Event-related functional MRI: past, present, and future

Neuromodulation in Small Animal fMRI

The integration of functional magnetic resonance imaging (fMRI) with advanced neuroscience technologies in experimental small animal models offers a unique path to interrogate the causal relationships between regional brain activity and brain-wide network measures-a goal challenging to accomplish in human subjects. This review traces the historical development of the neuromodulation techniques commonly used in rodents, such as electrical deep brain stimulation, optogenetics, and chemogenetics, and focuses on their application with fMRI. We discuss their advantageousness roles in uncovering the signaling architecture within the brain and the methodological considerations necessary when conducting these experiments. By presenting several rodent-based case studies, we aim to demonstrate the potential of the multimodal neuromodulation approach in shedding light on neurovascular coupling, the neural basis of brain network functions, and their connections to behaviors. Key findings highlight the cell-type and circuit-specific modulation of brain-wide activity patterns and their behavioral correlates. We also discuss several future directions and feature the use of mediation and moderation analytical models beyond the intuitive evoked response mapping, to better leverage the rich information available in fMRI data with neuromodulation. Using fMRI alongside neuromodulation techniques provide insights into the mesoscopic (relating to the intermediate scale between single neurons and large-scale brain networks) and macroscopic fMRI measures that correlate with specific neuronal events. This integration bridges the gap between different scales of neuroscience research, facilitating the exploration and testing of novel therapeutic strategies aimed at altering network-mediated behaviors. In conclusion, the combination of fMRI with neuromodulation techniques provides crucial insights into mesoscopic and macroscopic brain dynamics, advancing our understanding of brain function in health and disease. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 1.

A fully Bayesian approach for comprehensive mapping of magnitude and phase brain activation in complex-valued fMRI data

Functional magnetic resonance imaging (fMRI) plays a crucial role in neuroimaging, enabling the exploration of brain activity through complex-valued signals. These signals, composed of magnitude and phase, offer a rich source of information for understanding brain functions. Traditional fMRI analyses have largely focused on magnitude information, often overlooking the potential insights offered by phase data. In this paper, we propose a novel fully Bayesian model designed for analyzing single-subject complex-valued fMRI (cv-fMRI) data. Our model, which we refer to as the CV-M&P model, is distinctive in its comprehensive utilization of both magnitude and phase information in fMRI signals, allowing for independent prediction of different types of activation maps. We incorporate Gaussian Markov random fields (GMRFs) to capture spatial correlations within the data, and employ image partitioning and parallel computation to enhance computational efficiency. Our model is rigorously tested through simulation studies, and then applied to a real dataset from a unilateral finger-tapping experiment. The results demonstrate the model's effectiveness in accurately identifying brain regions activated in response to specific tasks, distinguishing between magnitude and phase activation.

What Does the Human Olfactory System Do, and How Does It Do It?

Historically, the human sense of smell has been regarded as the odd stepchild of the senses, especially compared to the sensory bravado of seeing, touching, and hearing. The idea that the human olfaction has little to contribute to our experience of the world is commonplace, though with the emergence of COVID-19 there has rather been a sea change in this understanding. An ever increasing body of work has convincingly highlighted the keen capabilities of the human nose and the sophistication of the human olfactory system. Here, we provide a concise overview of the neuroscience of human olfaction spanning the last 10-15 years, with focus on the peripheral and central mechanisms that underlie how odor information is processed, packaged, parceled, predicted, and perturbed to serve odor-guided behaviors. We conclude by offering some guideposts for harnessing the next decade of olfactory research in all its shapes and forms.

A neuroergonomics approach to driver's cooperation with Lane Departure Warning Systems

Lane Departure Warning Systems (LDWS) are automation that warn drivers in case of immediate lane departure. While LDWS are associated with increased road safety, little is known about the neural aspects of the cooperation between an LDWS and the driver behind the wheel. The present study addresses this issue by combining fMRI and driving simulation for experienced and novice drivers. The results reveal brain areas activated immediately after warning: it involves areas linked to the alertness network (midbrain, thalamus, anterior cingulate cortex), to motor actions and planning (motor and premotor cortexes; BA4/6 -cerebellum) and to attentional redirection (superior frontal cortex; BA10). There were no differences between experienced and novice drivers in this network of cerebral areas. However, prior driving experience mediates the number of lane departures. The results allow for refining a model of cooperation proposed earlier in the literature, by adding a cerebral dimension.

Layer-fMRI VASO with short stimuli and event-related designs at 7 T

Layers and columns are the dominant processing units in the human (neo)cortex at the mesoscopic scale. While the blood oxygenation dependent (BOLD) signal has a high detection sensitivity, it is biased towards unwanted signals from large draining veins at the cortical surface. The additional fMRI contrast of vascular space occupancy (VASO) has the potential to augment the neuroscientific interpretability of layer-fMRI results by means of capturing complementary information of locally specific changes in cerebral blood volume (CBV). Specifically, VASO is not subject to unwanted sensitivity amplifications of large draining veins. Because of constrained sampling efficiency, it has been mainly applied in combination with efficient block task designs and long trial durations. However, to study cognitive processes in neuroscientific contexts, or probe vascular reactivity, short stimulation periods are often necessary. Here, we developed a VASO acquisition procedure with a short acquisition period and sub-millimeter resolution. During visual event-related stimulation, we show reliable responses in visual cortices within a reasonable number of trials (∼20). Furthermore, the short TR and high spatial specificity of our VASO implementation enabled us to show differences in laminar reactivity and onset times. Finally, we explore the generalizability to a different stimulus modality (somatosensation). With this, we showed that CBV-sensitive VASO provides the means to capture layer-specific haemodynamic responses with high spatio-temporal resolution and is able to be used with event-related paradigms.

Event-related functional magnetic resonance spectroscopy

Proton-Magnetic Resonance Spectroscopy (MRS) is a non-invasive brain imaging technique used to measure the concentration of different neurochemicals. "Single-voxel" MRS data is typically acquired across several minutes, before individual transients are averaged through time to give a measurement of neurochemical concentrations. However, this approach is not sensitive to more rapid temporal dynamics of neurochemicals, including those that reflect functional changes in neural computation relevant to perception, cognition, motor control and ultimately behaviour. In this review we discuss recent advances in functional MRS (fMRS) that now allow us to obtain event-related measures of neurochemicals. Event-related fMRS involves presenting different experimental conditions as a series of trials that are intermixed. Critically, this approach allows spectra to be acquired at a time resolution in the order of seconds. Here we provide a comprehensive user guide for event-related task designs, choice of MRS sequence, analysis pipelines, and appropriate interpretation of event-related fMRS data. We raise various technical considerations by examining protocols used to quantify dynamic changes in GABA, the primary inhibitory neurotransmitter in the brain. Overall, we propose that although more data is needed, event-related fMRS can be used to measure dynamic changes in neurochemicals at a temporal resolution relevant to computations that support human cognition and behaviour.

Older adults compensate for switch, but not mixing costs, relative to younger adults on an intrinsically cued task switching experiment

Introduction

Aging negatively impacts the ability to rapidly and successfully switch between two or more tasks that have different rules or objectives. However, previous work has shown that the context impacts the extent of this age-related impairment: while there is relative age-related invariance when participants must rapidly switch back and forth between two simple tasks (often called "switch costs"), age-related differences emerge when the contexts changes from one in which only one task must be performed to one in which multiple tasks must be performed, but a trial-level switch is not required (e.g., task repeat trials within dual task blocks, often called "mixing costs"). Here, we explored these two kinds of costs behaviorally, and also investigated the neural correlates of these effects.

Methods

Seventy-one younger adults and 175 older adults completed a task-switching experiment while they underwent fMRI brain imaging. We investigated the impact of age on behavioral performance and neural activity considering two types of potential costs: switch costs (dual-task switch trials minus dual-task non-switch trials), and mixing costs (dual-task non-switch minus single-task trials).

Results

We replicated previous behavioral findings, with greater age associated with mixing, but not switch costs. Neurally, we found age-related compensatory activations for switch costs in the dorsal lateral prefrontal cortex, pars opercularis, superior temporal gyrus, and the posterior and anterior cingulate, but age-related under recruitment for mixing costs in fronto-parietal areas including the supramarginal gyrus and pre and supplemental motor areas.

Discussion

These results suggest an age-based dissociation between executive components that contribute to task switching.

Aging changes the interactions between the oculomotor and memory systems

The use of multi-modal approaches, particularly in conjunction with multivariate analytic techniques, can enrich models of cognition, brain function, and how they change with age. Recently, multivariate approaches have been applied to the study of eye movements in a manner akin to that of neural activity (i.e., pattern similarity). Here, we review the literature regarding multi-modal and/or multivariate approaches, with specific reference to the use of eyetracking to characterize age-related changes in memory. By applying multi-modal and multivariate approaches to the study of aging, research has shown that aging is characterized by moment-to-moment alterations in the amount and pattern of visual exploration, and by extension, alterations in the activity and function of the hippocampus and broader medial temporal lobe (MTL). These methodological advances suggest that age-related declines in the integrity of the memory system has consequences for oculomotor behavior in the moment, in a reciprocal fashion. Age-related changes in hippocampal and MTL structure and function may lead to an increase in, and change in the patterns of, visual exploration in an effort to upregulate the encoding of information. However, such visual exploration patterns may be non-optimal and actually reduce the amount and/or type of incoming information that is bound into a lasting memory representation. This research indicates that age-related cognitive impairments are considerably broader in scope than previously realized.

Arterial blood stealing as a mechanism of negative BOLD response: From the steady-flow with nonlinear phase separation to a windkessel-based model

Blood Oxygen Level Dependent (BOLD) signal indirectly characterizes neuronal activity by measuring hemodynamic and metabolic changes in the nearby microvasculature. A deeper understanding of how localized changes in electrical, metabolic and hemodynamic factors translate into a BOLD signal is crucial for the interpretation of functional brain imaging techniques. While positive BOLD responses (PBR) are widely considered to be linked with neuronal activation, the origins of negative BOLD responses (NBR) have remained largely unknown. As NBRs are sometimes observed in close proximity of regions with PBR, a blood "stealing" effect, i.e., redirection of blood from a passive periphery to the area with high neuronal activity, has been postulated. In this study, we used the Hagen-Poiseuille equation to model hemodynamics in an idealized microvascular network that account for the particulate nature of blood and nonlinearities arising from the red blood cell (RBC) distribution (i.e., the Fåhraeus, Fåhraeus-Lindqvist and the phase separation effects). Using this detailed model, we evaluate determinants driving this "stealing" effect in a microvascular network with geometric parameters within physiological ranges. Model simulations predict that during localized cerebral blood flow (CBF) increases due to neuronal activation-hyperemic response, blood from surrounding vessels is reallocated towards the activated region. This stealing effect depended on the resistance of the microvasculature and the uneven distribution of RBCs at vessel bifurcations. A parsimonious model consisting of two-connected windkessel regions sharing a supplying artery was proposed to simulate the stealing effect with a minimum number of parameters. Comparison with the detailed model showed that the parsimonious model can reproduce the observed response for hematocrit values within the physiological range for different species. Our novel parsimonious model promise to be of use for statistical inference (top-down analysis) from direct blood flow measurements (e.g., arterial spin labeling and laser Doppler/Speckle flowmetry), and when combined with theoretical models for oxygen extraction/diffusion will help account for some types of NBRs.

Investigating Language and Domain-General Processing in Neurotypicals and Individuals With Aphasia - A Functional Near-Infrared Spectroscopy Pilot Study

Brain reorganization patterns associated with language recovery after stroke have long been debated. Studying mechanisms of spontaneous and treatment-induced language recovery in post-stroke aphasia requires a network-based approach given the potential for recruitment of perilesional left hemisphere language regions, homologous right hemisphere language regions, and/or spared bilateral domain-general regions. Recent hardware, software, and methodological advances in functional near-infrared spectroscopy (fNIRS) make it well-suited to examine this question. fNIRS is cost-effective with minimal contraindications, making it a robust option to monitor treatment-related brain activation changes over time. Establishing clear activation patterns in neurotypical adults during language and domain-general cognitive processes via fNIRS is an important first step. Some fNIRS studies have investigated key language processes in healthy adults, yet findings are challenging to interpret in the context of methodological limitations. This pilot study used fNIRS to capture brain activation during language and domain-general processing in neurotypicals and individuals with aphasia. These findings will serve as a reference when interpreting treatment-related changes in brain activation patterns in post-stroke aphasia in the future. Twenty-four young healthy controls, seventeen older healthy controls, and six individuals with left hemisphere stroke-induced aphasia completed two language tasks (i.e., semantic feature, picture naming) and one domain-general cognitive task (i.e., arithmetic) twice during fNIRS. The probe covered bilateral frontal, parietal, and temporal lobes and included short-separation detectors for scalp signal nuisance regression. Younger and older healthy controls activated core language regions during semantic feature processing (e.g., left inferior frontal gyrus pars opercularis) and lexical retrieval (e.g., left inferior frontal gyrus pars triangularis) and domain-general regions (e.g., bilateral middle frontal gyri) during hard versus easy arithmetic as expected. Consistent with theories of post-stroke language recovery, individuals with aphasia activated areas outside the traditional networks: left superior frontal gyrus and left supramarginal gyrus during semantic feature judgment; left superior frontal gyrus and right precentral gyrus during picture naming; and left inferior frontal gyrus pars opercularis during arithmetic processing. The preliminary findings in the stroke group highlight the utility of using fNIRS to study language and domain-general processing in aphasia.

Genetic variations influence brain changes in patients with attention-deficit hyperactivity disorder

Attention-deficit hyperactivity disorder (ADHD) is a neurological and neurodevelopmental childhood-onset disorder characterized by a persistent pattern of inattentiveness, impulsiveness, restlessness, and hyperactivity. These symptoms may continue in 55-66% of cases from childhood into adulthood. Even though the precise etiology of ADHD is not fully understood, it is considered as a multifactorial and heterogeneous disorder with several contributing factors such as heritability, auxiliary to neurodevelopmental issues, severe brain injuries, neuroinflammation, consanguineous marriages, premature birth, and exposure to environmental toxins. Neuroimaging and neurodevelopmental assessments may help to explore the possible role of genetic variations on ADHD neuropsychobiology. Multiple genetic studies have observed a strong genetic association with various aspects of neuropsychobiological functions, including neural abnormalities and delayed neurodevelopment in ADHD. The advancement in neuroimaging and molecular genomics offers the opportunity to analyze the impact of genetic variations alongside its dysregulated pathways on structural and functional derived brain imaging phenotypes in various neurological and psychiatric disorders, including ADHD. Recently, neuroimaging genomic studies observed a significant association of brain imaging phenotypes with genetic susceptibility in ADHD. Integrating the neuroimaging-derived phenotypes with genomics deciphers various neurobiological pathways that can be leveraged for the development of novel clinical biomarkers, new treatment modalities as well as therapeutic interventions for ADHD patients. In this review, we discuss the neurobiology of ADHD with particular emphasis on structural and functional changes in the ADHD brain and their interactions with complex genomic variations utilizing imaging genetics methodologies. We also highlight the genetic variants supposedly allied with the development of ADHD and how these, in turn, may affect the brain circuit function and related behaviors. In addition to reviewing imaging genetic studies, we also examine the need for complementary approaches at various levels of biological complexity and emphasize the importance of combining and integrating results to explore biological pathways involved in ADHD disorder. These approaches include animal models, computational biology, bioinformatics analyses, and multimodal imaging genetics studies.

The Effects of Useful Field of View Training on Brain Activity and Connectivity

OBJECTIVES

Useful Field of View training (UFOVt) is an adaptive computerized cognitive intervention that improves visual attention and transfers to maintained health and everyday functioning in older adults. Although its efficacy is well established, the neural mechanisms underlying this intervention are unknown. This pilot study used functional MRI (fMRI) to explore neural changes following UFOVt.

METHOD

Task-driven and resting-state fMRI were used to examine changes in brain activity and connectivity in healthy older adults randomized to 10 hr of UFOVt (n = 13), 10 hr of cognitively stimulating activities (CSA; n = 11), or a no-contact control (NC; n = 10).

RESULTS

UFOVt resulted in reduced task-driven activity in the majority of regions of interest (ROIs) associated with task performance, CSA resulted in reduced activity in one ROI, and there were no changes within the NC group. Relative to NC, UFOVt reduced activity in ROIs involved in effortful information processing. There were no other significant between-group task-based differences. Resting-state functional connectivity between ROIs involved in executive function and visual attention was strengthened following UFOVt compared with CSA and NC.

DISCUSSION

UFOVt enhances connections needed for visual attention. Together with prior work, this study provides evidence that improvement of the brain's visual attention efficiency is one mechanism underlying UFOVt.

Auditory Frequency Representations in Human Somatosensory Cortex

Recent studies have challenged the traditional notion of modality-dedicated cortical systems by showing that audition and touch evoke responses in the same sensory brain regions. While much of this work has focused on somatosensory responses in auditory regions, fewer studies have investigated sound responses and representations in somatosensory regions. In this functional magnetic resonance imaging (fMRI) study, we measured BOLD signal changes in participants performing an auditory frequency discrimination task and characterized activation patterns related to stimulus frequency using both univariate and multivariate analysis approaches. Outside of bilateral temporal lobe regions, we observed robust and frequency-specific responses to auditory stimulation in classically defined somatosensory areas. Moreover, using representational similarity analysis to define the relationships between multi-voxel activation patterns for all sound pairs, we found clear similarity patterns for auditory responses in the parietal lobe that correlated significantly with perceptual similarity judgments. Our results demonstrate that auditory frequency representations can be distributed over brain regions traditionally considered to be dedicated to somatosensation. The broad distribution of auditory and tactile responses over parietal and temporal regions reveals a number of candidate brain areas that could support general temporal frequency processing and mediate the extensive and robust perceptual interactions between audition and touch.

Functional neuroimaging of the central autonomic network: recent developments and clinical implications

Purpose

The central autonomic network (CAN) is an intricate system of brainstem, subcortical, and cortical structures that play key roles in the function of the autonomic nervous system. Prior to the advent of functional neuroimaging, in vivo studies of the human CAN were limited. The purpose of this review is to highlight the contribution of functional neuroimaging, specifically functional magnetic resonance imaging (fMRI), to the study of the CAN, and to discuss recent advances in this area. Additionally, we aim to emphasize exciting areas for future research.

Methods

We reviewed the existing literature in functional neuroimaging of the CAN. Here, we focus on fMRI research conducted in healthy human subjects, as well as research that has been done in disease states, to understand CAN function. To minimize confounding, papers examining CAN function in the context of cognition, emotion, pain, and affective disorders were excluded.

Results

fMRI has led to significant advances in the understanding of human CAN function. The CAN is composed of widespread brainstem and forebrain structures that are intricately connected and play key roles in reflexive and modulatory control of autonomic function.

Conclusions

fMRI technology has contributed extensively to current knowledge of CAN function. It holds promise to serve as a biomarker in disease states. With ongoing advancements in fMRI technology, there is great opportunity and need for future research involving the CAN.

Neural correlates of trauma-related single word processing in posttraumatic stress disorder

Interpersonal violence (IPV) is one of the most frequent causes for the development of posttraumatic stress disorder (PTSD) in women. One key component in PTSD is altered processing of trauma-related cues, leading to emotional symptoms. In the everyday environment, words with trauma-associated semantic content represent typical, albeit abstract, trauma-related stimuli for patients suffering from PTSD. However, the functional neuroanatomy associated with processing single trauma-related words in IPV-PTSD is not understood. The present event-related functional magnetic resonance imaging study investigated the neural basis of trauma-related word processing in women with IPV-PTSD relative to healthy controls (HC) during a non-emotional vigilance task in which the emotional content of the words was task-irrelevant. On the behavioral level, trauma-related relative to neutral word stimuli evoked more unpleasant feelings, higher arousal as well as anxiety in IPV-PTSD patients as compared to HC. Functional imaging data showed hyperactivation to trauma-related versus neutral words in the basolateral amygdala (BLA) and cortical language-processing regions (inferior frontal gyrus, posterior cingulate cortex, angular/supramarginal gyrus) in IPV-PTSD compared to HC. These results propose a role of the BLA in hypervigilant responding to verbal trauma associated cues in IPV-PTSD. Furthermore, the particular involvement of cortical language-processing regions indicates enhanced processing of trauma-related words in brain regions associated with analysis and memory of verbal material. Taken together, our findings suggest that both subcortical and cortical mechanisms contribute to automatic responsivity to verbal trauma cues in PTSD.

Cortical activation patterns to spatially presented pure tone stimuli with different intensities measured by functional near-infrared spectroscopy

Functional near-infrared spectroscopy (fNIRS) is an emerging technique for the assessment of functional activity of the cerebral cortex. Recently fNIRS was also envisaged as a novel neuroimaging approach for measuring the auditory cortex activity in the field of in auditory diagnostics. This study aimed to investigate differences in brain activity related to spatially presented sounds with different intensities in 10 subjects by means of functional near-infrared spectroscopy (fNIRS). We found pronounced cortical activation patterns in the temporal and frontal regions of both hemispheres. In contrast to these activation patterns, we found deactivation patterns in central and parietal regions of both hemispheres. Furthermore our results showed an influence of spatial presentation and intensity of the presented sounds on brain activity in related regions of interest. These findings are in line with previous fMRI studies which also reported systematic changes of activation in temporal and frontal areas with increasing sound intensity. Although clear evidence for contralaterality effects and hemispheric asymmetries were absent in the group data, these effects were partially visible on the single subject level. Concluding, fNIRS is sensitive enough to capture differences in brain responses during the spatial presentation of sounds with different intensities in several cortical regions. Our results may serve as a valuable contribution for further basic research and the future use of fNIRS in the area of central auditory diagnostics.

Neural representations for newly learned words are modulated by overnight consolidation, reading skill, and age

Word learning depends not only on efficient online binding of phonological, orthographic and lexical information, but also on consolidation of new word representations into permanent lexical memory. Work on word learning under a variety of contexts indicates that reading and language skill impact facility of word learning in both print and speech. In addition, recent research finds that individuals with language impairments show deficits in both initial word form learning and in maintaining newly learned representations over time, implicating mechanisms associated with maintenance that may be driven by deficits in overnight consolidation. Although several recent studies have explored the neural bases of overnight consolidation of newly learned words, no extant work has examined individual differences in overnight consolidation at the neural level. The current study addresses this gap in the literature by investigating how individual differences in reading and language skills modulate patterns of neural activation associated with newly learned words following a period of overnight consolidation. Specifically, a community sample of adolescents and young adults with significant variability in reading and oral language (vocabulary) ability were trained on two spoken artificial lexicons, one in the evening on the day before fMRI scanning and one in the morning just prior to scanning. Comparisons of activation between words that were trained and consolidated vs. those that were trained but not consolidated revealed increased cortical activation in a number of language associated and memory associated regions. In addition, individual differences in age, reading skill and vocabulary modulated learning rate in our artificial lexicon learning task and the size of the cortical consolidation effect in the precuneus/posterior cingulate, such that older readers and more skilled readers had larger cortical consolidation effects in this learning-critical region. These findings suggest that age (even into late adolescence) and reading and language skills are important individual differences that affect overnight consolidation of newly learned words. These findings have significant implications for understanding reading and language disorders and should inform pedagogical models.

Automatized smoking-related action schemata are reflected by reduced fMRI activity in sensorimotor brain regions of smokers

In the later stages of addiction, automatized processes play a prominent role in guiding drug-seeking and drug-taking behavior. However, little is known about the neural correlates of automatized drug-taking skills and drug-related action knowledge in humans. We employed functional magnetic resonance imaging (fMRI) while smokers and non-smokers performed an orientation affordance task, where compatibility between the hand used for a behavioral response and the spatial orientation of a priming stimulus leads to shorter reaction times resulting from activation of the corresponding motor representations. While non-smokers exhibited this behavioral effect only for control objects, smokers showed the affordance effect for both control and smoking-related objects. Furthermore, smokers exhibited reduced fMRI activation for smoking-related as compared to control objects for compatible stimulus-response pairings in a sensorimotor brain network consisting of the right primary motor cortex, supplementary motor area, middle occipital gyrus, left fusiform gyrus and bilateral cingulate gyrus. In the incompatible condition, we found higher fMRI activation in smokers for smoking-related as compared to control objects in the right primary motor cortex, cingulate gyrus, and left fusiform gyrus. This suggests that the activation and performance of deeply embedded, automatized drug-taking schemata employ less brain resources. This might reduce the threshold for relapsing in individuals trying to abstain from smoking. In contrast, the interruption or modification of already triggered automatized action representations require increased neural resources.

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We measured smokers and non-smokers with fMRI and a behavioral affordance task.

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Smoking paraphernalia and control objects were employed as stimuli.

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Automatized smoking schemata employ less brain resources in sensorimotor regions.

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This might reduce the motor threshold in smokers trying to abstain from smoking.

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Interruption of triggered action representations requires more neural resources.

Effect of confounding variables on hemodynamic response function estimation using averaging and deconvolution analysis: An event-related NIRS study

Slow and rapid event-related designs are used in fMRI and functional near-infrared spectroscopy (fNIRS) experiments to temporally characterize the brain hemodynamic response to discrete events. Conventional averaging (CA) and the deconvolution method (DM) are the two techniques commonly used to estimate the Hemodynamic Response Function (HRF) profile in event-related designs. In this study, we conducted a series of simulations using synthetic and real NIRS data to examine the effect of the main confounding factors, including event sequence timing parameters, different types of noise, signal-to-noise ratio (SNR), temporal autocorrelation and temporal filtering on the performance of these techniques in slow and rapid event-related designs. We also compared systematic errors in the estimates of the fitted HRF amplitude, latency and duration for both techniques. We further compared the performance of deconvolution methods based on Finite Impulse Response (FIR) basis functions and gamma basis sets. Our results demonstrate that DM was much less sensitive to confounding factors than CA. Event timing was the main parameter largely affecting the accuracy of CA. In slow event-related designs, deconvolution methods provided similar results to those obtained by CA. In rapid event-related designs, our results showed that DM outperformed CA for all SNR, especially above -5 dB regardless of the event sequence timing and the dynamics of background NIRS activity. Our results also show that periodic low-frequency systemic hemodynamic fluctuations as well as phase-locked noise can markedly obscure hemodynamic evoked responses. Temporal autocorrelation also affected the performance of both techniques by inducing distortions in the time profile of the estimated hemodynamic response with inflated t-statistics, especially at low SNRs. We also found that high-pass temporal filtering could substantially affect the performance of both techniques by removing the low-frequency components of HRF profiles. Our results emphasize the importance of characterization of event timing, background noise and SNR when estimating HRF profiles using CA and DM in event-related designs.

Brain structure, function, and neurochemistry in schizophrenia and bipolar disorder-a systematic review of the magnetic resonance neuroimaging literature

Since Emil Kraepelin's conceptualization of endogenous psychoses as dementia praecox and manic depression, the separation between primary psychotic disorders and primary affective disorders has been much debated. We conducted a systematic review of case-control studies contrasting magnetic resonance imaging studies in schizophrenia and bipolar disorder. A literature search in PubMed of studies published between January 2005 and December 2016 was conducted, and 50 structural, 29 functional, 7 magnetic resonance spectroscopy, and 8 combined imaging and genetic studies were deemed eligible for systematic review. Structural neuroimaging studies suggest white matter integrity deficits that are consistent across the illnesses, while gray matter reductions appear more widespread in schizophrenia compared to bipolar disorder. Spectroscopy studies in cortical gray matter report evidence of decreased neuronal integrity in both disorders. Functional neuroimaging studies typically report similar functional architecture of brain networks in healthy controls and patients across the psychosis spectrum, but find differential extent of alterations in task related activation and resting state connectivity between illnesses. The very limited imaging-genetic literature suggests a relationship between psychosis risk genes and brain structure, and possible gene by diagnosis interaction effects on functional imaging markers. While the existing literature suggests some shared and some distinct neural markers in schizophrenia and bipolar disorder, it will be imperative to conduct large, well designed, multi-modal neuroimaging studies in medication-naïve first episode patients that will be followed longitudinally over the course of their illness in an effort to advance our understanding of disease mechanisms.

Attention Diversion Improves Response Inhibition of Immediate Reward, But Only When it Is Beneficial: An fMRI Study

Deficits of self-control are associated with a number of mental state disorders. The ability to direct attention away from an alluring stimulus appears to aid inhibition of an impulsive response. However, further functional imaging research is required to assess the impact of shifts in attention on self-regulating processes. We varied the level of attentional disengagement in an functional magnetic resonance imaging (fMRI)-based Go/No-go task to probe whether diversion of attention away from alluring stimuli facilitates response inhibition. We used the attention-grabbing characteristic of faces to exogenously direct attention away from stimuli and investigated the relative importance of attention and response inhibition mechanisms under different delayed reward scenarios [i.e., where forgoing an immediate reward ($1) led to a higher ($10) or no payoff in the future]. We found that diverting attention improved response inhibition performance, but only when resistance to an alluring stimulus led to delayed reward. Region of interest analyses indicated significant increased activity in posterior right inferior frontal gyrus during successful No-go trials for delayed reward trials compared to no delayed reward trials, and significant reduction in activity in the superior temporal gyri and left caudate in contexts of high attentional diversion. Our findings imply that strategies that increase the perceived benefits of response inhibition might assist individuals in abstaining from problematic impulsive behaviors.

Pharmacological fMRI: A New Tool for Drug Development in Humans

Until now, our understanding of human brain pharmacology has depended on indirect assessments or animal models. The advent of pharmacological functional magnetic resonance imaging (phMRI) has enabled researchers to focus directly on human pharmacology and brain function.

Functional MRI, with its increased spatial and temporal resolution, has a further advantage over other neuroimaging methods in that being totally noninvasive, it allows serial, longitudinal studies to be performed on the same subject. This opens the door to a new era of phMRI, as the effects of drugs can be readily monitored in one subject (control or patient) over time. In addition, sophisticated paradigms can be developed that can isolate specific brain regions of activation. These regions can then be subsequently targeted and challenged with appropriate drugs. This allows for a “battery” of paradigms aimed at determining a drug’s mechanism and site of action, which would be valuable for drug development and discovery.

Review : Metabolic Imaging: A Window on Brain Development and Plasticity

Various biochemical and physiological processes that undergo maturational changes during human brain development can be now studied in vivo using PET. The distribution of local cerebral glucose utilization shows regional alterations in the first year of life in agreement with behavioral, neurophysiological, and anatomical changes known to occur during development of the infant. Measurement of the absolute rates of glucose utilization with PET reveals that during the major portion of the first decade, the human brain has a higher energy (glucose) demand compared with both the newborn and adult brains. With adolescence, glucose utilization rates decline to reach adult values by age 16-18 years. This nonlinear course of cerebral glucose 'metabolic' maturation is also seen in a number of animal models and coincides with the develop mental course of transient synaptic exuberance associated with enhanced brain plasticity and efficient learn ing. Evidence of brain reorganization detected with PET is discussed in children with unilateral brain injury and early sensory deprivation. NEUROSCIENTIST 5:29-40, 1999

Optogenetic fMRI in the mouse hippocampus: Hemodynamic response to brief glutamatergic stimuli

The combination of optogenetics with functional magnetic resonance imaging is a promising tool to study the causal relationship between specific neuronal populations and global brain activity. We employed this technique to study the brain response to recruitment of glutamatergic neurons in the mouse hippocampus. The light-sensitive protein channelrhodopsin-2 was expressed in α-CamKII-positive glutamatergic neurons in the left hippocampus (N = 10). Functional magnetic resonance imaging was performed during local laser stimulation, with stimulus duration of 1 second. The hemodynamic response to these stimuli was analyzed on a whole-brain level. In a secondary analysis, we examined the impact of the stimulation locus on the dorso-ventral axis within the hippocampal formation. The hemodynamic response in the mouse hippocampus had an earlier peak and a shorter duration compared to those observed in humans. Photostimulation was associated with significantly increased blood oxygen level-dependent signal in group statistics: bilaterally in the hippocampus, frontal lobe and septum, ipsilaterally in the nucleus accumbens and contralaterally in the striatum. More dorsal position of the laser fiber was associated with a stronger activation in projection regions (insular cortex and striatum). The characterization of brain-region-specific hemodynamic response functions may enable more precise interpretation of future functional magnetic resonance imaging experiments.

Distinct effects of trial-driven and task Set-related control in primary visual cortex

Task sets are task-specific configurations of cognitive processes that facilitate task-appropriate reactions to stimuli. While it is established that the trial-by-trial deployment of visual attention to expected stimuli influences neural responses in primary visual cortex (V1) in a retinotopically specific manner, it is not clear whether the mechanisms that help maintain a task set over many trials also operate with similar retinotopic specificity. Here, we address this question by using BOLD fMRI to characterize how portions of V1 that are specialized for different eccentricities respond during distinct components of an attention-demanding discrimination task: cue-driven preparation for a trial, trial-driven processing, task-initiation at the beginning of a block of trials, and task-maintenance throughout a block of trials. Tasks required either unimodal attention to an auditory or a visual stimulus or selective intermodal attention to the visual or auditory component of simultaneously presented visual and auditory stimuli. We found that while the retinotopic patterns of trial-driven and cue-driven activity depended on the attended stimulus, the retinotopic patterns of task-initiation and task-maintenance activity did not. Further, only the retinotopic patterns of trial-driven activity were found to depend on the presence of inter-modal distraction. Participants who performed well on the intermodal selective attention tasks showed strong task-specific modulations of both trial-driven and task-maintenance activity. Importantly, task-related modulations of trial-driven and task-maintenance activity were in opposite directions. Together, these results confirm that there are (at least) two different processes for top-down control of V1: One, working trial-by-trial, differently modulates activity across different eccentricity sectors - portions of V1 corresponding to different visual eccentricities. The second process works across longer epochs of task performance, and does not differ among eccentricity sectors. These results are discussed in the context of previous literature examining top-down control of visual cortical areas.

Functional Neuroimaging: Fundamental Principles and Clinical Applications

Functional imaging modalities, such as functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI), are rapidly changing the scope and practice of neuroradiology. While these modalities have long been used in research, they are increasingly being used in clinical practice to enable reliable identification of eloquent cortex and white matter tracts in order to guide treatment planning and to serve as a diagnostic supplement when traditional imaging fails. An understanding of the scientific principles underlying fMRI and DTI is necessary in current radiological practice. fMRI relies on a compensatory hemodynamic response seen in cortical activation and the intrinsic discrepant magnetic properties of deoxy- and oxyhemoglobin. Neuronal activity can be indirectly visualized based on a hemodynamic response, termed neurovascular coupling. fMRI demonstrates utility in identifying areas of cortical activation (i.e., task-based activation) and in discerning areas of neuronal connectivity when used during the resting state, termed resting state fMRI. While fMRI is limited to visualization of gray matter, DTI permits visualization of white matter tracts through diffusion restriction along different axes. We will discuss the physical, statistical and physiological principles underlying these functional imaging modalities and explore new promising clinical applications.

Early visual cortex reflects initiation and maintenance of task set

The human brain is able to process information flexibly, depending on a person's task. The mechanisms underlying this ability to initiate and maintain a task set are not well understood, but they are important for understanding the flexibility of human behavior and developing therapies for disorders involving attention. Here we investigate the differential roles of early visual cortical areas in initiating and maintaining a task set. Using functional Magnetic Resonance Imaging (fMRI), we characterized three different components of task set-related, but trial-independent activity in retinotopically mapped areas of early visual cortex, while human participants performed attention demanding visual or auditory tasks. These trial-independent effects reflected: (1) maintenance of attention over a long duration, (2) orienting to a cue, and (3) initiation of a task set. Participants performed tasks that differed in the modality of stimulus to be attended (auditory or visual) and in whether there was a simultaneous distractor (auditory only, visual only, or simultaneous auditory and visual). We found that patterns of trial-independent activity in early visual areas (V1, V2, V3, hV4) depend on attended modality, but not on stimuli. Further, different early visual areas play distinct roles in the initiation of a task set. In addition, activity associated with maintaining a task set tracks with a participant's behavior. These results show that trial-independent activity in early visual cortex reflects initiation and maintenance of a person's task set.

Neural substrates associated with humor processing

Background

Humor is composed of a cognitive element related to the detection of humor and an affective element related to the appreciation of humor. To investigate activated areas of the brain related to the two components of humor and to identify neural substrates associated with the degree of humor intensity, 13 participants were scanned while watching cartoons.

Findings

While watching humorous scenes, various areas of the brain were activated, including (1) the inferior gyrus, an area involved in reconciling ambiguous semantic content with stored knowledge, and (2) the temporal gyrus and fusiform gyrus, brain regions associated with the feeling of mirth. Further, humor intensity was positively correlated with BOLD signal magnitude in the nucleus accumbens, a region known to be involved in psychologically and psychopharmacologically driven rewards.

Conclusions

Our findings demonstrate a two-component neural circuit model of humor processing and a key region important in pleasurable feelings accompanied by humor.

Does functional MRI detect activation in white matter? A review of emerging evidence, issues, and future directions

Functional magnetic resonance imaging (fMRI) is a non-invasive technique that allows for visualization of activated brain regions. Until recently, fMRI studies have focused on gray matter. There are two main reasons white matter fMRI remains controversial: (1) the blood oxygen level dependent (BOLD) fMRI signal depends on cerebral blood flow and volume, which are lower in white matter than gray matter and (2) fMRI signal has been associated with post-synaptic potentials (mainly localized in gray matter) as opposed to action potentials (the primary type of neural activity in white matter). Despite these observations, there is no direct evidence against measuring fMRI activation in white matter and reports of fMRI activation in white matter continue to increase. The questions underlying white matter fMRI activation are important. White matter fMRI activation has the potential to greatly expand the breadth of brain connectivity research, as well as improve the assessment and diagnosis of white matter and connectivity disorders. The current review provides an overview of the motivation to investigate white matter fMRI activation, as well as the published evidence of this phenomenon. We speculate on possible neurophysiologic bases of white matter fMRI signals, and discuss potential explanations for why reports of white matter fMRI activation are relatively scarce. We end with a discussion of future basic and clinical research directions in the study of white matter fMRI.

Recent developments in optimal experimental designs for functional magnetic resonance imaging

Functional magnetic resonance imaging (fMRI) is one of the leading brain mapping technologies for studying brain activity in response to mental stimuli. For neuroimaging studies utilizing this pioneering technology, there is a great demand of high-quality experimental designs that help to collect informative data to make precise and valid inference about brain functions. This paper provides a survey on recent developments in experimental designs for fMRI studies. We briefly introduce some analytical and computational tools for obtaining good designs based on a specified design selection criterion. Research results about some commonly considered designs such as blocked designs, and m-sequences are also discussed. Moreover, we present a recently proposed new type of fMRI designs that can be constructed using a certain type of Hadamard matrices. Under certain assumptions, these designs can be shown to be statistically optimal. Some future research directions in design of fMRI experiments are also discussed.

Increasing fMRI sampling rate improves Granger causality estimates

Estimation of causal interactions between brain areas is necessary for elucidating large-scale functional brain networks underlying behavior and cognition. Granger causality analysis of time series data can quantitatively estimate directional information flow between brain regions. Here, we show that such estimates are significantly improved when the temporal sampling rate of functional magnetic resonance imaging (fMRI) is increased 20-fold. Specifically, healthy volunteers performed a simple visuomotor task during blood oxygenation level dependent (BOLD) contrast based whole-head inverse imaging (InI). Granger causality analysis based on raw InI BOLD data sampled at 100-ms resolution detected the expected causal relations, whereas when the data were downsampled to the temporal resolution of 2 s typically used in echo-planar fMRI, the causality could not be detected. An additional control analysis, in which we SINC interpolated additional data points to the downsampled time series at 0.1-s intervals, confirmed that the improvements achieved with the real InI data were not explainable by the increased time-series length alone. We therefore conclude that the high-temporal resolution of InI improves the Granger causality connectivity analysis of the human brain.

Inferring common cognitive mechanisms from brain blood-flow lateralization data: a new methodology for fTCD analysis

Current neuroimaging techniques with high spatial resolution constrain participant motion so that many natural tasks cannot be carried out. The aim of this paper is to show how a time-locked correlation-analysis of cerebral blood flow velocity (CBFV) lateralization data, obtained with functional TransCranial Doppler (fTCD) ultrasound, can be used to infer cerebral activation patterns across tasks. In a first experiment we demonstrate that the proposed analysis method results in data that are comparable with the standard Lateralization Index (LI) for within-task comparisons of CBFV patterns, recorded during cued word generation (CWG) at two difficulty levels. In the main experiment we demonstrate that the proposed analysis method shows correlated blood-flow patterns for two different cognitive tasks that are known to draw on common brain areas, CWG, and Music Synthesis. We show that CBFV patterns for Music and CWG are correlated only for participants with prior musical training. CBFV patterns for tasks that draw on distinct brain areas, the Tower of London and CWG, are not correlated. The proposed methodology extends conventional fTCD analysis by including temporal information in the analysis of cerebral blood-flow patterns to provide a robust, non-invasive method to infer whether common brain areas are used in different cognitive tasks. It complements conventional high resolution imaging techniques.

Neurovascular coupling in normal aging: a combined optical, ERP and fMRI study

Brain aging is characterized by changes in both hemodynamic and neuronal responses, which may be influenced by the cardiorespiratory fitness of the individual. To investigate the relationship between neuronal and hemodynamic changes, we studied the brain activity elicited by visual stimulation (checkerboard reversals at different frequencies) in younger adults and in older adults varying in physical fitness. Four functional brain measures were used to compare neuronal and hemodynamic responses obtained from BA17: two reflecting neuronal activity (the event-related optical signal, EROS, and the C1 response of the ERP), and two reflecting functional hemodynamic changes (functional magnetic resonance imaging, fMRI, and near-infrared spectroscopy, NIRS). The results indicated that both younger and older adults exhibited a quadratic relationship between neuronal and hemodynamic effects, with reduced increases of the hemodynamic response at high levels of neuronal activity. Although older adults showed reduced activation, similar neurovascular coupling functions were observed in the two age groups when fMRI and deoxy-hemoglobin measures were used. However, the coupling between oxy- and deoxy-hemoglobin changes decreased with age and increased with increasing fitness. These data indicate that departures from linearity in neurovascular coupling may be present when using hemodynamic measures to study neuronal function.

Neural underpinnings of the identifiable victim effect: affect shifts preferences for giving

The "identifiable victim effect" refers to peoples' tendency to preferentially give to identified versus anonymous victims of misfortune, and has been proposed to partly depend on affect. By soliciting charitable donations from human subjects during behavioral and neural (i.e., functional magnetic resonance imaging) experiments, we sought to determine whether and how affect might promote the identifiable victim effect. Behaviorally, subjects gave more to orphans depicted by photographs versus silhouettes, and their shift in preferences was mediated by photograph-induced feelings of positive arousal, but not negative arousal. Neurally, while photographs versus silhouettes elicited activity in widespread circuits associated with facial and affective processing, only nucleus accumbens activity predicted and could statistically account for increased donations. Together, these findings suggest that presenting evaluable identifiable information can recruit positive arousal, which then promotes giving. We propose that affect elicited by identifiable stimuli can compel people to give more to strangers, even despite costs to the self.

Passive reading and motor imagery about hand actions and tool-use actions: an fMRI study

Recent studies have shown that motor activations in action verb comprehension can be modulated by task demands (e.g., motor imagery vs. passive reading) and the specificity of action verb meaning. However, how the two factors work together to influence the involvement of the motor system during action verb comprehension is still unclear. To address the issue, the current study investigated the brain activations in motor imagery and passive reading of verbs about hand actions and tool-use actions. Three types of Chinese verbs were used, including hand-action verbs and two types of tool-use verbs emphasizing either the hand or tools information. Results indicated that all three types of verbs elicited common activations in hand motor areas during passive reading and motor imagery. Contrast analyses showed that in the hand verbs and the tool verbs where the hand information was emphasized, motor imagery elicited stronger effects than passive reading in the superior frontal gyrus, supplemental motor area and cingulate cortex that are related to motor control and regulation. For tool-use verbs emphasizing tools information, the motor imagery task elicited stronger activity than passive reading in occipital regions related to visual imagery. These results suggest that motor activations during action verb comprehension can be modulated by task demands and semantic features of action verbs. The sensorimotor simulation during language comprehension is flexible and determined by the interactions between linguistic and extralinguistic contexts.

Statistical analysis of high density diffuse optical tomography

High density diffuse optical tomography (HD-DOT) is a noninvasive neuroimaging modality with moderate spatial resolution and localization accuracy. Due to portability and wear-ability advantages, HD-DOT has the potential to be used in populations that are not amenable to functional magnetic resonance imaging (fMRI), such as hospitalized patients and young children. However, whereas the use of event-related stimuli designs, general linear model (GLM) analysis, and imaging statistics are standardized and routine with fMRI, such tools are not yet common practice in HD-DOT. In this paper we adapt and optimize fundamental elements of fMRI analysis for application to HD-DOT. We show the use of event-related protocols and GLM de-convolution analysis in un-mixing multi-stimuli event-related HD-DOT data. Statistical parametric mapping (SPM) in the framework of a general linear model is developed considering the temporal and spatial characteristics of HD-DOT data. The statistical analysis utilizes a random field noise model that incorporates estimates of the local temporal and spatial correlations of the GLM residuals. The multiple-comparison problem is addressed using a cluster analysis based on non-stationary Gaussian random field theory. These analysis tools provide access to a wide range of experimental designs necessary for the study of the complex brain functions. In addition, they provide a foundation for understanding and interpreting HD-DOT results with quantitative estimates for the statistical significance of detected activation foci.

Altered hub configurations within default mode network following acupuncture at ST36: a multimodal investigation combining fMRI and MEG

Acupuncture, an externally somatosensory stimulation in the Traditional Chinese Medicine, has been proposed about its modulations on the brain's default mode network (DMN). However, it is still unknown on how the internal brain resting networks are modulated and what inferences can be made about the physiological processes underlying these changes. Combining high spatial resolution of functional magnetic resonance imaging (fMRI) with high temporal resolution of magnetoencephalography (MEG), in the current multimodal study, we sought to explore spatiotemporally whether or not band-specific DMN hub configurations would be induced by verum acupuncture, compared with sham control. Spatial independent component analysis was applied to fMRI data, followed by the discrete regional sources seeded into MEG data. Partial correlation analysis was further adopted to estimate the intrinsic functional connectivity and network hub configurations. One of the most striking findings is that the posterior cingulate cortex is not only validated as a robust DMN hub, but served as a hub only within the delta and gamma bands following the verum acupuncture, compared with its consistently being a DMN hub in sham control group. Our preliminary results may provide a new perspective to lend support for the specificity of neural mechanism underlying acupuncture.

fMRI hemodynamics accurately reflects neuronal timing in the human brain measured by MEG

Neuronal activation sequence information is essential for understanding brain functions. Extracting such timing information from blood oxygenation level dependent (BOLD) fMRI is confounded by interregional neurovascular differences and poorly understood relations between BOLD and electrophysiological response delays. Here, we recorded whole-head BOLD fMRI at 100 ms resolution and magnetoencephalography (MEG) during a visuomotor reaction-time task. Both methods detected the same activation sequence across five regions, from visual towards motor cortices, with linearly correlated interregional BOLD and MEG response delays. The smallest significant interregional BOLD delay was 100 ms; all delays ≥400 ms were significant. Switching the order of external events reversed the sequence of BOLD activations, indicating that interregional neurovascular differences did not confound the results. This may open new avenues for using fMRI to follow rapid activation sequences in the brain.

Females and males are highly similar in language performance and cortical activation patterns during verb generation

OBJECTIVE

To test the existence of sex differences in cortical activation during verb generation when performance is controlled for.

METHODS

Twenty male and 20 female healthy adults underwent functional magnetic resonance imaging (fMRI) using a covert block-design verb generation task (BD-VGT) and its event-related version (ER-VGT) that allowed for intra-scanner recordings of overt responses. Task-specific activations were determined using the following contrasts: BD-VGT covert generation>finger-tapping; ER-VGT overt generation>repetition; ER-VGT overt>covert generation. Lateral cortical regions activated during each contrast were used for calculating language lateralization index scores. Voxelwise regressions were used to determine sex differences in activation, with and without controlling for performance. Each brain region showing male/female activation differences for ER-VGT overt generation>repetition (isolating noun-verb association) was defined as a region of interest (ROI). For each subject, the signal change in each ROI was extracted, and the association between ER-VGT activation related to noun-verb association and performance was assessed separately for each sex.

RESULTS

Males and females performed similarly on language assessments, had similar patterns of language lateralization, and exhibited similar activation patterns for each fMRI task contrast. Regression analysis controlling for overt intra-scanner performance either abolished (BD-VGT) or reduced (ER-VGT) the observed differences in activation between sexes. The main difference between sexes occurred during ER-VGT processing of noun-verb associations, where males showed greater activation than females in the right middle/superior frontal gyrus (MFG/SFG) and the right caudate/anterior cingulate gyrus (aCG) after controlling for performance. Better verb generation performance was associated with increased right caudate/aCG activation in males and with increased right MFG/SFG activation in females.

CONCLUSIONS

Males and females exhibit similar activation patterns during verb generation fMRI, and controlling for intra-scanner performance reduces or even abolishes sex differences in language-related activation. These results suggest that previous findings of sex differences in neuroimaging studies that did not control for task performance may reflect false positives.

Ultrafast inverse imaging techniques for fMRI

Inverse imaging (InI) supercharges the sampling rate of traditional functional MRI 10-100 fold at a cost of a moderate reduction in spatial resolution. The technique is inspired by similarities between multi-sensor magnetoencephalography (MEG) and highly parallel radio-frequency (RF) MRI detector arrays. Using presently available 32-channel head coils at 3T, InI can be sampled at 10 Hz and provides about 5-mm cortical spatial resolution with whole-brain coverage. Here we discuss the present applications of InI, as well as potential future challenges and opportunities in further improving its spatiotemporal resolution and sensitivity. InI may become a helpful tool for clinicians and neuroscientists for revealing the complex dynamics of brain functions during task-related and resting states.

Scale-Free and Multifractal Time Dynamics of fMRI Signals during Rest and Task

Scaling temporal dynamics in functional MRI (fMRI) signals have been evidenced for a decade as intrinsic characteristics of ongoing brain activity (Zarahn et al., 1997). Recently, scaling properties were shown to fluctuate across brain networks and to be modulated between rest and task (He, 2011): notably, Hurst exponent, quantifying long memory, decreases under task in activating and deactivating brain regions. In most cases, such results were obtained: First, from univariate (voxelwise or regionwise) analysis, hence focusing on specific cognitive systems such as Resting-State Networks (RSNs) and raising the issue of the specificity of this scale-free dynamics modulation in RSNs. Second, using analysis tools designed to measure a single scaling exponent related to the second order statistics of the data, thus relying on models that either implicitly or explicitly assume Gaussianity and (asymptotic) self-similarity, while fMRI signals may significantly depart from those either of those two assumptions (Ciuciu et al., 2008; Wink et al., 2008). To address these issues, the present contribution elaborates on the analysis of the scaling properties of fMRI temporal dynamics by proposing two significant variations. First, scaling properties are technically investigated using the recently introduced Wavelet Leader-based Multifractal formalism (WLMF; Wendt et al., 2007). This measures a collection of scaling exponents, thus enables a richer and more versatile description of scale invariance (beyond correlation and Gaussianity), referred to as multifractality. Also, it benefits from improved estimation performance compared to tools previously used in the literature. Second, scaling properties are investigated in both RSN and non-RSN structures (e.g., artifacts), at a broader spatial scale than the voxel one, using a multivariate approach, namely the Multi-Subject Dictionary Learning (MSDL) algorithm (Varoquaux et al., 2011) that produces a set of spatial components that appear more sparse than their Independent Component Analysis (ICA) counterpart. These tools are combined and applied to a fMRI dataset comprising 12 subjects with resting-state and activation runs (Sadaghiani et al., 2009). Results stemming from those analysis confirm the already reported task-related decrease of long memory in functional networks, but also show that it occurs in artifacts, thus making this feature not specific to functional networks. Further, results indicate that most fMRI signals appear multifractal at rest except in non-cortical regions. Task-related modulation of multifractality appears only significant in functional networks and thus can be considered as the key property disentangling functional networks from artifacts. These finding are discussed in the light of the recent literature reporting scaling dynamics of EEG microstate sequences at rest and addressing non-stationarity issues in temporally independent fMRI modes.