Mitigating susceptibility-induced distortions in high-resolution 3DEPI fMRI at 7T.

Geometric distortion is a major limiting factor for spatial specificity in high-resolution fMRI using EPI readouts and is exacerbated at higher field strengths due to increased B0 field inhomogeneity. Prominent correction schemes are based on B0 field-mapping or acquiring reverse phase-encoded (reversed-PE) data. However, to date, comparisons of these techniques in the context of fMRI have only been performed on 2DEPI data, either at lower field or lower resolution. In this study, we investigate distortion compensation in the context of sub-millimetre 3DEPI data at 7T. B0 field-mapping and reversed-PE distortion correction techniques were applied to both partial coverage BOLD-weighted and whole brain MT-weighted 3DEPI data with matched distortion. Qualitative assessment showed overall improvement in cortical alignment for both correction techniques in both 3DEPI fMRI and whole-brain MT-3DEPI datasets. The distortion-corrected MT-3DEPI images were quantitatively evaluated by comparing cortical alignment with an anatomical reference using dice coefficient (DC) and correlation ratio (CR) measures. These showed that B0 field-mapping and reversed-PE methods both improved correspondence between the MT-3DEPI and anatomical data, with more substantial improvements consistently obtained using the reversed-PE approach. Regional analyses demonstrated that the largest benefit of distortion correction, and in particular of the reversed-PE approach, occurred in frontal and temporal regions where susceptibility-induced distortions are known to be greatest, but had not led to complete signal dropout. In conclusion, distortion correction based on reversed-PE data has shown the greater capacity for achieving faithful alignment with anatomical data in the context of high-resolution fMRI at 7T using 3DEPI.

Maximising BOLD sensitivity through automated EPI protocol optimisation.

Gradient echo echo-planar imaging (GE EPI) is used for most fMRI studies but can suffer substantially from image distortions and BOLD sensitivity (BS) loss due to susceptibility-induced magnetic field inhomogeneities. While there are various post-processing methods for correcting image distortions, signal dropouts cannot be recovered and therefore need to be addressed at the data acquisition stage. Common approaches for reducing susceptibility-related BS loss in selected brain areas are: z-shimming, inverting the phase encoding (PE) gradient polarity, optimizing the slice tilt and increasing spatial resolution. The optimization of these parameters can be based on atlases derived from multiple echo-planar imaging (EPI) acquisitions. However, this requires resource and time, which imposes a practical limitation on the range over which parameters can be optimised meaning that the chosen settings may still be sub-optimal. To address this issue, we have developed an automated method that can be used to optimize across a large parameter space. It is based on numerical signal simulations of the BS loss predicted by physical models informed by a large database of magnetic field (B0) maps acquired on a broad cohort of participants. The advantage of our simulation-based approach compared to previous methods is that it saves time and expensive measurements and allows for optimizing EPI protocols by incorporating a broad range of factors, including different resolutions, echo times or slice orientations. To verify the numerical optimisation, results are compared to those from an earlier study and to experimental BS measurements carried out in six healthy volunteers.

Cohesion and Joint Speech: Right Hemisphere Contributions to Synchronized Vocal Production.

UNLABELLED: Synchronized behavior (chanting, singing, praying, dancing) is found in all human cultures and is central to religious, military, and political activities, which require people to act collaboratively and cohesively; however, we know little about the neural underpinnings of many kinds of synchronous behavior (e.g., vocal behavior) or its role in establishing and maintaining group cohesion. In the present study, we measured neural activity using fMRI while participants spoke simultaneously with another person. We manipulated whether the couple spoke the same sentence (allowing synchrony) or different sentences (preventing synchrony), and also whether the voice the participant heard was "live" (allowing rich reciprocal interaction) or prerecorded (with no such mutual influence). Synchronous speech was associated with increased activity in posterior and anterior auditory fields. When, and only when, participants spoke with a partner who was both synchronous and "live," we observed a lack of the suppression of auditory cortex, which is commonly seen as a neural correlate of speech production. Instead, auditory cortex responded as though it were processing another talker's speech. Our results suggest that detecting synchrony leads to a change in the perceptual consequences of one's own actions: they are processed as though they were other-, rather than self-produced. This may contribute to our understanding of synchronized behavior as a group-bonding tool. SIGNIFICANCE STATEMENT: Synchronized human behavior, such as chanting, dancing, and singing, are cultural universals with functional significance: these activities increase group cohesion and cause participants to like each other and behave more prosocially toward each other. Here we use fMRI brain imaging to investigate the neural basis of one common form of cohesive synchronized behavior: joint speaking (e.g., the synchronous speech seen in chants, prayers, pledges). Results showed that joint speech recruits additional right hemisphere regions outside the classic speech production network. Additionally, we found that a neural marker of self-produced speech, suppression of sensory cortices, did not occur during joint synchronized speech, suggesting that joint synchronized behavior may alter self-other distinctions in sensory processing.

Using the robust principal component analysis algorithm to remove RF spike artifacts from MR images.

PURPOSE: Brief bursts of RF noise during MR data acquisition ("k-space spikes") cause disruptive image artifacts, manifesting as stripes overlaid on the image. RF noise is often related to hardware problems, including vibrations during gradient-heavy sequences, such as diffusion-weighted imaging. In this study, we present an application of the Robust Principal Component Analysis (RPCA) algorithm to remove spike noise from k-space. METHODS: Corrupted k-space matrices were decomposed into their low-rank and sparse components using the RPCA algorithm, such that spikes were contained within the sparse component and artifact-free k-space data remained in the low-rank component. Automated center refilling was applied to keep the peaked central cluster of k-space from misclassification in the sparse component. RESULTS: This algorithm was demonstrated to effectively remove k-space spikes from four data types under conditions generating spikes: (i) mouse heart T1 mapping, (ii) mouse heart cine imaging, (iii) human kidney diffusion tensor imaging (DTI) data, and (iv) human brain DTI data. Myocardial T1 values changed by 86.1 ± 171 ms following despiking, and fractional anisotropy values were recovered following despiking of DTI data. CONCLUSION: The RPCA despiking algorithm will be a valuable postprocessing method for retrospectively removing stripe artifacts without affecting the underlying signal of interest. Magn Reson Med 75:2517-2525, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Prospective motion correction of 3D echo-planar imaging data for functional MRI using optical tracking.

We evaluated the performance of an optical camera based prospective motion correction (PMC) system in improving the quality of 3D echo-planar imaging functional MRI data. An optical camera and external marker were used to dynamically track the head movement of subjects during fMRI scanning. PMC was performed by using the motion information to dynamically update the sequence's RF excitation and gradient waveforms such that the field-of-view was realigned to match the subject's head movement. Task-free fMRI experiments on five healthy volunteers followed a 2 × 2 × 3 factorial design with the following factors: PMC on or off; 3.0mm or 1.5mm isotropic resolution; and no, slow, or fast head movements. Visual and motor fMRI experiments were additionally performed on one of the volunteers at 1.5mm resolution comparing PMC on vs PMC off for no and slow head movements. Metrics were developed to quantify the amount of motion as it occurred relative to k-space data acquisition. The motion quantification metric collapsed the very rich camera tracking data into one scalar value for each image volume that was strongly predictive of motion-induced artifacts. The PMC system did not introduce extraneous artifacts for the no motion conditions and improved the time series temporal signal-to-noise by 30% to 40% for all combinations of low/high resolution and slow/fast head movement relative to the standard acquisition with no prospective correction. The numbers of activated voxels (p<0.001, uncorrected) in both task-based experiments were comparable for the no motion cases and increased by 78% and 330%, respectively, for PMC on versus PMC off in the slow motion cases. The PMC system is a robust solution to decrease the motion sensitivity of multi-shot 3D EPI sequences and thereby overcome one of the main roadblocks to their widespread use in fMRI studies.

Improving visual perception through neurofeedback.

Perception depends on the interplay of ongoing spontaneous activity and stimulus-evoked activity in sensory cortices. This raises the possibility that training ongoing spontaneous activity alone might be sufficient for enhancing perceptual sensitivity. To test this, we trained human participants to control ongoing spontaneous activity in circumscribed regions of retinotopic visual cortex using real-time functional MRI-based neurofeedback. After training, we tested participants using a new and previously untrained visual detection task that was presented at the visual field location corresponding to the trained region of visual cortex. Perceptual sensitivity was significantly enhanced only when participants who had previously learned control over ongoing activity were now exercising control and only for that region of visual cortex. Our new approach allows us to non-invasively and non-pharmacologically manipulate regionally specific brain activity and thus provide "brain training" to deliver particular perceptual enhancements.

In vivo functional and myeloarchitectonic mapping of human primary auditory areas.

In contrast to vision, where retinotopic mapping alone can define areal borders, primary auditory areas such as A1 are best delineated by combining in vivo tonotopic mapping with postmortem cyto- or myeloarchitectonics from the same individual. We combined high-resolution (800 µm) quantitative T(1) mapping with phase-encoded tonotopic methods to map primary auditory areas (A1 and R) within the "auditory core" of human volunteers. We first quantitatively characterize the highly myelinated auditory core in terms of shape, area, cortical depth profile, and position, with our data showing considerable correspondence to postmortem myeloarchitectonic studies, both in cross-participant averages and in individuals. The core region contains two "mirror-image" tonotopic maps oriented along the same axis as observed in macaque and owl monkey. We suggest that these two maps within the core are the human analogs of primate auditory areas A1 and R. The core occupies a much smaller portion of tonotopically organized cortex on the superior temporal plane and gyrus than is generally supposed. The multimodal approach to defining the auditory core will facilitate investigations of structure-function relationships, comparative neuroanatomical studies, and promises new biomarkers for diagnosis and clinical studies.

Retrospective correction of physiological noise in DTI using an extended tensor model and peripheral measurements.

Diffusion tensor imaging is widely used in research and clinical applications, but this modality is highly sensitive to artefacts. We developed an easy-to-implement extension of the original diffusion tensor model to account for physiological noise in diffusion tensor imaging using measures of peripheral physiology (pulse and respiration), the so-called extended tensor model. Within the framework of the extended tensor model two types of regressors, which respectively modeled small (linear) and strong (nonlinear) variations in the diffusion signal, were derived from peripheral measures. We tested the performance of four extended tensor models with different physiological noise regressors on nongated and gated diffusion tensor imaging data, and compared it to an established data-driven robust fitting method. In the brainstem and cerebellum the extended tensor models reduced the noise in the tensor-fit by up to 23% in accordance with previous studies on physiological noise. The extended tensor model addresses both large-amplitude outliers and small-amplitude signal-changes. The framework of the extended tensor model also facilitates further investigation into physiological noise in diffusion tensor imaging. The proposed extended tensor model can be readily combined with other artefact correction methods such as robust fitting and eddy current correction.

The effect of local perturbation fields on human DTI: characterisation, measurement and correction.

Indices derived from diffusion tensor imaging (DTI) data, including the mean diffusivity (MD) and fractional anisotropy (FA), are often used to better understand the microstructure of the brain. DTI, however, is susceptible to imaging artefacts, which can bias these indices. The most important sources of artefacts in DTI include eddy currents, nonuniformity and mis-calibration of gradients. We modelled these and other artefacts using a local perturbation field (LPF) approach. LPFs during the diffusion-weighting period describe the local mismatches between the effective and the expected diffusion gradients resulting in a spatially varying error in the diffusion weighting B matrix and diffusion tensor estimation. We introduced a model that makes use of phantom measurements to provide a robust estimation of the LPF in DTI without requiring any scanner-hardware-specific information or special MRI sequences. We derived an approximation of the perturbed diffusion tensor in the isotropic-diffusion limit that can be used to identify regions in any DTI index map that are affected by LPFs. Using these models, we simulated and measured LPFs and characterised their effect on human DTI for three different clinical scanners. The small FA values found in grey matter were biased towards greater anisotropy leading to lower grey-to-white matter contrast (up to 10%). Differences in head position due to e.g. repositioning produced errors of up to 10% in the MD, reducing comparability in multi-centre or longitudinal studies. We demonstrate the importance of the proposed correction by showing improved consistency across scanners, different head positions and an increased FA contrast between grey and white matter.

Correction of vibration artifacts in DTI using phase-encoding reversal (COVIPER).

Diffusion tensor imaging is widely used in research and clinical applications, but still suffers from substantial artifacts. Here, we focus on vibrations induced by strong diffusion gradients in diffusion tensor imaging, causing an echo shift in k-space and consequential signal-loss. We refined the model of vibration-induced echo shifts, showing that asymmetric k-space coverage in widely used Partial Fourier acquisitions results in locally differing signal loss in images acquired with reversed phase encoding direction (blip-up/blip-down). We implemented a correction of vibration artifacts in diffusion tensor imaging using phase-encoding reversal (COVIPER) by combining blip-up and blip-down images, each weighted by a function of its local tensor-fit error. COVIPER was validated against low vibration reference data, resulting in an error reduction of about 72% in fractional anisotropy maps. COVIPER can be combined with other corrections based on phase encoding reversal, providing a comprehensive correction for eddy currents, susceptibility-related distortions and vibration artifact reduction.

Studying the role of human parietal cortex in visuospatial attention with concurrent TMS-fMRI.

Combining transcranial magnetic stimulation (TMS) with concurrent functional magnetic resonance imaging (fMRI) allows study of how local brain stimulation may causally affect activity in remote brain regions. Here, we applied bursts of high- or low-intensity TMS over right posterior parietal cortex, during a task requiring sustained covert visuospatial attention to either the left or right hemifield, or in a neutral control condition, while recording blood oxygenation-level-dependent signal with a posterior MR surface coil. As expected, the active attention conditions activated components of the well-described "attention network," as compared with the neutral baseline. Also as expected, when comparing left minus right attention, or vice versa, contralateral occipital visual cortex was activated. The critical new finding was that the impact of high- minus low-intensity parietal TMS upon these visual regions depended on the currently attended side. High- minus low-intensity parietal TMS increased the difference between contralateral versus ipsilateral attention in right extrastriate visual cortex. A related albeit less pronounced pattern was found for left extrastriate visual cortex. Our results confirm that right human parietal cortex can exert attention-dependent influences on occipital visual cortex and provide a proof of concept for the use of concurrent TMS-fMRI in studying how remote influences can vary in a purely top-down manner with attentional demands.

Transcranial direct current stimulation with functional magnetic resonance imaging: a detailed validation and operational guide.

Introduction: Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique used to modulate human brain and behavioural function in both research and clinical interventions. The combination of functional magnetic resonance imaging (fMRI) with tDCS enables researchers to directly test causal contributions of stimulated brain regions, answering questions about the physiology and neural mechanisms underlying behaviour. Despite the promise of the technique, advances have been hampered by technical challenges and methodological variability between studies, confounding comparability/replicability. Methods: Here tDCS-fMRI at 3T was developed for a series of experiments investigating language recovery after stroke. To validate the method, one healthy volunteer completed an fMRI paradigm with three conditions: (i) No-tDCS, (ii) Sham-tDCS, (iii) 2mA Anodal-tDCS. MR data were analysed in SPM12 with region-of-interest (ROI) analyses of the two electrodes and reference sites. Results: Quality assessment indicated no visible signal dropouts or distortions introduced by the tDCS equipment. After modelling scanner drift, motion-related variance, and temporal autocorrelation, we found no field inhomogeneity in functional sensitivity metrics across conditions in grey matter and in the three ROIs. Discussion: Key safety factors and risk mitigation strategies that must be taken into consideration when integrating tDCS into an fMRI environment are outlined. To obtain reliable results, we provide practical solutions to technical challenges and complications of the method. It is hoped that sharing these data and SOP will promote methodological replication in future studies, enhancing the quality of tDCS-fMRI application, and improve the reliability of scientific results in this field. Conclusions: The method and data provided here provide a technically safe, reliable tDCS-fMRI procedure to obtain high quality MR data. The detailed framework of the Standard Operation Procedure SOP ( https://doi.org/10.5281/zenodo.4606564) systematically reports the technical and procedural elements of our tDCS-fMRI approach, which we hope can be adopted and prove useful in future studies.

Activity or connectivity? A randomized controlled feasibility study evaluating neurofeedback training in Huntington's disease.

Non-invasive methods, such as neurofeedback training, could support cognitive symptom management in Huntington's disease by targeting brain regions whose function is impaired. The aim of our single-blind, sham-controlled study was to collect rigorous evidence regarding the feasibility of neurofeedback training in Huntington's disease by examining two different methods, activity and connectivity real-time functional MRI neurofeedback training. Thirty-two Huntington's disease gene-carriers completed 16 runs of neurofeedback training, using an optimized real-time functional MRI protocol. Participants were randomized into four groups, two treatment groups, one receiving neurofeedback derived from the activity of the supplementary motor area, and another receiving neurofeedback based on the correlation of supplementary motor area and left striatum activity (connectivity neurofeedback training), and two sham control groups, matched to each of the treatment groups. We examined differences between the groups during neurofeedback training sessions and after training at follow-up sessions. Transfer of training was measured by measuring the participants' ability to upregulate neurofeedback training target levels without feedback (near transfer), as well as by examining change in objective, a priori defined, behavioural measures of cognitive and psychomotor function (far transfer) before and at 2 months after training. We found that the treatment group had significantly higher neurofeedback training target levels during the training sessions compared to the control group. However, we did not find robust evidence of better transfer in the treatment group compared to controls, or a difference between the two neurofeedback training methods. We also did not find evidence in support of a relationship between change in cognitive and psychomotor function and learning success. We conclude that although there is evidence that neurofeedback training can be used to guide participants to regulate the activity and connectivity of specific regions in the brain, evidence regarding transfer of learning and clinical benefit was not robust.

Interhemispheric effect of parietal TMS on somatosensory response confirmed directly with concurrent TMS-fMRI.

Transcranial magnetic stimulation (TMS) has been used to document some apparent interhemispheric influences behaviorally, with TMS over the right parietal cortex reported to enhance processing of touch for the ipsilateral right hand (Seyal et al., 1995). However, the neural bases of such apparent interhemispheric influences from TMS remain unknown. Here, we studied this directly by combining TMS with concurrent functional magnetic resonance imaging (fMRI). We applied bursts of 10 Hz TMS over right parietal cortex, at a high or low intensity, during two sensory contexts: either without any other stimulation, or while participants received median nerve stimulation to the right wrist, which projects to left primary somatosensory cortex (SI). TMS to right parietal cortex affected the blood oxygenation level-dependent signal in left SI, with high- versus low-intensity TMS increasing the left SI signal during right-wrist somatosensory input, but decreasing this in the absence of somatosensory input. This state-dependent modulation of SI by parietal TMS over the other hemisphere was accompanied by a related pattern of TMS-induced influences in the thalamus, as revealed by region-of-interest analyses. A behavioral experiment confirmed that the same right parietal TMS protocol of 10 Hz bursts led to enhanced detection of perithreshold electrical stimulation of the right median nerve, which is initially processed in left SI. Our results confirm directly that TMS over right parietal cortex can affect processing in left SI of the other hemisphere, with rivalrous effects (possibly transcallosal) arising in the absence of somatosensory input, but facilitatory effects (possibly involving thalamic circuitry) in the presence of driving somatosensory input.

Concurrent TMS-fMRI and psychophysics reveal frontal influences on human retinotopic visual cortex.

BACKGROUND: Regions in human frontal cortex may have modulatory top-down influences on retinotopic visual cortex, but to date neuroimaging methods have only been able to provide indirect evidence for such functional interactions between remote but interconnected brain regions. Here we combined transcranial magnetic stimulation (TMS) with concurrent functional magnetic resonance imaging (fMRI), plus psychophysics, to show that stimulation of the right human frontal eye-field (FEF) produced a characteristic topographic pattern of activity changes in retinotopic visual areas V1-V4, with functional consequences for visual perception. RESULTS: FEF TMS led to activity increases for retinotopic representations of the peripheral visual field, but to activity decreases for the central field, in areas V1-V4. These frontal influences on visual cortex occurred in a top-down manner, independently of visual input. TMS of a control site (vertex) did not elicit such visual modulations, and saccades, blinks, or pupil dilation could not account for our results. Finally, the effects of FEF TMS on activity in retinotopic visual cortex led to a behavioral prediction that we confirmed psychophysically by showing that TMS of the frontal site (again compared with vertex) enhanced perceived contrast for peripheral relative to central visual stimuli. CONCLUSIONS: Our results provide causal evidence that circuits originating in the human FEF can modulate activity in retinotopic visual cortex, in a manner that differentiates the central and peripheral visual field, with functional consequences for perception. More generally, our study illustrates how the new approach of concurrent TMS-fMRI can now reveal causal interactions between remote but interconnected areas of the human brain.

Imaging seizure activity: a combined EEG/EMG-fMRI study in reading epilepsy.

PURPOSE: To characterize the spatial relationship between activations related to language-induced seizure activity, language processing, and motor control in patients with reading epilepsy. METHODS: We recorded and simultaneously monitored several physiological parameters [voice-recording, electromyography (EMG), electrocardiography (ECG), electroencephalography (EEG)] during blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) in nine patients with reading epilepsy. Individually tailored language paradigms were used to induce and record habitual seizures inside the MRI scanner. Voxel-based morphometry (VBM) was used for structural brain analysis. Reading-induced seizures occurred in six out of nine patients. RESULTS: One patient experienced abundant orofacial reflex myocloni during silent reading in association with bilateral frontal or generalized epileptiform discharges. In a further five patients, symptoms were only elicited while reading aloud with self-indicated events. Consistent activation patterns in response to reading-induced myoclonic seizures were observed within left motor and premotor areas in five of these six patients, in the left striatum (n = 4), in mesiotemporal/limbic areas (n = 4), in Brodmann area 47 (n = 3), and thalamus (n = 2). These BOLD activations were overlapping or adjacent to areas physiologically activated during language and facial motor tasks. No subtle structural abnormalities common to all patients were identified using VBM, but one patient had a left temporal ischemic lesion. DISCUSSION: Based on the findings, we hypothesize that reflex seizures occur in reading epilepsy when a critical mass of neurons are activated through a provoking stimulus within corticoreticular and corticocortical circuitry subserving normal functions.

The effect of prior visual information on recognition of speech and sounds.

To identify and categorize complex stimuli such as familiar objects or speech, the human brain integrates information that is abstracted at multiple levels from its sensory inputs. Using cross-modal priming for spoken words and sounds, this functional magnetic resonance imaging study identified 3 distinct classes of visuoauditory incongruency effects: visuoauditory incongruency effects were selective for 1) spoken words in the left superior temporal sulcus (STS), 2) environmental sounds in the left angular gyrus (AG), and 3) both words and sounds in the lateral and medial prefrontal cortices (IFS/mPFC). From a cognitive perspective, these incongruency effects suggest that prior visual information influences the neural processes underlying speech and sound recognition at multiple levels, with the STS being involved in phonological, AG in semantic, and mPFC/IFS in higher conceptual processing. In terms of neural mechanisms, effective connectivity analyses (dynamic causal modeling) suggest that these incongruency effects may emerge via greater bottom-up effects from early auditory regions to intermediate multisensory integration areas (i.e., STS and AG). This is consistent with a predictive coding perspective on hierarchical Bayesian inference in the cortex where the domain of the prediction error (phonological vs. semantic) determines its regional expression (middle temporal gyrus/STS vs. AG/intraparietal sulcus).

Distinct causal influences of parietal versus frontal areas on human visual cortex: evidence from concurrent TMS-fMRI.

It has often been proposed that regions of the human parietal and/or frontal lobe may modulate activity in visual cortex, for example, during selective attention or saccade preparation. However, direct evidence for such causal claims is largely missing in human studies, and it remains unclear to what degree the putative roles of parietal and frontal regions in modulating visual cortex may differ. Here we used transcranial magnetic stimulation (TMS) and functional magnetic resonance imaging (fMRI) concurrently, to show that stimulating right human intraparietal sulcus (IPS, at a site previously implicated in attention) elicits a pattern of activity changes in visual cortex that strongly depends on current visual context. Increased intensity of IPS TMS affected the blood oxygen level-dependent (BOLD) signal in V5/MT+ only when moving stimuli were present to drive this visual region, whereas TMS-elicited BOLD signal changes were observed in areas V1-V4 only during the absence of visual input. These influences of IPS TMS upon remote visual cortex differed significantly from corresponding effects of frontal (eye field) TMS, in terms of how they related to current visual input and their spatial topography for retinotopic areas V1-V4. Our results show directly that parietal and frontal regions can indeed have distinct patterns of causal influence upon functional activity in human visual cortex.

Dorsal premotor cortex exerts state-dependent causal influences on activity in contralateral primary motor and dorsal premotor cortex.

During voluntary action, dorsal premotor cortex (PMd) may exert influences on motor regions in both hemispheres, but such interregional interactions are not well understood. We used transcranial magnetic stimulation (TMS) concurrently with event-related functional magnetic resonance imaging to study such interactions directly. We tested whether causal influences from left PMd upon contralateral (right) motor areas depend on the current state of the motor system, involving regions engaged in a current task. We applied short bursts (360 ms) of high- or low-intensity TMS to left PMd during single isometric left-hand grips or during rest. TMS to left PMd affected activity in contralateral right PMd and primary motor cortex (M1) in a state-dependent manner. During active left-hand grip, high (vs. low)-intensity TMS led to activity increases in contralateral right PMd and M1, whereas activity decreases there due to TMS were observed during no-grip rest. Analyses of condition-dependent functional coupling confirmed topographically specific stronger coupling between left PMd and right PMd (and right M1), when high-intensity TMS was applied to left PMd during left-hand grip. We conclude that left PMd can exert state-dependent interhemispheric influences on contralateral cortical motor areas relevant for a current motor task.

Vagus nerve stimulation for treatment-resistant depression: behavioral and neural effects on encoding negative material.

OBJECTIVES: Vagus nerve stimulation (VNS) can improve depression. Cognitive models of depression highlight an over-representation of negative thoughts and memories, with depressed individuals showing memory facilitation for negative material. We hypothesized that the antidepressant action of VNS may emerge through corrective influences on 'negativity bias' in memory. We therefore examined the impact of VNS on emotional memory and its underlying brain activity. METHODS: We tested a single patient undergoing VNS for treatment-resistant depression (TRD). Stimulation was set at a 30/66-second on/off cycle during three encoding blocks when the patient viewed randomly presented positive, negative, and neutral words. Following each block, VNS was switched off and the patient identified previously seen words from distractors in a subsequent recognition memory task. The patient was scanned using functional magnetic resonance imaging (fMRI) during the first encoding block. RESULTS: There was robust recall of negative material viewed during 'off' cycles of VNS but subsequent memory of negative words was attenuated during active VNS ('on' cycles). VNS did not influence memory for neutral and positive words. With neuroimaging, direct modulatory effects of VNS were observed in dorsomedial, dorsolateral, and orbital regions of the prefrontal cortex. Moreover, during encoding of negative words, compared with positive and neutral words, VNS also modulated activity within orbitofrontal, ventromedial and polar prefrontal cortices, midcingulate cortex, and brain stem. CONCLUSIONS: Our observations show that VNS can interfere with memory of negative information, an effect that may contribute to its antidepressant role. Neuroimaging implicated regions including the ventral and medial prefrontal cortex as an underlying neural substrate.