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Functional MRI at ultra‐high field (UHF, ≥7 T) provides significant increases in BOLD contrast‐to‐noise ratio (CNR) compared with conventional field strength (3 T), and has been exploited for reduced field‐of‐view, high spatial resolution mapping of primary sensory areas. Applying these high spatial resolution methods to investigate whole brain functional responses to higher‐order cognitive tasks leads to a number of challenges, in particular how to perform robust group‐level statistical analyses. This study addresses these challenges using an inter‐sensory cognitive task which modulates top‐down attention at graded levels between the visual and somatosensory domains. At the individual level, highly focal functional activation to the task and task difficulty (modulated by attention levels) were detectable due to the high CNR at UHF. However, to assess group level effects, both anatomical and functional variability must be considered during analysis. We demonstrate the importance of surface over volume normalisation and the requirement of no spatial smoothing when assessing highly focal activity. Using novel group analysis on anatomically parcellated brain regions, we show that in higher cognitive areas (parietal and dorsal‐lateral‐prefrontal cortex) fMRI responses to graded attention levels were modulated quadratically, whilst in visual cortex and VIP, responses were modulated linearly. These group fMRI responses were not seen clearly using conventional second‐level GLM analyses, illustrating the limitations of a conventional approach when investigating such focal responses in higher cognitive regions which are more anatomically variable. The approaches demonstrated here complement other advanced analysis methods such as multivariate pattern analysis, allowing UHF to be fully exploited in cognitive neuroscience.

The authors thank the Birmingham Nottingham Strategic Collaboration Fund for supporting this work and MU and a University of Nottingham Anne McLaren Fellowship for funding KJM and a University of Birmingham Fellowship for funding SDM. We established an optimal combination of EEG recording during sparse multiband (MB) fMRI that preserves high-resolution, whole-brain fMRI coverage while enabling broad-band EEG recordings which are uncorrupted by MRI gradient artefacts (GAs). We first determined the safety of simultaneous EEG recording during MB fMRI. Application of MB factor = 4 produced

Most functional MRI (fMRI) studies map task-driven brain activity using a block or event-related paradigm. Sparse paradigm free mapping (SPFM) can detect the onset and spatial distribution of BOLD events in the brain without prior timing information, but relating the detected events to brain function remains a challenge. In this study, we developed a decoding method for SPFM using a coordinate-based meta-analysis method of activation likelihood estimation (ALE). We defined meta-maps of statistically significant ALE values that correspond to types of events and calculated a summation overlap between the normalized meta-maps and SPFM maps. As a proof of concept, this framework was applied to relate SPFM-detected events in the sensorimotor network (SMN) to six motor functions (left/right fingers, left/right toes, swallowing, and eye blinks). We validated the framework using simultaneous electromyography (EMG)–fMRI experiments and motor tasks with short and long duration, and random interstimulus interval. The decoding scores were considerably lower for eye movements relative to other movement types tested. The average successful rate for short and long motor events were 77 ± 13% and 74 ± 16%, respectively, excluding eye movements. We found good agreement between the decoding results and EMG for most events and subjects, with a range in sensitivity between 55% and 100%, excluding eye movements. The proposed method was then used to classify the movement types of spontaneous single-trial events in the SMN during resting state, which produced an average successful rate of 22 ± 12%. Finally, this article discusses methodological implications and improvements to increase the decoding performance.

Multiple sclerosis (MS) is a debilitating disease commonly attributed to degradation of white matter myelin. Symptoms include fatigue, as well as problems associated with vision and movement. Although areas of demyelination in white matter are observed routinely in patients undergoing MRI scans, such measures are often a poor predictor of disease severity. For this reason, it is instructive to measure associated changes in brain function. Widespread white-matter demyelination may lead to delays of propagation of neuronal activity, and with its excellent temporal resolution, magnetoencephalography can be used to probe such delays in controlled conditions (e.g., during a task). In healthy subjects, responses to visuomotor tasks are well documented: in motor cortex, movement elicits a localised decrease in the power of beta band oscillations (event-related beta desynchronisation) followed by an increase above baseline on movement cessation (post-movement beta rebound (PMBR)). In visual cortex, visual stimulation generates increased gamma oscillations. In this study, we use a visuomotor paradigm to measure these responses in MS patients and compare them to age- and gender-matched healthy controls. We show a significant increase in the time-to-peak of the PMBR in patients which correlates significantly with the symbol digit modalities test: a measure of information processing speed. A significant decrease in the amplitude of visual gamma oscillations in patients is also seen. These findings highlight the potential value of electrophysiological imaging in generating a new understanding of visual disturbances and abnormal motor control in MS patients.

Thermal taster status refers to the finding that, in some individuals, thermal stimulation of the tongue elicits a phantom taste. Little is known regarding the mechanism for this, it is hypothesised to be a result of cross-wiring between gustatory and trigeminal nerves whose receptors co-innervate papillae on the tongue. To address this, we use functional magnetic resonance imaging to perform the first study of whether the cortical response to gustatory-trigeminal samples is altered with thermal taster status. We study the response to cold (6°C) gustatory (sweet) samples at varying levels of trigeminal stimulation elicited by CO2 (no CO2, low CO2, high CO2) in thermal taster (TT) and thermal non-taster (TnT) groups, and evaluate associated behavioural measures. Behaviourally, the TT group perceived gustatory and trigeminal stimuli significantly more intense than TnTs, and were significantly more discriminating of CO2 level. fMRI data revealed elevated cortical activation to the no CO2 sample for the TT group compared to TnT group in taste, oral somatosensory and reward areas. In TnTs, a significant positive modulation in cortical response with increasing level of CO2 was found across taste, somatosensory and reward areas. In contrast, in TTs, a reduced positive modulation with increasing level of CO2 was found in somatosensory areas (SI, SII), whilst a significant negative modulation was found in taste (anterior insula) and reward (ACC) areas. This difference in cortical response to trigeminal stimuli supports cross-modal integration in TTs, with gustatory and trigeminal nerves highly stimulated by cold gustatory samples due to their intertwined nature.

The subsequent memory paradigm, according to which cerebral activity for later remembered (LR) and later forgotten (LF) items is contrasted, can be used to characterize the processes necessary for successful memory encoding. Previous simultaneous electroencephalography/functional magnetic resonance imaging (EEG/fMRI) memory studies suggest an inverse relationship between frontal theta band power and the blood oxygenation level dependent (BOLD) signal in the default mode network (DMN). The principal aim of this EEG/fMRI study was to test the hypothesis that this putative theta-DMN relationship is less evident in LF compared with LR trials. Fourteen healthy participants performed an episodic memory task in which pictorial stimuli were presented during encoding, and categorized (as LR or LF) by subsequent memory performance. For each encoding trial, the mean of the Hilbert envelope of the theta signal from 400 to 800 ms after stimulus presentation was calculated. To integrate the EEG and fMRI data, general linear models (GLMs) were used to assess the extent to which these single-trial theta values (as modulators of the main effect of stimulus) predicted DMN BOLD signal change, using: (i) whole-head univariate GLMs and (ii) GLMs in which the outcome variable was the time-course of a DMN component derived from spatial independent component analysis of the fMRI data. Theta was significantly greater for LR than LF stimuli. Furthermore, the inverse relationship between theta and BOLD in the DMN was consistently stronger for LR than LF pictures. These findings imply that theta oscillations are key to attenuating processes which may otherwise impair memory encoding. Hum Brain Mapp 34:2929–2943, 2013. © 2012 Wiley Periodicals, Inc.

fMRI studies of brain activity at rest study slow (

Spatial variation in connectivity is an integral aspect of the brain's architecture. In the absence of this variability, the brain may act as a single homogenous entity without regional specialization. In this study, we investigate the variability in functional links categorized on the basis of the presence of direct structural paths (primary) or indirect paths mediated by one (secondary) or more (tertiary) brain regions ascertained by diffusion tensor imaging. We quantified the variability in functional connectivity using an unbiased estimate of unpredictability (functional connectivity entropy) in a neuropsychiatric disorder where structure‐function relationship is considered to be abnormal; 34 patients with schizophrenia and 32 healthy controls underwent DTI and resting state functional MRI scans. Less than one‐third (27.4% in patients, 27.85% in controls) of functional links between brain regions were regarded as direct primary links on the basis of DTI tractography, while the rest were secondary or tertiary. The most significant changes in the distribution of functional connectivity in schizophrenia occur in indirect tertiary paths with no direct axonal linkage in both early (P = 0.0002, d = 1.46) and late (P = 1 × 10−17, d = 4.66) stages of schizophrenia, and are not altered by the severity of symptoms, suggesting that this is an invariant feature of this illness. Unlike those with early stage illness, patients with chronic illness show some additional reduction in the distribution of connectivity among functional links that have direct structural paths (P = 0.08, d = 0.44). Our findings address a critical gap in the literature linking structure and function in schizophrenia, and demonstrate for the first time that the abnormal state of functional connectivity preferentially affects structurally unconstrained links in schizophrenia. It also raises the question of a continuum of dysconnectivity ranging from less direct (structurally unconstrained) to more direct (structurally constrained) brain pathways underlying the progressive clinical staging and persistence of schizophrenia. Hum Brain Mapp 36:4529–4538, 2015. © 2015 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc.

The ability to detect single trial responses in functional magnetic resonance imaging (fMRI) studies is essential, particularly if investigating learning or adaptation processes or unpredictable events. We recently introduced paradigm free mapping (PFM), an analysis method that detects single trial blood oxygenation level dependent (BOLD) responses without specifying prior information on the timing of the events. PFM is based on the deconvolution of the fMRI signal using a linear hemodynamic convolution model. Our previous PFM method (Caballero‐Gaudes et al., 2011: Hum Brain Mapp) used the ridge regression estimator for signal deconvolution and required a baseline signal period for statistical inference. In this work, we investigate the application of sparse regression techniques in PFM. In particular, a novel PFM approach is developed using the Dantzig selector estimator, solved via an efficient homotopy procedure, along with statistical model selection criteria. Simulation results demonstrated that, using the Bayesian information criterion to select the regularization parameter, this method obtains high detection rates of the BOLD responses, comparable with a model‐based analysis, but requiring no information on the timing of the events and being robust against hemodynamic response function variability. The practical operation of this sparse PFM method was assessed with single‐trial fMRI data acquired at 7T, where it automatically detected all task‐related events, and was an improvement on our previous PFM method, as it does not require the definition of a baseline state and amplitude thresholding and does not compromise on specificity and sensitivity. Hum Brain Mapp, 2013. © 2011 Wiley Periodicals, Inc.