eICAB: A novel deep learning pipeline for Circle of Willis multiclass segmentation and analysis.

BACKGROUND: The accurate segmentation, labeling and quantification of cerebral blood vessels on MR imaging is important for basic and clinical research, yet results are not generalizable, and often require user intervention. New methods are needed to automate this process. PURPOSE: To automatically segment, label and quantify Circle of Willis (CW) arteries on Magnetic Resonance Angiography images using deep convolutional neural networks. MATERIALS AND METHODS: MRA images were pooled from three public and private databases. A total of 116 subjects (mean age 56 years ± 21 [standard deviation]; 72 women) were used to make up the training set (N=101) and the testing set (N=15). In each image, fourteen arterial segments making up or surrounding the CW were manually annotated and validated by a clinical expert. Convolutional neural network (CNN) models were trained on a training set to be finally combined in an ensemble to develop eICAB. Model performances were evaluated using (1) quantitative analysis (dice score on test set) and (2) qualitative analysis (external datasets, N=121). The reliability was assessed using multiple MRAs of healthy participants (ICC of vessel diameters and volumes on test-retest). RESULTS: Qualitative analysis showed that eICAB correctly predicted the large, medium and small arteries in 99±0.4%, 97±1% and 88±7% of all images, respectively. For quantitative assessment, the average dice score coefficients for the large (ICAs, BA), medium (ACAs, MCAs, PCAs-P2), and small (AComm, PComm, PCAs-P1) vessels were 0.76±0.07, 0.76±0.08 and 0.41±0.27, respectively. These results were similar and, in some cases, statistically better (p<0.05) than inter-expert annotation variability and robust to image SNR. Finally, test-retest analysis showed that the model yielded high diameter and volume reliability (ICC=0.99). CONCLUSION: We have developed a quick and reliable open-source CNN-based method capable of accurately segmenting and labeling the CW in MRA images. This method is largely independent of image quality. In the future, we foresee this approach as a critical step towards fully automated analysis of MRA databases in basic and clinical research.

The relationship between persistent organic pollutants and Attention Deficit Hyperactivity Disorder phenotypes: Evidence from task-based neural activity in an observational study of a community sample of Canadian mother-child dyads.

BACKGROUND: Prenatal exposure to persistent organic pollutants (POPs), widespread in North America, is associated with increased Attention Deficit/Hyperactivity Disorder (ADHD) symptoms and may be a modifiable risk for ADHD phenotypes. However, the effects of moderate exposure to POPs on task-based inhibitory control performance, related brain function, and ADHD-related symptoms remain unknown, limiting our ability to develop interventions targeting the neural impact of common levels of exposure. OBJECTIVES: The goal of this study was to examine the association between prenatal POP exposure and inhibitory control performance, neural correlates of inhibitory control and ADHD-related symptoms. METHODS: Prospective data was gathered in an observational study of Canadian mother-child dyads, with moderate exposure to POPs, including polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs), as part of the GESTation and the Environment (GESTE) cohort in Sherbrooke, Quebec, Canada. The sample included 87 eligible children, 46 with maternal plasma samples, functional magnetic resonance imaging (fMRI) data of Simon task performance at 9-11 years, and parental report of clinical symptoms via the Behavioral Assessment System for Children 3 (BASC-3). Simon task performance was probed via drift diffusion modeling, and parameter estimates were related to POP exposure. Simon task-based fMRI data was modeled to examine the difference in incongruent vs congruent trials in regions of interest (ROIs) identified by meta analysis. RESULTS: Of the 46 participants with complete data, 29 were male, and mean age was 10.42 ± 0.55 years. Increased POP exposure was associated with reduced accuracy (e.g. PCB molar sum rate ratio = 0.95; 95% CI [0.90, 0.99]), drift rate (e.g. for PCB molar sum ß = -0.42; 95% CI [-0.77, -0.07]), and task-related brain activity (e.g. in inferior frontal cortex for PCB molar sum ß = -0.35; 95% CI [-0.69, -0.02]), and increased ADHD symptoms (e.g. hyperactivity PCB molar sum ß = 2.35; 95%CI [0.17, 4.53]), supporting the possibility that prenatal exposure to POPs is a modifiable risk for ADHD phenotypes. DISCUSSION: We showed that exposure to POPs is related to task-based changes in neural activity in brain regions important for inhibitory control, suggesting a biological mechanism underlying previously documented associations between POPs and neurobehavioral deficits found in ADHD phenotypes.

The regional effect of serum hormone levels on cerebral blood flow in healthy nonpregnant women.

Sex hormones estrogen (EST) and progesterone (PROG) have received increased attention for their important physiological action outside of reproduction. While studies have shown that EST and PROG have significant impacts on brain function, their impact on the cerebrovascular system in humans remains largely unknown. To address this, we used a multi-modal magnetic resonance imaging (MRI) approach to investigate the link between serum hormones in the follicular phase and luteal phase of the menstrual cycle (MC) with measures of cerebrovascular function (cerebral blood flow [CBF]) and structure (intracranial artery diameter). Fourteen naturally cycling women were recruited and assessed at two-time points of their MC. CBF was derived from pseudo-continuous arterial spin labeling while diameters of the internal carotid and basilar artery was assessed using time of flight magnetic resonance angiography, blood samples were performed after the MRI. Results show that PROG and EST had opposing and spatially distinct effects on CBF: PROG correlated negatively with CBF in anterior brain regions (r = -.86, p < .01), while EST correlations were positive, yet weak and most prominent in posterior areas (r = .78, p < .01). No significant correlations between either hormone or intracranial artery diameter were observed. These results show that EST and PROG have opposing and regionally distinct effects on CBF and that this relationship is likely not due to interactions with large intracranial arteries. Considering that CBF in healthy women appears tightly linked to their current hormonal state, future studies should consider assessing MC-related hormone fluctuations in the design of functional MRI studies in this population.

Luring the Motor System: Impact of Performance-Contingent Incentives on Pre-Movement Beta-Band Activity and Motor Performance.

It has been shown that when incentives are provided during movement preparation, activity in parieto-frontal regions reflects both expected value and motivational salience. Yet behavioral work suggests that the processing of rewards is faster than for punishments, raising the possibility that expected value and motivational salience manifest at different latencies during movement planning. Given the role of beta oscillations (13-30 Hz) in movement preparation and in communication within the reward circuit, this study investigated how beta activity is modulated by positive and negative monetary incentives during reach planning, and in particular whether it reflects expected value and motivational salience at different latencies. Electroencephalography was recorded while male and female humans performed a reaching task in which reward or punishment delivery depended on movement accuracy. Before a preparatory delay period, participants were informed of the consequences of hitting or missing the target, according to four experimental conditions: Neutral (hit/miss:+0/-0¢), Reward (hit/miss:+5/-0¢), Punish (hit/miss:+0/-5¢) and Mixed (hit/miss:+5/-5¢). Results revealed that beta power over parieto-frontal regions was strongly modulated by incentives during the delay period, with power positively correlating with movement times. Interestingly, beta power was selectively sensitive to potential rewards early in the delay period, after which it came to reflect motivational salience as movement onset neared. These results demonstrate that beta activity reflects expected value and motivational salience on different time scales during reach planning. They also provide support for models that link beta activity with basal ganglia and dopamine for the allocation of neural resources according to behavioral salience.SIGNIFICANCE STATEMENT The present work demonstrates that pre-movement parieto-frontal beta power is modulated by monetary incentives in a goal-directed reaching task. Specifically, beta power transiently scaled with the availability of rewards early in movement planning, before reflecting motivational salience as movement onset neared. Moreover, pre-movement beta activity correlated with the vigor of the upcoming movement. These findings suggest that beta oscillations reflect neural processes that mediate the invigorating effect of incentives on motor performance, possibly through dopamine-mediated interactions with the basal ganglia.

Perturbing the activity of the superior temporal gyrus during pain encoding prevents the exaggeration of pain memories: A virtual lesion study using single-pulse transcranial magnetic stimulation.

BACKGROUND: Past studies have shown that pain memories are often inaccurate, a phenomenon known as mnemonic pain bias. Pain memories are thought to play an important role on how future pain is felt. Recent evidence from our laboratory suggests that individuals who exaggerate past pain display increased superior temporal gyrus (STG) activity during the encoding of experimental painful stimulations, suggesting that this brain structure plays an important role in pain memories. OBJECTIVE: /hypothesis. To determine whether a virtual lesion paradigm, targeting the STG during pain encoding, can affect long-lasting pain memories. We hypothesized that interfering with the activity of the STG would attenuate mnemonic bias. METHODS: Randomized double-blind study with two parallel groups. Participants received either sham (n = 21) or real (n = 21) transcranial magnetic stimulation (TMS - virtual lesion paradigm) over the STG during pain encoding (milliseconds after the administration of a painful stimuli). Pain intensity and unpleasantness were evaluated using a visual analog scale (VAS; 0 to 10) immediately after the painful event, and at recall, 2 months later. The mnemonic pain bias (calculated by subtracting the pain scores obtained at recall from the pain score obtained during encoding) was compared between the two groups for both pain intensity and unpleasantness. RESULTS: Participants in both groups did not differ in terms of age and gender (real TMS = 27 years ±â€¯9, 43% female; sham TMS = 25 years ±â€¯4, 49% female; p > 0.64). The mnemonic bias related to pain intensity was similar in both groups (p = 0.83). However, the mnemonic bias related to pain unpleasantness was lower in the real TMS group (p = 0.04). CONCLUSIONS: Our results provide the first evidence that the STG, is causally involved in the formation of biased memories of pain unpleasantness.

Cortical distance, not cancellation, dominates inter-subject EEG gamma rhythm amplitude.

The neurophysiological response to visual stimulation in both humans and animals is characterized by an increase in high frequency amplitude peaking in the gamma range (40-100Hz) and a suppression of low frequency amplitude peaking in the alpha range (10-16Hz). Due to the large number of studies linking amplitude and peak frequency to perception and neurological disorders, there is great interest in understanding the basis of inter-subject variability in gamma and alpha responses. To address this, we measured gamma and alpha amplitude and peak frequency of response to visual stimulation in 42 healthy humans. Using FMRI to delineate active cortical tissue in the same subjects, we correlated these neurophysiological metrics with two structural metrics: distance from active cortex to electrode, and dipole cancellation over active cortex. We find that distance strongly predicted inter-subject gamma amplitude, but had little effect on alpha amplitude, while cancellation had little effect on gamma or alpha amplitude. Neither alpha peak frequency nor gamma peak frequency correlated with our structural metrics. These results suggest that inter-subject variability in gamma amplitude may reflect gross morphology rather than neurophysiological variability, and should be interpreted with caution, while peak frequency may serve as a more sensitive metric of differences in neuronal activity across subjects.

White matter information flow mapping from diffusion MRI and EEG.

The human brain can be described as a network of specialized and spatially distributed regions. The activity of individual regions can be estimated using electroencephalography and the structure of the network can be measured using diffusion magnetic resonance imaging. However, the communication between the different cortical regions occurring through the white matter, coined information flow, cannot be observed by either modalities independently. Here, we present a new method to infer information flow in the white matter of the brain from joint diffusion MRI and EEG measurements. This is made possible by the millisecond resolution of EEG which makes the transfer of information from one region to another observable. A subject specific Bayesian network is built which captures the possible interactions between brain regions at different times. This network encodes the connections between brain regions detected using diffusion MRI tractography derived white matter bundles and their associated delays. By injecting the EEG measurements as evidence into this model, we are able to estimate the directed dynamical functional connectivity whose delays are supported by the diffusion MRI derived structural connectivity. We present our results in the form of information flow diagrams that trace transient communication between cortical regions over a functional data window. The performance of our algorithm under different noise levels is assessed using receiver operating characteristic curves on simulated data. In addition, using the well-characterized visual motor network as grounds to test our model, we present the information flow obtained during a reaching task following left or right visual stimuli. These promising results present the transfer of information from the eyes to the primary motor cortex. The information flow obtained using our technique can also be projected back to the anatomy and animated to produce videos of the information path through the white matter, opening a new window into multi-modal dynamic brain connectivity.

Delta-Band Oscillations in Motor Regions Predict Hand Selection for Reaching.

Current models hold that action selection is achieved by competitive interactions between co-existing motor representations associated with each potential action. Critically, selection via competition requires biasing signals to enable one of these alternatives to be selected. This study tested the hypothesis that selection is related to the prestimulus excitability of neuronal ensembles in which movements are encoded, as assessed through the phase of delta-band oscillations (2-4 Hz). Electroencephalography was recorded while participants performed speeded reaches toward appearing visual targets using the hand of their choice. The target locations were controlled such that only targets for which the left and right hands were selected equally often were used for analysis. Results revealed that hand selection as well as reach reaction times strongly depended upon the instantaneous phase of delta at the moment of target onset. This effect was maximal over contralateral motor regions, and occurred in the absence of prestimulus alpha- (8-12 Hz) and beta-band (15-30 Hz) amplitude modulations. These findings demonstrate that the excitability of motor regions acts as a modulatory factor for hand choice during reaching. They extend current models by showing that action selection is related to the underlying brain state independently of previously known decision variables.

A ketogenic drink improves brain energy and some measures of cognition in mild cognitive impairment.

INTRODUCTION: Unlike for glucose, uptake of the brain's main alternative fuel, ketones, remains normal in mild cognitive impairment (MCI). Ketogenic medium chain triglycerides (kMCTs) could improve cognition in MCI by providing the brain with more fuel. METHODS: Fifty-two subjects with MCI were blindly randomized to 30 g/day of kMCT or matching placebo. Brain ketone and glucose metabolism (quantified by positron emission tomography; primary outcome) and cognitive performance (secondary outcome) were assessed at baseline and 6 months later. RESULTS: Brain ketone metabolism increased by 230% for subjects on the kMCT (P < .001) whereas brain glucose uptake remained unchanged. Measures of episodic memory, language, executive function, and processing speed improved on the kMCT versus baseline. Increased brain ketone uptake was positively related to several cognitive measures. Seventy-five percent of participants completed the intervention. DISCUSSION: A dose of 30 g/day of kMCT taken for 6 months bypasses a significant part of the brain glucose deficit and improves several cognitive outcomes in MCI.

Decorrelated Input Dissociates Narrow Band γ Power and BOLD in Human Visual Cortex.

Although fMRI using the BOLD contrast is widely used for noninvasively mapping hemodynamic brain activity in humans, its exact link to underlying neural processing is poorly understood. Whereas some studies have reported that BOLD signals measured in visual cortex are tightly linked to neural activity in the narrow band γ (NBG) range, others have found a weak correlation between the two. To elucidate the mechanisms behind these conflicting findings, we hypothesized that BOLD reflects the strength of synaptic inputs to cortex, whereas NBG is more dependent on how well these inputs are correlated. To test this, we measured NBG, BOLD, and cerebral blood flow responses to stimuli that either correlate or decorrelate neural activity in human visual cortex. Next, we simulated a recurrent network model of excitatory and inhibitory neurons that reproduced in detail the experimental NBG and BOLD data. Results show that the visually evoked BOLD response was solely predicted by the sum of local inputs, whereas NBG was critically dependent on how well these inputs were correlated. In summary, the NBG-BOLD relationship strongly depends on the nature of sensory input to cortex: stimuli that increase the number of correlated inputs to visual cortex will increase NBG and BOLD in a similar manner, whereas stimuli that increase the number of decorrelated inputs will dissociate the two. The NBG-BOLD relationship is therefore not fixed but is rather highly dependent on input correlations that are both stimulus- and state-dependent.SIGNIFICANCE STATEMENT It is widely believed that γ oscillations in cortex are tightly linked to local hemodynamic activity. Here, we present experimental evidence showing how a stimulus can increase local blood flow to the brain despite suppressing γ power. Moreover, using a sophisticated model of cortical neurons, it is proposed that this occurs when synaptic input to cortex is strong yet decorrelated. Because input correlations are largely determined by the state of the brain, our results demonstrate that the relationship between γ and local hemodynamics is not fixed, but rather context dependent. This likely explains why certain neurodevelopmental disorders are characterized by weak γ activity despite showing normal blood flow.

Added value of money on motor performance feedback: Increased left central beta-band power for rewards and fronto-central theta-band power for punishments.

Monetary rewards and punishments have been shown to respectively enhance retention of motor memories and short-term motor performance, but their underlying neural bases in the context of motor control tasks remain unclear. Using electroencephalography (EEG), the present study tested the hypothesis that monetary rewards and punishments are respectively reflected in post-feedback beta-band (20-30 Hz) and theta-band (3-8 Hz) oscillatory power. While participants performed upper limb reaching movements toward visual targets using their right hand, the delivery of monetary rewards and punishments was manipulated as well as their probability (i.e., by changing target size). Compared to unrewarded and unpunished trials, monetary rewards and the successful avoidance of punishments both entailed greater beta-band power at left central electrodes overlaying contralateral motor areas. In contrast, monetary punishments and reward omissions both entailed increased theta-band power at fronto-central scalp sites. Additional analyses revealed that beta-band power was further increased when rewards were lowly probable. In light of previous work demonstrating similar beta-band modulations in basal ganglia during reward processing, the present results may reflect functional communication of reward-related information between the basal ganglia and motor cortical regions. In turn, the increase in fronto-central theta-band power after monetary punishments may reflect an emphasized cognitive need for behavioral adjustments. Globally, the present work identifies possible neural substrates for the growing behavioral evidence showing beneficial effects of monetary feedback on motor learning and performance.

The morphology of the human cerebrovascular system.

While several methodologies exist for quantifying gray and white matter properties in humans, relatively little is known regarding the spatial organization and the intersubject variability of cerebral vessels. To resolve this, we developed a fast, open-source processing algorithm using advanced vessel segmentation schemes and iterative nonlinear registration to isolate, extract, and quantify cerebral vessels in susceptibility weighting imaging (SWI) and time-of-flight angiography (TOF-MRA) datasets acquired in a large cohort (n = 42) of healthy individuals. From this, whole-brain venous and arterial probabilistic maps were generated along with the computation of regional densities and diameters within regions based on popular anatomical and functional atlases. The results show that cerebral vasculature is highly heterogeneous, displaying disproportionally large vessel densities in brain areas such as the anterior and posterior cingulate, cuneus, precuneus, parahippocampus, insula, and temporal gyri. On average, venous densities were slightly higher and less variable across subjects than arterial. Moreover, regional variations in both venous and arterial density were significantly correlated to cortical thickness (R = 0.42). This publicly available new atlas of the human cerebrovascular system provides a first step toward quantifying morphological changes in the diseased brain and serving as a potential regression tool in fMRI analysis.

Diffusion MRI monitoring of specific structures in the irradiated rat brain.

PURPOSE: The analysis of biological and mesoscopic structures properties by diffusion MRI (dMRI) in brain after radiation therapy remains challenging. In our study, we described the consequences associated with an unwanted dose to healthy tissue, assessing radiation-induced brain alterations of living rats with dMRI compared to histopathology and behavioral assays. METHODS: The right primary motor cortex M1 of the rat brain was targeted by stereotactic radiosurgery with a mean radiation dose of 41 Gy. Multidirectional single b-value dMRI data of the whole brain were acquired with a 7T small-animal scanner before irradiation until 110 days post-irradiation. Diffusion tensor imaging metrics, such as fractional anisotropy (FA), mean diffusivity (MD), axial (AD), and radial diffusivity (RD) were compared to brain alterations detected by immunohistochemistry and motor performances measured by a behavioral test. RESULTS: Between days 90 and 110, radiation necrosis was observed into the white matter spreading into M1 . Results showed a reduction of FA in the corpus callosum and in the striatum, which was driven by an increase in RD from 90 to 110 days post-irradiation, whereas only RD increased in M1 . Values of RD and AD increased in the irradiated hippocampus, while FA remained constant. Moreover, an increased MD, AD and RD was observed in the hippocampus that was probably related to inflammation as well as reactive astrogliosis after 110 days post-irradiation. Finally, rats did not exhibit locomotor deficits. CONCLUSIONS: dMRI metrics can assess brain damage; the sensitivity of dMRI metrics depends on the brain region.

Spatial distribution of resting-state BOLD regional homogeneity as a predictor of brain glucose uptake: A study in healthy aging.

Positron emission tomography using [18F]-fluorodeoxyglucose (PET-FDG) is the primary imaging modality used to measure glucose metabolism in the brain (CMRGlu). CMRGlu has been used as a biomarker of brain aging and neurodegenerative diseases, but the complexity and invasive nature of PET often limits its use in research. There is therefore great interest in developing non-invasive metrics for estimating brain CMRGlu. We therefore investigated resting state fMRI metrics such as regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF) and regional global connectivity (Closeness) with multiple analytical approaches to determine their relationship to CMRGlu. We investigated this relation in two distinct cognitively healthy populations separated by age (27 young adults and 35 older adults). Overall, we found that both regionally and across participants, ReHo strongly correlated with CMRGlu in healthy young and older adults. Moreover, ReHo demonstrated the same age-related differences as CMRGlu throughout all cortical regions, particularly in the default network and frontal areas.

Active delineation of Meyer's loop using oriented priors through MAGNEtic tractography (MAGNET).

Streamline tractography algorithms infer connectivity from diffusion MRI (dMRI) by following diffusion directions which are similarly aligned between neighboring voxels. However, not all white matter (WM) fascicles are organized in this manner. For example, Meyer's loop is a highly curved portion of the optic radiation (OR) that exhibits a narrow turn, kissing and crossing pathways, and changes in fascicle dispersion. From a neurosurgical perspective, damage to Meyer's loop carries a potential risk of inducing vision deficits to the patient, especially during temporal lobe resection surgery. To prevent such impairment, achieving an accurate delineation of Meyer's loop with tractography is thus of utmost importance. However, current algorithms tend to under-estimate the full extent of Meyer's loop, mainly attributed to the aforementioned rule for connectivity which requires a direction to be chosen across a field of orientations. In this article, it was demonstrated that MAGNEtic Tractography (MAGNET) can benefit Meyer's loop delineation by incorporating anatomical knowledge of the expected fiber orientation to overcome local ambiguities. A new ROI-mechanism was proposed which supplies additional information to streamline reconstruction algorithms by the means of oriented priors. Their results showed that MAGNET can accurately generate Meyer's loop in all of our 15 child subjects (8 males; mean age 10.2 years ± 3.1). It effectively improved streamline coverage when compared with deterministic tractography, and significantly reduced the distance between the anterior-most portion of Meyer's loop and the temporal pole by 16.7 mm on average, a crucial landmark used for preoperative planning of temporal lobe surgery. Hum Brain Mapp 38:509-527, 2017. © 2016 Wiley Periodicals, Inc.

AxTract: Toward microstructure informed tractography.

Diffusion-weighted (DW) magnetic resonance imaging (MRI) tractography has become the tool of choice to probe the human brain's white matter in vivo. However, tractography algorithms produce a large number of erroneous streamlines (false positives), largely due to complex ambiguous tissue configurations. Moreover, the relationship between the resulting streamlines and the underlying white matter microstructure characteristics remains poorly understood. In this work, we introduce a new approach to simultaneously reconstruct white matter fascicles and characterize the apparent distribution of axon diameters within fascicles. To achieve this, our method, AxTract, takes full advantage of the recent development DW-MRI microstructure acquisition, modeling, and reconstruction techniques. This enables AxTract to separate parallel fascicles with different microstructure characteristics, hence reducing ambiguities in areas of complex tissue configuration. We report a decrease in the incidence of erroneous streamlines compared to the conventional deterministic tractography algorithms on simulated data. We also report an average increase in streamline density over 15 known fascicles of the 34 healthy subjects. Our results suggest that microstructure information improves tractography in crossing areas of the white matter. Moreover, AxTract provides additional microstructure information along the fascicle that can be studied alongside other streamline-based indices. Overall, AxTract provides the means to distinguish and follow white matter fascicles using their microstructure characteristics, bringing new insights into the white matter organization. This is a step forward in microstructure informed tractography, paving the way to a new generation of algorithms able to deal with intricate configurations of white matter fibers and providing quantitative brain connectivity analysis. Hum Brain Mapp 38:5485-5500, 2017. © 2017 Wiley Periodicals, Inc.

Understanding the continuum of radionecrosis and vascular disorders in the brain following gamma knife irradiation: An MRI study.

PURPOSE: The radiation dose delivered to brain tumors is limited by the possibility to induce vascular damage and necrosis in surrounding healthy tissue. In the present study, we assessed the ability of MRI to monitor the cascade of events occurring in the healthy rat brain after stereotactic radiosurgery, which could be used to optimize the radiation treatment planning. METHODS: The primary somatosensory forelimb area (S1FL) and the primary motor cortex in the right hemisphere of Fischer rats (n = 6) were irradiated with a single dose of Gamma Knife radiation (Leksell Perfexion, Elekta AG, Stockholm, Sweden). Rats were scanned with a small-animal 7 Tesla MRI scanner before treatment and 16, 21, 54, 82, and 110 days following irradiation. At every imaging session, T2 -weighted (T2 w), Gd-DTPA dynamic contrast-enhanced MRI (DCE-MRI), and T2*-weighted ( T2* w) images were acquired to measure changes in fluid content, blood vessel permeability, and structure, respectively. At days 10, 110, and 140, histopathology was performed on brain sections. Locomotion and spatial memory ability were assessed longitudinally by behavioral tests. RESULTS: No vascular changes were initially observed. After 54 days, a small necrotic volume in the white matter below the S1FL, surrounded by an area presenting significant vascular permeability, was revealed. Between 54 and 110 days, the necrotic volume increased and was accompanied by the formation of a ring-like region, where a mixture of necrosis and permeable blood vessels were observed, as confirmed by histology. Behavioral changes were only observed after day 82. CONCLUSION: Together, DCE-MRI and T2* w images supported by histology provided a coherent picture of the phenomena involved in the formation of new, leaky blood vessels, which was followed by the detection of radionecrosis in a preclinical model of brain irradiation. Magn Reson Med 78:1420-1431, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Stimulus statistics shape oscillations in nonlinear recurrent neural networks.

Rhythmic activity plays a central role in neural computations and brain functions ranging from homeostasis to attention, as well as in neurological and neuropsychiatric disorders. Despite this pervasiveness, little is known about the mechanisms whereby the frequency and power of oscillatory activity are modulated, and how they reflect the inputs received by neurons. Numerous studies have reported input-dependent fluctuations in peak frequency and power (as well as couplings across these features). However, it remains unresolved what mediates these spectral shifts among neural populations. Extending previous findings regarding stochastic nonlinear systems and experimental observations, we provide analytical insights regarding oscillatory responses of neural populations to stimulation from either endogenous or exogenous origins. Using a deceptively simple yet sparse and randomly connected network of neurons, we show how spiking inputs can reliably modulate the peak frequency and power expressed by synchronous neural populations without any changes in circuitry. Our results reveal that a generic, non-nonlinear and input-induced mechanism can robustly mediate these spectral fluctuations, and thus provide a framework in which inputs to the neurons bidirectionally regulate both the frequency and power expressed by synchronous populations. Theoretical and computational analysis of the ensuing spectral fluctuations was found to reflect the underlying dynamics of the input stimuli driving the neurons. Our results provide insights regarding a generic mechanism supporting spectral transitions observed across cortical networks and spanning multiple frequency bands.

Attenuation of visual reafferent signals in the parietal cortex during voluntary movement.

It is well established that the cortical processing of somatosensory and auditory signals is attenuated when they result from self-generated actions compared with external events. This phenomenon is thought to result from an efference copy of motor commands used to predict the sensory consequences of an action through a forward model. The present work examined whether attenuation also takes place for visual reafferent signals from the moving limb during voluntary reaching movements. To address this issue, EEG activity was recorded in a condition in which visual feedback of the hand was provided in real time and compared with a condition in which it was presented with a 150-ms delay, thus creating a mismatch between the predicted and actual visual consequences of the movement. Results revealed that the amplitude of the N1 component of the visual event-related potential evoked by hand visual feedback over the parietal cortex was significantly smaller when presented in real time compared with when it was delayed. These data suggest that the cortical processing of visual reafferent signals is attenuated when they are correctly predicted, likely as a result of a forward model.

Effects of neural synchrony on surface EEG.

It has long been assumed that the surface electroencephalography (EEG) signal depends on both the amplitude and spatial synchronization of underlying neural activity, though isolating their respective contribution remains elusive. To address this, we made simultaneous surface EEG measurements along with intracortical recordings of local field potentials (LFPs) in the primary visual cortex of behaving nonhuman primates. We found that trial-by-trial fluctuations in EEG power could be explained by a linear combination of LFP power and interelectrode temporal synchrony. This effect was observed in both stimulus and stimulus-free conditions and was particularly strong in the gamma range (30-100 Hz). Subsequently, we used pharmacological manipulations to show that neural synchrony can produce a positively modulated EEG signal even when the LFP signal is negatively modulated. Taken together, our results demonstrate that neural synchrony can modulate EEG signals independently of amplitude changes in neural activity. This finding has strong implications for the interpretation of EEG in basic and clinical research, and helps reconcile EEG response discrepancies observed in different modalities (e.g., EEG vs. functional magnetic resonance imaging) and different spatial scales (e.g., EEG vs. intracranial EEG).