fMRI Changes Research Articles

Using dynamic time warping for quantifying effects of sinusoidal oscillation deviations during EEG time series prediction and for finding interesting EEG and fMRI changes

Dynamic time warping (DTW) has successfully been used in feature extraction and analysis of brain data [1,2]. However, DTW and other dynamic programming (DP) methods are not nearly as widespread in neuroscientific contexts, as they are in bioinformatics, where they are central [3]. DP algorithms are extremely powerful and efficient [4], so we explored further uses of DTW in the analysis of brain data. The first part a) applies DTW to successfully find locally interesting signal changes in EEG and functional magnetic resonance imaging (fMRI) data. In the second part b) we focused on harmonic analysis. Harmonic analysis as conducted via Fourier Transform (FT) or Wavelet Transform (WT) is extremely widespread in analyzing brain data, especially electroencephalography (EEG) data. The fundamental assumption of these methods is that a complex function (the time series waveform) can be represented as a superposition of sinusoidal oscillations. While comparing spectra is useful, it is incorrect to assume that the entirety of the spectral density is due to oscillatory activity proper (especially sinusoidal) [5]. We wanted to get some idea of the amount and effects of non-sinusoidal oscillations in EEG data. In a) we quantify the amount of local signal dissimilarity, which is often equivalent to where there is interesting sudden activity, and in b) we quantify how much non-sinusoidal activity there is in spectra computed in a standard way. For a) we apply the method on a data set from a simultaneous EEG/fMRI session with 18 subjects that has been used in other published works before [6] and show that we can easily detect movement, changes in brain state accompanying large reaction time changes during a choice reaction time task, and other interesting events in the EEG and fMRI data sets. The method is applicable to both modalities, as DTW is very general and can be used with any type of time series. The method we used works by either running DTW on a selected time interval (or volume) against sequential intervals (or volumes), or by running it as a sliding-window for detecting sudden local signal changes in the EEG or fMRI. For b) we show that the spectral power, as it's typically computed, includes non-sinusoidal activity, when compared to the signal compared against a series of equal-length (to the signal) sinusoidal waves of varying frequencies. We also found when the sinusoidal-oscillation deviations occurred during an EEG time series extrapolation which we performed using a deep learning Toolbox. The EEG time series prediction gave another point of view for the oscillation changes. We find that the prediction breakdown points are related to sudden oscillation changes, which are presumably time points when other neural oscillator generators become active and mixed in the signal. We interpret both prediction breakdowns and momentary oscillatory deviations as being possible reflections of sudden phase changes in the local or global brain state related, which may be related to EEG microstate changes. We hope to bring to attention the flexibility and power of DP to the neuroscientific community.

Attenuation of functional hyperemia to visual stimulation in mild Alzheimer's disease and its sensitivity to cholinesterase inhibition

Despite the growing recognition of the significance of cerebrovascular impairment in the etiology and progression of Alzheimer's disease (AD), the early stage brain vascular dysfunction and its sensitivity to pharmacological interventions is still not fully characterized. Due to the early and aggressive treatment of probable AD with cholinesterase inhibitors (ChEI), which in and of themselves have direct effects on brain vasculature, the vast majority of hemodynamic measurements in early AD subjects reported hitherto have consequently been made only after the start of treatment, complicating the disentanglement of disease- vs. treatment-related effects on the cerebral vasculature. To address this gap, we used pseudo continuous arterial spin labeling MRI to measure resting perfusion and visual stimulation elicited changes in cerebral blood flow (CBF) and blood oxygenation dependent (BOLD) fMRI signal in a cohort of mild AD patients immediately prior to, 6months post, and 12months post commencement of open label cholinesterase inhibitor treatment. Although patients exhibited no gray matter atrophy prior to treatment and their resting perfusion was not distinguishable from that in age, education and gender-matched controls, the patients' visual stimulation-elicited changes in BOLD fMRI and blood flow were decreased by 10±4% (BOLD) and 23±2% (CBF), relative to those in controls. Induction of cholinesterase inhibition treatment was associated with a further, 7±2% reduction in patients' CBF response to visual stimulation, but it stabilized, at this new lower level, over the follow-up period. Likewise, MMSE scores remained stable during the treatment; furthermore, higher MMSE scores were associated with higher perfusion responses to visual stimulation. This study represents the initial step in disentangling the effects of AD pathology from those of the first line treatment with cholinesterase inhibitors on cerebral hemodynamics and supports the use of arterial spin labeling MRI for quantitative evaluation of the brain vascular function in mild Alzheimer's disease. The findings provide evidence of a pronounced deficit in the visual cortex hyperemia despite the relative sparing of visual function in early stage AD, its reduction with ChEI treatment induction, and its stabilization in the first year of cholinesterase inhibition treatment. This article is part of a Special Issue entitled: Vascular Contributions to Cognitive Impairment and Dementia edited by M. Paul Murphy, Roderick A. Corriveau and Donna M. Wilcock.

La neuroprotection périnatale en 2015

Perinatal brain injury is a significant cause of adverse neurodevelopmental outcomes. The objective of this systematic review was to identify patterns of altered brain function, quantified using functional connectivity (FC) changes in resting-state fMRI (rs-fMRI) data, that were associated with motor and language outcomes in individuals with a history of perinatal brain injury. A systematic search using electronic databases was conducted to identify relevant studies. A total of 10 studies were included in the systematic review, representing 260 individuals with a history of perinatal brain injury. Motor and language outcomes were measured at time points ranging from 4 months to 29 years 1 month. Relations between FC and motor measures revealed increased intra-hemispheric FC, reduced inter-hemispheric FC and impaired lateralization of motor-related brain regions associated with motor outcomes. Altered FC within sensorimotor, visual, cerebellum and frontoparietal networks, and between sensorimotor, visual, auditory and higher-order networks, including cerebellum, frontoparietal, default-mode, salience, self-referential and attentional networks were also associated with motor outcomes. In studies assessing the relationship between rs-fMRI and language outcome, reduced intra-hemispheric FC, increased inter-hemispheric FC and right-hemisphere lateralization of language-related brain regions correlated with language outcomes. Evidence from this systematic review suggests a possible association between diaschisis and motor and language impairments in individuals after perinatal brain lesions. These findings support the need to explore the contributions of additional brain regions functionally connected but remote from the primary lesioned brain area for targeted treatments and appropriate intervention, though more studies with increased standardization across neuroimaging and neurodevelopmental assessments are needed.

Cognitive Improvement after Mild Traumatic Brain Injury Measured with Functional Neuroimaging during the Acute Period.

Functional neuroimaging studies in mild traumatic brain injury (mTBI) have been largely limited to patients with persistent post-concussive symptoms, utilizing images obtained months to years after the actual head trauma. We sought to distinguish acute and delayed effects of mild traumatic brain injury on working memory functional brain activation patterns < 72 hours after mild traumatic brain injury (mTBI) and again one-week later. We hypothesized that clinical and fMRI measures of working memory would be abnormal in symptomatic mTBI patients assessed < 72 hours after injury, with most patients showing clinical recovery (i.e., improvement in these measures) within 1 week after the initial assessment. We also hypothesized that increased memory workload at 1 week following injury would expose different cortical activation patterns in mTBI patients with persistent post-concussive symptoms, compared to those with full clinical recovery. We performed a prospective, cohort study of working memory in emergency department patients with isolated head injury and clinical diagnosis of concussion, compared to control subjects (both uninjured volunteers and emergency department patients with extremity injuries and no head trauma). The primary outcome of cognitive recovery was defined as resolution of reported cognitive impairment and quantified by scoring the subject’s reported cognitive post-concussive symptoms at 1 week. Secondary outcomes included additional post-concussive symptoms and neurocognitive testing results. We enrolled 46 subjects: 27 with mild TBI and 19 controls. The time of initial neuroimaging was 48 (+22 S.D.) hours after injury (time 1). At follow up (8.7, + 1.2 S.D., days after injury, time 2), 18 of mTBI subjects (64%) reported moderate to complete cognitive recovery, 8 of whom fully recovered between initial and follow-up imaging. fMRI changes from time 1 to time 2 showed an increase in posterior cingulate activation in the mTBI subjects compared to controls. Increases in activation were greater in those mTBI subjects without cognitive recovery. As workload increased in mTBI subjects, activation increased in cortical regions in the right hemisphere. In summary, we found neuroimaging evidence for working memory deficits during the first week following mild traumatic brain injury. Subjects with persistent cognitive symptoms after mTBI had increased requirement for posterior cingulate activation to complete memory tasks at 1 week following a brain injury. These results provide insight into functional activation patterns during initial recovery from mTBI and expose the regional activation networks that may be involved in working memory deficits.

The Role of Location of Subconcussive Head Impacts in fMRI Brain Activation Change

Monte-Carlo permutation analysis was used to identify sets of head impacts most predictive of functional magnetic resonance imaging (fMRI) changes in football players. The relative distribution of impact location was found to be more predictive of brain activation changes than the number of impacts, suggesting that fMRI changes are related to systematic playing style.

3. Functional MRI in the diagnosis and prognosis of multiple sclerosis

Whereas morphological MR imaging provides clear evidence of white and gray matter lesions reflecting multiple sclerosis (MS) pathology, functional MRI (fMRI) studies of the motor, visual and cognitive networks in MS patients have provided evidence of more diffuse cortical changes. Compared with healthy subjects, fMRI changes are characterized by expansion within physiological task-related networks, such as more prominent participation of higher-level areas or recruitment of additional areas, as well as differences in resting state networks and disrupted within-network connectivity. Longitudinal fMRI studies have demonstrated that the observed abnormalities vary over the course of the disease, even in patients in disease remission (i.e., outside of relapses). Treatment interventions, such as treatment of leg spasticity with intramuscular botulinum toxin, may cause notable, even if transient, normalization of task-related networks. Functional MRI changes in MS reflect morphological MRI abnormalities, especially when more sensitive techniques are applied to detect normal-appearing white and gray matter of the brain and spinal cord. This phenomenon fits in the more widely described mechanism of increased recruitment within functional networks to at least partially compensate for structural damage in brain diseases as diverse as stroke and amyotrophic lateral sclerosis ( Weiller et al., 2006 ). While notable progress has been made to improve prognosis of the clinical course of MS using sophisticated morphological markers, e.g., ( Kalincik et al., 2012 , Zivadinov et al., 2013 ), functional MRI might also contribute to improve disease monitoring prognosis. Finally, functional MRI may be used to study the effects of different therapies on central nervous system engagement ( Filippi and Rocca, 2013 ).

New approaches for the neuroimaging of gene expression.

New approaches for the neuroimaging of gene expression.

Task-evoked fMRI changes in attention networks are associated with preclinical Alzheimer’s disease biomarkers

There is a growing emphasis on examining preclinical levels of Alzheimer’s disease (AD)–related pathology in the absence of cognitive impairment. Previous work examining biomarkers has focused almost exclusively on memory, although there is mounting evidence that attention also declines early in disease progression. In the current experiment, 2 attentional control tasks were used to examine alterations in task-evoked functional magnetic resonance imaging data related to biomarkers of AD pathology. Seventy-one cognitively normal individuals (females = 44, mean age = 63.5 years) performed 2 attention-demanding cognitive tasks in a design that modeled both trial- and task-level functional magnetic resonance imaging changes. Biomarkers included amyloid β42, tau, and phosphorylated tau measured from cerebrospinal fluid and positron emission tomography measures of amyloid deposition. Both tasks elicited widespread patterns of activation and deactivation associated with large task-level manipulations of attention. Importantly, results from both tasks indicated that higher levels of tau and phosphorylated tau pathologies were associated with block-level overactivations of attentional control areas. This suggests early alteration in attentional control with rising levels of AD pathology.

Separating slow BOLD from non-BOLD baseline drifts using multi-echo fMRI

The functional magnetic resonance (fMRI) baseline is known to drift over the course of an experiment and is often attributed to hardware instability. These ultraslow fMRI fluctuations are inseparable from blood oxygenation level dependent (BOLD) changes in standard single echo fMRI and they are therefore typically removed before further analysis in both resting-state and task paradigms. However, some part of these fluctuations may be of neuronal origin, as neural activity can indeed fluctuate at the scale of several minutes or even longer, such as after the administration of drugs or during the ultradian rhythms. Here, we show that it is possible to separate the slow BOLD and non-BOLD drifts automatically using multi-echo fMRI and multi-echo independent components analysis (ME-ICA) denoising by demonstrating the detection of a visual signal evoked from a flickering checkerboard with slowly changing contrast.

Mapping (and modeling) physiological movements during EEG-fMRI recordings: the added value of the video acquired simultaneously.

During resting-state EEG-fMRI studies in epilepsy, patients' spontaneous head-face movements occur frequently. We tested the usefulness of synchronous video recording to identify and model the fMRI changes associated with non-epileptic movements to improve sensitivity and specificity of fMRI maps related to interictal epileptiform discharges (IED). Categorization of different facial/cranial movements during EEG-fMRI was obtained for 38 patients [with benign epilepsy with centro-temporal spikes (BECTS, n=16); with idiopathic generalized epilepsy (IGE, n=17); focal symptomatic/cryptogenic epilepsy (n=5)]. We compared at single subject- and at group-level the IED-related fMRI maps obtained with and without additional regressors related to spontaneous movements. As secondary aim, we considered facial movements as events of interest to test the usefulness of video information to obtain fMRI maps of the following face movements: swallowing, mouth-tongue movements, and blinking. Video information substantially improved the identification and classification of the artifacts with respect to the EEG observation alone (mean gain of 28 events per exam). Inclusion of physiological activities as additional regressors in the GLM model demonstrated an increased Z-score and number of voxels of the global maxima and/or new BOLD clusters in around three quarters of the patients. Video-related fMRI maps for swallowing, mouth-tongue movements, and blinking were comparable to the ones obtained in previous task-based fMRI studies. Video acquisition during EEG-fMRI is a useful source of information. Modeling physiological movements in EEG-fMRI studies for epilepsy will lead to more informative IED-related fMRI maps in different epileptic conditions.

Relating resting-state fMRI and EEG whole-brain connectomes across frequency bands.

Whole brain functional connectomes hold promise for understanding human brain activity across a range of cognitive, developmental and pathological states. So called resting-state (rs) functional MRI studies have contributed to the brain being considered at a macroscopic scale as a set of interacting regions. Interactions are defined as correlation-based signal measurements driven by blood oxygenation level dependent (BOLD) contrast. Understanding the neurophysiological basis of these measurements is important in conveying useful information about brain function. Local coupling between BOLD fMRI and neurophysiological measurements is relatively well defined, with evidence that gamma (range) frequency EEG signals are the closest correlate of BOLD fMRI changes during cognitive processing. However, it is less clear how whole-brain network interactions relate during rest where lower frequency signals have been suggested to play a key role. Simultaneous EEG-fMRI offers the opportunity to observe brain network dynamics with high spatio-temporal resolution. We utilize these measurements to compare the connectomes derived from rs-fMRI and EEG band limited power (BLP). Merging this multi-modal information requires the development of an appropriate statistical framework. We relate the covariance matrices of the Hilbert envelope of the source localized EEG signal across bands to the covariance matrices derived from rs-fMRI with the means of statistical prediction based on sparse Canonical Correlation Analysis (sCCA). Subsequently, we identify the most prominent connections that contribute to this relationship. We compare whole-brain functional connectomes based on their geodesic distance to reliably estimate the performance of the prediction. The performance of predicting fMRI from EEG connectomes is considerably better than predicting EEG from fMRI across all bands, whereas the connectomes derived in low frequency EEG bands resemble best rs-fMRI connectivity.

Classification of EEG abnormalities in partial epilepsy with simultaneous EEG–fMRI recordings

Scalp EEG recordings and the classification of interictal epileptiform discharges (IED) in patients with epilepsy provide valuable information about the epileptogenic network, particularly by defining the boundaries of the “irritative zone” (IZ), and hence are helpful during pre-surgical evaluation of patients with severe refractory epilepsies. The current detection and classification of epileptiform signals essentially rely on expert observers. This is a very time-consuming procedure, which also leads to inter-observer variability. Here, we propose a novel approach to automatically classify epileptic activity and show how this method provides critical and reliable information related to the IZ localization beyond the one provided by previous approaches. We applied Wave_clus, an automatic spike sorting algorithm, for the classification of IED visually identified from pre-surgical simultaneous Electroencephalogram–functional Magnetic Resonance Imagining (EEG–fMRI) recordings in 8 patients affected by refractory partial epilepsy candidate for surgery. For each patient, two fMRI analyses were performed: one based on the visual classification and one based on the algorithmic sorting. This novel approach successfully identified a total of 29 IED classes (compared to 26 for visual identification). The general concordance between methods was good, providing a full match of EEG patterns in 2 cases, additional EEG information in 2 other cases and, in general, covering EEG patterns of the same areas as expert classification in 7 of the 8 cases. Most notably, evaluation of the method with EEG–fMRI data analysis showed hemodynamic maps related to the majority of IED classes representing improved performance than the visual IED classification-based analysis (72% versus 50%). Furthermore, the IED-related BOLD changes revealed by using the algorithm were localized within the presumed IZ for a larger number of IED classes (9) in a greater number of patients than the expert classification (7 and 5, respectively). In contrast, in only one case presented the new algorithm resulted in fewer classes and activation areas. We propose that the use of automated spike sorting algorithms to classify IED provides an efficient tool for mapping IED-related fMRI changes and increases the EEG–fMRI clinical value for the pre-surgical assessment of patients with severe epilepsy.

The use of fMRI to detect neural responses to cognitive interference and planning: evidence for a contribution of task related changes in heart rate?

fMRI signals during rest are strongly correlated with heart rate variations. These heart rate/fMRI associations may influence the results of brain activation studies, particularly if heart rate is affected by the task. To assess the contribution of task-related heart rate changes on fMRI brain activation related to executive processing, we co-registered the electrocardiogram with fMRI in 91 subjects during an interference task (color-word Stroop) and during a planning task (Tower of London; ToL). We found that both Stroop interference and ToL planning significantly increased heart rate in the scanner and confirmed significant main effects of heart rate regressors on the fMRI signals. Nevertheless, statistical contrasts that test for increased fMRI during Stroop interference and ToL planning were not significantly influenced by inclusion of heart rate regressors. We conclude therefore that fMRI changes associated with heart rate changes do not impact strongly on higher-order fMRI effects in these commonly used executive function tasks, but routinely adding a correction seems prudent.

Vascular Action as the Primary Mechanism of Cognitive Effects of Cholinergic, CNS-Acting Drugs, a Rat phMRI BOLD Study

Concordant results of functional magnetic resonance imaging (fMRI) and behavioral tests prove that some non-blood-brain barrier-penetrating drugs produce robust central nervous system (CNS) effects. The anticholinergic scopolamine interferes with learning when tested in rats, which coincides with a negative blood-oxygen-level-dependent (BOLD) change in the prefrontal cortex (PFC) as demonstrated by fMRI. The peripherally acting butylscopolamine also evokes a learning deficit in a water-labyrinth test and provokes a negative BOLD signal in the PFC. Donepezil-a highly CNS-penetrating cholinesterase inhibitor-prevents the negative BOLD and cognitive deficits regardless whether the provoking agent is scopolamine or butylscopolamine. Interestingly, the non-BBB-penetrating cholinesterase inhibitor neostigmine also prevents or substantially inhibits those cognitive and fMRI changes. Intact cerebral blood flow and optimal metabolism are crucial for the normal functioning of neurons and other cells in the brain. Drugs that are not BBB penetrating yet act on the CNS highlight the importance of unimpaired circulation, and point to the cerebral vasculature as a primary target for drug action in diseases where impaired circulation and consequently suboptimal energy metabolism are followed by upstream pathologic events.

Abstract 154: Changes in Task fMRI After Stroke Rehabilitation Using Closed-Loop Neurofeedback

Introduction: Brain-computer interface (BCI) is an emerging technology for stroke rehabilitation, but little is known about brain changes associated with its use. We examine changes in laterality index (LI) and functional connectivity (FC) during hand movements associated with BCI interventional therapy. Methods: We collected anatomical and functional MRI of 8 stroke patients with upper extremity motor impairment before, during, and after up to 6 weeks of therapy using a BCI system with tongue and functional electrical stimulations. We acquired functional images during imagined (MI) and executed (ME) tapping and squeezing of each hand; not all subjects performed all tasks. Two subjects’ scans were flipped so that as a group the lesion was left (L) and the impaired limb right (R). We computed LI using 3 mask sets: whole brain, motor network, and motor cortex. Group-level analyses examined FC changes to motor network seeds using AFNI and Matlab NBS toolbox. Results: BCI intervention led to decreased average LI during tapping. Overall, R taps shifted L to bilateral; all L taps shifted bilateral to R. Trends were consistent across all masks at thresholds p&lt;.05 &amp; p&lt;.001 and were linearly modeled (r2 0.614 to 0.999). During R-ME, FC increased between each thalamus with L M1 and the cingulum. During L-ME, most FC increases were intrahemispheric (R M1 to R thalamus; within L M1). L-ME FC also decreased between each thalamus and contralateral frontal regions and between the cerebellum and frontal lobes. This pattern of inter- and intrahemispheric FC increases during respective R and L movement was also observed with MI, and many FC findings persisted in a subanalysis excluding flipped scans. A network of 6 seeds and 9 edges within the motor network had increased FC during R-ME. All FC changes p&lt;.05. Conclusions: BCI interventional therapy of the impaired hand leads to more bilateral brain activity, while more lateralized activation was seen of the unimpaired hand to its corresponding contralateral motor regions. With different patterns of change observed during tasks using the impaired or unimpaired hand, lesioned brain areas may respond differently to BCI than unlesioned counterparts.

FMRI resting state networks and their association with cognitive fluctuations in dementia with Lewy bodies.

Cognitive fluctuations are a core symptom in dementia with Lewy bodies (DLB) and may relate to pathological alterations in distributed brain networks. To test this we analysed resting state fMRI changes in a cohort of fluctuating DLB patients (n = 16) compared with age matched controls (n = 17) with the aim of finding functional connectivity (FC) differences between these two groups and whether these associate with cognitive fluctuations in DLB. Resting state networks (RSNs) were estimated using independent component analysis and FC between the RSN maps and the entirety of the brain was assessed using dual regression. The default mode network (DMN) appeared unaffected in DLB compared to controls but significant cluster differences between DLB and controls were found for the left fronto-parietal, temporal, and sensory–motor networks. Desynchronization of a number of cortical and subcortical areas related to the left fronto-parietal network was associated with the severity and frequency of cognitive fluctuations. Our findings provide empirical evidence for the potential role of attention–executive networks in the aetiology of this core symptom in DLB.

Present and future of fMRI in multiple sclerosis

Studies with functional MRI (fMRI) of the motor, visual and cognitive networks have consistently demonstrated functional cortical changes in the major multiple sclerosis (MS) clinical phenotypes. Compared with healthy subjects, these fMRI modifications are characterized by an altered recruitment of regions normally devoted to the performance of a given task, recruitment of additional areas, different resting state activity and disrupted connectivity. Studies that applied fMRI longitudinally have shown that such abnormalities vary over the course of the disease, not only after an acute relapse but also in clinically stable patients. fMRI and structural MRI abnormalities of the MS brain are correlated. Movement- and cognitive-associated fMRI changes were found to correlate with the amount of damage to brain normal-appearing white and gray matter and to the spinal cord. This suggests that, at least in some phases of the disease, increased recruitment of ‘critical’ central nervous system regions might contribute to limiting the functional impact of MS-related injury. fMRI has recently been applied to the assessment of functional modifications in the cervical cord of patients with MS. Evidence to date shows that cervical cord fMRI can reliably identify regions involved with tactile and proprioceptive stimulation in MS patients and different clinical phenotypes. As shown in brain studies, these investigations have detected increased recruitment in MS patients compared with healthy controls. At present, fMRI is a useful research tool, and reliable analysis and display methods have been developed. Future perspectives include development of fMRI paradigms for patients with MS-related disability and application of this technique in longitudinal studies to define the temporal evolution of functional cortical changes in different MS phenotypes as well as the effects of various therapeutic approaches on central nervous system plasticity.

P 124. Behavioral and fMRI changes associated with combined tDCS and cognitive rehabilitation in a case series of patients with mild cognitive impairment

A growing body of evidence supports the use of transcranial direct current stimulation (tDCS) for motor rehabilitation; however, the use of tDCS for cognitive rehabilitation has rarely been examined. Patients with mild cognitive impairment (MCI) demonstrate significant learning and memory deficits and are likely to develop Alzheimer’s disease. Functional magnetic resonance imaging (fMRI) typically demonstrates hypoactivation in MCI patients relative to healthy individuals, suggesting reduced neuronal functioning. tDCS provides a non-invasive method through which it may be possible to facilitate neuronal functioning. However, such facilitation may only reinforce the suboptimal networks that have emerged as a result of the disease process. We previously demonstrated that cognitive rehabilitation enhances learning and memory, alters the pattern of task-based activation, and increases connectivity in those with MCI. The primary question is whether the combined use of tDCS and cognitive rehabilitation can engage and reinforce adaptive brain networks more than either approach in isolation. We present a case series of MCI patients who were administered 5 consecutive days of tDCS (2 mA for 20 min; 35 cm 2 anode over FP1, cathode on right deltoid). Patients underwent fMRI during rest-state and task-based (memory encoding of object location associations) conditions before and after tDCS. One patient received only tDCS, while the other two received tDCS and cognitive rehabilitation (combined treatment). Behavioral change was measured using an object-location task in which the distance (in cm) between the recalled vs. actual object location was the dependent variable. Change in task-based activation used the contrast: (novel stimuli (post > pre) > repeated (post > pre)). Regions of interest were selected based on these changes and theoretical rationale and used as seed regions for rest-state cross-correlation based functional connectivity. Behaviorally, patients receiving combined treatment became more accurate (3–4 cm improvement) whereas the tDCS only patient showed minimal change (∼0.6 cm improvement). fMRI showed increased activation within task-relevant regions including the prefrontal, parietal, and inferior temporal cortices, bilaterally. Conversely, the tDCS only patient showed a pattern of increased activation that was restricted to the right superior temporal gyrus and reduced activation in the temporal poles bilaterally. Across all patients, increased activation seemed to be more common in sulcal depths, possibly reflecting the pooling of electrical current in these regions. Reduced activation was observed in the frontopolar cortex (i.e., the area immediately under the anode). Rest-state analyses consistently demonstrated more focused patterns of connectivity post-compared to pre-training in the combined treatment patients. These changes seemed to restore the “normal” differences between the attention and default mode networks in at least some areas (dorsolateral prefrontal cortex). The tDCS only patient showed substantial increases in connectivity that appeared non-specific and involved a number of both lateral and medial prefrontal and parietal cortices. Although caution is warranted in interpreting our findings, these cases provide behavioral and physiologic evidence suggesting the combination of tDCS and cognitive rehabilitation may facilitate learning and memory in patients with MCI.

Changes in resting-state fMRI in vestibular neuritis

Vestibular neuritis (VN) is a sudden peripheral unilateral vestibular failure with often persistent head movement-related dizziness and unsteadiness. Compensation of asymmetrical activity in the primary peripheral vestibular afferents is accomplished by restoration of impaired brainstem vestibulo-ocular and vestibulo-spinal reflexes, but presumably also by changing cortical vestibular tone imbalance subserving, e.g., spatial perception and orientation. The aim of this study was to elucidate (i) whether there are changes of cerebral resting-state networks with respect to functional interregional connectivity (resting-state activity) in VN patients and (ii) whether these are related to neurophysiological, perceptual and functional parameters of vestibular-induced disability. Using independent component analysis (ICA), we compared resting-state networks between 20 patients with unilateral VN and 20 age- and gender-matched healthy control subjects. Patients were examined in the acute VN stage and after 3months. A neural network (component 50) comprising the parietal lobe, medial aspect of the superior parietal lobule, posterior cingulate cortex, middle frontal gyrus, middle temporal gyrus, parahippocampal gyrus, anterior cingulate cortex, insular cortex, caudate nucleus, thalamus and midbrain was modulated between acute VN patients and healthy controls and in patients over time. Within this network, acute VN patients showed decreased resting-state activity (ICA) in the contralateral intraparietal sulcus (IPS), in close vicinity to the supramarginal gyrus (SMG), which increased after 3months. Resting-state activity in IPS tended to increase over 3months in VN patients who improved with respect to functional parameters of vestibular-induced disability (VADL). Resting-state activity in the IPS was not related to perceptual (subjective visual vertical) or neurophysiological parameters of vestibular-induced disability (e.g., gain of vestibulo-ocular reflex, caloric responsiveness, postural sway). VN leads to a change in resting-state activity of the contralateral IPS adjacent to the SMG, which reverses during vestibular compensation over 3months. The ventral intraparietal area in the IPS contains multimodal regions with directionally selective responses to vestibular stimuli making them suitable for participating in spatial orientation and multisensory integration. The clinical importance is indicated by the fact that the increase in resting-state activity tended to be larger in those patients with only little disability at the follow-up examination. This may indicate powerful restitution-related or compensatory cortical changes in resting-state activity.

Quantification and correction of respiration induced dynamic field map changes in fMRI using 3D single shot techniques

Respiration induced dynamic field map changes in the brain are quantified and the influence on the magnitude signal (physiological noise) is investigated. Dynamic off-resonance correction allows to reduce the signal fluctuations overlaying the blood oxygenation level dependent signal in T2*-weighted functional imaging. A single-shot whole brain imaging technique with 100 ms temporal resolution was used to measure dynamic off-resonance maps that were calculated from the incremental changes of the image phase. These off-resonance maps are then used to dynamically update the off-resonance corrected reconstruction. A global resonance offset and a pronounced gradient in head-foot direction were identified as the main components of the change during a respiration cycle. On average, correction for these fluctuations decreases the magnitude fluctuations by around 30%. Single shot 3D imaging allows for a robust quantification of dynamic off-resonance changes in the brain. Correction for these fluctuations removes the physiological noise component associated with dynamic point spread function changes.