophysiology of developmental disorders, while recognizing the assumptions and limitations of the subtraction paradigms that are used to isolate the brain functions of interest. Statistical challenges include incorporating adequate statistical models for scaling effects within the brain, as well as modeling important demographic correlates that contribute to the substantial interindividual variability inherent in most imaging data. Statistical analyses need to consider the substantial intercorrelation of measures across the brain and the importance of correcting for multiple statistical comparisons, as well as the need for improved methods for brain warping and for assessing effective connectivity in functional imaging studies.

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