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Functional Imaging: Magnetic Resonance Imaging
Abstract
Magnetic resonance imaging (MRI) has had a substantial clinical impact since the first commercial scanners were introduced in the early 1980s. The ability to image most human tissue and a wide range of pathologies at high-resolution and high anatomic contrast has led to the explosive propagation of MRI scanners worldwide. Anatomic MRI has enabled identification of tumors, lesions, and other pathologies throughout the body and has been particularly effective and suitable for brain imaging due to the predominance of its MR-differentiable soft tissue, lack of motion, and high levels of magnetic field homogeneity relative to the rest of the body.
... After several processing steps, the information captured in the images was translated into statistical maps representing an indirect indicator of the regional neural activity underpinning cognitive processing (Bandettini, 2006). ...
... The scanner actually works by taking thousands of images of the brain activity (i.e. the BOLD signal). After several steps of processing, these are translated into statistical maps representing an indirect indicator of regional neural activity that underpins cognitive processing (Bandettini, 2006). ...
In this article we argue that in order to understand failure or success in adapting to environmental change, we should better understand why people hesitate to pursue novel choices. This article asks: what forces hinder individuals’ exploration choices of different alternatives, and hence their ability to learn from them? To answer this question, this article looks to the cognitive sciences to identify a set of plausible mechanisms that hinder people’s tendency to explore. So far, “exploration” has been studied as a relatively monolithic behavior. Instead, we propose that exploration can be characterized in terms of some distinctive forces behind it. On one hand, agents experience “attachment” to choices that proved successful in the past, and hence comfort when sticking with them. On the other hand, they also experience concerns about less familiar options, as they lack knowledge about “distant” choices that have not been tried for a long time, or ever. We propose that high attachment is related to anxiety, and high distance to fear. Both these negative affective states hinder exploration. We find and discuss preliminary and tentative evidence of this effect.
... Termination of the RF pulse causes the protons to exponentially recover alignment with the external magnetic field in the z plane (Atlas, 2009). The time constant describing the rate of recovery in the z direction is denoted Bandettini, 2006). The time constant describing signal decay on the x − y plane, resulting from dephasing of the precessing protons, is denoted T 2 . ...
... However, extracting neuron-specific information from BOLD data is complicated because the signals depend on factors other than neuronal activity, being composed of complex interactions between neuronal activity, metabolism, blood flow, and blood volume (Bandettini, 2009b). Since these factors are regionally dependent, it is only meaningful to examine changes in the BOLD signal; BOLD is not considered a quantitative measure (Bandettini, 2006). Moreover, signal changes in BOLD appear to be determined by local field potentials, which provide a measure of the sum of local neuronal activity rather than neuronal spiking (Viswanatham and Freeman, 2007). ...
... Las características de este tipo de registro conllevan a una menor precisión de los datos obtenidos en su aspecto temporal. Esto se debe al hiato temporal que existe entre el proceso de detección de la actividad hemodinámica en el cerebro (de una duración de segundos) y la activación neuronal (en el orden de los milisegundos), considerada responsable de los procesos cognitivos bajo estudio (Bandettini, 2006). ...
Functional magnetic resonance imaging is one of the most commonly used neuroimaging techniques in cognitive neuroscience. Its influence had a central role in establishing the experimental side of the field. Given this, we consider that its status as a source of evidence has not been sufficiently dealt within the philosophical literature. We focus on this issue from the standpoint of the classical problem of defining the scope of localizationist approaches in neuroscience. We attend to the way this tension unfolds today, considering some recent examples of neuroscientific approaches that tackle the dynamic character of the brain's large scale activity. We take into account a number of limitations that functional magnetic resonance imaging presents, distinguishing those of them whose treatment involves not merely technical issues. On the basis of an analysis of some ways researchers deal with them, we claim that there is a considerable extent in which this kind of neuroimaging studies can be oriented according to general assumptions and theoretical considerations. We conclude that this particular theoretical permeability is a main factor affecting the technique's status as neuroscientific evidence.
... However, EEG has a very poor spatial resolution, which is additionally complicated by having to solve the inverse problem [for a review of the properties of EEG see Rippon, 2006]. Conversely, fMRI has an excellent spatial resolution, but it images hemodynamic activity, which not only is an indirect measure of neuronal activity, but also has a rather low temporal resolution [for a review of the properties of fMRI see Bandettini, 2006]. Likewise, when choosing almost any other noninvasive neuroscientific method, such as magnetoencephalography, positron emission tomography, near infrared spectroscopy, etc., researchers have to make a decision between poor temporal or poor spatial resolution and decide between the lesser of two evils. ...
Performance errors are associated with distinct electrophysiological and hemodynamic signatures: a fronto-central error-related negativity (ERN) is seen in the event-related potentials and a network of activations including medio-frontal, parietal, and insular cortex is revealed by functional magnetic resonance imaging. We used simultaneous electroencephalography and functional magnetic resonance imaging (fMRI) to characterize the relationship between the electrophysiological and hemodynamic responses to errors. Participants performed a modified Flanker task. When analyzed independently, we found the ERN and hemodynamic activations in dorsal anterior cingulate cortex, superior frontal gyrus, precentral gyrus, inferior frontal gyrus, and inferior parietal lobule. fMRI-informed dipole modeling and joint independent component analysis (ICA) were used to couple electrophysiological and hemodynamic data. Both techniques revealed a temporal evolution of the areas found in the fMRI analysis, with the right hemisphere activations peaking before the left hemisphere. However, joint ICA added information, revealing a number of cortical and subcortical areas that had not been shown with parametric mapping. This technique also uncovered how these areas evolve over time. All together, these analyses provide a more detailed picture of the spatiotemporal dynamics of the processing of performance errors.
... Deoxyhemoglobin has a different susceptibility than surrounding brain tissue and water, whereas oxyhemoglobin has the same susceptibility. A hemoglobin molecule that has a different susceptibility from its surrounding tissue creates a magnetic field distortion when placed in a magnetic field [109]. When there is an increase in the activity of neurons, there is also an increase in the blood volume and oxygen consumption in that area. ...
In dit project onderzoeken we verschillende componenten die te maken hebben met aandacht. Aandacht is een term die gebruikt wordt om een brede waaier van processen te beschrijven. Zoals bijvoorbeeld het verplaatsen van de aandacht naar een bepaalde positie in het visuele veld, uw aandacht richten op bepaalde kenmerken van een figuur, de aandacht erbij houden (cognitieve controle), ... . Na een cerebrovasculair accident (CVA) kunnen er zich aandachtproblemen voordoen zoals bijvoorbeeld neglect (het niet bewust zijn van objecten in het contralesionele (= tegengestelde kant van het letsel) gezichtsveld), visuele extinctie (wanneer 2 stimuli worden aangeboden, enkel degene waarnemen die het meest ipsilesioneel staat in het gezichtveld), gebrek aan cognitieve controle, ... . We proberen deze aandachtsprocessen te onderscheiden door gebruikt te maken van psychofysische studies, anatomische studies bij patiënten met een CVA en functionele beeldvormingsexperimenten (fMRI) bij gezonde vrijwilligers.
In een eerste reeks van experimenten onderzoeken we het effect van de relatieve positie van een afleidende stimulus t.o.v. een relevante stimulus op het aandachtsnetwerk. We [1] hebben reeds ontdekt dat wanneer proefpersonen tijdens een fMRI experiment hun aandacht moeten richten op een stimulus er meer activatie is in de sulcus intraparietalis wanneer er een tweede irrelevante stimulus wordt getoond dan wanneer er geen afleidende stimulus wordt getoond. di Pellegrino en de Renzi [2] testen een patiënt met visuele extinctie en beschrijven dat de persoon geen probleem heeft om twee figuren tegelijkertijd waar te nemen wanneer deze figuren onder elkaar staan, maar wanneer de figuren naast elkaar staan dan neemt de patiënt de meest linkse van de 2 figuren niet waar. In ons onderzoek testen we ook of het iets uit maakt als we de 2 figuren naast elkaar presenteren of onder elkaar. We testen 20 patiënten met een CVA met een experiment waarbij we de plaats van de afleidende stimulus manipuleren (op de horizontale as t.o.v. de target of op de verticale as t.o.v. de target) en doen een MRI scan om de plaats van hun letsel te localiseren. Daarnaast testen we hetzelfde experiment tijdens een fMRI experiment met 23 gezonde vrijwilligers. We vinden dat de patiënten met een letsel in de rechter sulcus intraparietalis en rechter inferieure pariëtale regio meer problemen hebben met het waarnemen van een stimulus in het contralesionele gezichtveld als er op hetzelfde moment een irrelevante stimulus in het ipsilesionele gezichtsveld staat in het symmetrische quadrant in vergelijking met een irrelevante stimulus in hetzelfde gezichtsveld in het andere quadrant. Dezelfde patiënten hebben ook een slechtere score op testen voor neglect en visuele extinctie. Gezonde vrijwilligers tonen tijdens hetzelfde experiment in de scanner meer activatie in de sulcus intraparietalis tijdens de conditie waarbij de irrelevante stimulus in het andere gezichtsveld op een horizontale as staat in vergelijking met wanneer deze in hetzelfde gezichtsveld staat op een verticale as. De kritieke regio bij de patiënten en de activatie bij de gezonde vrijwilligers overlapt in de rechter sulcus intraparietalis. We hebben in enkele controle experimenten dan verder deze regio onderzocht en vinden dat deze regio vooral actief is wanneer de irrelevante stimulus op een horizontale as staat t.o.v. de relevante stimulus, los van het feit of die in het andere gezichtveld staat.
In een tweede reeks van experimenten gingen we d.m.v. fMRI bij gezonde vrijwilligers na welke gebieden in de hersenen actief zijn tijdens enerzijds ”verplaatsen van de aandacht” en anderzijds ”het herschikken van aandachtsgewichten” zoals beschreven in de theorie van visuele aandacht [3]. Met ”herschikken van aandachtsgewichten” wordt het proces bedoeld waarbij de hersenen verschillende aandachtsgewichten geven aan objecten of eigenschappen van objecten (bv. kleur, vorm, ...) in onze omgeving die voor ons relevant (hoog aandachtsgewicht) of niet relevant (laag aandachtsgewicht) zijn. We vinden dat tijdens het verplaatsen van de aandacht vooral de lobulus parietalis superior actief is. Dit gebied is zowel actief tijdens een verplaatsing van de stimulus, als wanneer de aandacht moest verplaatst worden door het feit dat een ander object relevant wordt. De sulcus intraparietalis aan de andere kant is vooral actief tijdens het ”herschikken van aandachtsgewichten” zelfs als de aandacht niet verplaatst hoeft te worden, bijvoorbeeld als figuren van vorm veranderen en er dus nieuwe aandachtsgewichten aan de figuren moeten gegeven worden.
In een derde reeks van experimenten testen we 44 patiënten met een CVA op een reeks van spatiële en niet-spatiële aandachtstaken. Als niet-spatiële aandachtstaak gebruiken we de ”Sustained Attention to Response Task” (SART) [4]. In deze test moeten proefpersonen op een knop drukken telkens als ze een cijfer zien (gaande van 1 t.e.m. 9), behalve bij het cijfer 3. Wanneer proefpersonen toch drukken bij het cijfer 3 noemt men dit een commissie fout. Na een commissie fout gaan mensen hun reactietijd vertragen in de volgende trial (= post-error slowing) omdat ze zojuist een fout hebben gemaakt en dus niet terug dezelfde fout willen maken. Mensen willen dus terug cognitieve controle verwerven. We vinden dat patiënten met een letsel in de sulcus frontalis inferior geen post-error slowing vertonen. Daarenboven vinden we geen verband tussen de spatiële en niet-spatiële aandachtstaken. Dus om samen te vatten, we hebben drie gebieden kunnen onderscheiden die belangrijk zijn bij aandachtsprocessen.
1. De eerste is de lobulus parietalis superior die vooral actief was bij het verplaatsen van de aandacht.
2. De tweede is de sulcus intraparietalis die vooral actief is tijdens ”het herschikken van aandachtsgewichten”, bijvoorbeeld wanneer subjecten moeten kiezen tussen verschillende figuren of wanneer de relevantie van een figuur verandert.
3. De derde regio is de sulcus frontalis inferior . Letsels in deze regio kunnen leiden tot een verminderde congnitieve controle.
Dit project heeft bijgedragen tot een betere kennis van de functionele betekenis van de verschillende anatomische componenten betrokken bij aandacht. Daarnaast hebben we bijgedragen tot een beter inzicht in de ziekte-mechanismen die gepaard gaan met aandachtsproblemen zoals neglect, visuele extinctie en gebrek aan cognitieve controle.
[1] R. Vandenberghe, S. Geeraerts, P. Molenberghs, C. Lafosse, M. Vandenbulcke, K. Peeters, R. Peeters, P. Van Hecke, and G.A. Orban. Attentional responses to unattended stimuli in human parietal cortex. Brain, 128:2843–2857, 2005.
[2] G. di Pellegrino and E. de Renzi. An experimental investigation on the nature of extinction. Neuropsychologia, 33:153–170, 1995.
[3] C. Bundesen, T. Habekost, and S. Kyllingsbaek. A neural theory of visual attention: Bridging cognition and neurophysiology. Psychol Rev, 112:291–328, 2005.
[4] I.H. Robertson, T. Manly, J. Andrade, B.T. Baddeley, and J. Yiend. ’Oops!’: Performance correlates of everyday attentional failures in traumatic brain injured and normal subjects. Neuropsychologia, 35(6):747–758, 1997.
By using different methods (fMRI, VLSM, psychophysics) and studying different groups (healthy volunteers and stroke patients), we disentangle some of the processes that are associated with attention and relate them with different brain regions. By subdividing the broad term ”attention” into more precisely defined processes, the individual processes can be defined more precisely so that ”attention” can be somewhere instead of everywhere. In our studies we define the differential contribution of 3 different brain regions to attention.
1. The superior parietal lobule is involved during spatial attentional shifts, elicited by a displacement of a stimulus or when a change in stimulus relevance elicites a spatial shift.
2. The middle third of the intraparietal sulcus is more involved during the calibration of relative attentional weights, for instance when subjects have to select between competing stimuli, or when stimuli change and a saliency map must be re-compiled.
3. The third region is the inferior frontal sulcus. Lesions in this region are associated with non-spatial attentional deficits that can lead to diminished cognitive control.
In chapter 2, we examine the role of the axis of configuration between target and distracter during spatially selective attention. We find a region of overlap in the right intraparietal sulcus between an fMRI study with 23 healthy volunteers and a VLSM study with 20 patients with ischemic stroke. This region shows activation during the fMRI study when the axis of configuration between distracter and target was horizontal compared to diagonal or vertical. Patients with a lesion in this region show impairment during contralesional orienting when the distracter is in the ipsilesional hemifield at a symmetrical position compared with a distracter that occupies the diagonal position in the ipsilesional hemifield or the opposite quadrant within the same hemifield. We find that the crucial factor was whether or not the configuration axis was horizontal, regardless of symmetry or bilaterality.
In chapter 3, we use fMRI to study the role of posterior parietal cortex during the re-mapping of attentional priorities. In the main experiment, we find that the superior parietal lobule is preferentially active in all conditions where a spatial displacement occurres in either the location of the target or the distracter, regardless of whether this change is driven endogenously or exogenously. In a second, ”auditory switching” experiment, we find that SPL is also more activate in absence of any visual change when an auditory cue indicated a shift of the focus of attention compared with no shift. The intraparietal sulcus region on the other hand, is more activate by transient re-setting of target significance when the stimulus configuration changes (feature attention shifts) compared with no change, even when there is no spatial shift of attention.
In chapter 4, we investigate the neuroanatomy of non-spatial attentional deficits by studying 44 patients with ischemic stroke. We use VLSM to investigate the critical lesion site and use spatial and non-spatial behavioral parameters as input. We find that lesions of the right inferior frontal gyrus lead to a significant increase in commission error rate and lesions of the middle third of the right inferior frontal sulcus lead to a reduction of post-error slowing. We demonstrate that the right inferior frontal sulcus plays a critical role in the readjustment of cognitive resources following errors, providing strong evidence that IFS is a critical region in cognitive control. In the acute phase spatial attentional deficits were associated with lesions of the posterior end of the right superior frontal sulcus. This provides evidenc for a dissociation between spatial and non-spatial processing in the right frontal convexity.
Doctor of Medical Sciences Afdeling Experimentele Neurologie Departement Neurowetenschappen Faculteit Geneeskunde Doctoral thesis Doctoraatsthesis
Driven by an appreciation of the field’s early stage of development, I apply the concept of exploratory experimentation, originally put forward in the late 90s philosophy of biology, to current research in cognitive neuroscience. I concentrate on functional magnetic resonance imaging and how this wide-spread technique is used, from experimental design to data analysis. I claim that, although subject to certain significant modifications with respect to the concept’s original rendering, the exploratory character of neuroimaging experiments can be appreciated considering their goals, centered on the stabilization of experimental systems for phenomenological description, and the relevance of their methodological facet. Although I do not claim that there is a specific kind of experiment that one can single out as definitely exploratory, exploration can be seen as a general trait imbuing fMRI-based experimentation.
Örgütsel bilişsel nörobilim, örgütlerin uygulamalı ortamında insan davranışları hakkındaki anlayışı açıklığa kavuşturmak ve davranışların sebeplerini anlamak için nörobilimsel yöntemlerin uygulandığı bir alandır (Butler ve Senior, 2007a: 8). Yıllar içerisinde örgütsel süreçlerin analizinde, gelişen nörobilimsel araştırma stratejilerinden faydalanma eğilimi artmaktadır. Örgütsel bilişsel nörobilim literatürüne dair çalışmaların sınırlı sayıda olduğu Türkiye’de, literatür taraması yapan ve bu yeni alanı keşfe çıkan çalışma bulunmamaktadır. Bu tez çalışması, örgütsel bilişsel nörobilimin nasıl tanımlandığı, çalışma konularının, araştırma metotlarının ve yönetim alanyazınına katkılarının neler olduğu sorularına yanıt arayarak teorik çerçevede, yönetim alanyazınında yeni bir alan olan örgütsel bilişsel nörobilimi betimleme amacı gütmekte ve pratik çerçevede örgütsel bilişsel nörobilimi çalışmalarına dâhil etmek isteyen yönetim araştırmacılarına genel bir tablo sunarak rehber olmayı ummaktadır. Bu çalışmada, yayım dili İngilizce olan 51 adet örgütsel bilişsel nörobilim makalesinin içerik analizi, nitel içerik analiz yönteminden yararlanılarak yapılmıştır. Derinlemesine incelenen makaleler, araştırma sorularını temsil edecek şekilde “Kuram ve Yöntem”, “Örgütsel Davranış” ve “Liderlik” olmak üzere üç tema etrafında toplanmıştır. Sınırları hususunda henüz fikir birliği sağlanamamış olan örgütsel bilişsel nörobilim alanında, alanı tanımlama çabalarının önemli bir yer tuttuğu ve çeşitli araştırma konularının ele alındığı görülmektedir. Teorik çerçevede bu çalışma, örgütteki insan davranışının altında yatan sebeplere odaklanan örgütsel bilişsel nörobilim alanını keşfe çıkarak, yönetim literatürüne bir sentez sağlamaktadır. Pratik çerçevede, nörobilimsel bilginin iş ortamına nasıl uygulanacağına dair yönetim araştırmacılarına yeni sorunsallarla ilgili işaretler vermektedir.
Traditionally, electroencephalographic (EEG) and event-related brain potentials (ERPs) research on visual attentional processing attempted to account for mental processes in conceptual terms without reference to the way in which they were physically realized by the anatomical structures and physiological processes of the human brain. The brain science level of analysis, in contrast, attempted to explain the brain as an information processing system and to explain mental events in terms of brain processes. Somehow overcoming the separation between the two abovementioned levels of analysis, the cognitive neuroscience level considered how information was represented and processed in the brain. Neurofunctional processing takes place in a fraction of a second. Hence, the very high time resolution and the reliable sensitivity of EEG and ERPs in detecting fast functional changes in brain activity provided advantages over hemodynamic imaging techniques such as positron emission tomography (PET) or functional magnetic resonance imaging (fMRI), as well as over behavioral measures. However, volume conduction and lack of three-dimensionality limited applications of EEG and ERPs per se more than hemodynamic techniques for revealing locations in which brain processing occurs. These limits could only be overcome by subtraction methods for isolating attentional effects that might endure over time in EEG and may be riding even over several different ERP components, and by intracerebral single and distributed electric source analyses as well as the combining of these signals with high-spatial resolution hemodynamic signals (fMRI), both in healthy individuals and clinical patients. In my view, the articles of the Special Issue concerned with “ERP and EEG Markers of Brain Visual Attentional Processing” of the present journal Brain Sciences provide very good examples of all these levels of analysis.
In the article the author analyzed the idea of neuroplasticity-human brain change throughout person life under pressure of social, economic, cultural, and other factors-as a source of the increasing interest in human brain studies and widespread of the ideas of neuroscience within the body of scientific knowledge and beyond the laboratories. An opportunity to influence on social behavior by chemical brain intervention and neurostimulation attracted the attention of the politicians, militaries and pharmacological companies. The idea of brain plasticity was also continued in novel interdisciplinary research areas-social cognitive and affective neuroscience, cultural neuroscience, neuroeconomics, neurosociology, and others. This whole positive trend has a flaw. The transition from neuroscience facts to its social applications sometimes accompanies by information loss and misinterpretation. This damaged neuroscience and lead to dissemination of false ideas, promoting ambiguous social activity, strengthening control over person by access to the information ‘encrypted’ on the neural level. The analysis also sheds light on the background of the discussed recently neuroethics issues.
The capacity to identify the unique functional architecture of an individual's brain is a crucial step toward personalized medicine and understanding the neural basis of variation in human cognition and behavior. Here we developed a cortical parcellation approach to accurately map functional organization at the individual level using resting-state functional magnetic resonance imaging (fMRI). A population-based functional atlas and a map of inter-individual variability were employed to guide the iterative search for functional networks in individual subjects. Functional networks mapped by this approach were highly reproducible within subjects and effectively captured the variability across subjects, including individual differences in brain lateralization. The algorithm performed well across different subject populations and data types, including task fMRI data. The approach was then validated by invasive cortical stimulation mapping in surgical patients, suggesting potential for use in clinical applications.
Resting-state functional MRI (rs-fMRI) permits study of the brain's functional networks without requiring participants to perform tasks. Robust changes in such resting state networks (RSNs) have been observed in neurologic disorders, and rs-fMRI outcome measures are candidate biomarkers for monitoring clinical trials, including trials of extended therapeutic interventions for rehabilitation of patients with chronic conditions. In this study, we aim to present a unique longitudinal dataset reporting on a healthy adult subject scanned weekly over 3.5 years and identify rs-fMRI outcome measures appropriate for clinical trials. Accordingly, we assessed the reproducibility, and characterized the temporal structure of, rs-fMRI outcome measures derived using independent component analysis (ICA). Data was compared to a 21-person dataset acquired on the same scanner in order to confirm that the values of the single-subject RSN measures were within the expected range as assessed from the multi-participant dataset. Fourteen RSNs were identified, and the inter-session reproducibility of outcome measures-network spatial map, temporal signal fluctuation magnitude, and between-network connectivity (BNC)-was high, with executive RSNs showing the highest reproducibility. Analysis of the weekly outcome measures also showed that many rs-fMRI outcome measures had a significant linear trend, annual periodicity, and persistence. Such temporal structure was most prominent in spatial map similarity, and least prominent in BNC. High reproducibility supports the candidacy of rs-fMRI outcome measures as biomarkers, but the presence of significant temporal structure needs to be taken into account when such outcome measures are considered as biomarkers for rehabilitation-style therapeutic interventions in chronic conditions.
Functional magnetic resonance imaging (fMRI) studies typically collapse data from many subjects, but brain functional organization varies between individuals. Here we establish that this individual variability is both robust and reliable, using data from the Human Connectome Project to demonstrate that functional connectivity profiles act as a 'fingerprint' that can accurately identify subjects from a large group. Identification was successful across scan sessions and even between task and rest conditions, indicating that an individual's connectivity profile is intrinsic, and can be used to distinguish that individual regardless of how the brain is engaged during imaging. Characteristic connectivity patterns were distributed throughout the brain, but the frontoparietal network emerged as most distinctive. Furthermore, we show that connectivity profiles predict levels of fluid intelligence: the same networks that were most discriminating of individuals were also most predictive of cognitive behavior. Results indicate the potential to draw inferences about single subjects on the basis of functional connectivity fMRI.
Magnetic resonance spectroscopy (MRS) provides unique information about the neurobiological substrates of brain function in health and disease. However, many of the physical principles underlying MRS are distinct from those underlying magnetic resonance imaging, and they may not be widely understood by neuroscientists new to this methodology. This review describes these physical principles and many of the technical methods in current use for MRS experiments. A better understanding these principles and methods may help investigators select pulse sequences and quantification methods best suited to the aims of their research program and avoid pitfalls that can hamper new investigators in this field.
Significance
Recently, it was shown that functional connectivity patterns exhibit complex spatiotemporal dynamics at the scale of tens of seconds. Of particular interest is the observation of a limited set of quasi-stable, whole-brain, recurring configurations—commonly referred to as functional connectivity states (FC states)—hypothesized to reflect the continuous flux of cognitive processes. Here, to test this hypothesis, subjects were continuously scanned as they engaged in and transitioned between mental states dictated by tasks. We demonstrate that there is a strong relationship between FC states and ongoing cognition that permits accurate tracking of mental states in individual subjects. We also demonstrate how informative changes in connectivity are not restricted solely to those regions with sustained elevations in activity during task performance.
Spider phobics show an exaggerated fear response when encountering spiders. This fear response is aggravated by negative and irrational beliefs about the feared object. Cognitive reappraisal can target these beliefs, and therefore has a fear regulating effect. The presented study investigated if neurofeedback derived from functional magnetic resonance imaging (fMRI) would facilitate anxiety regulation by cognitive reappraisal, using spider phobia as a model of anxiety disorders. Feedback was provided based on activation in left dorsolateral prefrontal cortex and right insula, as indicators of engagement and regulation success, respectively.
Eighteen female spider phobics participated in a randomized, controlled, single-blinded study. All participants completed a training session in the MRI scanner. Participants assigned to the neurofeedback condition were instructed to shape their regulatory strategy based on the provided feedback. Participants assigned to the control condition were asked to adapt their strategy intuitively.
Neurofeedback participants exhibited lower anxiety levels than the control group at the end of the training. In addition, only neurofeedback participants achieved down-regulation of insula activation levels by cognitive reappraisal. Group differences became more pronounced over time, supporting learning as a mechanism behind this effect. Importantly, within the neurofeedback group, achieved changes in insula activation levels during training predicted long-term anxiety reduction.
The conducted study provides first evidence that fMRI neurofeedback has a facilitating effect on anxiety regulation in spider phobia.
Objective
Pathology in both cortex and deep gray matter contribute to disability in multiple sclerosis (MS). We used the increased signal-to-noise ratio of 7-tesla (7T) MRI to visualize small lesions within the thalamus and to relate this to clinical information and cortical lesions.
Methods
We obtained 7T MRI scans on 34 MS cases and 15 healthy volunteers. Thalamic lesion number and volume were related to demographic data, clinical disability measures, and lesions in cortical gray matter.
Results
Thalamic lesions were found in 24/34 of MS cases. Two lesion subtypes were noted: discrete, ovoid lesions, and more diffuse lesional areas lining the periventricular surface. The number of thalamic lesions was greater in progressive MS compared to relapsing–remitting (mean ±SD, 10.7 ±0.7 vs. 3.0 ±0.7, respectively, p < 0.001). Thalamic lesion burden (count and volume) correlated with EDSS score and measures of cortical lesion burden, but not with white matter lesion burden or white matter volume.
Conclusions
Using 7T MRI allows identification of thalamic lesions in MS, which are associated with disability, progressive disease, and cortical lesions. Thalamic lesion analysis may be a simpler, more rapid estimate of overall gray matter lesion burden in MS.
While reducing the burden of brain disorders remains a top priority of organizations like the World Health Organization and National Institutes of Health, the development of novel, safe and effective treatments for brain disorders has been slow. In this paper, we describe the state of the science for an emerging technology, real time functional magnetic resonance imaging (rtfMRI) neurofeedback, in clinical neurotherapeutics. We review the scientific potential of rtfMRI and outline research strategies to optimize the development and application of rtfMRI neurofeedback as a next generation therapeutic tool. We propose that rtfMRI can be used to address a broad range of clinical problems by improving our understanding of brain–behavior relationships in order to develop more specific and effective interventions for individuals with brain disorders. We focus on the use of rtfMRI neurofeedback as a clinical neurotherapeutic tool to drive plasticity in brain function, cognition, and behavior. Our overall goal is for rtfMRI to advance personalized assessment and intervention approaches to enhance resilience and reduce morbidity by correcting maladaptive patterns of brain function in those with brain disorders.
Over the past decade, functional Magnetic Resonance Imaging (fMRI) has emerged as a powerful new instrument to collect vast quantities of data about activity in the human brain. A typical fMRI experiment can produce a three-dimensional image related to the human subject's brain activity every half second, at a spatial resolution of a few millimeters. As in other modern empirical sciences, this new instrumentation has led to a flood of new data, and a corresponding need for new data analysis methods. We describe recent research applying machine learning methods to the problem of classifying the cognitive state of a human subject based on fRMI data observed over a single time interval. In particular, we present case studies in which we have successfully trained classifiers to distinguish cognitive states such as (1) whether the human subject is looking at a picture or a sentence, (2) whether the subject is reading an ambiguous or non-ambiguous sentence, and (3) whether the word the subject is viewing is a word describing food, people, buildings, etc. This learning problem provides an interesting case study of classifier learning from extremely high dimensional (105 features), extremely sparse (tens of training examples), noisy data. This paper summarizes the results obtained in these three case studies, as well as lessons learned about how to successfully apply machine learning methods to train classifiers in such settings.
A relationship between working memory impairment, disordered neuronal oscillations, and abnormal prefrontal GABA function has been hypothesized in schizophrenia; however, in vivo GABA measurements and gamma band neural synchrony have not yet been compared in schizophrenia. This case-control pilot study (N = 24) compared baseline and working memory task-induced neuronal oscillations acquired with high-density electroencephalograms (EEGs) to GABA levels measured in vivo with magnetic resonance spectroscopy. Working memory performance, baseline GABA level in the left dorsolateral prefrontal cortex (DLPFC), and measures of gamma oscillations from EEGs at baseline and during a working memory task were obtained. A major limitation of this study is a relatively small sample size for several analyses due to the integration of diverse methodologies and participant compliance. Working memory performance was significantly lower for patients than for controls. During the working memory task, patients (n = 7) had significantly lower amplitudes in gamma oscillations than controls (n = 9). However, both at rest and across working memory stages, there were significant correlations between gamma oscillation amplitude and left DLPFC GABA level. Peak gamma frequency during the encoding stage of the working memory task (n = 16) significantly correlated with GABA level and working memory performance. Despite gamma band amplitude deficits in patients across working memory stages, both baseline and working memory-induced gamma oscillations showed strong dependence on baseline GABA levels in patients and controls. These findings suggest a critical role for GABA function in gamma band oscillations, even under conditions of system and cognitive impairments as seen in schizophrenia.
Impairment in consciousness is common in acute stroke patients and is correlated with the clinical outcome after stroke. The underlying mechanism is not completely understood, with little known about brain activity and connectivity changes in acute stroke patients having impaired consciousness. In this study, we investigated changes in regional brain activity and brain networks of consciousness impaired stroke patients, as well as the amplitude of spontaneous low frequency fluctuation (ALFF) of each time series. Regional homogeneity (ReHo) of each voxel was measured, and resting state network analysis was consequently conducted. Results from this study demonstrate that, compared to normal subjects, the intensities of ALFF and ReHo, as well as the strength of the default mode network (DMN) connectivity, were significantly decreased in the precuneus and posterior cingulate cortex regions among stroke patients with impaired consciousness. Furthermore, the strength of the DMN was highly correlated with differences in the Glasgow Coma Scale (GCS) scores between the onset time and the scanning time. Results from this study suggest that the resting state fMRI is a feasible tool for the evaluation of acute stroke patients with an early impairment of consciousness. The detailed mechanisms, implications of these brain activities and networks exhibiting changes will require further investigation.
Functional connectivity analysis of resting state blood oxygen level-dependent (BOLD) functional MRI is widely used for noninvasively studying brain functional networks. Recent findings have indicated, however, that even small (≤1 mm) amounts of head movement during scanning can disproportionately bias connectivity estimates, despite various preprocessing efforts. Further complications for interregional connectivity estimation from time domain signals include the unaccounted reduction in BOLD degrees of freedom related to sensitivity losses from high subject motion. To address these issues, we describe an integrated strategy for data acquisition, denoising, and connectivity estimation. This strategy builds on our previously published technique combining data acquisition with multiecho (ME) echo planar imaging and analysis with spatial independent component analysis (ICA), called ME-ICA, which distinguishes BOLD (neuronal) and non-BOLD (artifactual) components based on linear echo-time dependence of signals-a characteristic property of BOLD signal changes. Here we show for 32 control subjects that this method provides a physically principled and nearly operator-independent way of removing complex artifacts such as motion from resting state data. We then describe a robust estimator of functional connectivity based on interregional correlation of BOLD-independent component coefficients. This estimator, called independent components regression, considerably simplifies statistical inference for functional connectivity because degrees of freedom equals the number of independent coefficients. Compared with traditional connectivity estimation methods, the proposed strategy results in fourfold improvements in signal-to-noise ratio, functional connectivity analysis with improved specificity, and valid statistical inference with nominal control of type 1 error in contrasts of connectivity between groups with different levels of subject motion.
Head motion systematically alters correlations in resting state functional connectivity fMRI (RSFC). In this report we examine impact of motion on signal intensity and RSFC correlations. We find that motion-induced signal changes (1) are often complex and variable waveforms, (2) are often shared across nearly all brain voxels, and (3) often persist more than 10seconds after motion ceases. These signal changes, both during and after motion, increase observed RSFC correlations in a distance-dependent manner. Motion-related signal changes are not removed by a variety of motion-based regressors, but are effectively reduced by global signal regression. We link several measures of data quality to motion, changes in signal intensity, and changes in RSFC correlations. We demonstrate that improvements in data quality measures during processing may represent cosmetic improvements rather than true correction of the data. We demonstrate a within-subject, censoring-based artifact removal strategy based on volume censoring that reduces group differences due to motion to chance levels. We note conditions under which group-level regressions do and do not correct motion-related effects.
The relation between changes in the blood oxygen dependent metabolic changes imaged by functional magnetic resonance imaging (fMRI) and neural events directly recorded from human cortex from single neurons, local field potentials (LFPs) and electrocorticogram (ECoG) is critically reviewed, based on the published literature including findings from the authors' laboratories. All these data are from special populations, usually patients with medically refractory epilepsy, as this provides the major opportunity for direct cortical neuronal recording in humans. For LFP and ECoG changes are often sought in different frequency bands, for single neurons in frequency of action potentials. Most fMRI studies address issues of functional localization. The relation of those findings to localized changes in neuronal recordings in humans has been established in several ways. Only a few studies have directly compared changes in activity from the same sites in the same individual, using the same behavioral measure. More often the comparison has been between fMRI and electrophysiologic changes in populations recorded from the same functional anatomic system as defined by lesion effects; in a few studies those systems have been defined by fMRI changes such as the “default” network. The fMRI-electrophysiologic relationships have been evaluated empirically by colocalization of significant changes, and by quantitative analyses, often multiple linear regression. There is some evidence that the fMRI-electrophysiology relationships differ in different cortical areas, particularly primary motor and sensory cortices compared to association cortex, but also within areas of association cortex. Although crucial for interpretation of fMRI changes as reflecting neural activity in human cortex, controversy remains as to these relationships. Supported by: Dutch Technology Foundation and University of Utrecht Grant UGT7685, ERC-Advanced grant 320708 (NR) and NIH grant NS065186 (JO)
Hemodynamic-based functional magnetic resonance imaging (fMRI) techniques have proven to be extremely robust and sensitive
methods for noninvasive detection and mapping of human brain activation. Nevertheless, limitations in temporal and spatial
resolution as well as interpretation remain because hemodynamic changes accompanying brain activation are relatively sluggish
and variable and therefore imprecise measures of neuronal activity. A hope among brain imagers would be to possess a technique
that would allow direct mapping of brain activity with spatial resolution on the order of a cortical column and temporal resolution
on the order of an action potential or at least a postsynaptic potential. Recent efforts in understanding the direct effects
of neuronal activity on MRI signal have provided some degree of hope for those who want a more precise noninvasive brain activation
mapping technique than fMRI as we know it now. While the manner in which electrical currents influence MRI signal is well
understood, the manner in which neuronal firing spatially and temporally integrates on the spatial scale of an MRI voxel to
produce a magnetic field shift and subsequently an NMR phase and/or magnitude change is not well understood. It is also not
established that this field shift would be large or long enough in duration to be detected. The objective of this paper is
to provide a perspective of the work that has been performed towards the direction of achieving direct neuronal current imaging
with MRI. A specific goal is to further clarify what is understood about the theoretical and practical possibilities of neuronal
current imaging. Specifically discussed are modeling efforts, phantom studies, in vitro studies, and human studies.
Many patients show no or incomplete responses to current pharmacological or psychological therapies for depression. Here we explored the feasibility of a new brain self-regulation technique that integrates psychological and neurobiological approaches through neurofeedback with functional magnetic resonance imaging (fMRI). In a proof-of-concept study, eight patients with depression learned to upregulate brain areas involved in the generation of positive emotions (such as the ventrolateral prefrontal cortex (VLPFC) and insula) during four neurofeedback sessions. Their clinical symptoms, as assessed with the 17-item Hamilton Rating Scale for Depression (HDRS), improved significantly. A control group that underwent a training procedure with the same cognitive strategies but without neurofeedback did not improve clinically. Randomised blinded clinical trials are now needed to exclude possible placebo effects and to determine whether fMRI-based neurofeedback might become a useful adjunct to current therapies for depression.
New theoretical and practical concepts are presented for considerably enhancing the performance of magnetic resonance imaging (MRI) by means of arrays of multiple receiver coils. Sensitivity encoding (SENSE) is based on the fact that receiver sensitivity generally has an encoding effect complementary to Fourier preparation by linear field gradients. Thus, by using multiple receiver coils in parallel scan time in Fourier imaging can be considerably reduced. The problem of image reconstruction from sensitivity encoded data is formulated in a general fashion and solved for arbitrary coil configurations and k-space sampling patterns. Special attention is given to the currently most practical case, namely, sampling a common Cartesian grid with reduced density. For this case the feasibility of the proposed methods was verified both in vitro and in vivo. Scan time was reduced to one-half using a two-coil array in brain imaging. With an array of five coils double-oblique heart images were obtained in one-third of conventional scan time. Magn Reson Med 42:952-962, 1999.
We investigated the relationship between individual subjects' functional connectomes and 280 behavioral and demographic measures in a single holistic multivariate analysis relating imaging to non-imaging data from 461 subjects in the Human Connectome Project. We identified one strong mode of population co-variation: subjects were predominantly spread along a single 'positive-negative' axis linking lifestyle, demographic and psychometric measures to each other and to a specific pattern of brain connectivity.
Water diffusion magnetic resonance imaging (dMRI) allows tissue structure to be probed and imaged on a microscopic scale, providing unique clues to the fine architecture of neural tissues and to changes associated with various physiological and pathological states, such as acute brain ischaemia. Because diffusion is anisotropic in brain white matter, reflecting its organization in bundles of fibres running in parallel, dMRI can also be used to map the orientation in space of the white matter tracks in the brain, opening a new window on brain connectivity and brain maturation studies. This article provides an introduction to the key physical concepts that underlie dMRI, and reviews its potential applications in the neurosciences and associated clinical fields.
The MGH-USC CONNECTOM MRI scanner housed at the Massachusetts General Hospital (MGH) is a major hardware innovation of the Human Connectome Project (HCP). The 3T CONNECTOM scanner is capable of producing magnetic field gradient of up to 300 mT/m strength for in vivo human brain imaging, which greatly shortens the time spent on diffusion encoding, and decreases the signal loss due to T2 decay. To demonstrate the capability of the novel gradient system, data of healthy adult participants were acquired for this MGH-USC Adult Diffusion Dataset (N=35), minimally preprocessed, and shared through the Laboratory of Neuro Imaging Image Data Archive (LONI IDA) and the WU-Minn Connectome Database (ConnecomeDB). Another purpose of sharing the data is to facilitate methodological studies of diffusion MRI (dMRI) analyses utilizing high diffusion contrast, which perhaps is not easily feasible with standard MR gradient system. In addition, acquisition of the MGH-Harvard-USC Lifespan Dataset is currently underway to include 120 healthy participants ranging from 8 to 90 years old, which will also be shared through LONI IDA and ConnectomeDB. Here we describe the efforts of the MGH-USC HCP consortium in acquiring and sharing the ultra-high b-value diffusion MRI data and provide a report on data preprocessing and access. We conclude with a demonstration of the example data, along with results of standard diffusion analyses, including q-ball Orientation Distribution Function (ODF) reconstruction and tractography.
Neuroimaging has greatly enhanced the cognitive neuroscience understanding of the human brain and its variation across individuals (neurodiversity) in both health and disease. Such progress has not yet, however, propelled changes in educational or medical practices that improve people's lives. We review neuroimaging findings in which initial brain measures (neuromarkers) are correlated with or predict future education, learning, and performance in children and adults; criminality; health-related behaviors; and responses to pharmacological or behavioral treatments. Neuromarkers often provide better predictions (neuroprognosis), alone or in combination with other measures, than traditional behavioral measures. With further advances in study designs and analyses, neuromarkers may offer opportunities to personalize educational and clinical practices that lead to better outcomes for people.
Copyright © 2015 Elsevier Inc. All rights reserved.
The purpose of this review is to communicate and synthesize recent findings related to motion artifact in resting state fMRI. In 2011, three groups reported that small head movements produced spurious but structured noise in brain scans, causing distance-dependent changes in signal correlations. This finding has prompted both methods development and the re-examination of prior findings with more stringent motion correction. Since 2011, over a dozen papers have been published specifically on motion artifact in resting state fMRI. We will attempt to distill these papers to their most essential content. We will point out some aspects of motion artifact that are easily or often overlooked. Throughout the review, we will highlight gaps in current knowledge and avenues for future research.
Copyright © 2014. Published by Elsevier Inc.
Deficits in emotion regulation are a prominent feature of psychiatric conditions and a promising target for treatment. For instance, cognitive reappraisal is regarded as an effective strategy for emotion regulation. Neurophysiological models have established the lateral prefrontal cortex (LPFC) as a key structure in the regulation of emotion processing through modulations of emotion-eliciting structures such as the amygdala. Feedback of the LPFC activity by real-time functional magnetic resonance (fMRI) may thus enhance the efficacy of cognitive reappraisal. During cognitive reappraisal of aversive visual stimuli, LPFC activity was fed back to the experimental group, whereas control participants received no such information. As a result, during reappraisal, amygdala activity was lower in the experimental group than in the controls. Furthermore, an increase of inter-hemispheric functional connectivity emerged in the feedback group. The current study extends the neurofeedback literature by suggesting that fMRI feedback can modify brain activity during a given task.
Copyright © 2014. Published by Elsevier B.V.
Humans spend much of their time engaged in stimulus-independent thoughts, colloquially known as "daydreaming" or "mind-wandering." A fundamental question concerns how awake, spontaneous brain activity represents the ongoing cognition of daydreaming versus unconscious processes characterized as "intrinsic." Since daydreaming involves brief cognitive events that spontaneously fluctuate, we tested the hypothesis that the dynamics of brain network functional connectivity (FC) are linked with daydreaming. We determined the general tendency to daydream in healthy adults based on a daydreaming frequency scale (DDF). Subjects then underwent both resting state functional magnetic resonance imaging (rs-fMRI) and fMRI during sensory stimulation with intermittent thought probes to determine the occurrences of mind-wandering events. Brain regions within the default mode network (DMN), purported to be involved in daydreaming, were assessed for 1) static FC across entire fMRI scans, and 2) dynamic FC based on FC variability (FCV) across 30s progressively sliding windows of 2s increments within each scan. We found that during both resting and sensory stimulation states, individual differences in DDF were negatively correlated with static FC between the posterior cingulate cortex and a ventral DMN subsystem involved in future-oriented thought. Dynamic FC analysis revealed that DDF was positively correlated with FCV within the same DMN subsystem in the resting state but not during stimulation. However, dynamic but not static FC, in this subsystem was positively correlated with an individual's degree of self-reported mind-wandering during sensory stimulation. These findings identify temporal aspects of spontaneous DMN activity that reflect conscious and unconscious processes.
Abstract Dreaming is a subjective experience during sleep that is often accompanied by vivid perceptual and emotional contents. Because of its fundamentally subjective nature, the objective study of dream contents has been challenging. However, since the discovery of rapid eye movements during sleep, scientific knowledge on the relationship between dreaming and physiological measures including brain activity has accumulated. Recent advances in neuroimaging analysis methods have made it possible to uncover direct links between specific dream contents and brain activity patterns. In this review, we first give a historical overview on dream researches with a focus on the neurophysiological and behavioral signatures of dreaming. We then discuss our recent study in which visual dream contents were predicted, or decoded, from brain activity during sleep onset periods using machine learning-based pattern recognition of functional MRI data. We suggest that advanced analytical tools combined with neural and behavioral databases will reveal the relevance of spontaneous brain activity during sleep to waking experiences.
Background:
An increasing number of studies have examined the effects of training of cognitive and other tasks on brain structure, using magnetic resonance imaging.
Methods:
Studies combining cognitive and other tasks training with longitudinal imaging designs were reviewed, with a view to identify paradigms potentially applicable to treatment of cognitive impairment.
Results:
We identified 36 studies, employing training as variable as juggling, working memory, meditation, learning abstract information, and aerobic exercise. There were training-related structural changes, increases in gray matter volume, decreases, increases and decreases in different regions, or no change at all. There was increased integrity in white matter following training, but other patterns of results were also reported.
Conclusions:
Questions still to be answered are: Are changes due to use-dependent effects or are they specific to learning? What are the underlying neural correlates of learning, the temporal dynamics of changes, the relations between structure and function, and the upper limits of improvement? How can gains be maintained? The question whether neuroplasticity will contribute to the treatment of dementia will need to be posed again at that stage.
In recent years functional neuroimaging techniques such as fMRI, MEG, EEG and PET have provided researchers with a wealth of information on human brain function. However none of these modalities can measure directly either the neuro-electrical or neuro-chemical processes that mediate brain function. This means that metrics directly reflecting brain 'activity' must be inferred from other metrics (e.g. magnetic fields (MEG) or haemodynamics (fMRI)). To overcome this limitation, many studies seek to combine multiple complementary modalities and an excellent example of this is the combination of MEG (which has high temporal resolution) with fMRI (which has high spatial resolution). However, the full potential of multi-modal approaches can only be truly realised in cases where the relationship between metrics is known. In this paper, we explore the relationship between measurements made using fMRI and MEG. We describe the origins of the two signals as well as their relationship to electrophysiology. We review multiple studies that have attempted to characterise the spatial relationship between fMRI and MEG, and we also describe studies that exploit the rich information content of MEG to explore differing relationships between MEG and fMRI across neural oscillatory frequency bands. Monitoring the brain at "rest" has become of significant recent interest to the neuroimaging community and we review recent evidence comparing MEG and fMRI metrics of functional connectivity. A brief discussion of the use of magnetic resonance spectroscopy (MRS) to probe the relationship between MEG/fMRI and neurochemistry is also given. Finally, we highlight future areas of interest and offer some recommendations for the parallel use of fMRI and MEG.
The goal of resting-state functional magnetic resonance imaging (FMRI) is to investigate the brain's functional connections by using the temporal similarity between blood oxygenation level dependent (BOLD) signals in different regions of the brain "at rest" as an indicator of synchronous neural activity. Since this measure relies on the temporal correlation of FMRI signal changes between different parts of the brain, any non-neural activity-related process that affects the signals will influence the measure of functional connectivity, yielding spurious results. To understand the sources of these resting-state FMRI confounds, this article describes the origins of the BOLD signal in terms of MR physics and cerebral physiology. Potential confounds arising from motion, cardiac and respiratory cycles, arterial CO2 concentration, blood pressure/cerebral autoregulation, and vasomotion are discussed. Two classes of techniques to remove confounds from resting-state BOLD time series are reviewed: 1) those utilising external recordings of physiology and 2) data-based cleanup methods that only use the resting-state FMRI data itself. Further methods that remove noise from functional connectivity measures at a group level are also discussed. For successful interpretation of resting-state FMRI comparisons and results, noise cleanup is an often over-looked but essential step in the analysis pipeline.
The recent advancement of simultaneous multi-slice imaging using multiband excitation has dramatically reduced the scan time of the brain. The evolution of this parallel imaging technique began over a decade ago and through recent sequence improvements has reduced the acquisition time of multi-slice EPI by over ten fold. This technique has recently become extremely useful for (i) functional MRI studies for improving the statistical definition of neuronal networks, and (ii) diffusion based fiber tractography for improving the ability to visualize structural connections in the human brain. Several applications and evaluations are underway which show promise for this family of fast imaging sequences.
MR spectroscopic imaging (MRSI) has become a valuable tool for quantifying metabolic abnormalities in human brain, prostate, breast and other organs. It is used in routine clinical imaging, particularly for cancer assessment, and in clinical research applications. This article describes basic principles of commonly used MRSI data acquisition and analysis methods and their impact on clinical applications. It also highlights technical advances, such as parallel imaging and newer high-speed MRSI approaches that are becoming viable alternatives to conventional MRSI methods. Although the main focus is on (1) H-MRSI, the principles described are applicable to other MR-compatible nuclei. This review of the state-of-the-art in MRSI methodology provides a framework for critically assessing the clinical utility of MRSI and for defining future technical development that is expected to lead to increased clinical use of MRSI. Future technical development will likely focus on ultra-high field MRI scanners, novel hyperpolarized contrast agents using metabolically active compounds, and ultra-fast MRSI techniques because these technologies offer unprecedented sensitivity and specificity for probing tissue metabolic status and dynamics. J. Magn. Reson. Imaging 2012;. © 2012 Wiley Periodicals, Inc.
The six cortical layers have distinct anatomical and physiological properties, like different energy use and different feedforward and feedback connectivity. It is not known if and how layer-specific neural processes are reflected in the fMRI signal. To address this question we used high-resolution fMRI to measure BOLD, CBV, and CBF responses to stimuli that elicit positive and negative BOLD signals in macaque primary visual cortex. We found that regions with positive BOLD responses had parallel increases in CBV and CBF, whereas areas with negative BOLD responses showed a decrease in CBF but an increase in CBV. For positive BOLD responses, CBF and CBV increased in the center of the cortex, but for negative BOLD responses, CBF decreased superficially while CBV increased in the center. Our findings suggest different mechanisms for neurovascular coupling for BOLD increases and decreases, as well as laminar differences in neurovascular coupling.
We investigated the decoding of millisecond-order timing information in ocular dominance stimulation from the blood oxygen level dependent (BOLD) signal in human functional magnetic resonance imaging (fMRI). In our experiment, ocular dominance columns were activated by monocular visual stimulation with 500- or 100- ms onset differences. We observed that the event-related hemodynamic response (HDR) in the human visual cortex was sensitive to the subtle onset difference. The HDR shapes were related to the stimulus timings in various manners: the timing difference was represented in either the amplitude of positive peak, amplitude of negative peak, delay of peak time, or response duration of HDR. These complex relationships were different across voxels and subjects. To find an informative feature of HDR for discriminating the subtle timing difference of ocular dominance stimulations, we examined various characteristics of HDR including response amplitude, time to peak, full width at half-maximum response, as inputs for decoding analysis. Using a canonical HDR function for estimating the voxel's response did not yield good decoding scores, suggesting that information may reside in the variability of HDR shapes. Using all the values from the deconvolved HDR also showed low performance, which could be due to an over-fitting problem with the large data dimensionality. When using either positive or negative peak amplitude of the deconvolved HDR, high decoding performance could be achieved for both the 500ms and the 100ms onset differences. The high accuracy even for the 100ms difference, given that the signal was sampled at a TR of 250ms and 2x2x3-mm voxels, implies a possibility of spatiotemporally hyper-resolution decoding. Furthermore, both down-sampling and smoothing did not affect the decoding accuracies very much. These results suggest a complex spatiotemporal relationship between the multi-voxel pattern of the BOLD response and the population activation of neuronal columns. The demonstrated possibility of decoding a 100-ms difference of stimulations for columnar-level organization with lower resolution imaging data may broaden the scope of application of the BOLD fMRI.
Using gradient-echo echo-planar MRI, a local signal increase of 4.3 ± 0.3% is observed in the human brain during task activation, suggesting a local decrease in blood deoxyhemoglobin concentration and an increase in blood oxygenation. Images highlighting areas of signal enhancement temporally correlated to the task are created. © 1992 Academic Press, Inc.
Understanding the relationship between fMRI signal changes and activated cortex is paramount to successful mapping of neuronal activity. To this end, the relative extravascular and intravascular contribution to fMRI signal change from capillaries (localized), venules (less localized) and macrovessels (remote, draining veins) must be determined. In this work, the authors assessed both the extravascular and intravascular contribution to blood oxygenation level-dependent gradient echo signal change at 1.5 T by using a Monte Carlo model for susceptibility-based contrast in conjunction with a physiological model for neuronal activation-induced changes in oxygenation and vascular volume fraction. The authors compared our Model results with experimental fMRI signal changes with and without velocity sensitization via bipolar gradients to null the intravascular signal. The model and experimental results are in agreement and suggest that the intravascular spins account for the majority of fMRI signal change on T2*-weighted images at 1.5 T.
Relative cerebral blood flow changes can be measured by a novel simple blood flow measurement technique with endogenous water protons as a tracer based on flow-sensitive alternating inversion recovery (FAIR). Two inversion recovery (IR) images are acquired by interleaving slice-selective inversion and nonselective inversion. During the inversion delay time after slice-selective inversion, fully magnetized blood spins move into the imaging slice and exchange with tissue water. The signal enhancement (FAIR image) measured by the signal difference between two images is directly related to blood flow. For functional MR imaging studies, two IR images are alternatively and repeatedly acquired during control and task periods. Relative signal changes in the FAIR images during the task periods represent the relative regional cerebral blood flow changes. The FAIR technique has been successfully applied to functional brain mapping studies in humans during finger opposition movements. The technique is capable of generating microvascular-based functional maps.
Measurement of tissue perfusion is important for the functional assessment of organs in vivo. Here we report the use of 1H NMR imaging to generate perfusion maps in the rat brain at 4.7 T. Blood water flowing to the brain is saturated in the neck region with a sliceselective saturation imaging sequence, creating an endogenous tracer in the form of proximally saturated spins. Because proton T1 times are relatively long, particularly at high field strengths, saturated spins exchange with bulk water in the brain and a steady state is created where the regional concentration of saturated spins is determined by the regional blood flow and regional T1. Distal saturation applied equidistantly outside the brain serves as a control for effects of the saturation pulses. Average cerebral blood flow in normocapnic rat brain under halothane anesthesia was determined to be 105 ± 16 cc. 100 g−1. min−1 (mean ± SEM, n = 3), in good agreement with values reported in the literature, and was sensitive to increases in arterial pCO2. This technique allows regional perfusion maps to be measured noninvasively, with the resolution of 1H MRI, and should be readily applicable to human studies. © 1992 Academic Press, Inc.
The simultaneous acquisition of spatial harmonics (SMASH) imaging technique uses spatial information from an array of RF coils to substitute for omitted encoding gradient steps and thereby to accelerate MR image acquisition. Since SMASH image reconstructions rely on the accurate generation of sinusoidally varying composite sensitivity functions to emulate the spatial modulations produced by gradients, the technique was originally believed to be limited to certain image planes or coil array configurations which were particularly suited to the generation of spatial harmonics. Several key improvements to the SMASH reconstruction procedure are described, taking advantage of various degrees of freedom in the spatial harmonic fit. The use of tailored fitting procedures, in combination with a numerical conditioning approach based on new observations about noise propagation in the fit, are shown to allow high-quality SMASH image reconstructions in oblique and double-oblique image planes, both in phantoms and in high-resolution cardiac MR images. Magn Reson Med 44:243–251, 2000. © 2000 Wiley-Liss, Inc.
An MRI time course of 512 echo-planar images (EPI) in resting human brain obtained every 250 ms reveals fluctuations in signal intensity in each pixel that have a physiologic origin. Regions of the sensorimotor cortex that were activated secondary to hand movement were identified using functional MRI methodology (FMRI). Time courses of low frequency (<0.1 Hz) fluctuations in resting brain were observed to have a high degree of temporal correlation (P < 10−3) within these regions and also with time courses in several other regions that can be associated with motor function. It is concluded that correlation of low frequency fluctuations, which may arise from fluctuations in blood oxygenation or flow, is a manifestation of functional connectivity of the brain.
Functional magnetic resonance imaging with blood oxygenation level-dependent (BOLD) contrast has had a tremendous influence on human neuroscience in the last twenty years, providing a non-invasive means of mapping human brain function with often exquisite sensitivity and detail. However the BOLD method remains a largely qualitative approach. While the same can be said of anatomic MRI techniques, whose clinical and research impact has not been diminished in the slightest by the lack of a quantitative interpretation of their image intensity, the quantitative expression of BOLD responses as a percent of the baseline T2*- weighted signal has been viewed as necessary since the earliest days of fMRI. Calibrated MRI attempts to dissociate changes in oxygen metabolism from changes in blood flow and volume, the latter three quantities contributing jointly to determine the physiologically ambiguous percent BOLD change. This dissociation is typically performed using a "calibration" procedure in which subjects inhale a gas mixture containing small amounts of carbon dioxide or enriched oxygen to produce changes in blood flow and BOLD signal which can be measured under well-defined hemodynamic conditions. The outcome is a calibration parameter M which can then be substituted into an expression providing the fractional change in oxygen metabolism given changes in blood flow and BOLD signal during a task. The latest generation of calibrated MRI methods goes beyond fractional changes to provide absolute quantification of resting-state oxygen consumption in micromolar units, in addition to absolute measures of evoked metabolic response. This review discusses the history, challenges, and advances in calibrated MRI, from the personal perspective of the author.