Functional MRI Neurofeedback Outperforms Cognitive Behavioral Therapy for Reducing Tinnitus Distress: A Prospective Randomized Clinical Trial.

Background Cognitive behavioral therapy (CBT) is the current standard treatment for chronic severe tinnitus; however, preliminary evidence suggests that real-time functional MRI (fMRI) neurofeedback therapy may be more effective. Purpose To compare the efficacy of real-time fMRI neurofeedback against CBT for reducing chronic tinnitus distress. Materials and Methods In this prospective controlled trial, participants with chronic severe tinnitus were randomized from December 2017 to December 2021 to receive either CBT (CBT group) for 10 weekly group sessions or real-time fMRI neurofeedback (fMRI group) individually during 15 weekly sessions. Change in the Tinnitus Handicap Inventory (THI) score (range, 0-100) from baseline to 6 or 12 months was assessed. Secondary outcomes included four quality-of-life questionnaires (Beck Depression Inventory, Pittsburgh Sleep Quality Index, State-Trait Anxiety Inventory, and World Health Organization Disability Assessment Schedule). Questionnaire scores between treatment groups and between time points were assessed using repeated measures analysis of variance and the nonparametric Wilcoxon signed rank test. Results The fMRI group included 21 participants (mean age, 49 years ± 11.4 [SD]; 16 male participants) and the CBT group included 22 participants (mean age, 53.6 years ± 8.8; 16 male participants). The fMRI group showed a greater reduction in THI scores compared with the CBT group at both 6 months (mean score change, -28.21 points ± 18.66 vs -12.09 points ± 18.86; P = .005) and 12 months (mean score change, -30 points ± 25.44 vs -4 points ± 17.2; P = .01). Compared with baseline, the fMRI group showed improved sleep (mean score, 8.62 points ± 4.59 vs 7.25 points ± 3.61; P = .006) and trait anxiety (mean score, 44 points ± 11.5 vs 39.84 points ± 10.5; P = .02) at 1 month and improved depression (mean score, 13.71 points ± 9.27 vs 6.53 points ± 5.17; P = .01) and general functioning (mean score, 24.91 points ± 17.05 vs 13.06 points ± 10.1; P = .01) at 6 months. No difference in these metrics over time was observed for the CBT group (P value range, .14 to >.99). Conclusion Real-time fMRI neurofeedback therapy led to a greater reduction in tinnitus distress than the current standard treatment of CBT. ClinicalTrials.gov registration no.: NCT05737888; Swiss Ethics registration no.: BASEC2017-00813 © RSNA, 2024 Supplemental material is available for this article.

Predictors of real-time fMRI neurofeedback performance and improvement - A machine learning mega-analysis.

Real-time fMRI neurofeedback is an increasingly popular neuroimaging technique that allows an individual to gain control over his/her own brain signals, which can lead to improvements in behavior in healthy participants as well as to improvements of clinical symptoms in patient populations. However, a considerably large ratio of participants undergoing neurofeedback training do not learn to control their own brain signals and, consequently, do not benefit from neurofeedback interventions, which limits clinical efficacy of neurofeedback interventions. As neurofeedback success varies between studies and participants, it is important to identify factors that might influence neurofeedback success. Here, for the first time, we employed a big data machine learning approach to investigate the influence of 20 different design-specific (e.g. activity vs. connectivity feedback), region of interest-specific (e.g. cortical vs. subcortical) and subject-specific factors (e.g. age) on neurofeedback performance and improvement in 608 participants from 28 independent experiments. With a classification accuracy of 60% (considerably different from chance level), we identified two factors that significantly influenced neurofeedback performance: Both the inclusion of a pre-training no-feedback run before neurofeedback training and neurofeedback training of patients as compared to healthy participants were associated with better neurofeedback performance. The positive effect of pre-training no-feedback runs on neurofeedback performance might be due to the familiarization of participants with the neurofeedback setup and the mental imagery task before neurofeedback training runs. Better performance of patients as compared to healthy participants might be driven by higher motivation of patients, higher ranges for the regulation of dysfunctional brain signals, or a more extensive piloting of clinical experimental paradigms. Due to the large heterogeneity of our dataset, these findings likely generalize across neurofeedback studies, thus providing guidance for designing more efficient neurofeedback studies specifically for improving clinical neurofeedback-based interventions. To facilitate the development of data-driven recommendations for specific design details and subpopulations the field would benefit from stronger engagement in open science research practices and data sharing.

Can we predict real-time fMRI neurofeedback learning success from pretraining brain activity?

Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report large inter-individual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta-analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pretraining functional localizer or no-feedback runs (i.e., self-regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pretraining activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain-based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning.

Impact of Coffee, Wine, and Chocolate Consumption on Cognitive Outcome and MRI Parameters in Old Age.

Coffee, wine and chocolate are three frequently consumed substances with a significant impact on cognition. In order to define the structural and cerebral blood flow correlates of self-reported consumption of coffee, wine and chocolate in old age, we assessed cognition and brain MRI measures in 145 community-based elderly individuals with preserved cognition (69 to 86 years). Based on two neuropsychological assessments during a 3-year follow-up, individuals were classified into stable-stable (52 sCON), intermediate (61 iCON) and deteriorating-deteriorating (32 dCON). MR imaging included voxel-based morphometry (VBM), tract-based spatial statistics (TBSS) and arterial spin labelling (ASL). Concerning behavior, moderate consumption of caffeine was related to better cognitive outcome. In contrast, increased consumption of wine was related to an unfavorable cognitive evolution. Concerning MRI, we observed a negative correlation of wine and VBM in bilateral deep white matter (WM) regions across all individuals, indicating less WM lesions. Only in sCON individuals, we observed a similar yet weaker association with caffeine. Moreover, again only in sCON individuals, we observed a significant positive correlation between ASL and wine in overlapping left parietal WM indicating better baseline brain perfusion. In conclusion, the present observations demonstrate an inverse association of wine and coffee consumption with cognitive performances. Moreover, low consumption of wine but also moderate to heavy coffee drinking was associated with better WM preservation and cerebral blood-flow notably in cognitively stable elders.

Distributed Patterns of Brain Activity Underlying Real-Time fMRI Neurofeedback Training.

Neurofeedback (NF) based on real-time functional magnetic resonance imaging (rt-fMRI) is an exciting neuroimaging application. In most rt-fMRI NF studies, the activity level of a single region of interest (ROI) is provided as a feedback signal and the participants are trained to up or down regulate the feedback signal. NF training effects are typically analyzed using a confirmatory univariate approach, i.e., changes in the target ROI are explained by a univariate linear modulation. However, learning to self-regulate the ROI activity through NF is mediated by distributed changes across the brain. Here, we deploy a multivariate decoding model for assessing NF training effects across the whole brain. Specifically, we first explain the NF training effect by a posthoc multivariate model that leads to a pattern of coactivation based on 90 functional atlas regions. We then use cross validation to reveal the set of brain regions with the best fit. This novel approach was applied to the data from a rt-fMRI NF study where the participants learned to down regulate the auditory cortex. We found that the optimal model consisted of 16 brain regions whose coactivation patterns best described the training effect over the NF training days. Cross validation of the multivariate model showed that it generalized across the participants. Interestingly, the participants could be clustered into two groups with distinct patterns of coactivation, potentially reflecting different NF learning strategies. Overall, our findings revealed that multiple brain regions are involved in learning to regulate an activity in a single ROI, and thus leading to a better understanding of the mechanisms underlying NF training.

Continuous vs. intermittent neurofeedback to regulate auditory cortex activity of tinnitus patients using real-time fMRI - A pilot study.

The emerging technique of real-time fMRI neurofeedback trains individuals to regulate their own brain activity via feedback from an fMRI measure of neural activity. Optimum feedback presentation has yet to be determined, particularly when working with clinical populations. To this end, we compared continuous against intermittent feedback in subjects with tinnitus. Fourteen participants with tinnitus completed the whole experiment consisting of nine runs (3 runs × 3 days). Prior to the neurofeedback, the target region was localized within the auditory cortex using auditory stimulation (1 kHz tone pulsating at 6 Hz) in an ON-OFF block design. During neurofeedback runs, participants received either continuous (n = 7, age 46.84 ± 12.01, Tinnitus Functional Index (TFI) 49.43 ± 15.70) or intermittent feedback (only after the regulation block) (n = 7, age 47.42 ± 12.39, TFI 49.82 ± 20.28). Participants were asked to decrease auditory cortex activity that was presented to them by a moving bar. In the first and the last session, participants also underwent arterial spin labeling (ASL) and resting-state fMRI imaging. We assessed tinnitus severity using the TFI questionnaire before all sessions, directly after all sessions and six weeks after all sessions. We then compared neuroimaging results from neurofeedback using a general linear model (GLM) and region-of-interest analysis as well as behavior measures employing a repeated-measures ANOVA. In addition, we looked at the seed-based connectivity of the auditory cortex using resting-state data and the cerebral blood flow using ASL data. GLM group analysis revealed that a considerable part of the target region within the auditory cortex was significantly deactivated during neurofeedback. When comparing continuous and intermittent feedback groups, the continuous group showed a stronger deactivation of parts of the target region, specifically the secondary auditory cortex. This result was confirmed in the region-of-interest analysis that showed a significant down-regulation effect for the continuous but not the intermittent group. Additionally, continuous feedback led to a slightly stronger effect over time while intermittent feedback showed best results in the first session. Behaviorally, there was no significant effect on the total TFI score, though on a descriptive level TFI scores tended to decrease after all sessions and in the six weeks follow up in the continuous group. Seed-based connectivity with a fixed-effects analysis revealed that functional connectivity increased over sessions in the posterior cingulate cortex, premotor area and part of the insula when looking at all patients while cerebral blood flow did not change significantly over time. Overall, these results show that continuous feedback is suitable for long-term neurofeedback experiments while intermittent feedback presentation promises good results for single session experiments when using the auditory cortex as a target region. In particular, the down-regulation effect is more pronounced in the secondary auditory cortex, which might be more susceptible to voluntary modulation in comparison to a primary sensory region.

Active pain coping is associated with the response in real-time fMRI neurofeedback during pain.

Real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback is used as a tool to gain voluntary control of activity in various brain regions. Little emphasis has been put on the influence of cognitive and personality traits on neurofeedback efficacy and baseline activity. Here, we assessed the effect of individual pain coping on rt-fMRI neurofeedback during heat-induced pain. Twenty-eight healthy subjects completed the Coping Strategies Questionnaire (CSQ) prior to scanning. The first part of the fMRI experiment identified target regions using painful heat stimulation. Then, subjects were asked to down-regulate the pain target brain region during four neurofeedback runs with painful heat stimulation. Functional MRI analysis included correlation analysis between fMRI activation and pain ratings as well as CSQ ratings. At the behavioral level, the active pain coping (first principal component of CSQ) was correlated with pain ratings during neurofeedback. Concerning neuroimaging, pain sensitive regions were negatively correlated with pain coping. During neurofeedback, the pain coping was positively correlated with activation in the anterior cingulate cortex, prefrontal cortex, hippocampus and visual cortex. Thermode temperature was negatively correlated with anterior insula and dorsolateral prefrontal cortex activation. In conclusion, self-reported pain coping mechanisms and pain sensitivity are a source of variance during rt-fMRI neurofeedback possibly explaining variations in regulation success. In particular, active coping seems to be associated with successful pain regulation.

Closed-loop brain training: the science of neurofeedback.

Neurofeedback is a psychophysiological procedure in which online feedback of neural activation is provided to the participant for the purpose of self-regulation. Learning control over specific neural substrates has been shown to change specific behaviours. As a progenitor of brain-machine interfaces, neurofeedback has provided a novel way to investigate brain function and neuroplasticity. In this Review, we examine the mechanisms underlying neurofeedback, which have started to be uncovered. We also discuss how neurofeedback is being used in novel experimental and clinical paradigms from a multidisciplinary perspective, encompassing neuroscientific, neuroengineering and learning-science viewpoints.

Meta-analysis of real-time fMRI neurofeedback studies using individual participant data: How is brain regulation mediated?

An increasing number of studies using real-time fMRI neurofeedback have demonstrated that successful regulation of neural activity is possible in various brain regions. Since these studies focused on the regulated region(s), little is known about the target-independent mechanisms associated with neurofeedback-guided control of brain activation, i.e. the regulating network. While the specificity of the activation during self-regulation is an important factor, no study has effectively determined the network involved in self-regulation in general. In an effort to detect regions that are responsible for the act of brain regulation, we performed a post-hoc analysis of data involving different target regions based on studies from different research groups. We included twelve suitable studies that examined nine different target regions amounting to a total of 175 subjects and 899 neurofeedback runs. Data analysis included a standard first- (single subject, extracting main paradigm) and second-level (single subject, all runs) general linear model (GLM) analysis of all participants taking into account the individual timing. Subsequently, at the third level, a random effects model GLM included all subjects of all studies, resulting in an overall mixed effects model. Since four of the twelve studies had a reduced field of view (FoV), we repeated the same analysis in a subsample of eight studies that had a well-overlapping FoV to obtain a more global picture of self-regulation. The GLM analysis revealed that the anterior insula as well as the basal ganglia, notably the striatum, were consistently active during the regulation of brain activation across the studies. The anterior insula has been implicated in interoceptive awareness of the body and cognitive control. Basal ganglia are involved in procedural learning, visuomotor integration and other higher cognitive processes including motivation. The larger FoV analysis yielded additional activations in the anterior cingulate cortex, the dorsolateral and ventrolateral prefrontal cortex, the temporo-parietal area and the visual association areas including the temporo-occipital junction. In conclusion, we demonstrate that several key regions, such as the anterior insula and the basal ganglia, are consistently activated during self-regulation in real-time fMRI neurofeedback independent of the targeted region-of-interest. Our results imply that if the real-time fMRI neurofeedback studies target regions of this regulation network, such as the anterior insula, care should be given whether activation changes are related to successful regulation, or related to the regulation process per se. Furthermore, future research is needed to determine how activation within this regulation network is related to neurofeedback success.

Neural underpinnings of background acoustic noise in normal aging and mild cognitive impairment.

Previous contributions in younger cohorts have revealed that reallocation of cerebral resources, a crucial mechanism for working memory (WM), may be disrupted by parallel demands of background acoustic noise suppression. To date, no study has explored the impact of such disruption on brain activation in elderly individuals with or without subtle cognitive deficits. We performed a functional Magnetic Resonance Imaging (fMRI) study in 23 cases (mean age=75.7 y.o., 16 men) with mild cognitive impairment (MCI) and 16 elderly healthy controls (HC, mean age=70.1 y.o., three men) using a 2-back WM task, under two distinct MRI background acoustic noise conditions (louder vs. lower noise echo-planar imaging). General linear models were used to assess brain activation as a function of group and noise. In both groups, lower background noise is associated with increased activation of the working memory network (WMN). A decrease of the normally observed deactivation of the default mode network (DMN) is found under louder noise in both groups. Unlike HC, MCI cases also show decreased deactivation of the DMN under both louder and lower background noise. Under louder noise, this decrease is observed in anterior parts of the DMN in HC, and in the posterior cingulate cortex in MCI cases. Our results suggest that background acoustic noise has a differential impact on WMN activation in normal aging as a function of the cognitive status. Only louder noise has a disruptive effect on the usually observed DMN deactivation during WM task performance in HC. In contrast, MCI cases show altered DMN reactivity even in the presence of lower noise.

Dynamic reconfiguration of human brain functional networks through neurofeedback.

Recent fMRI studies demonstrated that functional connectivity is altered following cognitive tasks (e.g., learning) or due to various neurological disorders. We tested whether real-time fMRI-based neurofeedback can be a tool to voluntarily reconfigure brain network interactions. To disentangle learning-related from regulation-related effects, we first trained participants to voluntarily regulate activity in the auditory cortex (training phase) and subsequently asked participants to exert learned voluntary self-regulation in the absence of feedback (transfer phase without learning). Using independent component analysis (ICA), we found network reconfigurations (increases in functional network connectivity) during the neurofeedback training phase between the auditory target region and (1) the auditory pathway; (2) visual regions related to visual feedback processing; (3) insula related to introspection and self-regulation and (4) working memory and high-level visual attention areas related to cognitive effort. Interestingly, the auditory target region was identified as the hub of the reconfigured functional networks without a-priori assumptions. During the transfer phase, we again found specific functional connectivity reconfiguration between auditory and attention network confirming the specific effect of self-regulation on functional connectivity. Functional connectivity to working memory related networks was no longer altered consistent with the absent demand on working memory. We demonstrate that neurofeedback learning is mediated by widespread changes in functional connectivity. In contrast, applying learned self-regulation involves more limited and specific network changes in an auditory setup intended as a model for tinnitus. Hence, neurofeedback training might be used to promote recovery from neurological disorders that are linked to abnormal patterns of brain connectivity.

Recovery of the default mode network after demanding neurofeedback training occurs in spatio-temporally segregated subnetworks.

The default mode (DM) network is a major large-scale cerebral network that can be identified with functional magnetic resonance imaging (fMRI) during resting state. Most studies consider functional connectivity networks as stationary phenomena. Consequently, the transient behavior of the DM network and its subnetworks is still largely unexplored. Most functional connectivity fMRI studies assess the steady state of resting without any task. To specifically investigate the recovery of the DM network during the transition from activation to rest, we implemented a cognitively demanding real-time fMRI neurofeedback task that targeted down-regulation of the primary auditory cortex. Each of twelve healthy subjects performed 16 block-design fMRI runs (4 runs per day repeated on 4 days) resulting 192 runs in total. The analysis included data-driven independent component analysis (ICA) and high-resolution latency estimation between the four components that corresponded to subnetworks of the DM network. These different subnetworks reemerged after regulation with an average time lag or 3.3s and a time lag of 4.4s between the first and fourth components; i.e., the DM recovery first shifts from anterior to posterior, and then gradually focuses on the ventral part of the posterior cingulate cortex, which is known to be implicated in internally directed cognition. In addition, we found less reactivation in the early anterior subnetwork as regulation strength increased, but more reactivation with larger regulation for the late subnetwork that encompassed the ventral PCC. This finding confirms that the level of task engagement influences inversely the subsequent recovery of regions related to attention compared to those related to internally directed cognition.

Cerebral microhemorrhage and iron deposition in mild cognitive impairment: susceptibility-weighted MR imaging assessment.

PURPOSE: To test whether susceptibility-weighted magnetic resonance imaging at baseline may help predict cognitive decline. MATERIALS AND METHODS: This prospective study was approved by the institutional review board, and written informed consent was obtained from all participants. Thirty-five healthy control subjects and 69 patients with mild cognitive impairment were included. Patients with mild cognitive impairment underwent neuropsychologic follow-up after 1 year (40 patients with stable mild cognitive impairment, 27 with progressive mild cognitive impairment, and two lost to follow-up). Cerebral microhemorrhages were visually analyzed by two experienced neuroradiologists in consensus. Iron deposition in deep gray matter was assessed with voxel-wise and region-of-interest analysis after nonlinear spatial registration. In addition, individual classification of mild cognitive impairment was analyzed by using a support vector machine (SVM). RESULTS: At baseline, the number of cerebral microhemorrhages was significantly higher in the mild cognitive impairment group than in the control group (P < .01) but did not differ between the patients with stable and those with progressive mild cognitive impairment. Compared with the control group, patients with mild cognitive impairment had increased iron concentration in the right pallidum (P < .01) and right substantia nigra (P < .01) but decreased concentration in the right red nucleus (P < .05). The classification based on the SVM successfully helped discriminate patients with mild cognitive impairment from the healthy control subjects (accuracy, 84%; sensitivity, 89%; specificity, 85%) and those with stable from those with progressive mild cognitive impairment (accuracy, 85%; sensitivity, 84%; specificity, 83%). CONCLUSION: The findings reveal an accumulation of cerebral microhemorrhage in patients with mild cognitive impairment that is present at baseline, independent of subsequent cognitive decline, as well as an altered iron distribution in subcortical nuclei between the healthy control subjects and patients with mild cognitive impairment. Analysis of iron deposition at baseline performed with an SVM might help identify individual patients with mild cognitive impairment at risk for cognitive decline. SUPPLEMENTAL MATERIAL: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.10100612/-/DC1.

Real-time fMRI feedback training may improve chronic tinnitus.

OBJECTIVES: Tinnitus consists of a more or less constant aversive tone or noise and is associated with excess auditory activation. Transient distortion of this activation (repetitive transcranial magnetic stimulation, rTMS) may improve tinnitus. Recently proposed operant training in real-time functional magnetic resonance imaging (rtfMRI) neurofeedback allows voluntary modification of specific circumscribed neuronal activations. Combining these observations, we investigated whether patients suffering from tinnitus can (1) learn to voluntarily reduce activation of the auditory system by rtfMRI neurofeedback and whether (2) successful learning improves tinnitus symptoms. METHODS: Six participants with chronic tinnitus were included. First, location of the individual auditory cortex was determined in a standard fMRI auditory block-design localizer. Then, participants were trained to voluntarily reduce the auditory activation (rtfMRI) with visual biofeedback of the current auditory activation. RESULTS: Auditory activation significantly decreased after rtfMRI neurofeedback. This reduced the subjective tinnitus in two of six participants. CONCLUSION: These preliminary results suggest that tinnitus patients learn to voluntarily reduce spatially specific auditory activations by rtfMRI neurofeedback and that this may reduce tinnitus symptoms. Optimized training protocols (frequency, duration, etc.) may further improve the results.

Background MR gradient noise and non-auditory BOLD activations: a data-driven perspective.

The effect of echoplanar imaging (EPI) acoustic background noise on blood oxygenation level dependent (BOLD) activations was investigated. Two EPI pulse sequences were compared: (i) conventional EPI with a pulsating sound component of typically 8-10 Hz, which is a potent physiological stimulus, and (ii) the more recently developed continuous-sound EPI, which is perceived as less distractive despite equivalent peak sound pressure levels. Sixteen healthy subjects performed an established demanding visual n-back working memory task. Using an exploratory data analysis technique (tensorial probabilistic independent component analysis; tensor-PICA), we studied the inter-session/within-subject response variability introduced by continuous-sound versus conventional EPI acoustic background noise in addition to temporal and spatial signal characteristics. The analysis revealed a task-related component associated with the established higher-level working memory and motor feedback response network, which exhibited a significant 19% increase in its average effect size for the continuous-sound as opposed to conventional EPI. Stimulus-related lower-level activations, such as primary visual areas, were not modified. EPI acoustic background noise influences much more than the auditory system per se. This analysis provides additional evidence for an enhancement of task-related, extra-auditory BOLD activations by continuous-sound EPI due to less distractive acoustic background gradient noise.

Magnetic resonance imaging techniques in white matter disease: potentials and limitations.

OBJECTIVES: excellent soft tissue contrast, noninvasiveness, assessment of multiple structural and functional parameters, and absence of radiation are the essential properties of magnetic resonance imaging explaining why this modality is the technique of choice for the assessment of cerebral white matter (WM). METHODS: the present review discusses various standard and advance magnetic resonance imaging techniques with respect to WM assessment in a clinical context. Techniques assessing predominantly structure are T2, fluid-attenuated inversion recovery, echo-gradient T2*, and susceptibility weighted imaging. Techniques assessing a mix between structure and function are diffusion-weighted and diffusion tensor imaging to investigate WM tracts, magnetization transfer to assess bound and free water pool, and magnetic resonance spectroscopy investigating brain metabolites. Finally, functional techniques are perfusion-weighted imaging and perfusion reserve imaging to assess cerebral perfusion and cerebral perfusion reserve, respectively. CONCLUSIONS: magnetic resonance imaging may assess various and complementary WM parameters. Because acquisition time is limited in the clinical setting, MR techniques must be adapted to the primary question asked. The basic imaging of WM might include axial T2, diffusion-weighted imaging, and coronal fluid-attenuated inversion recovery. This provides an excellent overview in a relatively short time and 2 imaging planes. The remaining MR techniques can add complementary information, for example, PWI/perfusion reserve imaging in vascular disease, T2*/susceptibility weighted imaging in degenerative disease (iron deposition) and head trauma (microbleeds), magnetic resonance spectroscopy (metabolic disease and neoplasm), magnetization transfer (demyelinating disease), and diffusion tensor imaging (degenerative diseases, presurgical evaluation).

Mapping continuous neuronal activation without an ON-OFF paradigm: initial results of BOLD ceiling fMRI.

Standard functional magnetic resonance imaging (fMRI) requires alternations between activation (ON) and baseline (OFF) periods to map the haemodynamic response to neuronal activation. Consequently, standard fMRI cannot map continuous activations in conditions like tinnitus without an ON-OFF paradigm. We present a novel approach to fMRI that allows mapping of continuous neuronal activation. Compared with standard fMRI, we introduced the application of CO(2) as potent vasodilator. CO(2) induces a 'global' blood oxygenation level-dependent (BOLD) response. The neurovascular coupling in conjunction with the limited cerebral vasodilation implies a limitation or ceiling of the BOLD response. We hypothesize that active areas exhibit a reduced CO(2)-induced DeltaBOLD due to pre-existing 'local' task-induced BOLD response. This putative reduction in DeltaBOLD might be exploited for mapping of continuous neuronal activation. BOLD ceiling fMRI was tested in the auditory system. Six healthy subjects performed three runs: only continuous monaural auditory; only 10% CO(2); simultaneous auditory and CO(2) stimulation. First, we demonstrated the ceiling of DeltaBOLD during continuous auditory activation. According to the known predominantly contralateral auditory processing, monaural auditory stimulation reduced predominantly contralateral (0.41 +/- 0.13%; P < 0.00001) and significantly less (P < 0.0001) ipsilateral DeltaBOLD (0.33 +/- 0.17%; P < 0.00001). The non-auditory area was not affected. Second, this BOLD ceiling was exploited to generate an initial activation map of continuous auditory activation (ON period). In contrast to standard fMRI, an OFF period without neuronal activation was not required. BOLD ceiling fMRI is proposed as a complement to standard fMRI for those conditions where ON-OFF paradigms are impossible.

Effect of fMRI acoustic noise on non-auditory working memory task: comparison between continuous and pulsed sound emitting EPI.

Conventional blood oxygenation level-dependent (BOLD) based functional magnetic resonance imaging (fMRI) is accompanied by substantial acoustic gradient noise. This noise can influence the performance as well as neuronal activations. Conventional fMRI typically has a pulsed noise component, which is a particularly efficient auditory stimulus. We investigated whether the elimination of this pulsed noise component in a recent modification of continuous-sound fMRI modifies neuronal activations in a cognitively demanding non-auditory working memory task. Sixteen normal subjects performed a letter variant n-back task. Brain activity and psychomotor performance was examined during fMRI with continuous-sound fMRI and conventional fMRI. We found greater BOLD responses in bilateral medial frontal gyrus, left middle frontal gyrus, left middle temporal gyrus, left hippocampus, right superior frontal gyrus, right precuneus and right cingulate gyrus with continuous-sound compared to conventional fMRI. Conversely, BOLD responses were greater in bilateral cingulate gyrus, left middle and superior frontal gyrus and right lingual gyrus with conventional compared to continuous-sound fMRI. There were no differences in psychomotor performance between both scanning protocols. Although behavioral performance was not affected, acoustic gradient noise interferes with neuronal activations in non-auditory cognitive tasks and represents a putative systematic confound.