Functional Imaging and Related Techniques: An Introduction for Rehabilitation Researchers
Crosson, Bruce; Ford, Anastasia; McGregor, Keith M.; Meinzer, Marcus; Cheshkov, Sergey; Li, Xiufeng; Walker-Batson, Delaina; Briggs, Richard W.
2010-01-01
Functional neuroimaging and related neuroimaging techniques are becoming important tools for rehabilitation research. Functional neuroimaging techniques can be used to determine the effects of brain injury or disease on brain systems related to cognition and behavior and to determine how rehabilitation changes brain systems. These techniques include: functional magnetic resonance imaging (fMRI), positron emission tomography (PET), electroencephalography (EEG), magnetoencephalography (MEG), near infrared spectroscopy (NIRS), and transcranial magnetic stimulation (TMS). Related diffusion weighted magnetic resonance imaging techniques (DWI), including diffusion tensor imaging (DTI) and high angular resolution diffusion imaging (HARDI), can quantify white matter integrity. With the proliferation of these imaging techniques in rehabilitation research, it is critical that rehabilitation researchers, as well as consumers of rehabilitation research, become familiar with neuroimaging techniques, what they can offer, and their strengths and weaknesses The purpose to this review is to provide such an introduction to these neuroimaging techniques. PMID:20593321
Arbizu, J; Luquin, M R; Abella, J; de la Fuente-Fernández, R; Fernandez-Torrón, R; García-Solís, D; Garrastachu, P; Jiménez-Hoyuela, J M; Llaneza, M; Lomeña, F; Lorenzo-Bosquet, C; Martí, M J; Martinez-Castrillo, J C; Mir, P; Mitjavila, M; Ruiz-Martínez, J; Vela, L
2014-01-01
Functional Neuroimaging has been traditionally used in research for patients with different Parkinsonian syndromes. However, the emergence of commercial radiotracers together with the availability of single photon emission computed tomography (SPECT) and, more recently, positron emission tomography (PET) have made them available for clinical practice. Particularly, the development of clinical evidence achieved by functional neuroimaging techniques over the past two decades have motivated a progressive inclusion of several biomarkers in the clinical diagnostic criteria for neurodegenerative diseases that occur with Parkinsonism. However, the wide range of radiotracers designed to assess the involvement of different pathways in the neurodegenerative process underlying Parkinsonian syndromes (dopaminergic nigrostriatal pathway integrity, basal ganglia and cortical neuronal activity, myocardial sympathetic innervation), and the different neuroimaging techniques currently available (scintigraphy, SPECT and PET), have generated some controversy concerning the best neuroimaging test that should be indicated for the differential diagnosis of Parkinsonism. In this article, a panel of nuclear medicine and neurology experts has evaluated the functional neuroimaging techniques emphazising practical considerations related to the diagnosis of patients with uncertain origin parkinsonism and the assessment Parkinson's disease progression. Copyright © 2014 Elsevier España, S.L. and SEMNIM. All rights reserved.
Galvao-de Almeida, Amanda; Araujo Filho, Gerardo Maria de; Berberian, Arthur de Almeida; Trezsniak, Clarissa; Nery-Fernandes, Fabiana; Araujo Neto, Cesar Augusto; Jackowski, Andrea Parolin; Miranda-Scippa, Angela; Oliveira, Irismar Reis de
2013-01-01
Functional neuroimaging techniques represent fundamental tools in the context of translational research integrating neurobiology, psychopathology, neuropsychology, and therapeutics. In addition, cognitive-behavioral therapy (CBT) has proven its efficacy in the treatment of anxiety disorders and may be useful in phobias. The literature has shown that feelings and behaviors are mediated by specific brain circuits, and changes in patterns of interaction should be associated with cerebral alterations. Based on these concepts, a systematic review was conducted aiming to evaluate the impact of CBT on phobic disorders measured by functional neuroimaging techniques. A systematic review of the literature was conducted including studies published between January 1980 and April 2012. Studies written in English, Spanish or Portuguese evaluating changes in the pattern of functional neuroimaging before and after CBT in patients with phobic disorders were included. The initial search strategy retrieved 45 studies. Six of these studies met all inclusion criteria. Significant deactivations in the amygdala, insula, thalamus and hippocampus, as well as activation of the medial orbitofrontal cortex, were observed after CBT in phobic patients when compared with controls. In spite of their technical limitations, neuroimaging techniques provide neurobiological support for the efficacy of CBT in the treatment of phobic disorders. Further studies are needed to confirm this conclusion.
Furukawa, Katsutoshi; Ishiki, Aiko; Tomita, Naoki; Onaka, Yuta; Saito, Haruka; Nakamichi, Tomoko; Hara, Kazunari; Kusano, Yusuke; Ebara, Masamune; Arata, Yuki; Sakota, Miku; Miyazawa, Isabelle; Totsune, Tomoko; Okinaga, Shoji; Okamura, Nobuyuki; Kudo, Yukitsuka; Arai, Hiroyuki
2016-09-01
It is well known that the brain is one of the organs particularly affected by aging in terms of function, relative to the gastrointestinal tract and liver, which exhibit less functional decline. There is also a wide range of age-related neurological disorders such as stroke, Alzheimer's disease, and Parkinson's disease. Therefore, it is very important to understand the relationship between functional age-related change and neurological dysfunction. Neuroimaging techniques including magnetic resonance imaging and positron emission tomography have been significantly improved over recent years. Many physicians and researchers have investigated various mechanisms of age-related cerebral change and associated neurological disorders using neuroimaging techniques. In this special issue of Ageing Research Reviews, we focus on cerebral- and neuro-imaging, which are a range of tools used to visualize structure, functions, and pathogenic molecules in the nervous system. In addition, we summarize several review articles about the history, present values, and future perspectives of neuroimaging modalities. Copyright © 2016 Elsevier B.V. All rights reserved.
Kelley, Daniel J; Johnson, Sterling C
2007-01-01
Background With rapid advances in functional imaging methods, human studies that feature functional neuroimaging techniques are increasing exponentially and have opened a vast arena of new possibilities for understanding brain function and improving the care of patients with cognitive disorders in the clinical setting. There is a growing need for medical centers to offer clinically relevant functional neuroimaging courses that emphasize the multifaceted and multidisciplinary nature of this field. In this paper, we describe the implementation of a functional neuroimaging course focusing on cognitive disorders that might serve as a model for other medical centers. We identify key components of an active learning course design that impact student learning gains in methods and issues pertaining to functional neuroimaging that deserve consideration when optimizing the medical neuroimaging curriculum. Methods Learning gains associated with the course were assessed using polychoric correlation analysis of responses to the SALG (Student Assessment of Learning Gains) instrument. Results Student gains in the functional neuroimaging of cognition as assessed by the SALG instrument were strongly associated with several aspects of the course design. Conclusion Our implementation of a multidisciplinary and active learning functional neuroimaging course produced positive learning outcomes. Inquiry-based learning activities and an online learning environment contributed positively to reported gains. This functional neuroimaging course design may serve as a useful model for other medical centers. PMID:17953758
Advanced Neuroimaging in Traumatic Brain Injury
Edlow, Brian L.; Wu, Ona
2013-01-01
Advances in structural and functional neuroimaging have occurred at a rapid pace over the past two decades. Novel techniques for measuring cerebral blood flow, metabolism, white matter connectivity, and neural network activation have great potential to improve the accuracy of diagnosis and prognosis for patients with traumatic brain injury (TBI), while also providing biomarkers to guide the development of new therapies. Several of these advanced imaging modalities are currently being implemented into clinical practice, whereas others require further development and validation. Ultimately, for advanced neuroimaging techniques to reach their full potential and improve clinical care for the many civilians and military personnel affected by TBI, it is critical for clinicians to understand the applications and methodological limitations of each technique. In this review, we examine recent advances in structural and functional neuroimaging and the potential applications of these techniques to the clinical care of patients with TBI. We also discuss pitfalls and confounders that should be considered when interpreting data from each technique. Finally, given the vast amounts of advanced imaging data that will soon be available to clinicians, we discuss strategies for optimizing data integration, visualization and interpretation. PMID:23361483
Bigler, E D
1999-08-01
Contemporary neuorimaging techniques in child traumatic brain injury are reviewed, with an emphasis on computerized tomography (CT) and magnetic resonance (MR) imaging. A brief overview of MR spectroscopy (MRS), functional MR imaging (fMRI), single-photon emission computed tomography (SPECT), and magnetoencephalography (MEG) is also provided because these techniques will likely constitute important neuroimaging techniques of the future. Numerous figures are provided to illustrate the multifaceted manner in which traumatic deficits can be imaged and the role of neuroimaging information as it relates to TBI outcome.
[Recent progress of neuroimaging studies on sleeping brain].
Sasaki, Yuka
2012-06-01
Although sleep is a familiar phenomenon, its functions are yet to be elucidated. Understanding these functions of sleep is an important focus area in neuroscience. Electroencephalography (EEG) has been the predominantly used method in human sleep research but does not provide detailed spatial information about brain activation during sleep. To supplement the spatial information provided by this method, researchers have started using a combination of EEG and various advanced neuroimaging techniques that have been recently developed, including positron emission tomography (PET) and magnetic resonance imaging (MRI). In this paper, we will review the recent progress in sleep studies, especially studies that have used such advanced neuroimaging techniques. First, we will briefly introduce several neuroimaging techniques available for use in sleep studies. Next, we will review the spatiotemporal brain activation patterns during non-rapid eye movement (NREM) and rapid eye movement (REM) sleep, the dynamics of functional connectivity during sleep, and the consolidation of learning and memory during sleep; studies on the neural correlates of dreams, which have not yet been identified, will also be discussed. Lastly, possible directions for future research in this area will be discussed.
Brain imaging and cognitive dysfunctions in Huntington's disease
Montoya, Alonso; Price, Bruce H.; Menear, Matthew; Lepage, Martin
2006-01-01
Recent decades have seen tremendous growth in our understanding of the cognitive dysfunctions observed in Huntington's disease (HD). Advances in neuroimaging have contributed greatly to this growth. We reviewed the role that structural and functional neuroimaging techniques have played in elucidating the cerebral bases of the cognitive deficits associated with HD. We conducted a computer-based search using PubMed and PsycINFO databases to retrieve studies of patients with HD published between 1965 and December 2004 that reported measures on cognitive tasks and used neuroimaging techniques. Structural neuroimaging has provided important evidence of morphological brain changes in HD. Striatal and cortical atrophy are the most common findings, and they correlate with cognitive deficits in attention, working memory and executive functions. Functional studies have also demonstrated correlations between striatal dysfunction and cognitive performance. Striatal hypoperfusion and decreased glucose utilization correlate with executive dysfunction. Hypometabolism also occurs throughout the cerebral cortex and correlates with performance on recognition memory, language and perceptual tests. Measures of presynaptic and postsynaptic dopamine biochemistry have also correlated with measurements of episodic memory, speed of processing and executive functioning. Aided by the results of numerous neuroimaging studies, it is becoming increasingly clear that cognitive deficits in HD involve abnormal connectivity between the basal ganglia and cortical areas. In the future, neuroimaging techniques may shed the most light on the pathophysiology of HD by defining neurodegenerative disease phenotypes as a valuable tool for knowing when patients become “symptomatic,” having been in a gene-positive presymptomatic state, and as a biomarker in following the disease, thereby providing a prospect for improved patient care. PMID:16496032
Auditory neuroimaging with fMRI and PET.
Talavage, Thomas M; Gonzalez-Castillo, Javier; Scott, Sophie K
2014-01-01
For much of the past 30 years, investigations of auditory perception and language have been enhanced or even driven by the use of functional neuroimaging techniques that specialize in localization of central responses. Beginning with investigations using positron emission tomography (PET) and gradually shifting primarily to usage of functional magnetic resonance imaging (fMRI), auditory neuroimaging has greatly advanced our understanding of the organization and response properties of brain regions critical to the perception of and communication with the acoustic world in which we live. As the complexity of the questions being addressed has increased, the techniques, experiments and analyses applied have also become more nuanced and specialized. A brief review of the history of these investigations sets the stage for an overview and analysis of how these neuroimaging modalities are becoming ever more effective tools for understanding the auditory brain. We conclude with a brief discussion of open methodological issues as well as potential clinical applications for auditory neuroimaging. This article is part of a Special Issue entitled Human Auditory Neuroimaging. Copyright © 2013 Elsevier B.V. All rights reserved.
A Review on the Bioinformatics Tools for Neuroimaging
MAN, Mei Yen; ONG, Mei Sin; Mohamad, Mohd Saberi; DERIS, Safaai; SULONG, Ghazali; YUNUS, Jasmy; CHE HARUN, Fauzan Khairi
2015-01-01
Neuroimaging is a new technique used to create images of the structure and function of the nervous system in the human brain. Currently, it is crucial in scientific fields. Neuroimaging data are becoming of more interest among the circle of neuroimaging experts. Therefore, it is necessary to develop a large amount of neuroimaging tools. This paper gives an overview of the tools that have been used to image the structure and function of the nervous system. This information can help developers, experts, and users gain insight and a better understanding of the neuroimaging tools available, enabling better decision making in choosing tools of particular research interest. Sources, links, and descriptions of the application of each tool are provided in this paper as well. Lastly, this paper presents the language implemented, system requirements, strengths, and weaknesses of the tools that have been widely used to image the structure and function of the nervous system. PMID:27006633
Gosseries, Olivia; Pistoia, Francesca; Charland-Verville, Vanessa; Carolei, Antonio; Sacco, Simona; Laureys, Steven
2016-01-01
Non-communicative brain damaged patients raise important clinical and scientific issues. Here, we review three major pathological disorders of consciousness: coma, the unresponsive wakefulness syndrome and the minimally conscious state. A number of clinical studies highlight the difficulty in making a correct diagnosis in patients with disorders of consciousness based only on behavioral examinations. The increasing use of neuroimaging techniques allows improving clinical characterization of these patients. Recent neuroimaging studies using positron emission tomography, functional magnetic resonance imaging, electroencephalography and transcranial magnetic stimulation can help assess diagnosis, prognosis, and therapeutic treatment. These techniques, using resting state, passive and active paradigms, also highlight possible dissociations between consciousness and responsiveness, and are facilitating a more accurate understanding of brain function in this challenging population. PMID:27347265
Auditory Neuroimaging with fMRI and PET
Talavage, Thomas M.; Gonzalez-Castillo, Javier; Scott, Sophie K.
2013-01-01
For much of the past 30 years, investigations of auditory perception and language have been enhanced or even driven by the use of functional neuroimaging techniques that specialize in localization of central responses. Beginning with investigations using positron emission tomography (PET) and gradually shifting primarily to usage of functional magnetic resonance imaging (fMRI), auditory neuroimaging has greatly advanced our understanding of the organization and response properties of brain regions critical to the perception of and communication with the acoustic world in which we live. As the complexity of the questions being addressed has increased, the techniques, experiments and analyses applied have also become more nuanced and specialized. A brief review of the history of these investigations sets the stage for an overview and analysis of how these neuroimaging modalities are becoming ever more effective tools for understanding the auditory brain. We conclude with a brief discussion of open methodological issues as well as potential clinical applications for auditory neuroimaging. PMID:24076424
Shafi, Mouhsin M.; Westover, M. Brandon; Fox, Michael D.; Pascual-Leone, Alvaro
2012-01-01
Much recent work in systems neuroscience has focused on how dynamic interactions between different cortical regions underlie complex brain functions such as motor coordination, language, and emotional regulation. Various studies using neuroimaging and neurophysiologic techniques have suggested that in many neuropsychiatric disorders, these dynamic brain networks are dysregulated. Here we review the utility of combined noninvasive brain stimulation and neuroimaging approaches towards greater understanding of dynamic brain networks in health and disease. Brain stimulation techniques, such as transcranial magnetic stimulation and transcranial direct current stimulation, use electromagnetic principles to noninvasively alter brain activity, and induce focal but also network effects beyond the stimulation site. When combined with brain imaging techniques such as functional MRI, PET and EEG, these brain stimulation techniques enable a causal assessment of the interaction between different network components, and their respective functional roles. The same techniques can also be applied to explore hypotheses regarding the changes in functional connectivity that occur during task performance and in various disease states such as stroke, depression and schizophrenia. Finally, in diseases characterized by pathologic alterations in either the excitability within a single region or in the activity of distributed networks, such techniques provide a potential mechanism to alter cortical network function and architectures in a beneficial manner. PMID:22429242
Fusing DTI and FMRI Data: A Survey of Methods and Applications
Zhu, Dajiang; Zhang, Tuo; Jiang, Xi; Hu, Xintao; Chen, Hanbo; Yang, Ning; Lv, Jinglei; Han, Junwei; Guo, Lei; Liu, Tianming
2014-01-01
The relationship between brain structure and function has been one of the centers of research in neuroimaging for decades. In recent years, diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) techniques have been widely available and popular in cognitive and clinical neurosciences for examining the brain’s white matter (WM) micro-structures and gray matter (GM) functions, respectively. Given the intrinsic integration of WM/GM and the complementary information embedded in DTI/fMRI data, it is natural and well-justified to combine these two neuroimaging modalities together to investigate brain structure and function and their relationships simultaneously. In the past decade, there have been remarkable achievements of DTI/fMRI fusion methods and applications in neuroimaging and human brain mapping community. This survey paper aims to review recent advancements on methodologies and applications in incorporating multimodal DTI and fMRI data, and offer our perspectives on future research directions. We envision that effective fusion of DTI/fMRI techniques will play increasingly important roles in neuroimaging and brain sciences in the years to come. PMID:24103849
Giacino, Joseph T; Hirsch, Joy; Schiff, Nicholas; Laureys, Steven
2006-12-01
To describe the theoretic framework, design, and potential clinical applications of functional neuroimaging protocols in patients with disorders of consciousness. Recent published literature and authors' own work. Studies using functional neuroimaging techniques to investigate cognitive processing in patients diagnosed with vegetative and minimally conscious state. Not applicable. Positron-emission tomography activation studies suggest that the vegetative state represents a global disconnection syndrome in which higher order association cortices are functionally disconnected from primary cortical areas. In contrast, patterns of activation in functional magnetic resonance imaging studies of patients in the minimally conscious state show preservation of large-scale cortical networks associated with language and visual processing. Novel applications of functional neuroimaging in patients with disorders of consciousness may aid in differential diagnosis, prognostic assessment and identification of pathophysiologic mechanisms. Improvements in patient characterization may, in turn, provide new opportunities for restoration of function through interventional neuromodulation.
Torta, D M; Legrain, V; Mouraux, A; Valentini, E
2017-04-01
Several studies have used neuroimaging techniques to investigate brain correlates of the attentional modulation of pain. Although these studies have advanced the knowledge in the field, important confounding factors such as imprecise theoretical definitions of attention, incomplete operationalization of the construct under exam, and limitations of techniques relying on measuring regional changes in cerebral blood flow have hampered the potential relevance of the conclusions. Here, we first provide an overview of the major theories of attention and of attention in the study of pain to bridge theory and experimental results. We conclude that load and motivational/affective theories are particularly relevant to study the attentional modulation of pain and should be carefully integrated in functional neuroimaging studies. Then, we summarize previous findings and discuss the possible neural correlates of the attentional modulation of pain. We discuss whether classical functional neuroimaging techniques are suitable to measure the effect of a fluctuating process like attention, and in which circumstances functional neuroimaging can be reliably used to measure the attentional modulation of pain. Finally, we argue that the analysis of brain networks and spontaneous oscillations may be a crucial future development in the study of attentional modulation of pain, and why the interplay between attention and pain, as examined so far, may rely on neural mechanisms shared with other sensory modalities. Copyright © 2017 Elsevier Ltd. All rights reserved.
Neural modeling and functional neuroimaging.
Horwitz, B; Sporns, O
1994-01-01
Two research areas that so far have had little interaction with one another are functional neuroimaging and computational neuroscience. The application of computational models and techniques to the inherently rich data sets generated by "standard" neurophysiological methods has proven useful for interpreting these data sets and for providing predictions and hypotheses for further experiments. We suggest that both theory- and data-driven computational modeling of neuronal systems can help to interpret data generated by functional neuroimaging methods, especially those used with human subjects. In this article, we point out four sets of questions, addressable by computational neuroscientists whose answere would be of value and interest to those who perform functional neuroimaging. The first set consist of determining the neurobiological substrate of the signals measured by functional neuroimaging. The second set concerns developing systems-level models of functional neuroimaging data. The third set of questions involves integrating functional neuroimaging data across modalities, with a particular emphasis on relating electromagnetic with hemodynamic data. The last set asks how one can relate systems-level models to those at the neuronal and neural ensemble levels. We feel that there are ample reasons to link functional neuroimaging and neural modeling, and that combining the results from the two disciplines will result in furthering our understanding of the central nervous system. © 1994 Wiley-Liss, Inc. This Article is a US Goverment work and, as such, is in the public domain in the United State of America. Copyright © 1994 Wiley-Liss, Inc.
Multimodal Neuroimaging: Basic Concepts and Classification of Neuropsychiatric Diseases.
Tulay, Emine Elif; Metin, Barış; Tarhan, Nevzat; Arıkan, Mehmet Kemal
2018-06-01
Neuroimaging techniques are widely used in neuroscience to visualize neural activity, to improve our understanding of brain mechanisms, and to identify biomarkers-especially for psychiatric diseases; however, each neuroimaging technique has several limitations. These limitations led to the development of multimodal neuroimaging (MN), which combines data obtained from multiple neuroimaging techniques, such as electroencephalography, functional magnetic resonance imaging, and yields more detailed information about brain dynamics. There are several types of MN, including visual inspection, data integration, and data fusion. This literature review aimed to provide a brief summary and basic information about MN techniques (data fusion approaches in particular) and classification approaches. Data fusion approaches are generally categorized as asymmetric and symmetric. The present review focused exclusively on studies based on symmetric data fusion methods (data-driven methods), such as independent component analysis and principal component analysis. Machine learning techniques have recently been introduced for use in identifying diseases and biomarkers of disease. The machine learning technique most widely used by neuroscientists is classification-especially support vector machine classification. Several studies differentiated patients with psychiatric diseases and healthy controls with using combined datasets. The common conclusion among these studies is that the prediction of diseases increases when combining data via MN techniques; however, there remain a few challenges associated with MN, such as sample size. Perhaps in the future N-way fusion can be used to combine multiple neuroimaging techniques or nonimaging predictors (eg, cognitive ability) to overcome the limitations of MN.
25 years of neuroimaging in amyotrophic lateral sclerosis.
Foerster, Bradley R; Welsh, Robert C; Feldman, Eva L
2013-09-01
Amyotrophic lateral sclerosis (ALS) is a fatal motor neuron disease for which a precise cause has not yet been identified. Standard CT or MRI evaluation does not demonstrate gross structural nervous system changes in ALS, so conventional neuroimaging techniques have provided little insight into the pathophysiology of this disease. Advanced neuroimaging techniques--such as structural MRI, diffusion tensor imaging and proton magnetic resonance spectroscopy--allow evaluation of alterations of the nervous system in ALS. These alterations include focal loss of grey and white matter and reductions in white matter tract integrity, as well as changes in neural networks and in the chemistry, metabolism and receptor distribution in the brain. Given their potential for investigation of both brain structure and function, advanced neuroimaging methods offer important opportunities to improve diagnosis, guide prognosis, and direct future treatment strategies in ALS. In this article, we review the contributions made by various advanced neuroimaging techniques to our understanding of the impact of ALS on different brain regions, and the potential role of such measures in biomarker development.
The Role of Functional Neuroimaging in Pre-Surgical Epilepsy Evaluation
Pittau, Francesca; Grouiller, Frédéric; Spinelli, Laurent; Seeck, Margitta; Michel, Christoph M.; Vulliemoz, Serge
2014-01-01
The prevalence of epilepsy is about 1% and one-third of cases do not respond to medical treatment. In an eligible subset of patients with drug-resistant epilepsy, surgical resection of the epileptogenic zone is the only treatment that can possibly cure the disease. Non-invasive techniques provide information for the localization of the epileptic focus in the majority of cases, whereas in others invasive procedures are required. In the last years, non-invasive neuroimaging techniques, such as simultaneous recording of functional magnetic resonance imaging and electroencephalogram (EEG-fMRI), positron emission tomography (PET), single photon emission computed tomography (SPECT), electric and magnetic source imaging (MSI, ESI), spectroscopy (MRS), have proved their usefulness in defining the epileptic focus. The combination of these functional techniques can yield complementary information and their concordance is crucial for guiding clinical decision, namely the planning of invasive EEG recordings or respective surgery. The aim of this review is to present these non-invasive neuroimaging techniques, their potential combination, and their role in the pre-surgical evaluation of patients with pharmaco-resistant epilepsy. PMID:24715886
Agbangla, Nounagnon F; Audiffren, Michel; Albinet, Cédric T
2017-09-01
The cognitive neuroscience of aging is a growing and stimulating research area. The development of neuroimaging techniques in the past two decades has considerably increased our understanding of the brain mechanisms that might underlie cognitive performance and resulting changes due to normal aging. Beside traditional metabolic neuroimaging techniques, such as Positron Emission Tomography and functional Magnetic Resonance Imaging, near infrared spectroscopy (NIRS), an optical imaging technique allowing to monitor real-time cerebral blood oxygenation, has gained recent interest in this field. The aim of the present review paper, after briefly presenting the NIRS technique, is to review and to summarize the recent results of neuroimaging studies using this technique in the field of cognitive aging. The reviewed literature shows that, despite low spatial resolution and cerebral depth penetration, this technique provides consistent findings on the reduced hemodynamic activity as a function of chronological age, mainly in the prefrontal cortex. Important moderators of brain hemodynamics, such as cognitive load, subjects' characteristics and experimental conditions, for which the NIRS technique is sensitive, are discussed. Strengths and weaknesses of functional NIRS in the field of cognitive aging are presented and finally, novel perspectives of research are proposed. Copyright © 2017 Elsevier B.V. All rights reserved.
Rooijackers, Hanne M M; Wiegers, Evita C; Tack, Cees J; van der Graaf, Marinette; de Galan, Bastiaan E
2016-02-01
Hypoglycemia is the most frequent complication of insulin therapy in patients with type 1 diabetes. Since the brain is reliant on circulating glucose as its main source of energy, hypoglycemia poses a threat for normal brain function. Paradoxically, although hypoglycemia commonly induces immediate decline in cognitive function, long-lasting changes in brain structure and cognitive function are uncommon in patients with type 1 diabetes. In fact, recurrent hypoglycemia initiates a process of habituation that suppresses hormonal responses to and impairs awareness of subsequent hypoglycemia, which has been attributed to adaptations in the brain. These observations sparked great scientific interest into the brain's handling of glucose during (recurrent) hypoglycemia. Various neuroimaging techniques have been employed to study brain (glucose) metabolism, including PET, fMRI, MRS and ASL. This review discusses what is currently known about cerebral metabolism during hypoglycemia, and how findings obtained by functional and metabolic neuroimaging techniques contributed to this knowledge.
[Pedophilia: contribution of neurology and neuroimaging techniques].
Fonteille, V; Cazala, F; Moulier, V; Stoléru, S
2012-12-01
Pedophilia is characterized by a persistent sexual interest of an adult for prepubescent children. The development of neuroimaging techniques such as functional Magnetic Resonance Imaging (fMRI) is starting to clarify the cerebral basis of disorders of sexual behavior such as pedophilia, which had been previously suggested by case studies. To review structural and functional neuroimaging studies of pedophilia. An exhaustive consultation of PubMed and Ovid databases was conducted. We obtained 19 articles presented in the present review of the literature. Case studies have demonstrated various changes of sexual behavior in relation to brain lesions, including the late appearance in adults of a sexual attraction to prepubescent children. In most cases of pedophilia associated with brain lesions, these lesions were located in frontal or in temporal regions. Structural neuroimaging studies have compared pedophiles with healthy subjects and tried to relate pedophilia to anatomical differences between these two groups. The location of structural changes is inconsistent across studies. Recent functional neuroimaging studies have also attempted to investigate the cerebral correlates of pedophilia. Results suggest that the activation pattern found in pedophiles in response to pictures of prepubescent nude girls or boys is similar to the pattern observed in healthy subjects in response to pictures of adult nude women or men. However, regions that become more activated in patients than in healthy controls in response to the presentation of pictures of children vary across studies. Studies that have begun to investigate the cerebral correlates of pedophilia demonstrate that it is possible to explore them through neuroimaging techniques. These initial results have to be confirmed by new studies backed with objective measurements of sexual arousal such as phallometry. Copyright © 2012 L’Encéphale, Paris. Published by Elsevier Masson SAS. All rights reserved.
Structured Illumination Diffuse Optical Tomography for Mouse Brain Imaging
NASA Astrophysics Data System (ADS)
Reisman, Matthew David
As advances in functional magnetic resonance imaging (fMRI) have transformed the study of human brain function, they have also widened the divide between standard research techniques used in humans and those used in mice, where high quality images are difficult to obtain using fMRI given the small volume of the mouse brain. Optical imaging techniques have been developed to study mouse brain networks, which are highly valuable given the ability to study brain disease treatments or development in a controlled environment. A planar imaging technique known as optical intrinsic signal (OIS) imaging has been a powerful tool for capturing functional brain hemodynamics in rodents. Recent wide field-of-view implementations of OIS have provided efficient maps of functional connectivity from spontaneous brain activity in mice. However, OIS requires scalp retraction and is limited to imaging a 2-dimensional view of superficial cortical tissues. Diffuse optical tomography (DOT) is a non-invasive, volumetric neuroimaging technique that has been valuable for bedside imaging of patients in the clinic, but previous DOT systems for rodent neuroimaging have been limited by either sparse spatial sampling or by slow speed. My research has been to develop diffuse optical tomography for whole brain mouse neuroimaging by expanding previous techniques to achieve high spatial sampling using multiple camera views for detection and high speed using structured illumination sources. I have shown the feasibility of this method to perform non-invasive functional neuroimaging in mice and its capabilities of imaging the entire volume of the brain. Additionally, the system has been built with a custom, flexible framework to accommodate the expansion to imaging multiple dynamic contrasts in the brain and populations that were previously difficult or impossible to image, such as infant mice and awake mice. I have contributed to preliminary feasibility studies of these more advanced techniques using OIS, which can now be carried out using the structured illumination diffuse optical tomography technique to perform longitudinal, non-invasive studies of the whole volume of the mouse brain.
Neuroimaging evaluation in refractory epilepsy
Granados, Ana M; Orejuela, Juan F
2015-01-01
Purpose To describe the application of neuroimaging analysis, compared to neuropsychological tests and video-electroencephalogram, for the evaluation of refractory epilepsy in a reference centre in Cali, Colombia. Methods Between March 2013 and November 2014, 29 patients, 19 men and 10 women, aged 9–65 years and with refractory epilepsy, were assessed by structural and functional magnetic resonance imaging while performing tasks related to language, verbal and non-verbal memory. Also, volumetric evaluation was performed. A 1.5 Tesla magnetic resonance imaging scanner was used in all cases. Results Neuroimaging evaluation identified 13 patients with mesial temporal sclerosis. The remaining patients were classified as: 10 patients with neoplastic masses, two patients with cortical atrophy, two patients with scarring lesions and two patients with non-structural aetiology. Among patients with mesial temporal sclerosis, comparison between techniques for lateralising the epileptogenic foci was made; the κ index between functional magnetic resonance imaging and hippocampi volumetry was κ = 1.00, agreement between neuroimaging and video-electroencephalogram was good (κ = 0.78) and comparison with a neuropsychological test was mild (κ = 0.24). Conclusions Neuroimaging studies allow the assessment of functional and structural damage related to epileptogenic lesions and foci, and are helpful to select surgical treatment, conduct intraoperative neuronavigation techniques, predict surgical deficits and evaluate patient recovery. PMID:26427897
Parks, Nathan A.
2013-01-01
The simultaneous application of transcranial magnetic stimulation (TMS) with non-invasive neuroimaging provides a powerful method for investigating functional connectivity in the human brain and the causal relationships between areas in distributed brain networks. TMS has been combined with numerous neuroimaging techniques including, electroencephalography (EEG), functional magnetic resonance imaging (fMRI), and positron emission tomography (PET). Recent work has also demonstrated the feasibility and utility of combining TMS with non-invasive near-infrared optical imaging techniques, functional near-infrared spectroscopy (fNIRS) and the event-related optical signal (EROS). Simultaneous TMS and optical imaging affords a number of advantages over other neuroimaging methods but also involves a unique set of methodological challenges and considerations. This paper describes the methodology of concurrently performing optical imaging during the administration of TMS, focusing on experimental design, potential artifacts, and approaches to controlling for these artifacts. PMID:24065911
Neuroimaging essentials in essential tremor: A systematic review
Sharifi, Sarvi; Nederveen, Aart J.; Booij, Jan; van Rootselaar, Anne-Fleur
2014-01-01
Background Essential tremor is regarded to be a disease of the central nervous system. Neuroimaging is a rapidly growing field with potential benefits to both diagnostics and research. The exact role of imaging techniques with respect to essential tremor in research and clinical practice is not clear. A systematic review of the different imaging techniques in essential tremor is lacking in the literature. Methods We performed a systematic literature search combining the terms essential tremor and familial tremor with the following keywords: imaging, MRI, VBM, DWI, fMRI, PET and SPECT, both in abbreviated form as well as in full form. We summarize and discuss the quality and the external validity of each study and place the results in the context of existing knowledge regarding the pathophysiology of essential tremor. Results A total of 48 neuroimaging studies met our search criteria, roughly divided into 19 structural and 29 functional and metabolic studies. The quality of the studies varied, especially concerning inclusion criteria. Functional imaging studies indicated cerebellar hyperactivity during rest and during tremor. The studies also pointed to the involvement of the thalamus, the inferior olive and the red nucleus. Structural studies showed less consistent results. Discussion and conclusion Neuroimaging techniques in essential tremor give insight into the pathophysiology of essential tremor indicating the involvement of the cerebellum as the most consistent finding. GABAergic dysfunction might be a major premise in the pathophysiological hypotheses. Inconsistencies between studies can be partly explained by the inclusion of heterogeneous patient groups. Improvement of scientific research requires more stringent inclusion criteria and application of advanced analysis techniques. Also, the use of multimodal neuroimaging techniques is a promising development in movement disorders research. Currently, the role of imaging techniques in essential tremor in daily clinical practice is limited. PMID:25068111
Neural Signatures of Autism Spectrum Disorders: Insights into Brain Network Dynamics
Hernandez, Leanna M; Rudie, Jeffrey D; Green, Shulamite A; Bookheimer, Susan; Dapretto, Mirella
2015-01-01
Neuroimaging investigations of autism spectrum disorders (ASDs) have advanced our understanding of atypical brain function and structure, and have recently converged on a model of altered network-level connectivity. Traditional task-based functional magnetic resonance imaging (MRI) and volume-based structural MRI studies have identified widespread atypicalities in brain regions involved in social behavior and other core ASD-related behavioral deficits. More recent advances in MR-neuroimaging methods allow for quantification of brain connectivity using diffusion tensor imaging, functional connectivity, and graph theoretic methods. These newer techniques have moved the field toward a systems-level understanding of ASD etiology, integrating functional and structural measures across distal brain regions. Neuroimaging findings in ASD as a whole have been mixed and at times contradictory, likely due to the vast genetic and phenotypic heterogeneity characteristic of the disorder. Future longitudinal studies of brain development will be crucial to yield insights into mechanisms of disease etiology in ASD sub-populations. Advances in neuroimaging methods and large-scale collaborations will also allow for an integrated approach linking neuroimaging, genetics, and phenotypic data. PMID:25011468
Near-Infrared Neuroimaging with NinPy
Strangman, Gary E.; Zhang, Quan; Zeffiro, Thomas
2009-01-01
There has been substantial recent growth in the use of non-invasive optical brain imaging in studies of human brain function in health and disease. Near-infrared neuroimaging (NIN) is one of the most promising of these techniques and, although NIN hardware continues to evolve at a rapid pace, software tools supporting optical data acquisition, image processing, statistical modeling, and visualization remain less refined. Python, a modular and computationally efficient development language, can support functional neuroimaging studies of diverse design and implementation. In particular, Python's easily readable syntax and modular architecture allow swift prototyping followed by efficient transition to stable production systems. As an introduction to our ongoing efforts to develop Python software tools for structural and functional neuroimaging, we discuss: (i) the role of non-invasive diffuse optical imaging in measuring brain function, (ii) the key computational requirements to support NIN experiments, (iii) our collection of software tools to support NIN, called NinPy, and (iv) future extensions of these tools that will allow integration of optical with other structural and functional neuroimaging data sources. Source code for the software discussed here will be made available at www.nmr.mgh.harvard.edu/Neural_SystemsGroup/software.html. PMID:19543449
Dynamics of the brain: Mathematical models and non-invasive experimental studies
NASA Astrophysics Data System (ADS)
Toronov, V.; Myllylä, T.; Kiviniemi, V.; Tuchin, V. V.
2013-10-01
Dynamics is an essential aspect of the brain function. In this article we review theoretical models of neural and haemodynamic processes in the human brain and experimental non-invasive techniques developed to study brain functions and to measure dynamic characteristics, such as neurodynamics, neurovascular coupling, haemodynamic changes due to brain activity and autoregulation, and cerebral metabolic rate of oxygen. We focus on emerging theoretical biophysical models and experimental functional neuroimaging results, obtained mostly by functional magnetic resonance imaging (fMRI) and near-infrared spectroscopy (NIRS). We also included our current results on the effects of blood pressure variations on cerebral haemodynamics and simultaneous measurements of fast processes in the brain by near-infrared spectroscopy and a very novel functional MRI technique called magnetic resonance encephalography. Based on a rapid progress in theoretical and experimental techniques and due to the growing computational capacities and combined use of rapidly improving and emerging neuroimaging techniques we anticipate during next decade great achievements in the overall knowledge of the human brain.
Emerging MRI and metabolic neuroimaging techniques in mild traumatic brain injury.
Lu, Liyan; Wei, Xiaoer; Li, Minghua; Li, Yuehua; Li, Wenbin
2014-01-01
Traumatic brain injury (TBI) is one of the leading causes of death worldwide, and mild traumatic brain injury (mTBI) is the most common traumatic injury. It is difficult to detect mTBI using a routine neuroimaging. Advanced techniques with greater sensitivity and specificity for the diagnosis and treatment of mTBI are required. The aim of this review is to offer an overview of various emerging neuroimaging methodologies that can solve the clinical health problems associated with mTBI. Important findings and improvements in neuroimaging that hold value for better detection, characterization and monitoring of objective brain injuries in patients with mTBI are presented. Conventional computed tomography (CT) and magnetic resonance imaging (MRI) are not very efficient for visualizing mTBI. Moreover, techniques such as diffusion tensor imaging, magnetization transfer imaging, susceptibility-weighted imaging, functional MRI, single photon emission computed tomography, positron emission tomography and magnetic resonance spectroscopy imaging were found to be useful for mTBI imaging.
25 years of neuroimaging in amyotrophic lateral sclerosis
Foerster, Bradley R.; Welsh, Robert C.; Feldman, Eva L.
2014-01-01
Amyotrophic lateral sclerosis (ALS) is a fatal motor neuron disease for which a precise cause has not yet been identified. Standard CT or MRI evaluation does not demonstrate gross structural nervous system changes in ALS, so conventional neuroimaging techniques have provided little insight into the pathophysiology of this disease. Advanced neuroimaging techniques—such as structural MRI, diffusion tensor imaging and proton magnetic resonance spectroscopy—allow evaluation of alterations of the nervous system in ALS. These alterations include focal loss of grey and white matter and reductions in white matter tract integrity, as well as changes in neural networks and in the chemistry, metabolism and receptor distribution in the brain. Given their potential for investigation of both brain structure and function, advanced neuroimaging methods offer important opportunities to improve diagnosis, guide prognosis, and direct future treatment strategies in ALS. In this article, we review the contributions made by various advanced neuroimaging techniques to our understanding of the impact of ALS on different brain regions, and the potential role of such measures in biomarker development. PMID:23917850
Application of positron emission tomography to neuroimaging in sports sciences.
Tashiro, Manabu; Itoh, Masatoshi; Fujimoto, Toshihiko; Masud, Md Mehedi; Watanuki, Shoichi; Yanai, Kazuhiko
2008-08-01
To investigate exercise-induced regional metabolic and perfusion changes in the human brain, various methods are available, such as positron emission tomography (PET), functional magnetic resonance imaging (fMRI), near-infrared spectroscopy (NIRS) and electroencephalography (EEG). In this paper, details of methods of metabolic measurement using PET, [(18)F]fluorodeoxyglucose ([(18)F]FDG) and [(15)O]radio-labelled water ([(15)O]H(2)O) will be explained. Functional neuroimaging in the field of neuroscience was started in the 1970s using an autoradiography technique on experimental animals. The first human functional neuroimaging exercise study was conducted in 1987 using a rough measurement system known as (133)Xe inhalation. Although the data was useful, more detailed and exact functional neuroimaging, especially with respect to spatial resolution, was achieved by positron emission tomography. Early studies measured the cerebral blood flow changes during exercise. Recently, PET was made more applicable to exercise physiology and psychology by the use of the tracer [(18)F]FDG. This technique allowed subjects to be scanned after an exercise task is completed but still obtain data from the exercise itself, which is similar to autoradiography studies. In this report, methodological information is provided with respect to the recommended protocol design, the selection of the scanning mode, how to evaluate the cerebral glucose metabolism and how to interpret the regional brain activity using voxel-by-voxel analysis and regions of interest techniques (ROI). Considering the important role of exercise in health promotion, further efforts in this line of research should be encouraged in order to better understand health behavior. Although the number of research papers is still limited, recent work has indicated that the [(18)F]FDG-PET technique is a useful tool to understand brain activity during exercise.
Neuroimaging the interaction of mind and metabolism in humans
D’Agostino, Alexandra E.; Small, Dana M.
2012-01-01
Hormonal and metabolic signals interact with neural circuits orchestrating behavior to guide food intake. Neuroimaging techniques such as functional magnetic resonance imaging (fMRI) enable the identification of where in the brain particular mental processes like desire, satiety and pleasure occur. Once these neural circuits are described it then becomes possible to determine how metabolic and hormonal signals can alter brain response to influence psychological states and decision-making processes to guide intake. Here, we provide an overview of the contributions of functional neuroimaging to the understanding of how subjective and neural responses to food and food cues interact with metabolic/hormonal factors. PMID:24024114
Bufkin, Jana L; Luttrell, Vickie R
2005-04-01
With the availability of new functional and structural neuroimaging techniques, researchers have begun to localize brain areas that may be dysfunctional in offenders who are aggressive and violent. Our review of 17 neuroimaging studies reveals that the areas associated with aggressive and/or violent behavioral histories, particularly impulsive acts, are located in the prefrontal cortex and the medial temporal regions. These findings are explained in the context of negative emotion regulation, and suggestions are provided concerning how such findings may affect future theoretical frameworks in criminology, crime prevention efforts, and the functioning of the criminal justice system.
Whole-Brain Microscopy Meets In Vivo Neuroimaging: Techniques, Benefits, and Limitations.
Aswendt, Markus; Schwarz, Martin; Abdelmoula, Walid M; Dijkstra, Jouke; Dedeurwaerdere, Stefanie
2017-02-01
Magnetic resonance imaging, positron emission tomography, and optical imaging have emerged as key tools to understand brain function and neurological disorders in preclinical mouse models. They offer the unique advantage of monitoring individual structural and functional changes over time. What remained unsolved until recently was to generate whole-brain microscopy data which can be correlated to the 3D in vivo neuroimaging data. Conventional histological sections are inappropriate especially for neuronal tracing or the unbiased screening for molecular targets through the whole brain. As part of the European Society for Molecular Imaging (ESMI) meeting 2016 in Utrecht, the Netherlands, we addressed this issue in the Molecular Neuroimaging study group meeting. Presentations covered new brain clearing methods, light sheet microscopes for large samples, and automatic registration of microscopy to in vivo imaging data. In this article, we summarize the discussion; give an overview of the novel techniques; and discuss the practical needs, benefits, and limitations.
Neuroimaging and Recovery of Language in Aphasia
Thompson, Cynthia K.; den Ouden, Dirk-Bart
2010-01-01
The use of functional neuroimaging techniques has advanced what is known about the neural mechanisms used to support language processing in aphasia resulting from brain damage. This paper highlights recent findings derived from neuroimaging studies focused on neuroplasticity of language networks, the role of the left and right hemispheres in this process, and studies examining how treatment affects the neurobiology of recovery. We point out variability across studies as well as factors related to this variability, and we emphasize challenges that remain for research. PMID:18957184
Functions of the human frontoparietal attention network: Evidence from neuroimaging
Scolari, Miranda; Seidl-Rathkopf, Katharina N; Kastner, Sabine
2016-01-01
Human frontoparietal cortex has long been implicated as a source of attentional control. However, the mechanistic underpinnings of these control functions have remained elusive due to limitations of neuroimaging techniques that rely on anatomical landmarks to localize patterns of activation. The recent advent of topographic mapping via functional magnetic resonance imaging (fMRI) has allowed the reliable parcellation of the network into 18 independent subregions in individual subjects, thereby offering unprecedented opportunities to address a wide range of empirical questions as to how mechanisms of control operate. Here, we review the human neuroimaging literature that has begun to explore space-based, feature-based, object-based and category-based attentional control within the context of topographically defined frontoparietal cortex. PMID:27398396
Alferova, V V; Mayorova, L A; Ivanova, E G; Guekht, A B; Shklovskij, V M
2017-01-01
The introduction of non-invasive functional neuroimaging techniques such as functional magnetic resonance imaging (fMRI), in the practice of scientific and clinical research can increase our knowledge about the organization of cognitive processes, including language, in normal and reorganization of these cognitive functions in post-stroke aphasia. The article discusses the results of fMRI studies of functional organization of the cortex of a healthy adult's brain in the processing of various voice information as well as the main types of speech reorganization after post-stroke aphasia in different stroke periods. The concepts of 'effective' and 'ineffective' brain plasticity in post-stroke aphasia were considered. It was concluded that there was an urgent need for further comprehensive studies, including neuropsychological testing and several complementary methods of functional neuroimaging, to develop a phased treatment plan and neurorehabilitation of patients with post-stroke aphasia.
Phillips, Mary L.; Chase, Henry W.; Sheline, Yvette I.; Etkin, Amit; Almeida, Jorge R.C.; Deckersbach, Thilo; Trivedi, Madhukar H.
2015-01-01
Objective Despite significant advances in neuroscience and treatment development, no widely accepted biomarkers are available to inform diagnostics or identify preferred treatments for individuals with major depressive disorder. Method In this critical review, the authors examine the extent to which multimodal neuroimaging techniques can identify biomarkers reflecting key pathophysiologic processes in depression and whether such biomarkers may act as predictors, moderators, and mediators of treatment response that might facilitate development of personalized treatments based on a better understanding of these processes. Results The authors first highlight the most consistent findings from neuroimaging studies using different techniques in depression, including structural and functional abnormalities in two parallel neural circuits: serotonergically modulated implicit emotion regulation circuitry, centered on the amygdala and different regions in the medial prefrontal cortex; and dopaminergically modulated reward neural circuitry, centered on the ventral striatum and medial prefrontal cortex. They then describe key findings from the relatively small number of studies indicating that specific measures of regional function and, to a lesser extent, structure in these neural circuits predict treatment response in depression. Conclusions Limitations of existing studies include small sample sizes, use of only one neuroimaging modality, and a focus on identifying predictors rather than moderators and mediators of differential treatment response. By addressing these limitations and, most importantly, capitalizing on the benefits of multimodal neuroimaging, future studies can yield moderators and mediators of treatment response in depression to facilitate significant improvements in shorter- and longer-term clinical and functional outcomes. PMID:25640931
Running Neuroimaging Applications on Amazon Web Services: How, When, and at What Cost?
Madhyastha, Tara M; Koh, Natalie; Day, Trevor K M; Hernández-Fernández, Moises; Kelley, Austin; Peterson, Daniel J; Rajan, Sabreena; Woelfer, Karl A; Wolf, Jonathan; Grabowski, Thomas J
2017-01-01
The contribution of this paper is to identify and describe current best practices for using Amazon Web Services (AWS) to execute neuroimaging workflows "in the cloud." Neuroimaging offers a vast set of techniques by which to interrogate the structure and function of the living brain. However, many of the scientists for whom neuroimaging is an extremely important tool have limited training in parallel computation. At the same time, the field is experiencing a surge in computational demands, driven by a combination of data-sharing efforts, improvements in scanner technology that allow acquisition of images with higher image resolution, and by the desire to use statistical techniques that stress processing requirements. Most neuroimaging workflows can be executed as independent parallel jobs and are therefore excellent candidates for running on AWS, but the overhead of learning to do so and determining whether it is worth the cost can be prohibitive. In this paper we describe how to identify neuroimaging workloads that are appropriate for running on AWS, how to benchmark execution time, and how to estimate cost of running on AWS. By benchmarking common neuroimaging applications, we show that cloud computing can be a viable alternative to on-premises hardware. We present guidelines that neuroimaging labs can use to provide a cluster-on-demand type of service that should be familiar to users, and scripts to estimate cost and create such a cluster.
Can understanding the neurobiology of body dysmorphic disorder (BDD) inform treatment?
Rossell, Susan L; Harrison, Ben J; Castle, David
2015-08-01
We aim to provide a clinically focused review of the neurobiological literature in body dysmorphic disorder (BDD), with a focus on structural and functional neuroimaging. There has been a recent influx of studies examining the underlying neurobiology of BDD using structural and functional neuroimaging methods. Despite obvious symptom similarities with obsessive-compulsive disorder (OCD), no study to date has directly compared the two groups using neuroimaging techniques. Studies have established that there are limbic and visual cortex abnormalities in BDD, in contrast to fronto-striatal differences in OCD. Such data suggests affect or visual training maybe useful in BDD. © The Royal Australian and New Zealand College of Psychiatrists 2015.
Syntactic Processing in Bilinguals: An fNIRS Study
ERIC Educational Resources Information Center
Scherer, Lilian Cristine; Fonseca, Rochele Paz; Amiri, Mahnoush; Adrover-Roig, Daniel; Marcotte, Karine; Giroux, Francine; Senhadji, Noureddine; Benali, Habib; Lesage, Frederic; Ansaldo, Ana Ines
2012-01-01
The study of the neural basis of syntactic processing has greatly benefited from neuroimaging techniques. Research on syntactic processing in bilinguals has used a variety of techniques, including mainly functional magnetic resonance imaging (fMRI) and event-related potentials (ERP). This paper reports on a functional near-infrared spectroscopy…
Pan, Zhujun; Su, Xiwen; Fang, Qun; Hou, Lijuan; Lee, Younghan; Chen, Chih C; Lamberth, John; Kim, Mi-Lyang
2018-01-01
Aging is a process associated with a decline in cognitive and motor functions, which can be attributed to neurological changes in the brain. Tai Chi, a multimodal mind-body exercise, can be practiced by people across all ages. Previous research identified effects of Tai Chi practice on delaying cognitive and motor degeneration. Benefits in behavioral performance included improved fine and gross motor skills, postural control, muscle strength, and so forth. Neural plasticity remained in the aging brain implies that Tai Chi-associated benefits may not be limited to the behavioral level. Instead, neurological changes in the human brain play a significant role in corresponding to the behavioral improvement. However, previous studies mainly focused on the effects of behavioral performance, leaving neurological changes largely unknown. This systematic review summarized extant studies that used brain imaging techniques and EEG to examine the effects of Tai Chi on older adults. Eleven articles were eligible for the final review. Three neuroimaging techniques including fMRI ( N = 6), EEG ( N = 4), and MRI ( N = 1), were employed for different study interests. Significant changes were reported on subjects' cortical thickness, functional connectivity and homogeneity of the brain, and executive network neural function after Tai Chi intervention. The findings suggested that Tai Chi intervention give rise to beneficial neurological changes in the human brain. Future research should develop valid and convincing study design by applying neuroimaging techniques to detect effects of Tai Chi intervention on the central nervous system of older adults. By integrating neuroimaging techniques into randomized controlled trials involved with Tai Chi intervention, researchers can extend the current research focus from behavioral domain to neurological level.
Neuroimaging Techniques: a Conceptual Overview of Physical Principles, Contribution and History
NASA Astrophysics Data System (ADS)
Minati, Ludovico
2006-06-01
This paper is meant to provide a brief overview of the techniques currently used to image the brain and to study non-invasively its anatomy and function. After a historical summary in the first section, general aspects are outlined in the second section. The subsequent six sections survey, in order, computed tomography (CT), morphological magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), diffusion-tensor magnetic resonance imaging (DWI/DTI), positron emission tomography (PET), and electro- and magneto-encephalography (EEG/MEG) based imaging. Underlying physical principles, modelling and data processing approaches, as well as clinical and research relevance are briefly outlined for each technique. Given the breadth of the scope, there has been no attempt to be comprehensive. The ninth and final section outlines some aspects of active research in neuroimaging.
Functional neuroimaging of extraversion-introversion.
Lei, Xu; Yang, Tianliang; Wu, Taoyu
2015-12-01
Neuroimaging techniques such as functional magnetic resonance imaging and positron emission tomography have provided an unprecedented neurobiological perspective for research on personality traits. Evidence from task-related neuroimaging has shown that extraversion is associated with activations in regions of the anterior cingulate cortex, dorsolateral prefrontal cortex, middle temporal gyrus and the amygdala. Currently, resting-state neuroimaging is being widely used in cognitive neuroscience. Initial exploration of extraversion has revealed correlations with the medial prefrontal cortex, anterior cingulate cortex, insular cortex, and the precuneus. Recent research work has indicated that the long-range temporal dependence of the resting-state spontaneous oscillation has high test-retest reliability. Moreover, the long-range temporal dependence of the resting-state networks is highly correlated with personality traits, and this can be used for the prediction of extraversion. As the long-range temporal dependence reflects real-time information updating in individuals, this method may provide a new approach to research on personality traits.
Soltanlou, Mojtaba; Sitnikova, Maria A; Nuerk, Hans-Christoph; Dresler, Thomas
2018-01-01
In this review, we aim to highlight the application of functional near-infrared spectroscopy (fNIRS) as a useful neuroimaging technique for the investigation of cognitive development. We focus on brain activation changes during the development of mathematics and language skills in schoolchildren. We discuss how technical limitations of common neuroimaging techniques such as functional magnetic resonance imaging (fMRI) have resulted in our limited understanding of neural changes during development, while fNIRS would be a suitable and child-friendly method to examine cognitive development. Moreover, this technique enables us to go to schools to collect large samples of data from children in ecologically valid settings. Furthermore, we report findings of fNIRS studies in the fields of mathematics and language, followed by a discussion of the outlook of fNIRS in these fields. We suggest fNIRS as an additional technique to track brain activation changes in the field of educational neuroscience.
Soltanlou, Mojtaba; Sitnikova, Maria A.; Nuerk, Hans-Christoph; Dresler, Thomas
2018-01-01
In this review, we aim to highlight the application of functional near-infrared spectroscopy (fNIRS) as a useful neuroimaging technique for the investigation of cognitive development. We focus on brain activation changes during the development of mathematics and language skills in schoolchildren. We discuss how technical limitations of common neuroimaging techniques such as functional magnetic resonance imaging (fMRI) have resulted in our limited understanding of neural changes during development, while fNIRS would be a suitable and child-friendly method to examine cognitive development. Moreover, this technique enables us to go to schools to collect large samples of data from children in ecologically valid settings. Furthermore, we report findings of fNIRS studies in the fields of mathematics and language, followed by a discussion of the outlook of fNIRS in these fields. We suggest fNIRS as an additional technique to track brain activation changes in the field of educational neuroscience. PMID:29666589
Recent neuroimaging techniques in mild traumatic brain injury.
Belanger, Heather G; Vanderploeg, Rodney D; Curtiss, Glenn; Warden, Deborah L
2007-01-01
Mild traumatic brain injury (TBI) is characterized by acute physiological changes that result in at least some acute cognitive difficulties and typically resolve by 3 months postinjury. Because the majority of mild TBI patients have normal structural magnetic resonance imaging (MRI)/computed tomography (CT) scans, there is increasing attention directed at finding objective physiological correlates of persistent cognitive and neuropsychiatric symptoms through experimental neuroimaging techniques. The authors review studies utilizing these techniques in patients with mild TBI; these techniques may provide more sensitive assessment of structural and functional abnormalities following mild TBI. Particular promise is evident with fMRI, PET, and SPECT scanning, as demonstrated by associations between brain activation and clinical outcomes.
ERIC Educational Resources Information Center
Downar, Jonathan; Krizova, Adriana; Ghaffar, Omar; Zaretsky, Ari
2010-01-01
Objective: Neuroimaging techniques are increasingly important in psychiatric research and clinical practice, but few postgraduate psychiatry programs offer formal training in neuroimaging. To address this need, the authors developed a course to prepare psychiatric residents to use neuroimaging techniques effectively in independent practice.…
Running Neuroimaging Applications on Amazon Web Services: How, When, and at What Cost?
Madhyastha, Tara M.; Koh, Natalie; Day, Trevor K. M.; Hernández-Fernández, Moises; Kelley, Austin; Peterson, Daniel J.; Rajan, Sabreena; Woelfer, Karl A.; Wolf, Jonathan; Grabowski, Thomas J.
2017-01-01
The contribution of this paper is to identify and describe current best practices for using Amazon Web Services (AWS) to execute neuroimaging workflows “in the cloud.” Neuroimaging offers a vast set of techniques by which to interrogate the structure and function of the living brain. However, many of the scientists for whom neuroimaging is an extremely important tool have limited training in parallel computation. At the same time, the field is experiencing a surge in computational demands, driven by a combination of data-sharing efforts, improvements in scanner technology that allow acquisition of images with higher image resolution, and by the desire to use statistical techniques that stress processing requirements. Most neuroimaging workflows can be executed as independent parallel jobs and are therefore excellent candidates for running on AWS, but the overhead of learning to do so and determining whether it is worth the cost can be prohibitive. In this paper we describe how to identify neuroimaging workloads that are appropriate for running on AWS, how to benchmark execution time, and how to estimate cost of running on AWS. By benchmarking common neuroimaging applications, we show that cloud computing can be a viable alternative to on-premises hardware. We present guidelines that neuroimaging labs can use to provide a cluster-on-demand type of service that should be familiar to users, and scripts to estimate cost and create such a cluster. PMID:29163119
ERIC Educational Resources Information Center
Van der Haegen, Lise; Cai, Qing; Seurinck, Ruth; Brysbaert, Marc
2011-01-01
The best established lateralized cerebral function is speech production, with the majority of the population having left hemisphere dominance. An important question is how to best assess the laterality of this function. Neuroimaging techniques such as functional Magnetic Resonance Imaging (fMRI) are increasingly used in clinical settings to…
Franco, Alexandre R; Ling, Josef; Caprihan, Arvind; Calhoun, Vince D; Jung, Rex E; Heileman, Gregory L; Mayer, Andrew R
2008-12-01
The human brain functions as an efficient system where signals arising from gray matter are transported via white matter tracts to other regions of the brain to facilitate human behavior. However, with a few exceptions, functional and structural neuroimaging data are typically optimized to maximize the quantification of signals arising from a single source. For example, functional magnetic resonance imaging (FMRI) is typically used as an index of gray matter functioning whereas diffusion tensor imaging (DTI) is typically used to determine white matter properties. While it is likely that these signals arising from different tissue sources contain complementary information, the signal processing algorithms necessary for the fusion of neuroimaging data across imaging modalities are still in a nascent stage. In the current paper we present a data-driven method for combining measures of functional connectivity arising from gray matter sources (FMRI resting state data) with different measures of white matter connectivity (DTI). Specifically, a joint independent component analysis (J-ICA) was used to combine these measures of functional connectivity following intensive signal processing and feature extraction within each of the individual modalities. Our results indicate that one of the most predominantly used measures of functional connectivity (activity in the default mode network) is highly dependent on the integrity of white matter connections between the two hemispheres (corpus callosum) and within the cingulate bundles. Importantly, the discovery of this complex relationship of connectivity was entirely facilitated by the signal processing and fusion techniques presented herein and could not have been revealed through separate analyses of both data types as is typically performed in the majority of neuroimaging experiments. We conclude by discussing future applications of this technique to other areas of neuroimaging and examining potential limitations of the methods.
Neuroimaging and Drug Taking in Primates Abbreviated title: Neuroimaging and Drug taking
Murnane, Kevin S.; Howell, Leonard L.
2011-01-01
Rationale Neuroimaging techniques have led to significant advances in our understanding of the neurobiology of drug-taking and the treatment of drug addiction in humans. Neuroimaging approaches provide a powerful translational approach that can link findings from humans and laboratory animals. Objective This review describes the utility of neuroimaging toward understanding the neurobiological basis of drug taking, and documents the close concordance that can be achieved among neuroimaging, neurochemical and behavioral endpoints. Results The study of drug interactions with dopamine and serotonin transporters in vivo has identified pharmacological mechanisms of action associated with the abuse liability of stimulants. Neuroimaging has identified the extended limbic system, including the prefrontal cortex and anterior cingulate, as important neuronal circuitry that underlies drug taking. The ability to conduct within-subject, longitudinal assessments of brain chemistry and neuronal function has enhanced our efforts to document long-term changes in dopamine D2 receptors, monoamine transporters, and prefrontal metabolism due to chronic drug exposure. Dysregulation of dopamine function and brain metabolic changes in areas involved in reward circuitry have been linked to drug-taking behavior, cognitive impairment and treatment response. Conclusions Experimental designs employing neuroimaging should consider well-documented determinants of drug taking, including pharmacokinetic considerations, subject history and environmental variables. Methodological issues to consider include limited molecular probes, lack of neurochemical specificity in brain activation studies, and the potential influence of anesthetics in animal studies. Nevertheless, these integrative approaches should have important implications for understanding drug-taking behavior and the treatment of drug addiction. PMID:21360099
Neuroimaging Insights into the Pathophysiology of Sleep Disorders
Desseilles, Martin; Dang-Vu, Thanh; Schabus, Manuel; Sterpenich, Virginie; Maquet, Pierre; Schwartz, Sophie
2008-01-01
Neuroimaging methods can be used to investigate whether sleep disorders are associated with specific changes in brain structure or regional activity. However, it is still unclear how these new data might improve our understanding of the pathophysiology underlying adult sleep disorders. Here we review functional brain imaging findings in major intrinsic sleep disorders (i.e., idiopathic insomnia, narcolepsy, and obstructive sleep apnea) and in abnormal motor behavior during sleep (i.e., periodic limb movement disorder and REM sleep behavior disorder). The studies reviewed include neuroanatomical assessments (voxel-based morphometry, magnetic resonance spectroscopy), metabolic/functional investigations (positron emission tomography, single photon emission computed tomography, functional magnetic resonance imaging), and ligand marker measurements. Based on the current state of the research, we suggest that brain imaging is a useful approach to assess the structural and functional correlates of sleep impairments as well as better understand the cerebral consequences of various therapeutic approaches. Modern neuroimaging techniques therefore provide a valuable tool to gain insight into possible pathophysiological mechanisms of sleep disorders in adult humans. Citation: Desseilles M; Dang-Vu TD; Schabus M; Sterpenich V; Maquet P; Schwartz S. Neuroimaging insights into the pathophysiology of sleep disorders. SLEEP 2008;31(6):777–794. PMID:18548822
Functional neuroimaging: technical, logical, and social perspectives.
Aguirre, Geoffrey K
2014-01-01
Neuroscientists have long sought to study the dynamic activity of the human brain-what's happening in the brain, that is, while people are thinking, feeling, and acting. Ideally, an inside look at brain function would simultaneously and continuously measure the biochemical state of every cell in the central nervous system. While such a miraculous method is science fiction, a century of progress in neuroimaging technologies has made such simultaneous and continuous measurement a plausible fiction. Despite this progress, practitioners of modern neuroimaging struggle with two kinds of limitations: those that attend the particular neuroimaging methods we have today and those that would limit any method of imaging neural activity, no matter how powerful. In this essay, I consider the liabilities and potential of techniques that measure human brain activity. I am concerned here only with methods that measure relevant physiologic states of the central nervous system and relate those measures to particular mental states. I will consider in particular the preeminent method of functional neuroimaging: BOLD fMRI. While there are several practical limits on the biological information that current technologies can measure, these limits-as important as they are-are minor in comparison to the fundamental logical restraints on the conclusions that can be drawn from brain imaging studies. © 2014 by The Hastings Center.
Cendes, Fernando; Theodore, William H.; Brinkmann, Benjamin H.; Sulc, Vlastimil; Cascino, Gregory D.
2017-01-01
Imaging is pivotal in the evaluation and management of patients with seizure disorders. Elegant structural neuroimaging with magnetic resonance imaging (MRI) may assist in determining the etiology of focal epilepsy and demonstrating the anatomical changes associated with seizure activity. The high diagnostic yield of MRI to identify the common pathological findings in individuals with focal seizures including mesial temporal sclerosis, vascular anomalies, low-grade glial neoplasms and malformations of cortical development has been demonstrated. Positron emission tomography (PET) is the most commonly performed interictal functional neuroimaging technique that may reveal a focal hypometabolic region concordant with seizure onset. Single photon emission computed tomography (SPECT) studies may assist performance of ictal neuroimaging in patients with pharmacoresistant focal epilepsy being considered for neurosurgical treatment. This chapter highlights neuroimaging developments and innovations, and provides a comprehensive overview of the imaging strategies used to improve the care and management of people with epilepsy. PMID:27430454
Neuroimaging and sexual behavior: identification of regional and functional differences.
Cheng, Joseph C; Secondary, Joseph; Burke, William H; Fedoroff, J Paul; Dwyer, R Gregg
2015-07-01
The neuroanatomical correlates of human sexual desire, arousal, and behavior have been characterized in recent years with functional brain imaging techniques such as magnetic resonance imaging (MRI) and positron emission tomography (PET). Here, we briefly review the results of functional neuroimaging studies in humans, whether healthy or suffering from sexual disorders, and the current models of regional and network activation in sexual arousal. Attention is paid, in particular, to findings from both regional and network studies in the past 3 years. We also identify yet unanswered and pressing questions of interest to areas of ongoing investigations for psychiatric, scientific, and forensic disciplines.
[Neuroimaging and Blood Biomarkers in Functional Prognosis after Stroke].
Branco, João Paulo; Costa, Joana Santos; Sargento-Freitas, João; Oliveira, Sandra; Mendes, Bruno; Laíns, Jorge; Pinheiro, João
2016-11-01
Stroke remains one of the leading causes of morbidity and mortality around the world and it is associated with an important long-term functional disability. Some neuroimaging resources and certain peripheral blood or cerebrospinal fluid proteins can give important information about etiology, therapeutic approach, follow-up and functional prognosis in acute ischemic stroke patients. However, among the scientific community, there is currently more interest in the stroke vital prognosis over the functional prognosis. Predicting the functional prognosis during acute phase would allow more objective rehabilitation programs and better management of the available resources. The aim of this work is to review the potential role of acute phase neuroimaging and blood biomarkers as functional recovery predictors after ischemic stroke. Review of the literature published between 2005 and 2015, in English, using the terms "ischemic stroke", "neuroimaging" e "blood biomarkers". We included nine studies, based on abstract reading. Computerized tomography, transcranial doppler ultrasound and diffuse magnetic resonance imaging show potential predictive value, based on the blood flow study and the evaluation of stroke's volume and localization, especially when combined with the National Institutes of Health Stroke Scale. Several biomarkers have been studied as diagnostic, risk stratification and prognostic tools, namely the S100 calcium binding protein B, C-reactive protein, matrix metalloproteinases and cerebral natriuretic peptide. Although some biomarkers and neuroimaging techniques have potential predictive value, none of the studies were able to support its use, alone or in association, as a clinically useful functionality predictor model. All the evaluated markers were considered insufficient to predict functional prognosis at three months, when applied in the first hours after stroke. Additional studies are necessary to identify reliable predictive markers for functional prognosis after ischemic stroke.
Smucny, Jason; Tregellas, Jason R
2018-01-01
Patients with schizophrenia self-administer nicotine at rates higher than is self-administered for any other psychiatric illness. Although the reasons are unclear, one hypothesis suggests that nicotine is a form of ‘self-medication’ in order to restore normal levels of nicotinic signaling and target abnormalities in neuronal function associated with cognitive processes. This brief review discusses evidence from neurophysiological and neuroimaging studies in schizophrenia patients that nicotinic agonists may effectively target dysfunctional neuronal circuits in the illness. Evidence suggests that nicotine significantly modulates a number of these circuits, although relatively few studies have used modern neuroimaging techniques (e.g. functional magnetic resonance imaging (fMRI)) to examine the effects of nicotinic drugs on disease-related neurobiology. The neuronal effects of nicotine and other nicotinic agonists in schizophrenia remain a priority for psychiatry research. PMID:28441884
Variational Bayesian Parameter Estimation Techniques for the General Linear Model
Starke, Ludger; Ostwald, Dirk
2017-01-01
Variational Bayes (VB), variational maximum likelihood (VML), restricted maximum likelihood (ReML), and maximum likelihood (ML) are cornerstone parametric statistical estimation techniques in the analysis of functional neuroimaging data. However, the theoretical underpinnings of these model parameter estimation techniques are rarely covered in introductory statistical texts. Because of the widespread practical use of VB, VML, ReML, and ML in the neuroimaging community, we reasoned that a theoretical treatment of their relationships and their application in a basic modeling scenario may be helpful for both neuroimaging novices and practitioners alike. In this technical study, we thus revisit the conceptual and formal underpinnings of VB, VML, ReML, and ML and provide a detailed account of their mathematical relationships and implementational details. We further apply VB, VML, ReML, and ML to the general linear model (GLM) with non-spherical error covariance as commonly encountered in the first-level analysis of fMRI data. To this end, we explicitly derive the corresponding free energy objective functions and ensuing iterative algorithms. Finally, in the applied part of our study, we evaluate the parameter and model recovery properties of VB, VML, ReML, and ML, first in an exemplary setting and then in the analysis of experimental fMRI data acquired from a single participant under visual stimulation. PMID:28966572
Advances in neuroimaging of traumatic brain injury and posttraumatic stress disorder
Van Boven, Robert W.; Harrington, Greg S.; Hackney, David B.; Ebel, Andreas; Gauger, Grant; Bremner, J. Douglas; D’Esposito, Mark; Detre, John A.; Haacke, E. Mark; Jack, Clifford R.; Jagust, William J.; Le Bihan, Denis; Mathis, Chester A.; Mueller, Susanne; Mukherjee, Pratik; Schuff, Norbert; Chen, Anthony; Weiner, Michael W.
2011-01-01
Improved diagnosis and treatment of traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD) are needed for our military and veterans, their families, and society at large. Advances in brain imaging offer important biomarkers of structural, functional, and metabolic information concerning the brain. This article reviews the application of various imaging techniques to the clinical problems of TBI and PTSD. For TBI, we focus on findings and advances in neuroimaging that hold promise for better detection, characterization, and monitoring of objective brain changes in symptomatic patients with combat-related, closed-head brain injuries not readily apparent by standard computed tomography or conventional magnetic resonance imaging techniques. PMID:20104401
Heggdal, Peder O Laugen; Brännström, Jonas; Aarstad, Hans Jørgen; Vassbotn, Flemming S; Specht, Karsten
2016-02-01
This paper aims to provide a review of studies using neuroimaging to measure functional-structural reorganisation of the neuronal network for auditory perception after unilateral hearing loss. A literature search was performed in PubMed. Search criterions were peer reviewed original research papers in English completed by the 11th of March 2015. Twelve studies were found to use neuroimaging in subjects with unilateral hearing loss. An additional five papers not identified by the literature search were provided by a reviewer. Thus, a total of 17 studies were included in the review. Four different neuroimaging methods were used in these studies: Functional magnetic resonance imaging (fMRI) (n = 11), diffusion tensor imaging (DTI) (n = 4), T1/T2 volumetric images (n = 2), magnetic resonance spectroscopy (MRS) (n = 1). One study utilized two imaging methods (fMRI and T1 volumetric images). Neuroimaging techniques could provide valuable information regarding the effects of unilateral hearing loss on both auditory and non-auditory performance. fMRI-studies showing a bilateral BOLD-response in patients with unilateral hearing loss have not yet been followed by DTI studies confirming their microstructural correlates. In addition, the review shows that an auditory modality-specific deficit could affect multi-modal brain regions and their connections. Copyright © 2015 Elsevier B.V. All rights reserved.
[Language Functions in the Frontal Association Area: Brain Mechanisms That Create Language].
Yamamoto, Kayako; Sakai, Kuniyoshi L
2016-11-01
Broca's area is known to be critically involved in language processing for more than 150 years. Recent neuroimaging techniques, including functional magnetic resonance imaging (fMRI) and diffusion MRI, enabled the subdivision of Broca's area based on both functional and anatomical aspects. Networks among the frontal association areas, especially the left inferior frontal gyrus (IFG), and other cortical regions in the temporal/parietal association areas, are also important for language-related information processing. Here, we review how neuroimaging studies, combined with research paradigms based on theoretical linguistics, have contributed to clarifying the critical roles of the left IFG in syntactic processing and those of language-related networks, including cortical and cerebellar regions.
Neuropsychological and neuroimaging underpinnings of schizoaffective disorder: a systematic review.
Madre, M; Canales-Rodríguez, E J; Ortiz-Gil, J; Murru, A; Torrent, C; Bramon, E; Perez, V; Orth, M; Brambilla, P; Vieta, E; Amann, B L
2016-07-01
The neurobiological basis and nosological status of schizoaffective disorder remains elusive and controversial. This study provides a systematic review of neurocognitive and neuroimaging findings in the disorder. A comprehensive literature search was conducted via PubMed, ScienceDirect, Scopus and Web of Knowledge (from 1949 to 31st March 2015) using the keyword 'schizoaffective disorder' and any of the following terms: 'neuropsychology', 'cognition', 'structural neuroimaging', 'functional neuroimaging', 'multimodal', 'DTI' and 'VBM'. Only studies that explicitly examined a well defined sample, or subsample, of patients with schizoaffective disorder were included. Twenty-two of 43 neuropsychological and 19 of 51 neuroimaging articles fulfilled inclusion criteria. We found a general trend towards schizophrenia and schizoaffective disorder being related to worse cognitive performance than bipolar disorder. Grey matter volume loss in schizoaffective disorder is also more comparable to schizophrenia than to bipolar disorder which seems consistent across further neuroimaging techniques. Neurocognitive and neuroimaging abnormalities in schizoaffective disorder resemble more schizophrenia than bipolar disorder. This is suggestive for schizoaffective disorder being a subtype of schizophrenia or being part of the continuum spectrum model of psychosis, with schizoaffective disorder being more skewed towards schizophrenia than bipolar disorder. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Sidhu, Meneka Kaur; Duncan, John S; Sander, Josemir W
2018-05-17
Epilepsy neuroimaging is important for detecting the seizure onset zone, predicting and preventing deficits from surgery and illuminating mechanisms of epileptogenesis. An aspiration is to integrate imaging and genetic biomarkers to enable personalized epilepsy treatments. The ability to detect lesions, particularly focal cortical dysplasia and hippocampal sclerosis, is increased using ultra high-field imaging and postprocessing techniques such as automated volumetry, T2 relaxometry, voxel-based morphometry and surface-based techniques. Statistical analysis of PET and single photon emission computer tomography (STATISCOM) are superior to qualitative analysis alone in identifying focal abnormalities in MRI-negative patients. These methods have also been used to study mechanisms of epileptogenesis and pharmacoresistance.Recent language fMRI studies aim to localize, and also lateralize language functions. Memory fMRI has been recommended to lateralize mnemonic function and predict outcome after surgery in temporal lobe epilepsy. Combinations of structural, functional and post-processing methods have been used in multimodal and machine learning models to improve the identification of the seizure onset zone and increase understanding of mechanisms underlying structural and functional aberrations in epilepsy.
The 100 most-cited articles in neuroimaging: A bibliometric analysis.
Kim, Hye Jeong; Yoon, Dae Young; Kim, Eun Soo; Lee, Kwanseop; Bae, Jong Seok; Lee, Ju-Hun
2016-10-01
The purpose of our study was to identify and characterize the 100 most-cited articles in neuroimaging. Based on the database of Journal Citation Reports, we selected 669 journals that were considered as potential outlets for neuroimaging articles. The Web of Science search tools were used to identify the 100 most-cited articles relevant to neuroimaging within the selected journals. The following information was recorded for each article: publication year, journal, category and impact factor of journal, number of citations, number of annual citations, authorship, department, institution, country, article type, imaging technique used, and topic. The 100 most-cited articles in neuroimaging were published between 1980 and 2012, with 1995-2004 producing 69 articles. Citations ranged from 4384 to 673 and annual citations ranged from 313.1 to 24.9. The majority of articles were published in radiology/imaging journals (n=75), originated in the United States (n=58), were original articles (n=63), used MRI as imaging modality (n=85), and dealt with imaging technique (n=45). The Oxford Centre for Functional Magnetic Resonance Imaging of the Brain at John Radcliffe Hospital (n=10) was the leading institutions and Karl J. Friston (n=11) was the most prolific author. Our study presents a detailed list and an analysis of the 100 most-cited articles in the field of neuroimaging, which provides an insight into historical developments and allows for recognition of the important advances in this field. Copyright © 2016 Elsevier Inc. All rights reserved.
Mapping brain function in freely moving subjects
Holschneider, Daniel P.; Maarek, Jean-Michel I.
2014-01-01
Expression of many fundamental mammalian behaviors such as, for example, aggression, mating, foraging or social behaviors, depend on locomotor activity. A central dilemma in the functional neuroimaging of these behaviors has been the fact that conventional neuroimaging techniques generally rely on immobilization of the subject, which extinguishes all but the simplest activity. Ideally, imaging could occur in freely moving subjects, while presenting minimal interference with the subject’s natural behavior. Here we provide an overview of several approaches that have been undertaken in the past to achieve this aim in both tethered and freely moving animals, as well as in nonrestrained human subjects. Applications of specific radiotracers to single photon emission computed tomography and positron emission tomography are discussed in which brain activation is imaged after completion of the behavioral task and capture of the tracer. Potential applications to clinical neuropsychiatry are discussed, as well as challenges inherent to constraint-free functional neuroimaging. Future applications of these methods promise to increase our understanding of the neural circuits underlying mammalian behavior in health and disease. PMID:15465134
Assessing Language Dominance with Functional MRI: The Role of Control Tasks and Statistical Analysis
ERIC Educational Resources Information Center
Dodoo-Schittko, Frank; Rosengarth, Katharina; Doenitz, Christian; Greenlee, Mark W.
2012-01-01
There is a discrepancy between the brain regions revealed by functional neuroimaging techniques and those brain regions where a loss of function, either by lesion or by electrocortical stimulation, induces language disorders. To differentiate between essential and non-essential language-related processes, we investigated the effects of linguistic…
Combined neurostimulation and neuroimaging in cognitive neuroscience: past, present, and future.
Bestmann, Sven; Feredoes, Eva
2013-08-01
Modern neurostimulation approaches in humans provide controlled inputs into the operations of cortical regions, with highly specific behavioral consequences. This enables causal structure-function inferences, and in combination with neuroimaging, has provided novel insights into the basic mechanisms of action of neurostimulation on distributed networks. For example, more recent work has established the capacity of transcranial magnetic stimulation (TMS) to probe causal interregional influences, and their interaction with cognitive state changes. Combinations of neurostimulation and neuroimaging now face the challenge of integrating the known physiological effects of neurostimulation with theoretical and biological models of cognition, for example, when theoretical stalemates between opposing cognitive theories need to be resolved. This will be driven by novel developments, including biologically informed computational network analyses for predicting the impact of neurostimulation on brain networks, as well as novel neuroimaging and neurostimulation techniques. Such future developments may offer an expanded set of tools with which to investigate structure-function relationships, and to formulate and reconceptualize testable hypotheses about complex neural network interactions and their causal roles in cognition. © 2013 New York Academy of Sciences.
Making MR Imaging Child's Play - Pediatric Neuroimaging Protocol, Guidelines and Procedure
Raschle, Nora M.; Lee, Michelle; Buechler, Roman; Christodoulou, Joanna A.; Chang, Maria; Vakil, Monica; Stering, Patrice L.; Gaab, Nadine
2009-01-01
Within the last decade there has been an increase in the use of structural and functional magnetic resonance imaging (fMRI) to investigate the neural basis of human perception, cognition and behavior 1, 2. Moreover, this non-invasive imaging method has grown into a tool for clinicians and researchers to explore typical and atypical brain development. Although advances in neuroimaging tools and techniques are apparent, (f)MRI in young pediatric populations remains relatively infrequent 2. Practical as well as technical challenges when imaging children present clinicians and research teams with a unique set of problems 3, 2. To name just a few, the child participants are challenged by a need for motivation, alertness and cooperation. Anxiety may be an additional factor to be addressed. Researchers or clinicians need to consider time constraints, movement restriction, scanner background noise and unfamiliarity with the MR scanner environment2,4-10. A progressive use of functional and structural neuroimaging in younger age groups, however, could further add to our understanding of brain development. As an example, several research groups are currently working towards early detection of developmental disorders, potentially even before children present associated behavioral characteristics e.g.11. Various strategies and techniques have been reported as a means to ensure comfort and cooperation of young children during neuroimaging sessions. Play therapy 12, behavioral approaches 13, 14,15, 16-18 and simulation 19, the use of mock scanner areas 20,21, basic relaxation 22 and a combination of these techniques 23 have all been shown to improve the participant's compliance and thus MRI data quality. Even more importantly, these strategies have proven to increase the comfort of families and children involved 12. One of the main advances of such techniques for the clinical practice is the possibility of avoiding sedation or general anesthesia (GA) as a way to manage children's compliance during MR imaging sessions 19,20. In the current video report, we present a pediatric neuroimaging protocol with guidelines and procedures that have proven to be successful to date in young children. PMID:19684560
Neuroimaging the Effectiveness of Substance Use Disorder Treatments.
Cabrera, Elizabeth A; Wiers, Corinde E; Lindgren, Elsa; Miller, Gregg; Volkow, Nora D; Wang, Gene-Jack
2016-09-01
Neuroimaging techniques to measure the function and biochemistry of the human brain such as positron emission tomography (PET), proton magnetic resonance spectroscopy ((1)H MRS), and functional magnetic resonance imaging (fMRI), are powerful tools for assessing neurobiological mechanisms underlying the response to treatments in substance use disorders. Here, we review the neuroimaging literature on pharmacological and behavioral treatment in substance use disorder. We focus on neural effects of medications that reduce craving (e.g., naltrexone, bupropion hydrochloride, baclofen, methadone, varenicline) and that improve cognitive control (e.g., modafinil, N-acetylcysteine), of behavioral treatments for substance use disorders (e.g., cognitive bias modification training, virtual reality, motivational interventions) and neuromodulatory interventions such as neurofeedback and transcranial magnetic stimulation. A consistent finding for the effectiveness of therapeutic interventions identifies the improvement of executive control networks and the dampening of limbic activation, highlighting their values as targets for therapeutic interventions in substance use disorders.
Musical hallucinations: a brief review of functional neuroimaging findings.
Bernardini, Francesco; Attademo, Luigi; Blackmon, Karen; Devinsky, Orrin
2017-10-01
Musical hallucinations are uncommon phenomena characterized by intrusive and frequently distressful auditory musical percepts without an external source, often associated with hypoacusis, psychiatric illness, focal brain lesion, epilepsy, and intoxication/pharmacology. Their physiological basis is thought to involve diverse mechanisms, including "release" from normal sensory or inhibitory inputs as well as stimulation during seizures, or they can be produced by functional or structural disorders in diverse cortical and subcortical areas. The aim of this review is to further explore their pathophysiology, describing the functional neuroimaging findings regarding musical hallucinations. A literature search of the PubMed electronic database was conducted through to 29 December 2015. Search terms included "musical hallucinations" combined with the names of specific functional neuroimaging techniques. A total of 18 articles, all clinical case reports, providing data on 23 patients, comprised the set we reviewed. Diverse pathological processes and patient populations with musical hallucinations were included in the studies. Converging data from multiple studies suggest that the superior temporal sulcus is the most common site and that activation is the most common mechanism. Further neurobiological research is needed to clarify the pathophysiology of musical hallucinations.
[Methodological aspects of functional neuroimaging at high field strength: a critical review].
Scheef, L; Landsberg, M W; Boecker, H
2007-09-01
The last few years have proven that high field magnetic resonance imaging (MRI) is superior in nearly every way to conventional equipment up to 1.5 tesla (T). Following the global success of 3T-scanners in research institutes and medical practices, a new generation of MRI devices with field strengths of 7T and higher is now on the horizon. The introduction of ultra high fields has brought MRI technology closer to the physical limitations and increasingly greater costs are required to achieve this goal. This article provides a critical overview of the advantages and problems of functional neuroimaging using ultra high field strengths. This review is principally limited to T2*-based functional imaging techniques not dependent on contrast agents. The main issues include the significance of high field technology with respect to SNR, CNR, resolution, and sequences, as well as artifacts, noise exposure, and SAR. Of great relevance is the discussion of parallel imaging, which will presumably determine the further development of high and ultra high field strengths. Finally, the importance of high field strengths for functional neuroimaging is explained by selected publications.
Mind-Body Practices and the Adolescent Brain: Clinical Neuroimaging Studies.
Sharma, Anup; Newberg, Andrew B
Mind-Body practices constitute a large and diverse group of practices that can substantially affect neurophysiology in both healthy individuals and those with various psychiatric disorders. In spite of the growing literature on the clinical and physiological effects of mind-body practices, very little is known about their impact on central nervous system (CNS) structure and function in adolescents with psychiatric disorders. This overview highlights findings in a select group of mind-body practices including yoga postures, yoga breathing techniques and meditation practices. Mind-body practices offer novel therapeutic approaches for adolescents with psychiatric disorders. Findings from these studies provide insights into the design and implementation of neuroimaging studies for adolescents with psychiatric disorders. Clinical neuroimaging studies will be critical in understanding how different practices affect disease pathogenesis and symptomatology in adolescents. Neuroimaging of mind-body practices on adolescents with psychiatric disorders will certainly be an open and exciting area of investigation.
Val-Laillet, D; Aarts, E; Weber, B; Ferrari, M; Quaresima, V; Stoeckel, L E; Alonso-Alonso, M; Audette, M; Malbert, C H; Stice, E
2015-01-01
Functional, molecular and genetic neuroimaging has highlighted the existence of brain anomalies and neural vulnerability factors related to obesity and eating disorders such as binge eating or anorexia nervosa. In particular, decreased basal metabolism in the prefrontal cortex and striatum as well as dopaminergic alterations have been described in obese subjects, in parallel with increased activation of reward brain areas in response to palatable food cues. Elevated reward region responsivity may trigger food craving and predict future weight gain. This opens the way to prevention studies using functional and molecular neuroimaging to perform early diagnostics and to phenotype subjects at risk by exploring different neurobehavioral dimensions of the food choices and motivation processes. In the first part of this review, advantages and limitations of neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), positron emission tomography (PET), single photon emission computed tomography (SPECT), pharmacogenetic fMRI and functional near-infrared spectroscopy (fNIRS) will be discussed in the context of recent work dealing with eating behavior, with a particular focus on obesity. In the second part of the review, non-invasive strategies to modulate food-related brain processes and functions will be presented. At the leading edge of non-invasive brain-based technologies is real-time fMRI (rtfMRI) neurofeedback, which is a powerful tool to better understand the complexity of human brain-behavior relationships. rtfMRI, alone or when combined with other techniques and tools such as EEG and cognitive therapy, could be used to alter neural plasticity and learned behavior to optimize and/or restore healthy cognition and eating behavior. Other promising non-invasive neuromodulation approaches being explored are repetitive transcranial magnetic stimulation (rTMS) and transcranial direct-current stimulation (tDCS). Converging evidence points at the value of these non-invasive neuromodulation strategies to study basic mechanisms underlying eating behavior and to treat its disorders. Both of these approaches will be compared in light of recent work in this field, while addressing technical and practical questions. The third part of this review will be dedicated to invasive neuromodulation strategies, such as vagus nerve stimulation (VNS) and deep brain stimulation (DBS). In combination with neuroimaging approaches, these techniques are promising experimental tools to unravel the intricate relationships between homeostatic and hedonic brain circuits. Their potential as additional therapeutic tools to combat pharmacorefractory morbid obesity or acute eating disorders will be discussed, in terms of technical challenges, applicability and ethics. In a general discussion, we will put the brain at the core of fundamental research, prevention and therapy in the context of obesity and eating disorders. First, we will discuss the possibility to identify new biological markers of brain functions. Second, we will highlight the potential of neuroimaging and neuromodulation in individualized medicine. Third, we will introduce the ethical questions that are concomitant to the emergence of new neuromodulation therapies.
Val-Laillet, D.; Aarts, E.; Weber, B.; Ferrari, M.; Quaresima, V.; Stoeckel, L.E.; Alonso-Alonso, M.; Audette, M.; Malbert, C.H.; Stice, E.
2015-01-01
Functional, molecular and genetic neuroimaging has highlighted the existence of brain anomalies and neural vulnerability factors related to obesity and eating disorders such as binge eating or anorexia nervosa. In particular, decreased basal metabolism in the prefrontal cortex and striatum as well as dopaminergic alterations have been described in obese subjects, in parallel with increased activation of reward brain areas in response to palatable food cues. Elevated reward region responsivity may trigger food craving and predict future weight gain. This opens the way to prevention studies using functional and molecular neuroimaging to perform early diagnostics and to phenotype subjects at risk by exploring different neurobehavioral dimensions of the food choices and motivation processes. In the first part of this review, advantages and limitations of neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), positron emission tomography (PET), single photon emission computed tomography (SPECT), pharmacogenetic fMRI and functional near-infrared spectroscopy (fNIRS) will be discussed in the context of recent work dealing with eating behavior, with a particular focus on obesity. In the second part of the review, non-invasive strategies to modulate food-related brain processes and functions will be presented. At the leading edge of non-invasive brain-based technologies is real-time fMRI (rtfMRI) neurofeedback, which is a powerful tool to better understand the complexity of human brain–behavior relationships. rtfMRI, alone or when combined with other techniques and tools such as EEG and cognitive therapy, could be used to alter neural plasticity and learned behavior to optimize and/or restore healthy cognition and eating behavior. Other promising non-invasive neuromodulation approaches being explored are repetitive transcranial magnetic stimulation (rTMS) and transcranial direct-current stimulation (tDCS). Converging evidence points at the value of these non-invasive neuromodulation strategies to study basic mechanisms underlying eating behavior and to treat its disorders. Both of these approaches will be compared in light of recent work in this field, while addressing technical and practical questions. The third part of this review will be dedicated to invasive neuromodulation strategies, such as vagus nerve stimulation (VNS) and deep brain stimulation (DBS). In combination with neuroimaging approaches, these techniques are promising experimental tools to unravel the intricate relationships between homeostatic and hedonic brain circuits. Their potential as additional therapeutic tools to combat pharmacorefractory morbid obesity or acute eating disorders will be discussed, in terms of technical challenges, applicability and ethics. In a general discussion, we will put the brain at the core of fundamental research, prevention and therapy in the context of obesity and eating disorders. First, we will discuss the possibility to identify new biological markers of brain functions. Second, we will highlight the potential of neuroimaging and neuromodulation in individualized medicine. Third, we will introduce the ethical questions that are concomitant to the emergence of new neuromodulation therapies. PMID:26110109
Functional brain imaging in neuropsychology over the past 25 years.
Roalf, David R; Gur, Ruben C
2017-11-01
Outline effects of functional neuroimaging on neuropsychology over the past 25 years. Functional neuroimaging methods and studies will be described that provide a historical context, offer examples of the utility of neuroimaging in specific domains, and discuss the limitations and future directions of neuroimaging in neuropsychology. Tracking the history of publications on functional neuroimaging related to neuropsychology indicates early involvement of neuropsychologists in the development of these methodologies. Initial progress in neuropsychological application of functional neuroimaging has been hampered by costs and the exposure to ionizing radiation. With rapid evolution of functional methods-in particular functional MRI (fMRI)-neuroimaging has profoundly transformed our knowledge of the brain. Its current applications span the spectrum of normative development to clinical applications. The field is moving toward applying sophisticated statistical approaches that will help elucidate distinct neural activation networks associated with specific behavioral domains. The impact of functional neuroimaging on clinical neuropsychology is more circumscribed, but the prospects remain enticing. The theoretical insights and empirical findings of functional neuroimaging have been led by many neuropsychologists and have transformed the field of behavioral neuroscience. Thus far they have had limited effects on the clinical practices of neuropsychologists. Perhaps it is time to add training in functional neuroimaging to the clinical neuropsychologist's toolkit and from there to the clinic or bedside. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
[Seeking the aetiology of autistic spectrum disorder. Part 2: Functional neuroimaging].
Bryńska, Anita
2012-01-01
Multiple functional imaging techniques help to a better understanding of the neurobiological basis of autism-spectrum disorders (ASD). The early functional imaging studies on ASD focused on task-specific methods related to core symptom domains and explored patterns of activation in response to face processing, theory of mind tasks, language processing and executive function tasks. On the other hand, fMRI research in ASD focused on the development of functional connectivity methods and has provided evidence of alterations in cortical connectivity in ASD and establish autism as a disorder of under-connectivity among the brain regions participating in cortical networks. This atypical functional connectivity in ASD results in inefficiency and poor integration of processing in network connections to achieve task performance. The goal of this review is to summarise the actual neuroimaging functional data and examine their implication for understanding of the neurobiology of ASD.
A Bayesian spatial model for neuroimaging data based on biologically informed basis functions.
Huertas, Ismael; Oldehinkel, Marianne; van Oort, Erik S B; Garcia-Solis, David; Mir, Pablo; Beckmann, Christian F; Marquand, Andre F
2017-11-01
The dominant approach to neuroimaging data analysis employs the voxel as the unit of computation. While convenient, voxels lack biological meaning and their size is arbitrarily determined by the resolution of the image. Here, we propose a multivariate spatial model in which neuroimaging data are characterised as a linearly weighted combination of multiscale basis functions which map onto underlying brain nuclei or networks or nuclei. In this model, the elementary building blocks are derived to reflect the functional anatomy of the brain during the resting state. This model is estimated using a Bayesian framework which accurately quantifies uncertainty and automatically finds the most accurate and parsimonious combination of basis functions describing the data. We demonstrate the utility of this framework by predicting quantitative SPECT images of striatal dopamine function and we compare a variety of basis sets including generic isotropic functions, anatomical representations of the striatum derived from structural MRI, and two different soft functional parcellations of the striatum derived from resting-state fMRI (rfMRI). We found that a combination of ∼50 multiscale functional basis functions accurately represented the striatal dopamine activity, and that functional basis functions derived from an advanced parcellation technique known as Instantaneous Connectivity Parcellation (ICP) provided the most parsimonious models of dopamine function. Importantly, functional basis functions derived from resting fMRI were more accurate than both structural and generic basis sets in representing dopamine function in the striatum for a fixed model order. We demonstrate the translational validity of our framework by constructing classification models for discriminating parkinsonian disorders and their subtypes. Here, we show that ICP approach is the only basis set that performs well across all comparisons and performs better overall than the classical voxel-based approach. This spatial model constitutes an elegant alternative to voxel-based approaches in neuroimaging studies; not only are their atoms biologically informed, they are also adaptive to high resolutions, represent high dimensions efficiently, and capture long-range spatial dependencies, which are important and challenging objectives for neuroimaging data. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Rupawala, Mohammed; Dehghani, Hamid; Lucas, Samuel J. E.; Tino, Peter; Cruse, Damian
2018-01-01
Qualitative clinical assessments of the recovery of awareness after severe brain injury require an assessor to differentiate purposeful behavior from spontaneous behavior. As many such behaviors are minimal and inconsistent, behavioral assessments are susceptible to diagnostic errors. Advanced neuroimaging tools can bypass behavioral responsiveness and reveal evidence of covert awareness and cognition within the brains of some patients, thus providing a means for more accurate diagnoses, more accurate prognoses, and, in some instances, facilitated communication. The majority of reports to date have employed the neuroimaging methods of functional magnetic resonance imaging, positron emission tomography, and electroencephalography (EEG). However, each neuroimaging method has its own advantages and disadvantages (e.g., signal resolution, accessibility, etc.). Here, we describe a burgeoning technique of non-invasive optical neuroimaging—functional near-infrared spectroscopy (fNIRS)—and review its potential to address the clinical challenges of prolonged disorders of consciousness. We also outline the potential for simultaneous EEG to complement the fNIRS signal and suggest the future directions of research that are required in order to realize its clinical potential. PMID:29872420
Neuroimaging studies of social cognition in schizophrenia.
Fujiwara, Hironobu; Yassin, Walid; Murai, Toshiya
2015-05-01
Impaired social cognition is considered a core contributor to unfavorable psychosocial functioning in schizophrenia. Rather than being a unitary process, social cognition is a collection of multifaceted processes that recruit multiple brain structures, thus structural and functional neuroimaging techniques are ideal methodologies for revealing the underlying pathophysiology of impaired social cognition. Many neuroimaging studies have suggested that in addition to white-matter deficits, schizophrenia is associated with decreased gray-matter volume in multiple brain areas, especially fronto-temporal and limbic regions. However, few schizophrenia studies have examined associations between brain abnormalities and social cognitive disabilities. During the last decade, we have investigated structural brain abnormalities in schizophrenia using high-resolution magnetic resonance imaging, and our findings have been confirmed by us and others. By assessing different types of social cognitive abilities, structural abnormalities in multiple brain regions have been found to be associated with disabilities in social cognition, such as recognition of facial emotion, theory of mind, and empathy. These structural deficits have also been associated with alexithymia and quality of life in ways that are closely related to the social cognitive disabilities found in schizophrenia. Here, we overview a series of neuroimaging studies from our laboratory that exemplify current research into this topic, and discuss how it can be further tackled using recent advances in neuroimaging technology. © 2014 The Authors. Psychiatry and Clinical Neurosciences © 2014 Japanese Society of Psychiatry and Neurology.
Single photon emission computed tomography (SPECT) in epilepsy
DOE Office of Scientific and Technical Information (OSTI.GOV)
Leroy, R.F.
1991-12-31
Epilepsy is a common neurologic disorder which has just begun to be studied with single photon emission computerized tomography (SPECT). Epilepsy usually is studied with electroencephalographic (EEG) techniques that demonstrate the physiologic changes that occur during seizures, and with neuroimaging techniques that show the brain structures where seizures originate. Neither method alone has been adequate to describe the pathophysiology of the patient with epilepsy. EEG techniques lack anatomic sensitivity, and there are no structural abnormalities shown by neuroimaging which are specific for epilepsy. Functional imaging (FI) has developed as a physiologic tool with anatomic sensitivity, and SPECT has been promotedmore » as a FI technique because of its potentially wide availability. However, SPECT is early in its development and its clinical utility for epilepsy still has to be demonstrated. To understand this role of SPECT, consideration must be given to the pathophysiology of epilepsy, brain physiology, types of seizure, epileptic syndromes, and the SPECT technique itself. 44 refs., 2 tabs.« less
Horton, Megan K; Margolis, Amy E; Tang, Cheuk; Wright, Robert
2014-04-01
The prevalence of childhood neurodevelopmental disorders has been increasing over the last several decades. Prenatal and early childhood exposure to environmental toxicants is increasingly recognized as contributing to the growing rate of neurodevelopmental disorders. Very little information is known about the mechanistic processes by which environmental chemicals alter brain development. We review the recent advances in brain imaging modalities and discuss their application in epidemiologic studies of prenatal and early childhood exposure to environmental toxicants. Neuroimaging techniques (volumetric and functional MRI, diffusor tensor imaging, and magnetic resonance spectroscopy) have opened unprecedented access to study the developing human brain. These techniques are noninvasive and free of ionization radiation making them suitable for research applications in children. Using these techniques, we now understand much about structural and functional patterns in the typically developing brain. This knowledge allows us to investigate how prenatal exposure to environmental toxicants may alter the typical developmental trajectory. MRI is a powerful tool that allows in-vivo visualization of brain structure and function. Used in epidemiologic studies of environmental exposure, it offers the promise to causally link exposure with behavioral and cognitive manifestations and ultimately to inform programs to reduce exposure and mitigate adverse effects of exposure.
[Clinical application of functional near-infrared spectroscopy in rehabilitation medicine].
Mihara, Masahito; Yagura, Hajime; Hatakenaka, Megumi; Hattori, Noriaki; Miyai, Ichiro
2010-02-01
Functional near-infrared spectroscopy (fNIRS) is an effective tool to non-invasively investigate cerebral oxygenation and hemodynamics. fNIRS as well as other functional neuroimaging techniques including functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) have been used for investigating the neural mechanisms of functional recovery after a stroke or a traumatic brain injury. fNIRS has several advantages over other neuroimaging techniques in terms of clinical application in the field of rehabilitation medicine. In addition to its portability and low equipment cost, fNIRS does not require strict motion restriction during measurement, unlike other functional imaging techniques. Therefore, this technique enables the examination of cortical activation during physically dynamic activities, like gait or balance perturbation. Studies using fNIRS have revealed several implications for gait recovery after stroke. These studies have shown that the medial sensorimotor cortex (SMC) and the supplementary motor area (SMA) are mainly involved in steadying gait and that the prefrontal cortex (PFC) is involved in the adjustment of walking speed. In hemiparetic patients, lateralization of SMC activation during gait is reduced, and additional cortical activations in the premotor cortex and PFC during gait became evident after focused rehabilitation for several months. The cortical activation pattern may be modified after different types of rehabilitative interventions. These results imply that fNIRS data is a potential biomarker for functional recovery and the response to rehabilitative interventions. Although further studies are required, fNIRS might provide useful information for customizing rehabilitation programs in order to enhance functional recovery.
Predicting Age Using Neuroimaging: Innovative Brain Ageing Biomarkers.
Cole, James H; Franke, Katja
2017-12-01
The brain changes as we age and these changes are associated with functional deterioration and neurodegenerative disease. It is vital that we better understand individual differences in the brain ageing process; hence, techniques for making individualised predictions of brain ageing have been developed. We present evidence supporting the use of neuroimaging-based 'brain age' as a biomarker of an individual's brain health. Increasingly, research is showing how brain disease or poor physical health negatively impacts brain age. Importantly, recent evidence shows that having an 'older'-appearing brain relates to advanced physiological and cognitive ageing and the risk of mortality. We discuss controversies surrounding brain age and highlight emerging trends such as the use of multimodality neuroimaging and the employment of 'deep learning' methods. Copyright © 2017 Elsevier Ltd. All rights reserved.
Structured illumination diffuse optical tomography for noninvasive functional neuroimaging in mice.
Reisman, Matthew D; Markow, Zachary E; Bauer, Adam Q; Culver, Joseph P
2017-04-01
Optical intrinsic signal (OIS) imaging has been a powerful tool for capturing functional brain hemodynamics in rodents. Recent wide field-of-view implementations of OIS have provided efficient maps of functional connectivity from spontaneous brain activity in mice. However, OIS requires scalp retraction and is limited to superficial cortical tissues. Diffuse optical tomography (DOT) techniques provide noninvasive imaging, but previous DOT systems for rodent neuroimaging have been limited either by sparse spatial sampling or by slow speed. Here, we develop a DOT system with asymmetric source-detector sampling that combines the high-density spatial sampling (0.4 mm) detection of a scientific complementary metal-oxide-semiconductor camera with the rapid (2 Hz) imaging of a few ([Formula: see text]) structured illumination (SI) patterns. Analysis techniques are developed to take advantage of the system's flexibility and optimize trade-offs among spatial sampling, imaging speed, and signal-to-noise ratio. An effective source-detector separation for the SI patterns was developed and compared with light intensity for a quantitative assessment of data quality. The light fall-off versus effective distance was also used for in situ empirical optimization of our light model. We demonstrated the feasibility of this technique by noninvasively mapping the functional response in the somatosensory cortex of the mouse following electrical stimulation of the forepaw.
ARIANNA: A research environment for neuroimaging studies in autism spectrum disorders.
Retico, Alessandra; Arezzini, Silvia; Bosco, Paolo; Calderoni, Sara; Ciampa, Alberto; Coscetti, Simone; Cuomo, Stefano; De Santis, Luca; Fabiani, Dario; Fantacci, Maria Evelina; Giuliano, Alessia; Mazzoni, Enrico; Mercatali, Pietro; Miscali, Giovanni; Pardini, Massimiliano; Prosperi, Margherita; Romano, Francesco; Tamburini, Elena; Tosetti, Michela; Muratori, Filippo
2017-08-01
The complexity and heterogeneity of Autism Spectrum Disorders (ASD) require the implementation of dedicated analysis techniques to obtain the maximum from the interrelationship among many variables that describe affected individuals, spanning from clinical phenotypic characterization and genetic profile to structural and functional brain images. The ARIANNA project has developed a collaborative interdisciplinary research environment that is easily accessible to the community of researchers working on ASD (https://arianna.pi.infn.it). The main goals of the project are: to analyze neuroimaging data acquired in multiple sites with multivariate approaches based on machine learning; to detect structural and functional brain characteristics that allow the distinguishing of individuals with ASD from control subjects; to identify neuroimaging-based criteria to stratify the population with ASD to support the future development of personalized treatments. Secure data handling and storage are guaranteed within the project, as well as the access to fast grid/cloud-based computational resources. This paper outlines the web-based architecture, the computing infrastructure and the collaborative analysis workflows at the basis of the ARIANNA interdisciplinary working environment. It also demonstrates the full functionality of the research platform. The availability of this innovative working environment for analyzing clinical and neuroimaging information of individuals with ASD is expected to support researchers in disentangling complex data thus facilitating their interpretation. Copyright © 2017 Elsevier Ltd. All rights reserved.
Mind-Body Practices and the Adolescent Brain: Clinical Neuroimaging Studies
Sharma, Anup; Newberg, Andrew B
2016-01-01
Background Mind-Body practices constitute a large and diverse group of practices that can substantially affect neurophysiology in both healthy individuals and those with various psychiatric disorders. In spite of the growing literature on the clinical and physiological effects of mind-body practices, very little is known about their impact on central nervous system (CNS) structure and function in adolescents with psychiatric disorders. Method This overview highlights findings in a select group of mind-body practices including yoga postures, yoga breathing techniques and meditation practices. Results Mind-body practices offer novel therapeutic approaches for adolescents with psychiatric disorders. Findings from these studies provide insights into the design and implementation of neuroimaging studies for adolescents with psychiatric disorders. Conclusions Clinical neuroimaging studies will be critical in understanding how different practices affect disease pathogenesis and symptomatology in adolescents. Neuroimaging of mind-body practices on adolescents with psychiatric disorders will certainly be an open and exciting area of investigation. PMID:27347478
Structural and functional neural correlates of music perception.
Limb, Charles J
2006-04-01
This review article highlights state-of-the-art functional neuroimaging studies and demonstrates the novel use of music as a tool for the study of human auditory brain structure and function. Music is a unique auditory stimulus with properties that make it a compelling tool with which to study both human behavior and, more specifically, the neural elements involved in the processing of sound. Functional neuroimaging techniques represent a modern and powerful method of investigation into neural structure and functional correlates in the living organism. These methods have demonstrated a close relationship between the neural processing of music and language, both syntactically and semantically. Greater neural activity and increased volume of gray matter in Heschl's gyrus has been associated with musical aptitude. Activation of Broca's area, a region traditionally considered to subserve language, is important in interpreting whether a note is on or off key. The planum temporale shows asymmetries that are associated with the phenomenon of perfect pitch. Functional imaging studies have also demonstrated activation of primitive emotional centers such as ventral striatum, midbrain, amygdala, orbitofrontal cortex, and ventral medial prefrontal cortex in listeners of moving musical passages. In addition, studies of melody and rhythm perception have elucidated mechanisms of hemispheric specialization. These studies show the power of music and functional neuroimaging to provide singularly useful tools for the study of brain structure and function.
Batalla, Albert; Bhattacharyya, Sagnik; Yücel, Murat; Fusar-Poli, Paolo; Crippa, Jose Alexandre; Nogué, Santiago; Torrens, Marta; Pujol, Jesús; Farré, Magí; Martin-Santos, Rocio
2013-01-01
The growing concern about cannabis use, the most commonly used illicit drug worldwide, has led to a significant increase in the number of human studies using neuroimaging techniques to determine the effect of cannabis on brain structure and function. We conducted a systematic review to assess the evidence of the impact of chronic cannabis use on brain structure and function in adults and adolescents. Papers published until August 2012 were included from EMBASE, Medline, PubMed and LILACS databases following a comprehensive search strategy and pre-determined set of criteria for article selection. Only neuroimaging studies involving chronic cannabis users with a matched control group were considered. One hundred and forty-two studies were identified, of which 43 met the established criteria. Eight studies were in adolescent population. Neuroimaging studies provide evidence of morphological brain alterations in both population groups, particularly in the medial temporal and frontal cortices, as well as the cerebellum. These effects may be related to the amount of cannabis exposure. Functional neuroimaging studies suggest different patterns of resting global and brain activity during the performance of several cognitive tasks both in adolescents and adults, which may indicate compensatory effects in response to chronic cannabis exposure. However, the results pointed out methodological limitations of the work conducted to date and considerable heterogeneity in the findings. Chronic cannabis use may alter brain structure and function in adult and adolescent population. Further studies should consider the use of convergent methodology, prospective large samples involving adolescent to adulthood subjects, and data-sharing initiatives.
Batalla, Albert; Bhattacharyya, Sagnik; Yücel, Murat; Fusar-Poli, Paolo; Crippa, Jose Alexandre; Nogué, Santiago; Torrens, Marta; Pujol, Jesús; Farré, Magí; Martin-Santos, Rocio
2013-01-01
Background The growing concern about cannabis use, the most commonly used illicit drug worldwide, has led to a significant increase in the number of human studies using neuroimaging techniques to determine the effect of cannabis on brain structure and function. We conducted a systematic review to assess the evidence of the impact of chronic cannabis use on brain structure and function in adults and adolescents. Methods Papers published until August 2012 were included from EMBASE, Medline, PubMed and LILACS databases following a comprehensive search strategy and pre-determined set of criteria for article selection. Only neuroimaging studies involving chronic cannabis users with a matched control group were considered. Results One hundred and forty-two studies were identified, of which 43 met the established criteria. Eight studies were in adolescent population. Neuroimaging studies provide evidence of morphological brain alterations in both population groups, particularly in the medial temporal and frontal cortices, as well as the cerebellum. These effects may be related to the amount of cannabis exposure. Functional neuroimaging studies suggest different patterns of resting global and brain activity during the performance of several cognitive tasks both in adolescents and adults, which may indicate compensatory effects in response to chronic cannabis exposure. Limitations However, the results pointed out methodological limitations of the work conducted to date and considerable heterogeneity in the findings. Conclusion Chronic cannabis use may alter brain structure and function in adult and adolescent population. Further studies should consider the use of convergent methodology, prospective large samples involving adolescent to adulthood subjects, and data-sharing initiatives. PMID:23390554
Integration of Network Topological and Connectivity Properties for Neuroimaging Classification
Jie, Biao; Gao, Wei; Wang, Qian; Wee, Chong-Yaw
2014-01-01
Rapid advances in neuroimaging techniques have provided an efficient and noninvasive way for exploring the structural and functional connectivity of the human brain. Quantitative measurement of abnormality of brain connectivity in patients with neurodegenerative diseases, such as mild cognitive impairment (MCI) and Alzheimer’s disease (AD), have also been widely reported, especially at a group level. Recently, machine learning techniques have been applied to the study of AD and MCI, i.e., to identify the individuals with AD/MCI from the healthy controls (HCs). However, most existing methods focus on using only a single property of a connectivity network, although multiple network properties, such as local connectivity and global topological properties, can potentially be used. In this paper, by employing multikernel based approach, we propose a novel connectivity based framework to integrate multiple properties of connectivity network for improving the classification performance. Specifically, two different types of kernels (i.e., vector-based kernel and graph kernel) are used to quantify two different yet complementary properties of the network, i.e., local connectivity and global topological properties. Then, multikernel learning (MKL) technique is adopted to fuse these heterogeneous kernels for neuroimaging classification. We test the performance of our proposed method on two different data sets. First, we test it on the functional connectivity networks of 12 MCI and 25 HC subjects. The results show that our method achieves significant performance improvement over those using only one type of network property. Specifically, our method achieves a classification accuracy of 91.9%, which is 10.8% better than those by single network-property-based methods. Then, we test our method for gender classification on a large set of functional connectivity networks with 133 infants scanned at birth, 1 year, and 2 years, also demonstrating very promising results. PMID:24108708
Systems Biology, Neuroimaging, Neuropsychology, Neuroconnectivity and Traumatic Brain Injury
Bigler, Erin D.
2016-01-01
The patient who sustains a traumatic brain injury (TBI) typically undergoes neuroimaging studies, usually in the form of computed tomography (CT) and magnetic resonance imaging (MRI). In most cases the neuroimaging findings are clinically assessed with descriptive statements that provide qualitative information about the presence/absence of visually identifiable abnormalities; though little if any of the potential information in a scan is analyzed in any quantitative manner, except in research settings. Fortunately, major advances have been made, especially during the last decade, in regards to image quantification techniques, especially those that involve automated image analysis methods. This review argues that a systems biology approach to understanding quantitative neuroimaging findings in TBI provides an appropriate framework for better utilizing the information derived from quantitative neuroimaging and its relation with neuropsychological outcome. Different image analysis methods are reviewed in an attempt to integrate quantitative neuroimaging methods with neuropsychological outcome measures and to illustrate how different neuroimaging techniques tap different aspects of TBI-related neuropathology. Likewise, how different neuropathologies may relate to neuropsychological outcome is explored by examining how damage influences brain connectivity and neural networks. Emphasis is placed on the dynamic changes that occur following TBI and how best to capture those pathologies via different neuroimaging methods. However, traditional clinical neuropsychological techniques are not well suited for interpretation based on contemporary and advanced neuroimaging methods and network analyses. Significant improvements need to be made in the cognitive and behavioral assessment of the brain injured individual to better interface with advances in neuroimaging-based network analyses. By viewing both neuroimaging and neuropsychological processes within a systems biology perspective could represent a significant advancement for the field. PMID:27555810
On whether mirror neurons play a significant role in processing affective prosody.
Ramachandra, Vijayachandra
2009-02-01
Several behavioral and neuroimaging studies have indicated that both right and left cortical structures and a few subcortical ones are involved in processing affective prosody. Recent investigations have shown that the mirror neuron system plays a crucial role in several higher-level functions such as empathy, theory of mind, language, etc., but no studies so far link the mirror neuron system with affective prosody. In this paper is a speculation that the mirror neuron system, which serves as a common neural substrate for different higher-level functions, may play a significant role in processing affective prosody via its connections with the limbic lobe. Actual research must apply electrophysiological and neuroimaging techniques to assess whether the mirror neuron systems underly affective prosody in humans.
Structural imaging in premanifest and manifest Huntington disease.
Scahill, Rachael I; Andre, Ralph; Tabrizi, Sarah J; Aylward, Elizabeth H
2017-01-01
Huntington disease (HD) neuropathology has a devastating effect on brain structure and consequently brain function; neuroimaging provides a means to assess these effects in gene carriers. In this chapter we first outline the unique utility of structural imaging in understanding HD and discuss some of the acquisition and analysis techniques currently available. We review the existing literature to summarize what we know so far about structural brain changes across the spectrum of disease from premanifest through to manifest disease. We then consider how these neuroimaging findings relate to patient function and nonimaging biomarkers, and can be used to predict disease onset. Finally we review the utility of imaging measures for assessment of treatment efficacy in clinical trials. Copyright © 2017 Elsevier B.V. All rights reserved.
Auriat, Angela M.; Neva, Jason L.; Peters, Sue; Ferris, Jennifer K.; Boyd, Lara A.
2015-01-01
Following stroke, the brain undergoes various stages of recovery where the central nervous system can reorganize neural circuitry (neuroplasticity) both spontaneously and with the aid of behavioral rehabilitation and non-invasive brain stimulation. Multiple neuroimaging techniques can characterize common structural and functional stroke-related deficits, and importantly, help predict recovery of function. Diffusion tensor imaging (DTI) typically reveals increased overall diffusivity throughout the brain following stroke, and is capable of indexing the extent of white matter damage. Magnetic resonance spectroscopy (MRS) provides an index of metabolic changes in surviving neural tissue after stroke, serving as a marker of brain function. The neural correlates of altered brain activity after stroke have been demonstrated by abnormal activation of sensorimotor cortices during task performance, and at rest, using functional magnetic resonance imaging (fMRI). Electroencephalography (EEG) has been used to characterize motor dysfunction in terms of increased cortical amplitude in the sensorimotor regions when performing upper limb movement, indicating abnormally increased cognitive effort and planning in individuals with stroke. Transcranial magnetic stimulation (TMS) work reveals changes in ipsilesional and contralesional cortical excitability in the sensorimotor cortices. The severity of motor deficits indexed using TMS has been linked to the magnitude of activity imbalance between the sensorimotor cortices. In this paper, we will provide a narrative review of data from studies utilizing DTI, MRS, fMRI, EEG, and brain stimulation techniques focusing on TMS and its combination with uni- and multimodal neuroimaging methods to assess recovery after stroke. Approaches that delineate the best measures with which to predict or positively alter outcomes will be highlighted. PMID:26579069
The addicted brain: imaging neurological complications of recreational drug abuse.
Montoya-Filardi, A; Mazón, M
Recreational drug abuse represents a serious public health problem. Neuroimaging traditionally played a secondary role in this scenario, where it was limited to detecting acute vascular events. However, thanks to advances in knowledge about disease and in morphological and functional imaging techniques, radiologists have now become very important in the diagnosis of acute and chronic neurological complications of recreational drug abuse. The main complications are neurovascular disease, infection, toxicometabolic disorders, and brain atrophy. The nonspecific symptoms and denial of abuse make the radiologist's involvement fundamental in the management of these patients. Neuroimaging makes it possible to detect early changes and to suggest an etiological diagnosis in cases with specific patterns of involvement. We aim to describe the pattern of abuse and the pathophysiological mechanisms of the drugs with the greatest neurological repercussions as well as to illustrate the depiction of the acute and chronic cerebral complications on conventional and functional imaging techniques. Copyright © 2016 SERAM. Publicado por Elsevier España, S.L.U. All rights reserved.
Neuroimaging: A Window to the Neurological Foundations of Learning and Behavior in Children.
ERIC Educational Resources Information Center
Lyon, G. Reid, Ed.; Rumsey, Judith M., Ed.
This book presents 11 papers on the use of neuroimaging technology in brain-related disorders. The text contains full-color neuroimaging scans and provides both theoretical and methodological explanations of the various neuroimaging techniques and their application to developmental disorders in children. The papers are grouped into three sections,…
The neuroimaging of sacred values.
Vilarroya, Oscar; Hilferty, Joseph
2013-09-01
Sacred (or protected) values (SVs) constitute core beliefs that define primary reference groups. There is significant research on SVs at a behavioral level, but their neural underpinnings are just beginning to be discovered. In this paper, we highlight the current state of neuroimaging research concerning SVs. Given that SVs are considered to be strongly motivated by moral principles, we first provide an outline of the neural circuits that have been found to be involved in moral cognition. We then review various neuroimaging studies that have explored the notion of SVs. Specifically, we concentrate on neuroimaging studies dealing with intergroup bias and those that focus on social norms, since these are two basic dimensions of SVs that have been studied with neuroimaging techniques. Finally, we review two studies that have directly addressed SVs with neuroimaging techniques, and we offer suggestions for further avenues of study. © 2013 New York Academy of Sciences.
Cognitive Abilities Independent of IQ Correlate with Regional Brain Structure
ERIC Educational Resources Information Center
Johnson, Wendy; Jung, Rex E.; Colom, Roberto; Haier, Richard J.
2008-01-01
There is increasing evidence relating psychometric measures of general intelligence and reasoning to regional brain structure and function assessed with a variety of neuroimaging techniques. Cognitive dimensions independent of general intelligence can also be identified psychometrically and studied for any neuroanatomical correlates. Here we…
Neuroanatomical Substrates of Social Cognition Dysfunction in Autism
ERIC Educational Resources Information Center
Pelphrey, Kevin; Adolphs, Ralph; Morris, James P.
2004-01-01
In this review article, we summarize recent progress toward understanding the neural structures and circuitry underlying dysfunctional social cognition in autism. We review selected studies from the growing literature that has used the functional neuroimaging techniques of cognitive neuroscience to map out the neuroanatomical substrates of social…
Neuroimaging is a novel tool to understand the impact of environmental chemicals on neurodevelopment
Horton, Megan K.; Margolis, Amy E.; Tang, Cheuk; Wright, Robert
2014-01-01
Purpose of review The prevalence of childhood neurodevelopmental disorders (ND) has been increasing over the last several decades. Prenatal and early childhood exposure to environmental toxicants is increasingly recognized as contributing to the growing rate of NDs. Very little is known about the mechanistic processes by which environmental chemicals alter brain development. We review recent advances in brain imaging modalities and discuss their application in epidemiologic studies of prenatal and early childhood exposure to environmental toxicants. Recent findings Neuroimaging techniques (volumetric and functional magnetic resonance imaging (MRI), diffusor tensor imaging (DTI), magnetic resonance spectroscopy (MRS)) have opened unprecedented access to study the developing human brain. These techniques are non-invasive and free of ionization radiation making them suitable for research applications in children. Using these techniques, we now understand much about structural and functional patterns in the typically developing brain. This knowledge allows us to investigate how prenatal exposure to environmental toxicants may alter the typical developmental trajectory. Summary MRI is a powerful tool that allows in vivo visualization of brain structure and function. Used in epidemiologic studies of environmental exposure, it offers the promise to causally link exposure with behavioral and cognitive manifestations and ultimately to inform programs to reduce exposure and mitigate adverse effects of exposure. PMID:24535497
Deprez, Sabine; Kesler, Shelli R; Saykin, Andrew J; Silverman, Daniel H S; de Ruiter, Michiel B; McDonald, Brenna C
2018-03-01
Cancer- and treatment-related cognitive changes have been a focus of increasing research since the early 1980s, with meta-analyses demonstrating poorer performance in cancer patients in cognitive domains including executive functions, processing speed, and memory. To facilitate collaborative efforts, in 2011 the International Cognition and Cancer Task Force (ICCTF) published consensus recommendations for core neuropsychological tests for studies of cancer populations. Over the past decade, studies have used neuroimaging techniques, including structural and functional magnetic resonance imaging (fMRI) and positron emission tomography, to examine the underlying brain basis for cancer- and treatment-related cognitive declines. As yet, however, there have been no consensus recommendations to guide researchers new to this field or to promote the ability to combine data sets. We first discuss important methodological issues with regard to neuroimaging study design, scanner considerations, and sequence selection, focusing on concerns relevant to cancer populations. We propose a minimum recommended set of sequences, including a high-resolution T1-weighted volume and a resting state fMRI scan. Additional advanced imaging sequences are discussed for consideration when feasible, including task-based fMRI and diffusion tensor imaging. Important image data processing and analytic considerations are also reviewed. These recommendations are offered to facilitate increased use of neuroimaging in studies of cancer- and treatment-related cognitive dysfunction. They are not intended to discourage investigator-initiated efforts to develop cutting-edge techniques, which will be helpful in advancing the state of the knowledge. Use of common imaging protocols will facilitate multicenter and data-pooling initiatives, which are needed to address critical mechanistic research questions.
Neuroimaging of Cerebrovascular Disease in the Aging Brain
Gupta, Ajay; Nair, Sreejit; Schweitzer, Andrew D.; Kishore, Sirish; Johnson, Carl E.; Comunale, Joseph P.; Tsiouris, Apostolos J.; Sanelli, Pina C.
2012-01-01
Cerebrovascular disease remains a significant public health burden with its greatest impact on the elderly population. Advances in neuroimaging techniques allow detailed and sophisticated evaluation of many manifestations of cerebrovascular disease in the brain parenchyma as well as in the intracranial and extracranial vasculature. These tools continue to contribute to our understanding of the multifactorial processes that occur in the age-dependent development of cerebrovascular disease. Structural abnormalities related to vascular disease in the brain and vessels have been well characterized with CT and MRI based techniques. We review some of the pathophysiologic mechanisms in the aging brain and cerebral vasculature and the related structural abnormalities detectable on neuroimaging, including evaluation of age-related white matter changes, atherosclerosis of the cerebral vasculature, and cerebral infarction. In addition, newer neuroimaging techniques, such as diffusion tensor imaging, perfusion techniques, and assessment of cerebrovascular reserve, are also reviewed, as these techniques can detect physiologic alterations which complement the morphologic changes that cause cerebrovascular disease in the aging brain.Further investigation of these advanced imaging techniques has potential application to the understanding and diagnosis of cerebrovascular disease in the elderly. PMID:23185721
Neuroscience, Education and Special Education
ERIC Educational Resources Information Center
Goswami, Usha
2004-01-01
The discipline of neuroscience draws from the fields of neurology, psychology, physiology and biology, but is best understood in the wider world as brain science. Of particular interest for education is the development of techniques for imaging the brain as it performs different cognitive functions. Cognitive neuroimaging has already led to…
ERIC Educational Resources Information Center
Cohen Kadosh, Kathrin; Linden, David E. J.; Lau, Jennifer Y. F.
2013-01-01
Adolescence is a period of profound change, which holds substantial developmental milestones, but also unique challenges to the individual. In this opinion paper, we highlight the potential of combining two recently developed behavioural and neural training techniques (cognitive bias modification and functional magnetic neuroimaging-based…
Riera, J; Aubert, E; Iwata, K; Kawashima, R; Wan, X; Ozaki, T
2005-01-01
The elucidation of the complex machinery used by the human brain to segregate and integrate information while performing high cognitive functions is a subject of imminent future consequences. The most significant contributions to date in this field, known as cognitive neuroscience, have been achieved by using innovative neuroimaging techniques, such as electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI), which measure variations in both the time and the space of some interpretable physical magnitudes. Extraordinary maps of cerebral activation involving function-restricted brain areas, as well as graphs of the functional connectivity between them, have been obtained from EEG and fMRI data by solving some spatio-temporal inverse problems, which constitutes a top-down approach. However, in many cases, a natural bridge between these maps/graphs and the causal physiological processes is lacking, leading to some misunderstandings in their interpretation. Recent advances in the comprehension of the underlying physiological mechanisms associated with different cerebral scales have provided researchers with an excellent scenario to develop sophisticated biophysical models that permit an integration of these neuroimage modalities, which must share a common aetiology. This paper proposes a bottom-up approach, involving physiological parameters in a specific mesoscopic dynamic equations system. Further observation equations encapsulating the relationship between the mesostates and the EEG/fMRI data are obtained on the basis of the physical foundations of these techniques. A methodology for the estimation of parameters from fused EEG/fMRI data is also presented. In this context, the concepts of activation and effective connectivity are carefully revised. This new approach permits us to examine and discuss some future prospects for the integration of multimodal neuroimages. PMID:16087446
TWave: High-Order Analysis of Functional MRI
Barnathan, Michael; Megalooikonomou, Vasileios; Faloutsos, Christos; Faro, Scott; Mohamed, Feroze B.
2011-01-01
The traditional approach to functional image analysis models images as matrices of raw voxel intensity values. Although such a representation is widely utilized and heavily entrenched both within neuroimaging and in the wider data mining community, the strong interactions among space, time, and categorical modes such as subject and experimental task inherent in functional imaging yield a dataset with “high-order” structure, which matrix models are incapable of exploiting. Reasoning across all of these modes of data concurrently requires a high-order model capable of representing relationships between all modes of the data in tandem. We thus propose to model functional MRI data using tensors, which are high-order generalizations of matrices equivalent to multidimensional arrays or data cubes. However, several unique challenges exist in the high-order analysis of functional medical data: naïve tensor models are incapable of exploiting spatiotemporal locality patterns, standard tensor analysis techniques exhibit poor efficiency, and mixtures of numeric and categorical modes of data are very often present in neuroimaging experiments. Formulating the problem of image clustering as a form of Latent Semantic Analysis and using the WaveCluster algorithm as a baseline, we propose a comprehensive hybrid tensor and wavelet framework for clustering, concept discovery, and compression of functional medical images which successfully addresses these challenges. Our approach reduced runtime and dataset size on a 9.3 GB finger opposition motor task fMRI dataset by up to 98% while exhibiting improved spatiotemporal coherence relative to standard tensor, wavelet, and voxel-based approaches. Our clustering technique was capable of automatically differentiating between the frontal areas of the brain responsible for task-related habituation and the motor regions responsible for executing the motor task, in contrast to a widely used fMRI analysis program, SPM, which only detected the latter region. Furthermore, our approach discovered latent concepts suggestive of subject handedness nearly 100x faster than standard approaches. These results suggest that a high-order model is an integral component to accurate scalable functional neuroimaging. PMID:21729758
Similarities and Differences in Neuroimaging.
Sun, Yan-Kun; Sun, Yan; Lin, Xiao; Lu, Lin; Shi, Jie
2017-01-01
Addiction is a chronically relapsing disease characterized by drug intoxication, craving, bingeing, and withdrawal with loss of control. An increasing number of studies have indicated that non-substance addiction, like internet addiction and pathological gambling, share clinical, phenomenological, and biological features with substance addiction. With the development of imaging technology in the past three decades, neuroimaging studies have provided information on the neurobiological effects, and revealed neurochemical and functional changes in the brains of both drug-addicted and non-substance addicted subjects. Imaging techniques play a more critical role in understanding the neuronal processes of addiction and will lead the direction in future research for medication development of addiction treatment, especially for non-substance addiction, which shares an increasing percentage of addiction disorder. This article will review the similarities and differences between substance and non-substance addiction based on neuroimaging studies that may provide clues for future study on these two main kinds of addiction, especially the growing non-substance addiction.
What We Know About the Brain Structure-Function Relationship.
Batista-García-Ramó, Karla; Fernández-Verdecia, Caridad Ivette
2018-04-18
How the human brain works is still a question, as is its implication with brain architecture: the non-trivial structure–function relationship. The main hypothesis is that the anatomic architecture conditions, but does not determine, the neural network dynamic. The functional connectivity cannot be explained only considering the anatomical substrate. This involves complex and controversial aspects of the neuroscience field and that the methods and methodologies to obtain structural and functional connectivity are not always rigorously applied. The goal of the present article is to discuss about the progress made to elucidate the structure–function relationship of the Central Nervous System, particularly at the brain level, based on results from human and animal studies. The current novel systems and neuroimaging techniques with high resolutive physio-structural capacity have brought about the development of an integral framework of different structural and morphometric tools such as image processing, computational modeling and graph theory. Different laboratories have contributed with in vivo, in vitro and computational/mathematical models to study the intrinsic neural activity patterns based on anatomical connections. We conclude that multi-modal techniques of neuroimaging are required such as an improvement on methodologies for obtaining structural and functional connectivity. Even though simulations of the intrinsic neural activity based on anatomical connectivity can reproduce much of the observed patterns of empirical functional connectivity, future models should be multifactorial to elucidate multi-scale relationships and to infer disorder mechanisms.
Labeling and tracking exosomes within the brain using gold nanoparticles
NASA Astrophysics Data System (ADS)
Betzer, Oshra; Perets, Nisim; Barnoy, Eran; Offen, Daniel; Popovtzer, Rachela
2018-02-01
Cell-to-cell communication system involves Exosomes, small, membrane-enveloped nanovesicles. Exosomes are evolving as effective therapeutic tools for different pathologies. These extracellular vesicles can bypass biological barriers such as the blood-brain barrier, and can function as powerful nanocarriers for drugs, proteins and gene therapeutics. However, to promote exosomes' therapy development, especially for brain pathologies, a better understanding of their mechanism of action, trafficking, pharmacokinetics and bio-distribution is needed. In this research, we established a new method for non-invasive in-vivo neuroimaging of mesenchymal stem cell (MSC)-derived exosomes, based on computed tomography (CT) imaging with glucose-coated gold nanoparticle (GNP) labeling. We demonstrated that the exosomes were efficiently and directly labeled with GNPs, via an energy-dependent mechanism. Additionally, we found the optimal parameters for exosome labeling and neuroimaging, wherein 5 nm GNPs enhanced labeling, and intranasal administration produced superior brain accumulation. We applied our technique in a mouse model of focal ischemia. Imaging and tracking of intranasally-administered GNP-labeled exosomes revealed specific accumulation and prolonged presence at the lesion area, up to 24 hrs. We propose that this novel exosome labeling and in-vivo neuroimaging technique can serve as a general platform for brain theranostics.
Fox, Kieran C R; Dixon, Matthew L; Nijeboer, Savannah; Girn, Manesh; Floman, James L; Lifshitz, Michael; Ellamil, Melissa; Sedlmeier, Peter; Christoff, Kalina
2016-06-01
Meditation is a family of mental practices that encompasses a wide array of techniques employing distinctive mental strategies. We systematically reviewed 78 functional neuroimaging (fMRI and PET) studies of meditation, and used activation likelihood estimation to meta-analyze 257 peak foci from 31 experiments involving 527 participants. We found reliably dissociable patterns of brain activation and deactivation for four common styles of meditation (focused attention, mantra recitation, open monitoring, and compassion/loving-kindness), and suggestive differences for three others (visualization, sense-withdrawal, and non-dual awareness practices). Overall, dissociable activation patterns are congruent with the psychological and behavioral aims of each practice. Some brain areas are recruited consistently across multiple techniques-including insula, pre/supplementary motor cortices, dorsal anterior cingulate cortex, and frontopolar cortex-but convergence is the exception rather than the rule. A preliminary effect-size meta-analysis found medium effects for both activations (d=0.59) and deactivations (d=-0.74), suggesting potential practical significance. Our meta-analysis supports the neurophysiological dissociability of meditation practices, but also raises many methodological concerns and suggests avenues for future research. Copyright © 2016 Elsevier Ltd. All rights reserved.
Robust biological parametric mapping: an improved technique for multimodal brain image analysis
NASA Astrophysics Data System (ADS)
Yang, Xue; Beason-Held, Lori; Resnick, Susan M.; Landman, Bennett A.
2011-03-01
Mapping the quantitative relationship between structure and function in the human brain is an important and challenging problem. Numerous volumetric, surface, region of interest and voxelwise image processing techniques have been developed to statistically assess potential correlations between imaging and non-imaging metrics. Recently, biological parametric mapping has extended the widely popular statistical parametric approach to enable application of the general linear model to multiple image modalities (both for regressors and regressands) along with scalar valued observations. This approach offers great promise for direct, voxelwise assessment of structural and functional relationships with multiple imaging modalities. However, as presented, the biological parametric mapping approach is not robust to outliers and may lead to invalid inferences (e.g., artifactual low p-values) due to slight mis-registration or variation in anatomy between subjects. To enable widespread application of this approach, we introduce robust regression and robust inference in the neuroimaging context of application of the general linear model. Through simulation and empirical studies, we demonstrate that our robust approach reduces sensitivity to outliers without substantial degradation in power. The robust approach and associated software package provides a reliable way to quantitatively assess voxelwise correlations between structural and functional neuroimaging modalities.
Jensen, Karin B.; Berna, Chantal; Loggia, Marco L.; Wasan, Ajay; Edwards, Robert R.; Gollub, Randy L.
2013-01-01
A large number of studies have provided evidence for the efficacy of psychological and other non-pharmacological interventions in the treatment of chronic pain. While these methods are increasingly used to treat pain, remarkably few studies focused on the exploration of their neural correlates. The aim of this article was to review the findings from neuroimaging studies that evaluated the neural response to distraction-based techniques, cognitive behavioral therapy (CBT), clinical hypnosis, mental imagery, physical therapy/exercise, biofeedback, and mirror therapy. To date, the results from studies that used neuroimaging to evaluate these methods have not been conclusive and the experimental methods have been suboptimal for assessing clinical pain. Still, several different psychological and non-pharmacological treatment modalities were associated with increased painrelated activations of executive cognitive brain regions, such as the ventral- and dorsolateral prefrontal cortex. There was also evidence for decreased pain-related activations in afferent pain regions and limbic structures. If future studies will address the technical and methodological challenges of today’s experiments, neuroimaging might have the potential of segregating the neural mechanisms of different treatment interventions and elucidate predictive and mediating factors for successful treatment outcomes. Evaluations of treatment-related brain changes (functional and structural) might also allow for sub-grouping of patients and help to develop individualized treatments. PMID:22445888
The Java Image Science Toolkit (JIST) for rapid prototyping and publishing of neuroimaging software.
Lucas, Blake C; Bogovic, John A; Carass, Aaron; Bazin, Pierre-Louis; Prince, Jerry L; Pham, Dzung L; Landman, Bennett A
2010-03-01
Non-invasive neuroimaging techniques enable extraordinarily sensitive and specific in vivo study of the structure, functional response and connectivity of biological mechanisms. With these advanced methods comes a heavy reliance on computer-based processing, analysis and interpretation. While the neuroimaging community has produced many excellent academic and commercial tool packages, new tools are often required to interpret new modalities and paradigms. Developing custom tools and ensuring interoperability with existing tools is a significant hurdle. To address these limitations, we present a new framework for algorithm development that implicitly ensures tool interoperability, generates graphical user interfaces, provides advanced batch processing tools, and, most importantly, requires minimal additional programming or computational overhead. Java-based rapid prototyping with this system is an efficient and practical approach to evaluate new algorithms since the proposed system ensures that rapidly constructed prototypes are actually fully-functional processing modules with support for multiple GUI's, a broad range of file formats, and distributed computation. Herein, we demonstrate MRI image processing with the proposed system for cortical surface extraction in large cross-sectional cohorts, provide a system for fully automated diffusion tensor image analysis, and illustrate how the system can be used as a simulation framework for the development of a new image analysis method. The system is released as open source under the Lesser GNU Public License (LGPL) through the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC).
The Java Image Science Toolkit (JIST) for Rapid Prototyping and Publishing of Neuroimaging Software
Lucas, Blake C.; Bogovic, John A.; Carass, Aaron; Bazin, Pierre-Louis; Prince, Jerry L.; Pham, Dzung
2010-01-01
Non-invasive neuroimaging techniques enable extraordinarily sensitive and specific in vivo study of the structure, functional response and connectivity of biological mechanisms. With these advanced methods comes a heavy reliance on computer-based processing, analysis and interpretation. While the neuroimaging community has produced many excellent academic and commercial tool packages, new tools are often required to interpret new modalities and paradigms. Developing custom tools and ensuring interoperability with existing tools is a significant hurdle. To address these limitations, we present a new framework for algorithm development that implicitly ensures tool interoperability, generates graphical user interfaces, provides advanced batch processing tools, and, most importantly, requires minimal additional programming or computational overhead. Java-based rapid prototyping with this system is an efficient and practical approach to evaluate new algorithms since the proposed system ensures that rapidly constructed prototypes are actually fully-functional processing modules with support for multiple GUI's, a broad range of file formats, and distributed computation. Herein, we demonstrate MRI image processing with the proposed system for cortical surface extraction in large cross-sectional cohorts, provide a system for fully automated diffusion tensor image analysis, and illustrate how the system can be used as a simulation framework for the development of a new image analysis method. The system is released as open source under the Lesser GNU Public License (LGPL) through the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC). PMID:20077162
Yanes, Julio A; Riedel, Michael C; Ray, Kimberly L; Kirkland, Anna E; Bird, Ryan T; Boeving, Emily R; Reid, Meredith A; Gonzalez, Raul; Robinson, Jennifer L; Laird, Angela R; Sutherland, Matthew T
2018-03-01
Lagging behind rapid changes to state laws, societal views, and medical practice is the scientific investigation of cannabis's impact on the human brain. While several brain imaging studies have contributed important insight into neurobiological alterations linked with cannabis use, our understanding remains limited. Here, we sought to delineate those brain regions that consistently demonstrate functional alterations among cannabis users versus non-users across neuroimaging studies using the activation likelihood estimation meta-analysis framework. In ancillary analyses, we characterized task-related brain networks that co-activate with cannabis-affected regions using data archived in a large neuroimaging repository, and then determined which psychological processes may be disrupted via functional decoding techniques. When considering convergent alterations among users, decreased activation was observed in the anterior cingulate cortex, which co-activated with frontal, parietal, and limbic areas and was linked with cognitive control processes. Similarly, decreased activation was observed in the dorsolateral prefrontal cortex, which co-activated with frontal and occipital areas and linked with attention-related processes. Conversely, increased activation among users was observed in the striatum, which co-activated with frontal, parietal, and other limbic areas and linked with reward processing. These meta-analytic outcomes indicate that cannabis use is linked with differential, region-specific effects across the brain.
ERIC Educational Resources Information Center
Gegenfurtner, Andreas; Kok, Ellen M.; van Geel, Koos; de Bruin, Anique B. H.; Sorger, Bettina
2017-01-01
Functional neuroimaging is a useful approach to study the neural correlates of visual perceptual expertise. The purpose of this paper is to review the functional-neuroimaging methods that have been implemented in previous research in this context. First, we will discuss research questions typically addressed in visual expertise research. Second,…
Yu, Ying; Sun, Qian; Yan, Lin-Feng; Hu, Yu-Chuan; Nan, Hai-Yan; Yang, Yang; Liu, Zhi-Cheng; Wang, Wen; Cui, Guang-Bin
2016-08-24
Type 2 diabetes mellitus (T2DM) is a risk factor for dementia. Mild cognitive impairment (MCI), an intermediary state between normal cognition and dementia, often occurs during the prodromal diabetic stage, making early diagnosis and intervention of MCI very important. Latest neuroimaging techniques revealed some underlying microstructure alterations for diabetic MCI, from certain aspects. But there still lacks an integrated multimodal MRI system to detect early neuroimaging changes in diabetic MCI patients. Thus, we intended to conduct a diagnostic trial using multimodal MRI techniques to detect early diabetic MCI that is determined by the Montreal Cognitive Assessment (MoCA). In this study, healthy controls, prodromal diabetes and diabetes subjects (53 subjects/group) aged 40-60 years will be recruited from the physical examination center of Tangdu Hospital. The neuroimaging and psychometric measurements will be repeated at a 0.5 year-interval for 2.5 years' follow-up. The primary outcome measures are 1) Microstructural and functional alterations revealed with multimodal MRI scans including structure magnetic resonance imaging (sMRI), resting state functional magnetic resonance imaging (rs-fMRI), diffusion kurtosis imaging (DKI), and three-dimensional pseudo-continuous arterial spin labeling (3D-pCASL); 2) Cognition evaluation with MoCA. The second outcome measures are obesity, metabolic characteristics, lifestyle and quality of life. The study will provide evidence for the potential use of multimodal MRI techniques with psychometric evaluation in diagnosing MCI at prodromal diabetic stage so as to help decision making in early intervention and improve the prognosis of T2DM. This study has been registered to ClinicalTrials.gov ( NCT02420470 ) on April 2, 2015 and published on July 29, 2015.
Gorgolewski, Krzysztof J; Auer, Tibor; Calhoun, Vince D; Craddock, R Cameron; Das, Samir; Duff, Eugene P; Flandin, Guillaume; Ghosh, Satrajit S; Glatard, Tristan; Halchenko, Yaroslav O; Handwerker, Daniel A; Hanke, Michael; Keator, David; Li, Xiangrui; Michael, Zachary; Maumet, Camille; Nichols, B Nolan; Nichols, Thomas E; Pellman, John; Poline, Jean-Baptiste; Rokem, Ariel; Schaefer, Gunnar; Sochat, Vanessa; Triplett, William; Turner, Jessica A; Varoquaux, Gaël; Poldrack, Russell A
2016-06-21
The development of magnetic resonance imaging (MRI) techniques has defined modern neuroimaging. Since its inception, tens of thousands of studies using techniques such as functional MRI and diffusion weighted imaging have allowed for the non-invasive study of the brain. Despite the fact that MRI is routinely used to obtain data for neuroscience research, there has been no widely adopted standard for organizing and describing the data collected in an imaging experiment. This renders sharing and reusing data (within or between labs) difficult if not impossible and unnecessarily complicates the application of automatic pipelines and quality assurance protocols. To solve this problem, we have developed the Brain Imaging Data Structure (BIDS), a standard for organizing and describing MRI datasets. The BIDS standard uses file formats compatible with existing software, unifies the majority of practices already common in the field, and captures the metadata necessary for most common data processing operations.
Gorgolewski, Krzysztof J.; Auer, Tibor; Calhoun, Vince D.; Craddock, R. Cameron; Das, Samir; Duff, Eugene P.; Flandin, Guillaume; Ghosh, Satrajit S.; Glatard, Tristan; Halchenko, Yaroslav O.; Handwerker, Daniel A.; Hanke, Michael; Keator, David; Li, Xiangrui; Michael, Zachary; Maumet, Camille; Nichols, B. Nolan; Nichols, Thomas E.; Pellman, John; Poline, Jean-Baptiste; Rokem, Ariel; Schaefer, Gunnar; Sochat, Vanessa; Triplett, William; Turner, Jessica A.; Varoquaux, Gaël; Poldrack, Russell A.
2016-01-01
The development of magnetic resonance imaging (MRI) techniques has defined modern neuroimaging. Since its inception, tens of thousands of studies using techniques such as functional MRI and diffusion weighted imaging have allowed for the non-invasive study of the brain. Despite the fact that MRI is routinely used to obtain data for neuroscience research, there has been no widely adopted standard for organizing and describing the data collected in an imaging experiment. This renders sharing and reusing data (within or between labs) difficult if not impossible and unnecessarily complicates the application of automatic pipelines and quality assurance protocols. To solve this problem, we have developed the Brain Imaging Data Structure (BIDS), a standard for organizing and describing MRI datasets. The BIDS standard uses file formats compatible with existing software, unifies the majority of practices already common in the field, and captures the metadata necessary for most common data processing operations. PMID:27326542
Neuroimaging with functional near infrared spectroscopy: From formation to interpretation
NASA Astrophysics Data System (ADS)
Herrera-Vega, Javier; Treviño-Palacios, Carlos G.; Orihuela-Espina, Felipe
2017-09-01
Functional Near Infrared Spectroscopy (fNIRS) is gaining momentum as a functional neuroimaging modality to investigate the cerebral hemodynamics subsequent to neural metabolism. As other neuroimaging modalities, it is neuroscience's tool to understand brain systems functions at behaviour and cognitive levels. To extract useful knowledge from functional neuroimages it is critical to understand the series of transformations applied during the process of the information retrieval and how they bound the interpretation. This process starts with the irradiation of the head tissues with infrared light to obtain the raw neuroimage and proceeds with computational and statistical analysis revealing hidden associations between pixels intensities and neural activity encoded to end up with the explanation of some particular aspect regarding brain function.To comprehend the overall process involved in fNIRS there is extensive literature addressing each individual step separately. This paper overviews the complete transformation sequence through image formation, reconstruction and analysis to provide an insight of the final functional interpretation.
Mood and neural correlates of excessive daytime sleepiness in Parkinson's disease.
Wen, M-C; Chan, L L; Tan, L C S; Tan, E K
2017-08-01
For patients with Parkinson's disease (PD), excessive daytime sleepiness (PD-EDS) is a debilitating non-motor symptom and may be affected by mood symptoms, especially depression and anxiety. Few neuroimaging works have attempted to identify the neural features of PD-EDS, but various findings were reported. The purpose of this study was to systematically review the literature on mood and neuroimaging correlates of PD-EDS. A MEDLINE, PubMed, EMBASE, and PsycInfo search for peer-reviewed original research articles on depression, anxiety, and neuroimaging in PD-EDS identified 26 studies on depression, nine on anxiety, and eight on neuroimaging. Half of the studies reported greater depression in PD-EDS-positive patients compared with PD-EDS-negative patients. There was a significantly positive correlation between depression and PD-EDS. Limited studies on anxiety in PD-EDS suggested a weak correlation between anxiety and EDS. For depression and anxiety, the effect sizes were medium when EDS was subjectively measured, but became small when EDS was objective measured. Current neuroimaging studies generally suggested diminished neural structural and functional features (eg, brain volume, white matter integrity as indicated by fractional anisotropy, and cerebral metabolism) in patients with PD-EDS. Future studies should apply objective and subjective measures of mood symptoms and EDS and improve the neuroimaging methodology via using multimodal techniques and whole-brain analysis to provide new clues on the mood and neural correlates of PD-EDS. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Cognitive neuroimaging: cognitive science out of the armchair.
de Zubicaray, Greig I
2006-04-01
Cognitive scientists were not quick to embrace the functional neuroimaging technologies that emerged during the late 20th century. In this new century, cognitive scientists continue to question, not unreasonably, the relevance of functional neuroimaging investigations that fail to address questions of interest to cognitive science. However, some ultra-cognitive scientists assert that these experiments can never be of relevance to the study of cognition. Their reasoning reflects an adherence to a functionalist philosophy that arbitrarily and purposefully distinguishes mental information-processing systems from brain or brain-like operations. This article addresses whether data from properly conducted functional neuroimaging studies can inform and subsequently constrain the assumptions of theoretical cognitive models. The article commences with a focus upon the functionalist philosophy espoused by the ultra-cognitive scientists, contrasting it with the materialist philosophy that motivates both cognitive neuroimaging investigations and connectionist modelling of cognitive systems. Connectionism and cognitive neuroimaging share many features, including an emphasis on unified cognitive and neural models of systems that combine localist and distributed representations. The utility of designing cognitive neuroimaging studies to test (primarily) connectionist models of cognitive phenomena is illustrated using data from functional magnetic resonance imaging (fMRI) investigations of language production and episodic memory.
Erdeniz, Burak; Rohe, Tim; Done, John; Seidler, Rachael D
2013-01-01
Conventional neuroimaging techniques provide information about condition-related changes of the BOLD (blood-oxygen-level dependent) signal, indicating only where and when the underlying cognitive processes occur. Recently, with the help of a new approach called "model-based" functional neuroimaging (fMRI), researchers are able to visualize changes in the internal variables of a time varying learning process, such as the reward prediction error or the predicted reward value of a conditional stimulus. However, despite being extremely beneficial to the imaging community in understanding the neural correlates of decision variables, a model-based approach to brain imaging data is also methodologically challenging due to the multicollinearity problem in statistical analysis. There are multiple sources of multicollinearity in functional neuroimaging including investigations of closely related variables and/or experimental designs that do not account for this. The source of multicollinearity discussed in this paper occurs due to correlation between different subjective variables that are calculated very close in time. Here, we review methodological approaches to analyzing such data by discussing the special case of separating the reward prediction error signal from reward outcomes.
Kobyakov, G L; Lubnin, A Yu; Kulikov, A S; Gavrilov, A G; Goryaynov, S A; Poddubskiy, A A; Lodygina, K S
2016-01-01
Awake craniotomy is a neurosurgical intervention aimed at identifying and preserving the eloquent functional brain areas during resection of tumors located near the cortical and subcortical language centers. This article provides a review of the modern literature devoted to the issue. The anatomical rationale and data of preoperative functional neuroimaging, intraoperative electrophysiological monitoring, and neuropsychological tests as well as the strategy of active surgical intervention are presented. Awake craniotomy is a rapidly developing technique aimed at both preserving speech and motor functions and improving our knowledge in the field of speech psychophysiology.
Can Emotional and Behavioral Dysregulation in Youth Be Decoded from Functional Neuroimaging?
Portugal, Liana C L; Rosa, Maria João; Rao, Anil; Bebko, Genna; Bertocci, Michele A; Hinze, Amanda K; Bonar, Lisa; Almeida, Jorge R C; Perlman, Susan B; Versace, Amelia; Schirda, Claudiu; Travis, Michael; Gill, Mary Kay; Demeter, Christine; Diwadkar, Vaibhav A; Ciuffetelli, Gary; Rodriguez, Eric; Forbes, Erika E; Sunshine, Jeffrey L; Holland, Scott K; Kowatch, Robert A; Birmaher, Boris; Axelson, David; Horwitz, Sarah M; Arnold, Eugene L; Fristad, Mary A; Youngstrom, Eric A; Findling, Robert L; Pereira, Mirtes; Oliveira, Leticia; Phillips, Mary L; Mourao-Miranda, Janaina
2016-01-01
High comorbidity among pediatric disorders characterized by behavioral and emotional dysregulation poses problems for diagnosis and treatment, and suggests that these disorders may be better conceptualized as dimensions of abnormal behaviors. Furthermore, identifying neuroimaging biomarkers related to dimensional measures of behavior may provide targets to guide individualized treatment. We aimed to use functional neuroimaging and pattern regression techniques to determine whether patterns of brain activity could accurately decode individual-level severity on a dimensional scale measuring behavioural and emotional dysregulation at two different time points. A sample of fifty-seven youth (mean age: 14.5 years; 32 males) was selected from a multi-site study of youth with parent-reported behavioral and emotional dysregulation. Participants performed a block-design reward paradigm during functional Magnetic Resonance Imaging (fMRI). Pattern regression analyses consisted of Relevance Vector Regression (RVR) and two cross-validation strategies implemented in the Pattern Recognition for Neuroimaging toolbox (PRoNTo). Medication was treated as a binary confounding variable. Decoded and actual clinical scores were compared using Pearson's correlation coefficient (r) and mean squared error (MSE) to evaluate the models. Permutation test was applied to estimate significance levels. Relevance Vector Regression identified patterns of neural activity associated with symptoms of behavioral and emotional dysregulation at the initial study screen and close to the fMRI scanning session. The correlation and the mean squared error between actual and decoded symptoms were significant at the initial study screen and close to the fMRI scanning session. However, after controlling for potential medication effects, results remained significant only for decoding symptoms at the initial study screen. Neural regions with the highest contribution to the pattern regression model included cerebellum, sensory-motor and fronto-limbic areas. The combination of pattern regression models and neuroimaging can help to determine the severity of behavioral and emotional dysregulation in youth at different time points.
Neuroimaging and Research into Second Language Acquisition
ERIC Educational Resources Information Center
Sabourin, Laura
2009-01-01
Neuroimaging techniques are becoming not only more and more sophisticated but are also coming to be increasingly accessible to researchers. One thing that one should take note of is the potential of neuroimaging research within second language acquisition (SLA) to contribute to issues pertaining to the plasticity of the adult brain and to general…
Cognitive Neuroimaging: Cognitive Science out of the Armchair
ERIC Educational Resources Information Center
de Zubicaray, Greig I.
2006-01-01
Cognitive scientists were not quick to embrace the functional neuroimaging technologies that emerged during the late 20th century. In this new century, cognitive scientists continue to question, not unreasonably, the relevance of functional neuroimaging investigations that fail to address questions of interest to cognitive science. However, some…
Turner Syndrome: Neuroimaging Findings--Structural and Functional
ERIC Educational Resources Information Center
Mullaney, Ronan; Murphy, Declan
2009-01-01
Neuroimaging studies of Turner syndrome can advance our understanding of the X chromosome in brain development, and the modulatory influence of endocrine factors. There is increasing evidence from neuroimaging studies that TX individuals have significant differences in the anatomy, function, and metabolism of a number of brain regions; including…
Neuroimaging biomarkers of preterm brain injury: toward developing the preterm connectome
Panigrahy, Ashok; Wisnowski, Jessica L.; Furtado, Andre; Lepore, Natasha; Paquette, Lisa; Bluml, Stefan
2013-01-01
For typically developing infants, the last trimester of fetal development extending into the first post-natal months is a period of rapid brain development. Infants who are born premature face significant risk of brain injury (e.g., intraventricular or germinal matrix hemorrhage and periventricular leukomalacia) from complications in the perinatal period and also potential long-term neurodevelopmental disabilities because these early injuries can interrupt normal brain maturation. Neuroimaging has played an important role in the diagnosis and management of the preterm infant. Both cranial US and conventional MRI techniques are useful in diagnostic and prognostic evaluation of preterm brain development and injury. Cranial US is highly sensitive for intraventricular hemorrhage IVH and provides prognostic information regarding cerebral palsy. Data are limited regarding the utility of MRI as a routine screening instrument for brain injury for all preterm infants. However, MRI might provide diagnostic or prognostic information regarding PVL and other types of preterm brain injury in the setting of specific clinical indications and risk factors. Further development of advanced MR techniques like volumetric MR imaging, diffusion tensor imaging, metabolic imaging (MR spectroscopy) and functional connectivity are necessary to provide additional insight into the molecular, cellular and systems processes that underlie brain development and outcome in the preterm infant. The adult concept of the “connectome” is also relevant in understanding brain networks that underlie the preterm brain. Knowledge of the preterm connectome will provide a framework for understanding preterm brain function and dysfunction, and potentially even a roadmap for brain plasticity. By combining conventional imaging techniques with more advanced techniques, neuroimaging findings will likely be used not only as diagnostic and prognostic tools, but also as biomarkers for long-term neurodevelopmental outcomes, instruments to assess the efficacy of neuroprotective agents and maneuvers in the NICU, and as screening instruments to appropriately select infants for longitudinal developmental interventions. PMID:22395719
Biology and therapy of fibromyalgia. Functional magnetic resonance imaging findings in fibromyalgia
Williams, David A; Gracely, Richard H
2006-01-01
Techniques in neuroimaging such as functional magnetic resonance imaging (fMRI) have helped to provide insights into the role of supraspinal mechanisms in pain perception. This review focuses on studies that have applied fMRI in an attempt to gain a better understanding of the mechanisms involved in the processing of pain associated with fibromyalgia. This article provides an overview of the nociceptive system as it functions normally, reviews functional brain imaging methods, and integrates the existing literature utilizing fMRI to study central pain mechanisms in fibromyalgia. PMID:17254318
Brain Connectivity Networks and the Aesthetic Experience of Music.
Reybrouck, Mark; Vuust, Peter; Brattico, Elvira
2018-06-12
Listening to music is above all a human experience, which becomes an aesthetic experience when an individual immerses himself/herself in the music, dedicating attention to perceptual-cognitive-affective interpretation and evaluation. The study of these processes where the individual perceives, understands, enjoys and evaluates a set of auditory stimuli has mainly been focused on the effect of music on specific brain structures, as measured with neurophysiology and neuroimaging techniques. The very recent application of network science algorithms to brain research allows an insight into the functional connectivity between brain regions. These studies in network neuroscience have identified distinct circuits that function during goal-directed tasks and resting states. We review recent neuroimaging findings which indicate that music listening is traceable in terms of network connectivity and activations of target regions in the brain, in particular between the auditory cortex, the reward brain system and brain regions active during mind wandering.
Imaging brain development: the adolescent brain.
Blakemore, Sarah-Jayne
2012-06-01
The past 15 years have seen a rapid expansion in the number of studies using neuroimaging techniques to investigate maturational changes in the human brain. In this paper, I review MRI studies on structural changes in the developing brain, and fMRI studies on functional changes in the social brain during adolescence. Both MRI and fMRI studies point to adolescence as a period of continued neural development. In the final section, I discuss a number of areas of research that are just beginning and may be the subject of developmental neuroimaging in the next twenty years. Future studies might focus on complex questions including the development of functional connectivity; how gender and puberty influence adolescent brain development; the effects of genes, environment and culture on the adolescent brain; development of the atypical adolescent brain; and implications for policy of the study of the adolescent brain. Copyright © 2011 Elsevier Inc. All rights reserved.
Neuroimaging in aphasia treatment research: Consensus and practical guidelines for data analysis
Meinzer, Marcus; Beeson, Pélagie M.; Cappa, Stefano; Crinion, Jenny; Kiran, Swathi; Saur, Dorothee; Parrish, Todd; Crosson, Bruce; Thompson, Cynthia K.
2012-01-01
Functional magnetic resonance imaging is the most widely used imaging technique to study treatment-induced recovery in post-stroke aphasia. The longitudinal design of such studies adds to the challenges researchers face when studying patient populations with brain damage in cross-sectional settings. The present review focuses on issues specifically relevant to neuroimaging data analysis in aphasia treatment research identified in discussions among international researchers at the Neuroimaging in Aphasia Treatment Research Workshop held at Northwestern University (Evanston, Illinois, USA). In particular, we aim to provide the reader with a critical review of unique problems related to the pre-processing, statistical modeling and interpretation of such data sets. Despite the fact that data analysis procedures critically depend on specific design features of a given study, we aim to discuss and communicate a basic set of practical guidelines that should be applicable to a wide range of studies and useful as a reference for researchers pursuing this line of research. PMID:22387474
Functional neuroimaging in psychiatry.
Fu, C H; McGuire, P K
1999-01-01
Functional neuroimaging is one of the most powerful means available for investigating the pathophysiology of psychiatric disorders. In this review, we shall focus on the different ways that it can be employed to this end, describing the major findings in the field in the context of different methodological approaches. We will also discuss practical issues that are particular to studying psychiatric disorders and the potential contribution of functional neuroimaging to future psychiatric research. PMID:10466156
Reading the Freudian theory of sexual drives from a functional neuroimaging perspective
Stoléru, Serge
2014-01-01
One of the essential tasks of neuropsychoanalysis is to investigate the neural correlates of sexual drives. Here, we consider the four defining characteristics of sexual drives as delineated by Freud: their pressure, aim, object, and source. We systematically examine the relations between these characteristics and the four-component neurophenomenological model that we have proposed based on functional neuroimaging studies, which comprises a cognitive, a motivational, an emotional and an autonomic/neuroendocrine component. Functional neuroimaging studies of sexual arousal (SA) have thrown a new light on the four fundamental characteristics of sexual drives by identifying their potential neural correlates. While these studies are essentially consistent with the Freudian model of drives, the main difference emerging between the functional neuroimaging perspective on sexual drives and the Freudian theory relates to the source of drives. From a functional neuroimaging perspective, sources of sexual drives, conceived by psychoanalysis as processes of excitation occurring in a peripheral organ, do not seem, at least in adult subjects, to be an essential part of the determinants of SA. It is rather the central processing of visual or genital stimuli that gives to these stimuli their sexually arousing and sexually pleasurable character. Finally, based on functional neuroimaging results, some possible improvements to the psychoanalytic theory of sexual drives are suggested. PMID:24672467
The Meditative Mind: A Comprehensive Meta-Analysis of MRI Studies
2015-01-01
Over the past decade mind and body practices, such as yoga and meditation, have raised interest in different scientific fields; in particular, the physiological mechanisms underlying the beneficial effects observed in meditators have been investigated. Neuroimaging studies have studied the effects of meditation on brain structure and function and findings have helped clarify the biological underpinnings of the positive effects of meditation practice and the possible integration of this technique in standard therapy. The large amount of data collected thus far allows drawing some conclusions about the neural effects of meditation practice. In the present study we used activation likelihood estimation (ALE) analysis to make a coordinate-based meta-analysis of neuroimaging data on the effects of meditation on brain structure and function. Results indicate that meditation leads to activation in brain areas involved in processing self-relevant information, self-regulation, focused problem-solving, adaptive behavior, and interoception. Results also show that meditation practice induces functional and structural brain modifications in expert meditators, especially in areas involved in self-referential processes such as self-awareness and self-regulation. These results demonstrate that a biological substrate underlies the positive pervasive effect of meditation practice and suggest that meditation techniques could be adopted in clinical populations and to prevent disease. PMID:26146618
Soto-Montenegro, María Luisa; Vicente-Rodríguez, Marta; Pérez-García, Carmen; Gramage, Esther; Desco, Manuel; Herradón, Gonzalo
2015-03-30
Amphetamine-induced neurotoxic effects have traditionally been studied using immunohistochemistry and other post-mortem techniques, which have proven invaluable for the definition of amphetamine-induced dopaminergic damage in the nigrostriatal pathway. However, these approaches are limited in that they require large numbers of animals and do not provide the temporal data that can be collected in longitudinal studies using functional neuroimaging techniques. Unfortunately, functional imaging studies in rodent models of drug-induced neurotoxicity are lacking. The aim of this study was to evaluate in vivo the changes in brain glucose metabolism caused by amphetamine in the pleiotrophin knockout mouse (PTN-/-), a genetic model with increased vulnerability to amphetamine-induced neurotoxic effects. We showed that administration of amphetamine causes a significantly greater loss of striatal tyrosine hydroxylase content in PTN-/- mice than in wild-type (WT) mice. In addition, [(18)F]-FDG-PET shows that amphetamine produces a significant decrease in glucose metabolism in the striatum and prefrontal cortex in the PTN-/- mice, compared to WT mice. These findings suggest that [(18)F]-FDG uptake measured by PET is useful for detecting amphetamine-induced changes in glucose metabolism in vivo in specific brain areas, including the striatum, a key feature of amphetamine-induced neurotoxicity. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
The role of magnetic resonance imaging in the diagnosis of Parkinson's disease: a review.
Al-Radaideh, Ali M; Rababah, Eman M
2016-01-01
Parkinson's disease (PD) is the second most common neurodegenerative disease after Alzheimer's in elderly people. Different structural and functional neuroimaging methods play a great role in the early diagnosis of neurodegenerative diseases. This review discusses the role of magnetic resonance imaging (MRI) in the diagnosis of PD. MRI provides clinicians with structural and functional information of human brain noninvasively. Advanced quantitative MRI techniques have shown promise for detecting pathological changes related to different stages of PD. Collectively, advanced MRI techniques at high and ultrahigh magnetic fields aid in better understanding of the nature and progression of PD. Copyright © 2016 Elsevier Inc. All rights reserved.
On the role of general system theory for functional neuroimaging.
Stephan, Klaas Enno
2004-12-01
One of the most important goals of neuroscience is to establish precise structure-function relationships in the brain. Since the 19th century, a major scientific endeavour has been to associate structurally distinct cortical regions with specific cognitive functions. This was traditionally accomplished by correlating microstructurally defined areas with lesion sites found in patients with specific neuropsychological symptoms. Modern neuroimaging techniques with high spatial resolution have promised an alternative approach, enabling non-invasive measurements of regionally specific changes of brain activity that are correlated with certain components of a cognitive process. Reviewing classic approaches towards brain structure-function relationships that are based on correlational approaches, this article argues that these approaches are not sufficient to provide an understanding of the operational principles of a dynamic system such as the brain but must be complemented by models based on general system theory. These models reflect the connectional structure of the system under investigation and emphasize context-dependent couplings between the system elements in terms of effective connectivity. The usefulness of system models whose parameters are fitted to measured functional imaging data for testing hypotheses about structure-function relationships in the brain and their potential for clinical applications is demonstrated by several empirical examples.
On the role of general system theory for functional neuroimaging
Stephan, Klaas Enno
2004-01-01
One of the most important goals of neuroscience is to establish precise structure–function relationships in the brain. Since the 19th century, a major scientific endeavour has been to associate structurally distinct cortical regions with specific cognitive functions. This was traditionally accomplished by correlating microstructurally defined areas with lesion sites found in patients with specific neuropsychological symptoms. Modern neuroimaging techniques with high spatial resolution have promised an alternative approach, enabling non-invasive measurements of regionally specific changes of brain activity that are correlated with certain components of a cognitive process. Reviewing classic approaches towards brain structure–function relationships that are based on correlational approaches, this article argues that these approaches are not sufficient to provide an understanding of the operational principles of a dynamic system such as the brain but must be complemented by models based on general system theory. These models reflect the connectional structure of the system under investigation and emphasize context-dependent couplings between the system elements in terms of effective connectivity. The usefulness of system models whose parameters are fitted to measured functional imaging data for testing hypotheses about structure–function relationships in the brain and their potential for clinical applications is demonstrated by several empirical examples. PMID:15610393
Uncovering the etiology of conversion disorder: insights from functional neuroimaging
Ejareh dar, Maryam; Kanaan, Richard AA
2016-01-01
Conversion disorder (CD) is a syndrome of neurological symptoms arising without organic cause, arguably in response to emotional stress, but the exact neural substrates of these symptoms and the underlying mechanisms remain poorly understood with the hunt for a biological basis afoot for centuries. In the past 15 years, novel insights have been gained with the advent of functional neuroimaging studies in patients suffering from CDs in both motor and nonmotor domains. This review summarizes recent functional neuroimaging studies including functional magnetic resonance imaging (fMRI), single photon emission computerized tomography (SPECT), and positron emission tomography (PET) to see whether they bring us closer to understanding the etiology of CD. Convergent functional neuroimaging findings suggest alterations in brain circuits that could point to different mechanisms for manifesting functional neurological symptoms, in contrast with feigning or healthy controls. Abnormalities in emotion processing and in emotion-motor processing suggest a diathesis, while differential reactions to certain stressors implicate a specific response to trauma. No comprehensive theory emerges from these clues, and all results remain preliminary, but functional neuroimaging has at least given grounds for hope that a model for CD may soon be found. PMID:26834476
Neurocognitive and Neuroplastic Mechanisms of Novel Clinical Signs in CRPS.
Kuttikat, Anoop; Noreika, Valdas; Shenker, Nicholas; Chennu, Srivas; Bekinschtein, Tristan; Brown, Christopher Andrew
2016-01-01
Complex regional pain syndrome (CRPS) is a chronic, debilitating pain condition that usually arises after trauma to a limb, but its precise etiology remains elusive. Novel clinical signs based on body perceptual disturbances have been reported, but their pathophysiological mechanisms remain poorly understood. Investigators have used functional neuroimaging techniques (including MEG, EEG, fMRI, and PET) to study changes mainly within the somatosensory and motor cortices. Here, we provide a focused review of the neuroimaging research findings that have generated insights into the potential neurocognitive and neuroplastic mechanisms underlying perceptual disturbances in CRPS. Neuroimaging findings, particularly with regard to somatosensory processing, have been promising but limited by a number of technique-specific factors (such as the complexity of neuroimaging investigations, poor spatial resolution of EEG/MEG, and use of modeling procedures that do not draw causal inferences) and more general factors including small samples sizes and poorly characterized patients. These factors have led to an underappreciation of the potential heterogeneity of pathophysiology that may underlie variable clinical presentation in CRPS. Also, until now, neurological deficits have been predominantly investigated separately from perceptual and cognitive disturbances. Here, we highlight the need to identify neurocognitive phenotypes of patients with CRPS that are underpinned by causal explanations for perceptual disturbances. We suggest that a combination of larger cohorts, patient phenotyping, the use of both high temporal, and spatial resolution neuroimaging methods, and the identification of simplified biomarkers is likely to be the most fruitful approach to identifying neurocognitive phenotypes in CRPS. Based on our review, we explain how such phenotypes could be characterized in terms of hierarchical models of perception and corresponding disturbances in recurrent processing involving the somatosensory, salience and executive brain networks. We also draw attention to complementary neurological factors that may explain some CRPS symptoms, including the possibility of central neuroinflammation and neuronal atrophy, and how these phenomena may overlap but be partially separable from neurocognitive deficits.
Neurocognitive and Neuroplastic Mechanisms of Novel Clinical Signs in CRPS
Kuttikat, Anoop; Noreika, Valdas; Shenker, Nicholas; Chennu, Srivas; Bekinschtein, Tristan; Brown, Christopher Andrew
2016-01-01
Complex regional pain syndrome (CRPS) is a chronic, debilitating pain condition that usually arises after trauma to a limb, but its precise etiology remains elusive. Novel clinical signs based on body perceptual disturbances have been reported, but their pathophysiological mechanisms remain poorly understood. Investigators have used functional neuroimaging techniques (including MEG, EEG, fMRI, and PET) to study changes mainly within the somatosensory and motor cortices. Here, we provide a focused review of the neuroimaging research findings that have generated insights into the potential neurocognitive and neuroplastic mechanisms underlying perceptual disturbances in CRPS. Neuroimaging findings, particularly with regard to somatosensory processing, have been promising but limited by a number of technique-specific factors (such as the complexity of neuroimaging investigations, poor spatial resolution of EEG/MEG, and use of modeling procedures that do not draw causal inferences) and more general factors including small samples sizes and poorly characterized patients. These factors have led to an underappreciation of the potential heterogeneity of pathophysiology that may underlie variable clinical presentation in CRPS. Also, until now, neurological deficits have been predominantly investigated separately from perceptual and cognitive disturbances. Here, we highlight the need to identify neurocognitive phenotypes of patients with CRPS that are underpinned by causal explanations for perceptual disturbances. We suggest that a combination of larger cohorts, patient phenotyping, the use of both high temporal, and spatial resolution neuroimaging methods, and the identification of simplified biomarkers is likely to be the most fruitful approach to identifying neurocognitive phenotypes in CRPS. Based on our review, we explain how such phenotypes could be characterized in terms of hierarchical models of perception and corresponding disturbances in recurrent processing involving the somatosensory, salience and executive brain networks. We also draw attention to complementary neurological factors that may explain some CRPS symptoms, including the possibility of central neuroinflammation and neuronal atrophy, and how these phenomena may overlap but be partially separable from neurocognitive deficits. PMID:26858626
[Neuroimaging follow-up of cerebral aneurysms treated with endovascular techniques].
Delgado, F; Saiz, A; Hilario, A; Murias, E; San Román Manzanera, L; Lagares Gomez-Abascal, A; Gabarrós, A; González García, A
2014-01-01
There are no specific recommendations in clinical guidelines about the best time, imaging tests, or intervals for following up patients with intracranial aneurysms treated with endovascular techniques. We reviewed the literature, using the following keywords to search in the main medical databases: cerebral aneurysm, coils, endovascular procedure, and follow-up. Within the Cerebrovascular Disease Group of the Spanish Society of Neuroradiology, we aimed to propose recommendations and an orientative protocol based on the scientific evidence for using neuroimaging to monitor intracranial aneurysms that have been treated with endovascular techniques. We aimed to specify the most appropriate neuroimaging techniques, the interval, the time of follow-up, and the best approach to defining the imaging findings, with the ultimate goal of improving clinical outcomes while optimizing and rationalizing the use of available resources. Copyright © 2013 SERAM. Published by Elsevier Espana. All rights reserved.
One-stop-shop stroke imaging with functional CT.
Tong, Elizabeth; Komlosi, Peter; Wintermark, Max
2015-12-01
Advanced imaging techniques have extended beyond traditional anatomic imaging and progressed to dynamic, physiologic and functional imaging. Neuroimaging is no longer a mere diagnostic tool. Multimodal functional CT, comprising of NCCT, PCT and CTA, provides a one-stop-shop for rapid stroke imaging. Integrating those imaging findings with pertinent clinical information can help guide subsequent treatment decisions, medical management and follow-up imaging selection. This review article will briefly discuss the indication and utility of each modality in acute stroke imaging. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Neuroimaging of the Periaqueductal Gray: State of the Field
Linnman, Clas; Moulton, Eric A.; Barmettler, Gabi; Becerra, Lino; Borsook, David
2011-01-01
This review and meta-analysis aims at summarizing and integrating the human neuroimaging studies that report periaqueductal gray (PAG) involvement; 250 original manuscripts on human neuroimaging of the PAG were identified. A narrative review and meta-analysis using activation likelihood estimates is included. Behaviors covered include pain and pain modulation, anxiety, bladder and bowel function and autonomic regulation. Methods include structural and functional magnetic resonance imaging, functional connectivity measures, diffusion weighted imaging and positron emission tomography. Human neuroimaging studies in healthy and clinical populations largely confirm the animal literature indicating that the PAG is involved in homeostatic regulation of salient functions such as pain, anxiety and autonomic function. Methodological concerns in the current literature, including resolution constraints, imaging artifacts and imprecise neuroanatomical labeling are discussed, and future directions are proposed. A general conclusion is that PAG neuroimaging is a field with enormous potential to translate animal data onto human behaviors, but with some growing pains that can and need to be addressed in order to add to our understanding of the neurobiology of this key region. PMID:22197740
Investigating the pathogenesis of posttraumatic stress disorder with neuroimaging.
Pitman, R K; Shin, L M; Rauch, S L
2001-01-01
Rapidly evolving brain neuroimaging techniques such as magnetic resonance imaging (MRI) and positron emission tomography (PET) are proving fruitful in exploring the pathogenesis and pathophysiology of posttraumatic stress disorder (PTSD). Structural abnormalities in PTSD found with MRI include nonspecific white matter lesions and decreased hippocampal volume. These abnormalities may reflect pretrauma vulnerability to develop PTSD, or they may be a consequence of traumatic exposure, PTSD, and/or PTSD sequelae. Functional neuroimaging symptom provocation and cognitive activation paradigms using PET measurement of regional cerebral blood flow have revealed greater activation of the amygdala and anterior paralimbic structures (which are known to be involved in processing negative emotions such as fear), greater deactivation of Broca's region (motor speech) and other nonlimbic cortical regions, and failure of activation of the cingulate cortex (which possibly plays an inhibitory role) in response to trauma-related stimuli in individuals with PTSD. Functional MRI research has shown the amygdala to be hyperresponsive to fear-related stimuli in this disorder. Research with PET suggests that cortical, notably hippocampal, metabolism is suppressed to a greater extent by pharmacologic stimulation of the noradrenergic system in persons with PTSD. The growth of knowledge concerning the anatomical and neurochemical basis of this important mental disorder will hopefully eventually lead to rational psychological and pharmacologic treatments.
Systematic Redaction for Neuroimage Data
Matlock, Matt; Schimke, Nakeisha; Kong, Liang; Macke, Stephen; Hale, John
2013-01-01
In neuroscience, collaboration and data sharing are undermined by concerns over the management of protected health information (PHI) and personal identifying information (PII) in neuroimage datasets. The HIPAA Privacy Rule mandates measures for the preservation of subject privacy in neuroimaging studies. Unfortunately for the researcher, the management of information privacy is a burdensome task. Wide scale data sharing of neuroimages is challenging for three primary reasons: (i) A dearth of tools to systematically expunge PHI/PII from neuroimage data sets, (ii) a facility for tracking patient identities in redacted datasets has not been produced, and (iii) a sanitization workflow remains conspicuously absent. This article describes the XNAT Redaction Toolkit—an integrated redaction workflow which extends a popular neuroimage data management toolkit to remove PHI/PII from neuroimages. Quickshear defacing is also presented as a complementary technique for deidentifying the image data itself. Together, these tools improve subject privacy through systematic removal of PII/PHI. PMID:24179597
The Status of the Quality Control in Acupuncture-Neuroimaging Studies
Qiu, Ke; Jing, Miaomiao; Liu, Xiaoyan; Gao, Feifei; Liang, Fanrong; Zeng, Fang
2016-01-01
Using neuroimaging techniques to explore the central mechanism of acupuncture gains increasing attention, but the quality control of acupuncture-neuroimaging study remains to be improved. We searched the PubMed Database during 1995 to 2014. The original English articles with neuroimaging scan performed on human beings were included. The data involved quality control including the author, sample size, characteristics of the participant, neuroimaging technology, and acupuncture intervention were extracted and analyzed. The rigorous inclusion and exclusion criteria are important guaranty for the participants' homogeneity. The standard operation process of acupuncture and the stricter requirement for acupuncturist play significant role in quality control. More attention should be paid to the quality control in future studies to improve the reproducibility and reliability of the acupuncture-neuroimaging studies. PMID:27242911
Jasińska, Kaja K; Guei, Sosthène
2018-02-02
Portable neuroimaging approaches provide new advances to the study of brain function and brain development with previously inaccessible populations and in remote locations. This paper shows the development of field functional Near Infrared Spectroscopy (fNIRS) imaging to the study of child language, reading, and cognitive development in a rural village setting of Côte d'Ivoire. Innovation in methods and the development of culturally appropriate neuroimaging protocols allow a first-time look into the brain's development and children's learning outcomes in understudied environments. This paper demonstrates protocols for transporting and setting up a mobile laboratory, discusses considerations for field versus laboratory neuroimaging, and presents a guide for developing neuroimaging consent procedures and building meaningful long-term collaborations with local government and science partners. Portable neuroimaging methods can be used to study complex child development contexts, including the impact of significant poverty and adversity on brain development. The protocol presented here has been developed for use in Côte d'Ivoire, the world's primary source of cocoa, and where reports of child labor in the cocoa sector are common. Yet, little is known about the impact of child labor on brain development and learning. Field neuroimaging methods have the potential to yield new insights into such urgent issues, and the development of children globally.
LEVINE, BRIAN; FUJIWARA, ESTHER; O’CONNOR, CHARLENE; RICHARD, NADINE; KOVACEVIC, NATASA; MANDIC, MARINA; RESTAGNO, ADRIANA; EASDON, CRAIG; ROBERTSON, IAN H.; GRAHAM, SIMON J.; CHEUNG, GORDON; GAO, FUQIANG; SCHWARTZ, MICHAEL L.; BLACK, SANDRA E.
2007-01-01
Quantitative neuroimaging is increasingly used to study the effects of traumatic brain injury (TBI) on brain structure and function. This paper reviews quantitative structural and functional neuroimaging studies of patients with TBI, with an emphasis on the effects of diffuse axonal injury (DAI), the primary neuropathology in TBI. Quantitative structural neuroimaging has evolved from simple planometric measurements through targeted region-of-interest analyses to whole-brain analysis of quantified tissue compartments. Recent studies converge to indicate widespread volume loss of both gray and white matter in patients with moderate-to-severe TBI. These changes can be documented even when patients with focal lesions are excluded. Broadly speaking, performance on standard neuropsychological tests of speeded information processing are related to these changes, but demonstration of specific brain-behavior relationships requires more refined experimental behavioral measures. The functional consequences of these structural changes can be imaged with activation functional neuroimaging. Although this line of research is at an early stage, results indicate that TBI causes a more widely dispersed activation in frontal and posterior cortices. Further progress in analysis of the consequences of TBI on neural structure and function will require control of variability in neuropathology and behavior. PMID:17020478
Wegbreit, Ezra; Pavuluri, Mani
2012-01-01
Recent neuroimaging studies have uncovered much about the specific neural deficits in adult bipolar disorder (ABD), but despite promising results, neuroimaging research for pediatric bipolar disorder (PBD) is still developing. The neuroimaging literature is highly heterogeneous, varying in the paradigms used and in participants' mood states and medication status. Despite this variability, several dominant patterns emerge. In response to emotional stimuli, both ABD and PBD show limbic hyperactivity coupled with hypoactivity in ventral prefrontal emotion regulation systems. This pattern occurred most robustly in response to negative incidental stimuli and was especially apparent in manic PBD. ABD showed more variability in ventral prefrontal activity, possibly due to maturational and medication factors. On numerous cognitive paradigms, PBD showed dorsal prefrontal hypoactivity linked to ventral dysfunction, whereas ABD showed compensatory frontal, parietal, and temporal activity with paradigm-specific variations. In emotion-cognition interaction paradigms, patients show dysregulation in regions interfacing between cognitive and emotional brain systems (e.g., ventral prefrontal and cingulate cortices), which expend extra effort to process emotional stimuli effectively and recruit additional posterior attention systems to cope with affective instability. In addition, novel functional connectivity techniques have uncovered connectivity deficits between frontal and limbic regions in ABD and PBD at rest and during active emotional and cognitive tasks. Finally, the neuroimaging literature currently lacks cross-sectional studies comparing PBD with ABD and longitudinal studies following children and adolescents with BD into adulthood. Such studies would provide important insights into patients' prognosis and would determine targets for early interventions in the evolving illness diathesis.
Phillips, Mary L; Swartz, Holly A.
2014-01-01
Objective This critical review appraises neuroimaging findings in bipolar disorder in emotion processing, emotion regulation, and reward processing neural circuitry, to synthesize current knowledge of the neural underpinnings of bipolar disorder, and provide a neuroimaging research “roadmap” for future studies. Method We examined findings from all major studies in bipolar disorder that used fMRI, volumetric analyses, diffusion imaging, and resting state techniques, to inform current conceptual models of larger-scale neural circuitry abnormalities in bipolar disorder Results Bipolar disorder can be conceptualized in neural circuitry terms as parallel dysfunction in bilateral prefrontal cortical (especially ventrolateral prefrontal cortical)-hippocampal-amygdala emotion processing and emotion regulation neural circuitries, together with an “overactive” left-sided ventral striatal-ventrolateral and orbitofrontal cortical reward processing circuitry, that result in characteristic behavioral abnormalities associated with bipolar disorder: emotional lability, emotional dysregulation and heightened reward sensitivity. A potential structural basis for these functional abnormalities are gray matter decreases in prefrontal and temporal cortices, amygdala and hippocampus, and fractional anisotropy decreases in white matter tracts connecting prefrontal and subcortical regions. Conclusion Neuroimaging studies of bipolar disorder clearly demonstrate abnormalities in neural circuitries supporting emotion processing, emotion regulation and reward processing, although there are several limitations to these studies. Future neuroimaging research in bipolar disorder should include studies adopting dimensional approaches; larger studies examining neurodevelopmental trajectories in bipolar disorder and at-risk youth; multimodal neuroimaging studies using integrated systems approaches; and studies using pattern recognition approaches to provide clinically useful, individual-level data. Such studies will help identify clinically-relevant biomarkers to guide diagnosis and treatment decision-making for individuals with bipolar disorder. PMID:24626773
Martucci, Katherine T; Mackey, Sean C
2018-06-01
Neuroimaging research has demonstrated definitive involvement of the central nervous system in the development, maintenance, and experience of chronic pain. Structural and functional neuroimaging has helped elucidate central nervous system contributors to chronic pain in humans. Neuroimaging of pain has provided a tool for increasing our understanding of how pharmacologic and psychologic therapies improve chronic pain. To date, findings from neuroimaging pain research have benefitted clinical practice by providing clinicians with an educational framework to discuss the biopsychosocial nature of pain with patients. Future advances in neuroimaging-based therapeutics (e.g., transcranial magnetic stimulation, real-time functional magnetic resonance imaging neurofeedback) may provide additional benefits for clinical practice. In the future, with standardization and validation, brain imaging could provide objective biomarkers of chronic pain, and guide treatment for personalized pain management. Similarly, brain-based biomarkers may provide an additional predictor of perioperative prognoses.
Neural and Behavioral Sequelae of Blast-Related Traumatic Brain Injury
2012-09-01
fMRI, DTI , cognition 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF RESPONSIBLE PERSON USAMRMC a...techniques [task-activated functional MRI (fMRI) and diffusion tensor imaging ( DTI )] to gain a comprehensive understanding of the neural changes...orthopedic injuries. We accomplished this goal by conducting advanced neuroimaging (task-activated fMRI and DTI fiber tracking) and neurobehavioral
Raffa, R B
2010-02-01
The diminution in cognitive function reported to occur in patients treated with adjuvant cancer chemotherapy (a phenomenon known as 'chemo-fog, 'chemo-brain' or similar designation) is supported with varying degrees of evidence by prospective and retrospective clinical studies. However, the cognitive deficits are often subtle and the methodologies used to measure them not consistent. Additionally, patients might be able to compensate for the deficits, thereby leading to underestimates of the problem by this type of assessment. For these reasons, direct neuroimaging techniques might provide additional insight. The relatively few such studies, and fewer electrophysiological studies, offer an alternative way to evaluate changes that might be related to cognitive deficits in patients treated with cancer chemotherapeutic regimens.
The missing link: evolution of the primate cerebellum.
MacLeod, Carol
2012-01-01
The cerebellum has too often been seen as the "little brain," subservient to the "big brain," the cerebrum. That is changing, as neuroimaging uncovers the cerebellum as the "missing link" in the neurological underpinnings of many cognitive domains. Connections between the neocortex and the cerebellum are now more precisely defined, with functionally localized areas of cerebellar cortex understood for cognitive tasks in humans. Comparative volumetric studies of the primate cerebellum have isolated some elements of circuitry, and our field is moving toward a better integration with the neurosciences in a systematic comparative framework. The next decade may show great advances, as relatively noninvasive techniques of neuroimaging have the potential to build a comparative model of the evolution of primate neurocircuitry. Copyright © 2012 Elsevier B.V. All rights reserved.
[Mechanism of pain sensation].
Gyulaházi, Judit
2009-11-15
Pain, as subjective content of consciousness, is an essential attention-calling sign that helps to survive. Pain relieve is obligatory for every physician, thus, its individual appearance can make the analgesia difficult to carry out. The improving neuroimaging techniques allow understanding the development of pain sensation. Through the 24 articles on the PubMed found with keywords 'pain' and 'neuroimaging', we review here the parts of the pain neuron matrix, their tasks and the assumed mechanism of the acute pain sensation. The mechanism of the individual pain sensation is illustrated by the view of the modular function of the medial part of the pain matrix. Experimental results of empathic pain suggest that pain sensation may occur without real damage of the tissues, as well. The pain network plays main role in chronic pain.
Stoléru, Serge; Fonteille, Véronique; Cornélis, Christel; Joyal, Christian; Moulier, Virginie
2012-07-01
In the last fifteen years, functional neuroimaging techniques have been used to investigate the neuroanatomical correlates of sexual arousal in healthy human subjects. In most studies, subjects have been requested to watch visual sexual stimuli and control stimuli. Our review and meta-analysis found that in heterosexual men, sites of cortical activation consistently reported across studies are the lateral occipitotemporal, inferotemporal, parietal, orbitofrontal, medial prefrontal, insular, anterior cingulate, and frontal premotor cortices as well as, for subcortical regions, the amygdalas, claustrum, hypothalamus, caudate nucleus, thalami, cerebellum, and substantia nigra. Heterosexual and gay men show a similar pattern of activation. Visual sexual stimuli activate the amygdalas and thalami more in men than in women. Ejaculation is associated with decreased activation throughout the prefrontal cortex. We present a neurophenomenological model to understand how these multiple regional brain responses could account for the varied facets of the subjective experience of sexual arousal. Further research should shift from passive to active paradigms, focus on functional connectivity and use subliminal presentation of stimuli. Copyright © 2012 Elsevier Ltd. All rights reserved.
Changes of Visual Pathway and Brain Connectivity in Glaucoma: A Systematic Review
Nuzzi, Raffaele; Dallorto, Laura; Rolle, Teresa
2018-01-01
Background: Glaucoma is a leading cause of irreversible blindness worldwide. The increasing interest in the involvement of the cortical visual pathway in glaucomatous patients is due to the implications in recent therapies, such as neuroprotection and neuroregeneration. Objective: In this review, we outline the current understanding of brain structural, functional, and metabolic changes detected with the modern techniques of neuroimaging in glaucomatous subjects. Methods: We screened MEDLINE, EMBASE, CINAHL, CENTRAL, LILACS, Trip Database, and NICE for original contributions published until 31 October 2017. Studies with at least six patients affected by any type of glaucoma were considered. We included studies using the following neuroimaging techniques: functional Magnetic Resonance Imaging (fMRI), resting-state fMRI (rs-fMRI), magnetic resonance spectroscopy (MRS), voxel- based Morphometry (VBM), surface-based Morphometry (SBM), diffusion tensor MRI (DTI). Results: Over a total of 1,901 studies, 56 case series with a total of 2,381 patients were included. Evidence of neurodegenerative process in glaucomatous patients was found both within and beyond the visual system. Structural alterations in visual cortex (mainly reduced cortex thickness and volume) have been demonstrated with SBM and VBM; these changes were not limited to primary visual cortex but also involved association visual areas. Other brain regions, associated with visual function, demonstrated a certain grade of increased or decreased gray matter volume. Functional and metabolic abnormalities resulted within primary visual cortex in all studies with fMRI and MRS. Studies with rs-fMRI found disrupted connectivity between the primary and higher visual cortex and between visual cortex and associative visual areas in the task-free state of glaucomatous patients. Conclusions: This review contributes to the better understanding of brain abnormalities in glaucoma. It may stimulate further speculation about brain plasticity at a later age and therapeutic strategies, such as the prevention of cortical degeneration in patients with glaucoma. Structural, functional, and metabolic neuroimaging methods provided evidence of changes throughout the visual pathway in glaucomatous patients. Other brain areas, not directly involved in the processing of visual information, also showed alterations. PMID:29896087
Moore, Eider B; Poliakov, Andrew V; Lincoln, Peter; Brinkley, James F
2007-01-01
Background Three-dimensional (3-D) visualization of multimodality neuroimaging data provides a powerful technique for viewing the relationship between structure and function. A number of applications are available that include some aspect of 3-D visualization, including both free and commercial products. These applications range from highly specific programs for a single modality, to general purpose toolkits that include many image processing functions in addition to visualization. However, few if any of these combine both stand-alone and remote multi-modality visualization in an open source, portable and extensible tool that is easy to install and use, yet can be included as a component of a larger information system. Results We have developed a new open source multimodality 3-D visualization application, called MindSeer, that has these features: integrated and interactive 3-D volume and surface visualization, Java and Java3D for true cross-platform portability, one-click installation and startup, integrated data management to help organize large studies, extensibility through plugins, transparent remote visualization, and the ability to be integrated into larger information management systems. We describe the design and implementation of the system, as well as several case studies that demonstrate its utility. These case studies are available as tutorials or demos on the associated website: . Conclusion MindSeer provides a powerful visualization tool for multimodality neuroimaging data. Its architecture and unique features also allow it to be extended into other visualization domains within biomedicine. PMID:17937818
Moore, Eider B; Poliakov, Andrew V; Lincoln, Peter; Brinkley, James F
2007-10-15
Three-dimensional (3-D) visualization of multimodality neuroimaging data provides a powerful technique for viewing the relationship between structure and function. A number of applications are available that include some aspect of 3-D visualization, including both free and commercial products. These applications range from highly specific programs for a single modality, to general purpose toolkits that include many image processing functions in addition to visualization. However, few if any of these combine both stand-alone and remote multi-modality visualization in an open source, portable and extensible tool that is easy to install and use, yet can be included as a component of a larger information system. We have developed a new open source multimodality 3-D visualization application, called MindSeer, that has these features: integrated and interactive 3-D volume and surface visualization, Java and Java3D for true cross-platform portability, one-click installation and startup, integrated data management to help organize large studies, extensibility through plugins, transparent remote visualization, and the ability to be integrated into larger information management systems. We describe the design and implementation of the system, as well as several case studies that demonstrate its utility. These case studies are available as tutorials or demos on the associated website: http://sig.biostr.washington.edu/projects/MindSeer. MindSeer provides a powerful visualization tool for multimodality neuroimaging data. Its architecture and unique features also allow it to be extended into other visualization domains within biomedicine.
Dopaminergic Neurotransmission in the Human Brain: New Lessons from Perturbation and Imaging
Ko, Ji Hyun; Strafella, Antonio P.
2012-01-01
Dopamine plays an important role in several brain functions and is involved in the pathogenesis of several psychiatric and neurological disorders. Neuroimaging techniques such as positron emission tomography allow us to quantify dopaminergic activity in the living human brain. Combining these with brain stimulation techniques offers us the unique opportunity to tackle questions regarding region-specific neurochemical activity. Such studies may aid clinicians and scientists to disentangle neural circuitries within the human brain and thereby help them to understand the underlying mechanisms of a given function in relation to brain diseases. Furthermore, it may also aid the development of alternative treatment approaches for various neurological and psychiatric conditions. PMID:21536838
Neurophysiology of action anticipation in athletes: A systematic review.
Smith, Daniel M
2016-01-01
The purpose of this study was to provide a systematic review of action anticipation studies using functional neuroimaging or brain stimulation during a sport-specific anticipation task. A total of 15 studies from 2008 to 2014 were evaluated and are reported in four sections: expert-novice samples, action anticipation tasks, neuroimaging and stimulation techniques, and key findings. Investigators examined a wide range of action anticipation scenarios specific to eight different sports and utilized functional magnetic resonance imaging (fMRI), electroencephalogram (EEG), and transcranial magnetic stimulation (TMS). Expert-novice comparisons were commonly used to investigate differences in action anticipation performance and neurophysiology. Experts tended to outperform novices, and an extensive array of brain structures were reported to be involved differently for experts and novices during action anticipation. However, these neurophysiological findings were generally inconsistent across the studies reviewed. The discussion focuses on strengths and four key limitations. The conclusion posits remaining questions and recommendations for future research. Copyright © 2015 Elsevier Ltd. All rights reserved.
Moreno, Andrea; Jego, Pierrick; de la Cruz, Feliberto; Canals, Santiago
2013-01-01
Complete understanding of the mechanisms that coordinate work and energy supply of the brain, the so called neurovascular coupling, is fundamental to interpreting brain energetics and their influence on neuronal coding strategies, but also to interpreting signals obtained from brain imaging techniques such as functional magnetic resonance imaging. Interactions between neuronal activity and cerebral blood flow regulation are largely compartmentalized. First, there exists a functional compartmentalization in which glutamatergic peri-synaptic activity and its electrophysiological events occur in close proximity to vascular responses. Second, the metabolic processes that fuel peri-synaptic activity are partially segregated between glycolytic and oxidative compartments. Finally, there is cellular segregation between astrocytic and neuronal compartments, which has potentially important implications on neurovascular coupling. Experimental data is progressively showing a tight interaction between the products of energy consumption and neurotransmission-driven signaling molecules that regulate blood flow. Here, we review some of these issues in light of recent findings with special attention to the neuron-glia interplay on the generation of neuroimaging signals. PMID:23543907
Multimodal neuroimaging in presurgical evaluation of drug-resistant epilepsy☆
Zhang, Jing; Liu, Weifang; Chen, Hui; Xia, Hong; Zhou, Zhen; Mei, Shanshan; Liu, Qingzhu; Li, Yunlin
2013-01-01
Intracranial EEG (icEEG) monitoring is critical in epilepsy surgical planning, but it has limitations. The advances of neuroimaging have made it possible to reveal epileptic abnormalities that could not be identified previously and improve the localization of the seizure focus and the vital cortex. A frequently asked question in the field is whether non-invasive neuroimaging could replace invasive icEEG or reduce the need for icEEG in presurgical evaluation. This review considers promising neuroimaging techniques in epilepsy presurgical assessment in order to address this question. In addition, due to large variations in the accuracies of neuroimaging across epilepsy centers, multicenter neuroimaging studies are reviewed, and there is much need for randomized controlled trials (RCTs) to better reveal the utility of presurgical neuroimaging. The results of multiple studies indicate that non-invasive neuroimaging could not replace invasive icEEG in surgical planning especially in non-lesional or extratemporal lobe epilepsies, but it could reduce the need for icEEG in certain cases. With technical advances, multimodal neuroimaging may play a greater role in presurgical evaluation to reduce the costs and risks of epilepsy surgery, and provide surgical options for more patients with drug-resistant epilepsy. PMID:24282678
Laureys, Steven; Giacino, Joseph T.; Schiff, Nicholas D.; Schabus, Manuel; Owen, Adrian M.
2010-01-01
Purpose of review We discuss the problems of evidence-based neurorehabilitation in disorders of consciousness, and recent functional neuroimaging data obtained in the vegetative state and minimally conscious state. Recent findings Published data are insufficient to make recommendations for or against any of the neurorehabilitative treatments in vegetative state and minimally conscious state patients. Electrophysiological and functional imaging studies have been shown to be useful in measuring residual brain function in noncommunicative brain-damaged patients. Despite the fact that such studies could in principle allow an objective quantification of the putative cerebral effect of rehabilitative treatment in the vegetative state and minimally conscious state, they have so far not been used in this context. Summary Without controlled studies and careful patient selection criteria it will not be possible to evaluate the potential of therapeutic interventions in disorders of consciousness. There also is a need to elucidate the neurophysiological effects of such treatments. Integration of multimodal neuroimaging techniques should eventually improve our ability to disentangle differences in outcome on the basis of underlying mechanisms and better guide our therapeutic options in the challenging patient populations encountered following severe acute brain damage. PMID:17102688
NASA Astrophysics Data System (ADS)
Liao, Steve M.; Gregg, Nick M.; White, Brian R.; Zeff, Benjamin W.; Bjerkaas, Katelin A.; Inder, Terrie E.; Culver, Joseph P.
2010-03-01
The neurodevelopmental outcome of neonatal intensive care unit (NICU) infants is a major clinical concern with many infants displaying neurobehavioral deficits in childhood. Functional neuroimaging may provide early recognition of neural deficits in high-risk infants. Near-infrared spectroscopy (NIRS) has the advantage of providing functional neuroimaging in infants at the bedside. However, limitations in traditional NIRS have included contamination from superficial vascular dynamics in the scalp. Furthermore, controversy exists over the nature of normal vascular, responses in infants. To address these issues, we extend the use of novel high-density NIRS arrays with multiple source-detector distances and a superficial signal regression technique to infants. Evaluations of healthy term-born infants within the first three days of life are performed without sedation using a visual stimulus. We find that the regression technique significantly improves brain activation signal quality. Furthermore, in six out of eight infants, both oxy- and total hemoglobin increases while deoxyhemoglobin decreases, suggesting that, at term, the neurovascular coupling in the visual cortex is similar to that found in healthy adults. These results demonstrate the feasibility of using high-density NIRS arrays in infants to improve signal quality through superficial signal regression, and provide a foundation for further development of high-density NIRS as a clinical tool.
Functional Neuroimaging Studies of Written Sentence Comprehension
ERIC Educational Resources Information Center
Caplan, David
2004-01-01
Sentences convey relationships between the meanings of words, such as who is accomplishing an action or receiving it. Functional neuroimaging based on positron-emission tomography and functional magnetic resonance imaging has been used to identify areas of the brain involved in structuring sentences and determining aspects of meaning associated…
Goh, S. Y. Matthew; Irimia, Andrei; Torgerson, Carinna M.; Horn, John D. Van
2014-01-01
Throughout the past few decades, the ability to treat and rehabilitate traumatic brain injury (TBI) patients has become critically reliant upon the use of neuroimaging to acquire adequate knowledge of injury-related effects upon brain function and recovery. As a result, the need for TBI neuroimaging analysis methods has increased in recent years due to the recognition that spatiotemporal computational analyses of TBI evolution are useful for capturing the effects of TBI dynamics. At the same time, however, the advent of such methods has brought about the need to analyze, manage, and integrate TBI neuroimaging data using informatically inspired approaches which can take full advantage of their large dimensionality and informational complexity. Given this perspective, we here discuss the neuroinformatics challenges for TBI neuroimaging analysis in the context of structural, connectivity, and functional paradigms. Within each of these, the availability of a wide range of neuroimaging modalities can be leveraged to fully understand the heterogeneity of TBI pathology; consequently, large-scale computer hardware resources and next-generation processing software are often required for efficient data storage, management, and analysis of TBI neuroimaging data. However, each of these paradigms poses challenges in the context of informatics such that the ability to address them is critical for augmenting current capabilities to perform neuroimaging analysis of TBI and to improve therapeutic efficacy. PMID:24616696
Pain perception and hypnosis: findings from recent functional neuroimaging studies.
Del Casale, Antonio; Ferracuti, Stefano; Rapinesi, Chiara; Serata, Daniele; Caltagirone, Saverio Simone; Savoja, Valeria; Piacentino, Daria; Callovini, Gemma; Manfredi, Giovanni; Sani, Gabriele; Kotzalidis, Georgios D; Girardi, Paolo
2015-01-01
Hypnosis modulates pain perception and tolerance by affecting cortical and subcortical activity in brain regions involved in these processes. By reviewing functional neuroimaging studies focusing on pain perception under hypnosis, the authors aimed to identify brain activation-deactivation patterns occurring in hypnosis-modulated pain conditions. Different changes in brain functionality occurred throughout all components of the pain network and other brain areas. The anterior cingulate cortex appears to be central in modulating pain circuitry activity under hypnosis. Most studies also showed that the neural functions of the prefrontal, insular, and somatosensory cortices are consistently modified during hypnosis-modulated pain conditions. Functional neuroimaging studies support the clinical use of hypnosis in the management of pain conditions.
Neuroimaging in mental health care: voices in translation
Borgelt, Emily L.; Buchman, Daniel Z.; Illes, Judy
2012-01-01
Images of brain function, popularly called “neuroimages,” have become a mainstay of contemporary communication about neuroscience and mental health. Paralleling media coverage of neuroimaging research and the high visibility of clinics selling scans is pressure from sponsors to move basic research about brain function along the translational pathway. Indeed, neuroimaging may offer benefits to mental health care: early or tailored intervention, opportunities for education and planning, and access to resources afforded by objectification of disorder. However, risks of premature technology transfer, such as misinterpretation, misrepresentation, and increased stigmatization, could compromise patient care. The insights of stakeholder groups about neuroimaging for mental health care are a largely untapped resource of information and guidance for translational efforts. We argue that the insights of key stakeholders—including researchers, healthcare providers, patients, and families—have an essential role to play upstream in professional, critical, and ethical discourse surrounding neuroimaging in mental health. Here we integrate previously orthogonal lines of inquiry involving stakeholder research to describe the translational landscape as well as challenges on its horizon. PMID:23097640
Neuroimaging and Other Biomarkers for Alzheimer's Disease: The Changing Landscape of Early Detection
Risacher, Shannon L.; Saykin, Andrew J.
2014-01-01
The goal of this review is to provide an overview of biomarkers for Alzheimer's disease (AD), with emphasis on neuroimaging and cerebrospinal fluid (CSF) biomarkers. We first review biomarker changes in patients with late-onset AD, including findings from studies using structural and functional magnetic resonance imaging (MRI), advanced MRI techniques (diffusion tensor imaging, magnetic resonance spectroscopy, perfusion), positron emission tomography with fluorodeoxyglucose, amyloid tracers, and other neurochemical tracers, and CSF protein levels. Next, we evaluate findings from these biomarkers in preclinical and prodromal stages of AD including mild cognitive impairment (MCI) and pre-MCI conditions conferring elevated risk. We then discuss related findings in patients with dominantly inherited AD. We conclude with a discussion of the current theoretical framework for the role of biomarkers in AD and emergent directions for AD biomarker research. PMID:23297785
Wronkiewicz, Mark; Larson, Eric; Lee, Adrian Kc
2016-10-01
Brain-computer interface (BCI) technology allows users to generate actions based solely on their brain signals. However, current non-invasive BCIs generally classify brain activity recorded from surface electroencephalography (EEG) electrodes, which can hinder the application of findings from modern neuroscience research. In this study, we use source imaging-a neuroimaging technique that projects EEG signals onto the surface of the brain-in a BCI classification framework. This allowed us to incorporate prior research from functional neuroimaging to target activity from a cortical region involved in auditory attention. Classifiers trained to detect attention switches performed better with source imaging projections than with EEG sensor signals. Within source imaging, including subject-specific anatomical MRI information (instead of using a generic head model) further improved classification performance. This source-based strategy also reduced accuracy variability across three dimensionality reduction techniques-a major design choice in most BCIs. Our work shows that source imaging provides clear quantitative and qualitative advantages to BCIs and highlights the value of incorporating modern neuroscience knowledge and methods into BCI systems.
Developmental Sex Differences in the Relation of Neuroanatomical Connectivity to Intelligence
ERIC Educational Resources Information Center
Schmithorst, Vincent J.
2009-01-01
Recent neuroimaging research has shown sex-related differences in the relationship between brain structure and cognitive function. Anatomical studies have shown a greater reliance for cognitive function on white matter structure in adult females, and a greater reliance on gray matter structure in adult males. Functional neuroimaging studies have…
Neuroimaging of Cognitive Load in Instructional Multimedia
ERIC Educational Resources Information Center
Whelan, Robert R.
2007-01-01
This paper reviews research literature on cognitive load measurement in learning and neuroimaging, and describes a mapping between the main elements of cognitive load theory and findings in functional neuroanatomy. It is argued that these findings may lead to the improved measurement of cognitive load using neuroimaging. The paper describes how…
Multilingual Processing in the Brain
ERIC Educational Resources Information Center
van den Noort, Maurits; Struys, Esli; Kim, Kayoung; Bosch, Peggy; Mondt, Katrien; van Kralingen, Rosalinde; Lee, Mikyoung; van de Craen, Piet
2014-01-01
In this paper, in contrast to previous neuroimaging literature reviews on first language (L1) and second language (L2), the focus was only on neuroimaging studies that were directly conducted on multilingual participants. In total, 14 neuroimaging studies were included in our study such as 10 functional magnetic resonance imaging, 1 positron…
Pena-Garijo, Josep; Ruipérez-Rodríguez, M Angeles; Barros-Loscertales, Alfonso
2010-05-01
In recent years, neuroscience has shown a growing interest in applying its methods to furthering the knowledge of psychiatric disorders, and one of the fundamental tools used to do so are neuroimaging techniques. Yet, in general, few studies have been conducted in which functional magnetic resonance has been applied in this field and findings are sometimes contradictory. In this study we review the specialised bibliography and present a critical discussion on the scientific literature published to date on the application of functional magnetic resonance and diffusion tensor imaging to one of the most widely studied disorders, from a neurobiological point of view, namely, obsessive-compulsive disorder. The study reviews the articles on the use of functional magnetic resonance imaging, as well as those dealing with neural connectivity, that have been indexed in the most commonly used medical databases on the topic since 1996. Most studies suggest that the prefrontal cortex (orbitofrontal and cingulate), the basal ganglia and the thalamus are involved in the pathogenesis of obsessive-compulsive disorder. Likewise, alterations in the white matter that affect neural connectivity have also been found. The contributions made by neuroimaging and, more specifically, by functional magnetic resonance imaging are and will undoubtedly continue to be a particularly interesting tool for explaining the aetiology of this disorder.
Amyot, Franck; Arciniegas, David B; Brazaitis, Michael P; Curley, Kenneth C; Diaz-Arrastia, Ramon; Gandjbakhche, Amir; Herscovitch, Peter; Hinds, Sidney R; Manley, Geoffrey T; Pacifico, Anthony; Razumovsky, Alexander; Riley, Jason; Salzer, Wanda; Shih, Robert; Smirniotopoulos, James G; Stocker, Derek
2015-11-15
The incidence of traumatic brain injury (TBI) in the United States was 3.5 million cases in 2009, according to the Centers for Disease Control and Prevention. It is a contributing factor in 30.5% of injury-related deaths among civilians. Additionally, since 2000, more than 260,000 service members were diagnosed with TBI, with the vast majority classified as mild or concussive (76%). The objective assessment of TBI via imaging is a critical research gap, both in the military and civilian communities. In 2011, the Department of Defense (DoD) prepared a congressional report summarizing the effectiveness of seven neuroimaging modalities (computed tomography [CT], magnetic resonance imaging [MRI], transcranial Doppler [TCD], positron emission tomography, single photon emission computed tomography, electrophysiologic techniques [magnetoencephalography and electroencephalography], and functional near-infrared spectroscopy) to assess the spectrum of TBI from concussion to coma. For this report, neuroimaging experts identified the most relevant peer-reviewed publications and assessed the quality of the literature for each of these imaging technique in the clinical and research settings. Although CT, MRI, and TCD were determined to be the most useful modalities in the clinical setting, no single imaging modality proved sufficient for all patients due to the heterogeneity of TBI. All imaging modalities reviewed demonstrated the potential to emerge as part of future clinical care. This paper describes and updates the results of the DoD report and also expands on the use of angiography in patients with TBI.
A Review of the Effectiveness of Neuroimaging Modalities for the Detection of Traumatic Brain Injury
Amyot, Franck; Arciniegas, David B.; Brazaitis, Michael P.; Curley, Kenneth C.; Diaz-Arrastia, Ramon; Gandjbakhche, Amir; Herscovitch, Peter; Hinds, Sidney R.; Manley, Geoffrey T.; Razumovsky, Alexander; Riley, Jason; Salzer, Wanda; Shih, Robert; Smirniotopoulos, James G.; Stocker, Derek
2015-01-01
Abstract The incidence of traumatic brain injury (TBI) in the United States was 3.5 million cases in 2009, according to the Centers for Disease Control and Prevention. It is a contributing factor in 30.5% of injury-related deaths among civilians. Additionally, since 2000, more than 260,000 service members were diagnosed with TBI, with the vast majority classified as mild or concussive (76%). The objective assessment of TBI via imaging is a critical research gap, both in the military and civilian communities. In 2011, the Department of Defense (DoD) prepared a congressional report summarizing the effectiveness of seven neuroimaging modalities (computed tomography [CT], magnetic resonance imaging [MRI], transcranial Doppler [TCD], positron emission tomography, single photon emission computed tomography, electrophysiologic techniques [magnetoencephalography and electroencephalography], and functional near-infrared spectroscopy) to assess the spectrum of TBI from concussion to coma. For this report, neuroimaging experts identified the most relevant peer-reviewed publications and assessed the quality of the literature for each of these imaging technique in the clinical and research settings. Although CT, MRI, and TCD were determined to be the most useful modalities in the clinical setting, no single imaging modality proved sufficient for all patients due to the heterogeneity of TBI. All imaging modalities reviewed demonstrated the potential to emerge as part of future clinical care. This paper describes and updates the results of the DoD report and also expands on the use of angiography in patients with TBI. PMID:26176603
Tost, H; Meyer-Lindenberg, A; Ruf, M; Demirakça, T; Grimm, O; Henn, F A; Ende, G
2005-02-01
Modern neuroimaging techniques such as magnetic resonance imaging (MRI) and positron emission tomography (PET) have contributed tremendously to our current understanding of psychiatric disorders in the context of functional, biochemical and microstructural alterations of the brain. Since the mid-nineties, functional MRI has provided major insights into the neurobiological correlates of signs and symptoms in schizophrenia. The current paper reviews important fMRI studies of the past decade in the domains of motor, visual, auditory, attentional and working memory function. Special emphasis is given to new methodological approaches, such as the visualisation of medication effects and the functional characterisation of risk genes.
Towards a model-based cognitive neuroscience of stopping - a neuroimaging perspective.
Sebastian, Alexandra; Forstmann, Birte U; Matzke, Dora
2018-07-01
Our understanding of the neural correlates of response inhibition has greatly advanced over the last decade. Nevertheless the specific function of regions within this stopping network remains controversial. The traditional neuroimaging approach cannot capture many processes affecting stopping performance. Despite the shortcomings of the traditional neuroimaging approach and a great progress in mathematical and computational models of stopping, model-based cognitive neuroscience approaches in human neuroimaging studies are largely lacking. To foster model-based approaches to ultimately gain a deeper understanding of the neural signature of stopping, we outline the most prominent models of response inhibition and recent advances in the field. We highlight how a model-based approach in clinical samples has improved our understanding of altered cognitive functions in these disorders. Moreover, we show how linking evidence-accumulation models and neuroimaging data improves the identification of neural pathways involved in the stopping process and helps to delineate these from neural networks of related but distinct functions. In conclusion, adopting a model-based approach is indispensable to identifying the actual neural processes underlying stopping. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.
ERIC Educational Resources Information Center
Baker, Joseph M.; Moyer-Packenham, Patricia S.; Tucker, Stephen I.; Shumway, Jessica F.; Jordan, Kerry E.; Gillam, Ronald B.
2018-01-01
Functional near-infrared spectroscopy (fNIRS) is an easy to use neuroimaging technique that is portable and maintains a liberal tolerance to movement. As such, fNIRS represents an ideal tool to observe children's neural activity as they engage in real-world classroom activities, such as the interaction with digital math apps on an iPad. Here, we…
Emotion, Cognition, and Behavior
NASA Astrophysics Data System (ADS)
Dolan, R. J.
2002-11-01
Emotion is central to the quality and range of everyday human experience. The neurobiological substrates of human emotion are now attracting increasing interest within the neurosciences motivated, to a considerable extent, by advances in functional neuroimaging techniques. An emerging theme is the question of how emotion interacts with and influences other domains of cognition, in particular attention, memory, and reasoning. The psychological consequences and mechanisms underlying the emotional modulation of cognition provide the focus of this article.
Parsing brain activity with fMRI and mixed designs: what kind of a state is neuroimaging in?
Donaldson, David I
2004-08-01
Neuroimaging is often pilloried for providing little more than pretty pictures that simply show where activity occurs in the brain. Strong critics (notably Uttal) have even argued that neuroimaging is nothing more than a modern day version of phrenology: destined to fail, and fundamentally uninformative. Here, I make the opposite case, arguing that neuroimaging is in a vibrant and healthy state of development. As recent investigations of memory illustrate, when used well, neuroimaging goes beyond asking 'where' activity is occurring, to ask questions concerned more with 'what' functional role the activity reflects.
Restructuring consciousness -the psychedelic state in light of integrated information theory.
Gallimore, Andrew R
2015-01-01
The psychological state elicited by the classic psychedelics drugs, such as LSD and psilocybin, is one of the most fascinating and yet least understood states of consciousness. However, with the advent of modern functional neuroimaging techniques, the effect of these drugs on neural activity is now being revealed, although many of the varied phenomenological features of the psychedelic state remain challenging to explain. Integrated information theory (IIT) is one of the foremost contemporary theories of consciousness, providing a mathematical formalization of both the quantity and quality of conscious experience. This theory can be applied to all known states of consciousness, including the psychedelic state. Using the results of functional neuroimaging data on the psychedelic state, the effects of psychedelic drugs on both the level and structure of consciousness can be explained in terms of the conceptual framework of IIT. This new IIT-based model of the psychedelic state provides an explanation for many of its phenomenological features, including unconstrained cognition, alterations in the structure and meaning of concepts and a sense of expanded awareness. This model also suggests that whilst cognitive flexibility, creativity, and imagination are enhanced during the psychedelic state, this occurs at the expense of cause-effect information, as well as degrading the brain's ability to organize, categorize, and differentiate the constituents of conscious experience. Furthermore, the model generates specific predictions that can be tested using a combination of functional imaging techniques, as has been applied to the study of levels of consciousness during anesthesia and following brain injury.
Fantini, Sergio
2014-01-15
This article presents a dynamic model that quantifies the temporal evolution of the concentration and oxygen saturation of hemoglobin in tissue, as determined by time-varying hemodynamic and metabolic parameters: blood volume, flow velocity, and oxygen consumption. This multi-compartment model determines separate contributions from arterioles, capillaries, and venules that comprise the tissue microvasculature, and treats them as a complete network, without making assumptions on the details of the architecture and morphology of the microvascular bed. A key parameter in the model is the effective blood transit time through the capillaries and its associated probability of oxygen release from hemoglobin to tissue, as described by a rate constant for oxygen diffusion. The solution of the model in the time domain predicts the signals measured by hemodynamic-based neuroimaging techniques such as functional near-infrared spectroscopy (fNIRS) and functional magnetic resonance imaging (fMRI) in response to brain activation. In the frequency domain, the model yields an analytical solution based on a phasor representation that provides a framework for quantitative spectroscopy of coherent hemodynamic oscillations. I term this novel technique coherent hemodynamics spectroscopy (CHS), and this article describes how it can be used for the assessment of cerebral autoregulation and the study of hemodynamic oscillations resulting from a variety of periodic physiological challenges, brain activation protocols, or physical maneuvers. Copyright © 2013 Elsevier Inc. All rights reserved.
Fantini, Sergio
2013-01-01
This article presents a dynamic model that quantifies the temporal evolution of the concentration and oxygen saturation of hemoglobin in tissue, as determined by time-varying hemodynamic and metabolic parameters: blood volume, flow velocity, and oxygen consumption. This multi-compartment model determines separate contributions from arterioles, capillaries, and venules that comprise the tissue microvasculature, and treats them as a complete network, without making assumptions on the details of the architecture and morphology of the microvascular bed. A key parameter in the model is the effective blood transit time through the capillaries and its associated probability of oxygen release from hemoglobin to tissue, as described by a rate constant for oxygen diffusion. The solution of the model in the time domain predicts the signals measured by hemodynamic-based neuroimaging techniques such as functional near-infrared spectroscopy (fNIRS) and functional magnetic resonance imaging (fMRI) in response to brain activation. In the frequency domain, the model yields an analytical solution based on a phasor representation that provides a framework for quantitative spectroscopy of coherent hemodynamic oscillations. I term this novel technique coherent hemodynamics spectroscopy (CHS), and this article describes how it can be used for the assessment of cerebral autoregulation and the study of hemodynamic oscillations resulting from a variety of periodic physiological challenges, brain activation protocols, or physical maneuvers. PMID:23583744
Kulynych, Jennifer
2002-12-01
Humans subjects research entails significant legal and ethical obligations. Neuroimaging researchers must be familiar with the requirements of human subjects protection, including evolving standards for the protection of privacy and the disclosure of risk in "non-therapeutic" research. Techniques for creating veridical surface renderings from volumetric anatomical imaging data raise new privacy concerns, particularly under the federal medical privacy regulation. Additionally, neuroimaging researchers must consider their obligation to communicate research results responsibly. The emerging field of neuroethics should strive to raise awareness of these issues and to involve neuroimaging researchers in the legal, ethical, and policy debates that currently surround human subjects research.
Groman, Stephanie M.; James, Alex S.; Seu, Emanuele; Tran, Steven; Clark, Taylor A.; Harpster, Sandra N.; Crawford, Maverick; Burtner, Joanna Lee; Feiler, Karen; Roth, Robert H.; Elsworth, John D.; London, Edythe D.
2014-01-01
For >30 years, positron emission tomography (PET) has proven to be a powerful approach for measuring aspects of dopaminergic transmission in the living human brain; this technique has revealed important relationships between dopamine D2-like receptors and dimensions of normal behavior, such as human impulsivity, and psychopathology, particularly behavioral addictions. Nevertheless, PET is an indirect estimate that lacks cellular and functional resolution and, in some cases, is not entirely pharmacologically specific. To identify the relationships between PET estimates of D2-like receptor availability and direct in vitro measures of receptor number, affinity, and function, we conducted neuroimaging and behavioral and molecular pharmacological assessments in a group of adult male vervet monkeys. Data gathered from these studies indicate that variation in D2-like receptor PET measurements is related to reversal-learning performance and sensitivity to positive feedback and is associated with in vitro estimates of the density of functional dopamine D2-like receptors. Furthermore, we report that a simple behavioral measure, eyeblink rate, reveals novel and crucial links between neuroimaging assessments and in vitro measures of dopamine D2 receptors. PMID:25339755
Human Fear Conditioning and Extinction in Neuroimaging: A Systematic Review
Sehlmeyer, Christina; Schöning, Sonja; Zwitserlood, Pienie; Pfleiderer, Bettina; Kircher, Tilo; Arolt, Volker; Konrad, Carsten
2009-01-01
Fear conditioning and extinction are basic forms of associative learning that have gained considerable clinical relevance in enhancing our understanding of anxiety disorders and facilitating their treatment. Modern neuroimaging techniques have significantly aided the identification of anatomical structures and networks involved in fear conditioning. On closer inspection, there is considerable variation in methodology and results between studies. This systematic review provides an overview of the current neuroimaging literature on fear conditioning and extinction on healthy subjects, taking into account methodological issues such as the conditioning paradigm. A Pubmed search, as of December 2008, was performed and supplemented by manual searches of bibliographies of key articles. Two independent reviewers made the final study selection and data extraction. A total of 46 studies on cued fear conditioning and/or extinction on healthy volunteers using positron emission tomography or functional magnetic resonance imaging were reviewed. The influence of specific experimental factors, such as contingency and timing parameters, assessment of conditioned responses, and characteristics of conditioned and unconditioned stimuli, on cerebral activation patterns was examined. Results were summarized descriptively. A network consisting of fear-related brain areas, such as amygdala, insula, and anterior cingulate cortex, is activated independently of design parameters. However, some neuroimaging studies do not report these findings in the presence of methodological heterogeneities. Furthermore, other brain areas are differentially activated, depending on specific design parameters. These include stronger hippocampal activation in trace conditioning and tactile stimulation. Furthermore, tactile unconditioned stimuli enhance activation of pain related, motor, and somatosensory areas. Differences concerning experimental factors may partly explain the variance between neuroimaging investigations on human fear conditioning and extinction and should, therefore, be taken into serious consideration in the planning and the interpretation of research projects. PMID:19517024
Functional neuroimaging of emotional learning and autonomic reactions.
Peper, Martin; Herpers, Martin; Spreer, Joachim; Hennig, Jürgen; Zentner, Josef
2006-06-01
This article provides a selective overview of the functional neuroimaging literature with an emphasis on emotional activation processes. Emotions are fast and flexible response systems that provide basic tendencies for adaptive action. From the range of involved component functions, we first discuss selected automatic mechanisms that control basic adaptational changes. Second, we illustrate how neuroimaging work has contributed to the mapping of the network components associated with basic emotion families (fear, anger, disgust, happiness), and secondary dimensional concepts that organise the meaning space for subjective experience and verbal labels (emotional valence, activity/intensity, approach/withdrawal, etc.). Third, results and methodological difficulties are discussed in view of own neuroimaging experiments that investigated the component functions involved in emotional learning. The amygdala, prefrontal cortex, and striatum form a network of reciprocal connections that show topographically distinct patterns of activity as a correlate of up and down regulation processes during an emotional episode. Emotional modulations of other brain systems have attracted recent research interests. Emotional neuroimaging calls for more representative designs that highlight the modulatory influences of regulation strategies and socio-cultural factors responsible for inhibitory control and extinction. We conclude by emphasising the relevance of the temporal process dynamics of emotional activations that may provide improved prediction of individual differences in emotionality.
Prediction of recovery of motor function after stroke.
Stinear, Cathy
2010-12-01
Stroke is a leading cause of disability. The ability to live independently after stroke depends largely on the reduction of motor impairment and the recovery of motor function. Accurate prediction of motor recovery assists rehabilitation planning and supports realistic goal setting by clinicians and patients. Initial impairment is negatively related to degree of recovery, but inter-individual variability makes accurate prediction difficult. Neuroimaging and neurophysiological assessments can be used to measure the extent of stroke damage to the motor system and predict subsequent recovery of function, but these techniques are not yet used routinely. The use of motor impairment scores and neuroimaging has been refined by two recent studies in which these investigations were used at multiple time points early after stroke. Voluntary finger extension and shoulder abduction within 5 days of stroke predicted subsequent recovery of upper-limb function. Diffusion-weighted imaging within 7 days detected the effects of stroke on caudal motor pathways and was predictive of lasting motor impairment. Thus, investigations done soon after stroke had good prognostic value. The potential prognostic value of cortical activation and neural plasticity has been explored for the first time by two recent studies. Functional MRI detected a pattern of cortical activation at the acute stage that was related to subsequent reduction in motor impairment. Transcranial magnetic stimulation enabled measurement of neural plasticity in the primary motor cortex, which was related to subsequent disability. These studies open interesting new lines of enquiry. WHERE NEXT?: The accuracy of prediction might be increased by taking into account the motor system's capacity for functional reorganisation in response to therapy, in addition to the extent of stroke-related damage. Improved prognostic accuracy could also be gained by combining simple tests of motor impairment with neuroimaging, genotyping, and neurophysiological assessment of neural plasticity. The development of algorithms to guide the sequential combinations of these assessments could also further increase accuracy, in addition to improving rehabilitation planning and outcomes. Copyright © 2010 Elsevier Ltd. All rights reserved.
Functional Neuro-Imaging and Post-Traumatic Olfactory Impairment
Roberts, Richard J.; Sheehan, William; Thurber, Steven; Roberts, Mary Ann
2010-01-01
Objective: To evaluate via a research literature survey the anterior neurological significance of decreased olfactory functioning following traumatic brain injuries. Materials and Methods: A computer literature review was performed to locate all functional neuro-imaging studies on patients with post-traumatic anosmia and other olfactory deficits. Results: A convergence of findings from nine functional neuro-imaging studies indicating evidence for reduced metabolic activity at rest or relative hypo-perfusion during olfactory activations. Hypo-activation of the prefrontal regions was apparent in all nine post-traumatic samples, with three samples yielding evidence of reduced activity in the temporal regions as well. Conclusions: The practical ramifications include the reasonable hypothesis that a total anosmic head trauma patient likely has frontal lobe involvement. PMID:21716782
How the blind "see" Braille: lessons from functional magnetic resonance imaging.
Sadato, Norihiro
2005-12-01
What does the visual cortex of the blind do during Braille reading? This process involves converting simple tactile information into meaningful patterns that have lexical and semantic properties. The perceptual processing of Braille might be mediated by the somatosensory system, whereas visual letter identity is accomplished within the visual system in sighted people. Recent advances in functional neuroimaging techniques, such as functional magnetic resonance imaging, have enabled exploration of the neural substrates of Braille reading. The primary visual cortex of early-onset blind subjects is functionally relevant to Braille reading, suggesting that the brain shows remarkable plasticity that potentially permits the additional processing of tactile information in the visual cortical areas.
ERIC Educational Resources Information Center
Pavuluri, Mani N.; Sweeney, John A.
2008-01-01
The use of cognitive neuroscience and functional brain neuroimaging to understand brain dysfunction in pediatric psychiatric disorders is discussed. Results show that bipolar youths demonstrate impairment in affective and cognitive neural systems and in these two circuits' interface. Implications for the diagnosis and treatment of psychiatric…
The social evaluation of faces: a meta-analysis of functional neuroimaging studies
Mende-Siedlecki, Peter; Said, Christopher P.
2013-01-01
Neuroscience research on the social evaluation of faces has accumulated over the last decade, yielding divergent results. We used a meta-analytic technique, multi-level kernel density analysis (MKDA), to analyze 29 neuroimaging studies on face evaluation. Across negative face evaluations, we observed the most consistent activations in bilateral amygdala. Across positive face evaluations, we observed the most consistent activations in medial prefrontal cortex, pregenual anterior cingulate cortex (pgACC), medial orbitofrontal cortex (mOFC), left caudate and nucleus accumbens (NAcc). Based on additional analyses comparing linear and non-linear responses, we propose a ventral/dorsal dissociation within the amygdala, wherein separate populations of neurons code for face valence and intensity, respectively. Finally, we argue that some of the differences between studies are attributable to differences in the typicality of face stimuli. Specifically, extremely attractive faces are more likely to elicit responses in NAcc/caudate and mOFC. PMID:22287188
2010-01-01
In clinical neurology, a comprehensive understanding of consciousness has been regarded as an abstract concept - best left to philosophers. However, times are changing and the need to clinically assess consciousness is increasingly becoming a real-world, practical challenge. Current methods for evaluating altered levels of consciousness are highly reliant on either behavioural measures or anatomical imaging. While these methods have some utility, estimates of misdiagnosis are worrisome (as high as 43%) - clearly this is a major clinical problem. The solution must involve objective, physiologically based measures that do not rely on behaviour. This paper reviews recent advances in physiologically based measures that enable better evaluation of consciousness states (coma, vegetative state, minimally conscious state, and locked in syndrome). Based on the evidence to-date, electroencephalographic and neuroimaging based assessments of consciousness provide valuable information for evaluation of residual function, formation of differential diagnoses, and estimation of prognosis. PMID:20113490
Neuroimaging Endophenotypes in Autism Spectrum Disorder
Mahajan, Rajneesh; Mostofsky, Stewart H.
2015-01-01
Autism spectrum disorder (ASD) is a neurodevelopmental disorder that has a strong genetic basis, and is heterogeneous in its etiopathogenesis and clinical presentation. Neuroimaging studies, in concert with neuropathological and clinical research, have been instrumental in delineating trajectories of development in children with ASD. Structural neuroimaging has revealed ASD to be a disorder with general and regional brain enlargement, especially in the frontotemporal cortices, while functional neuroimaging studies have highlighted diminished connectivity, especially between frontal-posterior regions. The diverse and specific neuroimaging findings may represent potential neuroendophenotypes, and may offer opportunities to further understand the etiopathogenesis of ASD, predict treatment response and lead to the development of new therapies. PMID:26234701
Machine learning for neuroimaging with scikit-learn.
Abraham, Alexandre; Pedregosa, Fabian; Eickenberg, Michael; Gervais, Philippe; Mueller, Andreas; Kossaifi, Jean; Gramfort, Alexandre; Thirion, Bertrand; Varoquaux, Gaël
2014-01-01
Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of activation images or resting-state time series. Supervised learning is typically used in decoding or encoding settings to relate brain images to behavioral or clinical observations, while unsupervised learning can uncover hidden structures in sets of images (e.g., resting state functional MRI) or find sub-populations in large cohorts. By considering different functional neuroimaging applications, we illustrate how scikit-learn, a Python machine learning library, can be used to perform some key analysis steps. Scikit-learn contains a very large set of statistical learning algorithms, both supervised and unsupervised, and its application to neuroimaging data provides a versatile tool to study the brain.
Machine learning for neuroimaging with scikit-learn
Abraham, Alexandre; Pedregosa, Fabian; Eickenberg, Michael; Gervais, Philippe; Mueller, Andreas; Kossaifi, Jean; Gramfort, Alexandre; Thirion, Bertrand; Varoquaux, Gaël
2014-01-01
Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of activation images or resting-state time series. Supervised learning is typically used in decoding or encoding settings to relate brain images to behavioral or clinical observations, while unsupervised learning can uncover hidden structures in sets of images (e.g., resting state functional MRI) or find sub-populations in large cohorts. By considering different functional neuroimaging applications, we illustrate how scikit-learn, a Python machine learning library, can be used to perform some key analysis steps. Scikit-learn contains a very large set of statistical learning algorithms, both supervised and unsupervised, and its application to neuroimaging data provides a versatile tool to study the brain. PMID:24600388
Zając-Lamparska, Ludmiła; Wiłkość, Monika; Markowska, Anita; Laskowska-Levy, Ilona Paulina; Wróbel, Marek; Małkowski, Bogdan
2017-08-29
Functional neuroimaging of the brain is a widely used method to study cognitive functions. The aim of this study was to compare the activity of the brain during performance of the tasks of phonemic and semantic fluency with the paced-overt technique in terms of prolonged activation of the brain. The study included 17 patients aged 20-40 years who were treated in the past for Hodgkin'slymphoma, now in remission. Due to the type of task, the subjectswere divided into two groups. Nine people performed the phonemic fluency task, and eight semantic. Due to the disease, all subjects were subject to neuropsychological diagnosis. The diagnosis of any cognitive impairment was an exclusion criterion. Neuroimaging was performed using PET technique with 18F-fluorodeoxyglucose (FDG) tracer. Performance of a verbal fluency test, regardless of the version of the task, was associated with greater activity of the left hemisphere of the brain. The most involved areas compared with other areas of key importance for the performance of verbal fluency tasks were frontal lobes. An increased activity of parietal structures was also shown. The study did not reveal differences in brain activity depending on the type of task. Performing the test in both phonemic and semantic form for a long time, in terms of increased cognitive control resulting from the test procedure, could result in significant advantage of prefrontal lobe activityin both types of tasks and made it impossible to observe the processes specific to each of them.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Minati, Ludovico
This paper is meant to provide a brief overview of the techniques currently used to image the brain and to study non-invasively its anatomy and function. After a historical summary in the first section, general aspects are outlined in the second section. The subsequent six sections survey, in order, computed tomography (CT), morphological magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), diffusion-tensor magnetic resonance imaging (DWI/DTI), positron emission tomography (PET), and electro- and magneto-encephalography (EEG/MEG) based imaging. Underlying physical principles, modelling and data processing approaches, as well as clinical and research relevance are briefly outlined for each technique. Givenmore » the breadth of the scope, there has been no attempt to be comprehensive. The ninth and final section outlines some aspects of active research in neuroimaging.« less
Magnetic resonance imaging for diagnosis of early Alzheimer's disease.
Colliot, O; Hamelin, L; Sarazin, M
2013-10-01
A major challenge for neuroimaging is to contribute to the early diagnosis of Alzheimer's disease (AD). In particular, magnetic resonance imaging (MRI) allows detecting different types of structural and functional abnormalities at an early stage of the disease. Anatomical MRI is the most widely used technique and provides local and global measures of atrophy. The recent diagnostic criteria of "mild cognitive impairment due to AD" include hippocampal atrophy, which is considered a marker of neuronal injury. Advanced image analysis techniques generate automatic and reproducible measures both in the hippocampus and throughout the whole brain. Recent modalities such as diffusion-tensor imaging and resting-state functional MRI provide additional measures that could contribute to the early diagnosis but require further validation. Copyright © 2013 Elsevier Masson SAS. All rights reserved.
A convergent functional architecture of the insula emerges across imaging modalities.
Kelly, Clare; Toro, Roberto; Di Martino, Adriana; Cox, Christine L; Bellec, Pierre; Castellanos, F Xavier; Milham, Michael P
2012-07-16
Empirical evidence increasingly supports the hypothesis that patterns of intrinsic functional connectivity (iFC) are sculpted by a history of evoked coactivation within distinct neuronal networks. This, together with evidence of strong correspondence among the networks defined by iFC and those delineated using a variety of other neuroimaging techniques, suggests a fundamental brain architecture detectable across multiple functional and structural imaging modalities. Here, we leverage this insight to examine the functional organization of the human insula. We parcellated the insula on the basis of three distinct neuroimaging modalities - task-evoked coactivation, intrinsic (i.e., task-independent) functional connectivity, and gray matter structural covariance. Clustering of these three different covariance-based measures revealed a convergent elemental organization of the insula that likely reflects a fundamental brain architecture governing both brain structure and function at multiple spatial scales. While not constrained to be hierarchical, our parcellation revealed a pseudo-hierarchical, multiscale organization that was consistent with previous clustering and meta-analytic studies of the insula. Finally, meta-analytic examination of the cognitive and behavioral domains associated with each of the insular clusters obtained elucidated the broad functional dissociations likely underlying the topography observed. To facilitate future investigations of insula function across healthy and pathological states, the insular parcels have been made freely available for download via http://fcon_1000.projects.nitrc.org, along with the analytic scripts used to perform the parcellations. Copyright © 2012 Elsevier Inc. All rights reserved.
Practical management of heterogeneous neuroimaging metadata by global neuroimaging data repositories
Neu, Scott C.; Crawford, Karen L.; Toga, Arthur W.
2012-01-01
Rapidly evolving neuroimaging techniques are producing unprecedented quantities of digital data at the same time that many research studies are evolving into global, multi-disciplinary collaborations between geographically distributed scientists. While networked computers have made it almost trivial to transmit data across long distances, collecting and analyzing this data requires extensive metadata if the data is to be maximally shared. Though it is typically straightforward to encode text and numerical values into files and send content between different locations, it is often difficult to attach context and implicit assumptions to the content. As the number of and geographic separation between data contributors grows to national and global scales, the heterogeneity of the collected metadata increases and conformance to a single standardization becomes implausible. Neuroimaging data repositories must then not only accumulate data but must also consolidate disparate metadata into an integrated view. In this article, using specific examples from our experiences, we demonstrate how standardization alone cannot achieve full integration of neuroimaging data from multiple heterogeneous sources and why a fundamental change in the architecture of neuroimaging data repositories is needed instead. PMID:22470336
Neu, Scott C; Crawford, Karen L; Toga, Arthur W
2012-01-01
Rapidly evolving neuroimaging techniques are producing unprecedented quantities of digital data at the same time that many research studies are evolving into global, multi-disciplinary collaborations between geographically distributed scientists. While networked computers have made it almost trivial to transmit data across long distances, collecting and analyzing this data requires extensive metadata if the data is to be maximally shared. Though it is typically straightforward to encode text and numerical values into files and send content between different locations, it is often difficult to attach context and implicit assumptions to the content. As the number of and geographic separation between data contributors grows to national and global scales, the heterogeneity of the collected metadata increases and conformance to a single standardization becomes implausible. Neuroimaging data repositories must then not only accumulate data but must also consolidate disparate metadata into an integrated view. In this article, using specific examples from our experiences, we demonstrate how standardization alone cannot achieve full integration of neuroimaging data from multiple heterogeneous sources and why a fundamental change in the architecture of neuroimaging data repositories is needed instead.
Wintermark, M; Sanelli, P C; Anzai, Y; Tsiouris, A J; Whitlow, C T
2015-02-01
Neuroimaging plays a critical role in the evaluation of patients with traumatic brain injury, with NCCT as the first-line of imaging for patients with traumatic brain injury and MR imaging being recommended in specific settings. Advanced neuroimaging techniques, including MR imaging DTI, blood oxygen level-dependent fMRI, MR spectroscopy, perfusion imaging, PET/SPECT, and magnetoencephalography, are of particular interest in identifying further injury in patients with traumatic brain injury when conventional NCCT and MR imaging findings are normal, as well as for prognostication in patients with persistent symptoms. These advanced neuroimaging techniques are currently under investigation in an attempt to optimize them and substantiate their clinical relevance in individual patients. However, the data currently available confine their use to the research arena for group comparisons, and there remains insufficient evidence at the time of this writing to conclude that these advanced techniques can be used for routine clinical use at the individual patient level. TBI imaging is a rapidly evolving field, and a number of the recommendations presented will be updated in the future to reflect the advances in medical knowledge. © 2015 by American Journal of Neuroradiology.
Prakash, Neal; Uhleman, Falk; Sheth, Sameer A.; Bookheimer, Susan; Martin, Neil; Toga, Arthur W.
2009-01-01
Resection of a cerebral arteriovenous malformation (AVM), epileptic focus, or glioma, ideally has a prerequisite of microscopic delineation of the lesion borders in relation to the normal gray and white matter that mediate critical functions. Currently, Wada testing and functional magnetic resonance imaging (fMRI) are used for preoperative mapping of critical function, whereas electrical stimulation mapping (ESM) is used for intraoperative mapping. For lesion delineation, MRI and positron emission tomography (PET) are used preoperatively, whereas microscopy and histological sectioning are used intraoperatively. However, for lesions near eloquent cortex, these imaging techniques may lack sufficient resolution to define the relationship between the lesion and language function, and thus not accurately determine which patients will benefit from neurosurgical resection of the lesion without iatrogenic aphasia. Optical techniques such as intraoperative optical imaging of intrinsic signals (iOIS) show great promise for the precise functional mapping of cortices, as well as delineation of the borders of AVMs, epileptic foci, and gliomas. Here we first review the physiology of neuroimaging, and then progress towards the validation and justification of using intraoperative optical techniques, especially in relation to neurosurgical planning of resection AVMs, epileptic foci, and gliomas near or in eloquent cortex. We conclude with a short description of potential novel intraoperative optical techniques. PMID:18786643
[Imaging techniques for studying functional recovery following a stroke: I. Methodological aspects].
Ramos-Cabrer, P; Agulla, J; Argibay, B; Brea, D; Campos, F; Castillo, J
2011-03-16
Many patients that survive stroke have to face serious functional disabilities for the rest of their lives, which is a personal drama for themselves and their relatives, and an elevated charge for society. Thus functional recovery following stroke should be a key objective for the development of new therapeutic approaches. In this series of two works we review the strategies and tools available nowadays for the evaluation of multiple aspects related to brain function (both in humans and research animals), and how they are helping neuroscientist to better understand the processes of restoration and reorganization of brain function that are triggered following stroke. We have mainly focused on magnetic resonance applications, probably the most versatile neuroimaging technique available nowadays, and that everyday surprises us with new and exciting applications. But we tackle other alternative and complementary techniques, since a multidisciplinary approach allows a wider perspective over the underlying mechanisms behind tissue repair, plastic reorganization of the brain and compensatory mechanisms that are triggered after stroke. The first of the works of this series is focused on methodological aspects that will help us to understand how it is possible to assess brain function based on different physical and physiological principles. In the second work we will focus on different practical issues related to the application of the techniques here discussed.
Resting state functional connectivity: its physiological basis and application in neuropharmacology.
Lu, Hanbing; Stein, Elliot A
2014-09-01
Brain structures do not work in isolation; they work in concert to produce sensory perception, motivation and behavior. Systems-level network activity can be investigated by resting state magnetic resonance imaging (rsMRI), an emerging neuroimaging technique that assesses the synchrony of the brain's ongoing spontaneous activity. Converging evidence reveals that rsMRI is able to consistently identify distinct spatiotemporal patterns of large-scale brain networks. Dysregulation within and between these networks has been implicated in a number of neurodegenerative and neuropsychiatric disorders, including Alzheimer's disease and drug addiction. Despite wide application of this approach in systems neuroscience, the physiological basis of these fluctuations remains incompletely understood. Here we review physiological studies in electrical, metabolic and hemodynamic fluctuations that are most pertinent to the rsMRI signal. We also review recent applications to neuropharmacology - specifically drug effects on resting state fluctuations. We speculate that the mechanisms governing spontaneous fluctuations in regional oxygenation availability likely give rise to the observed rsMRI signal. We conclude by identifying several open questions surrounding this technique. This article is part of the Special Issue Section entitled 'Neuroimaging in Neuropharmacology'. Published by Elsevier Ltd.
Combining Feature Extraction Methods to Assist the Diagnosis of Alzheimer's Disease.
Segovia, F; Górriz, J M; Ramírez, J; Phillips, C
2016-01-01
Neuroimaging data as (18)F-FDG PET is widely used to assist the diagnosis of Alzheimer's disease (AD). Looking for regions with hypoperfusion/ hypometabolism, clinicians may predict or corroborate the diagnosis of the patients. Modern computer aided diagnosis (CAD) systems based on the statistical analysis of whole neuroimages are more accurate than classical systems based on quantifying the uptake of some predefined regions of interests (ROIs). In addition, these new systems allow determining new ROIs and take advantage of the huge amount of information comprised in neuroimaging data. A major branch of modern CAD systems for AD is based on multivariate techniques, which analyse a neuroimage as a whole, considering not only the voxel intensities but also the relations among them. In order to deal with the vast dimensionality of the data, a number of feature extraction methods have been successfully applied. In this work, we propose a CAD system based on the combination of several feature extraction techniques. First, some commonly used feature extraction methods based on the analysis of the variance (as principal component analysis), on the factorization of the data (as non-negative matrix factorization) and on classical magnitudes (as Haralick features) were simultaneously applied to the original data. These feature sets were then combined by means of two different combination approaches: i) using a single classifier and a multiple kernel learning approach and ii) using an ensemble of classifier and selecting the final decision by majority voting. The proposed approach was evaluated using a labelled neuroimaging database along with a cross validation scheme. As conclusion, the proposed CAD system performed better than approaches using only one feature extraction technique. We also provide a fair comparison (using the same database) of the selected feature extraction methods.
Restructuring consciousness –the psychedelic state in light of integrated information theory
Gallimore, Andrew R.
2015-01-01
The psychological state elicited by the classic psychedelics drugs, such as LSD and psilocybin, is one of the most fascinating and yet least understood states of consciousness. However, with the advent of modern functional neuroimaging techniques, the effect of these drugs on neural activity is now being revealed, although many of the varied phenomenological features of the psychedelic state remain challenging to explain. Integrated information theory (IIT) is one of the foremost contemporary theories of consciousness, providing a mathematical formalization of both the quantity and quality of conscious experience. This theory can be applied to all known states of consciousness, including the psychedelic state. Using the results of functional neuroimaging data on the psychedelic state, the effects of psychedelic drugs on both the level and structure of consciousness can be explained in terms of the conceptual framework of IIT. This new IIT-based model of the psychedelic state provides an explanation for many of its phenomenological features, including unconstrained cognition, alterations in the structure and meaning of concepts and a sense of expanded awareness. This model also suggests that whilst cognitive flexibility, creativity, and imagination are enhanced during the psychedelic state, this occurs at the expense of cause-effect information, as well as degrading the brain's ability to organize, categorize, and differentiate the constituents of conscious experience. Furthermore, the model generates specific predictions that can be tested using a combination of functional imaging techniques, as has been applied to the study of levels of consciousness during anesthesia and following brain injury. PMID:26124719
Ruocco, Anthony C.; Rodrigo, Achala H.; Lam, Jaeger; Di Domenico, Stefano I.; Graves, Bryanna; Ayaz, Hasan
2014-01-01
Problem-solving is an executive function subserved by a network of neural structures of which the dorsolateral prefrontal cortex (DLPFC) is central. Whereas several studies have evaluated the role of the DLPFC in problem-solving, few standardized tasks have been developed specifically for use with functional neuroimaging. The current study adapted a measure with established validity for the assessment of problem-solving abilities to design a test more suitable for functional neuroimaging protocols. The Scarborough adaptation of the Tower of London (S-TOL) was administered to 38 healthy adults while hemodynamic oxygenation of the PFC was measured using 16-channel continuous-wave functional near-infrared spectroscopy (fNIRS). Compared to a baseline condition, problems that required two or three steps to achieve a goal configuration were associated with higher activation in the left DLPFC and deactivation in the medial PFC. Individuals scoring higher in trait deliberation showed consistently higher activation in the left DLPFC regardless of task difficulty, whereas individuals lower in this trait displayed less activation when solving simple problems. Based on these results, the S-TOL may serve as a standardized task to evaluate problem-solving abilities in functional neuroimaging studies. PMID:24734017
2016-04-01
compared to 50 healthy veteran controls in a protocol that includes physical and neuropsychological evaluations, neuroimaging (MRI, fMRI, DTI), adrenal...SUBJECT TERMS Gulf War illness, neuroimaging, neuropsychological testing, immune function, hypothalamic-pituitary-adrenal testing 16. SECURITY... neuropsychological evaluations, assessment of hypothalamic-pituitary-adrenal function, standard clinical diagnostic laboratory tests, and research
Functional imaging and the cerebellum: recent developments and challenges. Editorial.
Habas, Christophe
2012-06-01
Recent neuroimaging developments allow a better in vivo characterization of the structural and functional connectivity of the human cerebellum. Ultrahigh fields, which considerably increase spatial resolution, enable to visualize deep cerebellar nuclei and cerebello-cortical sublayers. Tractography reconstructs afferent and efferent pathway of the cerebellum. Resting-state functional connectivity individualizes the prewired, parallel close-looped sensorimotor, cognitive, and affective networks passing through the cerebellum. These results are un agreement with activation maps obtained during stimulation functional neuroimaging or inferred from neurological deficits due to cerebellar lesions. Therefore, neuroimaging supports the hypothesis that cerebellum constitutes a general modulator involved in optimizing mental performance and computing internal models. However, the great challenges will remain to unravel: (1) the functional role of red and bulbar olivary nuclei, (2) the information processing in the cerebellar microcircuitry, and (3) the abstract computation performed by the cerebellum and shared by sensorimotor, cognitive, and affective domains.
[Social neuroscience and psychiatry].
Takahashi, Hidehiko
2013-01-01
The topics of emotion, decision-making, and consciousness have been traditionally dealt with in the humanities and social sciences. With the dissemination of noninvasive human neuroimaging techniques such as fMRI and the advancement of cognitive science, neuroimaging studies focusing on emotions, social cognition, and decision-making have become established. I overviewed the history of social neurosciences. The emerging field of social brain research or social neuroscience will greatly contribute to clinical psychiatry. In the first part. I introduced our early fMRI studies on social emotions such as guilt, embarrassment, pride, and envy. Dysfunction of social emotions can be observed in various forms of psychiatric disorder, and the findings should contribute to a better understanding of the pathophysiology of psychiatric conditions. In the second part, I introduced our recent interdisciplinary neuroscience approach combining molecular neuroimaging techniques(positron emission tomography: PET), cognitive sciences, and economics to understand the neural as well as molecular basis of altered decision-making in neuropsychiatric disorders. An interdisciplinary approach combing molecular imaging techniques and cognitive neuroscience and clinical psychiatry will provide new perspectives for understanding the neurobiology of impaired decision-making in neuropsychiatric disorders and drug development.
Neuroimaging of amblyopia and binocular vision: a review
Joly, Olivier; Frankó, Edit
2014-01-01
Amblyopia is a cerebral visual impairment considered to derive from abnormal visual experience (e.g., strabismus, anisometropia). Amblyopia, first considered as a monocular disorder, is now often seen as a primarily binocular disorder resulting in more and more studies examining the binocular deficits in the patients. The neural mechanisms of amblyopia are not completely understood even though they have been investigated with electrophysiological recordings in animal models and more recently with neuroimaging techniques in humans. In this review, we summarize the current knowledge about the brain regions that underlie the visual deficits associated with amblyopia with a focus on binocular vision using functional magnetic resonance imaging. The first studies focused on abnormal responses in the primary and secondary visual areas whereas recent evidence shows that there are also deficits at higher levels of the visual pathways within the parieto-occipital and temporal cortices. These higher level areas are part of the cortical network involved in 3D vision from binocular cues. Therefore, reduced responses in these areas could be related to the impaired binocular vision in amblyopic patients. Promising new binocular treatments might at least partially correct the activation in these areas. Future neuroimaging experiments could help to characterize the brain response changes associated with these treatments and help devise them. PMID:25147511
Jak, Amy J.; Bangen, Katherine J.; Wierenga, Christina E.; Delano-Wood, Lisa; Corey-Bloom, Jody; Bondi, Mark W.
2010-01-01
The original conceptualization of mild cognitive impairment (MCI) was primarily as an amnestic disorder representing an intermediate stage between normal aging and Alzheimer’s dementia (AD). More recently, broader conceptualizations of MCI have emerged that also encompass cognitive domains other than memory. These characterizations delineate clinical subtypes that commonly include amnestic and non-amnestic forms, and that involve single and multiple cognitive domains. With the advent of these broader classifications, more specific information is emerging regarding the neuropsychological presentation of individuals with MCI, risk for dementia associated with different subtypes of MCI, and neuropathologic substrates connected to the clinical subtypes. This review provides an overview of this burgeoning literature specific to clinical subtypes of MCI. Focus is primarily on neuropsychological and structural neuroimaging findings specific to clinical subtypes of MCI as well as the issue of daily functioning. Although investigations of non-amnestic subtypes using advanced neuroimaging techniques and clinical trials are quite limited, we briefly review these topics in MCI because these data provide a framework for future investigations specifically examining additional clinical subtypes of MCI. Finally, the review comments on select methodological issues involved in studying this heterogeneous population, and future directions to continue to improve our understanding of MCI and its clinical subtypes are offered. PMID:19501714
McFarquhar, Martyn; McKie, Shane; Emsley, Richard; Suckling, John; Elliott, Rebecca; Williams, Stephen
2016-01-01
Repeated measurements and multimodal data are common in neuroimaging research. Despite this, conventional approaches to group level analysis ignore these repeated measurements in favour of multiple between-subject models using contrasts of interest. This approach has a number of drawbacks as certain designs and comparisons of interest are either not possible or complex to implement. Unfortunately, even when attempting to analyse group level data within a repeated-measures framework, the methods implemented in popular software packages make potentially unrealistic assumptions about the covariance structure across the brain. In this paper, we describe how this issue can be addressed in a simple and efficient manner using the multivariate form of the familiar general linear model (GLM), as implemented in a new MATLAB toolbox. This multivariate framework is discussed, paying particular attention to methods of inference by permutation. Comparisons with existing approaches and software packages for dependent group-level neuroimaging data are made. We also demonstrate how this method is easily adapted for dependency at the group level when multiple modalities of imaging are collected from the same individuals. Follow-up of these multimodal models using linear discriminant functions (LDA) is also discussed, with applications to future studies wishing to integrate multiple scanning techniques into investigating populations of interest. PMID:26921716
Neuroimaging of amblyopia and binocular vision: a review.
Joly, Olivier; Frankó, Edit
2014-01-01
Amblyopia is a cerebral visual impairment considered to derive from abnormal visual experience (e.g., strabismus, anisometropia). Amblyopia, first considered as a monocular disorder, is now often seen as a primarily binocular disorder resulting in more and more studies examining the binocular deficits in the patients. The neural mechanisms of amblyopia are not completely understood even though they have been investigated with electrophysiological recordings in animal models and more recently with neuroimaging techniques in humans. In this review, we summarize the current knowledge about the brain regions that underlie the visual deficits associated with amblyopia with a focus on binocular vision using functional magnetic resonance imaging. The first studies focused on abnormal responses in the primary and secondary visual areas whereas recent evidence shows that there are also deficits at higher levels of the visual pathways within the parieto-occipital and temporal cortices. These higher level areas are part of the cortical network involved in 3D vision from binocular cues. Therefore, reduced responses in these areas could be related to the impaired binocular vision in amblyopic patients. Promising new binocular treatments might at least partially correct the activation in these areas. Future neuroimaging experiments could help to characterize the brain response changes associated with these treatments and help devise them.
Hyde, Luke W.; Shaw, Daniel S.; Hariri, Ahmad R.
2013-01-01
Youth antisocial behavior (AB) is an important public health concern impacting perpetrators, victims, and society. Functional neuroimaging is becoming a more common and useful modality for understanding neural correlates of youth AB. Although there has been a recent increase in neuroimaging studies of youth AB and corresponding theoretical articles on the neurobiology of AB, there has been little work critically examining the strengths and weaknesses of individual studies and using this knowledge to inform the design of future studies. Additionally, research on neuroimaging and youth AB has not been integrated within the broader framework of developmental psychopathology. Thus, this paper provides an in-depth review of the youth AB functional neuroimaging literature with the following goals: 1. to evaluate how this literature has informed our understanding of youth AB, 2. to evaluate current neuroimaging studies of youth AB from a developmental psychopathology perspective with a focus on integrating research from neuroscience and developmental psychopathology, as well as placing this research in the context of other related areas (e.g., psychopathy, molecular genetics), and 3. to examine strengths and weaknesses of neuroimaging and behavioral studies of youth AB to suggest how future studies can develop a more informed and integrated understanding of youth AB. PMID:24273368
Neuroimaging of the Dopamine/Reward System in Adolescent Drug Use
Ernst, Monique; Luciana, Monica
2015-01-01
Adolescence is characterized by heightened risk-taking, including substance misuse. These behavioral patterns are influenced by ontogenic changes in neurotransmitter systems, particularly the dopamine system, which is fundamentally involved in the neural coding of reward and motivated approach behavior. During adolescence, this system evidences a peak in activity. At the same time, the dopamine system is neuroplastically altered by substance abuse, impacting subsequent function. Here, we describe properties of the dopamine system that change with typical adolescent development and that are altered with substance abuse. Much of this work has been gleaned from animal models due to limitations in measuring dopamine in pediatric samples. Structural and functional neuroimaging techniques have been used to examine structures that are heavily DA-innervated; they measure morphological and functional changes with age and with drug exposure. Presenting marijuana abuse as an exemplar, we consider recent findings that support an adolescent peak in DA-driven reward-seeking behavior and related deviations in motivational systems that are associated with marijuana abuse/dependence. Clinicians are advised that (1) chronic adolescent marijuana use may lead to deficiencies in incentive motivation, (2) that this state is due to marijuana’s interactions with the developing DA system, and (3) that treatment strategies should be directed to remediating resultant deficiencies in goal-directed activity. PMID:26095977
Pituitary gland in psychiatric disorders: a review of neuroimaging findings.
Atmaca, Murad
2014-08-01
In this paper, it was reviewed neuroimaging results of the pituitary gland in psychiatric disorders, particularly schizophrenia, mood disorders, anxiety disorders, and somatoform disorders. The author made internet search in detail by using PubMed database including the period between 1980 and 2012 October. It was included in the articles in English, Turkish and French languages on pituitary gland in psychiatric disorders through structural or functional neuroimaging results. After searching mentioned in the Methods section in detail, investigations were obtained on pituitary gland neuroimaging in a variety of psychiatric disorders. There have been so limited investigations on pituitary neuroimaging in psychiatric disorders including major psychiatric illnesses like schizophrenia and mood disorders. Current findings are so far from the generalizability of the results. For this reason, it is required to perform much more neuroimaging studies of pituitary gland in all psychiatric disorders to reach the diagnostic importance of measuring it.
Neuroimaging techniques for memory detection: scientific, ethical, and legal issues.
Meegan, Daniel V
2008-01-01
There is considerable interest in the use of neuroimaging techniques for forensic purposes. Memory detection techniques, including the well-publicized Brain Fingerprinting technique (Brain Fingerprinting Laboratories, Inc., Seattle WA), exploit the fact that the brain responds differently to sensory stimuli to which it has been exposed before. When a stimulus is specifically associated with a crime, the resulting brain activity should differentiate between someone who was present at the crime and someone who was not. This article reviews the scientific literature on three such techniques: priming, old/new, and P300 effects. The forensic potential of these techniques is evaluated based on four criteria: specificity, automaticity, encoding flexibility, and longevity. This article concludes that none of the techniques are devoid of forensic potential, although much research is yet to be done. Ethical issues, including rights to privacy and against self-incrimination, are discussed. A discussion of legal issues concludes that current memory detection techniques do not yet meet United States standards of legal admissibility.
Del Casale, Antonio; Ferracuti, Stefano; Rapinesi, Chiara; De Rossi, Pietro; Angeletti, Gloria; Sani, Gabriele; Kotzalidis, Georgios D; Girardi, Paolo
2015-12-01
Several studies reported that hypnosis can modulate pain perception and tolerance by affecting cortical and subcortical activity in brain regions involved in these processes. We conducted an Activation Likelihood Estimation (ALE) meta-analysis on functional neuroimaging studies of pain perception under hypnosis to identify brain activation-deactivation patterns occurring during hypnotic suggestions aiming at pain reduction, including hypnotic analgesic, pleasant, or depersonalization suggestions (HASs). We searched the PubMed, Embase and PsycInfo databases; we included papers published in peer-reviewed journals dealing with functional neuroimaging and hypnosis-modulated pain perception. The ALE meta-analysis encompassed data from 75 healthy volunteers reported in 8 functional neuroimaging studies. HASs during experimentally-induced pain compared to control conditions correlated with significant activations of the right anterior cingulate cortex (Brodmann's Area [BA] 32), left superior frontal gyrus (BA 6), and right insula, and deactivation of right midline nuclei of the thalamus. HASs during experimental pain impact both cortical and subcortical brain activity. The anterior cingulate, left superior frontal, and right insular cortices activation increases could induce a thalamic deactivation (top-down inhibition), which may correlate with reductions in pain intensity. Copyright © 2016 Elsevier Ltd. All rights reserved.
Recent advances in the neuroimaging and neuropsychology of cerebral palsy.
Gosling, A Sophia
2017-01-01
This article reviews the recent advances in understanding of cerebral palsy (CP) and outlines how these advances could inform pediatric neuropsychological rehabilitation. Three main areas are discussed: the improved delineation of differing presentations resulting from more advanced imaging techniques with emerging links to function; a brief review of research examining neuropsychological functioning of children with CP and their quality of life and participation; and lastly, some of the evidence for efficacious interventions and the extent to which these interventions are derived from neuropsychological theory and practice. Advances and gaps in knowledge in addition to suggestions of areas for future focus in research and practice are discussed throughout the article.
Miyake, Yoshie; Okamoto, Yuri; Jinnin, Ran; Shishida, Kazuhiro; Okamoto, Yasumasa
2015-02-01
Eating disorders are characterized by aberrant patterns of eating behavior, including such symptoms as extreme restriction of food intake or binge eating, and severe disturbances in the perception of body shape and weight, as well as a drive for thinness and obsessive fears of becoming fat. Eating disorder is an important cause for physical and psychosocial morbidity in young women. Patients with eating disorders have a deficit in the cognitive process and functional abnormalities in the brain system. Recently, brain-imaging techniques have been used to identify specific brain areas that function abnormally in patients with eating disorders. We have discussed the clinical and cognitive aspects of eating disorders and summarized neuroimaging studies of eating disorders.
Transcranial magnetic stimulation and neuroplasticity.
Pascual-Leone, A; Tarazona, F; Keenan, J; Tormos, J M; Hamilton, R; Catala, M D
1999-02-01
We review past results and present novel data to illustrate different ways in which TMS can be used to study neural plasticity. Procedural learning during the serial reaction time task (SRTT) is used as a model of neural plasticity to illustrate the applications of TMS. These different applications of TMS represent principles of use that we believe are applicable to studies of cognitive neuroscience in general and exemplify the great potential of TMS in the study of brain and behavior. We review the use of TMS for (1) cortical output mapping using focal, single-pulse TMS; (2) identification of the mechanisms underlying neuroplasticity using paired-pulse TMS techniques; (3) enhancement of the information of other neuroimaging techniques by transient disruption of cortical function using repetitive TMS; and finally (4) modulation of cortical function with repetitive TMS to influence behavior and guide plasticity.
Cheng, Wei; Ji, Xiaoxi; Zhang, Jie; Feng, Jianfeng
2012-01-01
Accurate classification or prediction of the brain state across individual subject, i.e., healthy, or with brain disorders, is generally a more difficult task than merely finding group differences. The former must be approached with highly informative and sensitive biomarkers as well as effective pattern classification/feature selection approaches. In this paper, we propose a systematic methodology to discriminate attention deficit hyperactivity disorder (ADHD) patients from healthy controls on the individual level. Multiple neuroimaging markers that are proved to be sensitive features are identified, which include multiscale characteristics extracted from blood oxygenation level dependent (BOLD) signals, such as regional homogeneity (ReHo) and amplitude of low-frequency fluctuations. Functional connectivity derived from Pearson, partial, and spatial correlation is also utilized to reflect the abnormal patterns of functional integration, or, dysconnectivity syndromes in the brain. These neuroimaging markers are calculated on either voxel or regional level. Advanced feature selection approach is then designed, including a brain-wise association study (BWAS). Using identified features and proper feature integration, a support vector machine (SVM) classifier can achieve a cross-validated classification accuracy of 76.15% across individuals from a large dataset consisting of 141 healthy controls and 98 ADHD patients, with the sensitivity being 63.27% and the specificity being 85.11%. Our results show that the most discriminative features for classification are primarily associated with the frontal and cerebellar regions. The proposed methodology is expected to improve clinical diagnosis and evaluation of treatment for ADHD patient, and to have wider applications in diagnosis of general neuropsychiatric disorders. PMID:22888314
NASA Astrophysics Data System (ADS)
Khan, Bilal; Hervey, Nathan; Stowe, Ann; Hodics, Timea; Alexandrakis, George
2013-03-01
Electrical stimulation of the human cortex in conjunction with physical rehabilitation has been a valuable approach in facilitating the plasticity of the injured brain. One such method is transcranial direct current stimulation (tDCS) which is a non-invasive method to elicit neural stimulation by delivering current through electrodes placed on the scalp. In order to better understand the effects tDCS has on cortical plasticity, neuroimaging techniques have been used pre and post tDCS stimulation. Recently, neuroimaging methods have discovered changes in resting state cortical hemodynamics after the application of tDCS on human subjects. However, analysis of the cortical hemodynamic activity for a physical task during and post tDCS stimulation has not been studied to our knowledge. A viable and sensitive neuroimaging method to map changes in cortical hemodynamics during activation is functional near-infrared spectroscopy (fNIRS). In this study, the cortical activity during an event-related, left wrist curl task was mapped with fNIRS before, during, and after tDCS stimulation on eight healthy adults. Along with the fNIRS optodes, two electrodes were placed over the sensorimotor hand areas of both brain hemispheres to apply tDCS. Changes were found in both resting state cortical connectivity and cortical activation patterns that occurred during and after tDCS. Additionally, changes to surface electromyography (sEMG) measurements of the wrist flexor and extensor of both arms during the wrist curl movement, acquired concurrently with fNIRS, were analyzed and related to the transient cortical plastic changes induced by tDCS.
Neural correlates of the LSD experience revealed by multimodal neuroimaging.
Carhart-Harris, Robin L; Muthukumaraswamy, Suresh; Roseman, Leor; Kaelen, Mendel; Droog, Wouter; Murphy, Kevin; Tagliazucchi, Enzo; Schenberg, Eduardo E; Nest, Timothy; Orban, Csaba; Leech, Robert; Williams, Luke T; Williams, Tim M; Bolstridge, Mark; Sessa, Ben; McGonigle, John; Sereno, Martin I; Nichols, David; Hellyer, Peter J; Hobden, Peter; Evans, John; Singh, Krish D; Wise, Richard G; Curran, H Valerie; Feilding, Amanda; Nutt, David J
2016-04-26
Lysergic acid diethylamide (LSD) is the prototypical psychedelic drug, but its effects on the human brain have never been studied before with modern neuroimaging. Here, three complementary neuroimaging techniques: arterial spin labeling (ASL), blood oxygen level-dependent (BOLD) measures, and magnetoencephalography (MEG), implemented during resting state conditions, revealed marked changes in brain activity after LSD that correlated strongly with its characteristic psychological effects. Increased visual cortex cerebral blood flow (CBF), decreased visual cortex alpha power, and a greatly expanded primary visual cortex (V1) functional connectivity profile correlated strongly with ratings of visual hallucinations, implying that intrinsic brain activity exerts greater influence on visual processing in the psychedelic state, thereby defining its hallucinatory quality. LSD's marked effects on the visual cortex did not significantly correlate with the drug's other characteristic effects on consciousness, however. Rather, decreased connectivity between the parahippocampus and retrosplenial cortex (RSC) correlated strongly with ratings of "ego-dissolution" and "altered meaning," implying the importance of this particular circuit for the maintenance of "self" or "ego" and its processing of "meaning." Strong relationships were also found between the different imaging metrics, enabling firmer inferences to be made about their functional significance. This uniquely comprehensive examination of the LSD state represents an important advance in scientific research with psychedelic drugs at a time of growing interest in their scientific and therapeutic value. The present results contribute important new insights into the characteristic hallucinatory and consciousness-altering properties of psychedelics that inform on how they can model certain pathological states and potentially treat others.
Neural correlates of the LSD experience revealed by multimodal neuroimaging
Carhart-Harris, Robin L.; Muthukumaraswamy, Suresh; Roseman, Leor; Kaelen, Mendel; Droog, Wouter; Murphy, Kevin; Tagliazucchi, Enzo; Schenberg, Eduardo E.; Nest, Timothy; Orban, Csaba; Leech, Robert; Williams, Luke T.; Williams, Tim M.; Bolstridge, Mark; Sessa, Ben; McGonigle, John; Sereno, Martin I.; Nichols, David; Hobden, Peter; Evans, John; Singh, Krish D.; Wise, Richard G.; Curran, H. Valerie; Feilding, Amanda; Nutt, David J.
2016-01-01
Lysergic acid diethylamide (LSD) is the prototypical psychedelic drug, but its effects on the human brain have never been studied before with modern neuroimaging. Here, three complementary neuroimaging techniques: arterial spin labeling (ASL), blood oxygen level-dependent (BOLD) measures, and magnetoencephalography (MEG), implemented during resting state conditions, revealed marked changes in brain activity after LSD that correlated strongly with its characteristic psychological effects. Increased visual cortex cerebral blood flow (CBF), decreased visual cortex alpha power, and a greatly expanded primary visual cortex (V1) functional connectivity profile correlated strongly with ratings of visual hallucinations, implying that intrinsic brain activity exerts greater influence on visual processing in the psychedelic state, thereby defining its hallucinatory quality. LSD’s marked effects on the visual cortex did not significantly correlate with the drug’s other characteristic effects on consciousness, however. Rather, decreased connectivity between the parahippocampus and retrosplenial cortex (RSC) correlated strongly with ratings of “ego-dissolution” and “altered meaning,” implying the importance of this particular circuit for the maintenance of “self” or “ego” and its processing of “meaning.” Strong relationships were also found between the different imaging metrics, enabling firmer inferences to be made about their functional significance. This uniquely comprehensive examination of the LSD state represents an important advance in scientific research with psychedelic drugs at a time of growing interest in their scientific and therapeutic value. The present results contribute important new insights into the characteristic hallucinatory and consciousness-altering properties of psychedelics that inform on how they can model certain pathological states and potentially treat others. PMID:27071089
Browning, Michael; Fletcher, Paul; Sharpe, Michael
2011-01-01
Objective Debate about the nature of the somatoform disorders and their current diagnostic classification has been stimulated by the anticipation of new editions of the DSM and ICD diagnostic classifications. In the current paper we systematically review the literature on the neuroimaging of somatoform disorders and related conditions with the aim of addressing two specific questions: Is there evidence of altered neural function or structure that is specifically associated with somatoform disorders? What conclusions can we draw from these findings about the etiology of somatoform disorders? Methods Studies reporting neuroimaging findings in patients with a somatoform disorder, or a functional somatic syndrome (such as Fibromyalgia) were found using Pubmed, PsycINFO and EMBASE database searches. Reported structural and functional neuroimaging findings were then extracted to form a narrative review. Results A relatively mature literature on symptoms of pain, and less developed literatures on conversion and fatigue symptoms were identified. The available evidence indicates that, when compared to non-clinical groups, somatoform diagnoses are associated with increased activity of limbic regions in response to painful stimuli and a generalized decrease in grey matter density; however methodological considerations restrict the interpretation of these findings. Conclusions While the neuroimaging literature has provided evidence about the possible mechanisms underlying somatoform disorders this is not yet sufficient to provide a basis for classification. By adopting a wider variety of experimental designs and a more dynamic approach to diagnosis there is every reason to be hopeful that neuroimaging data will play a significant role in future taxonomies. PMID:21217095
Molecular neuroimaging of emotional decision-making.
Takahashi, Hidehiko
2013-04-01
With the dissemination of non-invasive human neuroimaging techniques such as fMRI and the advancement of cognitive science, neuroimaging studies focusing on emotions and social cognition have become established. Along with this advancement, behavioral economics taking emotional and social factors into account for economic decisions has been merged with neuroscientific studies, and this interdisciplinary approach is called neuroeconomics. Past neuroeconomics studies have demonstrated that subcortical emotion-related brain structures play an important role in "irrational" decision-making. The research field that investigates the role of central neurotransmitters in this process is worthy of further development. Here, we provide an overview of recent molecular neuroimaging studies to further the understanding of the neurochemical basis of "irrational" or emotional decision-making and the future direction, including clinical implications, of the field. Copyright © 2013 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.
Hayhow, Bradleigh D; Hassan, Islam; Looi, Jeffrey C L; Gaillard, Francesco; Velakoulis, Dennis; Walterfang, Mark
2013-01-01
Movement disorders, particularly those associated with basal ganglia disease, have a high rate of comorbid neuropsychiatric illness. We consider the pathophysiological basis of the comorbidity between movement disorders and neuropsychiatric illness by 1) reviewing the epidemiology of neuropsychiatric illness in a range of hyperkinetic movement disorders, and 2) correlating findings to evidence from studies that have utilized modern neuroimaging techniques to investigate these disorders. In addition to diseases classically associated with basal ganglia pathology, such as Huntington disease, Wilson disease, the neuroacanthocytoses, and diseases of brain iron accumulation, we include diseases associated with pathology of subcortical white matter tracts, brain stem nuclei, and the cerebellum, such as metachromatic leukodystrophy, dentatorubropallidoluysian atrophy, and the spinocerebellar ataxias. Neuropsychiatric symptoms are integral to a thorough phenomenological account of hyperkinetic movement disorders. Drawing on modern theories of cortico-subcortical circuits, we argue that these disorders can be conceptualized as disorders of complex subcortical networks with distinct functional architectures. Damage to any component of these complex information-processing networks can have variable and often profound consequences for the function of more remote neural structures, creating a diverse but nonetheless rational pattern of clinical symptomatology.
Cerebellar and Brainstem Malformations.
Poretti, Andrea; Boltshauser, Eugen; Huisman, Thierry A G M
2016-08-01
The frequency and importance of the evaluation of the posterior fossa have increased significantly over the past 20 years owing to advances in neuroimaging. Conventional and advanced neuroimaging techniques allow detailed evaluation of the complex anatomic structures within the posterior fossa. A wide spectrum of cerebellar and brainstem malformations has been shown. Familiarity with the spectrum of cerebellar and brainstem malformations and their well-defined diagnostic criteria is crucial for optimal therapy, an accurate prognosis, and correct genetic counseling. This article discusses cerebellar and brainstem malformations, with emphasis on neuroimaging findings (including diagnostic criteria), neurologic presentation, systemic involvement, prognosis, and recurrence. Copyright © 2016 Elsevier Inc. All rights reserved.
Single Subject Prediction of Brain Disorders in Neuroimaging: Promises and Pitfalls
Arbabshirani, Mohammad R.; Plis, Sergey; Sui, Jing; Calhoun, Vince D.
2016-01-01
Neuroimaging-based single subject prediction of brain disorders has gained increasing attention in recent years. Using a variety of neuroimaging modalities such as structural, functional and diffusion MRI, along with machine learning techniques, hundreds of studies have been carried out for accurate classification of patients with heterogeneous mental and neurodegenerative disorders such as schizophrenia and Alzheimer's disease. More than 500 studies have been published during the past quarter century on single subject prediction focused on a multiple brain disorders. In the first part of this study, we provide a survey of more than 200 reports in this field with a focus on schizophrenia, mild cognitive impairment (MCI), Alzheimer's disease (AD), depressive disorders, autism spectrum disease (ASD) and attention-deficit hyperactivity disorder (ADHD). Detailed information about those studies such as sample size, type and number of extracted features and reported accuracy are summarized and discussed. To our knowledge, this is by far the most comprehensive review of neuroimaging-based single subject prediction of brain disorders. In the second part, we present our opinion on major pitfalls of those studies from a machine learning point of view. Common biases are discussed and suggestions are provided. Moreover, emerging trends such as decentralized data sharing, multimodal brain imaging, differential diagnosis, disease subtype classification and deep learning are also discussed. Based on this survey, there are extensive evidences showing the great potential of neuroimaging data for single subject prediction of various disorders. However, the main bottleneck of this exciting field is still the limited sample size, which could be potentially addressed by modern data sharing models such as the ones discussed in this paper. Emerging big data technologies and advanced data-intensive machine learning methodologies such as deep learning have coincided with an increasing need for accurate, robust and generalizable single subject prediction of brain disorders during an exciting time. In this report, we survey the past and offer some opinions regarding the road ahead. PMID:27012503
Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls.
Arbabshirani, Mohammad R; Plis, Sergey; Sui, Jing; Calhoun, Vince D
2017-01-15
Neuroimaging-based single subject prediction of brain disorders has gained increasing attention in recent years. Using a variety of neuroimaging modalities such as structural, functional and diffusion MRI, along with machine learning techniques, hundreds of studies have been carried out for accurate classification of patients with heterogeneous mental and neurodegenerative disorders such as schizophrenia and Alzheimer's disease. More than 500 studies have been published during the past quarter century on single subject prediction focused on a multiple brain disorders. In the first part of this study, we provide a survey of more than 200 reports in this field with a focus on schizophrenia, mild cognitive impairment (MCI), Alzheimer's disease (AD), depressive disorders, autism spectrum disease (ASD) and attention-deficit hyperactivity disorder (ADHD). Detailed information about those studies such as sample size, type and number of extracted features and reported accuracy are summarized and discussed. To our knowledge, this is by far the most comprehensive review of neuroimaging-based single subject prediction of brain disorders. In the second part, we present our opinion on major pitfalls of those studies from a machine learning point of view. Common biases are discussed and suggestions are provided. Moreover, emerging trends such as decentralized data sharing, multimodal brain imaging, differential diagnosis, disease subtype classification and deep learning are also discussed. Based on this survey, there is extensive evidence showing the great potential of neuroimaging data for single subject prediction of various disorders. However, the main bottleneck of this exciting field is still the limited sample size, which could be potentially addressed by modern data sharing models such as the ones discussed in this paper. Emerging big data technologies and advanced data-intensive machine learning methodologies such as deep learning have coincided with an increasing need for accurate, robust and generalizable single subject prediction of brain disorders during an exciting time. In this report, we survey the past and offer some opinions regarding the road ahead. Copyright © 2016 Elsevier Inc. All rights reserved.
Rasheed, Waqas; Neoh, Yee Yik; Bin Hamid, Nor Hisham; Reza, Faruque; Idris, Zamzuri; Tang, Tong Boon
2017-10-01
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. Copyright © 2017 Elsevier Ltd. All rights reserved.
Human Orbitofrontal Cortex Represents a Cognitive Map of State Space.
Schuck, Nicolas W; Cai, Ming Bo; Wilson, Robert C; Niv, Yael
2016-09-21
Although the orbitofrontal cortex (OFC) has been studied intensely for decades, its precise functions have remained elusive. We recently hypothesized that the OFC contains a "cognitive map" of task space in which the current state of the task is represented, and this representation is especially critical for behavior when states are unobservable from sensory input. To test this idea, we apply pattern-classification techniques to neuroimaging data from humans performing a decision-making task with 16 states. We show that unobservable task states can be decoded from activity in OFC, and decoding accuracy is related to task performance and the occurrence of individual behavioral errors. Moreover, similarity between the neural representations of consecutive states correlates with behavioral accuracy in corresponding state transitions. These results support the idea that OFC represents a cognitive map of task space and establish the feasibility of decoding state representations in humans using non-invasive neuroimaging. Copyright © 2016 Elsevier Inc. All rights reserved.
Haller, Sven; Lovblad, Karl-Olof; Giannakopoulos, Panteleimon; Van De Ville, Dimitri
2014-05-01
Many diseases are associated with systematic modifications in brain morphometry and function. These alterations may be subtle, in particular at early stages of the disease progress, and thus not evident by visual inspection alone. Group-level statistical comparisons have dominated neuroimaging studies for many years, proving fascinating insight into brain regions involved in various diseases. However, such group-level results do not warrant diagnostic value for individual patients. Recently, pattern recognition approaches have led to a fundamental shift in paradigm, bringing multivariate analysis and predictive results, notably for the early diagnosis of individual patients. We review the state-of-the-art fundamentals of pattern recognition including feature selection, cross-validation and classification techniques, as well as limitations including inter-individual variation in normal brain anatomy and neurocognitive reserve. We conclude with the discussion of future trends including multi-modal pattern recognition, multi-center approaches with data-sharing and cloud-computing.
Schulte, Tilman; Oberlin, Brandon G; Kareken, David A; Marinkovic, Ksenija; Müller-Oehring, Eva M; Meyerhoff, Dieter J; Tapert, Susan
2012-12-01
Multimodal imaging combining 2 or more techniques is becoming increasingly important because no single imaging approach has the capacity to elucidate all clinically relevant characteristics of a network. This review highlights recent advances in multimodal neuroimaging (i.e., combined use and interpretation of data collected through magnetic resonance imaging [MRI], functional MRI, diffusion tensor imaging, positron emission tomography, magnetoencephalography, MR perfusion, and MR spectroscopy methods) that leads to a more comprehensive understanding of how acute and chronic alcohol consumption affect neural networks underlying cognition, emotion, reward processing, and drinking behavior. Several innovative investigators have started utilizing multiple imaging approaches within the same individual to better understand how alcohol influences brain systems, both during intoxication and after years of chronic heavy use. Their findings can help identify mechanism-based therapeutic and pharmacological treatment options, and they may increase the efficacy and cost effectiveness of such treatments by predicting those at greatest risk for relapse. Copyright © 2012 by the Research Society on Alcoholism.
Complex biomarker discovery in neuroimaging data: Finding a needle in a haystack☆
Atluri, Gowtham; Padmanabhan, Kanchana; Fang, Gang; Steinbach, Michael; Petrella, Jeffrey R.; Lim, Kelvin; MacDonald, Angus; Samatova, Nagiza F.; Doraiswamy, P. Murali; Kumar, Vipin
2013-01-01
Neuropsychiatric disorders such as schizophrenia, bipolar disorder and Alzheimer's disease are major public health problems. However, despite decades of research, we currently have no validated prognostic or diagnostic tests that can be applied at an individual patient level. Many neuropsychiatric diseases are due to a combination of alterations that occur in a human brain rather than the result of localized lesions. While there is hope that newer imaging technologies such as functional and anatomic connectivity MRI or molecular imaging may offer breakthroughs, the single biomarkers that are discovered using these datasets are limited by their inability to capture the heterogeneity and complexity of most multifactorial brain disorders. Recently, complex biomarkers have been explored to address this limitation using neuroimaging data. In this manuscript we consider the nature of complex biomarkers being investigated in the recent literature and present techniques to find such biomarkers that have been developed in related areas of data mining, statistics, machine learning and bioinformatics. PMID:24179856
Ionic contrast terahertz near-field imaging of axonal water fluxes
Masson, Jean-Baptiste; Sauviat, Martin-Pierre; Martin, Jean-Louis; Gallot, Guilhem
2006-01-01
We demonstrate the direct and noninvasive imaging of functional neurons by ionic contrast terahertz near-field microscopy. This technique provides quantitative measurements of ionic concentrations in both the intracellular and extracellular compartments and opens the way to direct noninvasive imaging of neurons during electrical, toxin, or thermal stresses. Furthermore, neuronal activity results from both a precise control of transient variations in ionic conductances and a much less studied water exchange between the extracellular matrix and the intraaxonal compartment. The developed ionic contrast terahertz microscopy technique associated with a full three-dimensional simulation of the axon-aperture near-field system allows a precise measurement of the axon geometry and therefore the direct visualization of neuron swelling induced by temperature change or neurotoxin poisoning. Water influx as small as 20 fl per μm of axonal length can be measured. This technique should then provide grounds for the development of advanced functional neuroimaging methods based on diffusion anisotropy of water molecules. PMID:16547134
2018-01-01
Background Structural and functional brain images are essential imaging modalities for medical experts to study brain anatomy. These images are typically visually inspected by experts. To analyze images without any bias, they must be first converted to numeric values. Many software packages are available to process the images, but they are complex and difficult to use. The software packages are also hardware intensive. The results obtained after processing vary depending on the native operating system used and its associated software libraries; data processed in one system cannot typically be combined with data on another system. Objective The aim of this study was to fulfill the neuroimaging community’s need for a common platform to store, process, explore, and visualize their neuroimaging data and results using Neuroimaging Web Services Interface: a series of processing pipelines designed as a cyber physical system for neuroimaging and clinical data in brain research. Methods Neuroimaging Web Services Interface accepts magnetic resonance imaging, positron emission tomography, diffusion tensor imaging, and functional magnetic resonance imaging. These images are processed using existing and custom software packages. The output is then stored as image files, tabulated files, and MySQL tables. The system, made up of a series of interconnected servers, is password-protected and is securely accessible through a Web interface and allows (1) visualization of results and (2) downloading of tabulated data. Results All results were obtained using our processing servers in order to maintain data validity and consistency. The design is responsive and scalable. The processing pipeline started from a FreeSurfer reconstruction of Structural magnetic resonance imaging images. The FreeSurfer and regional standardized uptake value ratio calculations were validated using Alzheimer’s Disease Neuroimaging Initiative input images, and the results were posted at the Laboratory of Neuro Imaging data archive. Notable leading researchers in the field of Alzheimer’s Disease and epilepsy have used the interface to access and process the data and visualize the results. Tabulated results with unique visualization mechanisms help guide more informed diagnosis and expert rating, providing a truly unique multimodal imaging platform that combines magnetic resonance imaging, positron emission tomography, diffusion tensor imaging, and resting state functional magnetic resonance imaging. A quality control component was reinforced through expert visual rating involving at least 2 experts. Conclusions To our knowledge, there is no validated Web-based system offering all the services that Neuroimaging Web Services Interface offers. The intent of Neuroimaging Web Services Interface is to create a tool for clinicians and researchers with keen interest on multimodal neuroimaging. More importantly, Neuroimaging Web Services Interface significantly augments the Alzheimer’s Disease Neuroimaging Initiative data, especially since our data contain a large cohort of Hispanic normal controls and Alzheimer’s Disease patients. The obtained results could be scrutinized visually or through the tabulated forms, informing researchers on subtle changes that characterize the different stages of the disease. PMID:29699962
Computational Modeling and Neuroimaging Techniques for Targeting during Deep Brain Stimulation
Sweet, Jennifer A.; Pace, Jonathan; Girgis, Fady; Miller, Jonathan P.
2016-01-01
Accurate surgical localization of the varied targets for deep brain stimulation (DBS) is a process undergoing constant evolution, with increasingly sophisticated techniques to allow for highly precise targeting. However, despite the fastidious placement of electrodes into specific structures within the brain, there is increasing evidence to suggest that the clinical effects of DBS are likely due to the activation of widespread neuronal networks directly and indirectly influenced by the stimulation of a given target. Selective activation of these complex and inter-connected pathways may further improve the outcomes of currently treated diseases by targeting specific fiber tracts responsible for a particular symptom in a patient-specific manner. Moreover, the delivery of such focused stimulation may aid in the discovery of new targets for electrical stimulation to treat additional neurological, psychiatric, and even cognitive disorders. As such, advancements in surgical targeting, computational modeling, engineering designs, and neuroimaging techniques play a critical role in this process. This article reviews the progress of these applications, discussing the importance of target localization for DBS, and the role of computational modeling and novel neuroimaging in improving our understanding of the pathophysiology of diseases, and thus paving the way for improved selective target localization using DBS. PMID:27445709
Iyer, Kartik K
2017-11-01
Stroke is one of the leading causes of permanent disability worldwide, relying conventionally on extended periods of physiotherapy to recover functional ability. While neuroimaging techniques and emerging neurorehabilitation paradigms have advanced our understanding of pathophysiological mechanisms underlying stroke, recent evidence has renewed focus on quantifying features of cortical activity present in electroencephalography recordings to greatly enhance our understanding of stroke treatment and recovery. This Neuro Forum article reviews these key advances and discusses the importance of quantifying electroencephalography in future assessments of stroke survivors. Copyright © 2017 the American Physiological Society.
Using neuroimaging to understand the cortical mechanisms of auditory selective attention
Lee, Adrian KC; Larson, Eric; Maddox, Ross K; Shinn-Cunningham, Barbara G
2013-01-01
Over the last four decades, a range of different neuroimaging tools have been used to study human auditory attention, spanning from classic event-related potential studies using electroencephalography to modern multimodal imaging approaches (e.g., combining anatomical information based on magnetic resonance imaging with magneto- and electroencephalography). This review begins by exploring the different strengths and limitations inherent to different neuroimaging methods, and then outlines some common behavioral paradigms that have been adopted to study auditory attention. We argue that in order to design a neuroimaging experiment that produces interpretable, unambiguous results, the experimenter must not only have a deep appreciation of the imaging technique employed, but also a sophisticated understanding of perception and behavior. Only with the proper caveats in mind can one begin to infer how the cortex supports a human in solving the “cocktail party” problem. PMID:23850664
Integration of a neuroimaging processing pipeline into a pan-canadian computing grid
NASA Astrophysics Data System (ADS)
Lavoie-Courchesne, S.; Rioux, P.; Chouinard-Decorte, F.; Sherif, T.; Rousseau, M.-E.; Das, S.; Adalat, R.; Doyon, J.; Craddock, C.; Margulies, D.; Chu, C.; Lyttelton, O.; Evans, A. C.; Bellec, P.
2012-02-01
The ethos of the neuroimaging field is quickly moving towards the open sharing of resources, including both imaging databases and processing tools. As a neuroimaging database represents a large volume of datasets and as neuroimaging processing pipelines are composed of heterogeneous, computationally intensive tools, such open sharing raises specific computational challenges. This motivates the design of novel dedicated computing infrastructures. This paper describes an interface between PSOM, a code-oriented pipeline development framework, and CBRAIN, a web-oriented platform for grid computing. This interface was used to integrate a PSOM-compliant pipeline for preprocessing of structural and functional magnetic resonance imaging into CBRAIN. We further tested the capacity of our infrastructure to handle a real large-scale project. A neuroimaging database including close to 1000 subjects was preprocessed using our interface and publicly released to help the participants of the ADHD-200 international competition. This successful experiment demonstrated that our integrated grid-computing platform is a powerful solution for high-throughput pipeline analysis in the field of neuroimaging.
Seeing responsibility: can neuroimaging teach us anything about moral and legal responsibility?
Wasserman, David; Johnston, Josephine
2014-01-01
As imaging technologies help us understand the structure and function of the brain, providing insight into human capabilities as basic as vision and as complex as memory, and human conditions as impairing as depression and as fraught as psychopathy, some have asked whether they can also help us understand human agency. Specifically, could neuroimaging lead us to reassess the socially significant practice of assigning and taking responsibility? While responsibility itself is not a psychological process open to investigation through neuroimaging, decision-making is. Over the past decade, different researchers and scholars have sought to use neuroimaging (or the results of neuroimaging studies) to investigate what is going on in the brain when we make decisions. The results of this research raise the question whether neuroscience-especially now that it includes neuroimaging-can and should alter our understandings of responsibility and our related practice of holding people responsible. It is this question that we investigate here. © 2014 by The Hastings Center.
NASA Astrophysics Data System (ADS)
Ding, Xuemei; Wang, Bingyuan; Liu, Dongyuan; Zhang, Yao; He, Jie; Zhao, Huijuan; Gao, Feng
2018-02-01
During the past two decades there has been a dramatic rise in the use of functional near-infrared spectroscopy (fNIRS) as a neuroimaging technique in cognitive neuroscience research. Diffuse optical tomography (DOT) and optical topography (OT) can be employed as the optical imaging techniques for brain activity investigation. However, most current imagers with analogue detection are limited by sensitivity and dynamic range. Although photon-counting detection can significantly improve detection sensitivity, the intrinsic nature of sequential excitations reduces temporal resolution. To improve temporal resolution, sensitivity and dynamic range, we develop a multi-channel continuous-wave (CW) system for brain functional imaging based on a novel lock-in photon-counting technique. The system consists of 60 Light-emitting device (LED) sources at three wavelengths of 660nm, 780nm and 830nm, which are modulated by current-stabilized square-wave signals at different frequencies, and 12 photomultiplier tubes (PMT) based on lock-in photon-counting technique. This design combines the ultra-high sensitivity of the photon-counting technique with the parallelism of the digital lock-in technique. We can therefore acquire the diffused light intensity for all the source-detector pairs (SD-pairs) in parallel. The performance assessments of the system are conducted using phantom experiments, and demonstrate its excellent measurement linearity, negligible inter-channel crosstalk, strong noise robustness and high temporal resolution.
Insights into Human Behavior from Lesions to the Prefrontal Cortex
Szczepanski, Sara M.; Knight, Robert T.
2014-01-01
SUMMARY The prefrontal cortex (PFC), a cortical region that was once thought to be functionally insignificant, is now known to play an essential role in the organization and control of goal-directed thought and behavior. Neuroimaging, neurophysiological, and modeling techniques have lead to tremendous advances in our understanding of PFC functions over the last few decades. It should be noted, however, that neurological, neuropathological, and neuropsychological studies have contributed some of the most essential, historical, and often prescient, conclusions regarding the functions of this region. Importantly, examination of patients with brain damage allows one to draw conclusions about whether a brain area is necessary for a particular function. Here, we provide a broad overview of PFC functions based upon behavioral and neural changes resulting from damage to PFC in both human patients and non-human primates. PMID:25175878
Advances in magnetic resonance neuroimaging techniques in the evaluation of neonatal encephalopathy.
Panigrahy, Ashok; Blüml, Stefan
2007-02-01
Magnetic resonance (MR) imaging has become an essential tool in the evaluation of neonatal encephalopathy. Magnetic resonance-compatible neonatal incubators allow sick neonates to be transported to the MR scanner, and neonatal head coils can improve signal-to-noise ratio, critical for advanced MR imaging techniques. Refinement of conventional imaging techniques include the use of PROPELLER techniques for motion correction. Magnetic resonance spectroscopic imaging and diffusion tensor imaging provide quantitative assessment of both brain development and brain injury in the newborn with respect to metabolite abnormalities and hypoxic-ischemic injury. Knowledge of normal developmental changes in MR spectroscopy metabolite concentration and diffusion tensor metrics is essential to interpret pathological cases. Perfusion MR and functional MR can provide additional physiological information. Both MR spectroscopy and diffusion tensor imaging can provide additional information in the differential of neonatal encephalopathy, including perinatal white matter injury, hypoxic-ischemic brain injury, metabolic disease, infection, and birth injury.
Vitali, Paolo; Nobili, Flavio; Raiteri, Umberto; Canfora, Michela; Rosa, Marco; Calvini, Piero; Girtler, Nicola; Regesta, Giovanni; Rodriguez, Guido
2004-01-15
This article describes the unusual case of a 60-year-old woman suffering from pure progressive aphemia. The fusion of multimodal neuroimaging (MRI, perfusion SPECT) implicated the right frontal lobe, especially the inferior frontal gyrus. This area also showed the greatest functional MRI activation during the performance of a covert phonemic fluency task. Results are discussed in terms of bihemispheric language representation. The fusion of three sets of neuroimages has aided in the interpretation of the patient's cognitive brain dysfunction.
Magnetic Resonance Techniques Applied to the Diagnosis and Treatment of Parkinson’s Disease
de Celis Alonso, Benito; Hidalgo-Tobón, Silvia S.; Menéndez-González, Manuel; Salas-Pacheco, José; Arias-Carrión, Oscar
2015-01-01
Parkinson’s disease (PD) affects at least 10 million people worldwide. It is a neurodegenerative disease, which is currently diagnosed by neurological examination. No neuroimaging investigation or blood biomarker is available to aid diagnosis and prognosis. Most effort toward diagnosis using magnetic resonance (MR) has been focused on the use of structural/anatomical neuroimaging and diffusion tensor imaging (DTI). However, deep brain stimulation, a current strategy for treating PD, is guided by MR imaging (MRI). For clinical prognosis, diagnosis, and follow-up investigations, blood oxygen level-dependent MRI, DTI, spectroscopy, and transcranial magnetic stimulation have been used. These techniques represent the state of the art in the last 5 years. Here, we focus on MR techniques for the diagnosis and treatment of Parkinson’s disease. PMID:26191037
The iconography of mourning and its neural correlates: a functional neuroimaging study
Labek, Karin; Berger, Samantha; Buchheim, Anna; Bosch, Julia; Spohrs, Jennifer; Dommes, Lisa; Beschoner, Petra; Stingl, Julia C.
2017-01-01
Abstract The present functional neuroimaging study focuses on the iconography of mourning. A culture-specific pattern of body postures of mourning individuals, mostly suggesting withdrawal, emerged from a survey of visual material. When used in different combinations in stylized drawings in our neuroimaging study, this material activated cortical areas commonly seen in studies of social cognition (temporo-parietal junction, superior temporal gyrus, and inferior temporal lobe), empathy for pain (somatosensory cortex), and loss (precuneus, middle/posterior cingular gyrus). This pattern of activation developed over time. While in the early phases of exposure lower association areas, such as the extrastriate body area, were active, in the late phases activation in parietal and temporal association areas and the prefrontal cortex was more prominent. These findings are consistent with the conventional and contextual character of iconographic material, and further differentiate it from emotionally negatively valenced and high-arousing stimuli. In future studies, this neuroimaging assay may be useful in characterizing interpretive appraisal of material of negative emotional valence. PMID:28449116
A Hitchhiker's Guide to Functional Magnetic Resonance Imaging
Soares, José M.; Magalhães, Ricardo; Moreira, Pedro S.; Sousa, Alexandre; Ganz, Edward; Sampaio, Adriana; Alves, Victor; Marques, Paulo; Sousa, Nuno
2016-01-01
Functional Magnetic Resonance Imaging (fMRI) studies have become increasingly popular both with clinicians and researchers as they are capable of providing unique insights into brain functions. However, multiple technical considerations (ranging from specifics of paradigm design to imaging artifacts, complex protocol definition, and multitude of processing and methods of analysis, as well as intrinsic methodological limitations) must be considered and addressed in order to optimize fMRI analysis and to arrive at the most accurate and grounded interpretation of the data. In practice, the researcher/clinician must choose, from many available options, the most suitable software tool for each stage of the fMRI analysis pipeline. Herein we provide a straightforward guide designed to address, for each of the major stages, the techniques, and tools involved in the process. We have developed this guide both to help those new to the technique to overcome the most critical difficulties in its use, as well as to serve as a resource for the neuroimaging community. PMID:27891073
Baker, Joseph M; Rojas-Valverde, Daniel; Gutiérrez, Randall; Winkler, Mirko; Fuhrimann, Samuel; Eskenazi, Brenda; Reiss, Allan L; Mora, Ana M
2017-09-21
The widespread application of functional neuroimaging within the field of environmental epidemiology has the potential to greatly enhance our understanding of how environmental toxicants affect brain function. Because many epidemiological studies take place in remote and frequently changing environments, it is necessary that the primary neuroimaging approach adopted by the epidemiology community be robust to many environments, easy to use, and, preferably, mobile. Here, we outline our use of functional near-infrared spectroscopy (fNIRS) to collect functional brain imaging data from Costa Rican farm workers enrolled in an epidemiological study on the health effects of chronic pesticide exposure. While couched in this perspective, we focus on the methodological considerations that are necessary to conduct a mobile fNIRS study in a diverse range of environments. Thus, this guide is intended to be generalizable to all research scenarios and projects in which fNIRS may be used to collect functional brain imaging data in epidemiological field surveys. https://doi.org/10.1289/EHP2049.
Rojas-Valverde, Daniel; Gutiérrez, Randall; Winkler, Mirko; Fuhrimann, Samuel; Eskenazi, Brenda; Reiss, Allan L.; Mora, Ana M.
2017-01-01
Summary: The widespread application of functional neuroimaging within the field of environmental epidemiology has the potential to greatly enhance our understanding of how environmental toxicants affect brain function. Because many epidemiological studies take place in remote and frequently changing environments, it is necessary that the primary neuroimaging approach adopted by the epidemiology community be robust to many environments, easy to use, and, preferably, mobile. Here, we outline our use of functional near-infrared spectroscopy (fNIRS) to collect functional brain imaging data from Costa Rican farm workers enrolled in an epidemiological study on the health effects of chronic pesticide exposure. While couched in this perspective, we focus on the methodological considerations that are necessary to conduct a mobile fNIRS study in a diverse range of environments. Thus, this guide is intended to be generalizable to all research scenarios and projects in which fNIRS may be used to collect functional brain imaging data in epidemiological field surveys. https://doi.org/10.1289/EHP2049 PMID:28937962
McFarquhar, Martyn; McKie, Shane; Emsley, Richard; Suckling, John; Elliott, Rebecca; Williams, Stephen
2016-05-15
Repeated measurements and multimodal data are common in neuroimaging research. Despite this, conventional approaches to group level analysis ignore these repeated measurements in favour of multiple between-subject models using contrasts of interest. This approach has a number of drawbacks as certain designs and comparisons of interest are either not possible or complex to implement. Unfortunately, even when attempting to analyse group level data within a repeated-measures framework, the methods implemented in popular software packages make potentially unrealistic assumptions about the covariance structure across the brain. In this paper, we describe how this issue can be addressed in a simple and efficient manner using the multivariate form of the familiar general linear model (GLM), as implemented in a new MATLAB toolbox. This multivariate framework is discussed, paying particular attention to methods of inference by permutation. Comparisons with existing approaches and software packages for dependent group-level neuroimaging data are made. We also demonstrate how this method is easily adapted for dependency at the group level when multiple modalities of imaging are collected from the same individuals. Follow-up of these multimodal models using linear discriminant functions (LDA) is also discussed, with applications to future studies wishing to integrate multiple scanning techniques into investigating populations of interest. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.
Real-time interactive tractography analysis for multimodal brain visualization tool: MultiXplore
NASA Astrophysics Data System (ADS)
Bakhshmand, Saeed M.; de Ribaupierre, Sandrine; Eagleson, Roy
2017-03-01
Most debilitating neurological disorders can have anatomical origins. Yet unlike other body organs, the anatomy alone cannot easily provide an understanding of brain functionality. In fact, addressing the challenge of linking structural and functional connectivity remains in the frontiers of neuroscience. Aggregating multimodal neuroimaging datasets may be critical for developing theories that span brain functionality, global neuroanatomy and internal microstructures. Functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) are main such techniques that are employed to investigate the brain under normal and pathological conditions. FMRI records blood oxygenation level of the grey matter (GM), whereas DTI is able to reveal the underlying structure of the white matter (WM). Brain global activity is assumed to be an integration of GM functional hubs and WM neural pathways that serve to connect them. In this study we developed and evaluated a two-phase algorithm. This algorithm is employed in a 3D interactive connectivity visualization framework and helps to accelerate clustering of virtual neural pathways. In this paper, we will detail an algorithm that makes use of an index-based membership array formed for a whole brain tractography file and corresponding parcellated brain atlas. Next, we demonstrate efficiency of the algorithm by measuring required times for extracting a variety of fiber clusters, which are chosen in such a way to resemble all sizes probable output data files that algorithm will generate. The proposed algorithm facilitates real-time visual inspection of neuroimaging data to further the discovery in structure-function relationship of the brain networks.
Wiebking, Christine; Northoff, Georg
2013-04-01
Paraphilia is a set of disorders characterized by abnormal sexual desires. Perhaps most discussed amongst them, pedophilia is a complex interaction of disturbances of the emotional, cognitive and sexual experience. Using new imaging techniques such as functional magnetic resonance imaging, neural correlates of emotional, sexual and cognitive abnormalities and interactions have been investigated. As described on the basis of current research, altered patterns of brain activity, especially in the frontal areas of the brain, are seen in pedophilia. Building on these results, the analysis of neural correlates of impaired psychological functions opens the opportunity to further explore sexual deviances, which may contribute ultimately to the development of tools for risk assessment, classification methods and new therapeutic approaches.
Ray, Dipanjan; Roy, Dipanjan; Sindhu, Brahmdeep; Sharan, Pratap; Banerjee, Arpan
2017-01-01
Contemporary mental health practice primarily centers around the neurobiological and psychological processes at the individual level. However, a more careful consideration of interpersonal and other group-level attributes (e.g., interpersonal relationship, mutual trust/hostility, interdependence, and cooperation) and a better grasp of their pathology can add a crucial dimension to our understanding of mental health problems. A few recent studies have delved into the interpersonal behavioral processes in the context of different psychiatric abnormalities. Neuroimaging can supplement these approaches by providing insight into the neurobiology of interpersonal functioning. Keeping this view in mind, we discuss a recently developed approach in functional neuroimaging that calls for a shift from a focus on neural information contained within brain space to a multi-brain framework exploring degree of similarity/dissimilarity of neural signals between multiple interacting brains. We hypothesize novel applications of quantitative neuroimaging markers like inter-subject correlation that might be able to evaluate the role of interpersonal attributes affecting an individual or a group. Empirical evidences of the usage of these markers in understanding the neurobiology of social interactions are provided to argue for their application in future mental health research.
Ray, Dipanjan; Roy, Dipanjan; Sindhu, Brahmdeep; Sharan, Pratap; Banerjee, Arpan
2017-01-01
Contemporary mental health practice primarily centers around the neurobiological and psychological processes at the individual level. However, a more careful consideration of interpersonal and other group-level attributes (e.g., interpersonal relationship, mutual trust/hostility, interdependence, and cooperation) and a better grasp of their pathology can add a crucial dimension to our understanding of mental health problems. A few recent studies have delved into the interpersonal behavioral processes in the context of different psychiatric abnormalities. Neuroimaging can supplement these approaches by providing insight into the neurobiology of interpersonal functioning. Keeping this view in mind, we discuss a recently developed approach in functional neuroimaging that calls for a shift from a focus on neural information contained within brain space to a multi-brain framework exploring degree of similarity/dissimilarity of neural signals between multiple interacting brains. We hypothesize novel applications of quantitative neuroimaging markers like inter-subject correlation that might be able to evaluate the role of interpersonal attributes affecting an individual or a group. Empirical evidences of the usage of these markers in understanding the neurobiology of social interactions are provided to argue for their application in future mental health research. PMID:29033866
Linking Essential Tremor to the Cerebellum-Neuroimaging Evidence.
Cerasa, Antonio; Quattrone, Aldo
2016-06-01
Essential tremor (ET) is the most common pathological tremor disorder in the world, and post-mortem evidence has shown that the cerebellum is the most consistent area of pathology in ET. In the last few years, advanced neuroimaging has tried to confirm this evidence. The aim of the present review is to discuss to what extent the evidence provided by this field of study may be generalised. We performed a systematic literature search combining the terms ET with the following keywords: MRI, VBM, MRS, DTI, fMRI, PET and SPECT. We summarised and discussed each study and placed the results in the context of existing knowledge regarding the cerebellar involvement in ET. A total of 51 neuroimaging studies met our search criteria, roughly divided into 19 structural and 32 functional studies. Despite clinical and methodological differences, both functional and structural imaging studies showed similar findings but without defining a clear topography of neurodegeneration. Indeed, the vast majority of studies found functional and structural abnormalities in several parts of the anterior and posterior cerebellar lobules, but it remains to be established to what degree these neural changes contribute to clinical symptoms of ET. Currently, advanced neuroimaging has confirmed the involvement of the cerebellum in pathophysiological processes of ET, although a high variability in results persists. For this reason, the translation of this knowledge into daily clinical practice is again partially limited, although new advanced multivariate neuroimaging approaches (machine-learning) are proving interesting changes of perspective.
Krause-Utz, Annegret; Frost, Rachel; Winter, Dorina; Elzinga, Bernet M
2017-01-01
Dissociation involves disruptions of usually integrated functions of consciousness, perception, memory, identity, and affect (e.g., depersonalization, derealization, numbing, amnesia, and analgesia). While the precise neurobiological underpinnings of dissociation remain elusive, neuroimaging studies in disorders, characterized by high dissociation (e.g., depersonalization/derealization disorder (DDD), dissociative identity disorder (DID), dissociative subtype of posttraumatic stress disorder (D-PTSD)), have provided valuable insight into brain alterations possibly underlying dissociation. Neuroimaging studies in borderline personality disorder (BPD), investigating links between altered brain function/structure and dissociation, are still relatively rare. In this article, we provide an overview of neurobiological models of dissociation, primarily based on research in DDD, DID, and D-PTSD. Based on this background, we review recent neuroimaging studies on associations between dissociation and altered brain function and structure in BPD. These studies are discussed in the context of earlier findings regarding methodological differences and limitations and concerning possible implications for future research and the clinical setting.
NASA Astrophysics Data System (ADS)
Ren, Hugang; Luo, Zhongchi; Yuan, Zhijia; Pan, Yingtian; Du, Congwu
2012-02-01
Characterization of cerebral hemodynamic and oxygenation metabolic changes, as well neuronal function is of great importance to study of brain functions and the relevant brain disorders such as drug addiction. Compared with other neuroimaging modalities, optical imaging techniques have the potential for high spatiotemporal resolution and dissection of the changes in cerebral blood flow (CBF), blood volume (CBV), and hemoglobing oxygenation and intracellular Ca ([Ca2+]i), which serves as markers of vascular function, tissue metabolism and neuronal activity, respectively. Recently, we developed a multiwavelength imaging system and integrated it into a surgical microscope. Three LEDs of λ1=530nm, λ2=570nm and λ3=630nm were used for exciting [Ca2+]i fluorescence labeled by Rhod2 (AM) and sensitizing total hemoglobin (i.e., CBV), and deoxygenated-hemoglobin, whereas one LD of λ1=830nm was used for laser speckle imaging to form a CBF mapping of the brain. These light sources were time-sharing for illumination on the brain and synchronized with the exposure of CCD camera for multichannel images of the brain. Our animal studies indicated that this optical approach enabled simultaneous mapping of cocaine-induced changes in CBF, CBV and oxygenated- and deoxygenated hemoglobin as well as [Ca2+]i in the cortical brain. Its high spatiotemporal resolution (30μm, 10Hz) and large field of view (4x5 mm2) are advanced as a neuroimaging tool for brain functional study.
Lizarraga, Gabriel; Li, Chunfei; Cabrerizo, Mercedes; Barker, Warren; Loewenstein, David A; Duara, Ranjan; Adjouadi, Malek
2018-04-26
Structural and functional brain images are essential imaging modalities for medical experts to study brain anatomy. These images are typically visually inspected by experts. To analyze images without any bias, they must be first converted to numeric values. Many software packages are available to process the images, but they are complex and difficult to use. The software packages are also hardware intensive. The results obtained after processing vary depending on the native operating system used and its associated software libraries; data processed in one system cannot typically be combined with data on another system. The aim of this study was to fulfill the neuroimaging community’s need for a common platform to store, process, explore, and visualize their neuroimaging data and results using Neuroimaging Web Services Interface: a series of processing pipelines designed as a cyber physical system for neuroimaging and clinical data in brain research. Neuroimaging Web Services Interface accepts magnetic resonance imaging, positron emission tomography, diffusion tensor imaging, and functional magnetic resonance imaging. These images are processed using existing and custom software packages. The output is then stored as image files, tabulated files, and MySQL tables. The system, made up of a series of interconnected servers, is password-protected and is securely accessible through a Web interface and allows (1) visualization of results and (2) downloading of tabulated data. All results were obtained using our processing servers in order to maintain data validity and consistency. The design is responsive and scalable. The processing pipeline started from a FreeSurfer reconstruction of Structural magnetic resonance imaging images. The FreeSurfer and regional standardized uptake value ratio calculations were validated using Alzheimer’s Disease Neuroimaging Initiative input images, and the results were posted at the Laboratory of Neuro Imaging data archive. Notable leading researchers in the field of Alzheimer’s Disease and epilepsy have used the interface to access and process the data and visualize the results. Tabulated results with unique visualization mechanisms help guide more informed diagnosis and expert rating, providing a truly unique multimodal imaging platform that combines magnetic resonance imaging, positron emission tomography, diffusion tensor imaging, and resting state functional magnetic resonance imaging. A quality control component was reinforced through expert visual rating involving at least 2 experts. To our knowledge, there is no validated Web-based system offering all the services that Neuroimaging Web Services Interface offers. The intent of Neuroimaging Web Services Interface is to create a tool for clinicians and researchers with keen interest on multimodal neuroimaging. More importantly, Neuroimaging Web Services Interface significantly augments the Alzheimer’s Disease Neuroimaging Initiative data, especially since our data contain a large cohort of Hispanic normal controls and Alzheimer’s Disease patients. The obtained results could be scrutinized visually or through the tabulated forms, informing researchers on subtle changes that characterize the different stages of the disease. ©Gabriel Lizarraga, Chunfei Li, Mercedes Cabrerizo, Warren Barker, David A Loewenstein, Ranjan Duara, Malek Adjouadi. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 26.04.2018.
Language Switching in the Bilingual Brain: What's Next?
ERIC Educational Resources Information Center
Hernandez, Arturo E.
2009-01-01
Recent work using functional neuroimaging with early bilinguals has found little evidence for separate neural systems for each language during picture naming (Hernandez, A. E., Dapretto, M., Mazziotta, J., & Bookheimer, S. (2001). "Language switching and language representation in Spanish-English bilinguals: An fMRI study." "Neuroimage, 14,"…
Data sharing in neuroimaging research
Poline, Jean-Baptiste; Breeze, Janis L.; Ghosh, Satrajit; Gorgolewski, Krzysztof; Halchenko, Yaroslav O.; Hanke, Michael; Haselgrove, Christian; Helmer, Karl G.; Keator, David B.; Marcus, Daniel S.; Poldrack, Russell A.; Schwartz, Yannick; Ashburner, John; Kennedy, David N.
2012-01-01
Significant resources around the world have been invested in neuroimaging studies of brain function and disease. Easier access to this large body of work should have profound impact on research in cognitive neuroscience and psychiatry, leading to advances in the diagnosis and treatment of psychiatric and neurological disease. A trend toward increased sharing of neuroimaging data has emerged in recent years. Nevertheless, a number of barriers continue to impede momentum. Many researchers and institutions remain uncertain about how to share data or lack the tools and expertise to participate in data sharing. The use of electronic data capture (EDC) methods for neuroimaging greatly simplifies the task of data collection and has the potential to help standardize many aspects of data sharing. We review here the motivations for sharing neuroimaging data, the current data sharing landscape, and the sociological or technical barriers that still need to be addressed. The INCF Task Force on Neuroimaging Datasharing, in conjunction with several collaborative groups around the world, has started work on several tools to ease and eventually automate the practice of data sharing. It is hoped that such tools will allow researchers to easily share raw, processed, and derived neuroimaging data, with appropriate metadata and provenance records, and will improve the reproducibility of neuroimaging studies. By providing seamless integration of data sharing and analysis tools within a commodity research environment, the Task Force seeks to identify and minimize barriers to data sharing in the field of neuroimaging. PMID:22493576
Functional Neuroimaging in Psychopathy.
Del Casale, Antonio; Kotzalidis, Georgios D; Rapinesi, Chiara; Di Pietro, Simone; Alessi, Maria Chiara; Di Cesare, Gianluigi; Criscuolo, Silvia; De Rossi, Pietro; Tatarelli, Roberto; Girardi, Paolo; Ferracuti, Stefano
2015-01-01
Psychopathy is associated with cognitive and affective deficits causing disruptive, harmful and selfish behaviour. These have considerable societal costs due to recurrent crime and property damage. A better understanding of the neurobiological bases of psychopathy could improve therapeutic interventions, reducing the related social costs. To analyse the major functional neural correlates of psychopathy, we reviewed functional neuroimaging studies conducted on persons with this condition. We searched the PubMed database for papers dealing with functional neuroimaging and psychopathy, with a specific focus on how neural functional changes may correlate with task performances and human behaviour. Psychopathy-related behavioural disorders consistently correlated with dysfunctions in brain areas of the orbitofrontal-limbic (emotional processing and somatic reaction to emotions; behavioural planning and responsibility taking), anterior cingulate-orbitofrontal (correct assignment of emotional valence to social stimuli; violent/aggressive behaviour and challenging attitude) and prefrontal-temporal-limbic (emotional stimuli processing/response) networks. Dysfunctional areas more consistently included the inferior frontal, orbitofrontal, dorsolateral prefrontal, ventromedial prefrontal, temporal (mainly the superior temporal sulcus) and cingulated cortices, the insula, amygdala, ventral striatum and other basal ganglia. Emotional processing and learning, and several social and affective decision-making functions are impaired in psychopathy, which correlates with specific changes in neural functions. © 2015 S. Karger AG, Basel.
Technology-Aided Assessment of Sensorimotor Function in Early Infancy
Allievi, Alessandro G.; Arichi, Tomoki; Gordon, Anne L.; Burdet, Etienne
2014-01-01
There is a pressing need for new techniques capable of providing accurate information about sensorimotor function during the first 2 years of childhood. Here, we review current clinical methods and challenges for assessing motor function in early infancy, and discuss the potential benefits of applying technology-assisted methods. We also describe how the use of these tools with neuroimaging, and in particular functional magnetic resonance imaging (fMRI), can shed new light on the intra-cerebral processes underlying neurodevelopmental impairment. This knowledge is of particular relevance in the early infant brain, which has an increased capacity for compensatory neural plasticity. Such tools could bring a wealth of knowledge about the underlying pathophysiological processes of diseases such as cerebral palsy; act as biomarkers to monitor the effects of possible therapeutic interventions; and provide clinicians with much needed early diagnostic information. PMID:25324827
Functional, Structural, and Neurotoxicity Biomarkers in Integrative Assessment of Concussions
Dambinova, Svetlana A.; Maroon, Joseph C.; Sufrinko, Alicia M.; Mullins, John David; Alexandrova, Eugenia V.; Potapov, Alexander A.
2016-01-01
Concussion is a complex, heterogeneous process affecting the brain. Accurate assessment and diagnosis and appropriate management of concussion are essential to ensure that athletes do not prematurely return to play or others to work or active military duty, risking re-injury. To date, clinical diagnosis relies primarily on evaluating subjects for functional impairment using instruments that include neurocognitive testing, subjective symptom report, and neurobehavioral assessments, such as balance and vestibular-ocular reflex testing. Structural biomarkers, defined as advanced neuroimaging techniques and biomarkers assessing neurotoxicity and immunoexcitotoxicity, may complement the use of functional biomarkers. We hypothesize that neurotoxicity AMPA, NMDA, and kainite receptor biomarkers might be utilized as a part of comprehensive approach to concussion evaluations, with the goal of increasing diagnostic accuracy and facilitating treatment planning and prognostic assessment. PMID:27761129
Imperial College near infrared spectroscopy neuroimaging analysis framework.
Orihuela-Espina, Felipe; Leff, Daniel R; James, David R C; Darzi, Ara W; Yang, Guang-Zhong
2018-01-01
This paper describes the Imperial College near infrared spectroscopy neuroimaging analysis (ICNNA) software tool for functional near infrared spectroscopy neuroimaging data. ICNNA is a MATLAB-based object-oriented framework encompassing an application programming interface and a graphical user interface. ICNNA incorporates reconstruction based on the modified Beer-Lambert law and basic processing and data validation capabilities. Emphasis is placed on the full experiment rather than individual neuroimages as the central element of analysis. The software offers three types of analyses including classical statistical methods based on comparison of changes in relative concentrations of hemoglobin between the task and baseline periods, graph theory-based metrics of connectivity and, distinctively, an analysis approach based on manifold embedding. This paper presents the different capabilities of ICNNA in its current version.
Ruiz, Sergio; Birbaumer, Niels; Sitaram, Ranganatha
2012-01-01
Considering that single locations of structural and functional abnormalities are insufficient to explain the diverse psychopathology of schizophrenia, new models have postulated that the impairments associated with the disease arise from a failure to integrate the activity of local and distributed neural circuits: the “abnormal neural connectivity hypothesis.” In the last years, new evidence coming from neuroimaging have supported and expanded this theory. However, despite the increasing evidence that schizophrenia is a disorder of neural connectivity, so far there are no treatments that have shown to produce a significant change in brain connectivity, or that have been specifically designed to alleviate this problem. Brain-Computer Interfaces based on real-time functional Magnetic Resonance Imaging (fMRI-BCI) are novel techniques that have allowed subjects to achieve self-regulation of circumscribed brain regions. In recent studies, experiments with this technology have resulted in new findings suggesting that this methodology could be used to train subjects to enhance brain connectivity, and therefore could potentially be used as a therapeutic tool in mental disorders including schizophrenia. The present article summarizes the findings coming from hemodynamics-based neuroimaging that support the abnormal connectivity hypothesis in schizophrenia, and discusses a new approach that could address this problem. PMID:23525496
Desai, Rutvik H.; Graves, William W.; Conant, Lisa L.
2009-01-01
Semantic memory refers to knowledge about people, objects, actions, relations, self, and culture acquired through experience. The neural systems that store and retrieve this information have been studied for many years, but a consensus regarding their identity has not been reached. Using strict inclusion criteria, we analyzed 120 functional neuroimaging studies focusing on semantic processing. Reliable areas of activation in these studies were identified using the activation likelihood estimate (ALE) technique. These activations formed a distinct, left-lateralized network comprised of 7 regions: posterior inferior parietal lobe, middle temporal gyrus, fusiform and parahippocampal gyri, dorsomedial prefrontal cortex, inferior frontal gyrus, ventromedial prefrontal cortex, and posterior cingulate gyrus. Secondary analyses showed specific subregions of this network associated with knowledge of actions, manipulable artifacts, abstract concepts, and concrete concepts. The cortical regions involved in semantic processing can be grouped into 3 broad categories: posterior multimodal and heteromodal association cortex, heteromodal prefrontal cortex, and medial limbic regions. The expansion of these regions in the human relative to the nonhuman primate brain may explain uniquely human capacities to use language productively, plan, solve problems, and create cultural and technological artifacts, all of which depend on the fluid and efficient retrieval and manipulation of semantic knowledge. PMID:19329570
Niu, Haijing; Wang, Jinhui; Zhao, Tengda; Shu, Ni; He, Yong
2012-01-01
The human brain is a highly complex system that can be represented as a structurally interconnected and functionally synchronized network, which assures both the segregation and integration of information processing. Recent studies have demonstrated that a variety of neuroimaging and neurophysiological techniques such as functional magnetic resonance imaging (MRI), diffusion MRI and electroencephalography/magnetoencephalography can be employed to explore the topological organization of human brain networks. However, little is known about whether functional near infrared spectroscopy (fNIRS), a relatively new optical imaging technology, can be used to map functional connectome of the human brain and reveal meaningful and reproducible topological characteristics. We utilized resting-state fNIRS (R-fNIRS) to investigate the topological organization of human brain functional networks in 15 healthy adults. Brain networks were constructed by thresholding the temporal correlation matrices of 46 channels and analyzed using graph-theory approaches. We found that the functional brain network derived from R-fNIRS data had efficient small-world properties, significant hierarchical modular structure and highly connected hubs. These results were highly reproducible both across participants and over time and were consistent with previous findings based on other functional imaging techniques. Our results confirmed the feasibility and validity of using graph-theory approaches in conjunction with optical imaging techniques to explore the topological organization of human brain networks. These results may expand a methodological framework for utilizing fNIRS to study functional network changes that occur in association with development, aging and neurological and psychiatric disorders.
Non-invasive brain stimulation of the aging brain: State of the art and future perspectives.
Tatti, Elisa; Rossi, Simone; Innocenti, Iglis; Rossi, Alessandro; Santarnecchi, Emiliano
2016-08-01
Favored by increased life expectancy and reduced birth rate, worldwide demography is rapidly shifting to older ages. The golden age of aging is not only an achievement but also a big challenge because of the load of the elderly on social and medical health care systems. Moreover, the impact of age-related decline of attention, memory, reasoning and executive functions on self-sufficiency emphasizes the need of interventions to maintain cognitive abilities at a useful degree in old age. Recently, neuroscientific research explored the chance to apply Non-Invasive Brain Stimulation (NiBS) techniques (as transcranial electrical and magnetic stimulation) to healthy aging population to preserve or enhance physiologically-declining cognitive functions. The present review will update and address the current state of the art on NiBS in healthy aging. Feasibility of NiBS techniques will be discussed in light of recent neuroimaging (either structural or functional) and neurophysiological models proposed to explain neural substrates of the physiologically aging brain. Further, the chance to design multidisciplinary interventions to maximize the efficacy of NiBS techniques will be introduced as a necessary future direction. Copyright © 2016 Elsevier B.V. All rights reserved.
Spetter, Maartje S
2018-06-20
It is in the brain where the decision is made what and how much to eat. In the last decades neuroimaging research has contributed extensively to new knowledge about appetite control by revealing the underlying brain processes. Interestingly, there is the fast growing idea of using these methods to develop new treatments for obesity and eating disorders. In this review, we summarize the findings of the importance of the use of neuropharmacology and neuroimaging techniques in understanding and modifying appetite control. Appetite control is a complex interplay between homeostatic, hedonic, and cognitive processes. Administration of the neuropeptides insulin and oxytocin curb food intake and alter brain responses in reward and cognitive control areas. Additionally, these areas can be targeted for neuromodulation or neurofeedback to reduce food cravings and increase self-control to alter food intake. The recent findings reveal the potential of intranasal administration of hormones or modifying appetite control brain networks to reduce food consumption in volunteers with overweight and obesity or individuals with an eating disorder. Although long-term clinical studies are still needed.
Contribution of Neuroimaging Studies to Understanding Development of Human Cognitive Brain Functions
Morita, Tomoyo; Asada, Minoru; Naito, Eiichi
2016-01-01
Humans experience significant physical and mental changes from birth to adulthood, and a variety of perceptual, cognitive and motor functions mature over the course of approximately 20 years following birth. To deeply understand such developmental processes, merely studying behavioral changes is not sufficient; simultaneous investigation of the development of the brain may lead us to a more comprehensive understanding. Recent advances in noninvasive neuroimaging technologies largely contribute to this understanding. Here, it is very important to consider the development of the brain from the perspectives of “structure” and “function” because both structure and function of the human brain mature slowly. In this review, we first discuss the process of structural brain development, i.e., how the structure of the brain, which is crucial when discussing functional brain development, changes with age. Second, we introduce some representative studies and the latest studies related to the functional development of the brain, particularly for visual, facial recognition, and social cognition functions, all of which are important for humans. Finally, we summarize how brain science can contribute to developmental study and discuss the challenges that neuroimaging should address in the future. PMID:27695409
ERIC Educational Resources Information Center
Ghassabian, Akhgar; Herba, Catherine M.; Roza, Sabine J.; Govaert, Paul; Schenk, Jacqueline J.; Jaddoe, Vincent W.; Hofman, Albert; White, Tonya; Verhulst, Frank C.; Tiemeier, Henning
2013-01-01
Background: Neuroimaging findings have provided evidence for a relation between variations in brain structures and Attention Deficit/Hyperactivity Disorder (ADHD). However, longitudinal neuroimaging studies are typically confined to children who have already been diagnosed with ADHD. In a population-based study, we aimed to characterize the…
ERIC Educational Resources Information Center
Durston, Sarah; Konrad, Kerstin
2007-01-01
This paper aims to illustrate how combining multiple approaches can inform us about the neurobiology of ADHD. Converging evidence from genetic, psychopharmacological and functional neuroimaging studies has implicated dopaminergic fronto-striatal circuitry in ADHD. However, while the observation of converging evidence from multiple vantage points…
The iconography of mourning and its neural correlates: a functional neuroimaging study.
Labek, Karin; Berger, Samantha; Buchheim, Anna; Bosch, Julia; Spohrs, Jennifer; Dommes, Lisa; Beschoner, Petra; Stingl, Julia C; Viviani, Roberto
2017-08-01
The present functional neuroimaging study focuses on the iconography of mourning. A culture-specific pattern of body postures of mourning individuals, mostly suggesting withdrawal, emerged from a survey of visual material. When used in different combinations in stylized drawings in our neuroimaging study, this material activated cortical areas commonly seen in studies of social cognition (temporo-parietal junction, superior temporal gyrus, and inferior temporal lobe), empathy for pain (somatosensory cortex), and loss (precuneus, middle/posterior cingular gyrus). This pattern of activation developed over time. While in the early phases of exposure lower association areas, such as the extrastriate body area, were active, in the late phases activation in parietal and temporal association areas and the prefrontal cortex was more prominent. These findings are consistent with the conventional and contextual character of iconographic material, and further differentiate it from emotionally negatively valenced and high-arousing stimuli. In future studies, this neuroimaging assay may be useful in characterizing interpretive appraisal of material of negative emotional valence. © The Author (2017). Published by Oxford University Press.
Neural systems and time course of proactive interference in working memory.
Du, Yingchun; Zhang, John X; Xiao, Zhuangwei; Wu, Renhua
2007-01-01
The storage of information in working memory suffers as a function of proactive interference. Many works using neuroimaging technique have been done to reveal the brain mechanism of interference resolution. However, less is yet known about the time course of this process. Event-related potential method(ERP) and standardized Low Resolution Brain Electromagnetic Tomography method (sLORETA) were used in this study to discover the time course of interference resolution in working memory. The anterior P2 was thought to reflect interference resolution and if so, this process occurred earlier in working memory than in long-term memory.
[Non-medical applications for brain MRI: Ethical considerations].
Sarrazin, S; Fagot-Largeault, A; Leboyer, M; Houenou, J
2015-04-01
The recent neuroimaging techniques offer the possibility to better understand complex cognitive processes that are involved in mental disorders and thus have become cornerstone tools for research in psychiatry. The performances of functional magnetic resonance imaging are not limited to medical research and are used in non-medical fields. These recent applications represent new challenges for bioethics. In this article we aim at discussing the new ethical issues raised by the applications of the latest neuroimaging technologies to non-medical fields. We included a selection of peer-reviewed English medical articles after a search on NCBI Pubmed database and Google scholar from 2000 to 2013. We screened bibliographical tables for supplementary references. Websites of governmental French institutions implicated in ethical questions were also screened for governmental reports. Findings of brain areas supporting emotional responses and regulation have been used for marketing research, also called neuromarketing. The discovery of different brain activation patterns in antisocial disorder has led to changes in forensic psychiatry with the use of imaging techniques with unproven validity. Automated classification algorithms and multivariate statistical analyses of brain images have been applied to brain-reading techniques, aiming at predicting unconscious neural processes in humans. We finally report the current position of the French legislation recently revised and discuss the technical limits of such techniques. In the near future, brain imaging could find clinical applications in psychiatry as diagnostic or predictive tools. However, the latest advances in brain imaging are also used in non-scientific fields raising key ethical questions. Involvement of neuroscientists, psychiatrists, physicians but also of citizens in neuroethics discussions is crucial to challenge the risk of unregulated uses of brain imaging. Copyright © 2014 L’Encéphale, Paris. Published by Elsevier Masson SAS. All rights reserved.
Systematic review with meta-analysis: neuroimaging in hepatitis C chronic infection.
Oriolo, G; Egmond, E; Mariño, Z; Cavero, M; Navines, R; Zamarrenho, L; Solà, R; Pujol, J; Bargallo, N; Forns, X; Martin-Santos, R
2018-05-01
Chronic hepatitis C is considered a systemic disease because of extra-hepatic manifestations. Neuroimaging has been employed in hepatitis C virus-infected patients to find in vivo evidence of central nervous system alterations. Systematic review and meta-analysis of neuroimaging research in chronic hepatitis C treatment naive patients, or patients previously treated without sustained viral response, to study structural and functional brain impact of hepatitis C. Using PRISMA guidelines a database search was conducted from inception up until 1 May 2017 for peer-reviewed studies on structural or functional neuroimaging assessment of chronic hepatitis C patients without cirrhosis or encephalopathy, with control group. Meta-analyses were performed when possible. The final sample comprised 25 studies (magnetic resonance spectroscopy [N = 12], perfusion weighted imaging [N = 1], positron emission tomography [N = 3], single-photon emission computed tomography [N = 4], functional connectivity in resting state [N = 1], diffusion tensor imaging [N = 2] and structural magnetic resonance imaging [N = 2]). The whole sample was of 509 chronic hepatitis C patients, with an average age of 41.5 years old and mild liver disease. A meta-analysis of magnetic resonance spectroscopy studies showed increased levels of choline/creatine ratio (mean difference [MD] 0.12, 95% confidence interval [CI] 0.06-0.18), creatine (MD 0.85, 95% CI 0.42-1.27) and glutamate plus glutamine (MD 1.67, 95% CI 0.39-2.96) in basal ganglia and increased levels of choline/creatine ratio in centrum semiovale white matter (MD 0.13, 95% CI 0.07-0.19) in chronic hepatitis C patients compared with healthy controls. Photon emission tomography studies meta-analyses did not find significant differences in PK11195 binding potential in cortical and subcortical regions of chronic hepatitis C patients compared with controls. Correlations were observed between various neuroimaging alterations and neurocognitive impairment, fatigue and depressive symptoms in some studies. Patients with chronic hepatitis C exhibit cerebral metabolite alterations and structural or functional neuroimaging abnormalities, which sustain the hypothesis of hepatitis C virus involvement in brain disturbances. © 2018 John Wiley & Sons Ltd.
[Savant or idiot savant syndrome].
Muñoz-Yunta, J A; Ortiz-Alonso, T; Amo, C; Fernández-Lucas, A; Maestú, F; Palau-Baduell, M
2003-02-01
Savant syndrome is currently still very mysterious, yet, thanks to the progress made in neuroimaging studies and especially MSI (Magnetic Source Imaging) techniques, a little more is now known about it. The theory, formulated many years ago, about damage to the left hemisphere of the brain has been supported by functional neuroimaging. Its relation to developmental disorders or to autism spectrum disorders is far more justified today and can be explained on the basis of its neuropathology. We present a study based on a review of the scientific literature concerning the syndrome, from the first time it was described back in 1789 by Benjamin Rush up to the present day. We comment on its epidemiology and positive clinical manifestations, involving brilliant artistic talent and dazzling memory, but also the negative aspects suffered by these autistic patients. The most important theories are discussed together with the clinical coincidence with frontotemporal dementia and the responsibility of the right hemisphere when there are alterations in the contralateral hemisphere. The latest contributions made by Positron Emission Tomography and magnetoencephalography will be discussed and a mini-video of a personal case will be projected.
Hypnosis and imaging of the living human brain.
Landry, Mathieu; Raz, Amir
2015-01-01
Over more than two decades, studies using imaging techniques of the living human brain have begun to explore the neural correlates of hypnosis. The collective findings provide a gripping, albeit preliminary, account of the underlying neurobiological mechanisms involved in hypnotic phenomena. While substantial advances lend support to different hypotheses pertaining to hypnotic modulation of attention, control, and monitoring processes, the complex interactions among the many mediating variables largely hinder our ability to isolate robust commonalities across studies. The present account presents a critical integrative synthesis of neuroimaging studies targeting hypnosis as a function of suggestion. Specifically, hypnotic induction without task-specific suggestion is examined, as well as suggestions concerning sensation and perception, memory, and ideomotor response. The importance of carefully designed experiments is highlighted to better tease apart the neural correlates that subserve hypnotic phenomena. Moreover, converging findings intimate that hypnotic suggestions seem to induce specific neural patterns. These observations propose that suggestions may have the ability to target focal brain networks. Drawing on evidence spanning several technological modalities, neuroimaging studies of hypnosis pave the road to a more scientific understanding of a dramatic, yet largely evasive, domain of human behavior.
Neuroimaging of Fear-Associated Learning
Greco, John A; Liberzon, Israel
2016-01-01
Fear conditioning has been commonly used as a model of emotional learning in animals and, with the introduction of functional neuroimaging techniques, has proven useful in establishing the neurocircuitry of emotional learning in humans. Studies of fear acquisition suggest that regions such as amygdala, insula, anterior cingulate cortex, and hippocampus play an important role in acquisition of fear, whereas studies of fear extinction suggest that the amygdala is also crucial for safety learning. Extinction retention testing points to the ventromedial prefrontal cortex as an essential region in the recall of the safety trace, and explicit learning of fear and safety associations recruits additional cortical and subcortical regions. Importantly, many of these findings have implications in our understanding of the pathophysiology of psychiatric disease. Recent studies using clinical populations have lent insight into the changes in regional activity in specific disorders, and treatment studies have shown how pharmaceutical and other therapeutic interventions modulate brain activation during emotional learning. Finally, research investigating individual differences in neurotransmitter receptor genotypes has highlighted the contribution of these systems in fear-associated learning. PMID:26294108
Dynamic causal modelling: a critical review of the biophysical and statistical foundations.
Daunizeau, J; David, O; Stephan, K E
2011-09-15
The goal of dynamic causal modelling (DCM) of neuroimaging data is to study experimentally induced changes in functional integration among brain regions. This requires (i) biophysically plausible and physiologically interpretable models of neuronal network dynamics that can predict distributed brain responses to experimental stimuli and (ii) efficient statistical methods for parameter estimation and model comparison. These two key components of DCM have been the focus of more than thirty methodological articles since the seminal work of Friston and colleagues published in 2003. In this paper, we provide a critical review of the current state-of-the-art of DCM. We inspect the properties of DCM in relation to the most common neuroimaging modalities (fMRI and EEG/MEG) and the specificity of inference on neural systems that can be made from these data. We then discuss both the plausibility of the underlying biophysical models and the robustness of the statistical inversion techniques. Finally, we discuss potential extensions of the current DCM framework, such as stochastic DCMs, plastic DCMs and field DCMs. Copyright © 2009 Elsevier Inc. All rights reserved.
HomER: a review of time-series analysis methods for near-infrared spectroscopy of the brain
Huppert, Theodore J.; Diamond, Solomon G.; Franceschini, Maria A.; Boas, David A.
2009-01-01
Near-infrared spectroscopy (NIRS) is a noninvasive neuroimaging tool for studying evoked hemodynamic changes within the brain. By this technique, changes in the optical absorption of light are recorded over time and are used to estimate the functionally evoked changes in cerebral oxyhemoglobin and deoxyhemoglobin concentrations that result from local cerebral vascular and oxygen metabolic effects during brain activity. Over the past three decades this technology has continued to grow, and today NIRS studies have found many niche applications in the fields of psychology, physiology, and cerebral pathology. The growing popularity of this technique is in part associated with a lower cost and increased portability of NIRS equipment when compared with other imaging modalities, such as functional magnetic resonance imaging and positron emission tomography. With this increasing number of applications, new techniques for the processing, analysis, and interpretation of NIRS data are continually being developed. We review some of the time-series and functional analysis techniques that are currently used in NIRS studies, we describe the practical implementation of various signal processing techniques for removing physiological, instrumental, and motion-artifact noise from optical data, and we discuss the unique aspects of NIRS analysis in comparison with other brain imaging modalities. These methods are described within the context of the MATLAB-based graphical user interface program, HomER, which we have developed and distributed to facilitate the processing of optical functional brain data. PMID:19340120
A Neurogenetic Approach to Impulsivity
Congdon, Eliza; Canli, Turhan
2008-01-01
Impulsivity is a complex and multidimensional trait that is of interest to both personality psychologists and to clinicians. For investigators seeking the biological basis of personality traits, the use of neuroimaging techniques such as positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) revolutionized personality psychology in less than a decade. Now, another revolution is under way, and it originates from molecular biology. Specifically, new findings in molecular genetics, the detailed mapping and the study of the function of genes, have shown that individual differences in personality traits can be related to individual differences within specific genes. In this article, we will review the current state of the field with respect to the neural and genetic basis of trait impulsivity. PMID:19012655
Son, Seong-Jin; Kim, Jonghoon; Park, Hyunjin
2017-01-01
Regional volume atrophy and functional degeneration are key imaging hallmarks of Alzheimer's disease (AD) in structural and functional magnetic resonance imaging (MRI), respectively. We jointly explored regional volume atrophy and functional connectivity to better characterize neuroimaging data of AD and mild cognitive impairment (MCI). All data were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We compared regional volume atrophy and functional connectivity in 10 subcortical regions using structural MRI and resting-state functional MRI (rs-fMRI). Neuroimaging data of normal controls (NC) (n = 35), MCI (n = 40), and AD (n = 30) were compared. Significant differences of regional volumes and functional connectivity measures between groups were assessed using permutation tests in 10 regions. The regional volume atrophy and functional connectivity of identified regions were used as features for the random forest classifier to distinguish among three groups. The features of the identified regions were also regarded as connectional fingerprints that could distinctively separate a given group from the others. We identified a few regions with distinctive regional atrophy and functional connectivity patterns for NC, MCI, and AD groups. A three label classifier using the information of regional volume atrophy and functional connectivity of identified regions achieved classification accuracy of 53.33% to distinguish among NC, MCI, and AD. We identified distinctive regional atrophy and functional connectivity patterns that could be regarded as a connectional fingerprint.
Son, Seong-Jin; Kim, Jonghoon
2017-01-01
Regional volume atrophy and functional degeneration are key imaging hallmarks of Alzheimer’s disease (AD) in structural and functional magnetic resonance imaging (MRI), respectively. We jointly explored regional volume atrophy and functional connectivity to better characterize neuroimaging data of AD and mild cognitive impairment (MCI). All data were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We compared regional volume atrophy and functional connectivity in 10 subcortical regions using structural MRI and resting-state functional MRI (rs-fMRI). Neuroimaging data of normal controls (NC) (n = 35), MCI (n = 40), and AD (n = 30) were compared. Significant differences of regional volumes and functional connectivity measures between groups were assessed using permutation tests in 10 regions. The regional volume atrophy and functional connectivity of identified regions were used as features for the random forest classifier to distinguish among three groups. The features of the identified regions were also regarded as connectional fingerprints that could distinctively separate a given group from the others. We identified a few regions with distinctive regional atrophy and functional connectivity patterns for NC, MCI, and AD groups. A three label classifier using the information of regional volume atrophy and functional connectivity of identified regions achieved classification accuracy of 53.33% to distinguish among NC, MCI, and AD. We identified distinctive regional atrophy and functional connectivity patterns that could be regarded as a connectional fingerprint. PMID:28333946
Kober, Hedy; Barrett, Lisa Feldman; Joseph, Josh; Bliss-Moreau, Eliza; Lindquist, Kristen; Wager, Tor D.
2009-01-01
We performed an updated quantitative meta-analysis of 162 neuroimaging studies of emotion using a novel multi-level kernel-based approach, focusing on locating brain regions consistently activated in emotional tasks and their functional organization into distributed functional groups, independent of semantically defined emotion category labels (e.g., “anger,” “fear”). Such brain-based analyses are critical if our ways of labeling emotions are to be evaluated and revised based on consistency with brain data. Consistent activations were limited to specific cortical sub-regions, including multiple functional areas within medial, orbital, and inferior lateral frontal cortices. Consistent with a wealth of animal literature, multiple subcortical activations were identified, including amygdala, ventral striatum, thalamus, hypothalamus, and periaqueductal gray. We used multivariate parcellation and clustering techniques to identify groups of co-activated brain regions across studies. These analyses identified six distributed functional groups, including medial and lateral frontal groups, two posterior cortical groups, and paralimbic and core limbic/brainstem groups. These functional groups provide information on potential organization of brain regions into large-scale networks. Specific follow-up analyses focused on amygdala, periaqueductal gray (PAG), and hypothalamic (Hy) activations, and identified frontal cortical areas co-activated with these core limbic structures. While multiple areas of frontal cortex co-activated with amygdala sub-regions, a specific region of dorsomedial prefrontal cortex (dmPFC, Brodmann’s Area 9/32) was the only area co-activated with both PAG and Hy. Subsequent mediation analyses were consistent with a pathway from dmPFC through PAG to Hy. These results suggest that medial frontal areas are more closely associated with core limbic activation than their lateral counterparts, and that dmPFC may play a particularly important role in the cognitive generation of emotional states. PMID:18579414
Neuroimaging studies of the striatum in cognition Part I: healthy individuals
Provost, Jean-Sebastien; Hanganu, Alexandru; Monchi, Oury
2015-01-01
The striatum has traditionally mainly been associated with playing a key role in the modulation of motor functions. Indeed, lesion studies in animals and studies of some neurological conditions in humans have brought further evidence to this idea. However, better methods of investigation have raised concerns about this notion, and it was proposed that the striatum could also be involved in different types of functions including cognitive ones. Although the notion was originally a matter of debate, it is now well-accepted that the caudate nucleus contributes to cognition, while the putamen could be involved in motor functions, and to some extent in cognitive functions as well. With the arrival of modern neuroimaging techniques in the early 1990, knowledge supporting the cognitive aspect of the striatum has greatly increased, and a substantial number of scientific papers were published studying the role of the striatum in healthy individuals. For the first time, it was possible to assess the contribution of specific areas of the brain during the execution of a cognitive task. Neuroanatomical studies have described functional loops involving the striatum and the prefrontal cortex suggesting a specific interaction between these two structures. This review examines the data up to date and provides strong evidence for a specific contribution of the fronto-striatal regions in different cognitive processes, such as set-shifting, self-initiated responses, rule learning, action-contingency, and planning. Finally, a new two-level functional model involving the prefrontal cortex and the dorsal striatum is proposed suggesting an essential role of the dorsal striatum in selecting between competing potential responses or actions, and in resolving a high level of ambiguity. PMID:26500513
Neuroimaging studies of the striatum in cognition Part I: healthy individuals.
Provost, Jean-Sebastien; Hanganu, Alexandru; Monchi, Oury
2015-01-01
The striatum has traditionally mainly been associated with playing a key role in the modulation of motor functions. Indeed, lesion studies in animals and studies of some neurological conditions in humans have brought further evidence to this idea. However, better methods of investigation have raised concerns about this notion, and it was proposed that the striatum could also be involved in different types of functions including cognitive ones. Although the notion was originally a matter of debate, it is now well-accepted that the caudate nucleus contributes to cognition, while the putamen could be involved in motor functions, and to some extent in cognitive functions as well. With the arrival of modern neuroimaging techniques in the early 1990, knowledge supporting the cognitive aspect of the striatum has greatly increased, and a substantial number of scientific papers were published studying the role of the striatum in healthy individuals. For the first time, it was possible to assess the contribution of specific areas of the brain during the execution of a cognitive task. Neuroanatomical studies have described functional loops involving the striatum and the prefrontal cortex suggesting a specific interaction between these two structures. This review examines the data up to date and provides strong evidence for a specific contribution of the fronto-striatal regions in different cognitive processes, such as set-shifting, self-initiated responses, rule learning, action-contingency, and planning. Finally, a new two-level functional model involving the prefrontal cortex and the dorsal striatum is proposed suggesting an essential role of the dorsal striatum in selecting between competing potential responses or actions, and in resolving a high level of ambiguity.
Brain alterations in paedophilia: a critical review.
Mohnke, Sebastian; Müller, Sabine; Amelung, Till; Krüger, Tillmann H C; Ponseti, Jorge; Schiffer, Boris; Walter, Martin; Beier, Klaus M; Walter, Henrik
2014-11-01
Psychosocial and biological factors have been implicated in paedophilia, such as alterations in brain structure and function. The purpose of this paper is to review the expanding body of literature on this topic including brain abnormality case reports, as well as structural and functional neuroimaging studies. Case studies of men who have committed sexual offences against children implicate frontal and temporal abnormalities that may be associated with impaired impulse inhibition. Structural neuroimaging investigations show volume reductions in paedophilic men. Although the findings have been heterogeneous, smaller amygdala volume has been replicated repeatedly. Functional neuroimaging investigations demonstrate an overlap between paedophiles and teleiophiles during sexual arousal processing. While it is controversial among studies regarding group differences, reliable discrimination between paedophilic and teleiophilic men may be achieved using functional activation patterns. Nevertheless, the heterogeneous findings published so far suggest further research is necessary to disentangle the neurobiological mechanisms of paedophilic preference. A number of methodological confounds have been identified, which may account for the inconsistent results that could prove to be beneficial for future investigations. Copyright © 2014 Elsevier Ltd. All rights reserved.
Gray matter abnormalities in opioid-dependent patients: A neuroimaging meta-analysis.
Wollman, Scott C; Alhassoon, Omar M; Hall, Matthew G; Stern, Mark J; Connors, Eric J; Kimmel, Christine L; Allen, Kenneth E; Stephan, Rick A; Radua, Joaquim
2017-09-01
Prior research utilizing whole-brain neuroimaging techniques has identified structural differences in gray matter in opioid-dependent individuals. However, the results have been inconsistent. The current study meta-analytically examines the neuroimaging findings of studies published before 2016 comparing opioid-dependent individuals to drug-naïve controls. Exhaustive search of five databases yielded 12 studies that met inclusion criteria. Anisotropic Effect-Size Seed-Based d Mapping (AES-SDM) was used to analyze the data extracted by three independent researchers. Voxel-based AES-SDM distinguishes increases and decreases in brain matter significant at the whole-brain level. AES-SDM identified the fronto-temporal region, bilaterally, as being the primary site of gray matter deficits associated with opioid use. Moderator analysis revealed that length of opioid use was negatively associated with gray matter in the left cerebellar vermis and the right Rolandic operculum, including the insula. Meta-regression revealed no remaining significant areas of gray matter reductions, except in the precuneus, following longer abstinence from opioids. Opioid-dependent individuals had significantly less gray matter in several regions that play a key role in cognitive and affective processing. The findings provide evidence that opioid dependence may result in the breakdown of two distinct yet highly overlapping structural and functional systems. These are the fronto-cerebellar system that might be more responsible for impulsivity, compulsive behaviors, and affective disturbances and the fronto-insular system that might account more for the cognitive and decision-making impairments.
Renvall, Hanna; Salmela, Elina; Vihla, Minna; Illman, Mia; Leinonen, Eira; Kere, Juha; Salmelin, Riitta
2012-10-17
Neural processes are explored through macroscopic neuroimaging and microscopic molecular measures, but the two levels remain primarily detached. The identification of direct links between the levels would facilitate use of imaging signals as probes of genetic function and, vice versa, access to molecular correlates of imaging measures. Neuroimaging patterns have been mapped for a few isolated genes, chosen based on their connection with a clinical disorder. Here we propose an approach that allows an unrestricted discovery of the genetic basis of a neuroimaging phenotype in the normal human brain. The essential components are a subject population that is composed of relatives and selection of a neuroimaging phenotype that is reproducible within an individual and similar between relatives but markedly variable across a population. Our present combined magnetoencephalography and genome-wide linkage study in 212 healthy siblings demonstrates that auditory cortical activation strength is highly heritable and, specifically in the right hemisphere, regulated oligogenically with linkages to chromosomes 2q37, 3p12, and 8q24. The identified regions delimit as candidate genes TRAPPC9, operating in neuronal differentiation, and ROBO1, regulating projections of thalamocortical axons. Identification of normal genetic variation underlying neurophysiological phenotypes offers a non-invasive platform for an in-depth, concerted capitalization of molecular and neuroimaging levels in exploring neural function.
The role of neuroimaging in sport-related concussion.
Prabhu, Sanjay P
2011-01-01
This article describes some of the newer techniques that are being used in the clinical assessment of patients following mild to moderate TBI, addresses their use in the acute setting, and explores their potential role in long-term follow-up. Also addressed are the challenges faced before some of these newer techniques can be incorporated into routine clinical management. Large studies are needed with a special emphasis on the effects of repeated head trauma in the young athlete. This is especially relevant where conventional imaging does not demonstrate a macroscopic abnormality. The emphasis has to shift from identifying structural abnormalities on imaging studies to understanding the functional changes in the brain that may explain the long-term neuropsychological effects of concussion and mTBI. Copyright © 2011 Elsevier Inc. All rights reserved.
The cerebellum and cognition: evidence from functional imaging studies.
Stoodley, Catherine J
2012-06-01
Evidence for a role of the human cerebellum in cognitive functions comes from anatomical, clinical and neuroimaging data. Functional neuroimaging reveals cerebellar activation during a variety of cognitive tasks, including language, visual-spatial, executive, and working memory processes. It is important to note that overt movement is not a prerequisite for cerebellar activation: the cerebellum is engaged during conditions which either control for motor output or do not involve motor responses. Resting-state functional connectivity data reveal that, in addition to networks underlying motor control, the cerebellum is part of "cognitive" networks with prefrontal and parietal association cortices. Consistent with these findings, regional differences in activation patterns within the cerebellum are evident depending on the task demands, suggesting that the cerebellum can be broadly divided into functional regions based on the patterns of anatomical connectivity between different regions of the cerebellum and sensorimotor and association areas of the cerebral cortex. However, the distinct contribution of the cerebellum to cognitive tasks is not clear. Here, the functional neuroimaging evidence for cerebellar involvement in cognitive functions is reviewed and related to hypotheses as to why the cerebellum is active during such tasks. Identifying the precise role of the cerebellum in cognition-as well as the mechanism by which the cerebellum modulates performance during a wide range of tasks-remains a challenge for future investigations.
Source counting in MEG neuroimaging
NASA Astrophysics Data System (ADS)
Lei, Tianhu; Dell, John; Magee, Ralphy; Roberts, Timothy P. L.
2009-02-01
Magnetoencephalography (MEG) is a multi-channel, functional imaging technique. It measures the magnetic field produced by the primary electric currents inside the brain via a sensor array composed of a large number of superconducting quantum interference devices. The measurements are then used to estimate the locations, strengths, and orientations of these electric currents. This magnetic source imaging technique encompasses a great variety of signal processing and modeling techniques which include Inverse problem, MUltiple SIgnal Classification (MUSIC), Beamforming (BF), and Independent Component Analysis (ICA) method. A key problem with Inverse problem, MUSIC and ICA methods is that the number of sources must be detected a priori. Although BF method scans the source space on a point-to-point basis, the selection of peaks as sources, however, is finally made by subjective thresholding. In practice expert data analysts often select results based on physiological plausibility. This paper presents an eigenstructure approach for the source number detection in MEG neuroimaging. By sorting eigenvalues of the estimated covariance matrix of the acquired MEG data, the measured data space is partitioned into the signal and noise subspaces. The partition is implemented by utilizing information theoretic criteria. The order of the signal subspace gives an estimate of the number of sources. The approach does not refer to any model or hypothesis, hence, is an entirely data-led operation. It possesses clear physical interpretation and efficient computation procedure. The theoretical derivation of this method and the results obtained by using the real MEG data are included to demonstrates their agreement and the promise of the proposed approach.
2015-10-01
that includes physical and neuropsychological evaluations, neuroimaging (MRI, fMRI , DTI), adrenal function tests, and diverse immune, inflammatory...characterized by a profile of concurrent symptoms that typically includes persistent headaches, memory and cognitive difficulties, widespread pain, unexplained...includes physical examinations, neuroimaging (MRI volumetric assessments, fMRI , diffusion tensor imaging), neuropsychological evaluations, assessment
ERIC Educational Resources Information Center
Suskauer, Stacy J.; Huisman, Thierry A. G. M.
2009-01-01
Although neuroimaging has long played a role in the acute management of pediatric traumatic brain injury (TBI), until recently, its use as a tool for understanding and predicting long-term brain-behavior relationships after TBI has been limited by the relatively poor sensitivity of routine clinical imaging for detecting diffuse axonal injury…
Roussotte, Florence; Soderberg, Lindsay
2010-01-01
Prenatal exposure to alcohol and stimulants negatively affects the developing trajectory of the central nervous system in many ways. Recent advances in neuroimaging methods have allowed researchers to study the structural, metabolic, and functional abnormalities resulting from prenatal exposure to drugs of abuse in living human subjects. Here we review the neuroimaging literature of prenatal exposure to alcohol, cocaine, and methamphetamine. Neuroimaging studies of prenatal alcohol exposure have reported differences in the structure and metabolism of many brain systems, including in frontal, parietal, and temporal regions, in the cerebellum and basal ganglia, as well as in the white matter tracts that connect these brain regions. Functional imaging studies have identified significant differences in brain activation related to various cognitive domains as a result of prenatal alcohol exposure. The published literature of prenatal exposure to cocaine and methamphetamine is much smaller, but evidence is beginning to emerge suggesting that exposure to stimulant drugs in utero may be particularly toxic to dopamine-rich basal ganglia regions. Although the interpretation of such findings is somewhat limited by the problem of polysubstance abuse and by the difficulty of obtaining precise exposure histories in retrospective studies, such investigations provide important insights into the effects of drugs of abuse on the structure, function, and metabolism of the developing human brain. These insights may ultimately help clinicians develop better diagnostic tools and devise appropriate therapeutic interventions to improve the condition of children with prenatal exposure to drugs of abuse. PMID:20978945
Febo, Marcelo; Ferris, Craig F.
2014-01-01
Oxytocin and vasopressin modulate a range of species typical behavioral functions that include social recognition, maternal-infant attachment, and modulation of memory, offensive aggression, defensive fear reactions, and reward seeking. We have employed novel functional magnetic resonance mapping techniques in awake rats to explore the roles of these neuropeptides in the maternal and non-maternal brain. Results from the functional neuroimaging studies that are summarized here have directly and indirectly confirmed and supported previous findings. Oxytocin is released within the lactating rat brain during suckling stimulation and activates specific subcortical networks in the maternal brain. Both vasopressin and oxytocin modulate brain regions involved unconditioned fear, processing of social stimuli and the expression of agonistic behaviors. Across studies there are relatively consistent brain networks associated with internal motivational drives and emotional states that are modulated by oxytocin and vasopressin. PMID:24486356
Modeling Brain Dynamics in Brain Tumor Patients Using the Virtual Brain.
Aerts, Hannelore; Schirner, Michael; Jeurissen, Ben; Van Roost, Dirk; Achten, Eric; Ritter, Petra; Marinazzo, Daniele
2018-01-01
Presurgical planning for brain tumor resection aims at delineating eloquent tissue in the vicinity of the lesion to spare during surgery. To this end, noninvasive neuroimaging techniques such as functional MRI and diffusion-weighted imaging fiber tracking are currently employed. However, taking into account this information is often still insufficient, as the complex nonlinear dynamics of the brain impede straightforward prediction of functional outcome after surgical intervention. Large-scale brain network modeling carries the potential to bridge this gap by integrating neuroimaging data with biophysically based models to predict collective brain dynamics. As a first step in this direction, an appropriate computational model has to be selected, after which suitable model parameter values have to be determined. To this end, we simulated large-scale brain dynamics in 25 human brain tumor patients and 11 human control participants using The Virtual Brain, an open-source neuroinformatics platform. Local and global model parameters of the Reduced Wong-Wang model were individually optimized and compared between brain tumor patients and control subjects. In addition, the relationship between model parameters and structural network topology and cognitive performance was assessed. Results showed (1) significantly improved prediction accuracy of individual functional connectivity when using individually optimized model parameters; (2) local model parameters that can differentiate between regions directly affected by a tumor, regions distant from a tumor, and regions in a healthy brain; and (3) interesting associations between individually optimized model parameters and structural network topology and cognitive performance.
A cognitive neurobiological account of deception: evidence from functional neuroimaging.
Spence, Sean A; Hunter, Mike D; Farrow, Tom F D; Green, Russell D; Leung, David H; Hughes, Catherine J; Ganesan, Venkatasubramanian
2004-01-01
An organism may use misinformation, knowingly (through deception) or unknowingly (as in the case of camouflage), to gain advantage in a competitive environment. From an evolutionary perspective, greater tactical deception occurs among primates closer to humans, with larger neocortices. In humans, the onset of deceptive behaviours in childhood exhibits a developmental trajectory, which may be regarded as 'normal' in the majority and deficient among a minority with certain neurodevelopmental disorders (e.g. autism). In the human adult, deception and lying exhibit features consistent with their use of 'higher' or 'executive' brain systems. Accurate detection of deception in humans may be of particular importance in forensic practice, while an understanding of its cognitive neurobiology may have implications for models of 'theory of mind' and social cognition, and societal notions of responsibility, guilt and mitigation. In recent years, functional neuroimaging techniques (especially functional magnetic resonance imaging) have been used to study deception. Though few in number, and using very different experimental protocols, studies published in the peer-reviewed literature exhibit certain consistencies. Attempted deception is associated with activation of executive brain regions (particularly prefrontal and anterior cingulate cortices), while truthful responding has not been shown to be associated with any areas of increased activation (relative to deception). Hence, truthful responding may comprise a relative 'baseline' in human cognition and communication. The subject who lies may necessarily engage 'higher' brain centres, consistent with a purpose or intention (to deceive). While the principle of executive control during deception remains plausible, its precise anatomy awaits elucidation. PMID:15590616
Pharmacological MRI in animal models: a useful tool for 5-HT research?
Martin, Chris; Sibson, Nicola R
2008-11-01
Pharmacological magnetic resonance imaging (phMRI) offers the potential to provide novel insights into the functioning of neurotransmitter systems and drug action in the central nervous system. To date, much of the neuropharmacological research that has applied phMRI techniques has focused on the dopaminergic system with relatively few studies into serotonergic function. In this article, we discuss the current capabilities of, and future potential for phMRI to address fundamental questions in serotonergic research using animal models. Firstly we review existing literature on the application of phMRI to the serotonergic system by exploring 3 broad research themes: (i) the functional anatomy of the serotonergic system; (ii) drug-receptor targeting and distribution; and (iii) disease models and drug development. Subsequently, we discuss the interpretation of phMRI data in terms of neuropharmacological action with a focus on issues specific to neuroimaging studies of the serotonergic system. Unlike other neuroimaging approaches such as positron emission tomography, phMRI methods do not currently offer sensitivity to markers of specific pharmacological action. However, they can provide in vivo markers of the neuropharmacological modulation of neuronal activity across the whole brain with unparalleled spatial and temporal resolution. Furthermore, due to the non-invasive nature of MRI, these markers are readily translatable to human studies. Whilst there are a number of constraints and limitations to phMRI methods that necessitate careful data interpretation, we argue that phMRI could become a valuable research tool in neuropharmacological studies of the serotonergic system.
Sestini, S
2007-07-01
Functional imaging techniques such as positron and single-photon emission tomography exploit the relationship between neural activity, energy demand and cerebral blood flow to functionally map the brain. Despite the fact that neurobiological processes are not completely understood, several results have revealed the signals that trigger the metabolic and vascular changes accompanying variations in neural activity. Advances in this field have demonstrated that release of the major excitatory neurotransmitter glutamate initiates diverse signaling processes between neurons, astrocytes and blood perfusion, and that this signaling is crucial for the occurrence of brain imaging signals. Better understanding of the neural sites of energy consumption and the temporal correlation between energy demand, energy consumption and associated cerebrovascular hemodynamics gives novel insight into the potential of these imaging tools in the study of metabolic neurodegenerative disorders.
Kang, Yeona; Mozley, P David; Verma, Ajay; Schlyer, David; Henchcliffe, Claire; Gauthier, Susan A; Chiao, Ping C; He, Bin; Nikolopoulou, Anastasia; Logan, Jean; Sullivan, Jenna M; Pryor, Kane O; Hesterman, Jacob; Kothari, Paresh J; Vallabhajosula, Shankar
2018-05-04
Neuroinflammation has been implicated in the pathophysiology of Parkinson's disease (PD), which might be influenced by successful neuroprotective drugs. The uptake of [ 11 C](R)-PK11195 (PK) is often considered to be a proxy for neuroinflammation, and can be quantified using the Logan graphical method with an image-derived blood input function, or the Logan reference tissue model using automated reference region extraction. The purposes of this study were (1) to assess whether these noninvasive image analysis methods can discriminate between patients with PD and healthy volunteers (HVs), and (2) to establish the effect size that would be required to distinguish true drug-induced changes from system variance in longitudinal trials. The sample consisted of 20 participants with PD and 19 HVs. Two independent teams analyzed the data to compare the volume of distribution calculated using image-derived input functions (IDIFs), and binding potentials calculated using the Logan reference region model. With all methods, the higher signal-to-background in patients resulted in lower variability and better repeatability than in controls. We were able to use noninvasive techniques showing significantly increased uptake of PK in multiple brain regions of participants with PD compared to HVs. Although not necessarily reflecting absolute values, these noninvasive image analysis methods can discriminate between PD patients and HVs. We see a difference of 24% in the substantia nigra between PD and HV with a repeatability coefficient of 13%, showing that it will be possible to estimate responses in longitudinal, within subject trials of novel neuroprotective drugs. © 2018 The Authors. Journal of Neuroimaging published by Wiley Periodicals, Inc. on behalf of American Society of Neuroimaging.
Neuroimaging in human MDMA (Ecstasy) users: A cortical model
Cowan, Ronald L; Roberts, Deanne M; Joers, James M
2009-01-01
MDMA (3,4 methylenedioxymethamphetamine) has been used by millions of people worldwide as a recreational drug. MDMA and Ecstasy are often used synonymously but it is important to note that the purity of Ecstasy sold as MDMA is not certain. MDMA use is of public health concern, not so much because MDMA produces a common or severe dependence syndrome, but rather because rodent and non-human primate studies have indicated that MDMA (when administered at certain dosages and intervals) can cause long-lasting reductions in markers of brain serotonin (5-HT) that appear specific to fine diameter axons arising largely from the dorsal raphe nucleus (DR). Given the popularity of MDMA, the potential for the drug to produce long-lasting or permanent 5-HT axon damage or loss, and the widespread role of 5-HT function in the brain, there is a great need for a better understanding of brain function in human users of this drug. To this end, neuropsychological, neuroendocrine, and neuroimaging studies have all suggested that human MDMA users may have long-lasting changes in brain function consistent with 5-HT toxicity. Data from animal models leads to testable hypotheses regarding MDMA effects on the human brain. Because neuropsychological and neuroimaging findings have focused on the neocortex, a cortical model is developed to provide context for designing and interpreting neuroimaging studies in MDMA users. Aspects of the model are supported by the available neuroimaging data but there are controversial findings in some areas and most findings have not been replicated across different laboratories and using different modalities. This paper reviews existing findings in the context of a cortical model and suggests directions for future research. PMID:18991874
Neuroimaging in human MDMA (Ecstasy) users.
Cowan, Ronald L; Roberts, Deanne M; Joers, James M
2008-10-01
MDMA (3,4 methylenedioxymethamphetamine) has been used by millions of people worldwide as a recreational drug. The terms "MDMA" and "Ecstasy" are often used synonymously, but it is important to note that the purity of Ecstasy sold as MDMA is not certain. MDMA use is of public health concern, not so much because MDMA produces a common or severe dependence syndrome, but rather because rodent and nonhuman primate studies have indicated that MDMA (when administered at certain dosages and intervals) can cause long-lasting reductions in markers of brain serotonin (5-HT) that appear specific to fine-diameter axons arising largely from the dorsal raphe nucleus (DR). Given the popularity of MDMA, the potential for the drug to produce long-lasting or permanent 5-HT axon damage or loss, and the widespread role of 5-HT function in the brain, there is a great need for a better understanding of brain function in human users of this drug. To this end, neuropsychological, neuroendocrine, and neuroimaging studies have all suggested that human MDMA users may have long-lasting changes in brain function consistent with 5-HT toxicity. Data from animal models leads to testable hypotheses regarding MDMA's effects on the human brain. Because neuropsychological and neuroimaging findings have focused on the neocortex, a cortical model is developed to provide a context for designing and interpreting neuroimaging studies in MDMA users. Aspects of the model are supported by the available neuroimaging data, but there are controversial findings in some areas and most findings have not been replicated across different laboratories and using different modalities. This paper reviews existing findings in the context of a cortical model and suggests directions for future research.
Traumatic brain injury: future assessment tools and treatment prospects
Flanagan, Steven R; Cantor, Joshua B; Ashman, Teresa A
2008-01-01
Traumatic brain injury (TBI) is widespread and leads to death and disability in millions of individuals around the world each year. Overall incidence and prevalence of TBI are likely to increase in absolute terms in the future. Tackling the problem of treating TBI successfully will require improvements in the understanding of normal cerebral anatomy, physiology, and function throughout the lifespan, as well as the pathological and recuperative responses that result from trauma. New treatment approaches and combinations will need to be targeted to the heterogeneous needs of TBI populations. This article explores and evaluates the research evidence in areas that will likely lead to a reduction in TBI-related morbidity and improved outcomes. These include emerging assessment instruments and techniques in areas of structural/chemical and functional neuroimaging and neuropsychology, advances in the realms of cell-based therapies and genetics, promising cognitive rehabilitation techniques including cognitive remediation and the use of electronic technologies including assistive devices and virtual reality, and the emerging field of complementary and alternative medicine. PMID:19183780
Burns, Gully A.P.C.; Turner, Jessica A.
2015-01-01
Neuroimaging data is raw material for cognitive neuroscience experiments, leading to scientific knowledge about human neurological and psychological disease, language, perception, attention and ultimately, cognition. The structure of the variables used in the experimental design defines the structure of the data gathered in the experiments; this in turn structures the interpretative assertions that may be presented as experimental conclusions. Representing these assertions and the experimental data which support them in a computable way means that they could be used in logical reasoning environments, i.e. for automated meta-analyses, or linking hypotheses and results across different levels of neuroscientific experiments. Therefore, a crucial first step in being able to represent neuroimaging results in a clear, computable way is to develop representations for the scientific variables involved in neuroimaging experiments. These representations should be expressive, computable, valid, extensible, and easy-to-use. They should also leverage existing semantic standards to interoperate easily with other systems. We present an ontology design pattern called the Ontology of Experimental Variables and Values (OoEVV). This is designed to provide a lightweight framework to capture mathematical properties of data, with appropriate ‘hooks’ to permit linkage to other ontology-driven projects (such as the Ontology of Biomedical Investigations, OBI). We instantiate the OoEVV system with a small number of functional Magnetic Resonance Imaging datasets, to demonstrate the system’s ability to describe the variables of a neuroimaging experiment. OoEVV is designed to be compatible with the XCEDE neuroimaging data standard for data collection terminology, and with the Cognitive Paradigm Ontology (CogPO) for specific reasoning elements of neuroimaging experimental designs. PMID:23684873
Neuroimaging studies of cognitive remediation in schizophrenia: A systematic and critical review
Penadés, Rafael; González-Rodríguez, Alexandre; Catalán, Rosa; Segura, Bàrbara; Bernardo, Miquel; Junqué, Carme
2017-01-01
AIM To examine the effects of cognitive remediation therapies on brain functioning through neuroimaging procedures in patients with schizophrenia. METHODS A systematic, computerised literature search was conducted in the PubMed/Medline and PsychInfo databases. The search was performed through February 2016 without any restrictions on language or publication date. The search was performed using the following search terms: [(“cogniti*” and “remediation” or “training” or “enhancement”) and (“fMRI” or “MRI” or “PET” or “SPECT”) and (schizophrenia or schiz*)]. The search was accompanied by a manual online search and a review of the references from each of the papers selected, and those papers fulfilling our inclusion criteria were also included. RESULTS A total of 101 studies were found, but only 18 of them fulfilled the inclusion criteria. These studies indicated that cognitive remediation improves brain activation in neuroimaging studies. The most commonly reported changes were those that involved the prefrontal and thalamic regions. Those findings are in agreement with the hypofrontality hypothesis, which proposes that frontal hypoactivation is the underlying mechanism of cognitive impairments in schizophrenia. Nonetheless, great heterogeneity among the studies was found. They presented different hypotheses, different results and different findings. The results of more recent studies interpreted cognitive recovery within broader frameworks, namely, as amelioration of the efficiency of different networks. Furthermore, advances in neuroimaging methodologies, such as the use of whole-brain analysis, tractography, graph analysis, and other sophisticated methodologies of data processing, might be conditioning the interpretation of results and generating new theoretical frameworks. Additionally, structural changes were described in both the grey and white matter, suggesting a neuroprotective effect of cognitive remediation. Cognitive, functional and structural improvements tended to be positively correlated. CONCLUSION Neuroimaging studies of cognitive remediation in patients with schizophrenia suggest a positive effect on brain functioning in terms of the functional reorganisation of neural networks. PMID:28401047
Neuroimaging studies of cognitive remediation in schizophrenia: A systematic and critical review.
Penadés, Rafael; González-Rodríguez, Alexandre; Catalán, Rosa; Segura, Bàrbara; Bernardo, Miquel; Junqué, Carme
2017-03-22
To examine the effects of cognitive remediation therapies on brain functioning through neuroimaging procedures in patients with schizophrenia. A systematic, computerised literature search was conducted in the PubMed/Medline and PsychInfo databases. The search was performed through February 2016 without any restrictions on language or publication date. The search was performed using the following search terms: [("cogniti*" and "remediation" or "training" or "enhancement") and ("fMRI" or "MRI" or "PET" or "SPECT") and (schizophrenia or schiz*)]. The search was accompanied by a manual online search and a review of the references from each of the papers selected, and those papers fulfilling our inclusion criteria were also included. A total of 101 studies were found, but only 18 of them fulfilled the inclusion criteria. These studies indicated that cognitive remediation improves brain activation in neuroimaging studies. The most commonly reported changes were those that involved the prefrontal and thalamic regions. Those findings are in agreement with the hypofrontality hypothesis, which proposes that frontal hypoactivation is the underlying mechanism of cognitive impairments in schizophrenia. Nonetheless, great heterogeneity among the studies was found. They presented different hypotheses, different results and different findings. The results of more recent studies interpreted cognitive recovery within broader frameworks, namely, as amelioration of the efficiency of different networks. Furthermore, advances in neuroimaging methodologies, such as the use of whole-brain analysis, tractography, graph analysis, and other sophisticated methodologies of data processing, might be conditioning the interpretation of results and generating new theoretical frameworks. Additionally, structural changes were described in both the grey and white matter, suggesting a neuroprotective effect of cognitive remediation. Cognitive, functional and structural improvements tended to be positively correlated. Neuroimaging studies of cognitive remediation in patients with schizophrenia suggest a positive effect on brain functioning in terms of the functional reorganisation of neural networks.
Recent advances in Tourette syndrome research.
Albin, Roger L; Mink, Jonathan W
2006-03-01
Tourette syndrome (TS) is a developmentally regulated neurobehavioral disorder characterized by involuntary, stereotyped, repetitive movements. Recent anatomical and neuroimaging studies have provided evidence for abnormal basal ganglia and dopaminergic function in TS. Basic research on striatal inhibitory mechanisms and dopaminergic function complements the recent neuroimaging and anatomical data. Parallel studies of basal ganglia participation in the normal performance and learning of stereotyped repetitive behaviors or habits has provided additional insight. These lines of research have provided new pieces to the TS puzzle, and their increasing convergence is showing how those pieces can be put together.
Chronic disorders of consciousness: role of neuroimaging
NASA Astrophysics Data System (ADS)
Kremneva, E.; Sergeev, D.; Zmeykina, E.; Legostaeva, L.; Piradov, M.
2017-08-01
Chronic disorders of consciousness are clinically challenging conditions, and advanced methods of imaging for better understanding of diagnosis and prognosis are needed. Recent functional neuroradiological studies utilizing PET and fMRI demonstrated that besides widespread neuronal loss disruption of interconnection between certain cortical networks after the injury may also play the leading role in the development of behaviourally assessed unresponsiveness. Functional and structural connectivity, evaluated by neuroimaging approaches, may correlate with clinical status and may also play prognostic role. Integration of data from various diagnostic modalities is needed for further progress in this area.
Autistic Traits and Brain Activation during Face-to-Face Conversations in Typically Developed Adults
Suda, Masashi; Takei, Yuichi; Aoyama, Yoshiyuki; Narita, Kosuke; Sakurai, Noriko; Fukuda, Masato; Mikuni, Masahiko
2011-01-01
Background Autism spectrum disorders (ASD) are characterized by impaired social interaction and communication, restricted interests, and repetitive behaviours. The severity of these characteristics is posited to lie on a continuum that extends into the general population. Brain substrates underlying ASD have been investigated through functional neuroimaging studies using functional magnetic resonance imaging (fMRI). However, fMRI has methodological constraints for studying brain mechanisms during social interactions (for example, noise, lying on a gantry during the procedure, etc.). In this study, we investigated whether variations in autism spectrum traits are associated with changes in patterns of brain activation in typically developed adults. We used near-infrared spectroscopy (NIRS), a recently developed functional neuroimaging technique that uses near-infrared light, to monitor brain activation in a natural setting that is suitable for studying brain functions during social interactions. Methodology We monitored regional cerebral blood volume changes using a 52-channel NIRS apparatus over the prefrontal cortex (PFC) and superior temporal sulcus (STS), 2 areas implicated in social cognition and the pathology of ASD, in 28 typically developed participants (14 male and 14 female) during face-to-face conversations. This task was designed to resemble a realistic social situation. We examined the correlations of these changes with autistic traits assessed using the Autism-Spectrum Quotient (AQ). Principal Findings Both the PFC and STS were significantly activated during face-to-face conversations. AQ scores were negatively correlated with regional cerebral blood volume increases in the left STS during face-to-face conversations, especially in males. Conclusions Our results demonstrate successful monitoring of brain function during realistic social interactions by NIRS as well as lesser brain activation in the left STS during face-to-face conversations in typically developed participants with higher levels of autistic traits. PMID:21637754
Suda, Masashi; Takei, Yuichi; Aoyama, Yoshiyuki; Narita, Kosuke; Sakurai, Noriko; Fukuda, Masato; Mikuni, Masahiko
2011-01-01
Autism spectrum disorders (ASD) are characterized by impaired social interaction and communication, restricted interests, and repetitive behaviours. The severity of these characteristics is posited to lie on a continuum that extends into the general population. Brain substrates underlying ASD have been investigated through functional neuroimaging studies using functional magnetic resonance imaging (fMRI). However, fMRI has methodological constraints for studying brain mechanisms during social interactions (for example, noise, lying on a gantry during the procedure, etc.). In this study, we investigated whether variations in autism spectrum traits are associated with changes in patterns of brain activation in typically developed adults. We used near-infrared spectroscopy (NIRS), a recently developed functional neuroimaging technique that uses near-infrared light, to monitor brain activation in a natural setting that is suitable for studying brain functions during social interactions. We monitored regional cerebral blood volume changes using a 52-channel NIRS apparatus over the prefrontal cortex (PFC) and superior temporal sulcus (STS), 2 areas implicated in social cognition and the pathology of ASD, in 28 typically developed participants (14 male and 14 female) during face-to-face conversations. This task was designed to resemble a realistic social situation. We examined the correlations of these changes with autistic traits assessed using the Autism-Spectrum Quotient (AQ). Both the PFC and STS were significantly activated during face-to-face conversations. AQ scores were negatively correlated with regional cerebral blood volume increases in the left STS during face-to-face conversations, especially in males. Our results demonstrate successful monitoring of brain function during realistic social interactions by NIRS as well as lesser brain activation in the left STS during face-to-face conversations in typically developed participants with higher levels of autistic traits.
Structural, functional and spectroscopic MRI studies of methamphetamine addiction.
Salo, Ruth; Fassbender, Catherine
2012-01-01
This chapter reviews selected neuroimaging findings related to long-term amphetamine and methamphetamine (MA) use. An overview of structural and functional (fMRI) MR studies, Diffusion Tensor Imaging (DTI), Magnetic Resonance Spectroscopy (MRS) and Positron Emission Tomography (PET) studies conducted in long-term MA abusers is presented. The focus of this chapter is to present the relevant studies as tools to understand brain changes following drug abstinence and recovery from addiction. The behavioral relevance of these neuroimaging studies is discussed as they relate to clinical symptoms and treatment. Within each imaging section this chapter includes a discussion of the relevant imaging studies as they relate to patterns of drug use (i.e., duration of MA use, cumulative lifetime dose and time MA abstinent) as well as an overview of studies that link the imaging findings to cognitive measures. In our conclusion we discuss some of the future directions of neuroimaging as it relates to the pathophysiology of addiction.
Functional neuroimaging studies in addiction: multisensory drug stimuli and neural cue reactivity.
Yalachkov, Yavor; Kaiser, Jochen; Naumer, Marcus J
2012-02-01
Neuroimaging studies on cue reactivity have substantially contributed to the understanding of addiction. In the majority of studies drug cues were presented in the visual modality. However, exposure to conditioned cues in real life occurs often simultaneously in more than one sensory modality. Therefore, multisensory cues should elicit cue reactivity more consistently than unisensory stimuli and increase the ecological validity and the reliability of brain activation measurements. This review includes the data from 44 whole-brain functional neuroimaging studies with a total of 1168 subjects (812 patients and 356 controls). Correlations between neural cue reactivity and clinical covariates such as craving have been reported significantly more often for multisensory than unisensory cues in the motor cortex, insula and posterior cingulate cortex. Thus, multisensory drug cues are particularly effective in revealing brain-behavior relationships in neurocircuits of addiction responsible for motivation, craving awareness and self-related processing. Copyright © 2011 Elsevier Ltd. All rights reserved.
Isaacs, Elizabeth B.
2013-01-01
Nutrition is crucial to the initial development of the central nervous system (CNS), and then to its maintenance, because both depend on dietary intake to supply the elements required to develop and fuel the system. Diet in early life is often seen in the context of “programming” where a stimulus occurring during a vulnerable period can have long-lasting or even lifetime effects on some aspect of the organism's structure or function. Nutrition was first shown to be a programming stimulus for growth, and then for cognitive behavior, in animal studies that were able to employ methods that allowed the demonstration of neural effects of early nutrition. Such research raised the question of whether nutrition could also programme cognition/brain structure in humans. Initial studies of cognitive effects were observational, usually conducted in developing countries where the presence of confounding factors made it difficult to interpret the role of nutrition in the cognitive deficits that were seen. Attributing causality to nutrition required randomized controlled trials (RCTs) and these, often in developed countries, started to appear around 30 years ago. Most demonstrated convincingly that early nutrition could affect subsequent cognition. Until the advent of neuroimaging techniques that allowed in vivo examination of the brain, however, we could determine very little about the neural effects of early diet in humans. The combination of well-designed trials with neuroimaging tools means that we are now able to pose and answer questions that would have seemed impossible only recently. This review discusses various neuroimaging methods that are suitable for use in nutrition studies, while pointing out some of the limitations that they may have. The existing literature is small, but examples of studies that have used these methods are presented. Finally, some considerations that have arisen from previous studies, as well as suggestions for future research, are discussed. PMID:23964224
Predicting Violent Behavior: What Can Neuroscience Add?
Poldrack, Russell A; Monahan, John; Imrey, Peter B; Reyna, Valerie; Raichle, Marcus E; Faigman, David; Buckholtz, Joshua W
2018-02-01
The ability to accurately predict violence and other forms of serious antisocial behavior would provide important societal benefits, and there is substantial enthusiasm for the potential predictive accuracy of neuroimaging techniques. Here, we review the current status of violence prediction using actuarial and clinical methods, and assess the current state of neuroprediction. We then outline several questions that need to be addressed by future studies of neuroprediction if neuroimaging and other neuroscientific markers are to be successfully translated into public policy. Copyright © 2017 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Newberg, A. B.; Alavi, A.
The purpose of this paper is to review the potential functional and morphological effects of long duration space flight on the human central nervous system (CNS) and how current neuroimaging techniques may be utilized to study these effects. It must be determined if there will be any detrimental changes to the CNS from long term exposure to the space environment if human beings are to plan interplanetary missions or establish permanent space habitats. Research to date has focused primarily on the short term changes in the CNS as the result of space flight. The space environment has many factors such as weightlessness, electromagnetic fields, and radiation, that may impact upon the function and structure of the CNS. CNS changes known to occur during and after long term space flight include neurovestibular disturbances, cephalic fluid shifts, alterations in sensory perception, changes in proprioception, psychological disturbances, and cognitive changes. Animal studies have shown altered plasticity of the neural cytoarchitecture, decreased neuronal metabolism in the hypothalamus, and changes in neurotransmitter concentrations. Recent progress in the ability to study brain morphology, cerebral metabolism, and neurochemistry in vivo in the human brain would provide ample opportunity to investigate many of the changes that occur in the CNS as a result of space flight. These methods include positron emission tomography (PET), single photon emission computed tomography (SPECT), and magnetic resonance imaging (MRI).
The use of near-infrared spectroscopy in the study of typical and atypical development
Vanderwert, Ross E.; Nelson, Charles A.
2014-01-01
The use of functional Near Infrared Spectroscopy (fNIRS) has grown exponentially over the past decade, particularly among investigators interested in early brain development. The use of this neuroimaging technique has begun to shed light on the development of a variety of sensory, perceptual, linguistic, and social-cognitive functions. Rather than cast a wide net, in this paper we first discuss typical development, focusing on joint attention, face processing, language, and sensorimotor development. We then turn our attention to infants and children whose development has been compromised or who are at risk for atypical development. We conclude our review by critiquing some of the methodological issues that have plagued the extant literature as well as offer suggestions for future research. PMID:24128733
Plasticity following early-life brain injury: Insights from quantitative MRI.
Fiori, Simona; Guzzetta, Andrea
2015-03-01
Over the last decade, the application of novel advanced neuroimaging techniques to study congenital brain damage has provided invaluable insights into the mechanisms underlying early neuroplasticity. The concept that is clearly emerging, both from human and nun-human studies, is that functional reorganization in the immature brain is substantially different from that of the more mature, developed brain. This applies to the reorganization of language, the sensorimotor system, and the visual system. The rapid implementation and development of higher order imaging methods will offer increased, currently unavailable knowledge about the specific mechanisms of cerebral plasticity in infancy, which is essential to support the development of early therapeutic interventions aimed at supporting and enhancing functional reorganization during a time of greatest potential brain plasticity. Copyright © 2015. Published by Elsevier Inc.
Using brain stimulation to disentangle neural correlates of conscious vision
de Graaf, Tom A.; Sack, Alexander T.
2014-01-01
Research into the neural correlates of consciousness (NCCs) has blossomed, due to the advent of new and increasingly sophisticated brain research tools. Neuroimaging has uncovered a variety of brain processes that relate to conscious perception, obtained in a range of experimental paradigms. But methods such as functional magnetic resonance imaging or electroencephalography do not always afford inference on the functional role these brain processes play in conscious vision. Such empirical NCCs could reflect neural prerequisites, neural consequences, or neural substrates of a conscious experience. Here, we take a closer look at the use of non-invasive brain stimulation (NIBS) techniques in this context. We discuss and review how NIBS methodology can enlighten our understanding of brain mechanisms underlying conscious vision by disentangling the empirical NCCs. PMID:25295015
García-Campayo, Javier; Fayed, Nicolas; Serrano-Blanco, Antoni; Roca, Miquel
2009-03-01
Neuroimaging research in psychiatry has been increasing exponentially in recent years, yet many psychiatrists are relatively unfamiliar with this field. This article summarizes the findings of the most relevant research articles on the neuroimaging of somatoform, conversive, and dissociative disorders published from January 2007 through June 2008. Neuroimaging findings summarized here include alterations of stress regulation and coping in somatoform pain disorders, the importance of catastrophizing in somatization disorder, and the relevance of a history of physical/sexual abuse in irritable bowel syndrome. Regarding fibromyalgia, three of the most significant advances have been the impossibility of differentiating primary and concomitant fibromyalgia in the presence of quiescent underlying disease, the role of hippocampal dysfunction, and the possibility that fibromyalgia may be characterized as an aging process. In dissociative disorders, the high levels of elaborative memory encoding and the reduced size of the parietal lobe are highlighted. The most promising clinical consequence of these studies, in addition to improving knowledge about the etiology of these illnesses, is the possibility of using neuroimaging findings to identify subgroups of patients, which could allow treatments to be tailored.
Emotion and Theory of Mind in Schizophrenia-Investigating the Role of the Cerebellum.
Mothersill, Omar; Knee-Zaska, Charlotte; Donohoe, Gary
2016-06-01
Social cognitive dysfunction, including deficits in facial emotion recognition and theory of mind, is a core feature of schizophrenia and more strongly predicts functional outcome than neurocognition alone. Although traditionally considered to play an important role in motor coordination, the cerebellum has been suggested to play a role in emotion processing and theory of mind, and also shows structural and functional abnormalities in schizophrenia. The aim of this systematic review was to investigate the specific role of the cerebellum in emotion and theory of mind deficits in schizophrenia using previously published functional neuroimaging studies. PubMed and PsycINFO were used to search for all functional neuroimaging studies reporting altered cerebellum activity in schizophrenia patients during emotion processing or theory of mind tasks, published until December 2014. Overall, 14 functional neuroimaging studies were retrieved. Most emotion studies reported lower cerebellum activity in schizophrenia patients relative to healthy controls. In contrast, the theory of mind studies reported mixed findings. Altered activity was observed across several posterior cerebellar regions involved in emotion and cognition. Weaker cerebellum activity in schizophrenia patients relative to healthy controls during emotion processing may contribute to blunted affect and reduced ability to recognise emotion in others. This research could be expanded by examining the relationship between cerebellum function, symptomatology and behaviour, and examining cerebellum functional connectivity in patients during emotion and theory of mind tasks.
The Co-evolution of Neuroimaging and Psychiatric Neurosurgery.
Dyster, Timothy G; Mikell, Charles B; Sheth, Sameer A
2016-01-01
The role of neuroimaging in psychiatric neurosurgery has evolved significantly throughout the field's history. Psychiatric neurosurgery initially developed without the benefit of information provided by modern imaging modalities, and thus lesion targets were selected based on contemporary theories of frontal lobe dysfunction in psychiatric disease. However, by the end of the 20th century, the availability of structural and functional magnetic resonance imaging (fMRI) allowed for the development of mechanistic theories attempting to explain the anatamofunctional basis of these disorders, as well as the efficacy of stereotactic neuromodulatory treatments. Neuroimaging now plays a central and ever-expanding role in the neurosurgical management of psychiatric disorders, by influencing the determination of surgical candidates, allowing individualized surgical targeting and planning, and identifying network-level changes in the brain following surgery. In this review, we aim to describe the coevolution of psychiatric neurosurgery and neuroimaging, including ways in which neuroimaging has proved useful in elucidating the therapeutic mechanisms of neuromodulatory procedures. We focus on ablative over stimulation-based procedures given their historical precedence and the greater opportunity they afford for post-operative re-imaging, but also discuss important contributions from the deep brain stimulation (DBS) literature. We conclude with a discussion of how neuroimaging will transition the field of psychiatric neurosurgery into the era of precision medicine.
Gamma knife radiosurgery in movement disorders: Indications and limitations.
Higuchi, Yoshinori; Matsuda, Shinji; Serizawa, Toru
2017-01-01
Functional radiosurgery has advanced steadily during the past half century since the development of the gamma knife technique for treating intractable cancer pain. Applications of radiosurgery for intracranial diseases have increased with a focus on understanding radiobiology. Currently, the use of gamma knife radiosurgery to ablate deep brain structures is not widespread because visualization of the functional targets remains difficult despite the increased availability of advanced neuroimaging technology. Moreover, most existing reports have a small sample size or are retrospective. However, increased experience with intraoperative neurophysiological evaluations in radiofrequency thalamotomy and deep brain stimulation supports anatomical and neurophysiological approaches to the ventralis intermedius nucleus. Two recent prospective studies have promoted the clinical application of functional radiosurgery for movement disorders. For example, unilateral gamma knife thalamotomy is a potential alternative to radiofrequency thalamotomy and deep brain stimulation techniques for intractable tremor patients with contraindications for surgery. Despite the promising efficacy of gamma knife thalamotomy, however, these studies did not include sufficient follow-up to confirm long-term effects. Herein, we review the radiobiology literature, various techniques, and the treatment efficacy of gamma knife radiosurgery for patients with movement disorders. Future research should focus on randomized controlled studies and long-term effects. © 2016 International Parkinson and Movement Disorder Society. © 2016 International Parkinson and Movement Disorder Society.
GPU Accelerated Browser for Neuroimaging Genomics.
Zigon, Bob; Li, Huang; Yao, Xiaohui; Fang, Shiaofen; Hasan, Mohammad Al; Yan, Jingwen; Moore, Jason H; Saykin, Andrew J; Shen, Li
2018-04-25
Neuroimaging genomics is an emerging field that provides exciting opportunities to understand the genetic basis of brain structure and function. The unprecedented scale and complexity of the imaging and genomics data, however, have presented critical computational bottlenecks. In this work we present our initial efforts towards building an interactive visual exploratory system for mining big data in neuroimaging genomics. A GPU accelerated browsing tool for neuroimaging genomics is created that implements the ANOVA algorithm for single nucleotide polymorphism (SNP) based analysis and the VEGAS algorithm for gene-based analysis, and executes them at interactive rates. The ANOVA algorithm is 110 times faster than the 4-core OpenMP version, while the VEGAS algorithm is 375 times faster than its 4-core OpenMP counter part. This approach lays a solid foundation for researchers to address the challenges of mining large-scale imaging genomics datasets via interactive visual exploration.
Zhu, Xiao-Hong; Lu, Ming; Chen, Wei
2018-07-01
Brain energy metabolism relies predominantly on glucose and oxygen utilization to generate biochemical energy in the form of adenosine triphosphate (ATP). ATP is essential for maintaining basal electrophysiological activities in a resting brain and supporting evoked neuronal activity under an activated state. Studying complex neuroenergetic processes in the brain requires sophisticated neuroimaging techniques enabling noninvasive and quantitative assessment of cerebral energy metabolisms and quantification of metabolic rates. Recent state-of-the-art in vivo X-nuclear MRS techniques, including 2 H, 17 O and 31 P MRS have shown promise, especially at ultra-high fields, in the quest for understanding neuroenergetics and brain function using preclinical models and in human subjects under healthy and diseased conditions. Copyright © 2018 Elsevier Inc. All rights reserved.
Neuroimaging in attention-deficit hyperactivity disorder: beyond the frontostriatal circuitry.
Cherkasova, Mariya V; Hechtman, Lily
2009-10-01
To review the findings of structural and functional neuroimaging studies in attention-deficit hyperactivity disorder (ADHD), with a focus on abnormalities reported in brain regions that lie outside the frontostriatal circuitry, which is currently believed to play a central role in the pathophysiology of ADHD. Relevant publications were found primarily by searching the MEDLINE and PubMed databases using the keywords ADHD and the abbreviations of magnetic resonance imaging (MRI), functional MRI, positron emission tomography, and single photon emission computed tomography. The reference lists of the articles found through the databases were then reviewed for the purpose of finding additional articles. There is now substantial evidence of structural and functional alterations in regions outside the frontostriatal circuitry in ADHD, most notably in the cerebellum and the parietal lobes. Although there is compelling evidence suggesting that frontostriatal dysfunction may be central to the pathophysiology of ADHD, the neuroimaging findings point to distributed neural substrates rather than a single one. More research is needed to elucidate the nature of contributions of nonfrontostriatal regions to the pathophysiology of ADHD.
In vivo optoacoustic monitoring of calcium activity in the brain (Conference Presentation)
NASA Astrophysics Data System (ADS)
Deán-Ben, Xose Luís.; Gottschalk, Sven; Sela, Gali; Lauri, Antonella; Kneipp, Moritz; Ntziachristos, Vasilis; Westmeyer, Gil G.; Shoham, Shy; Razansky, Daniel
2017-03-01
Non-invasive observation of spatio-temporal neural activity of large neural populations distributed over the entire brain of complex organisms is a longstanding goal of neuroscience [1,2]. Recently, genetically encoded calcium indicators (GECIs) have revolutionized neuroimaging by enabling mapping the activity of entire neuronal populations in vivo [3]. Visualization of these powerful sensors with fluorescence microscopy has however been limited to superficial regions while deep brain areas have so far remained unreachable [4]. We have developed a volumetric multispectral optoacoustic tomography platform for imaging neural activation deep in scattering brains [5]. The developed methodology can render 100 volumetric frames per second across scalable fields of view ranging between 50-1000 mm3 with respective spatial resolution of 35-150µm. Experiments performed in immobilized and freely swimming larvae and in adult zebrafish brains expressing the genetically-encoded calcium indicator GCaMP5G demonstrated, for the first time, the fundamental ability to directly track neural dynamics using optoacoustics while overcoming the depth barrier of optical imaging in scattering brains [6]. It was further possible to monitor calcium transients in a scattering brain of a living adult transgenic zebrafish expressing GCaMP5G calcium indicator [7]. Fast changes in optoacoustic traces associated to GCaMP5G activity were detectable in the presence of other strongly absorbing endogenous chromophores, such as hemoglobin. The results indicate that the optoacoustic signal traces generally follow the GCaMP5G fluorescence dynamics and further enable overcoming the longstanding optical-diffusion penetration barrier associated to scattering in biological tissues [6]. The new functional optoacoustic neuroimaging method can visualize neural activity at penetration depths and spatio-temporal resolution scales not covered with the existing neuroimaging techniques. Thus, in addition to the well-established capacity of optoacoustics to resolve vascular anatomy and multiple hemodynamic parameters deep in scattering tissues, the newly developed methodology offers unprecedented capabilities for functional whole brain observations of fast calcium dynamics.
Hall, Deborah A; Guest, Hannah; Prendergast, Garreth; Plack, Christopher J; Francis, Susan T
2018-01-01
Background Rodent studies indicate that noise exposure can cause permanent damage to synapses between inner hair cells and high-threshold auditory nerve fibers, without permanently altering threshold sensitivity. These demonstrations of what is commonly known as hidden hearing loss have been confirmed in several rodent species, but the implications for human hearing are unclear. Objective Our Medical Research Council–funded program aims to address this unanswered question, by investigating functional consequences of the damage to the human peripheral and central auditory nervous system that results from cumulative lifetime noise exposure. Behavioral and neuroimaging techniques are being used in a series of parallel studies aimed at detecting hidden hearing loss in humans. The planned neuroimaging study aims to (1) identify central auditory biomarkers associated with hidden hearing loss; (2) investigate whether there are any additive contributions from tinnitus or diminished sound tolerance, which are often comorbid with hearing problems; and (3) explore the relation between subcortical functional magnetic resonance imaging (fMRI) measures and the auditory brainstem response (ABR). Methods Individuals aged 25 to 40 years with pure tone hearing thresholds ≤20 dB hearing level over the range 500 Hz to 8 kHz and no contraindications for MRI or signs of ear disease will be recruited into the study. Lifetime noise exposure will be estimated using an in-depth structured interview. Auditory responses throughout the central auditory system will be recorded using ABR and fMRI. Analyses will focus predominantly on correlations between lifetime noise exposure and auditory response characteristics. Results This paper reports the study protocol. The funding was awarded in July 2013. Enrollment for the study described in this protocol commenced in February 2017 and was completed in December 2017. Results are expected in 2018. Conclusions This challenging and comprehensive study will have the potential to impact diagnostic procedures for hidden hearing loss, enabling early identification of noise-induced auditory damage via the detection of changes in central auditory processing. Consequently, this will generate the opportunity to give personalized advice regarding provision of ear defense and monitoring of further damage, thus reducing the incidence of noise-induced hearing loss. PMID:29523503
Cagnin, Annachiara; Bandmann, Oliver; Venneri, Annalena
2017-01-01
Patients with Lewy body disease (LBD) frequently experience visual hallucinations (VH), well-formed images perceived without the presence of real stimuli. The structural and functional brain mechanisms underlying VH in LBD are still unclear. The present review summarises the current literature on the neural correlates of VH in LBD, namely Parkinson’s disease (PD), and dementia with Lewy bodies (DLB). Following a systematic literature search, 56 neuroimaging studies of VH in PD and DLB were critically reviewed and evaluated for quality assessment. The main structural neuroimaging results on VH in LBD revealed grey matter loss in frontal areas in patients with dementia, and parietal and occipito-temporal regions in PD without dementia. Parietal and temporal hypometabolism was also reported in hallucinating PD patients. Disrupted functional connectivity was detected especially in the default mode network and fronto-parietal regions. However, evidence on structural and functional connectivity is still limited and requires further investigation. The current literature is in line with integrative models of VH suggesting a role of attention and perception deficits in the development of VH. However, despite the close relationship between VH and cognitive impairment, its associations with brain structure and function have been explored only by a limited number of studies. PMID:28714891
Northwestern University Schizophrenia Data and Software Tool (NUSDAST)
Wang, Lei; Kogan, Alex; Cobia, Derin; Alpert, Kathryn; Kolasny, Anthony; Miller, Michael I.; Marcus, Daniel
2013-01-01
The schizophrenia research community has invested substantial resources on collecting, managing and sharing large neuroimaging datasets. As part of this effort, our group has collected high resolution magnetic resonance (MR) datasets from individuals with schizophrenia, their non-psychotic siblings, healthy controls and their siblings. This effort has resulted in a growing resource, the Northwestern University Schizophrenia Data and Software Tool (NUSDAST), an NIH-funded data sharing project to stimulate new research. This resource resides on XNAT Central, and it contains neuroimaging (MR scans, landmarks and surface maps for deep subcortical structures, and FreeSurfer cortical parcellation and measurement data), cognitive (cognitive domain scores for crystallized intelligence, working memory, episodic memory, and executive function), clinical (demographic, sibling relationship, SAPS and SANS psychopathology), and genetic (20 polymorphisms) data, collected from more than 450 subjects, most with 2-year longitudinal follow-up. A neuroimaging mapping, analysis and visualization software tool, CAWorks, is also part of this resource. Moreover, in making our existing neuroimaging data along with the associated meta-data and computational tools publically accessible, we have established a web-based information retrieval portal that allows the user to efficiently search the collection. This research-ready dataset meaningfully combines neuroimaging data with other relevant information, and it can be used to help facilitate advancing neuroimaging research. It is our hope that this effort will help to overcome some of the commonly recognized technical barriers in advancing neuroimaging research such as lack of local organization and standard descriptions. PMID:24223551
Northwestern University Schizophrenia Data and Software Tool (NUSDAST).
Wang, Lei; Kogan, Alex; Cobia, Derin; Alpert, Kathryn; Kolasny, Anthony; Miller, Michael I; Marcus, Daniel
2013-01-01
The schizophrenia research community has invested substantial resources on collecting, managing and sharing large neuroimaging datasets. As part of this effort, our group has collected high resolution magnetic resonance (MR) datasets from individuals with schizophrenia, their non-psychotic siblings, healthy controls and their siblings. This effort has resulted in a growing resource, the Northwestern University Schizophrenia Data and Software Tool (NUSDAST), an NIH-funded data sharing project to stimulate new research. This resource resides on XNAT Central, and it contains neuroimaging (MR scans, landmarks and surface maps for deep subcortical structures, and FreeSurfer cortical parcellation and measurement data), cognitive (cognitive domain scores for crystallized intelligence, working memory, episodic memory, and executive function), clinical (demographic, sibling relationship, SAPS and SANS psychopathology), and genetic (20 polymorphisms) data, collected from more than 450 subjects, most with 2-year longitudinal follow-up. A neuroimaging mapping, analysis and visualization software tool, CAWorks, is also part of this resource. Moreover, in making our existing neuroimaging data along with the associated meta-data and computational tools publically accessible, we have established a web-based information retrieval portal that allows the user to efficiently search the collection. This research-ready dataset meaningfully combines neuroimaging data with other relevant information, and it can be used to help facilitate advancing neuroimaging research. It is our hope that this effort will help to overcome some of the commonly recognized technical barriers in advancing neuroimaging research such as lack of local organization and standard descriptions.
Asymmetries of the human social brain in the visual, auditory and chemical modalities.
Brancucci, Alfredo; Lucci, Giuliana; Mazzatenta, Andrea; Tommasi, Luca
2009-04-12
Structural and functional asymmetries are present in many regions of the human brain responsible for motor control, sensory and cognitive functions and communication. Here, we focus on hemispheric asymmetries underlying the domain of social perception, broadly conceived as the analysis of information about other individuals based on acoustic, visual and chemical signals. By means of these cues the brain establishes the border between 'self' and 'other', and interprets the surrounding social world in terms of the physical and behavioural characteristics of conspecifics essential for impression formation and for creating bonds and relationships. We show that, considered from the standpoint of single- and multi-modal sensory analysis, the neural substrates of the perception of voices, faces, gestures, smells and pheromones, as evidenced by modern neuroimaging techniques, are characterized by a general pattern of right-hemispheric functional asymmetry that might benefit from other aspects of hemispheric lateralization rather than constituting a true specialization for social information.
Electrophysiological Source Imaging: A Noninvasive Window to Brain Dynamics.
He, Bin; Sohrabpour, Abbas; Brown, Emery; Liu, Zhongming
2018-06-04
Brain activity and connectivity are distributed in the three-dimensional space and evolve in time. It is important to image brain dynamics with high spatial and temporal resolution. Electroencephalography (EEG) and magnetoencephalography (MEG) are noninvasive measurements associated with complex neural activations and interactions that encode brain functions. Electrophysiological source imaging estimates the underlying brain electrical sources from EEG and MEG measurements. It offers increasingly improved spatial resolution and intrinsically high temporal resolution for imaging large-scale brain activity and connectivity on a wide range of timescales. Integration of electrophysiological source imaging and functional magnetic resonance imaging could further enhance spatiotemporal resolution and specificity to an extent that is not attainable with either technique alone. We review methodological developments in electrophysiological source imaging over the past three decades and envision its future advancement into a powerful functional neuroimaging technology for basic and clinical neuroscience applications.
Neuroimaging of Central Sensitivity Syndromes: Key Insights from the Scientific Literature
Walitt, Brian; Čeko, Marta; Gracely, John L.; Gracely, Richard H.
2016-01-01
Central sensitivity syndromes are characterized by distressing symptoms, such as pain and fatigue, in the absence of clinically obvious pathology. The scientific underpinnings of these disorders are not currently known. Modern neuroimaging techniques promise new insights into mechanisms mediating these postulated syndromes. We review the results of neuroimaging applied to five central sensitivity syndromes: fibromyalgia, chronic fatigue syndrome, irritable bowel syndrome, temporomandibular joint disorder, and vulvodynia syndrome. Neuroimaging studies of basal metabolism, anatomic constitution, molecular constituents, evoked neural activity, and treatment effect are compared across all of these syndromes. Evoked sensory paradigms reveal sensory augmentation to both painful and non-painful stimulation. This is a transformative observation for these syndromes, which were historically considered to be completely of hysterical or feigned in origin. However, whether sensory augmentation represents the cause of these syndromes, a predisposing factor, an endophenotype, or an epiphenomenon cannot be discerned from the current literature. Further, the result from cross-sectional neuroimaging studies of basal activity, anatomy, and molecular constituency are extremely heterogeneous within and between the syndromes. A defining neuroimaging “signature” cannot be discerned for any of the particular syndromes or for an over-arching central sensitization mechanism common to all of the syndromes. Several issues confound initial attempts to meaningfully measure treatment effects in these syndromes. At this time, the existence of “central sensitivity syndromes” is based more soundly on clinical and epidemiological evidence. A coherent picture of a “central sensitization” mechanism that bridges across all of these syndromes does not emerge from the existing scientific evidence. PMID:26717948
Cocozza, Sirio; Russo, Camilla; Pontillo, Giuseppe; Ugga, Lorenzo; Macera, Antonio; Cervo, Amedeo; De Liso, Maria; Di Paolo, Nilde; Ginocchio, Maria Isabella; Giordano, Flavio; Leone, Giuseppe; Rusconi, Giovanni; Stanzione, Arnaldo; Briganti, Francesco; Quarantelli, Mario; Caranci, Ferdinando; D'Amico, Alessandra; Elefante, Andrea; Tedeschi, Enrico; Brunetti, Arturo
2016-12-01
To evaluate if advanced neuroimaging research is mainly conducted by imaging specialists, we investigated the number of first authorships by radiologists and non-radiologist scientists in articles published in the field of advanced neuroimaging in the past 10 years. Articles in the field of advanced neuroimaging identified in this retrospective bibliometric analysis were divided in four groups, depending on the imaging technique used. For all included studies, educational background of the first authors was recorded (based on available online curriculum vitae) and classified in subgroups, depending on their specialty. Finally, journal impact factors were recorded and comparatively assessed among subgroups as a metric of research quality. A total number of 3831 articles were included in the study. Radiologists accounted as first authors for only 12.8 % of these publications, while 56.9 % of first authors were researchers without a medical degree. Mean impact factor (IF) of journals with non-MD researchers as first authors was significantly higher than the MD subgroup (p < 10 -20 ), while mean IF of journals with radiologists as first authors was significantly lower than articles authored by other MD specialists (p < 10 -11 ). The majority of the studies in the field of advanced neuroimaging in the last decade is conducted by professional figures other than radiologists, who account for less than the 13 % of the publications. Furthermore, the mean IF value of radiologists-authored articles was the lowest among all subgroups. These results, taken together, should question the radiology community about its future role in the development of advanced neuroimaging.
Imaging of Hemorrhagic Stroke.
Hakimi, Ryan; Garg, Ankur
2016-10-01
Hemorrhagic stroke comprises approximately 15% to 20% of all strokes. This article provides readers with an understanding of the indications and significance of various neuroimaging techniques available for patients presenting with hemorrhagic strokes of distinct causes. The most common initial neuroimaging study is a noncontrast head CT, which allows for the identification of hemorrhage. Once an intracranial hemorrhage has been identified, the pattern of blood and the patient's medical history, neurologic examination, and laboratory studies lead the practitioner to pursue further neuroimaging studies to guide the medical, surgical, and interventional management. Given that hemorrhagic stroke constitutes a heterogeneous collection of diagnoses, the subsequent neuroimaging pathway necessary to better evaluate and care for these patients is variable based on the etiology.With an increasing incidence and prevalence of atrial fibrillation associated with the aging population and the introduction of three new direct factor Xa inhibitors and one direct thrombin inhibitor to complement vitamin K antagonists, oral anticoagulant use continues to increase. Patients on oral anticoagulants have a sevenfold to tenfold increased risk for intracerebral hemorrhage (ICH). Furthermore, patients who have an ICH associated with oral anticoagulant use have a higher mortality rate than those with primary ICH. Despite the reduced incidence of hypertension-related ICH over the past decade, it is expected that the incidence of ICH will continue to increase. Neuroimaging studies are integral to the identification of hemorrhagic stroke, determination of the underlying etiology, prevention of hematoma expansion, treatment of acute complications, and treatment of the underlying etiology, if indicated. Neuroimaging is essential for prognostication and thus directly impacts patient care.
Davis, Tyler; Love, Bradley C.; Preston, Alison R.
2012-01-01
Category learning is a complex phenomenon that engages multiple cognitive processes, many of which occur simultaneously and unfold dynamically over time. For example, as people encounter objects in the world, they simultaneously engage processes to determine their fit with current knowledge structures, gather new information about the objects, and adjust their representations to support behavior in future encounters. Many techniques that are available to understand the neural basis of category learning assume that the multiple processes that subserve it can be neatly separated between different trials of an experiment. Model-based functional magnetic resonance imaging offers a promising tool to separate multiple, simultaneously occurring processes and bring the analysis of neuroimaging data more in line with category learning’s dynamic and multifaceted nature. We use model-based imaging to explore the neural basis of recognition and entropy signals in the medial temporal lobe and striatum that are engaged while participants learn to categorize novel stimuli. Consistent with theories suggesting a role for the anterior hippocampus and ventral striatum in motivated learning in response to uncertainty, we find that activation in both regions correlates with a model-based measure of entropy. Simultaneously, separate subregions of the hippocampus and striatum exhibit activation correlated with a model-based recognition strength measure. Our results suggest that model-based analyses are exceptionally useful for extracting information about cognitive processes from neuroimaging data. Models provide a basis for identifying the multiple neural processes that contribute to behavior, and neuroimaging data can provide a powerful test bed for constraining and testing model predictions. PMID:22746951
Internet and gaming addiction: a systematic literature review of neuroimaging studies.
Kuss, Daria J; Griffiths, Mark D
2012-09-05
In the past decade, research has accumulated suggesting that excessive Internet use can lead to the development of a behavioral addiction. Internet addiction has been considered as a serious threat to mental health and the excessive use of the Internet has been linked to a variety of negative psychosocial consequences. The aim of this review is to identify all empirical studies to date that used neuroimaging techniques to shed light upon the emerging mental health problem of Internet and gaming addiction from a neuroscientific perspective. Neuroimaging studies offer an advantage over traditional survey and behavioral research because with this method, it is possible to distinguish particular brain areas that are involved in the development and maintenance of addiction. A systematic literature search was conducted, identifying 18 studies. These studies provide compelling evidence for the similarities between different types of addictions, notably substance-related addictions and Internet and gaming addiction, on a variety of levels. On the molecular level, Internet addiction is characterized by an overall reward deficiency that entails decreased dopaminergic activity. On the level of neural circuitry, Internet and gaming addiction led to neuroadaptation and structural changes that occur as a consequence of prolonged increased activity in brain areas associated with addiction. On a behavioral level, Internet and gaming addicts appear to be constricted with regards to their cognitive functioning in various domains. The paper shows that understanding the neuronal correlates associated with the development of Internet and gaming addiction will promote future research and will pave the way for the development of addiction treatment approaches.
Internet and Gaming Addiction: A Systematic Literature Review of Neuroimaging Studies
Kuss, Daria J.; Griffiths, Mark D.
2012-01-01
In the past decade, research has accumulated suggesting that excessive Internet use can lead to the development of a behavioral addiction. Internet addiction has been considered as a serious threat to mental health and the excessive use of the Internet has been linked to a variety of negative psychosocial consequences. The aim of this review is to identify all empirical studies to date that used neuroimaging techniques to shed light upon the emerging mental health problem of Internet and gaming addiction from a neuroscientific perspective. Neuroimaging studies offer an advantage over traditional survey and behavioral research because with this method, it is possible to distinguish particular brain areas that are involved in the development and maintenance of addiction. A systematic literature search was conducted, identifying 18 studies. These studies provide compelling evidence for the similarities between different types of addictions, notably substance-related addictions and Internet and gaming addiction, on a variety of levels. On the molecular level, Internet addiction is characterized by an overall reward deficiency that entails decreased dopaminergic activity. On the level of neural circuitry, Internet and gaming addiction led to neuroadaptation and structural changes that occur as a consequence of prolonged increased activity in brain areas associated with addiction. On a behavioral level, Internet and gaming addicts appear to be constricted with regards to their cognitive functioning in various domains. The paper shows that understanding the neuronal correlates associated with the development of Internet and gaming addiction will promote future research and will pave the way for the development of addiction treatment approaches. PMID:24961198
Taylor, J S H; Rastle, Kathleen; Davis, Matthew H
2013-07-01
Reading in many alphabetic writing systems depends on both item-specific knowledge used to read irregular words (sew, yacht) and generative spelling-sound knowledge used to read pseudowords (tew, yash). Research into the neural basis of these abilities has been directed largely by cognitive accounts proposed by the dual-route cascaded and triangle models of reading. We develop a framework that enables predictions for neural activity to be derived from cognitive models of reading using 2 principles: (a) the extent to which a model component or brain region is engaged by a stimulus and (b) how much effort is exerted in processing that stimulus. To evaluate the derived predictions, we conducted a meta-analysis of 36 neuroimaging studies of reading using the quantitative activation likelihood estimation technique. Reliable clusters of activity are localized during word versus pseudoword and irregular versus regular word reading and demonstrate a great deal of convergence between the functional organization of the reading system put forward by cognitive models and the neural systems activated during reading tasks. Specifically, left-hemisphere activation clusters are revealed reflecting orthographic analysis (occipitotemporal cortex), lexical and/or semantic processing (anterior fusiform, middle temporal gyrus), spelling-sound conversion (inferior parietal cortex), and phonological output resolution (inferior frontal gyrus). Our framework and results establish that cognitive models of reading are relevant for interpreting neuroimaging studies and that neuroscientific studies can provide data relevant for advancing cognitive models. This article thus provides a firm empirical foundation from which to improve integration between cognitive and neural accounts of the reading process. 2013 APA, all rights reserved
NASA Astrophysics Data System (ADS)
Ancora, Daniele; Zacharopoulos, Athanasios; Ripoll, Jorge; Zacharakis, Giannis
2016-03-01
Optical Neuroimaging is a highly dynamical field of research owing to the combination of many advanced imaging techniques and computational tools that uncovered unexplored paths through the functioning of the brain. Light propagation modelling through such complicated structures has always played a crucial role as the basis for a high resolution and quantitative imaging where even the slightest improvement could lead to significant results. Fluorescence Diffuse Optical Tomography (fDOT), a widely used technique for three dimensional imaging of small animals and tissues, has been proved to be inaccurate for neuroimaging the mouse head without the knowledge of a-priori anatomical information of the subject. Commonly a normalized Born approximation model is used in fDOT reconstruction based on forward photon propagation using Diffusive Equation (DE) which has strong limitations in the optically clear regime. The presence of the Cerebral Spinal Fluid (CSF) instead, a thin optically clear layer surrounding the brain, can be more accurately taken into account using Monte Carlo approaches which nowadays is becoming more usable thanks to parallelized GPU algorithms. In this work we discuss the results of a synthetic experimental comparison, resulting to the increase of the accuracy for the Born approximation by introducing the CSF layer in a realistic mouse head structure with respect to the current model. We point out the importance of such clear layer for complex geometrical models, while for simple slab phantoms neglecting it does not introduce a significant error.
Brain Morphometry using MRI in Schizophrenia Patients
NASA Astrophysics Data System (ADS)
Abanshina, I.; Pirogov, Yu.; Kupriyanov, D.; Orlova, V.
2010-01-01
Schizophrenia has been the focus of intense neuroimaging research. Although its fundamental pathobiology remains elusive, neuroimaging studies provide evidence of abnormalities of cerebral structure and function in patients with schizophrenia. We used morphometry as a quantitative method for estimation of volume of brain structures. Seventy eight right-handed subjects aged 18-45 years were exposed to MRI-examination. Patients were divided into 3 groups: patients with schizophrenia, their relatives and healthy controls. The volumes of interested structures (caudate nucleus, putamen, ventricles, frontal and temporal lobe) were measured using T2-weighted MR-images. Correlations between structural differences and functional deficit were evaluated.
[Conversion disorder : functional neuroimaging and neurobiological mechanisms].
Lejeune, J; Piette, C; Salmon, E; Scantamburlo, G
2017-04-01
Conversion disorder is a psychiatric disorder often encountered in neurology services. This condition without organic lesions was and still is sometimes referred as an imaginary illness or feigning. However, the absence of organic lesions does not exclude the possibility of cerebral dysfunction. The etiologic mechanisms underlying this disorder remain uncertain even today.The advent of cognitive and functional imaging opens up a field of exploration for psychiatry in understanding the neurobiological mechanisms underlying mental disorders and especially the conversion disorder. This article reports several neuroimaging studies of conversion disorder and attempts to generate hypotheses about neurobiological mechanisms.
Mwangi, Benson; Soares, Jair C; Hasan, Khader M
2014-10-30
Neuroimaging machine learning studies have largely utilized supervised algorithms - meaning they require both neuroimaging scan data and corresponding target variables (e.g. healthy vs. diseased) to be successfully 'trained' for a prediction task. Noticeably, this approach may not be optimal or possible when the global structure of the data is not well known and the researcher does not have an a priori model to fit the data. We set out to investigate the utility of an unsupervised machine learning technique; t-distributed stochastic neighbour embedding (t-SNE) in identifying 'unseen' sample population patterns that may exist in high-dimensional neuroimaging data. Multimodal neuroimaging scans from 92 healthy subjects were pre-processed using atlas-based methods, integrated and input into the t-SNE algorithm. Patterns and clusters discovered by the algorithm were visualized using a 2D scatter plot and further analyzed using the K-means clustering algorithm. t-SNE was evaluated against classical principal component analysis. Remarkably, based on unlabelled multimodal scan data, t-SNE separated study subjects into two very distinct clusters which corresponded to subjects' gender labels (cluster silhouette index value=0.79). The resulting clusters were used to develop an unsupervised minimum distance clustering model which identified 93.5% of subjects' gender. Notably, from a neuropsychiatric perspective this method may allow discovery of data-driven disease phenotypes or sub-types of treatment responders. Copyright © 2014 Elsevier B.V. All rights reserved.
Irimia, A.; Goh, S.-Y. M.; Torgerson, C. M.; Vespa, P. M.; Van Horn, J. D.
2014-01-01
The integration of longitudinal brain structure analysis with neurointensive care strategies continues to be a substantial difficulty facing the traumatic brain injury (TBI) research community. For patient-tailored case analysis, it remains challenging to establish how lesion profile modulates longitudinal changes in cortical structure and connectivity, as well as how these changes lead to behavioral, cognitive and neural dysfunction. Additionally, despite the clinical potential of morphometric and connectomic studies, few analytic tools are available for their study in TBI. Here we review the state of the art in structural and connectomic neuroimaging for the study of TBI and illustrate a set of recently-developed, patient-tailored approaches for the study of TBI-related brain atrophy and alterations in morphometry as well as inter-regional connectivity. The ability of such techniques to quantify how injury modulates longitudinal changes in cortical shape, structure and circuitry is highlighted. Quantitative approaches such as these can be used to assess and monitor the clinical condition and evolution of TBI victims, and can have substantial translational impact, especially when used in conjunction with measures of neuropsychological function. PMID:24844173
Minati, L; Ghielmetti, F; Ciobanu, V; D'Incerti, L; Maccagnano, C; Bizzi, A; Bruzzone, M G
2007-03-01
Advanced neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), chemical shift spectroscopy imaging (CSI), diffusion tensor imaging (DTI), and perfusion-weighted imaging (PWI) create novel challenges in terms of data storage and management: huge amounts of raw data are generated, the results of analysis may depend on the software and settings that have been used, and most often intermediate files are inherently not compliant with the current DICOM (digital imaging and communication in medicine) standard, as they contain multidimensional complex and tensor arrays and various other types of data structures. A software architecture, referred to as Bio-Image Warehouse System (BIWS), which can be used alongside a radiology information system/picture archiving and communication system (RIS/PACS) system to store neuroimaging data for research purposes, is presented. The system architecture is conceived with the purpose of enabling to query by diagnosis according to a predefined two-layered classification taxonomy. The operational impact of the system and the time needed to get acquainted with the web-based interface and with the taxonomy are found to be limited. The development of modules enabling automated creation of statistical templates is proposed.
Machine learning patterns for neuroimaging-genetic studies in the cloud.
Da Mota, Benoit; Tudoran, Radu; Costan, Alexandru; Varoquaux, Gaël; Brasche, Goetz; Conrod, Patricia; Lemaitre, Herve; Paus, Tomas; Rietschel, Marcella; Frouin, Vincent; Poline, Jean-Baptiste; Antoniu, Gabriel; Thirion, Bertrand
2014-01-01
Brain imaging is a natural intermediate phenotype to understand the link between genetic information and behavior or brain pathologies risk factors. Massive efforts have been made in the last few years to acquire high-dimensional neuroimaging and genetic data on large cohorts of subjects. The statistical analysis of such data is carried out with increasingly sophisticated techniques and represents a great computational challenge. Fortunately, increasing computational power in distributed architectures can be harnessed, if new neuroinformatics infrastructures are designed and training to use these new tools is provided. Combining a MapReduce framework (TomusBLOB) with machine learning algorithms (Scikit-learn library), we design a scalable analysis tool that can deal with non-parametric statistics on high-dimensional data. End-users describe the statistical procedure to perform and can then test the model on their own computers before running the very same code in the cloud at a larger scale. We illustrate the potential of our approach on real data with an experiment showing how the functional signal in subcortical brain regions can be significantly fit with genome-wide genotypes. This experiment demonstrates the scalability and the reliability of our framework in the cloud with a 2 weeks deployment on hundreds of virtual machines.
Ochoa, John Fredy; Alonso, Joan Francesc; Duque, Jon Edinson; Tobón, Carlos Andrés; Mañanas, Miguel Angel; Lopera, Francisco; Hernández, Alher Mauricio
2016-01-01
Background: Recent studies report increases in neural activity in brain regions critical to episodic memory at preclinical stages of Alzheimer’s disease (AD). Although electroencephalography (EEG) is widely used in AD studies, given its non-invasiveness and low cost, there is a need to translate the findings in other neuroimaging methods to EEG. Objective: To examine how the previous findings using functional magnetic resonance imaging (fMRI) at preclinical stage in presenilin-1 E280A mutation carriers could be assessed and extended, using EEG and a connectivity approach. Methods: EEG signals were acquired during resting and encoding in 30 normal cognitive young subjects, from an autosomal dominant early-onset AD kindred from Antioquia, Colombia. Regions of the brain previously reported as hyperactive were used for connectivity analysis. Results: Mutation carriers exhibited increasing connectivity at analyzed regions. Among them, the right precuneus exhibited the highest changes in connectivity. Conclusion: Increased connectivity in hyperactive cerebral regions is seen in individuals, genetically-determined to develop AD, at preclinical stage. The use of a connectivity approach and a widely available neuroimaging technique opens the possibility to increase the use of EEG in early detection of preclinical AD. PMID:27792014
NASA Astrophysics Data System (ADS)
Gallagher, Anne; Tremblay, Julie; Vannasing, Phetsamone
2016-12-01
Patients with brain tumor or refractory epilepsy may be candidates for neurosurgery. Presurgical evaluation often includes language investigation to prevent or reduce the risk of postsurgical language deficits. Current techniques involve significant limitations with pediatric populations. Recently, near-infrared spectroscopy (NIRS) has been shown to be a valuable neuroimaging technique for language localization in children. However, it typically requires the child to perform a task (task-based NIRS), which may constitute a significant limitation. Resting-state functional connectivity NIRS (fcNIRS) is an approach that can be used to identify language networks at rest. This study aims to assess the utility of fcNIRS in children by comparing fcNIRS to more conventional task-based NIRS for language mapping in 33 healthy participants: 25 children (ages 3 to 16) and 8 adults. Data were acquired at rest and during a language task. Results show very good concordance between both approaches for language localization (Dice similarity coefficient=0.81±0.13) and hemispheric language dominance (kappa=0.86, p<0.006). The fcNIRS technique may be a valuable tool for language mapping in clinical populations, including children and patients with cognitive and behavioral impairments.
Understanding the impact of TV commercials: electrical neuroimaging.
Vecchiato, Giovanni; Kong, Wanzeng; Maglione, Anton Giulio; Wei, Daming
2012-01-01
Today, there is a greater interest in the marketing world in using neuroimaging tools to evaluate the efficacy of TV commercials. This field of research is known as neuromarketing. In this article, we illustrate some applications of electrical neuroimaging, a discipline that uses electroencephalography (EEG) and intensive signal processing techniques for the evaluation of marketing stimuli. We also show how the proper usage of these methodologies can provide information related to memorization and attention while people are watching marketing-relevant stimuli. We note that temporal and frequency patterns of EEG signals are able to provide possible descriptors that convey information about the cognitive process in subjects observing commercial advertisements (ads). Such information could be unobtainable through common tools used in standard marketing research. Evidence of this research shows how EEG methodologies could be employed to better design new products that marketers are going to promote and to analyze the global impact of video commercials already broadcast on TV.
The Dopamine Imbalance Hypothesis of Fatigue in Multiple Sclerosis and Other Neurological Disorders
Dobryakova, Ekaterina; Genova, Helen M.; DeLuca, John; Wylie, Glenn R.
2015-01-01
Fatigue is one of the most pervasive symptoms of multiple sclerosis (MS), and has engendered hundreds of investigations on the topic. While there is a growing literature using various methods to study fatigue, a unified theory of fatigue in MS is yet to emerge. In the current review, we synthesize findings from neuroimaging, pharmacological, neuropsychological, and immunological studies of fatigue in MS, which point to a specific hypothesis of fatigue in MS: the dopamine imbalance hypothesis. The communication between the striatum and prefrontal cortex is reliant on dopamine, a modulatory neurotransmitter. Neuroimaging findings suggest that fatigue results from the disruption of communication between these regions. Supporting the dopamine imbalance hypothesis, structural and functional neuroimaging studies show abnormalities in the frontal and striatal regions that are heavily innervated by dopamine neurons. Further, dopaminergic psychostimulant medication has been shown to alleviate fatigue in individuals with traumatic brain injury, chronic fatigue syndrome, and in cancer patients, also indicating that dopamine might play an important role in fatigue perception. This paper reviews the structural and functional neuroimaging evidence as well as pharmacological studies that suggest that dopamine plays a critical role in the phenomenon of fatigue. We conclude with how specific aspects of the dopamine imbalance hypothesis can be tested in future research. PMID:25814977
Cole, J H; Ritchie, S J; Bastin, M E; Valdés Hernández, M C; Muñoz Maniega, S; Royle, N; Corley, J; Pattie, A; Harris, S E; Zhang, Q; Wray, N R; Redmond, P; Marioni, R E; Starr, J M; Cox, S R; Wardlaw, J M; Sharp, D J; Deary, I J
2018-01-01
Age-associated disease and disability are placing a growing burden on society. However, ageing does not affect people uniformly. Hence, markers of the underlying biological ageing process are needed to help identify people at increased risk of age-associated physical and cognitive impairments and ultimately, death. Here, we present such a biomarker, ‘brain-predicted age’, derived using structural neuroimaging. Brain-predicted age was calculated using machine-learning analysis, trained on neuroimaging data from a large healthy reference sample (N=2001), then tested in the Lothian Birth Cohort 1936 (N=669), to determine relationships with age-associated functional measures and mortality. Having a brain-predicted age indicative of an older-appearing brain was associated with: weaker grip strength, poorer lung function, slower walking speed, lower fluid intelligence, higher allostatic load and increased mortality risk. Furthermore, while combining brain-predicted age with grey matter and cerebrospinal fluid volumes (themselves strong predictors) not did improve mortality risk prediction, the combination of brain-predicted age and DNA-methylation-predicted age did. This indicates that neuroimaging and epigenetics measures of ageing can provide complementary data regarding health outcomes. Our study introduces a clinically-relevant neuroimaging ageing biomarker and demonstrates that combining distinct measurements of biological ageing further helps to determine risk of age-related deterioration and death. PMID:28439103
Basic Emotions in Human Neuroscience: Neuroimaging and Beyond.
Celeghin, Alessia; Diano, Matteo; Bagnis, Arianna; Viola, Marco; Tamietto, Marco
2017-01-01
The existence of so-called 'basic emotions' and their defining attributes represents a long lasting and yet unsettled issue in psychology. Recently, neuroimaging evidence, especially related to the advent of neuroimaging meta-analytic methods, has revitalized this debate in the endeavor of systems and human neuroscience. The core theme focuses on the existence of unique neural bases that are specific and characteristic for each instance of basic emotion. Here we review this evidence, outlining contradictory findings, strengths and limits of different approaches. Constructionism dismisses the existence of dedicated neural structures for basic emotions, considering that the assumption of a one-to-one relationship between neural structures and their functions is central to basic emotion theories. While these critiques are useful to pinpoint current limitations of basic emotions theories, we argue that they do not always appear equally generative in fostering new testable accounts on how the brain relates to affective functions. We then consider evidence beyond PET and fMRI, including results concerning the relation between basic emotions and awareness and data from neuropsychology on patients with focal brain damage. Evidence from lesion studies are indeed particularly informative, as they are able to bring correlational evidence typical of neuroimaging studies to causation, thereby characterizing which brain structures are necessary for, rather than simply related to, basic emotion processing. These other studies shed light on attributes often ascribed to basic emotions, such as automaticity of perception, quick onset, and brief duration. Overall, we consider that evidence in favor of the neurobiological underpinnings of basic emotions outweighs dismissive approaches. In fact, the concept of basic emotions can still be fruitful, if updated to current neurobiological knowledge that overcomes traditional one-to-one localization of functions in the brain. In particular, we propose that the structure-function relationship between brain and emotions is better described in terms of pluripotentiality, which refers to the fact that one neural structure can fulfill multiple functions, depending on the functional network and pattern of co-activations displayed at any given moment.
Mapping Epileptic Activity: Sources or Networks for the Clinicians?
Pittau, Francesca; Mégevand, Pierre; Sheybani, Laurent; Abela, Eugenio; Grouiller, Frédéric; Spinelli, Laurent; Michel, Christoph M.; Seeck, Margitta; Vulliemoz, Serge
2014-01-01
Epileptic seizures of focal origin are classically considered to arise from a focal epileptogenic zone and then spread to other brain regions. This is a key concept for semiological electro-clinical correlations, localization of relevant structural lesions, and selection of patients for epilepsy surgery. Recent development in neuro-imaging and electro-physiology and combinations, thereof, have been validated as contributory tools for focus localization. In parallel, these techniques have revealed that widespread networks of brain regions, rather than a single epileptogenic region, are implicated in focal epileptic activity. Sophisticated multimodal imaging and analysis strategies of brain connectivity patterns have been developed to characterize the spatio-temporal relationships within these networks by combining the strength of both techniques to optimize spatial and temporal resolution with whole-brain coverage and directional connectivity. In this paper, we review the potential clinical contribution of these functional mapping techniques as well as invasive electrophysiology in human beings and animal models for characterizing network connectivity. PMID:25414692
Shenton, ME; Hamoda, HM; Schneiderman, JS; Bouix, S; Pasternak, O; Rathi, Y; M-A, Vu; Purohit, MP; Helmer, K; Koerte, I; Lin, AP; C-F, Westin; Kikinis, R; Kubicki, M; Stern, RA; Zafonte, R
2013-01-01
Mild traumatic brain injury (mTBI), also referred to as concussion, remains a controversial diagnosis because the brain often appears quite normal on conventional computed tomography (CT) and magnetic resonance imaging (MRI) scans. Such conventional tools, however, do not adequately depict brain injury in mTBI because they are not sensitive to detecting diffuse axonal injuries (DAI), also described as traumatic axonal injuries (TAI), the major brain injuries in mTBI. Furthermore, for the 15 to 30% of those diagnosed with mTBI on the basis of cognitive and clinical symptoms, i.e., the “miserable minority,” the cognitive and physical symptoms do not resolve following the first three months post-injury. Instead, they persist, and in some cases lead to long-term disability. The explanation given for these chronic symptoms, i.e., postconcussive syndrome, particularly in cases where there is no discernible radiological evidence for brain injury, has led some to posit a psychogenic origin. Such attributions are made all the easier since both post-traumatic stress disorder (PTSD) and depression are frequently co-morbid with mTBI. The challenge is thus to use neuroimaging tools that are sensitive to DAI/TAI, such as diffusion tensor imaging (DTI), in order to detect brain injuries in mTBI. Of note here, recent advances in neuroimaging techniques, such as DTI, make it possible to characterize better extant brain abnormalities in mTBI. These advances may lead to the development of biomarkers of injury, as well as to staging of reorganization and reversal of white matter changes following injury, and to the ability to track and to characterize changes in brain injury over time. Such tools will likely be used in future research to evaluate treatment efficacy, given their enhanced sensitivity to alterations in the brain. In this article we review the incidence of mTBI and the importance of characterizing this patient population using objective radiological measures. Evidence is presented for detecting brain abnormalities in mTBI based on studies that use advanced neuroimaging techniques. Taken together, these findings suggest that more sensitive neuroimaging tools improve the detection of brain abnormalities (i.e., diagnosis) in mTBI. These tools will likely also provide important information relevant to outcome (prognosis), as well as play an important role in longitudinal studies that are needed to understand the dynamic nature of brain injury in mTBI. Additionally, summary tables of MRI and DTI findings are included. We believe that the enhanced sensitivity of newer and more advanced neuroimaging techniques for identifying areas of brain damage in mTBI will be important for documenting the biological basis of postconcussive symptoms, which are likely associated with subtle brain alterations, alterations that have heretofore gone undetected due to the lack of sensitivity of earlier neuroimaging techniques. Nonetheless, it is noteworthy to point out that detecting brain abnormalities in mTBI does not mean that other disorders of a more psychogenic origin are not co-morbid with mTBI and equally important to treat. They arguably are. The controversy of psychogenic versus physiogenic, however, is not productive because the psychogenic view does not carefully consider the limitations of conventional neuroimaging techniques in detecting subtle brain injuries in mTBI, and the physiogenic view does not carefully consider the fact that PTSD and depression, and other co-morbid conditions, may be present in those suffering from mTBI. Finally, we end with a discussion of future directions in research that will lead to the improved care of patients diagnosed with mTBI. PMID:22438191
Schmaal, Lianne; Marquand, Andre F; Rhebergen, Didi; van Tol, Marie-José; Ruhé, Henricus G; van der Wee, Nic J A; Veltman, Dick J; Penninx, Brenda W J H
2015-08-15
A chronic course of major depressive disorder (MDD) is associated with profound alterations in brain volumes and emotional and cognitive processing. However, no neurobiological markers have been identified that prospectively predict MDD course trajectories. This study evaluated the prognostic value of different neuroimaging modalities, clinical characteristics, and their combination to classify MDD course trajectories. One hundred eighteen MDD patients underwent structural and functional magnetic resonance imaging (MRI) (emotional facial expressions and executive functioning) and were clinically followed-up at 2 years. Three MDD trajectories (chronic n = 23, gradual improving n = 36, and fast remission n = 59) were identified based on Life Chart Interview measuring the presence of symptoms each month. Gaussian process classifiers were employed to evaluate prognostic value of neuroimaging data and clinical characteristics (including baseline severity, duration, and comorbidity). Chronic patients could be discriminated from patients with more favorable trajectories from neural responses to various emotional faces (up to 73% accuracy) but not from structural MRI and functional MRI related to executive functioning. Chronic patients could also be discriminated from remitted patients based on clinical characteristics (accuracy 69%) but not when age differences between the groups were taken into account. Combining different task contrasts or data sources increased prediction accuracies in some but not all cases. Our findings provide evidence that the prediction of naturalistic course of depression over 2 years is improved by considering neuroimaging data especially derived from neural responses to emotional facial expressions. Neural responses to emotional salient faces more accurately predicted outcome than clinical data. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
A Training Program in Breast Cancer Research Using NMR Techniques
2005-07-01
to explore the application NMR molecular imaging techniques developed in this program in detection of amyloid plaques in the Alzheimer diseased mouse...one is to utilize the molecular imaging technique to exploit new application in imaging of amyloid plaques in Alzheimer disease. A abridge of each...matched, non-demented elderly suggests that volumetric studies of ante-mortem neuroimages may provide an early marker of AD in aging populations. In
Solopchuk, Oleg; Alamia, Andrea; Dricot, Laurence; Duque, Julie; Zénon, Alexandre
2017-12-01
Neuroimaging studies have repeatedly emphasized the role of the supplementary motor area (SMA) in motor sequence learning, but interferential approaches have led to inconsistent findings. Here, we aimed to test the role of the SMA in motor skill learning by combining interferential and neuroimaging techniques. Sixteen subjects were trained on simple finger movement sequences for 4 days. Afterwards, they underwent two neuroimaging sessions, in which they executed both trained and novel sequences. Prior to entering the scanner, the subjects received inhibitory transcranial magnetic stimulation (TMS) over the SMA or a control site. Using multivariate fMRI analysis, we confirmed that motor training enhances the neural representation of motor sequences in the SMA, in accordance with previous findings. However, although SMA inhibition altered sequence representation (i.e. between-sequence decoding accuracy) in this area, behavioural performance remained unimpaired. Our findings question the causal link between the neuroimaging correlate of elementary motor sequence representation in the SMA and sequence generation, calling for a more thorough investigation of the role of this region in performance of learned motor sequences. Copyright © 2017 Elsevier Inc. All rights reserved.
"This is Why you've Been Suffering": Reflections of Providers on Neuroimaging in Mental Health Care.
Borgelt, Emily; Buchman, Daniel Z; Illes, Judy
2011-03-01
Mental health care providers increasingly confront challenges posed by the introduction of new neurotechnology into the clinic, but little is known about the impact of such capabilities on practice patterns and relationships with patients. To address this important gap, we sought providers' perspectives on the potential clinical translation of functional neuroimaging for prediction and diagnosis of mental illness. We conducted 32 semi-structured telephone interviews with mental health care providers representing psychiatry, psychology, family medicine, and allied mental health. Our results suggest that mental health providers have begun to re-conceptualize mental illness with a neuroscience gaze. They report an epistemic commitment to the value of a brain scan to provide a meaningful explanation of mental illness for their clients. If functional neuroimaging continues along its projected trajectory to translation, providers will ultimately have to negotiate its role in mental health. Their perspectives, therefore, enrich bioethical discourse surrounding neurotechnology and inform the translational pathway.
“This is Why you've Been Suffering”: Reflections of Providers on Neuroimaging in Mental Health Care
Borgelt, Emily; Buchman, Daniel Z.; Illes, Judy
2011-01-01
Mental health care providers increasingly confront challenges posed by the introduction of new neurotechnology into the clinic, but little is known about the impact of such capabilities on practice patterns and relationships with patients. To address this important gap, we sought providers' perspectives on the potential clinical translation of functional neuroimaging for prediction and diagnosis of mental illness. We conducted 32 semi-structured telephone interviews with mental health care providers representing psychiatry, psychology, family medicine, and allied mental health. Our results suggest that mental health providers have begun to re-conceptualize mental illness with a neuroscience gaze. They report an epistemic commitment to the value of a brain scan to provide a meaningful explanation of mental illness for their clients. If functional neuroimaging continues along its projected trajectory to translation, providers will ultimately have to negotiate its role in mental health. Their perspectives, therefore, enrich bioethical discourse surrounding neurotechnology and inform the translational pathway. PMID:21572566
A studyforrest extension, retinotopic mapping and localization of higher visual areas
Sengupta, Ayan; Kaule, Falko R.; Guntupalli, J. Swaroop; Hoffmann, Michael B.; Häusler, Christian; Stadler, Jörg; Hanke, Michael
2016-01-01
The studyforrest (http://studyforrest.org) dataset is likely the largest neuroimaging dataset on natural language and story processing publicly available today. In this article, along with a companion publication, we present an update of this dataset that extends its scope to vision and multi-sensory research. 15 participants of the original cohort volunteered for a series of additional studies: a clinical examination of visual function, a standard retinotopic mapping procedure, and a localization of higher visual areas—such as the fusiform face area. The combination of this update, the previous data releases for the dataset, and the companion publication, which includes neuroimaging and eye tracking data from natural stimulation with a motion picture, form an extremely versatile and comprehensive resource for brain imaging research—with almost six hours of functional neuroimaging data across five different stimulation paradigms for each participant. Furthermore, we describe employed paradigms and present results that document the quality of the data for the purpose of characterising major properties of participants’ visual processing stream. PMID:27779618
[Neuropsychology of Tourette's disorder: cognition, neuroimaging and creativity].
Espert, R; Gadea, M; Alino, M; Oltra-Cucarella, J
2017-02-24
Tourette's disorder is the result of fronto-striatal brain dysfunction affecting people of all ages, with a debut in early childhood and continuing into adolescence and adulthood. This article reviews the main cognitive, functional neuroimaging and creativity-related studies in a disorder characterized by an excess of dopamine in the brain. Given the special cerebral configuration of these patients, neuropsychological alterations, especially in executive functions, should be expected. However, the findings are inconclusive and are conditioned by factors such as comorbidity with attention deficit hyperactivity disorder and obsessive-compulsive disorder, age or methodological variables. On the other hand, the neuroimaging studies carried out over the last decade have been able to explain the clinical symptoms of Tourette's disorder patients, with special relevance for the supplementary motor area and the anterior cingulate gyrus. Finally, although there is no linear relationship between excess of dopamine and creativity, the scientific literature emphasizes an association between Tourette's disorder and musical creativity, which could be translated into intervention programs based on music.
Takamura, T; Hanakawa, T
2017-07-01
Although functional magnetic resonance imaging (fMRI) has long been used to assess task-related brain activity in neuropsychiatric disorders, it has not yet become a widely available clinical tool. Resting-state fMRI (rs-fMRI) has been the subject of recent attention in the fields of basic and clinical neuroimaging research. This method enables investigation of the functional organization of the brain and alterations of resting-state networks (RSNs) in patients with neuropsychiatric disorders. Rs-fMRI does not require participants to perform a demanding task, in contrast to task fMRI, which often requires participants to follow complex instructions. Rs-fMRI has a number of advantages over task fMRI for application with neuropsychiatric patients, for example, although applications of task fMR to participants for healthy are easy. However, it is difficult to apply these applications to patients with psychiatric and neurological disorders, because they may have difficulty in performing demanding cognitive task. Here, we review the basic methodology and analysis techniques relevant to clinical studies, and the clinical applications of the technique for examining neuropsychiatric disorders, focusing on mood disorders (major depressive disorder and bipolar disorder) and dementia (Alzheimer's disease and mild cognitive impairment).
Review of functional near-infrared spectroscopy in neurorehabilitation
Mihara, Masahito; Miyai, Ichiro
2016-01-01
Abstract. We provide a brief overview of the research and clinical applications of near-infrared spectroscopy (NIRS) in the neurorehabilitation field. NIRS has several potential advantages and shortcomings as a neuroimaging tool and is suitable for research application in the rehabilitation field. As one of the main applications of NIRS, we discuss its application as a monitoring tool, including investigating the neural mechanism of functional recovery after brain damage and investigating the neural mechanisms for controlling bipedal locomotion and postural balance in humans. In addition to being a monitoring tool, advances in signal processing techniques allow us to use NIRS as a therapeutic tool in this field. With a brief summary of recent studies investigating the clinical application of NIRS using motor imagery task, we discuss the possible clinical usage of NIRS in brain–computer interface and neurofeedback. PMID:27429995
A critical review of the neuroimaging literature on synesthesia
Hupé, Jean-Michel; Dojat, Michel
2015-01-01
Synesthesia refers to additional sensations experienced by some people for specific stimulations, such as the systematic arbitrary association of colors to letters for the most studied type. Here, we review all the studies (based mostly on functional and structural magnetic resonance imaging) that have searched for the neural correlates of this subjective experience, as well as structural differences related to synesthesia. Most differences claimed for synesthetes are unsupported, due mainly to low statistical power, statistical errors, and methodological limitations. Our critical review therefore casts some doubts on whether any neural correlate of the synesthetic experience has been established yet. Rather than being a neurological condition (i.e., a structural or functional brain anomaly), synesthesia could be reconsidered as a special kind of childhood memory, whose signature in the brain may be out of reach with present brain imaging techniques. PMID:25873873
Shulman, Robert G; Hyder, Fahmeed; Rothman, Douglas L
2014-01-01
Functional neuroimaging measures quantitative changes in neurophysiological parameters coupled to neuronal activity during observable behavior. These results have usually been interpreted by assuming that mental causation of behavior arises from the simultaneous actions of distinct psychological mechanisms or modules. However, reproducible localization of these modules in the brain using functional magnetic resonance imaging (MRI) and positron emission tomography (PET) imaging has been elusive other than for sensory systems. In this paper, we show that neuroenergetic studies using PET, calibrated functional magnetic resonance imaging (fMRI), 13C magnetic resonance spectroscopy, and electrical recordings do not support the standard approach, which identifies the location of mental modules from changes in brain activity. Of importance in reaching this conclusion is that changes in neuronal activities underlying the fMRI signal are many times smaller than the high ubiquitous, baseline neuronal activity, or energy in resting, awake humans. Furthermore, the incremental signal depends on the baseline activity contradicting theoretical assumptions about linearity and insertion of mental modules. To avoid these problems, while making use of these valuable results, we propose that neuroimaging should be used to identify observable brain activities that are necessary for a person's observable behavior rather than being used to seek hypothesized mental processes. PMID:25160670
Smits, M; Wieberdink, R G; Bakker, S L M; Dippel, D W J
2011-04-01
We describe a left-handed patient with transient aphasia and bilateral carotid stenosis. Computed tomography (CT) arteriography showed a 90% stenosis of the right and 30% stenosis of the left internal carotid artery. Head CT and magnetic resonance imaging (MRI) of the brain showed no recent ischemic changes. As only the symptomatic side would require surgical intervention, and because hemispheric dominance for language in left-handed patients may be either left or right sided, a preoperative assessment of hemispheric dominance was required. We used functional MRI to determine hemispheric dominance for language and hence to establish the indication for carotid endarterectomy surgery. Functional MRI demonstrated right hemispheric dominance for language and right-sided carotid endarterectomy was performed. We propose that the clinical use of functional MRI as a noninvasive imaging technique for the assessment of hemispheric language dominance may be extended to the assessment of hemispheric language dominance prior to carotid endarterectomy. Copyright © 2010 by the American Society of Neuroimaging.
Febo, Marcelo; Ferris, Craig F
2014-09-11
Oxytocin and vasopressin modulate a range of species typical behavioral functions that include social recognition, maternal-infant attachment, and modulation of memory, offensive aggression, defensive fear reactions, and reward seeking. We have employed novel functional magnetic resonance mapping techniques in awake rats to explore the roles of these neuropeptides in the maternal and non-maternal brain. Results from the functional neuroimaging studies that are summarized here have directly and indirectly confirmed and supported previous findings. Oxytocin is released within the lactating rat brain during suckling stimulation and activates specific subcortical networks in the maternal brain. Both vasopressin and oxytocin modulate brain regions involved unconditioned fear, processing of social stimuli and the expression of agonistic behaviors. Across studies there are relatively consistent brain networks associated with internal motivational drives and emotional states that are modulated by oxytocin and vasopressin. This article is part of a Special Issue entitled Oxytocin and Social Behav. Copyright © 2014 Elsevier B.V. All rights reserved.
Understanding the role of the primary somatosensory cortex: Opportunities for rehabilitation
Borich, M.R.; Brodie, S.M.; Gray, W.A.; Ionta, S.; Boyd, L.A.
2016-01-01
Emerging evidence indicates impairments in somatosensory function may be a major contributor to motor dysfunction associated with neurologic injury or disorders. However, the neuroanatomical substrates underlying the connection between aberrant sensory input and ineffective motor output are still under investigation. The primary somatosensory cortex (S1) plays a critical role in processing afferent somatosensory input and contributes to the integration of sensory and motor signals necessary for skilled movement. Neuroimaging and neurostimulation approaches provide unique opportunities to non-invasively study S1 structure and function including connectivity with other cortical regions. These research techniques have begun to illuminate casual contributions of abnormal S1 activity and connectivity to motor dysfunction and poorer recovery of motor function in neurologic patient populations. This review synthesizes recent evidence illustrating the role of S1 in motor control, motor learning and functional recovery with an emphasis on how information from these investigations may be exploited to inform stroke rehabilitation to reduce motor dysfunction and improve therapeutic outcomes. PMID:26164474
Seymour, Karen E.; Reinblatt, Shauna P.; Benson, Leora; Carnell, Susan
2015-01-01
Attention-deficit/hyperactivity disorder (ADHD) and conditions involving excessive eating (e.g. obesity, binge / loss of control eating) are increasingly prevalent within pediatric populations, and correlational and some longitudinal studies have suggested inter-relationships between these disorders. In addition, a number of common neural correlates are emerging across conditions, e.g. functional abnormalities within circuits subserving reward processing and executive functioning. To explore this potential cross-condition overlap in neurobehavioral underpinnings, we selectively review relevant functional neuroimaging literature, specifically focusing on studies probing i) reward processing, ii) response inhibition, and iii) emotional processing and regulation, and outline three specific shared neurobehavioral circuits. Based on our review, we also identify gaps within the literature that would benefit from further research. PMID:26098969
The “Task B problem” and other considerations in developmental functional neuroimaging
Church, Jessica A.; Petersen, Steven E.; Schlaggar, Bradley L.
2012-01-01
Functional neuroimaging provides a remarkable tool to allow us to study cognition across the lifespan and in special populations in a safe way. However, experimenters face a number of methodological issues, and these issues are particularly pertinent when imaging children. This brief article discusses assessing task performance, strategies for dealing with group performance differences, controlling for movement, statistical power, proper atlas registration, and data analysis strategies. In addition, there will be discussion of two other topics that have important implications for interpreting fMRI data: the question of whether functional neuroanatomical differences between adults and children are the consequence of putative developmental neurovascular differences, and the issue of interpreting negative blood oxygenation-level dependent (BOLD) signal change. PMID:20496376
Morning Glory Syndrome with Carotid and Middle Cerebral Artery Vasculopathy.
Nezzar, Hachemi; Mbekeani, Joyce N; Dalens, Helen
2015-12-01
To report a case of incidental asymptomatic atypical morning glory syndrome (MGS) with concomitant ipsilateral carotid and middle cerebral dysgenesis. A 6-year-old child was discovered to have incidental findings of MGS, with atypia. All visual functions were normal including vision and stereopsis. Neuroimaging revealed ipsilateral carotid and middle cerebral vascular narrowing without associated collateral vessels or cerebral ischemia commonly seen in Moyamoya disease. Subsequent annual examinations have been stable, without signs of progression. This case demonstrates disparity between structural aberrations and final visual and neurological function and reinforces the association between MGS and intracranial vascular disruption. Full ancillary ophthalmic and neuroimaging studies should be performed in all patients with MGS with interval reassessments, even when the patient is asymptomatic and functionally intact.
Clinical neuroimaging in the preterm infant: Diagnosis and prognosis.
Hinojosa-Rodríguez, Manuel; Harmony, Thalía; Carrillo-Prado, Cristina; Van Horn, John Darrell; Irimia, Andrei; Torgerson, Carinna; Jacokes, Zachary
2017-01-01
Perinatal care advances emerging over the past twenty years have helped to diminish the mortality and severe neurological morbidity of extremely and very preterm neonates (e.g., cystic Periventricular Leukomalacia [c-PVL] and Germinal Matrix Hemorrhage - Intraventricular Hemorrhage [GMH-IVH grade 3-4/4]; 22 to < 32 weeks of gestational age, GA). However, motor and/or cognitive disabilities associated with mild-to-moderate white and gray matter injury are frequently present in this population (e.g., non-cystic Periventricular Leukomalacia [non-cystic PVL], neuronal-axonal injury and GMH-IVH grade 1-2/4). Brain research studies using magnetic resonance imaging (MRI) report that 50% to 80% of extremely and very preterm neonates have diffuse white matter abnormalities (WMA) which correspond to only the minimum grade of severity. Nevertheless, mild-to-moderate diffuse WMA has also been associated with significant affectations of motor and cognitive activities. Due to increased neonatal survival and the intrinsic characteristics of diffuse WMA, there is a growing need to study the brain of the premature infant using non-invasive neuroimaging techniques sensitive to microscopic and/or diffuse lesions. This emerging need has led the scientific community to try to bridge the gap between concepts or ideas from different methodologies and approaches; for instance, neuropathology, neuroimaging and clinical findings. This is evident from the combination of intense pre-clinical and clinicopathologic research along with neonatal neurology and quantitative neuroimaging research. In the following review, we explore literature relating the most frequently observed neuropathological patterns with the recent neuroimaging findings in preterm newborns and infants with perinatal brain injury. Specifically, we focus our discussions on the use of neuroimaging to aid diagnosis, measure morphometric brain damage, and track long-term neurodevelopmental outcomes.
Cholinergic modulation of cognition: Insights from human pharmacological functional neuroimaging
Bentley, Paul; Driver, Jon; Dolan, Raymond J.
2011-01-01
Evidence from lesion and cortical-slice studies implicate the neocortical cholinergic system in the modulation of sensory, attentional and memory processing. In this review we consider findings from sixty-three healthy human cholinergic functional neuroimaging studies that probe interactions of cholinergic drugs with brain activation profiles, and relate these to contemporary neurobiological models. Consistent patterns that emerge are: (1) the direction of cholinergic modulation of sensory cortex activations depends upon top-down influences; (2) cholinergic hyperstimulation reduces top-down selective modulation of sensory cortices; (3) cholinergic hyperstimulation interacts with task-specific frontoparietal activations according to one of several patterns, including: suppression of parietal-mediated reorienting; decreasing ‘effort’-associated activations in prefrontal regions; and deactivation of a ‘resting-state network’ in medial cortex, with reciprocal recruitment of dorsolateral frontoparietal regions during performance-challenging conditions; (4) encoding-related activations in both neocortical and hippocampal regions are disrupted by cholinergic blockade, or enhanced with cholinergic stimulation, while the opposite profile is observed during retrieval; (5) many examples exist of an ‘inverted-U shaped’ pattern of cholinergic influences by which the direction of functional neural activation (and performance) depends upon both task (e.g. relative difficulty) and subject (e.g. age) factors. Overall, human cholinergic functional neuroimaging studies both corroborate and extend physiological accounts of cholinergic function arising from other experimental contexts, while providing mechanistic insights into cholinergic-acting drugs and their potential clinical applications. PMID:21708219
DOE Office of Scientific and Technical Information (OSTI.GOV)
Parvaz M. A.; Parvaz, M.A.; Alia-Klein, N.
In this review, we highlight the role of neuroimaging techniques in studying the emotional and cognitive-behavioral components of the addiction syndrome by focusing on the neural substrates subserving them. The phenomenology of drug addiction can be characterized by a recurrent pattern of subjective experiences that includes drug intoxication, craving, bingeing, and withdrawal with the cycle culminating in a persistent preoccupation with obtaining, consuming, and recovering from the drug. In the past two decades, imaging studies of drug addiction have demonstrated deficits in brain circuits related to reward and impulsivity. The current review focuses on studies employing positron emission tomography (PET),more » functional magnetic resonance imaging (fMRI), and electroencephalography (EEG) to investigate these behaviors in drug-addicted human populations. We begin with a brief account of drug addiction followed by a technical account of each of these imaging modalities. We then discuss how these techniques have uniquely contributed to a deeper understanding of addictive behaviors.« less
In vivo optical imaging of cortical spreading depression in rat
NASA Astrophysics Data System (ADS)
Chen, Shangbin; Li, Pengcheng; Luo, Weihua; Gong, Hui; Cheng, Haiying; Luo, Qingming
2003-12-01
Intrinsic optical signals imaging (IOSI) and laser speckle imaging (LSI) are both novel techniques for functional neuroimaging in vivo. Combining them to study cortical spreading depression (CSD) which is an important disease model for migraine and other neurological disorders. CSD were induced by pinprick in Sprague-Dawley rats. Intrinsic optical signals (IOS) at 540 nm showed CSD evolution happened in one hemisphere cortex at speeds of 3.7+/-0.4 mm/min, and the vasodilation closely correlated a four-phasic response. By LSI, we observed a transient and significant increase cerebral blood flow (CBF). In this paper, optical imaging would be showed as a powerful tool for describing the hemodynamic character during CSD in rat.
[The nature, diagnosis and treatment of post-concussion syndrome].
Muñoz-Céspedes, J M; Pelegrín-Valero, C; Tirapu-Ustarroz, J; Fernández-Guinea, S
1998-11-01
The relationship between brief loss of consciousness, subsequent cognitive and emotional complaints, and impact on daily functioning continues to be hotly debated. In this paper the strong variability about prevalence of the postconcussional syndrome found in several studies is outstanding and the main issues of this disagreement are suggested. Recent neuroimaging techniques are discussed and some neuropsychological measures are suggested. Currents models (organic/psychogenic) of postconcussional symptoms are reviewed, and a multifactorial model which integrates biological factors with the relevance of neuropsychological deficits--attention, memory, speed of information processing--and coping process is proposed. Finally, according with this model, we conclude with some suggestions to improve neuropsychological intervention and medical treatment of these patients.
Leigh Syndrome in Childhood: Neurologic Progression and Functional Outcome.
Lee, Jin Sook; Kim, Hunmin; Lim, Byung Chan; Hwang, Hee; Choi, Jieun; Kim, Ki Joong; Hwang, Yong Seung; Chae, Jong Hee
2016-04-01
Few studies have analyzed the clinical course and functional outcome in Leigh syndrome (LS). The aim of this study was to determine the clinical, radiological, biochemical, and genetic features of patients with LS, and identify prognostic indicators of the disease progression and neurological outcome. Thirty-nine patients who had been diagnosed with LS at the Seoul National University Children's Hospital were included. Their medical records, neuroimaging findings, and histological/biochemical findings of skeletal muscle specimens were reviewed. Targeted sequencing of mitochondrial DNA was performed based on mitochondrial respiratory chain (MRC) enzyme defects. Isolated complex I deficiency was the most frequently observed MRC defect (in 42% of 38 investigated patients). Mitochondrial DNA mutations were identified in 11 patients, of which 81.8% were MT-ND genes. The clinical outcome varied widely, from independent daily activity to severe disability. Poor functional outcomes and neurological deterioration were significantly associated with early onset (before an age of 1 year) and the presence of other lesions additional to basal ganglia involvement in the initial neuroimaging. The neurological severity and outcome of LS may vary widely and be better than those predicted based on previous studies. We suggest that age at onset and initial neuroimaging findings are prognostic indicators in LS.
State Space Modeling of Time-Varying Contemporaneous and Lagged Relations in Connectivity Maps
Molenaar, Peter C. M.; Beltz, Adriene M.; Gates, Kathleen M.; Wilson, Stephen J.
2017-01-01
Most connectivity mapping techniques for neuroimaging data assume stationarity (i.e., network parameters are constant across time), but this assumption does not always hold true. The authors provide a description of a new approach for simultaneously detecting time-varying (or dynamic) contemporaneous and lagged relations in brain connectivity maps. Specifically, they use a novel raw data likelihood estimation technique (involving a second-order extended Kalman filter/smoother embedded in a nonlinear optimizer) to determine the variances of the random walks associated with state space model parameters and their autoregressive components. The authors illustrate their approach with simulated and blood oxygen level-dependent functional magnetic resonance imaging data from 30 daily cigarette smokers performing a verbal working memory task, focusing on seven regions of interest (ROIs). Twelve participants had dynamic directed functional connectivity maps: Eleven had one or more time-varying contemporaneous ROI state loadings, and one had a time-varying autoregressive parameter. Compared to smokers without dynamic maps, smokers with dynamic maps performed the task with greater accuracy. Thus, accurate detection of dynamic brain processes is meaningfully related to behavior in a clinical sample. PMID:26546863
The role of neuroimaging in the discovery of processing stages. A review.
Mulder, G; Wijers, A A; Lange, J J; Buijink, B M; Mulder, L J; Willemsen, A T; Paans, A M
1995-11-01
In this contribution we show how neuroimaging methods can augment behavioural methods to discover processing stages. Event Related Brain Potentials (ERPs), Brain Electrical Source Analysis (BESA) and regional changes in cerebral blood flow (rCBF) do not necessarily require behavioural responses. With the aid of rCBF we are able to discover several cortical and subcortical brain systems (processors) active in selective attention and memory search tasks. BESA describes cortical activity with high temporal resolution in terms of a limited number of neural generators within these brain systems. The combination of behavioural methods and neuroimaging provides a picture of the functional architecture of the brain. The review is organized around three processors: the Visual, Cognitive and Manual Motor Processors.
Monroe, Todd B.; Gore, John C.; Chen, Li Min; Mion, Lorraine C.; Cowan, Ronald L.
2015-01-01
Pain management in people with dementia is a critical problem. Recently, psychophysical and neuroimaging techniques have been used to extend our understanding of pain processing in the brain as well as to identify structural and functional changes in Alzheimer disease (AD). But interpreting the complex relationship between AD pathology, brain activation, and pain reports is challenging. This review proposes a conceptual framework for designing and interpreting psychophysical and neuroimaging studies of pain processing in people with AD. Previous human studies describe the lateral (sensory) and medial (affective) pain networks. Although the majority of the literature on pain supports the lateral and medial networks, some evidence supports an additional rostral pain network, which is believed to function in the production of pain behaviors. The sensory perception of pain as assessed through verbal report and behavioral display may be altered in AD. In addition, neural circuits mediating pain perception and behavioral expression may be hyperactive or underactive, depending on the brain region involved, stage of the disease, and type of pain (acute experimental stimuli or chronic medical conditions). People with worsening AD may therefore experience pain but be unable to indicate pain through verbal or behavioral reports, leaving them at great risk of experiencing untreated pain. Psychophysical (verbal or behavioral) and neurophysiological (brain activation) approaches can potentially address gaps in our knowledge of pain processing in AD by revealing the relationship between neural processes and verbal and behavioral outcomes in the presence of acute or chronic pain. PMID:23277361
MR connectomics: a conceptual framework for studying the developing brain
Hagmann, Patric; Grant, Patricia E.; Fair, Damien A.
2012-01-01
The combination of advanced neuroimaging techniques and major developments in complex network science, have given birth to a new framework for studying the brain: “connectomics.” This framework provides the ability to describe and study the brain as a dynamic network and to explore how the coordination and integration of information processing may occur. In recent years this framework has been used to investigate the developing brain and has shed light on many dynamic changes occurring from infancy through adulthood. The aim of this article is to review this work and to discuss what we have learned from it. We will also use this body of work to highlight key technical aspects that are necessary in general for successful connectome analysis using today's advanced neuroimaging techniques. We look to identify current limitations of such approaches, what can be improved, and how these points generalize to other topics in connectome research. PMID:22707934
Zeidan, F.; Grant, J.A.; Brown, C.A.; McHaffie, J.G.; Coghill, R.C.
2013-01-01
The cognitive modulation of pain is influenced by a number of factors ranging from attention, beliefs, conditioning, expectations, mood, and the regulation of emotional responses to noxious sensory events. Recently, mindfulness meditation has been found attenuate pain through some of these mechanisms including enhanced cognitive and emotional control, as well as altering the contextual evaluation of sensory events. This review discusses the brain mechanisms involved in mindfulness meditation-related pain relief across different meditative techniques, expertise and training levels, experimental procedures, and neuroimaging methodologies. Converging lines of neuroimaging evidence reveal that mindfulness meditation-related pain relief is associated with unique appraisal cognitive processes depending on expertise level and meditation tradition. Moreover, it is postulated that mindfulness meditation-related pain relief may share a common final pathway with other cognitive techniques in the modulation of pain. PMID:22487846
Berryhill, Marian E.
2012-01-01
The role of posterior parietal cortex (PPC) in various forms of memory is a current topic of interest in the broader field of cognitive neuroscience. This large cortical region has been linked with a wide range of mnemonic functions affecting each stage of memory processing: encoding, maintenance, and retrieval. Yet, the precise role of the PPC in memory remains mysterious and controversial. Progress in understanding PPC function will require researchers to incorporate findings in a convergent manner from multiple experimental techniques rather than emphasizing a particular type of data. To facilitate this process, here, we review findings from the human neuropsychological research and examine the consequences to memory following PPC damage. Recent patient-based research findings have investigated two typically disconnected fields: working memory (WM) and episodic memory. The findings from patient participants with unilateral and bilateral PPC lesions performing diverse experimental paradigms are summarized. These findings are then related to findings from other techniques including neurostimulation (TMS and tDCS) and the influential and more abundant functional neuroimaging literature. We then review the strengths and weaknesses of hypotheses proposed to account for PPC function in these forms of memory. Finally, we address what missing evidence is needed to clarify the role(s) of the PPC in memory. PMID:22701406
Alústiza, Irene; Radua, Joaquim; Albajes-Eizagirre, Anton; Domínguez, Manuel; Aubá, Enrique; Ortuño, Felipe
2016-01-01
Timing and other cognitive processes demanding cognitive control become interlinked when there is an increase in the level of difficulty or effort required. Both functions are interrelated and share neuroanatomical bases. A previous meta-analysis of neuroimaging studies found that people with schizophrenia had significantly lower activation, relative to normal controls, of most right hemisphere regions of the time circuit. This finding suggests that a pattern of disconnectivity of this circuit, particularly in the supplementary motor area, is a trait of this mental disease. We hypothesize that a dysfunctional temporal/cognitive control network underlies both cognitive and psychiatric symptoms of schizophrenia and that timing dysfunction is at the root of the cognitive deficits observed. The goal of our study was to look, in schizophrenia patients, for brain structures activated both by execution of cognitive tasks requiring increased effort and by performance of time perception tasks. We conducted a signed differential mapping (SDM) meta-analysis of functional neuroimaging studies in schizophrenia patients assessing the brain response to increasing levels of cognitive difficulty. Then, we performed a multimodal meta-analysis to identify common brain regions in the findings of that SDM meta-analysis and our previously-published activation likelihood estimate (ALE) meta-analysis of neuroimaging of time perception in schizophrenia patients. The current study supports the hypothesis that there exists an overlap between neural structures engaged by both timing tasks and non-temporal cognitive tasks of escalating difficulty in schizophrenia. The implication is that a deficit in timing can be considered as a trait marker of the schizophrenia cognitive profile. PMID:26925013
The cerebellum: its role in language and related cognitive and affective functions.
De Smet, Hyo Jung; Paquier, Philippe; Verhoeven, Jo; Mariën, Peter
2013-12-01
The traditional view on the cerebellum as the sole coordinator of motor function has been substantially redefined during the past decades. Neuroanatomical, neuroimaging and clinical studies have extended the role of the cerebellum to the modulation of cognitive and affective processing. Neuroanatomical studies have demonstrated cerebellar connectivity with the supratentorial association areas involved in higher cognitive and affective functioning, while functional neuroimaging and clinical studies have provided evidence of cerebellar involvement in a variety of cognitive and affective tasks. This paper reviews the recently acknowledged role of the cerebellum in linguistic and related cognitive and behavioral-affective functions. In addition, typical cerebellar syndromes such as the cerebellar cognitive affective syndrome (CCAS) and the posterior fossa syndrome (PFS) will be briefly discussed and the current hypotheses dealing with the presumed neurobiological mechanisms underlying the linguistic, cognitive and affective modulatory role of the cerebellum will be reviewed. Copyright © 2012 Elsevier Inc. All rights reserved.
McDowell, Jennifer E.; Dyckman, Kara A.; Austin, Benjamin; Clementz, Brett A.
2008-01-01
This review provides a summary of the contributions made by human functional neuroimaging studies to the understanding of neural correlates of saccadic control. The generation of simple visually-guided saccades (redirections of gaze to a visual stimulus or prosaccades) and more complex volitional saccades require similar basic neural circuitry with additional neural regions supporting requisite higher level processes. The saccadic system has been studied extensively in non-human primates (e.g. single unit recordings) and humans (e.g. lesions and neuroimaging). Considerable knowledge of this system’s functional neuroanatomy makes it useful for investigating models of cognitive control. The network involved in prosaccade generation (by definition exogenously-driven) includes subcortical (striatum, thalamus, superior colliculus, and cerebellar vermis) and cortical structures (primary visual, extrastriate, and parietal cortices, and frontal and supplementary eye fields). Activation in these regions is also observed during endogenously-driven voluntary saccades (e.g. antisaccades, ocular motor delayed response or memory saccades, predictive tracking tasks and anticipatory saccades, and saccade sequencing), all of which require complex cognitive processes like inhibition and working memory. These additional requirements are supported by changes in neural activity in basic saccade circuitry and by recruitment of additional neural regions (such as prefrontal and anterior cingulate cortices). Activity in visual cortex is modulated as a function of task demands and may predict the type of saccade to be generated, perhaps via top-down control mechanisms. Neuroimaging studies suggest two foci of activation within FEF - medial and lateral - which may correspond to volitional and reflexive demands, respectively. Future research on saccade control could usefully (i) delineate important anatomical subdivisions that underlie functional differences, (ii) evaluate functional connectivity of anatomical regions supporting saccade generation using methods such as ICA and structural equation modeling, (iii) investigate how context affects behavior and brain activity, and (iv) use multi-modal neuroimaging to maximize spatial and temporal resolution. PMID:18835656
Huang, Qi; Nie, Binbin; Ma, Chen; Wang, Jing; Zhang, Tianhao; Duan, Shaofeng; Wu, Shang; Liang, Shengxiang; Li, Panlong; Liu, Hua; Sun, Hua; Zhou, Jiangning; Xu, Lin; Shan, Baoci
2018-01-01
Tree shrews are proposed as an alternative animal model to nonhuman primates due to their close affinity to primates. Neuroimaging techniques are widely used to study brain functions and structures of humans and animals. However, tree shrews are rarely applied in neuroimaging field partly due to the lack of available species specific analysis methods. In this study, 10 PET/CT and 10 MRI images of tree shrew brain were used to construct PET and MRI templates; based on histological atlas we reconstructed a three-dimensional digital atlas with 628 structures delineated; then the digital atlas and templates were aligned into a stereotaxic space. Finally, we integrated the digital atlas and templates into a toolbox for tree shrew brain spatial normalization, statistical analysis and results localization. We validated the feasibility of the toolbox by simulated data with lesions in laterodorsal thalamic nucleus (LD). The lesion volumes of simulated PET and MRI images were (12.97±3.91)mm 3 and (7.04±0.84)mm 3 . Statistical results at p<0.005 showed the lesion volumes of PET and MRI were 13.18mm 3 and 8.06mm 3 in LD. To our knowledge, we report the first PET template and digital atlas of tree shrew brain. Compared to the existing MRI templates, our MRI template was aligned into stereotaxic space. And the toolbox is the first software dedicated for tree shrew brain analysis. The templates and digital atlas of tree shrew brain, as well as the toolbox, facilitate the use of tree shrews in neuroimaging field. Copyright © 2017 Elsevier B.V. All rights reserved.
MacMillan, Freya; Camfield, David A.; Seto, Sai W.
2017-01-01
Neuroimaging facilitates the assessment of complementary medicines (CMs) by providing a noninvasive insight into their mechanisms of action in the human brain. This is important for identifying the potential treatment options for target disease cohorts with complex pathophysiologies. The aim of this systematic review was to evaluate study characteristics, intervention efficacy, and the structural and functional neuroimaging methods used in research assessing nutritional and herbal medicines for mild cognitive impairment (MCI) and dementia. Six databases were searched for articles reporting on CMs, dementia, and neuroimaging methods. Data were extracted from 21/2,742 eligible full text articles and risk of bias was assessed. Nine studies examined people with Alzheimer's disease, 7 MCI, 4 vascular dementia, and 1 all-cause dementia. Ten studies tested herbal medicines, 8 vitamins and supplements, and 3 nootropics. Ten studies used electroencephalography (EEG), 5 structural magnetic resonance imaging (MRI), 2 functional MRI (fMRI), 3 cerebral blood flow (CBF), 1 single photon emission tomography (SPECT), and 1 positron emission tomography (PET). Four studies had a low risk of bias, with the majority consistently demonstrating inadequate reporting on randomisation, allocation concealment, blinding, and power calculations. A narrative synthesis approach was assumed due to heterogeneity in study methods, interventions, target cohorts, and quality. Eleven key recommendations are suggested to advance future work in this area. PMID:28303161
Statistical segmentation of multidimensional brain datasets
NASA Astrophysics Data System (ADS)
Desco, Manuel; Gispert, Juan D.; Reig, Santiago; Santos, Andres; Pascau, Javier; Malpica, Norberto; Garcia-Barreno, Pedro
2001-07-01
This paper presents an automatic segmentation procedure for MRI neuroimages that overcomes part of the problems involved in multidimensional clustering techniques like partial volume effects (PVE), processing speed and difficulty of incorporating a priori knowledge. The method is a three-stage procedure: 1) Exclusion of background and skull voxels using threshold-based region growing techniques with fully automated seed selection. 2) Expectation Maximization algorithms are used to estimate the probability density function (PDF) of the remaining pixels, which are assumed to be mixtures of gaussians. These pixels can then be classified into cerebrospinal fluid (CSF), white matter and grey matter. Using this procedure, our method takes advantage of using the full covariance matrix (instead of the diagonal) for the joint PDF estimation. On the other hand, logistic discrimination techniques are more robust against violation of multi-gaussian assumptions. 3) A priori knowledge is added using Markov Random Field techniques. The algorithm has been tested with a dataset of 30 brain MRI studies (co-registered T1 and T2 MRI). Our method was compared with clustering techniques and with template-based statistical segmentation, using manual segmentation as a gold-standard. Our results were more robust and closer to the gold-standard.
Cerebral localization, then and now.
Marshall, John C; Fink, Gereon R
2003-11-01
We review some of the progress made in understanding the nature of functional specialization in the human brain, beginning with the anatomical claim that all mental faculties have their own distinct material substrate in different regions of the brain and the psychological claim that each mental faculty is characterized by the content domain with which it deals. This conceptual framework led behavioral neurologists to show how discrete brain lesions provoked different types of language, praxic, gnostic, spatial, and memory disorders. The simplest way of interpreting these anatomoclinical associations was to conjecture that the normal function (now impaired by brain damage) was localized within that lesioned region. It was also realized that cognitive impairments could arise from lesions that spared the functional centers themselves but disconnected them from other centers. Nonetheless, many neuroscientists remained skeptical of the entire paradigm. Accordingly, in the late 19th century functional localization began to be studied in the intact human brain by such techniques as measuring the temperature of different brain regions when different cognitive tasks were performed. During the 20th century these crude techniques gave way to positron emission tomography, functional magnetic resonance imaging, and magnetoencephalography. The relatively precise spatial and temporal resolution of modern methods now raises a crucial question: Do the functional localizations obtained by the anatomoclinical method converge with those implied by the functional neuroimaging of cognition in healthy volunteers? We then conclude with some recent suggestions that functional specialization is not such a fixed property of brain regions as previously supposed.
... tissues are working. Other imaging tests, such as magnetic resonance imaging ( MRI ) and computed tomography ( CT ) scans only reveal ... M, Hellwig S, Kloppel S, Weiller C. Functional neuroimaging: functional magnetic resonance imaging, positron emission tomography, and single-photon emission computed ...
Venous compressions of the nerves in the lower limbs.
Artico, M; Stevanato, G; Ionta, B; Cesaroni, A; Bianchi, E; Morselli, C; Grippaudo, F R
2012-06-01
The lower limbs are frequently involved in neurovascular compression syndromes, owing to their anatomical, vascular and muscular characteristics and to the orthostatic position. These syndromes were identified by exclusion, using neuroimaging techniques and treated by microsurgical techniques. Eight patients with a neurovascular compression syndrome due to venous vascular lesions in the lower limbs (popliteal fossa, proximal and medial third of the inferior limb, tarsal tunnel) were selected. The symptomatology was characterized by pain, Tinel's sign, hyperalgesia, allodynia, numbness along the nerve course and foot weakness: all were exacerbated by the standing position, thus suggesting a neurovascular compression syndrome. Diagnostic tools comprised Doppler ultrasonography, Electromyography, CT 3D and MRI. Treatment consisted of microsurgery with neurovascular dissection. Following surgical treatment, rapid pain relief and a partial recovery of neurological deficits (including the ability to walk) was observed within 8-10 months. An early diagnosis of NCS using various neuroimaging techniques and prompt treatment may improve the response to surgical therapy. The aim of the case studies described is to improve understanding of these pathologies thus enabling correct clinical decisions.
Wang, Jiaojian; Yang, Yong; Fan, Lingzhong; Xu, Jinping; Li, Changhai; Liu, Yong; Fox, Peter T; Eickhoff, Simon B; Yu, Chunshui; Jiang, Tianzi
2015-01-01
The superior parietal lobule (SPL) plays a pivotal role in many cognitive, perceptive, and motor-related processes. This implies that a mosaic of distinct functional and structural subregions may exist in this area. Recent studies have demonstrated that the ongoing spontaneous fluctuations in the brain at rest are highly structured and, like coactivation patterns, reflect the integration of cortical locations into long-distance networks. This suggests that the internal differentiation of a complex brain region may be revealed by interaction patterns that are reflected in different neuroimaging modalities. On the basis of this perspective, we aimed to identify a convergent functional organization of the SPL using multimodal neuroimaging approaches. The SPL was first parcellated based on its structural connections as well as on its resting-state connectivity and coactivation patterns. Then, post hoc functional characterizations and connectivity analyses were performed for each subregion. The three types of connectivity-based parcellations consistently identified five subregions in the SPL of each hemisphere. The two anterior subregions were found to be primarily involved in action processes and in visually guided visuomotor functions, whereas the three posterior subregions were primarily associated with visual perception, spatial cognition, reasoning, working memory, and attention. This parcellation scheme for the SPL was further supported by revealing distinct connectivity patterns for each subregion in all the used modalities. These results thus indicate a convergent functional architecture of the SPL that can be revealed based on different types of connectivity and is reflected by different functions and interactions. © 2014 Wiley Periodicals, Inc.
CoSMoMVPA: Multi-Modal Multivariate Pattern Analysis of Neuroimaging Data in Matlab/GNU Octave.
Oosterhof, Nikolaas N; Connolly, Andrew C; Haxby, James V
2016-01-01
Recent years have seen an increase in the popularity of multivariate pattern (MVP) analysis of functional magnetic resonance (fMRI) data, and, to a much lesser extent, magneto- and electro-encephalography (M/EEG) data. We present CoSMoMVPA, a lightweight MVPA (MVP analysis) toolbox implemented in the intersection of the Matlab and GNU Octave languages, that treats both fMRI and M/EEG data as first-class citizens. CoSMoMVPA supports all state-of-the-art MVP analysis techniques, including searchlight analyses, classification, correlations, representational similarity analysis, and the time generalization method. These can be used to address both data-driven and hypothesis-driven questions about neural organization and representations, both within and across: space, time, frequency bands, neuroimaging modalities, individuals, and species. It uses a uniform data representation of fMRI data in the volume or on the surface, and of M/EEG data at the sensor and source level. Through various external toolboxes, it directly supports reading and writing a variety of fMRI and M/EEG neuroimaging formats, and, where applicable, can convert between them. As a result, it can be integrated readily in existing pipelines and used with existing preprocessed datasets. CoSMoMVPA overloads the traditional volumetric searchlight concept to support neighborhoods for M/EEG and surface-based fMRI data, which supports localization of multivariate effects of interest across space, time, and frequency dimensions. CoSMoMVPA also provides a generalized approach to multiple comparison correction across these dimensions using Threshold-Free Cluster Enhancement with state-of-the-art clustering and permutation techniques. CoSMoMVPA is highly modular and uses abstractions to provide a uniform interface for a variety of MVP measures. Typical analyses require a few lines of code, making it accessible to beginner users. At the same time, expert programmers can easily extend its functionality. CoSMoMVPA comes with extensive documentation, including a variety of runnable demonstration scripts and analysis exercises (with example data and solutions). It uses best software engineering practices including version control, distributed development, an automated test suite, and continuous integration testing. It can be used with the proprietary Matlab and the free GNU Octave software, and it complies with open source distribution platforms such as NeuroDebian. CoSMoMVPA is Free/Open Source Software under the permissive MIT license. Website: http://cosmomvpa.org Source code: https://github.com/CoSMoMVPA/CoSMoMVPA.
CoSMoMVPA: Multi-Modal Multivariate Pattern Analysis of Neuroimaging Data in Matlab/GNU Octave
Oosterhof, Nikolaas N.; Connolly, Andrew C.; Haxby, James V.
2016-01-01
Recent years have seen an increase in the popularity of multivariate pattern (MVP) analysis of functional magnetic resonance (fMRI) data, and, to a much lesser extent, magneto- and electro-encephalography (M/EEG) data. We present CoSMoMVPA, a lightweight MVPA (MVP analysis) toolbox implemented in the intersection of the Matlab and GNU Octave languages, that treats both fMRI and M/EEG data as first-class citizens. CoSMoMVPA supports all state-of-the-art MVP analysis techniques, including searchlight analyses, classification, correlations, representational similarity analysis, and the time generalization method. These can be used to address both data-driven and hypothesis-driven questions about neural organization and representations, both within and across: space, time, frequency bands, neuroimaging modalities, individuals, and species. It uses a uniform data representation of fMRI data in the volume or on the surface, and of M/EEG data at the sensor and source level. Through various external toolboxes, it directly supports reading and writing a variety of fMRI and M/EEG neuroimaging formats, and, where applicable, can convert between them. As a result, it can be integrated readily in existing pipelines and used with existing preprocessed datasets. CoSMoMVPA overloads the traditional volumetric searchlight concept to support neighborhoods for M/EEG and surface-based fMRI data, which supports localization of multivariate effects of interest across space, time, and frequency dimensions. CoSMoMVPA also provides a generalized approach to multiple comparison correction across these dimensions using Threshold-Free Cluster Enhancement with state-of-the-art clustering and permutation techniques. CoSMoMVPA is highly modular and uses abstractions to provide a uniform interface for a variety of MVP measures. Typical analyses require a few lines of code, making it accessible to beginner users. At the same time, expert programmers can easily extend its functionality. CoSMoMVPA comes with extensive documentation, including a variety of runnable demonstration scripts and analysis exercises (with example data and solutions). It uses best software engineering practices including version control, distributed development, an automated test suite, and continuous integration testing. It can be used with the proprietary Matlab and the free GNU Octave software, and it complies with open source distribution platforms such as NeuroDebian. CoSMoMVPA is Free/Open Source Software under the permissive MIT license. Website: http://cosmomvpa.org Source code: https://github.com/CoSMoMVPA/CoSMoMVPA PMID:27499741
Assessing the effects of common variation in the FOXP2 gene on human brain structure.
Hoogman, Martine; Guadalupe, Tulio; Zwiers, Marcel P; Klarenbeek, Patricia; Francks, Clyde; Fisher, Simon E
2014-01-01
The FOXP2 transcription factor is one of the most well-known genes to have been implicated in developmental speech and language disorders. Rare mutations disrupting the function of this gene have been described in different families and cases. In a large three-generation family carrying a missense mutation, neuroimaging studies revealed significant effects on brain structure and function, most notably in the inferior frontal gyrus, caudate nucleus, and cerebellum. After the identification of rare disruptive FOXP2 variants impacting on brain structure, several reports proposed that common variants at this locus may also have detectable effects on the brain, extending beyond disorder into normal phenotypic variation. These neuroimaging genetics studies used groups of between 14 and 96 participants. The current study assessed effects of common FOXP2 variants on neuroanatomy using voxel-based morphometry (VBM) and volumetric techniques in a sample of >1300 people from the general population. In a first targeted stage we analyzed single nucleotide polymorphisms (SNPs) claimed to have effects in prior smaller studies (rs2253478, rs12533005, rs2396753, rs6980093, rs7784315, rs17137124, rs10230558, rs7782412, rs1456031), beginning with regions proposed in the relevant papers, then assessing impact across the entire brain. In the second gene-wide stage, we tested all common FOXP2 variation, focusing on volumetry of those regions most strongly implicated from analyses of rare disruptive mutations. Despite using a sample that is more than 10 times that used for prior studies of common FOXP2 variation, we found no evidence for effects of SNPs on variability in neuroanatomy in the general population. Thus, the impact of this gene on brain structure may be largely limited to extreme cases of rare disruptive alleles. Alternatively, effects of common variants at this gene exist but are too subtle to be detected with standard volumetric techniques.
Torgerson, Carinna M; Quinn, Catherine; Dinov, Ivo; Liu, Zhizhong; Petrosyan, Petros; Pelphrey, Kevin; Haselgrove, Christian; Kennedy, David N; Toga, Arthur W; Van Horn, John Darrell
2015-03-01
Under the umbrella of the National Database for Clinical Trials (NDCT) related to mental illnesses, the National Database for Autism Research (NDAR) seeks to gather, curate, and make openly available neuroimaging data from NIH-funded studies of autism spectrum disorder (ASD). NDAR has recently made its database accessible through the LONI Pipeline workflow design and execution environment to enable large-scale analyses of cortical architecture and function via local, cluster, or "cloud"-based computing resources. This presents a unique opportunity to overcome many of the customary limitations to fostering biomedical neuroimaging as a science of discovery. Providing open access to primary neuroimaging data, workflow methods, and high-performance computing will increase uniformity in data collection protocols, encourage greater reliability of published data, results replication, and broaden the range of researchers now able to perform larger studies than ever before. To illustrate the use of NDAR and LONI Pipeline for performing several commonly performed neuroimaging processing steps and analyses, this paper presents example workflows useful for ASD neuroimaging researchers seeking to begin using this valuable combination of online data and computational resources. We discuss the utility of such database and workflow processing interactivity as a motivation for the sharing of additional primary data in ASD research and elsewhere.
A longitudinal model for functional connectivity networks using resting-state fMRI.
Hart, Brian; Cribben, Ivor; Fiecas, Mark
2018-06-04
Many neuroimaging studies collect functional magnetic resonance imaging (fMRI) data in a longitudinal manner. However, the current fMRI literature lacks a general framework for analyzing functional connectivity (FC) networks in fMRI data obtained from a longitudinal study. In this work, we build a novel longitudinal FC model using a variance components approach. First, for all subjects' visits, we account for the autocorrelation inherent in the fMRI time series data using a non-parametric technique. Second, we use a generalized least squares approach to estimate 1) the within-subject variance component shared across the population, 2) the baseline FC strength, and 3) the FC's longitudinal trend. Our novel method for longitudinal FC networks seeks to account for the within-subject dependence across multiple visits, the variability due to the subjects being sampled from a population, and the autocorrelation present in fMRI time series data, while restricting the number of parameters in order to make the method computationally feasible and stable. We develop a permutation testing procedure to draw valid inference on group differences in the baseline FC network and change in FC over longitudinal time between a set of patients and a comparable set of controls. To examine performance, we run a series of simulations and apply the model to longitudinal fMRI data collected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Overall, we found no difference in the global FC network between Alzheimer's disease patients and healthy controls, but did find differing local aging patterns in the FC between the left hippocampus and the posterior cingulate cortex. Copyright © 2018 Elsevier Inc. All rights reserved.
ERIC Educational Resources Information Center
de Guibert, Clement; Maumet, Camille; Jannin, Pierre; Ferre, Jean-Christophe; Treguier, Catherine; Barillot, Christian; Le Rumeur, Elisabeth; Allaire, Catherine; Biraben, Arnaud
2011-01-01
Atypical functional lateralization and specialization for language have been proposed to account for developmental language disorders, yet results from functional neuroimaging studies are sparse and inconsistent. This functional magnetic resonance imaging study compared children with a specific subtype of specific language impairment affecting…
Uga, Minako; Saito, Toshiyuki; Sano, Toshifumi; Yokota, Hidenori; Oguro, Keiji; Rizki, Edmi Edison; Mizutani, Tsutomu; Katura, Takusige; Dan, Ippeita; Watanabe, Eiju
2014-05-01
Functional near-infrared spectroscopy (fNIRS) is a neuroimaging technique for the noninvasive monitoring of human brain activation states utilizing the coupling between neural activity and regional cerebral hemodynamics. Illuminators and detectors, together constituting optodes, are placed on the scalp, but due to the presence of head tissues, an inter-optode distance of more than 2.5cm is necessary to detect cortical signals. Although direct cortical monitoring with fNIRS has been pursued, a high-resolution visualization of hemodynamic changes associated with sensory, motor and cognitive neural responses directly from the cortical surface has yet to be realized. To acquire robust information on the hemodynamics of the cortex, devoid of signal complications in transcranial measurement, we devised a functional near-infrared cortical imaging (fNCI) technique. Here we demonstrate the first direct functional measurement of temporal and spatial patterns of cortical hemodynamics using the fNCI technique. For fNCI, inter-optode distance was set at 5mm, and light leakage from illuminators was prevented by a special optode holder made of a light-shielding rubber sheet. fNCI successfully detected the somatotopy of pig nostril sensation, as assessed in comparison with concurrent and sequential somatosensory-evoked potential (SEP) measurements on the same stimulation sites. Accordingly, the fNCI system realized a direct cortical hemodynamic measurement with a spatial resolution comparable to that of SEP mapping on the rostral region of the pig brain. This study provides an important initial step toward realizing functional cortical hemodynamic monitoring during neurosurgery of human brains. Copyright © 2014. Published by Elsevier Inc.
Bhattacharyya, Sagnik; Atakan, Zerrin; Martin-Santos, Rocio; Crippa, Jose A; McGuire, Philip K
2012-01-01
Pharmacological challenge in conjunction with neuroimaging techniques has been employed for over two decades now to understand the neural basis of the cognitive, emotional and symptomatic effects of the main ingredients of cannabis, the most widely used illicit drug in the world. This selective critical review focuses on the human neuroimaging studies investigating the effects of delta-9- tetrahydrocannabinol (THC) and cannabidiol (CBD), the two main cannabinoids of interest present in the extract of the cannabis plant. These studies suggest that consistent with the polymorphic and heterogeneous nature of the effects of cannabis, THC and CBD have distinct and often opposing effects on widely distributed neural networks that include medial temporal and prefrontal cortex and striatum, brain regions that are rich in cannabinoid receptors and implicated in the pathophysiology of psychosis. They help elucidate the neurocognitive mechanisms underlying the acute induction of psychotic symptoms by cannabis and provide mechanistic understanding underlying the potential role of CBD as an anxiolytic and antipsychotic. Although there are ethical and methodological caveats, pharmacological neuroimaging studies such as those reviewed here may not only help model different aspects of the psychopathology of mental disorders such as schizophrenia and offer insights into their underlying mechanisms, but may suggest potentially new therapeutic targets for drug discovery.
Concepts of Connectivity and Human Epileptic Activity
Lemieux, Louis; Daunizeau, Jean; Walker, Matthew C.
2011-01-01
This review attempts to place the concept of connectivity from increasingly sophisticated neuroimaging data analysis methodologies within the field of epilepsy research. We introduce the more principled connectivity terminology developed recently in neuroimaging and review some of the key concepts related to the characterization of propagation of epileptic activity using what may be called traditional correlation-based studies based on EEG. We then show how essentially similar methodologies, and more recently models addressing causality, have been used to characterize whole-brain and regional networks using functional MRI data. Following a discussion of our current understanding of the neuronal system aspects of the onset and propagation of epileptic discharges and seizures, we discuss the most advanced and ambitious framework to attempt to fully characterize epileptic networks based on neuroimaging data. PMID:21472027
Functional specificity for high-level linguistic processing in the human brain.
Fedorenko, Evelina; Behr, Michael K; Kanwisher, Nancy
2011-09-27
Neuroscientists have debated for centuries whether some regions of the human brain are selectively engaged in specific high-level mental functions or whether, instead, cognition is implemented in multifunctional brain regions. For the critical case of language, conflicting answers arise from the neuropsychological literature, which features striking dissociations between deficits in linguistic and nonlinguistic abilities, vs. the neuroimaging literature, which has argued for overlap between activations for linguistic and nonlinguistic processes, including arithmetic, domain general abilities like cognitive control, and music. Here, we use functional MRI to define classic language regions functionally in each subject individually and then examine the response of these regions to the nonlinguistic functions most commonly argued to engage these regions: arithmetic, working memory, cognitive control, and music. We find little or no response in language regions to these nonlinguistic functions. These data support a clear distinction between language and other cognitive processes, resolving the prior conflict between the neuropsychological and neuroimaging literatures.
Wiłkość, Monika; Izdebski, Paweł; Żurawski, Bogdan
2017-01-01
Chemotherapy-induced cognitive deficits in patients with breast cancer, predominantly in attention and verbal memory, have been observed in numerous studies. These neuropsychological findings are corroborated by the results of neuroimaging studies. The aim of this paper was to survey the reports on cerebral structural and functional alterations in women with breast cancer treated with chemotherapy (CTx). First, we discuss the host-related and disease-related mechanisms underlying cognitive impairment after CTx. We point out the direct and indirect neurotoxic effect of cytostatics, which may cause: a damage to neurons or glial cells, changes in neurotransmitter levels, deregulation of the immune system and/or cytokine release. Second, we focus on the results of neuroimaging studies on brain structure and function that revealed decreased: density of grey matter, integrity of white matter and volume of multiple brain regions, as well as their lower activation during cognitive task performance. Finally, we concentrate on compensatory mechanisms, which activate additional brain areas or neural connection to reach the premorbid cognitive efficiency. PMID:28435392
Parasuraman, Raja; Jiang, Yang
2012-01-01
We describe the use of behavioral, neuroimaging, and genetic methods to examine individual differences in cognition and affect, guided by three criteria: (1) relevance to human performance in work and everyday settings; (2) interactions between working memory, decision-making, and affective processing; and (3) examination of individual differences. The results of behavioral, functional MRI (fMRI), event-related potential (ERP), and molecular genetic studies show that analyses at the group level often mask important findings associated with sub-groups of individuals. Dopaminergic/noradrenergic genes influencing prefrontal cortex activity contribute to inter-individual variation in working memory and decision behavior, including performance in complex simulations of military decision-making. The interactive influences of individual differences in anxiety, sensation seeking, and boredom susceptibility on evaluative decision-making can be systematically described using ERP and fMRI methods. We conclude that a multi-modal neuroergonomic approach to examining brain function (using both neuroimaging and molecular genetics) can be usefully applied to understanding individual differences in cognition and affect and has implications for human performance at work. PMID:21569853
Rauch, Scott L; Shin, Lisa M; Phelps, Elizabeth A
2006-08-15
The prevailing neurocircuitry models of anxiety disorders have been amygdalocentric in form. The bases for such models have progressed from theoretical considerations, extrapolated from research in animals, to in vivo human imaging data. For example, one current model of posttraumatic stress disorder (PTSD) has been highly influenced by knowledge from rodent fear conditioning research. Given the phenomenological parallels between fear conditioning and the pathogenesis of PTSD, we have proposed that PTSD is characterized by exaggerated amygdala responses (subserving exaggerated acquisition of fear associations and expression of fear responses) and deficient frontal cortical function (mediating deficits in extinction and the capacity to suppress attention/response to trauma-related stimuli), as well as deficient hippocampal function (mediating deficits in appreciation of safe contexts and explicit learning/memory). Neuroimaging studies have yielded convergent findings in support of this model. However, to date, neuroimaging investigations of PTSD have not principally employed conditioning and extinction paradigms per se. The recent development of such imaging probes now sets the stage for directly testing hypotheses regarding the neural substrates of fear conditioning and extinction abnormalities in PTSD.
Spatial Bayesian Latent Factor Regression Modeling of Coordinate-based Meta-analysis Data
Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D.; Nichols, Thomas E.
2017-01-01
Summary Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the paper are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to 1) identify areas of consistent activation; and 2) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterised as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. PMID:28498564
Eckert, Mark A; Teubner-Rhodes, Susan; Vaden, Kenneth I
2016-01-01
This review examines findings from functional neuroimaging studies of speech recognition in noise to provide a neural systems level explanation for the effort and fatigue that can be experienced during speech recognition in challenging listening conditions. Neuroimaging studies of speech recognition consistently demonstrate that challenging listening conditions engage neural systems that are used to monitor and optimize performance across a wide range of tasks. These systems appear to improve speech recognition in younger and older adults, but sustained engagement of these systems also appears to produce an experience of effort and fatigue that may affect the value of communication. When considered in the broader context of the neuroimaging and decision making literature, the speech recognition findings from functional imaging studies indicate that the expected value, or expected level of speech recognition given the difficulty of listening conditions, should be considered when measuring effort and fatigue. The authors propose that the behavioral economics or neuroeconomics of listening can provide a conceptual and experimental framework for understanding effort and fatigue that may have clinical significance.
Eckert, Mark A.; Teubner-Rhodes, Susan; Vaden, Kenneth I.
2016-01-01
This review examines findings from functional neuroimaging studies of speech recognition in noise to provide a neural systems level explanation for the effort and fatigue that can be experienced during speech recognition in challenging listening conditions. Neuroimaging studies of speech recognition consistently demonstrate that challenging listening conditions engage neural systems that are used to monitor and optimize performance across a wide range of tasks. These systems appear to improve speech recognition in younger and older adults, but sustained engagement of these systems also appears to produce an experience of effort and fatigue that may affect the value of communication. When considered in the broader context of the neuroimaging and decision making literature, the speech recognition findings from functional imaging studies indicate that the expected value, or expected level of speech recognition given the difficulty of listening conditions, should be considered when measuring effort and fatigue. We propose that the behavioral economics and/or neuroeconomics of listening can provide a conceptual and experimental framework for understanding effort and fatigue that may have clinical significance. PMID:27355759
Lateralized theta wave connectivity and language performance in 2- to 5-year-old children.
Kikuchi, Mitsuru; Shitamichi, Kiyomi; Yoshimura, Yuko; Ueno, Sanae; Remijn, Gerard B; Hirosawa, Tetsu; Munesue, Toshio; Tsubokawa, Tsunehisa; Haruta, Yasuhiro; Oi, Manabu; Higashida, Haruhiro; Minabe, Yoshio
2011-10-19
Recent neuroimaging studies support the view that a left-lateralized brain network is crucial for language development in children. However, no previous studies have demonstrated a clear link between lateralized brain functional network and language performance in preschool children. Magnetoencephalography (MEG) is a noninvasive brain imaging technique and is a practical neuroimaging method for use in young children. MEG produces a reference-free signal, and is therefore an ideal tool to compute coherence between two distant cortical rhythms. In the present study, using a custom child-sized MEG system, we investigated brain networks while 78 right-handed preschool human children (32-64 months; 96% were 3-4 years old) listened to stories with moving images. The results indicated that left dominance of parietotemporal coherence in theta band activity (6-8 Hz) was specifically correlated with higher performance of language-related tasks, whereas this laterality was not correlated with nonverbal cognitive performance, chronological age, or head circumference. Power analyses did not reveal any specific frequencies that contributed to higher language performance. Our results suggest that it is not the left dominance in theta oscillation per se, but the left-dominant phase-locked connectivity via theta oscillation that contributes to the development of language ability in young children.
Tremblay, Pascale; Gracco, Vincent L
2009-05-01
An emerging theoretical perspective, largely based on neuroimaging studies, suggests that the pre-SMA is involved in planning cognitive aspects of motor behavior and language, such as linguistic and non-linguistic response selection. Neuroimaging studies, however, cannot indicate whether a brain region is equally important to all tasks in which it is activated. In the present study, we tested the hypothesis that the pre-SMA is an important component of response selection, using an interference technique. High frequency repetitive TMS (10 Hz) was used to interfere with the functioning of the pre-SMA during tasks requiring selection of words and oral gestures under different selection modes (forced, volitional) and attention levels (high attention, low attention). Results show that TMS applied to the pre-SMA interferes selectively with the volitional selection condition, resulting in longer RTs. The low- and high-attention forced selection conditions were unaffected by TMS, demonstrating that the pre-SMA is sensitive to selection mode but not attentional demands. TMS similarly affected the volitional selection of words and oral gestures, reflecting the response-independent nature of the pre-SMA contribution to response selection. The implications of these results are discussed.
Alves, Gilberto Sousa; de Carvalho, Luiza de Amorim; Sudo, Felipe Kenji; Briand, Lucas; Laks, Jerson; Engelhardt, Eliasz
2017-01-01
ABSTRACT. The last decade has witnessed substantial progress in acquiring diagnostic biomarkers for the diagnostic workup of cerebrovascular disease (CVD). Advanced neuroimaging methods not only provide a strategic contribution for the differential diagnosis of vascular dementia (VaD) and vascular cognitive impairment (VCI), but also help elucidate the pathophysiological mechanisms ultimately leading to small vessel disease (SVD) throughout its course. Objective: In this review, the novel imaging methods, both structural and metabolic, were summarized and their impact on the diagnostic workup of age-related CVD was analysed. Methods: An electronic search between January 2010 and 2017 was carried out on PubMed/MEDLINE, Institute for Scientific Information Web of Knowledge and EMBASE. Results: The use of full functional multimodality in simultaneous Magnetic Resonance (MR)/Positron emission tomography (PET) may potentially improve the clinical characterization of VCI-VaD; for structural imaging, MRI at 3.0 T enables higher-resolution scanning with greater imaging matrices, thinner slices and more detail on the anatomical structure of vascular lesions. Conclusion: Although the importance of most of these techniques in the clinical setting has yet to be recognized, there is great expectancy in achieving earlier and more refined therapeutic interventions for the effective management of VCI-VaD. PMID:29354214
Thompson, Paul M.
2016-01-01
Sex differences in brain development and aging are important to identify, as they may help to understand risk factors and outcomes in brain disorders that are more prevalent in one sex compared with the other. Brain imaging techniques have advanced rapidly in recent years, yielding detailed structural and functional maps of the living brain. Even so, studies are often limited in sample size, and inconsistent findings emerge, one example being varying findings regarding sex differences in the size of the corpus callosum. More recently, large‐scale neuroimaging consortia such as the Enhancing Neuro Imaging Genetics through Meta Analysis Consortium have formed, pooling together expertise, data, and resources from hundreds of institutions around the world to ensure adequate power and reproducibility. These initiatives are helping us to better understand how brain structure is affected by development, disease, and potential modulators of these effects, including sex. This review highlights some established and disputed sex differences in brain structure across the life span, as well as pitfalls related to interpreting sex differences in health and disease. We also describe sex‐related findings from the ENIGMA consortium, and ongoing efforts to better understand sex differences in brain circuitry. © 2016 The Authors. Journal of Neuroscience Research Published by Wiley Periodicals, Inc. PMID:27870421
Insomnia Disorder and Brain's Default-Mode Network.
Marques, Daniel Ruivo; Gomes, Ana Allen; Caetano, Gina; Castelo-Branco, Miguel
2018-06-09
Insomnia disorder (ID) is a prevalent sleep disorder that significantly compromises the physical and mental health of individuals. This article reviews novel approaches in the study of brain networks and impaired function in ID through the application of modern neuroimaging techniques such as functional magnetic resonance imaging (fMRI). The default-mode network (DMN) is presumed to be correlated with self-referential information processing, and it appears to be altered or unbalanced in insomnia. A growing body of evidence suggests the lack of deactivation of brain regions comprising the DMN when insomnia patients are at rest. Moreover, core areas of the DMN demonstrate greater activation in insomnia patients when compared to healthy controls in self-referential related tasks. Despite the few studies on the topic, underpinning the correlation between abnormal DMN activity and ID deserves further attention in the future. Implications for therapeutics are briefly outlined.
Crunelle, Cleo L; Veltman, Dick J; Booij, Jan; Emmerik – van Oortmerssen, Katelijne; den Brink, Wim
2012-01-01
Stimulant dependence is associated with neuropsychological impairments. Here, we summarize and integrate the existing neuroimaging literature on the neural substrates of neuropsychological (dys)function in stimulant dependence, including cocaine, (meth-)amphetamine, ecstasy and nicotine dependence, and excessive caffeine use, comparing stimulant abusers (SAs) to nondrug using healthy controls (HCs). Despite some inconsistencies, most studies indicated altered brain activation in prefrontal cortex (PFC) and insula in response to reward and punishment, and higher limbic and anterior cingulate cortex (ACC)/PFC activation during craving and attentional bias paradigms in SAs compared with HCs. Impulsivity in SAs was associated with lower ACC and presupplementary motor area activity compared with HCs, and related to both ventral (amygdala, ventrolateral PFC, insula) and dorsal (dorsolateral PFC, dorsal ACC, posterior parietal cortex) systems. Decision making in SAs was associated with low dorsolateral PFC activity and high orbitofrontal activity. Finally, executive function in SAs was associated with lower activation in frontotemporal regions and higher activation in premotor cortex compared with HCs. It is concluded that the lower activations compared with HCs are likely to reflect the neural substrate of impaired neurocognitive functions, whereas higher activations in SAs compared with HCs are likely to reflect compensatory cognitive control mechanisms to keep behavioral task performance to a similar level as in HCs. However, before final conclusions can be drawn, additional research is needed using neuroimaging in SAs and HCs using larger and more homogeneous samples as well as more comparable task paradigms, study designs, and statistical analyses. PMID:22950052
Hamilton, J. Paul; Chen, Michael C.; Gotlib, Ian H.
2012-01-01
Recent research detailing the intrinsic functional organization of the brain provides a unique and useful framework to gain a better understanding of the neural bases of Major Depressive Disorder (MDD). In this review, we first present a brief history of neuroimaging research that has increased our understanding of the functional macro-architecture of the brain. From this macro-architectural perspective, we examine the extant body of functional neuroimaging research assessing MDD with a specific emphasis on the contributions of default-mode, executive, and salience networks in this debilitating disorder. Next, we describe recent investigations conducted in our laboratory in which we explicitly adopt a neural-systems perspective in examining the relations among these networks in MDD. Finally, we offer directions for future research that we believe will facilitate the development of more detailed and integrative models of neural dysfunction in depression. PMID:23477309
Madden, David J.
2007-01-01
Older adults are often slower and less accurate than are younger adults in performing visual-search tasks, suggesting an age-related decline in attentional functioning. Age-related decline in attention, however, is not entirely pervasive. Visual search that is based on the observer’s expectations (i.e., top-down attention) is relatively preserved as a function of adult age. Neuroimaging research suggests that age-related decline occurs in the structure and function of brain regions mediating the visual sensory input, whereas activation of regions in the frontal and parietal lobes is often greater for older adults than for younger adults. This increased activation may represent an age-related increase in the role of top-down attention during visual tasks. To obtain a more complete account of age-related decline and preservation of visual attention, current research is beginning to explore the relation of neuroimaging measures of brain structure and function to behavioral measures of visual attention. PMID:18080001
Basic Emotions in Human Neuroscience: Neuroimaging and Beyond
Celeghin, Alessia; Diano, Matteo; Bagnis, Arianna; Viola, Marco; Tamietto, Marco
2017-01-01
The existence of so-called ‘basic emotions’ and their defining attributes represents a long lasting and yet unsettled issue in psychology. Recently, neuroimaging evidence, especially related to the advent of neuroimaging meta-analytic methods, has revitalized this debate in the endeavor of systems and human neuroscience. The core theme focuses on the existence of unique neural bases that are specific and characteristic for each instance of basic emotion. Here we review this evidence, outlining contradictory findings, strengths and limits of different approaches. Constructionism dismisses the existence of dedicated neural structures for basic emotions, considering that the assumption of a one-to-one relationship between neural structures and their functions is central to basic emotion theories. While these critiques are useful to pinpoint current limitations of basic emotions theories, we argue that they do not always appear equally generative in fostering new testable accounts on how the brain relates to affective functions. We then consider evidence beyond PET and fMRI, including results concerning the relation between basic emotions and awareness and data from neuropsychology on patients with focal brain damage. Evidence from lesion studies are indeed particularly informative, as they are able to bring correlational evidence typical of neuroimaging studies to causation, thereby characterizing which brain structures are necessary for, rather than simply related to, basic emotion processing. These other studies shed light on attributes often ascribed to basic emotions, such as automaticity of perception, quick onset, and brief duration. Overall, we consider that evidence in favor of the neurobiological underpinnings of basic emotions outweighs dismissive approaches. In fact, the concept of basic emotions can still be fruitful, if updated to current neurobiological knowledge that overcomes traditional one-to-one localization of functions in the brain. In particular, we propose that the structure-function relationship between brain and emotions is better described in terms of pluripotentiality, which refers to the fact that one neural structure can fulfill multiple functions, depending on the functional network and pattern of co-activations displayed at any given moment. PMID:28883803
Altered Connectivity and Action Model Formation in Autism Is Autism
Mostofsky, Stewart H.; Ewen, Joshua B.
2014-01-01
Internal action models refer to sensory-motor programs that form the brain basis for a wide range of skilled behavior and for understanding others’ actions. Development of these action models, particularly those reliant on visual cues from the external world, depends on connectivity between distant brain regions. Studies of children with autism reveal anomalous patterns of motor learning and impaired execution of skilled motor gestures. These findings robustly correlate with measures of social and communicative function, suggesting that anomalous action model formation may contribute to impaired development of social and communicative (as well as motor) capacity in autism. Examination of the pattern of behavioral findings, as well as convergent data from neuroimaging techniques, further suggests that autism-associated action model formation may be related to abnormalities in neural connectivity, particularly decreased function of long-range connections. This line of study can lead to important advances in understanding the neural basis of autism and, more critically, can be used to guide effective therapies targeted at improving social, communicative, and motor function. PMID:21467306
Asymmetries of the human social brain in the visual, auditory and chemical modalities
Brancucci, Alfredo; Lucci, Giuliana; Mazzatenta, Andrea; Tommasi, Luca
2008-01-01
Structural and functional asymmetries are present in many regions of the human brain responsible for motor control, sensory and cognitive functions and communication. Here, we focus on hemispheric asymmetries underlying the domain of social perception, broadly conceived as the analysis of information about other individuals based on acoustic, visual and chemical signals. By means of these cues the brain establishes the border between ‘self’ and ‘other’, and interprets the surrounding social world in terms of the physical and behavioural characteristics of conspecifics essential for impression formation and for creating bonds and relationships. We show that, considered from the standpoint of single- and multi-modal sensory analysis, the neural substrates of the perception of voices, faces, gestures, smells and pheromones, as evidenced by modern neuroimaging techniques, are characterized by a general pattern of right-hemispheric functional asymmetry that might benefit from other aspects of hemispheric lateralization rather than constituting a true specialization for social information. PMID:19064350
Feasibility of functional neuroimaging to understand adolescent women's sexual decision making.
Hensel, Devon J; Hummer, Tom A; Acrurio, Lindsay R; James, Thomas W; Fortenberry, J Dennis
2015-04-01
For young women, new sexual experiences normatively increase after puberty and coincide with extensive changes to brain regions governing self-regulation of risk behavior. These neurodevelopmental changes could leave some young women vulnerable for negative sexual outcomes, including sexually transmitted infection and unintended pregnancy. We evaluated the feasibility of using functional neuroimaging to understand the sexual decision making of adolescent women. Adolescent women (N = 14; 14-15 years) completed enrollment interviews, a neuroimaging task gauging neural activation to appetitive stimuli, and 30 days of prospective diaries following the scan characterizing daily affect and sexual behaviors. Descriptive and inferential statistics assessed the association between imaging and behavioral data. Young women were highly compliant with neuroimaging and diary protocol. Neural activity in a cognitive-affective network, including prefrontal and anterior cingulate regions, was significantly greater during low-risk decisions. Compared with other decisions, high-risk sexual decisions elicited greater activity in the anterior cingulate, and low-risk sexual decision elicited greater activity in regions of the visual cortex. Young women's sexual decision ratings were linked to their sexual history characteristics and daily self-reports of sexual emotions and behaviors. It is feasible to recruit and retain a cohort of female participants to perform a functional magnetic resonance imaging task focused on making decisions about sex, on the basis of varying levels of hypothetical sexual risk, and to complete longitudinal prospective diaries following this task. Preliminary evidence suggests that risk level differentially impacts brain activity related to sexual decision making in these women, which may be related to past and future sexual behaviors. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.
Polyanska, Liliana; Critchley, Hugo D; Rae, Charlotte L
2017-01-01
Tourette Syndrome (TS) is a neurodevelopmental condition characterized by chronic multiple tics, which are experienced as compulsive and 'unwilled'. Patients with TS can differ markedly in the frequency, severity, and bodily distribution of tics. Moreover, there are high comorbidity rates with attention deficit hyperactivity disorder (ADHD), obsessive compulsive disorder (OCD), anxiety disorders, and depression. This complex clinical profile may account for apparent variability of findings across neuroimaging studies that connect neural function to cognitive and motor behavior in TS. Here we crystalized information from neuroimaging regarding the functional circuitry of TS, and furthermore, tested specifically for neural determinants of tic severity, by applying activation likelihood estimation (ALE) meta-analyses to neuroimaging (activation) studies of TS. Fourteen task-based studies (13 fMRI and one H2O-PET) met rigorous inclusion criteria. These studies, encompassing 25 experiments and 651 participants, tested for differences between TS participants and healthy controls across cognitive, motor, perceptual and somatosensory domains. Relative to controls, TS participants showed distributed differences in the activation of prefrontal (inferior, middle, and superior frontal gyri), anterior cingulate, and motor preparation cortices (lateral premotor cortex and supplementary motor area; SMA). Differences also extended into sensory (somatosensory cortex and the lingual gyrus; V4); and temporo-parietal association cortices (posterior superior temporal sulcus, supramarginal gyrus, and retrosplenial cortex). Within TS participants, tic severity (reported using the Yale Global Tic Severity Scale; YGTSS) selectively correlated with engagement of SMA, precentral gyrus, and middle frontal gyrus across tasks. The dispersed involvement of multiple cortical regions with differences in functional reactivity may account for heterogeneity in the symptomatic expression of TS and its comorbidities. More specifically for tics and tic severity, the findings reinforce previously proposed contributions of premotor and lateral prefrontal cortices to tic expression.
Groppe, David M; Bickel, Stephan; Dykstra, Andrew R; Wang, Xiuyuan; Mégevand, Pierre; Mercier, Manuel R; Lado, Fred A; Mehta, Ashesh D; Honey, Christopher J
2017-04-01
Intracranial electrical recordings (iEEG) and brain stimulation (iEBS) are invaluable human neuroscience methodologies. However, the value of such data is often unrealized as many laboratories lack tools for localizing electrodes relative to anatomy. To remedy this, we have developed a MATLAB toolbox for intracranial electrode localization and visualization, iELVis. NEW METHOD: iELVis uses existing tools (BioImage Suite, FSL, and FreeSurfer) for preimplant magnetic resonance imaging (MRI) segmentation, neuroimaging coregistration, and manual identification of electrodes in postimplant neuroimaging. Subsequently, iELVis implements methods for correcting electrode locations for postimplant brain shift with millimeter-scale accuracy and provides interactive visualization on 3D surfaces or in 2D slices with optional functional neuroimaging overlays. iELVis also localizes electrodes relative to FreeSurfer-based atlases and can combine data across subjects via the FreeSurfer average brain. It takes 30-60min of user time and 12-24h of computer time to localize and visualize electrodes from one brain. We demonstrate iELVis's functionality by showing that three methods for mapping primary hand somatosensory cortex (iEEG, iEBS, and functional MRI) provide highly concordant results. COMPARISON WITH EXISTING METHODS: iELVis is the first public software for electrode localization that corrects for brain shift, maps electrodes to an average brain, and supports neuroimaging overlays. Moreover, its interactive visualizations are powerful and its tutorial material is extensive. iELVis promises to speed the progress and enhance the robustness of intracranial electrode research. The software and extensive tutorial materials are freely available as part of the EpiSurg software project: https://github.com/episurg/episurg. Copyright © 2017 Elsevier B.V. All rights reserved.
Nowinski, Wieslaw L; Belov, Dmitry
2003-09-01
The article introduces an atlas-assisted method and a tool called the Cerefy Neuroradiology Atlas (CNA), available over the Internet for neuroradiology and human brain mapping. The CNA contains an enhanced, extended, and fully segmented and labeled electronic version of the Talairach-Tournoux brain atlas, including parcelated gyri and Brodmann's areas. To our best knowledge, this is the first online, publicly available application with the Talairach-Tournoux atlas. The process of atlas-assisted neuroimage analysis is done in five steps: image data loading, Talairach landmark setting, atlas normalization, image data exploration and analysis, and result saving. Neuroimage analysis is supported by a near-real-time, atlas-to-data warping based on the Talairach transformation. The CNA runs on multiple platforms; is able to process simultaneously multiple anatomical and functional data sets; and provides functions for a rapid atlas-to-data registration, interactive structure labeling and annotating, and mensuration. It is also empowered with several unique features, including interactive atlas warping facilitating fine tuning of atlas-to-data fit, navigation on the triplanar formed by the image data and the atlas, multiple-images-in-one display with interactive atlas-anatomy-function blending, multiple label display, and saving of labeled and annotated image data. The CNA is useful for fast atlas-assisted analysis of neuroimage data sets. It increases accuracy and reduces time in localization analysis of activation regions; facilitates to communicate the information on the interpreted scans from the neuroradiologist to other clinicians and medical students; increases the neuroradiologist's confidence in terms of anatomy and spatial relationships; and serves as a user-friendly, public domain tool for neuroeducation. At present, more than 700 users from five continents have subscribed to the CNA.
Dewey, Rebecca Susan; Hall, Deborah A; Guest, Hannah; Prendergast, Garreth; Plack, Christopher J; Francis, Susan T
2018-03-09
Rodent studies indicate that noise exposure can cause permanent damage to synapses between inner hair cells and high-threshold auditory nerve fibers, without permanently altering threshold sensitivity. These demonstrations of what is commonly known as hidden hearing loss have been confirmed in several rodent species, but the implications for human hearing are unclear. Our Medical Research Council-funded program aims to address this unanswered question, by investigating functional consequences of the damage to the human peripheral and central auditory nervous system that results from cumulative lifetime noise exposure. Behavioral and neuroimaging techniques are being used in a series of parallel studies aimed at detecting hidden hearing loss in humans. The planned neuroimaging study aims to (1) identify central auditory biomarkers associated with hidden hearing loss; (2) investigate whether there are any additive contributions from tinnitus or diminished sound tolerance, which are often comorbid with hearing problems; and (3) explore the relation between subcortical functional magnetic resonance imaging (fMRI) measures and the auditory brainstem response (ABR). Individuals aged 25 to 40 years with pure tone hearing thresholds ≤20 dB hearing level over the range 500 Hz to 8 kHz and no contraindications for MRI or signs of ear disease will be recruited into the study. Lifetime noise exposure will be estimated using an in-depth structured interview. Auditory responses throughout the central auditory system will be recorded using ABR and fMRI. Analyses will focus predominantly on correlations between lifetime noise exposure and auditory response characteristics. This paper reports the study protocol. The funding was awarded in July 2013. Enrollment for the study described in this protocol commenced in February 2017 and was completed in December 2017. Results are expected in 2018. This challenging and comprehensive study will have the potential to impact diagnostic procedures for hidden hearing loss, enabling early identification of noise-induced auditory damage via the detection of changes in central auditory processing. Consequently, this will generate the opportunity to give personalized advice regarding provision of ear defense and monitoring of further damage, thus reducing the incidence of noise-induced hearing loss. ©Rebecca Susan Dewey, Deborah A Hall, Hannah Guest, Garreth Prendergast, Christopher J Plack, Susan T Francis. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 09.03.2018.
Nordberg, A; Miniscalco, C; Lohmander, A; Himmelmann, K
2013-02-01
To describe speech ability in a population-based study of children with cerebral palsy (CP), in relation to CP subtype, motor function, cognitive level and neuroimaging findings. A retrospective chart review of 129 children (66 girls, 63 boys) with CP, born in 1999-2002, was carried out. Speech ability and background information, such as type of CP, motor function, cognitive level and neuroimaging data, were collected and analysed. Speech disorders were found in 21% of the children and were present in all types of CP. Forty-one per cent of the children with speech disorders also had mental retardation, and 42% were able to walk independently. A further 32% of the children were nonverbal, and maldevelopment and basal ganglia lesions were most common in this group. The remaining 47% had no speech disorders, and this group was most likely to display white matter lesions of immaturity. More than half of the children in this CP cohort had a speech disorder (21%) or were nonverbal (32%). Speech ability was related to the type of CP, gross motor function, the presence of mental retardation and the localization of brain maldevelopment and lesions. Neuroimaging results differed between the three speech ability groups. ©2012 The Author(s)/Acta Paediatrica ©2012 Foundation Acta Paediatrica.
Santiesteban, Idalmis; Banissy, Michael J; Catmur, Caroline; Bird, Geoffrey
2015-10-01
Although neuroimaging studies have consistently identified the temporoparietal junction (TPJ) as a key brain region involved in social cognition, the literature is far from consistent with respect to lateralization of function. For example, during theory-of-mind tasks bilateral TPJ activation is found in some studies but only right hemisphere activation in others. Visual perspective-taking and imitation inhibition, which have been argued to recruit the same socio-cognitive processes as theory of mind, are associated with unilateral activation of either left TPJ (perspective taking) or right TPJ (imitation inhibition). The present study investigated the functional lateralization of TPJ involvement in the above three socio-cognitive abilities using transcranial direct current stimulation. Three groups of healthy adults received anodal stimulation over right TPJ, left TPJ or the occipital cortex prior to performing three tasks (imitation inhibition, visual perspective-taking and theory of mind). In contrast to the extant neuroimaging literature, our results suggest bilateral TPJ involvement in imitation inhibition and visual perspective-taking, while no effect of anodal stimulation was observed on theory of mind. The discrepancy between these findings and those obtained using neuroimaging highlight the efficacy of neurostimulation as a complementary methodological tool in cognitive neuroscience. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
Saykin, Andrew J.; Shen, Li; Foroud, Tatiana M.; Potkin, Steven G.; Swaminathan, Shanker; Kim, Sungeun; Risacher, Shannon L.; Nho, Kwangsik; Huentelman, Matthew J.; Craig, David W.; Thompson, Paul M.; Stein, Jason L.; Moore, Jason H.; Farrer, Lindsay A.; Green, Robert C.; Bertram, Lars; Jack, Clifford R.; Weiner, Michael W.
2010-01-01
The role of the Alzheimer’s Disease Neuroimaging Initiative Genetics Core is to facilitate the investigation of genetic influences on disease onset and trajectory as reflected in structural, functional, and molecular imaging changes; fluid biomarkers; and cognitive status. Major goals include (1) blood sample processing, genotyping, and dissemination, (2) genome-wide association studies (GWAS) of longitudinal phenotypic data, and (3) providing a central resource, point of contact and planning group for genetics within Alzheimer’s Disease Neuroimaging Initiative. Genome-wide array data have been publicly released and updated, and several neuroimaging GWAS have recently been reported examining baseline magnetic resonance imaging measures as quantitative phenotypes. Other preliminary investigations include copy number variation in mild cognitive impairment and Alzheimer’s disease and GWAS of baseline cerebrospinal fluid biomarkers and longitudinal changes on magnetic resonance imaging. Blood collection for RNA studies is a new direction. Genetic studies of longitudinal phenotypes hold promise for elucidating disease mechanisms and risk, development of therapeutic strategies, and refining selection criteria for clinical trials. PMID:20451875
Neuroimaging-based biomarkers in psychiatry: clinical opportunities of a paradigm shift.
Fu, Cynthia H Y; Costafreda, Sergi G
2013-09-01
Neuroimaging research has substantiated the functional and structural abnormalities underlying psychiatric disorders but has, thus far, failed to have a significant impact on clinical practice. Recently, neuroimaging-based diagnoses and clinical predictions derived from machine learning analysis have shown significant potential for clinical translation. This review introduces the key concepts of this approach, including how the multivariate integration of patterns of brain abnormalities is a crucial component. We survey recent findings that have potential application for diagnosis, in particular early and differential diagnoses in Alzheimer disease and schizophrenia, and the prediction of clinical response to treatment in depression. We discuss the specific clinical opportunities and the challenges for developing biomarkers for psychiatry in the absence of a diagnostic gold standard. We propose that longitudinal outcomes, such as early diagnosis and prediction of treatment response, offer definite opportunities for progress. We propose that efforts should be directed toward clinically challenging predictions in which neuroimaging may have added value, compared with the existing standard assessment. We conclude that diagnostic and prognostic biomarkers will be developed through the joint application of expert psychiatric knowledge in addition to advanced methods of analysis.
Multimodal Neuroimaging in Schizophrenia: Description and Dissemination.
Aine, C J; Bockholt, H J; Bustillo, J R; Cañive, J M; Caprihan, A; Gasparovic, C; Hanlon, F M; Houck, J M; Jung, R E; Lauriello, J; Liu, J; Mayer, A R; Perrone-Bizzozero, N I; Posse, S; Stephen, J M; Turner, J A; Clark, V P; Calhoun, Vince D
2017-10-01
In this paper we describe an open-access collection of multimodal neuroimaging data in schizophrenia for release to the community. Data were acquired from approximately 100 patients with schizophrenia and 100 age-matched controls during rest as well as several task activation paradigms targeting a hierarchy of cognitive constructs. Neuroimaging data include structural MRI, functional MRI, diffusion MRI, MR spectroscopic imaging, and magnetoencephalography. For three of the hypothesis-driven projects, task activation paradigms were acquired on subsets of ~200 volunteers which examined a range of sensory and cognitive processes (e.g., auditory sensory gating, auditory/visual multisensory integration, visual transverse patterning). Neuropsychological data were also acquired and genetic material via saliva samples were collected from most of the participants and have been typed for both genome-wide polymorphism data as well as genome-wide methylation data. Some results are also presented from the individual studies as well as from our data-driven multimodal analyses (e.g., multimodal examinations of network structure and network dynamics and multitask fMRI data analysis across projects). All data will be released through the Mind Research Network's collaborative informatics and neuroimaging suite (COINS).
Neural and mental hierarchies.
Wiest, Gerald
2012-01-01
The history of the sciences of the human brain and mind has been characterized from the beginning by two parallel traditions. The prevailing theory that still influences the way current neuroimaging techniques interpret brain function, can be traced back to classical localizational theories, which in turn go back to early phrenological theories. The other approach has its origins in the hierarchical neurological theories of Hughlings-Jackson, which have been influenced by the philosophical conceptions of Herbert Spencer. Another hallmark of the hierarchical tradition, which is also inherent to psychoanalytic metapsychology, is its deeply evolutionary perspective by taking both ontogenetic and phylogenetic trajectories into consideration. This article provides an outline on hierarchical concepts in brain and mind sciences, which contrast with current cognitivistic and non-hierarchical theories in the neurosciences.
Non-invasive neuroimaging using near-infrared light
NASA Technical Reports Server (NTRS)
Strangman, Gary; Boas, David A.; Sutton, Jeffrey P.
2002-01-01
This article reviews diffuse optical brain imaging, a technique that employs near-infrared light to non-invasively probe the brain for changes in parameters relating to brain function. We describe the general methodology, including types of measurements and instrumentation (including the tradeoffs inherent in the various instrument components), and the basic theory required to interpret the recorded data. A brief review of diffuse optical applications is included, with an emphasis on research that has been done with psychiatric populations. Finally, we discuss some practical issues and limitations that are relevant when conducting diffuse optical experiments. We find that, while diffuse optics can provide substantial advantages to the psychiatric researcher relative to the alternative brain imaging methods, the method remains substantially underutilized in this field.
Wiest, Gerald
2012-01-01
The history of the sciences of the human brain and mind has been characterized from the beginning by two parallel traditions. The prevailing theory that still influences the way current neuroimaging techniques interpret brain function, can be traced back to classical localizational theories, which in turn go back to early phrenological theories. The other approach has its origins in the hierarchical neurological theories of Hughlings-Jackson, which have been influenced by the philosophical conceptions of Herbert Spencer. Another hallmark of the hierarchical tradition, which is also inherent to psychoanalytic metapsychology, is its deeply evolutionary perspective by taking both ontogenetic and phylogenetic trajectories into consideration. This article provides an outline on hierarchical concepts in brain and mind sciences, which contrast with current cognitivistic and non-hierarchical theories in the neurosciences. PMID:23189066
[Possibilities of modern imaging technologies in early diagnosis of Alzheimer disease].
Unschuld, Paul G
2015-04-01
Recent advances in neuroimaging technology and image analysis algorithms have significantly contributed to a better understanding of spatial and temporal aspects of brain change associated with Alzheimer Disease. The current review will demonstrate how functional (fMRI) and structural magnetic resonance imaging (MRI) techniques may be used to identify distinct patterns of brain change associated with disease progression and also increased risk for Alzheimer Disease. Moreover, Positron Emission Tomography (PET) based measures of glucosemetabolism (Fluorodeoxyglucose, FDG) and Amyloid-beta plaque density (11-C-Pittsburgh Compound B, PiB and 18-F) will be reviewed regarding their diagnostic value for assessing the individual degree of Alzheimer -pathology and thus complement the information provided by MRI and other clinical measures.
Experimental Design and Interpretation of Functional Neuroimaging Studies of Cognitive Processes
Caplan, David
2008-01-01
This article discusses how the relation between experimental and baseline conditions in functional neuroimaging studies affects the conclusions that can be drawn from a study about the neural correlates of components of the cognitive system and about the nature and organization of those components. I argue that certain designs in common use—in particular the contrast of qualitatively different representations that are processed at parallel stages of a functional architecture—can never identify the neural basis of a cognitive operation and have limited use in providing information about the nature of cognitive systems. Other types of designs—such as ones that contrast representations that are computed in immediately sequential processing steps and ones that contrast qualitatively similar representations that are parametrically related within a single processing stage—are more easily interpreted. PMID:17979122
Brumback, T.; Castro, N.; Jacobus, J.; Tapert, S.
2016-01-01
Marijuana, behind only tobacco and alcohol, is the most popular recreational drug in America with prevalence rates of use rising over the past decade. A wide range of research has highlighted neurocognitive deficits associated with marijuana use, particularly when initiated during childhood or adolescence. Neuroimaging, describing alterations to brain structure and function, has begun to provide a picture of possible mechanisms associated with the deleterious effects of marijuana use. This chapter provides a neurodevelopmental framework from which recent data on brain structural and functional abnormalities associated with marijuana use is reviewed. Based on the current data, we provide aims for future studies to more clearly delineate the effects of marijuana on the developing brain and to define underlying mechanisms of the potential long-term negative consequences of marijuana use. PMID:27503447
Neural correlates of cognitive intervention in persons at risk of developing Alzheimer’s disease
Hosseini, S. M. Hadi; Kramer, Joel H.; Kesler, Shelli R.
2014-01-01
Cognitive training is an emergent approach that has begun to receive increased attention in recent years as a non-pharmacological, cost-effective intervention for Alzheimer’s disease (AD). There has been increasing behavioral evidence regarding training-related improvement in cognitive performance in early stages of AD. Although these studies provide important insight about the efficacy of cognitive training, neuroimaging studies are crucial to pinpoint changes in brain structure and function associated with training and to examine their overlap with pathology in AD. In this study, we reviewed the existing neuroimaging studies on cognitive training in persons at risk of developing AD to provide an overview of the overlap between neural networks rehabilitated by the current training methods and those affected in AD. The data suggest a consistent training-related increase in brain activity in medial temporal, prefrontal, and posterior default mode networks, as well as increase in gray matter structure in frontoparietal and entorhinal regions. This pattern differs from the observed pattern in healthy older adults that shows a combination of increased and decreased activity in response to training. Detailed investigation of the data suggests that training in persons at risk of developing AD mainly improves compensatory mechanisms and partly restores the affected functions. While current neuroimaging studies are quite helpful in identifying the mechanisms underlying cognitive training, the data calls for future multi-modal neuroimaging studies with focus on multi-domain cognitive training, network level connectivity, and individual differences in response to training. PMID:25206335
de Almeida, Jorge Renner Cardoso; Phillips, Mary Louise
2012-01-01
Differentiating bipolar disorder (BD) from recurrent unipolar depression (UD) is a major clinical challenge. Main reasons for this include the higher prevalence of depressive relative to hypo/manic symptoms during the course of BD illness and the high prevalence of subthreshold manic symptoms in both BD and UD depression. Identifying objective markers of BD might help improve accuracy in differentiating between BD and UD depression, to ultimately optimize clinical and functional outcome for all depressed individuals. Yet, only eight neuroimaging studies to date directly compared UD and BD depressed individuals. Findings from these studies suggest more widespread abnormalities in white matter connectivity and white matter hyperintensities in BD than UD depression, habenula volume reductions in BD but not UD depression, and differential patterns of functional abnormalities in emotion regulation and attentional control neural circuitry in the two depression types. These findings suggest different pathophysiologic processes, especially in emotion regulation, reward and attentional control neural circuitry in BD versus UD depression. This review thereby serves as a “call to action” to highlight the pressing need for more neuroimaging studies, using larger samples sizes, comparing BD and UD depressed individuals. These future studies should also include dimensional approaches, studies of at risk individuals, and more novel neuroimaging approaches, such as, connectivity analysis and machine learning. Ultimately, these approaches might provide biomarkers to identify individuals at future risk for BD versus UD, and biological targets for more personalized treatment and new treatment developments for BD and UD depression. PMID:22784485
Gifford, Katherine A; Liu, Dandan; Damon, Stephen M; Chapman, William G; Romano Iii, Raymond R; Samuels, Lauren R; Lu, Zengqi; Jefferson, Angela L
2015-01-01
A cognitive concern from the patient, informant, or clinician is required for the diagnosis of mild cognitive impairment (MCI); however, the cognitive and neuroanatomical correlates of complaint are poorly understood. We assessed how self-complaint relates to cognitive and neuroimaging measures in older adults with MCI. MCI participants were drawn from the Alzheimer's Disease Neuroimaging Initiative and dichotomized into two groups based on the presence of self-reported memory complaint (no complaint n = 191, 77 ± 7 years; complaint n = 206, 73 ± 8 years). Cognitive outcomes included episodic memory, executive functioning, information processing speed, and language. Imaging outcomes included regional lobar volumes (frontal, parietal, temporal, cingulate) and specific medial temporal lobe structures (hippocampal volume, entorhinal cortex thickness, parahippocampal gyrus thickness). Linear regressions, adjusting for age, gender, race, education, Mini-Mental State Examination score, mood, and apolipoprotein E4 status, found that cognitive complaint related to immediate (β = -1.07, p < 0.001) and delayed episodic memory performances assessed on a serial list learning task (β = -1.06, p = 0.001) but no other cognitive measures or neuroimaging markers. Self-reported memory concern was unrelated to structural neuroimaging markers of atrophy and measures of information processing speed, executive functioning, or language. In contrast, subjective memory complaint related to objective verbal episodic learning performance. Future research is warranted to better understand the relation between cognitive complaint and surrogate markers of abnormal brain aging, including Alzheimer's disease, across the cognitive aging spectrum.
Menon, Samir; Brantner, Gerald; Aholt, Chris; Kay, Kendrick; Khatib, Oussama
2013-01-01
A challenging problem in motor control neuroimaging studies is the inability to perform complex human motor tasks given the Magnetic Resonance Imaging (MRI) scanner's disruptive magnetic fields and confined workspace. In this paper, we propose a novel experimental platform that combines Functional MRI (fMRI) neuroimaging, haptic virtual simulation environments, and an fMRI-compatible haptic device for real-time haptic interaction across the scanner workspace (above torso ∼ .65×.40×.20m(3)). We implement this Haptic fMRI platform with a novel haptic device, the Haptic fMRI Interface (HFI), and demonstrate its suitability for motor neuroimaging studies. HFI has three degrees-of-freedom (DOF), uses electromagnetic motors to enable high-fidelity haptic rendering (>350Hz), integrates radio frequency (RF) shields to prevent electromagnetic interference with fMRI (temporal SNR >100), and is kinematically designed to minimize currents induced by the MRI scanner's magnetic field during motor displacement (<2cm). HFI possesses uniform inertial and force transmission properties across the workspace, and has low friction (.05-.30N). HFI's RF noise levels, in addition, are within a 3 Tesla fMRI scanner's baseline noise variation (∼.85±.1%). Finally, HFI is haptically transparent and does not interfere with human motor tasks (tested for .4m reaches). By allowing fMRI experiments involving complex three-dimensional manipulation with haptic interaction, Haptic fMRI enables-for the first time-non-invasive neuroscience experiments involving interactive motor tasks, object manipulation, tactile perception, and visuo-motor integration.
Harnessing psychoanalytical methods for a phenomenological neuroscience
Cusumano, Emma P.; Raz, Amir
2014-01-01
Psychoanalysis proffers a wealth of phenomenological tools to advance the study of consciousness. Techniques for elucidating the structures of subjective life are sorely lacking in the cognitive sciences; as such, experiential reporting techniques must rise to meet both complex theories of brain function and increasingly sophisticated neuroimaging technologies. Analysis may offer valuable methods for bridging the gap between first-person and third-person accounts of the mind. Using both systematic observational approaches alongside unstructured narrative interactions, psychoanalysts help patients articulate their experience and bring unconscious mental contents into awareness. Similar to seasoned meditators or phenomenologists, individuals who have undergone analysis are experts in discerning and describing their subjective experience, thus making them ideal candidates for neurophenomenology. Moreover, analytic techniques may provide a means of guiding untrained experimental participants to greater awareness of their mental continuum, as well as gathering subjective reports about fundamental yet elusive aspects of experience including selfhood, temporality, and inter-subjectivity. Mining psychoanalysis for its methodological innovations provides a fresh turn for the neuropsychoanalysis movement and cognitive science as a whole – showcasing the integrity of analysis alongside the irreducibility of human experience. PMID:24808869
Non-invasive brain stimulation in neurorehabilitation: local and distant effects for motor recovery
Liew, Sook-Lei; Santarnecchi, Emilliano; Buch, Ethan R.; Cohen, Leonardo G.
2014-01-01
Non-invasive brain stimulation (NIBS) may enhance motor recovery after neurological injury through the causal induction of plasticity processes. Neurological injury, such as stroke, often results in serious long-term physical disabilities, and despite intensive therapy, a large majority of brain injury survivors fail to regain full motor function. Emerging research suggests that NIBS techniques, such as transcranial magnetic (TMS) and direct current (tDCS) stimulation, in association with customarily used neurorehabilitative treatments, may enhance motor recovery. This paper provides a general review on TMS and tDCS paradigms, the mechanisms by which they operate and the stimulation techniques used in neurorehabilitation, specifically stroke. TMS and tDCS influence regional neural activity underlying the stimulation location and also distant interconnected network activity throughout the brain. We discuss recent studies that document NIBS effects on global brain activity measured with various neuroimaging techniques, which help to characterize better strategies for more accurate NIBS stimulation. These rapidly growing areas of inquiry may hold potential for improving the effectiveness of NIBS-based interventions for clinical rehabilitation. PMID:25018714
Parra-Díaz, P; García-Casares, N
2017-04-19
Given that surgical treatment of refractory mesial temporal lobe epilepsy may cause memory impairment, determining which patients are eligible for surgery is essential. However, there is little agreement on which presurgical memory assessment methods are best able to predict memory outcome after surgery and identify those patients with a greater risk of surgery-induced memory decline. We conducted a systematic literature review to determine which presurgical memory assessment methods best predict memory outcome. The literature search of PubMed gathered articles published between January 2005 and December 2015 addressing pre- and postsurgical memory assessment in mesial temporal lobe epilepsy patients by means of neuropsychological testing, functional MRI, and other neuroimaging techniques. We obtained 178 articles, 31 of which were included in our review. Most of the studies used neuropsychological tests and fMRI; these methods are considered to have the greatest predictive ability for memory impairment. Other less frequently used techniques included the Wada test and FDG-PET. Current evidence supports performing a presurgical assessment of memory function using both neuropsychological tests and functional MRI to predict memory outcome after surgery. Copyright © 2017 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.
Noninvasive brain stimulation treatments for addiction and major depression
Dunlop, Katharine; Hanlon, Colleen A.
2016-01-01
Major depressive disorder (MDD) and substance use disorders (SUDs) are prevalent, disabling, and challenging illnesses for which new treatment options are needed, particularly in comorbid cases. Neuroimaging studies of the functional architecture of the brain suggest common neural substrates underlying MDD and SUDs. Intrinsic brain activity is organized into a set of functional networks, of which two are particularly relevant to psychiatry. The salience network (SN) is crucial for cognitive control and response inhibition, and deficits in SN function are implicated across a wide variety of psychiatric disorders, including MDD and SUDs. The ventromedial network (VMN) corresponds to the classic reward circuit, and pathological VMN activity for drug cues/negative stimuli is seen in SUDs/MDD. Noninvasive brain stimulation (NIBS) techniques, including rTMS and tDCS, have been used to enhance cortico–striatal–thalamic activity through the core SN nodes in the dorsal anterior cingulate cortex, dorsolateral prefrontal cortex, and anterior insula. Improvements in both MDD and SUD symptoms ensue, including in comorbid cases, via enhanced cognitive control. Inhibition of the VMN also appears promising in preclinical studies for quenching the pathological incentive salience underlying SUDs and MDD. Evolving techniques may further enhance the efficacy of NIBS for MDD and SUD cases that are unresponsive to conventional treatments. PMID:26849183
Scarapicchia, Vanessa; Brown, Cassandra; Mayo, Chantel; Gawryluk, Jodie R.
2017-01-01
Although blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) is a widely available, non-invasive technique that offers excellent spatial resolution, it remains limited by practical constraints imposed by the scanner environment. More recently, functional near infrared spectroscopy (fNIRS) has emerged as an alternative hemodynamic-based approach that possesses a number of strengths where fMRI is limited, most notably in portability and higher tolerance for motion. To date, fNIRS has shown promise in its ability to shed light on the functioning of the human brain in populations and contexts previously inaccessible to fMRI. Notable contributions include infant neuroimaging studies and studies examining full-body behaviors, such as exercise. However, much like fMRI, fNIRS has technical constraints that have limited its application to clinical settings, including a lower spatial resolution and limited depth of recording. Thus, by combining fMRI and fNIRS in such a way that the two methods complement each other, a multimodal imaging approach may allow for more complex research paradigms than is feasible with either technique alone. In light of these issues, the purpose of the current review is to: (1) provide an overview of fMRI and fNIRS and their associated strengths and limitations; (2) review existing combined fMRI-fNIRS recording studies; and (3) discuss how their combined use in future research practices may aid in advancing modern investigations of human brain function. PMID:28867998
Does Functional Neuroimaging Solve the Questions of Neurolinguistics?
ERIC Educational Resources Information Center
Sidtis, Diana Van Lancker
2006-01-01
Neurolinguistic research has been engaged in evaluating models of language using measures from brain structure and function, and/or in investigating brain structure and function with respect to language representation using proposed models of language. While the aphasiological strategy, which classifies aphasias based on performance modality and a…
Default-Mode Network Functional Connectivity in Aphasia: Therapy-Induced Neuroplasticity
ERIC Educational Resources Information Center
Marcotte, Karine; Perlbarg, Vincent; Marrelec, Guillaume; Benali, Habib; Ansaldo, Ana Ines
2013-01-01
Previous research on participants with aphasia has mainly been based on standard functional neuroimaging analysis. Recent studies have shown that functional connectivity analysis can detect compensatory activity, not revealed by standard analysis. Little is known, however, about the default-mode network in aphasia. In the current study, we studied…
Functional neuroimaging in epileptic encephalopathies.
Siniatchkin, Michael; Capovilla, Giuseppe
2013-11-01
Epileptic encephalopathies (EEs) represent a group of severe epileptic disorders associated with cognitive and behavioral disturbances. The mechanisms of cognitive disability in EEs remain unclear. This review summarized neuroimaging studies that have tried to describe specific fingerprints of brain activation in EE. Although the epileptic activity can be generated individually in different brain regions, it seems likely that the activity propagates in a syndrome-specific way. In some EEs, the epileptiform discharges were associated with an interruption of activity in the default mode network. In another EE, other mechanisms seem to underlie cognitive disability associated with epileptic activity, for example, abnormal connectivity pattern or interfering activity in the thalamocortical network. Further neuroimaging studies are needed to investigate the short-term and long-term impact of epileptic activity on cognition and development. Wiley Periodicals, Inc. © 2013 International League Against Epilepsy.
Using connectome-based predictive modeling to predict individual behavior from brain connectivity
Shen, Xilin; Finn, Emily S.; Scheinost, Dustin; Rosenberg, Monica D.; Chun, Marvin M.; Papademetris, Xenophon; Constable, R Todd
2017-01-01
Neuroimaging is a fast developing research area where anatomical and functional images of human brains are collected using techniques such as functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), and electroencephalography (EEG). Technical advances and large-scale datasets have allowed for the development of models capable of predicting individual differences in traits and behavior using brain connectivity measures derived from neuroimaging data. Here, we present connectome-based predictive modeling (CPM), a data-driven protocol for developing predictive models of brain-behavior relationships from connectivity data using cross-validation. This protocol includes the following steps: 1) feature selection, 2) feature summarization, 3) model building, and 4) assessment of prediction significance. We also include suggestions for visualizing the most predictive features (i.e., brain connections). The final result should be a generalizable model that takes brain connectivity data as input and generates predictions of behavioral measures in novel subjects, accounting for a significant amount of the variance in these measures. It has been demonstrated that the CPM protocol performs equivalently or better than most of the existing approaches in brain-behavior prediction. However, because CPM focuses on linear modeling and a purely data-driven driven approach, neuroscientists with limited or no experience in machine learning or optimization would find it easy to implement the protocols. Depending on the volume of data to be processed, the protocol can take 10–100 minutes for model building, 1–48 hours for permutation testing, and 10–20 minutes for visualization of results. PMID:28182017
Caudate nucleus reactivity predicts perceptual learning rate for visual feature conjunctions.
Reavis, Eric A; Frank, Sebastian M; Tse, Peter U
2015-04-15
Useful information in the visual environment is often contained in specific conjunctions of visual features (e.g., color and shape). The ability to quickly and accurately process such conjunctions can be learned. However, the neural mechanisms responsible for such learning remain largely unknown. It has been suggested that some forms of visual learning might involve the dopaminergic neuromodulatory system (Roelfsema et al., 2010; Seitz and Watanabe, 2005), but this hypothesis has not yet been directly tested. Here we test the hypothesis that learning visual feature conjunctions involves the dopaminergic system, using functional neuroimaging, genetic assays, and behavioral testing techniques. We use a correlative approach to evaluate potential associations between individual differences in visual feature conjunction learning rate and individual differences in dopaminergic function as indexed by neuroimaging and genetic markers. We find a significant correlation between activity in the caudate nucleus (a component of the dopaminergic system connected to visual areas of the brain) and visual feature conjunction learning rate. Specifically, individuals who showed a larger difference in activity between positive and negative feedback on an unrelated cognitive task, indicative of a more reactive dopaminergic system, learned visual feature conjunctions more quickly than those who showed a smaller activity difference. This finding supports the hypothesis that the dopaminergic system is involved in visual learning, and suggests that visual feature conjunction learning could be closely related to associative learning. However, no significant, reliable correlations were found between feature conjunction learning and genotype or dopaminergic activity in any other regions of interest. Copyright © 2015 Elsevier Inc. All rights reserved.
Neuroimaging Study Designs, Computational Analyses and Data Provenance Using the LONI Pipeline
Dinov, Ivo; Lozev, Kamen; Petrosyan, Petros; Liu, Zhizhong; Eggert, Paul; Pierce, Jonathan; Zamanyan, Alen; Chakrapani, Shruthi; Van Horn, John; Parker, D. Stott; Magsipoc, Rico; Leung, Kelvin; Gutman, Boris; Woods, Roger; Toga, Arthur
2010-01-01
Modern computational neuroscience employs diverse software tools and multidisciplinary expertise to analyze heterogeneous brain data. The classical problems of gathering meaningful data, fitting specific models, and discovering appropriate analysis and visualization tools give way to a new class of computational challenges—management of large and incongruous data, integration and interoperability of computational resources, and data provenance. We designed, implemented and validated a new paradigm for addressing these challenges in the neuroimaging field. Our solution is based on the LONI Pipeline environment [3], [4], a graphical workflow environment for constructing and executing complex data processing protocols. We developed study-design, database and visual language programming functionalities within the LONI Pipeline that enable the construction of complete, elaborate and robust graphical workflows for analyzing neuroimaging and other data. These workflows facilitate open sharing and communication of data and metadata, concrete processing protocols, result validation, and study replication among different investigators and research groups. The LONI Pipeline features include distributed grid-enabled infrastructure, virtualized execution environment, efficient integration, data provenance, validation and distribution of new computational tools, automated data format conversion, and an intuitive graphical user interface. We demonstrate the new LONI Pipeline features using large scale neuroimaging studies based on data from the International Consortium for Brain Mapping [5] and the Alzheimer's Disease Neuroimaging Initiative [6]. User guides, forums, instructions and downloads of the LONI Pipeline environment are available at http://pipeline.loni.ucla.edu. PMID:20927408
Brain Imaging in Children with Neurodevelopmental Disorders.
ERIC Educational Resources Information Center
Mantovani, John F.
1994-01-01
This article reviews neuroimaging techniques such as cranial ultrasound, computed tomography scanning, and magnetic resonance imaging. Their roles in the care of children with neurodevelopmental disabilities include identification of high-risk infants, establishment of the diagnosis and prognosis in affected children, and enhancement of discussion…
Fox, W Christopher; Park, Min S; Belverud, Shawn; Klugh, Arnett; Rivet, Dennis; Tomlin, Jeffrey M
2013-04-01
To follow the progression of neuroimaging as a means of non-invasive evaluation of mild traumatic brain injury (mTBI) in order to provide recommendations based on reproducible, defined imaging findings. A comprehensive literature review and analysis of contemporary published articles was performed to study the progression of neuroimaging findings as a non-invasive 'biomarker' for mTBI. Multiple imaging modalities exist to support the evaluation of patients with mTBI, including ultrasound (US), computed tomography (CT), single photon emission computed tomography (SPECT), positron emission tomography (PET), and magnetic resonance imaging (MRI). These techniques continue to evolve with the development of fractional anisotropy (FA), fiber tractography (FT), and diffusion tensor imaging (DTI). Modern imaging techniques, when applied in the appropriate clinical setting, may serve as a valuable tool for diagnosis and management of patients with mTBI. An understanding of modern neuroanatomical imaging will enhance our ability to analyse injury and recognize the manifestations of mTBI.
Toward an understanding of the cerebral substrates of woman's orgasm.
Bianchi-Demicheli, Francesco; Ortigue, Stephanie
2007-09-20
The way women experience orgasm is of interest to scientists, clinicians, and laypeople. Whereas the origin and the function of a woman's orgasm remains controversial, the current models of sexual function acknowledge a combined role of central (spinal and cerebral) and peripheral processes during orgasm experience. At the central level, although it is accepted that the spinal cord drives orgasm, the cerebral involvement and cognitive representation of a woman's orgasm has not been extensively investigated. Important gaps in our knowledge remain. Recently, the astonishing advances of neuroimaging techniques applied in parallel with a neuropsychological approach allowed the unravelling of specific functional neuroanatomy of a woman's orgasm. Here, clinical and experimental findings on the cortico-subcortical pathway of a woman's orgasm are reviewed and compared with the neural basis of a man's orgasm. By defining the specific brain areas that sustain the assumed higher-order representation of a woman's orgasm, this review provides a foundation for future studies. The next challenge of functional imaging and neuropsychological studies is to understand the hierarchical interactions between these multiple cortical areas, not only with a correlation analysis but also with high spatio-temporal resolution techniques demonstrating the causal necessity, the temporal time course and the direction of the causality. Further studies using a multi-disciplinary approach are needed to identify the spatio-temporal dynamic of a woman's orgasm, its dysfunctions and possible new treatments.
Dysfunction of the prefrontal cortex in addiction: neuroimaging findings and clinical implications.
Goldstein, Rita Z; Volkow, Nora D
2011-10-20
The loss of control over drug intake that occurs in addiction was initially believed to result from disruption of subcortical reward circuits. However, imaging studies in addictive behaviours have identified a key involvement of the prefrontal cortex (PFC) both through its regulation of limbic reward regions and its involvement in higher-order executive function (for example, self-control, salience attribution and awareness). This Review focuses on functional neuroimaging studies conducted in the past decade that have expanded our understanding of the involvement of the PFC in drug addiction. Disruption of the PFC in addiction underlies not only compulsive drug taking but also accounts for the disadvantageous behaviours that are associated with addiction and the erosion of free will.
Cognitive functions of the posterior parietal cortex: top-down and bottom-up attentional control
Shomstein, Sarah
2012-01-01
Although much less is known about human parietal cortex than that of homologous monkey cortex, recent studies, employing neuroimaging, and neuropsychological methods, have begun to elucidate increasingly fine-grained functional and structural distinctions. This review is focused on recent neuroimaging and neuropsychological studies elucidating the cognitive roles of dorsal and ventral regions of parietal cortex in top-down and bottom-up attentional orienting, and on the interaction between the two attentional allocation mechanisms. Evidence is reviewed arguing that regions along the dorsal areas of the parietal cortex, including the superior parietal lobule (SPL) are involved in top-down attentional orienting, while ventral regions including the temporo-parietal junction (TPJ) are involved in bottom-up attentional orienting. PMID:22783174
Dysfunction of the prefrontal cortex in addiction: neuroimaging findings and clinical implications
Goldstein, Rita Z.; Volkow, Nora D.
2012-01-01
The loss of control over drug intake that occurs in addiction was initially believed to result from disruption of subcortical reward circuits. However, imaging studies in addictive behaviours have identified a key involvement of the prefrontal cortex (PFC) both through its regulation of limbic reward regions and its involvement in higher-order executive function (for example, self-control, salience attribution and awareness). This Review focuses on functional neuroimaging studies conducted in the past decade that have expanded our understanding of the involvement of the PFC in drug addiction. Disruption of the PFC in addiction underlies not only compulsive drug taking but also accounts for the disadvantageous behaviours that are associated with addiction and the erosion of free will. PMID:22011681
Neurolinguistics: Structure, Function, and Connectivity in the Bilingual Brain
Wong, Becky; Yin, Bin; O'Brien, Beth
2016-01-01
Advances in neuroimaging techniques and analytic methods have led to a proliferation of studies investigating the impact of bilingualism on the cognitive and brain systems in humans. Lately, these findings have attracted much interest and debate in the field, leading to a number of recent commentaries and reviews. Here, we contribute to the ongoing discussion by compiling and interpreting the plethora of findings that relate to the structural, functional, and connective changes in the brain that ensue from bilingualism. In doing so, we integrate theoretical models and empirical findings from linguistics, cognitive/developmental psychology, and neuroscience to examine the following issues: (1) whether the language neural network is different for first (dominant) versus second (nondominant) language processing; (2) the effects of bilinguals' executive functioning on the structure and function of the “universal” language neural network; (3) the differential effects of bilingualism on phonological, lexical-semantic, and syntactic aspects of language processing on the brain; and (4) the effects of age of acquisition and proficiency of the user's second language in the bilingual brain, and how these have implications for future research in neurolinguistics. PMID:26881224
State space modeling of time-varying contemporaneous and lagged relations in connectivity maps.
Molenaar, Peter C M; Beltz, Adriene M; Gates, Kathleen M; Wilson, Stephen J
2016-01-15
Most connectivity mapping techniques for neuroimaging data assume stationarity (i.e., network parameters are constant across time), but this assumption does not always hold true. The authors provide a description of a new approach for simultaneously detecting time-varying (or dynamic) contemporaneous and lagged relations in brain connectivity maps. Specifically, they use a novel raw data likelihood estimation technique (involving a second-order extended Kalman filter/smoother embedded in a nonlinear optimizer) to determine the variances of the random walks associated with state space model parameters and their autoregressive components. The authors illustrate their approach with simulated and blood oxygen level-dependent functional magnetic resonance imaging data from 30 daily cigarette smokers performing a verbal working memory task, focusing on seven regions of interest (ROIs). Twelve participants had dynamic directed functional connectivity maps: Eleven had one or more time-varying contemporaneous ROI state loadings, and one had a time-varying autoregressive parameter. Compared to smokers without dynamic maps, smokers with dynamic maps performed the task with greater accuracy. Thus, accurate detection of dynamic brain processes is meaningfully related to behavior in a clinical sample. Published by Elsevier Inc.
Content-specific evidence accumulation in inferior temporal cortex during perceptual decision-making
Tremel, Joshua J.; Wheeler, Mark E.
2015-01-01
During a perceptual decision, neuronal activity can change as a function of time-integrated evidence. Such neurons may serve as decision variables, signaling a choice when activity reaches a boundary. Because the signals occur on a millisecond timescale, translating to human decision-making using functional neuroimaging has been challenging. Previous neuroimaging work in humans has identified patterns of neural activity consistent with an accumulation account. However, the degree to which the accumulating neuroimaging signals reflect specific sources of perceptual evidence is unknown. Using an extended face/house discrimination task in conjunction with cognitive modeling, we tested whether accumulation signals, as measured using functional magnetic resonance imaging (fMRI), are stimulus-specific. Accumulation signals were defined as a change in the slope of the rising edge of activation corresponding with response time (RT), with higher slopes associated with faster RTs. Consistent with an accumulation account, fMRI activity in face- and house-selective regions in the inferior temporal cortex increased at a rate proportional to decision time in favor of the preferred stimulus. This finding indicates that stimulus-specific regions perform an evidence integrative function during goal-directed behavior and that different sources of evidence accumulate separately. We also assessed the decision-related function of other regions throughout the brain and found that several regions were consistent with classifications from prior work, suggesting a degree of domain generality in decision processing. Taken together, these results provide support for an integration-to-boundary decision mechanism and highlight possible roles of both domain-specific and domain-general regions in decision evidence evaluation. PMID:25562821
Cavedo, E.; Lista, S.; Khachaturian, Z.; Aisen, P.; Amouyel, P.; Herholz, K.; Jack, C.R.; Sperling, R.; Cummings, J.; Blennow, K.; O’Bryant, S.; Frisoni, G.B.; Khachaturian, A.; Kivipelto, M.; Klunk, W.; Broich, K.; Andrieu, S.; de Schotten, M. Thiebaut; Mangin, J.-F.; Lammertsma, A.A.; Johnson, K.; Teipel, S.; Drzezga, A.; Bokde, A.; Colliot, O.; Bakardjian, H.; Zetterberg, H.; Dubois, B.; Vellas, B.; Schneider, L.S.; Hampel, H.
2015-01-01
Alzheimer’s disease (AD) is a slowly progressing non-linear dynamic brain disease in which pathophysiological abnormalities, detectable in vivo by biological markers, precede overt clinical symptoms by many years to decades. Use of these biomarkers for the detection of early and preclinical AD has become of central importance following publication of two international expert working group’s revised criteria for the diagnosis of AD dementia, mild cognitive impairment (MCI) due to AD, prodromal AD and preclinical AD. As a consequence of matured research evidence six AD biomarkers are sufficiently validated and partly qualified to be incorporated into operationalized clinical diagnostic criteria and use in primary and secondary prevention trials. These biomarkers fall into two molecular categories: biomarkers of amyloid-beta (Aβ) deposition and plaque formation as well as of tau-protein related hyperphosphorylation and neurodegeneration. Three of the six gold-standard (“core feasible) biomarkers are neuroimaging measures and three are cerebrospinal fluid (CSF) analytes. CSF Aβ1-42 (Aβ1-42), also expressed as Aβ1-42 : Aβ1-40 ratio, T-tau, and P-tau Thr181 & Thr231 proteins have proven diagnostic accuracy and risk enhancement in prodromal MCI and AD dementia. Conversely, having all three biomarkers in the normal range rules out AD. Intermediate conditions require further patient follow-up. Magnetic resonance imaging (MRI) at increasing field strength and resolution allows detecting the evolution of distinct types of structural and functional abnormality pattern throughout early to late AD stages. Anatomical or volumetric MRI is the most widely used technique and provides local and global measures of atrophy. The revised diagnostic criteria for “prodromal AD” and “mild cognitive impairment due to AD” include hippocampal atrophy (as the fourth validated biomarker), which is considered an indicator of regional neuronal injury. Advanced image analysis techniques generate automatic and reproducible measures both in regions of interest, such as the hippocampus and in an exploratory fashion, observer and hypothesis-indedendent, throughout the entire brain. Evolving modalities such as diffusion-tensor imaging (DTI) and advanced tractography as well as resting-state functional MRI provide useful additionally useful measures indicating the degree of fiber tract and neural network disintegration (structural, effective and functional connectivity) that may substantially contribute to early detection and the mapping of progression. These modalities require further standardization and validation. The use of molecular in vivo amyloid imaging agents (the fifth validated biomarker), such as the Pittsburgh Compound-B and markers of neurodegeneration, such as fluoro-2-deoxy-D-glucose (FDG) (as the sixth validated biomarker) support the detection of early AD pathological processes and associated neurodegeneration. How to use, interpret, and disclose biomarker results drives the need for optimized standardization. Multimodal AD biomarkers do not evolve in an identical manner but rather in a sequential but temporally overlapping fashion. Models of the temporal evolution of AD biomarkers can take the form of plots of biomarker severity (degree of abnormality) versus time. AD biomarkers can be combined to increase accuracy or risk. A list of genetic risk factors is increasingly included in secondary prevention trials to stratify and select individuals at genetic risk of AD. Although most of these biomarker candidates are not yet qualified and approved by regulatory authorities for their intended use in drug trials, they are nonetheless applied in ongoing clinical studies for the following functions: (i) inclusion/exclusion criteria, (ii) patient stratification, (iii) evaluation of treatment effect, (iv) drug target engagement, and (v) safety. Moreover, novel promising hypothesis-driven, as well as exploratory biochemical, genetic, electrophysiological, and neuroimaging markers for use in clinical trials are being developed. The current state-of-the-art and future perspectives on both biological and neuroimaging derived biomarker discovery and development as well as the intended application in prevention trials is outlined in the present publication. PMID:26478889
ERIC Educational Resources Information Center
Sahyoun, Cherif P.; Belliveau, John W.; Soulieres, Isabelle; Schwartz, Shira; Mody, Maria
2010-01-01
High-functioning individuals with autism have been found to favor visuospatial processing in the face of typically poor language abilities. We aimed to examine the neurobiological basis of this difference using functional magnetic resonance imaging and diffusion tensor imaging. We compared 12 children with high functioning autism (HFA) to 12 age-…
Lorenz, Romy; Monti, Ricardo Pio; Violante, Inês R.; Anagnostopoulos, Christoforos; Faisal, Aldo A.; Montana, Giovanni; Leech, Robert
2016-01-01
Functional neuroimaging typically explores how a particular task activates a set of brain regions. Importantly though, the same neural system can be activated by inherently different tasks. To date, there is no approach available that systematically explores whether and how distinct tasks probe the same neural system. Here, we propose and validate an alternative framework, the Automatic Neuroscientist, which turns the standard fMRI approach on its head. We use real-time fMRI in combination with modern machine-learning techniques to automatically design the optimal experiment to evoke a desired target brain state. In this work, we present two proof-of-principle studies involving perceptual stimuli. In both studies optimization algorithms of varying complexity were employed; the first involved a stochastic approximation method while the second incorporated a more sophisticated Bayesian optimization technique. In the first study, we achieved convergence for the hypothesized optimum in 11 out of 14 runs in less than 10 min. Results of the second study showed how our closed-loop framework accurately and with high efficiency estimated the underlying relationship between stimuli and neural responses for each subject in one to two runs: with each run lasting 6.3 min. Moreover, we demonstrate that using only the first run produced a reliable solution at a group-level. Supporting simulation analyses provided evidence on the robustness of the Bayesian optimization approach for scenarios with low contrast-to-noise ratio. This framework is generalizable to numerous applications, ranging from optimizing stimuli in neuroimaging pilot studies to tailoring clinical rehabilitation therapy to patients and can be used with multiple imaging modalities in humans and animals. PMID:26804778
Sanchez, Gaëtan; Lecaignard, Françoise; Otman, Anatole; Maby, Emmanuel; Mattout, Jérémie
2016-01-01
The relatively young field of Brain-Computer Interfaces has promoted the use of electrophysiology and neuroimaging in real-time. In the meantime, cognitive neuroscience studies, which make extensive use of functional exploration techniques, have evolved toward model-based experiments and fine hypothesis testing protocols. Although these two developments are mostly unrelated, we argue that, brought together, they may trigger an important shift in the way experimental paradigms are being designed, which should prove fruitful to both endeavors. This change simply consists in using real-time neuroimaging in order to optimize advanced neurocognitive hypothesis testing. We refer to this new approach as the instantiation of an Active SAmpling Protocol (ASAP). As opposed to classical (static) experimental protocols, ASAP implements online model comparison, enabling the optimization of design parameters (e.g., stimuli) during the course of data acquisition. This follows the well-known principle of sequential hypothesis testing. What is radically new, however, is our ability to perform online processing of the huge amount of complex data that brain imaging techniques provide. This is all the more relevant at a time when physiological and psychological processes are beginning to be approached using more realistic, generative models which may be difficult to tease apart empirically. Based upon Bayesian inference, ASAP proposes a generic and principled way to optimize experimental design adaptively. In this perspective paper, we summarize the main steps in ASAP. Using synthetic data we illustrate its superiority in selecting the right perceptual model compared to a classical design. Finally, we briefly discuss its future potential for basic and clinical neuroscience as well as some remaining challenges.
Lorenz, Romy; Monti, Ricardo Pio; Violante, Inês R; Anagnostopoulos, Christoforos; Faisal, Aldo A; Montana, Giovanni; Leech, Robert
2016-04-01
Functional neuroimaging typically explores how a particular task activates a set of brain regions. Importantly though, the same neural system can be activated by inherently different tasks. To date, there is no approach available that systematically explores whether and how distinct tasks probe the same neural system. Here, we propose and validate an alternative framework, the Automatic Neuroscientist, which turns the standard fMRI approach on its head. We use real-time fMRI in combination with modern machine-learning techniques to automatically design the optimal experiment to evoke a desired target brain state. In this work, we present two proof-of-principle studies involving perceptual stimuli. In both studies optimization algorithms of varying complexity were employed; the first involved a stochastic approximation method while the second incorporated a more sophisticated Bayesian optimization technique. In the first study, we achieved convergence for the hypothesized optimum in 11 out of 14 runs in less than 10 min. Results of the second study showed how our closed-loop framework accurately and with high efficiency estimated the underlying relationship between stimuli and neural responses for each subject in one to two runs: with each run lasting 6.3 min. Moreover, we demonstrate that using only the first run produced a reliable solution at a group-level. Supporting simulation analyses provided evidence on the robustness of the Bayesian optimization approach for scenarios with low contrast-to-noise ratio. This framework is generalizable to numerous applications, ranging from optimizing stimuli in neuroimaging pilot studies to tailoring clinical rehabilitation therapy to patients and can be used with multiple imaging modalities in humans and animals. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.
Discovering Cortical Folding Patterns in Neonatal Cortical Surfaces Using Large-Scale Dataset
Meng, Yu; Li, Gang; Wang, Li; Lin, Weili; Gilmore, John H.
2017-01-01
The cortical folding of the human brain is highly complex and variable across individuals. Mining the major patterns of cortical folding from modern large-scale neuroimaging datasets is of great importance in advancing techniques for neuroimaging analysis and understanding the inter-individual variations of cortical folding and its relationship with cognitive function and disorders. As the primary cortical folding is genetically influenced and has been established at term birth, neonates with the minimal exposure to the complicated postnatal environmental influence are the ideal candidates for understanding the major patterns of cortical folding. In this paper, for the first time, we propose a novel method for discovering the major patterns of cortical folding in a large-scale dataset of neonatal brain MR images (N = 677). In our method, first, cortical folding is characterized by the distribution of sulcal pits, which are the locally deepest points in cortical sulci. Because deep sulcal pits are genetically related, relatively consistent across individuals, and also stable during brain development, they are well suitable for representing and characterizing cortical folding. Then, the similarities between sulcal pit distributions of any two subjects are measured from spatial, geometrical, and topological points of view. Next, these different measurements are adaptively fused together using a similarity network fusion technique, to preserve their common information and also catch their complementary information. Finally, leveraging the fused similarity measurements, a hierarchical affinity propagation algorithm is used to group similar sulcal folding patterns together. The proposed method has been applied to 677 neonatal brains (the largest neonatal dataset to our knowledge) in the central sulcus, superior temporal sulcus, and cingulate sulcus, and revealed multiple distinct and meaningful folding patterns in each region. PMID:28229131
Motor Cortex Activity During Functional Motor Skills: An fNIRS Study.
Nishiyori, Ryota; Bisconti, Silvia; Ulrich, Beverly
2016-01-01
Assessments of brain activity during motor task performance have been limited to fine motor movements due to technological constraints presented by traditional neuroimaging techniques, such as functional magnetic resonance imaging. Functional near-infrared spectroscopy (fNIRS) offers a promising method by which to overcome these constraints and investigate motor performance of functional motor tasks. The current study used fNIRS to quantify hemodynamic responses within the primary motor cortex in twelve healthy adults as they performed unimanual right, unimanual left, and bimanual reaching, and stepping in place. Results revealed that during both unimanual reaching tasks, the contralateral hemisphere showed significant activation in channels located approximately 3 cm medial to the C3 (for right-hand reach) and C4 (for left-hand reach) landmarks. Bimanual reaching and stepping showed activation in similar channels, which were located bilaterally across the primary motor cortex. The medial channels, surrounding Cz, showed significantly higher activations during stepping when compared to bimanual reaching. Our results extend the viability of fNIRS to study motor function and build a foundation for future investigation of motor development in infants during nascent functional behaviors and monitor how they may change with age or practice.
[Review: executive functioning and cannabis use].
Almeida, Priscila Previato; Novaes, Maria Alice Fontes Pinto; Bressan, Rodrigo Affonseca; Lacerda, Acioly Luiz Tavares de
2008-03-01
Cannabis is the most used illicit drug worldwide, however only a few studies have examined cognitive deficits related to its use. Clinical manifestations associated with those deficits include a motivational syndrome, impairment in cognitive flexibility, inattention, deficits in abstract reasoning and concept formation, aspects intimately related to the executive functions, which potentially exert a central role in substance dependence. The objective was to make a review about consequences of cannabis use in executive functioning. This review was carried out on reports drawn from MedLine, SciELO, and Lilacs. In studies investigating acute use effects, higher doses of tetrahydrocannabinol are associated to impairments in performance of nonsevere users in planning and control impulse tasks. However, chronic cannabis users do not show those impairments. Although demonstration of residual effects of cannabis in the executive functioning is controversial, persistent deficits seem to be present at least in a subgroup of chronic users after 28 days of abstinence. The neuropsychological studies found did not have as a main aim the evaluation of executive functioning. A criterial selection of standardized neuropsychological tests, more appropriate study designs as well as concomitant investigations with structural and functional neuroimaging techniques may improve the understanding of eventual neurotoxicity associated with cannabis use.
Etchell, Andrew C; Civier, Oren; Ballard, Kirrie J; Sowman, Paul F
2018-03-01
Stuttering is a disorder that affects millions of people all over the world. Over the past two decades, there has been a great deal of interest in investigating the neural basis of the disorder. This systematic literature review is intended to provide a comprehensive summary of the neuroimaging literature on developmental stuttering. It is a resource for researchers to quickly and easily identify relevant studies for their areas of interest and enable them to determine the most appropriate methodology to utilize in their work. The review also highlights gaps in the literature in terms of methodology and areas of research. We conducted a systematic literature review on neuroimaging studies on developmental stuttering according to the PRISMA guidelines. We searched for articles in the pubmed database containing "stuttering" OR "stammering" AND either "MRI", "PET", "EEG", "MEG", "TMS"or "brain" that were published between 1995/01/01 and 2016/01/01. The search returned a total of 359 items with an additional 26 identified from a manual search. Of these, there were a total of 111 full text articles that met criteria for inclusion in the systematic literature review. We also discuss neuroimaging studies on developmental stuttering published throughout 2016. The discussion of the results is organized first by methodology and second by population (i.e., adults or children) and includes tables that contain all items returned by the search. There are widespread abnormalities in the structural architecture and functional organization of the brains of adults and children who stutter. These are evident not only in speech tasks, but also non-speech tasks. Future research should make greater use of functional neuroimaging and noninvasive brain stimulation, and employ structural methodologies that have greater sensitivity. Newly planned studies should also investigate sex differences, focus on augmenting treatment, examine moments of dysfluency and longitudinally or cross-sectionally investigate developmental trajectories in stuttering. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
How Acute Total Sleep Loss Affects the Attending Brain: A Meta-Analysis of Neuroimaging Studies
Ma, Ning; Dinges, David F.; Basner, Mathias; Rao, Hengyi
2015-01-01
Study Objectives: Attention is a cognitive domain that can be severely affected by sleep deprivation. Previous neuroimaging studies have used different attention paradigms and reported both increased and reduced brain activation after sleep deprivation. However, due to large variability in sleep deprivation protocols, task paradigms, experimental designs, characteristics of subject populations, and imaging techniques, there is no consensus regarding the effects of sleep loss on the attending brain. The aim of this meta-analysis was to identify brain activations that are commonly altered by acute total sleep deprivation across different attention tasks. Design: Coordinate-based meta-analysis of neuroimaging studies of performance on attention tasks during experimental sleep deprivation. Methods: The current version of the activation likelihood estimation (ALE) approach was used for meta-analysis. The authors searched published articles and identified 11 sleep deprivation neuroimaging studies using different attention tasks with a total of 185 participants, equaling 81 foci for ALE analysis. Results: The meta-analysis revealed significantly reduced brain activation in multiple regions following sleep deprivation compared to rested wakefulness, including bilateral intraparietal sulcus, bilateral insula, right prefrontal cortex, medial frontal cortex, and right parahippocampal gyrus. Increased activation was found only in bilateral thalamus after sleep deprivation compared to rested wakefulness. Conclusion: Acute total sleep deprivation decreases brain activation in the fronto-parietal attention network (prefrontal cortex and intraparietal sulcus) and in the salience network (insula and medial frontal cortex). Increased thalamic activation after sleep deprivation may reflect a complex interaction between the de-arousing effects of sleep loss and the arousing effects of task performance on thalamic activity. Citation: Ma N, Dinges DF, Basner M, Rao H. How acute total sleep loss affects the attending brain: a meta-analysis of neuroimaging studies. SLEEP 2015;38(2):233–240. PMID:25409102
Making Individual Prognoses in Psychiatry Using Neuroimaging and Machine Learning.
Janssen, Ronald J; Mourão-Miranda, Janaina; Schnack, Hugo G
2018-04-22
Psychiatric prognosis is a difficult problem. Making a prognosis requires looking far into the future, as opposed to making a diagnosis, which is concerned with the current state. During the follow-up period, many factors will influence the course of the disease. Combined with the usually scarcer longitudinal data and the variability in the definition of outcomes/transition, this makes prognostic predictions a challenging endeavor. Employing neuroimaging data in this endeavor introduces the additional hurdle of high dimensionality. Machine-learning techniques are especially suited to tackle this challenging problem. This review starts with a brief introduction to machine learning in the context of its application to clinical neuroimaging data. We highlight a few issues that are especially relevant for prediction of outcome and transition using neuroimaging. We then review the literature that discusses the application of machine learning for this purpose. Critical examination of the studies and their results with respect to the relevant issues revealed the following: 1) there is growing evidence for the prognostic capability of machine-learning-based models using neuroimaging; and 2) reported accuracies may be too optimistic owing to small sample sizes and the lack of independent test samples. Finally, we discuss options to improve the reliability of (prognostic) prediction models. These include new methodologies and multimodal modeling. Paramount, however, is our conclusion that future work will need to provide properly (cross-)validated accuracy estimates of models trained on sufficiently large datasets. Nevertheless, with the technological advances enabling acquisition of large databases of patients and healthy subjects, machine learning represents a powerful tool in the search for psychiatric biomarkers. Copyright © 2018 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
PandaEPL: a library for programming spatial navigation experiments.
Solway, Alec; Miller, Jonathan F; Kahana, Michael J
2013-12-01
Recent advances in neuroimaging and neural recording techniques have enabled researchers to make significant progress in understanding the neural mechanisms underlying human spatial navigation. Because these techniques generally require participants to remain stationary, computer-generated virtual environments are used. We introduce PandaEPL, a programming library for the Python language designed to simplify the creation of computer-controlled spatial-navigation experiments. PandaEPL is built on top of Panda3D, a modern open-source game engine. It allows users to construct three-dimensional environments that participants can navigate from a first-person perspective. Sound playback and recording and also joystick support are provided through the use of additional optional libraries. PandaEPL also handles many tasks common to all cognitive experiments, including managing configuration files, logging all internal and participant-generated events, and keeping track of the experiment state. We describe how PandaEPL compares with other software for building spatial-navigation experiments and walk the reader through the process of creating a fully functional experiment.
PandaEPL: A library for programming spatial navigation experiments
Solway, Alec; Miller, Jonathan F.
2013-01-01
Recent advances in neuroimaging and neural recording techniques have enabled researchers to make significant progress in understanding the neural mechanisms underlying human spatial navigation. Because these techniques generally require participants to remain stationary, computer-generated virtual environments are used. We introduce PandaEPL, a programming library for the Python language designed to simplify the creation of computer-controlled spatial-navigation experiments. PandaEPL is built on top of Panda3D, a modern open-source game engine. It allows users to construct three-dimensional environments that participants can navigate from a first-person perspective. Sound playback and recording and also joystick support are provided through the use of additional optional libraries. PandaEPL also handles many tasks common to all cognitive experiments, including managing configuration files, logging all internal and participant-generated events, and keeping track of the experiment state. We describe how PandaEPL compares with other software for building spatial-navigation experiments and walk the reader through the process of creating a fully functional experiment. PMID:23549683
Characteristics of voxel prediction power in full-brain Granger causality analysis of fMRI data
NASA Astrophysics Data System (ADS)
Garg, Rahul; Cecchi, Guillermo A.; Rao, A. Ravishankar
2011-03-01
Functional neuroimaging research is moving from the study of "activations" to the study of "interactions" among brain regions. Granger causality analysis provides a powerful technique to model spatio-temporal interactions among brain regions. We apply this technique to full-brain fMRI data without aggregating any voxel data into regions of interest (ROIs). We circumvent the problem of dimensionality using sparse regression from machine learning. On a simple finger-tapping experiment we found that (1) a small number of voxels in the brain have very high prediction power, explaining the future time course of other voxels in the brain; (2) these voxels occur in small sized clusters (of size 1-4 voxels) distributed throughout the brain; (3) albeit small, these clusters overlap with most of the clusters identified with the non-temporal General Linear Model (GLM); and (4) the method identifies clusters which, while not determined by the task and not detectable by GLM, still influence brain activity.
Neurobiology Research Findings: How the Brain Works during Reading
ERIC Educational Resources Information Center
Kweldju, Siusana
2015-01-01
In the past, neurobiology for reading was identical with neuropathology. Today, however, the advancement of modern neuroimaging techniques has contributed to the understanding of the reading processes of normal individuals. Neurobiology findings today have uncovered and illuminated the fundamental neural mechanism of reading. The findings have…
Letzen, Janelle E; Robinson, Michael E
2017-01-01
The default mode network (DMN) has been proposed as a biomarker for several chronic pain conditions. Default mode network functional connectivity (FC) is typically examined during resting-state functional neuroimaging, in which participants are instructed to let thoughts wander. However, factors at the time of data collection (eg, negative mood) that might systematically impact pain perception and its brain activity, influencing the application of the DMN as a pain biomarker, are rarely reported. This study measured whether positive and negative moods altered DMN FC patterns in patients with chronic low back pain (CLBP), specifically focusing on negative mood because of its clinical relevance. Thirty-three participants (CLBP = 17) underwent resting-state functional magnetic resonance imaging scanning before and after sad and happy mood inductions, and rated levels of mood and pain intensity at the time of scanning. Two-way repeated-measures analysis of variances were conducted on resting-state functional connectivity data. Significant group (CLBP > healthy controls) × condition (sadness > baseline) interaction effects were identified in clusters spanning parietal operculum/postcentral gyrus, insular cortices, anterior cingulate cortex, frontal pole, and a portion of the cerebellum (PFDR < 0.05). However, only 1 significant cluster covering a portion of the cerebellum was identified examining a two-way repeated-measures analysis of variance for happiness > baseline (PFDR < 0.05). Overall, these findings suggest that DMN FC is affected by negative mood in individuals with and without CLBP. It is possible that DMN FC seen in patients with chronic pain is related to an affective dimension of pain, which is important to consider in future neuroimaging biomarker development and implementation.
Thompkins, Andie M.; Deshpande, Gopikrishna; Waggoner, Paul; Katz, Jeffrey S.
2017-01-01
Neuroimaging of the domestic dog is a rapidly expanding research topic in terms of the cognitive domains being investigated. Because dogs have shared both a physical and social world with humans for thousands of years, they provide a unique and socially relevant means of investigating a variety of shared human and canine psychological phenomena. Additionally, their trainability allows for neuroimaging to be carried out noninvasively in an awake and unrestrained state. In this review, a brief overview of functional magnetic resonance imaging (fMRI) is followed by an analysis of recent research with dogs using fMRI. Methodological and conceptual concerns found across multiple studies are raised, and solutions to these issues are suggested. With the research capabilities brought by canine functional imaging, findings may improve our understanding of canine cognitive processes, identify neural correlates of behavioral traits, and provide early-life selection measures for dogs in working roles. PMID:29456781
Bilenko, Natalia Y; Gallant, Jack L
2016-01-01
In this article we introduce Pyrcca, an open-source Python package for performing canonical correlation analysis (CCA). CCA is a multivariate analysis method for identifying relationships between sets of variables. Pyrcca supports CCA with or without regularization, and with or without linear, polynomial, or Gaussian kernelization. We first use an abstract example to describe Pyrcca functionality. We then demonstrate how Pyrcca can be used to analyze neuroimaging data. Specifically, we use Pyrcca to implement cross-subject comparison in a natural movie functional magnetic resonance imaging (fMRI) experiment by finding a data-driven set of functional response patterns that are similar across individuals. We validate this cross-subject comparison method in Pyrcca by predicting responses to novel natural movies across subjects. Finally, we show how Pyrcca can reveal retinotopic organization in brain responses to natural movies without the need for an explicit model.
Bilenko, Natalia Y.; Gallant, Jack L.
2016-01-01
In this article we introduce Pyrcca, an open-source Python package for performing canonical correlation analysis (CCA). CCA is a multivariate analysis method for identifying relationships between sets of variables. Pyrcca supports CCA with or without regularization, and with or without linear, polynomial, or Gaussian kernelization. We first use an abstract example to describe Pyrcca functionality. We then demonstrate how Pyrcca can be used to analyze neuroimaging data. Specifically, we use Pyrcca to implement cross-subject comparison in a natural movie functional magnetic resonance imaging (fMRI) experiment by finding a data-driven set of functional response patterns that are similar across individuals. We validate this cross-subject comparison method in Pyrcca by predicting responses to novel natural movies across subjects. Finally, we show how Pyrcca can reveal retinotopic organization in brain responses to natural movies without the need for an explicit model. PMID:27920675
Hulvershorn, Leslie; Cullen, Kathryn; Anand, Amit
2011-01-01
Child and adolescent psychiatric neuroimaging research typically lags behind similar advances in adult disorders. While the pediatric depression imaging literature is less developed, a recent surge in interest has created the need for a synthetic review of this work. Major findings from pediatric volumetric and functional magnetic resonance imaging (fMRI), magnetic resonance spectroscopy (MRS), diffusion tensor imaging (DTI) and resting state functional connectivity studies converge to implicate a corticolimbic network of key areas that work together to mediate the task of emotion regulation. Imaging the brain of children and adolescents with unipolar depression began with volumetric studies of isolated brain regions that served to identify key prefrontal, cingulate and limbic nodes of depression-related circuitry elucidated from more recent advances in DTI and functional connectivity imaging. Systematic review of these studies preliminarily suggests developmental differences between findings in youth and adults, including prodromal neurobiological features, along with some continuity across development. PMID:21901425
Bruder, Gerard E; Stewart, Jonathan W; McGrath, Patrick J
2017-07-01
The right and left side of the brain are asymmetric in anatomy and function. We review electrophysiological (EEG and event-related potential), behavioral (dichotic and visual perceptual asymmetry), and neuroimaging (PET, MRI, NIRS) evidence of right-left asymmetry in depressive disorders. Recent electrophysiological and fMRI studies of emotional processing have provided new evidence of altered laterality in depressive disorders. EEG alpha asymmetry and neuroimaging findings at rest and during cognitive or emotional tasks are consistent with reduced left prefrontal activity in depressed patients, which may impair downregulation of amygdala response to negative emotional information. Dichotic listening and visual hemifield findings for non-verbal or emotional processing have revealed abnormal perceptual asymmetry in depressive disorders, and electrophysiological findings have shown reduced right-lateralized responsivity to emotional stimuli in occipitotemporal or parietotemporal cortex. We discuss models of neural networks underlying these alterations. Of clinical relevance, individual differences among depressed patients on measures of right-left brain function are related to diagnostic subtype of depression, comorbidity with anxiety disorders, and clinical response to antidepressants or cognitive behavioral therapy. Copyright © 2017 Elsevier Ltd. All rights reserved.
Morris, Gerwyn; Berk, Michael; Puri, Basant K
2018-04-01
There is copious evidence of abnormalities in resting-state functional network connectivity states, grey and white matter pathology and impaired cerebral perfusion in patients afforded a diagnosis of multiple sclerosis, major depression or chronic fatigue syndrome (CFS) (myalgic encephalomyelitis). Systemic inflammation may well be a major element explaining such findings. Inter-patient and inter-illness variations in neuroimaging findings may arise at least in part from regional genetic, epigenetic and environmental variations in the functions of microglia and astrocytes. Regional differences in neuronal resistance to oxidative and inflammatory insults and in the performance of antioxidant defences in the central nervous system may also play a role. Importantly, replicated experimental findings suggest that the use of high-resolution SPECT imaging may have the capacity to differentiate patients afforded a diagnosis of CFS from those with a diagnosis of depression. Further research involving this form of neuroimaging appears warranted in an attempt to overcome the problem of aetiologically heterogeneous cohorts which probably explain conflicting findings produced by investigative teams active in this field. However, the ionising radiation and relative lack of sensitivity involved probably preclude its use as a routine diagnostic tool.
Spatial Bayesian latent factor regression modeling of coordinate-based meta-analysis data.
Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D; Nichols, Thomas E
2018-03-01
Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the article are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to (i) identify areas of consistent activation; and (ii) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterized as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. © 2017, The International Biometric Society.