Principles of magnetic resonance assessment of brain function

Non-Cartesian 3D-SPARKLING vs Cartesian 3D-EPI encoding schemes for functional Magnetic Resonance Imaging at 7 Tesla

The quest for higher spatial and/or temporal resolution in functional MRI (fMRI) while preserving a sufficient temporal signal-to-noise ratio (tSNR) has generated a tremendous amount of methodological contributions in the last decade ranging from Cartesian vs. non-Cartesian readouts, 2D vs. 3D acquisition strategies, parallel imaging and/or compressed sensing (CS) accelerations and simultaneous multi-slice acquisitions to cite a few. In this paper, we investigate the use of a finely tuned version of 3D-SPARKLING. This is a non-Cartesian CS-based acquisition technique for high spatial resolution whole-brain fMRI. We compare it to state-of-the-art Cartesian 3D-EPI during both a retinotopic mapping paradigm and resting-state acquisitions at 1mm3 (isotropic spatial resolution). This study involves six healthy volunteers and both acquisition sequences were run on each individual in a randomly-balanced order across subjects. The performances of both acquisition techniques are compared to each other in regards to tSNR, sensitivity to the BOLD effect and spatial specificity. Our findings reveal that 3D-SPARKLING has a higher tSNR than 3D-EPI, an improved sensitivity to detect the BOLD contrast in the gray matter, and an improved spatial specificity. Compared to 3D-EPI, 3D-SPARKLING yields, on average, 7% more activated voxels in the gray matter relative to the total number of activated voxels.

High-temporal resolution functional PET/MRI reveals coupling between human metabolic and hemodynamic brain response

PURPOSE

Positron emission tomography (PET) provides precise molecular information on physiological processes, but its low temporal resolution is a major obstacle. Consequently, we characterized the metabolic response of the human brain to working memory performance using an optimized functional PET (fPET) framework at a temporal resolution of 3 s.

METHODS

Thirty-five healthy volunteers underwent fPET with [18F]FDG bolus plus constant infusion, 19 of those at a hybrid PET/MRI scanner. During the scan, an n-back working memory paradigm was completed. fPET data were reconstructed to 3 s temporal resolution and processed with a novel sliding window filter to increase signal to noise ratio. BOLD fMRI signals were acquired at 2 s.

RESULTS

Consistent with simulated kinetic modeling, we observed a constant increase in the [18F]FDG signal during task execution, followed by a rapid return to baseline after stimulation ceased. These task-specific changes were robustly observed in brain regions involved in working memory processing. The simultaneous acquisition of BOLD fMRI revealed that the temporal coupling between hemodynamic and metabolic signals in the primary motor cortex was related to individual behavioral performance during working memory. Furthermore, task-induced BOLD deactivations in the posteromedial default mode network were accompanied by distinct temporal patterns in glucose metabolism, which were dependent on the metabolic demands of the corresponding task-positive networks.

CONCLUSIONS

In sum, the proposed approach enables the advancement from parallel to truly synchronized investigation of metabolic and hemodynamic responses during cognitive processing. This allows to capture unique information in the temporal domain, which is not accessible to conventional PET imaging.

Functional FDG-PET: Measurement of Task Related Neural Activity in Humans-A Compartment Model Approach and Comparison to fMRI

Neuroimaging holds an essential position in global healthcare, as brain-related disorders are a substantial and growing burden. Non-degenerative disorders such as stress, depression and anxiety share common function related traits of diffuse and fluctuating changes, such as change in brain-based functions of mood, behavior and cognitive abilities, where underlying physiological mechanism remain unresolved. In this study we developed a novel application for studying intra-subject task-activated brain function by the quantitative physiological measurement of the change in glucose metabolism in a single scan setup. Data were acquired on a PET/MR-scanner. We implemented a functional [18F]-FDG PET-scan with double boli-tracer administration and finger-tapping activation, as proof-of-concept, in five healthy participants. The [18F]-FDG data were analyzed using a two-tissue compartment double boli kinetic model with an image-derived input function. For stand-alone visual reference, blood oxygenation level dependent (BOLD) functional MRI (fMRI) was acquired in the same session and analyzed separately. We were able to measure the cerebral glucose metabolic rate during baseline as well as activation. Results showed increased glucose metabolic rate during activation by 36.3-87.9% mean 62.0%, locally in the peak seed region of M1 in the brain, on an intra-subject level, as well as very good spatial accuracy on group level, and localization compared to the BOLD fMRI result at subject and group level. Our novel method successfully determined the relative increase in the cerebral metabolic rate of glucose on a voxel level with good visual association to fMRI at the subject-level, holding promise for future individual clinical application. This approach will be easily adapted in future clinical perspectives and pharmacological interventions studies.

Improved Resting-State Functional MRI Using Multi-Echo Echo-Planar Imaging on a Compact 3T MRI Scanner with High-Performance Gradients

In blood-oxygen-level-dependent (BOLD)-based resting-state functional (RS-fMRI) studies, usage of multi-echo echo-planar-imaging (ME-EPI) is limited due to unacceptable late echo times when high spatial resolution is used. Equipped with high-performance gradients, the compact 3T MRI system (C3T) enables a three-echo whole-brain ME-EPI protocol with smaller than 2.5 mm isotropic voxel and shorter than 1 s repetition time, as required in landmark fMRI studies. The performance of the ME-EPI was comprehensively evaluated with signal variance reduction and region-of-interest-, seed- and independent-component-analysis-based functional connectivity analyses and compared with a counterpart of single-echo EPI with the shortest TR possible. Through the multi-echo combination, the thermal noise level is reduced. Functional connectivity, as well as signal intensity, are recovered in the medial orbital sulcus and anterior transverse collateral sulcus in ME-EPI. It is demonstrated that ME-EPI provides superior sensitivity and accuracy for detecting functional connectivity and/or brain networks in comparison with single-echo EPI. In conclusion, the high-performance gradient enabled high-spatial-temporal resolution ME-EPI would be the method of choice for RS-fMRI study on the C3T.

Combining arterial blood contrast with BOLD increases fMRI intracortical contrast

BOLD fMRI is widely applied in human neuroscience but is limited in its spatial specificity due to a cortical-depth-dependent venous bias. This reduces its localization specificity with respect to neuronal responses, a disadvantage for neuroscientific research. Here, we modified a submillimeter BOLD protocol to selectively reduce venous and tissue signal and increase cerebral blood volume weighting through a pulsed saturation scheme (dubbed Arterial Blood Contrast) at 7 T. Adding Arterial Blood Contrast on top of the existing BOLD contrast modulated the intracortical contrast. Isolating the Arterial Blood Contrast showed a response free of pial-surface bias. The results suggest that Arterial Blood Contrast can modulate the typical fMRI spatial specificity, with important applications in in-vivo neuroscience.

Functional Segregation within the Dorsal Frontoparietal Network: A Multimodal Dynamic Causal Modeling Study

Discrimination and integration of motion direction requires the interplay of multiple brain areas. Theoretical accounts of perception suggest that stimulus-related (i.e., exogenous) and decision-related (i.e., endogenous) factors affect distributed neuronal processing at different levels of the visual hierarchy. To test these predictions, we measured brain activity of healthy participants during a motion discrimination task, using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). We independently modeled the impact of exogenous factors (task demand) and endogenous factors (perceptual decision-making) on the activity of the motion discrimination network and applied Dynamic Causal Modeling (DCM) to both modalities. DCM for event-related potentials (DCM-ERP) revealed that task demand impacted the reciprocal connections between the primary visual cortex (V1) and medial temporal areas (V5). With practice, higher visual areas were increasingly involved, as revealed by DCM-fMRI. Perceptual decision-making modulated higher levels (e.g., V5-to-Frontal Eye Fields, FEF), in a manner predictive of performance. Our data suggest that lower levels of the visual network support early, feature-based selection of responses, especially when learning strategies have not been implemented. In contrast, perceptual decision-making operates at higher levels of the visual hierarchy by integrating sensory information with the internal state of the subject.

Functional dynamics of dopamine synthesis during monetary reward and punishment processing

The assessment of dopamine release with the PET competition model is thoroughly validated but entails disadvantages for the investigation of cognitive processes. We introduce a novel approach incorporating 6-[¹⁸F]FDOPA uptake as index of the dynamic regulation of dopamine synthesis enzymes by neuronal firing. The feasibility of this approach is demonstrated by assessing widely described sex differences in dopamine neurotransmission. Reward processing was behaviorally investigated in 36 healthy participants, of whom 16 completed fPET and fMRI during the monetary incentive delay task. A single 50 min fPET acquisition with 6-[¹⁸F]FDOPA served to quantify task-specific changes in dopamine synthesis. In men monetary gain induced stronger increases in ventral striatum dopamine synthesis than loss. Interestingly, the opposite effect was discovered in women. These changes were further associated with reward (men) and punishment sensitivity (women). As expected, fMRI showed robust task-specific neuronal activation but no sex difference. Our findings provide a neurobiological basis for known behavioral sex differences in reward and punishment processing, with important implications in psychiatric disorders showing sex-specific prevalence, altered reward processing and dopamine signaling. The high temporal resolution and magnitude of task-specific changes make fPET a promising tool to investigate functional neurotransmitter dynamics during cognitive processing and in brain disorders.

Origins of Dissociations in the English Past Tense: A Synthetic Brain Imaging Model

Brain imaging studies of English past tense inflection have found dissociations between regular and irregular verbs, but no coherent picture has emerged to explain how these dissociations arise. Here we use synthetic brain imaging on a neural network model to provide a mechanistic account of the origins of such dissociations. The model suggests that dissociations between regional activation patterns in verb inflection emerge in an adult processing system that has been shaped through experience-dependent structural brain development. Although these dissociations appear to be between regular and irregular verbs, they arise in the model from a combination of statistical properties including frequency, relationships to other verbs, and phonological complexity, without a causal role for regularity or semantics. These results are consistent with the notion that all inflections are produced in a single associative mechanism. The model generates predictions about the patterning of active brain regions for different verbs that can be tested in future imaging studies.

Laminar fMRI using T2-prepared multi-echo FLASH

Functional magnetic resonance imaging (fMRI) using blood oxygenation level dependent (BOLD) contrast at a sub-millimeter scale is a promising technique to probe neural activity at the level of cortical layers. While gradient echo (GRE) BOLD sequences exhibit the highest sensitivity, their signal is confounded by unspecific extravascular (EV) and intravascular (IV) effects of large intracortical ascending veins and pial veins leading to a downstream blurring effect of local signal changes. In contrast, spin echo (SE) fMRI promises higher specificity towards signal changes near the microvascular compartment. However, the T₂-weighted signal is typically sampled with a gradient echo readout imposing additional T₂'-weighting. In this work, we used a T₂-prepared (T₂-prep) sequence with short GRE readouts to investigate its capability to acquire laminar fMRI data during a visual task in humans at 7 T. By varying the T₂-prep echo time (TE_prep) and acquiring multiple gradient echoes (TE_GRE) per excitation, we studied the specificity of the sequence and the influence of possible confounding contributions to the shape of laminar fMRI profiles. By fitting and extrapolating the multi-echo GRE data to a TE_GRE = 0 ms condition, we show for the first time laminar profiles free of T₂'-pollution, confined to gray matter. This finding is independent of TE_prep, except for the shortest one (31 ms) where hints of a remaining intravascular component can be seen. For TE_GRE > 0 ms a prominent peak at the pial surface is observed that increases with longer TE_GRE and dominates the shape of the profiles independent of the amount of T₂-weighting. Simulations show that the peak at the pial surface is a result of static EV dephasing around pial vessels in CSF visible in GM due to partial voluming. Additionally, another, weaker, static dephasing effect is observed throughout all layers of the cortex, which is particularly obvious in the data with shortest T₂-prep echo time. Our simulations show that this cannot be explained by intravascular dephasing but that it is likely caused by extravascular effects of the intracortical and pial veins. We conclude that even for TE_GRE as short as 2.3 ms, the T₂'-weighting added to the T₂-weighting is enough to dramatically affect the laminar specificity of the BOLD signal change. However, the bulk of this corruption stems from CSF partial volume effects which can in principle be addressed by increasing the spatial resolution of the acquisition.

New acquisition techniques and their prospects for the achievable resolution of fMRI

This work reviews recent advances in technologies for functional magnetic resonance imaging (fMRI) of the human brain and highlights the push for higher functional specificity based on increased spatial resolution and specific MR contrasts to reveal previously undetectable functional properties of small-scale cortical structures. We discuss how the combination of MR hardware, advanced acquisition techniques and various MR contrast mechanisms have enabled recent progress in functional neuroimaging. However, these advanced fMRI practices have only been applied to a handful of neuroscience questions to date, with the majority of the neuroscience community still using conventional imaging techniques. We thus discuss upcoming challenges and possibilities for fMRI technology development in human neuroscience. We hope that readers interested in functional brain imaging acquire an understanding of current and novel developments and potential future applications, even if they don't have a background in MR physics or engineering. We summarize the capabilities of standard fMRI acquisition schemes with pointers to relevant literature and comprehensive reviews and introduce more recent developments.

Accelerated spin-echo functional MRI using multisection excitation by simultaneous spin-echo interleaving (MESSI) with complex-encoded generalized slice dithered enhanced resolution (cgSlider) simultaneous multislice echo-planar imaging

PURPOSE

Spin-echo functional MRI (SE-fMRI) has the potential to improve spatial specificity when compared with gradient-echo fMRI. However, high spatiotemporal resolution SE-fMRI with large slice-coverage is challenging as SE-fMRI requires a long echo time to generate blood oxygenation level-dependent (BOLD) contrast, leading to long repetition times. The aim of this work is to develop an acquisition method that enhances the slice-coverage of SE-fMRI at high spatiotemporal resolution.

THEORY AND METHODS

An acquisition scheme was developed entitled multisection excitation by simultaneous spin-echo interleaving (MESSI) with complex-encoded generalized slice dithered enhanced resolution (cgSlider). MESSI uses the dead-time during the long echo time by interleaving the excitation and readout of 2 slices to enable 2× slice-acceleration, while cgSlider uses the stable temporal background phase in SE-fMRI to encode/decode 2 adjacent slices simultaneously with a "phase-constrained" reconstruction method. The proposed cgSlider-MESSI was also combined with simultaneous multislice (SMS) to achieve further slice-acceleration. This combined approach was used to achieve 1.5-mm isotropic whole-brain SE-fMRI with a temporal resolution of 1.5 s and was evaluated using sensory stimulation and breath-hold tasks at 3T.

RESULTS

Compared with conventional SE-SMS, cgSlider-MESSI-SMS provides 4-fold increase in slice-coverage for the same repetition time, with comparable temporal signal-to-noise ratio. Corresponding fMRI activation from cgSlider-MESSI-SMS for both fMRI tasks were consistent with those from conventional SE-SMS. Overall, cgSlider-MESSI-SMS achieved a 32× encoding-acceleration by combining Rinplane × MB × cgSlider × MESSI = 4 × 2 × 2 × 2.

CONCLUSION

High-quality, high-resolution whole-brain SE-fMRI was acquired at a short repetition time using cgSlider-MESSI-SMS. This method should be beneficial for high spatiotemporal resolution SE-fMRI studies requiring whole-brain coverage.

Adaptations in reward-related behaviors and mesolimbic dopamine function during motherhood and the postpartum period

Initiation and maintenance of maternal behavior is driven by a complex interaction between the physiology of parturition and offspring stimulation, causing functional changes in maternal brain and behavior. Maternal behaviors are among the most robust and rewarding motivated behaviors. Mesolimbic dopamine (DA) system alterations during pregnancy and the postpartum enable enhanced reward-related responses to offspring stimuli. Here, we review behavioral evidence demonstrating postpartum rodents exhibit a bias towards pups and pup-related stimuli in reward-related tasks. Next, we provide an overview of normative adaptations in the mesolimbic DA system induced by parturition and the postpartum, which likely mediate shifts in offspring valence. We also discuss a causal link between dopaminergic dysfunction and disrupted maternal behaviors, which are recapitulated in postpartum depression (PPD) and relevant rodent models. In sum, mesolimbic DA system activation drives infant-seeking behavior and strengthens the mother-infant bond, potentially representing a therapeutic target for reward-related deficits in PPD.

The Contribution of Functional Magnetic Resonance Imaging to the Understanding of the Effects of Acute Physical Exercise on Cognition

The fact that a single bout of acute physical exercise has a positive impact on cognition is well-established in the literature, but the neural correlates that underlie these cognitive improvements are not well understood. Here, the use of neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), offers great potential, which is just starting to be recognized. This review aims at providing an overview of those studies that used fMRI to investigate the effects of acute physical exercises on cerebral hemodynamics and cognition. To this end, a systematic literature survey was conducted by two independent reviewers across five electronic databases. The search returned 668 studies, of which 14 studies met the inclusion criteria and were analyzed in this systematic review. Although the findings of the reviewed studies suggest that acute physical exercise (e.g., cycling) leads to profound changes in functional brain activation, the small number of available studies and the great variability in the study protocols limits the conclusions that can be drawn with certainty. In order to overcome these limitations, new, more well-designed trials are needed that (i) use a more rigorous study design, (ii) apply more sophisticated filter methods in fMRI data analysis, (iii) describe the applied processing steps of fMRI data analysis in more detail, and (iv) provide a more precise exercise prescription.

Animal Functional Magnetic Resonance Imaging: Trends and Path Toward Standardization

Animal whole-brain functional magnetic resonance imaging (fMRI) provides a non-invasive window into brain activity. A collection of associated methods aims to replicate observations made in humans and to identify the mechanisms underlying the distributed neuronal activity in the healthy and disordered brain. Animal fMRI studies have developed rapidly over the past years, fueled by the development of resting-state fMRI connectivity and genetically encoded neuromodulatory tools. Yet, comparisons between sites remain hampered by lack of standardization. Recently, we highlighted that mouse resting-state functional connectivity converges across centers, although large discrepancies in sensitivity and specificity remained. Here, we explore past and present trends within the animal fMRI community and highlight critical aspects in study design, data acquisition, and post-processing operations, that may affect the results and influence the comparability between studies. We also suggest practices aimed to promote the adoption of standards within the community and improve between-lab reproducibility. The implementation of standardized animal neuroimaging protocols will facilitate animal population imaging efforts as well as meta-analysis and replication studies, the gold standards in evidence-based science.

Pros and cons of ultra-high-field MRI/MRS for human application

Magnetic resonance imaging and spectroscopic techniques are widely used in humans both for clinical diagnostic applications and in basic research areas such as cognitive neuroimaging. In recent years, new human MR systems have become available operating at static magnetic fields of 7 T or higher (≥300 MHz proton frequency). Imaging human-sized objects at such high frequencies presents several challenges including non-uniform radiofrequency fields, enhanced susceptibility artifacts, and higher radiofrequency energy deposition in the tissue. On the other side of the scale are gains in signal-to-noise or contrast-to-noise ratio that allow finer structures to be visualized and smaller physiological effects to be detected. This review presents an overview of some of the latest methodological developments in human ultra-high field MRI/MRS as well as associated clinical and scientific applications. Emphasis is given to techniques that particularly benefit from the changing physical characteristics at high magnetic fields, including susceptibility-weighted imaging and phase-contrast techniques, imaging with X-nuclei, MR spectroscopy, CEST imaging, as well as functional MRI. In addition, more general methodological developments such as parallel transmission and motion correction will be discussed that are required to leverage the full potential of higher magnetic fields, and an overview of relevant physiological considerations of human high magnetic field exposure is provided.

Artifacts in EEG of simultaneous EEG-fMRI: pulse artifact remainders in the gradient artifact template are a source of artifact residuals after average artifact subtraction

OBJECTIVE

The simultaneous application of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) opens up new ways to investigate the human brain. The EEG recordings of simultaneous EEG-fMRI, however, are overlaid to a great degree by fMRI related artifacts and an artifact reduction is mandatory before any EEG analysis. The most severe artifacts-the gradient artifact and the pulse artifact-are repetitive. Average artifact subtraction (AAS) technique exploits the repetitiveness and is presumably the most often used artifact reduction technique. In this method artifact templates are calculated by averaging over adjacent artifact epochs and subsequently the templates are subtracted to reduce the artifacts. Although the AAS technique is one of the best performing methods, artifact residuals are usually present in the resulting EEG after applying the AAS technique. This work aims at identifying sources of the artifact residuals.

APPROACH

Application of the AAS technique to artificial EEG that is contaminated with artificial fMRI related artifacts.

MAIN RESULTS

A new source of artifact residuals was identified. It was found that the AAS technique itself adds artifacts to the EEG during gradient artifact reduction, because the gradient artifact template is corrupted by pulse artifact remainders.

SIGNIFICANCE

This work shows that using a standard number of 25 epochs to calculate the gradient artifact template-as suggested by the inventors of AAS-results in substantial artifact residuals and consequently to a low EEG quality. Furthermore, the work discusses how potential solutions to this problem have serious side effects such as loss of adaptivity of the AAS technique. Hence, this problem must be considered carefully already in the design of simultaneous EEG-fMRI experiments.

Impaired cortical autonomic responses during sympathetic activation in neurogenic orthostatic hypotension characterized by postganglionic autonomic dysfunction

Neurogenic orthostatic hypotension (NOH) is a cardinal feature of autonomic dysfunction. The cortical autonomic network (CAN) is a network of brain regions associated with autonomic function. Therefore, our objective was to investigate whether impairment of CAN structures is involved in the pathophysiology of NOH. Fifteen controls (63 ± 13 yr) and 15 NOH patients (67 ± 6 yr; P = 0.2) with peripheral autonomic dysfunction completed standard tests of parasympathetic [deep breathing (DB)] and sympathetic [Valsalva maneuver (VM)] activation during a functional MRI. Blood-oxygen-level dependent (BOLD) contrasts were obtained and contrasted. Compared with controls, patients had significantly smaller heart rate responses to DB (control: 15.23 ± 9.6 vs. NOH: 5.7 ± 2.1) and Valsalva ratios (control: 2.1 ± 0.47 vs. NOH: 1.2 ± 0.1; P < 0.001). NOH patients had absent adrenergic phases (late phase II and phase IV) during VM as per a qualitative analysis. During VM, controls had greater activation in the right hippocampus (T-value: 8.03), left posterior cingulate (T_L: 7.6), and bilateral thalamus (T_R: 7.41, T_L: 8.45; P < 0.05). During phase IV, controls had greater activation in the right hippocampus (T_R: 5.78l P < 0.05). Following subtraction analysis, no significant differences were evident during DB. In conclusion, NOH patients have significantly less CAN activation during sympathetic, but not parasympathetic, activation. Impaired CANs associated with sympathetic activation may be involved in the pathophysiology of NOH. NEW & NOTEWORTHY Neurogenic orthostatic hypotension (NOH) is a cardinal feature of autonomic dysfunction characterized by failure of reflexive sympathetic activation. Our result reveal that patients with autonomic dysfunction caused by postganglionic sympathetic impairment also have impaired activation of structures within the cortical autonomic network. Impaired activation is evident during a test of sympathetic, but not parasympathetic, activation. Impaired cortical autonomic networks associated with sympathetic activation may be involved in the pathophysiology of NOH.

Pulse sequences and parallel imaging for high spatiotemporal resolution MRI at ultra-high field

The SNR and CNR benefits of ultra-high field (UHF) have helped push the envelope of achievable spatial resolution in MRI. For applications based on susceptibility contrast where there is a large CNR gain, high quality sub-millimeter resolution imaging is now being routinely performed, particularly in fMRI and phase imaging/QSM. This has enabled the study of structure and function of very fine-scale structures in the brain. UHF has also helped push the spatial resolution of many other MRI applications as will be outlined in this review. However, this push in resolution comes at a cost of a large encoding burden leading to very lengthy scans. Developments in parallel imaging with controlled aliasing and the move away from 2D slice-by-slice imaging to much more SNR-efficient simultaneous multi-slice (SMS) and 3D acquisitions have helped address this issue. In particular, these developments have revolutionized the efficiency of UHF MRI to enable high spatiotemporal resolution imaging at an order of magnitude faster acquisition. In addition to describing the main approaches to these techniques, this review will also outline important key practical considerations in using these methods in practice. Furthermore, new RF pulse design to tackle the B1+ and SAR issues of UHF and the increased SAR and power requirement of SMS RF pulses will also be touched upon. Finally, an outlook into new developments of smart encoding in more dimensions, particularly through using better temporal/across-contrast encoding and reconstruction will be described. Just as controlled aliasing fully exploits spatial encoding in parallel imaging to provide large multiplicative gains in accelerations, the complimentary use of these new approaches in temporal and across-contrast encoding are expected to provide exciting opportunities for further large gains in efficiency to further push the spatiotemporal resolution of MRI.

Non-invasive imaging modalities to study neurodegenerative diseases of aging brain

The aim of this article is to highlight current approaches for imaging elderly brain, indispensable for cognitive neuroscience research with emphasis on the basic physical principles of various non-invasive neuroimaging techniques. The first part of this article presents a quick overview of the primary non-invasive neuroimaging modalities used by cognitive neuroscientists such as transcranial magnetic stimulation (TMS), transcranial electrical stimulation (tES), electroencephalography (EEG), magnetoencephalography (MEG), single photon emission computed tomography (SPECT), positron emission tomography (PET), magnetic resonance spectroscopic imaging (MRSI), Profusion imaging, functional magnetic resonance imaging (fMRI), near infrared spectroscopy (NIRS) and diffusion tensor imaging (DTI) along with tractography and connectomics. The second part provides a comprehensive overview of different multimodality imaging techniques for various cognitive neuroscience studies of aging brain.

Online Reduction of Artifacts in EEG of Simultaneous EEG-fMRI Using Reference Layer Adaptive Filtering (RLAF)

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) allow us to study the active human brain from two perspectives concurrently. Signal processing based artifact reduction techniques are mandatory for this, however, to obtain reasonable EEG quality in simultaneous EEG-fMRI. Current artifact reduction techniques like average artifact subtraction (AAS), typically become less effective when artifact reduction has to be performed on-the-fly. We thus present and evaluate a new technique to improve EEG quality online. This technique adds up with online AAS and combines a prototype EEG-cap for reference recordings of artifacts, with online adaptive filtering and is named reference layer adaptive filtering (RLAF). We found online AAS + RLAF to be highly effective in improving EEG quality. Online AAS + RLAF outperformed online AAS and did so in particular online in terms of the chosen performance metrics, these being specifically alpha rhythm amplitude ratio between closed and opened eyes (3-45% improvement), signal-to-noise-ratio of visual evoked potentials (VEP) (25-63% improvement), and VEPs variability (16-44% improvement). Further, we found that EEG quality after online AAS + RLAF is occasionally even comparable with the offline variant of AAS at a 3T MRI scanner. In conclusion RLAF is a very effective add-on tool to enable high quality EEG in simultaneous EEG-fMRI experiments, even when online artifact reduction is necessary.

Comparing functional MRI protocols for small, iron-rich basal ganglia nuclei such as the subthalamic nucleus at 7 T and 3 T

The basal ganglia (BG) form a network of subcortical nuclei. Functional magnetic resonance imaging (fMRI) in the BG could provide insight in its functioning and the underlying mechanisms of Deep Brain Stimulation (DBS). However, fMRI of the BG with high specificity is challenging, because the nuclei are small and variable in their anatomical location. High resolution fMRI at field strengths of 7 Tesla (T) could help resolve these challenges to some extent. A set of MR protocols was developed for functional imaging of the BG nuclei at 3 T and 7 T. The protocols were validated using a stop-signal reaction task (Logan et al. []: J Exp Psychol: Human Percept Perform 10:276-291). Compared with sub-millimeter 7 T fMRI protocols aimed at cortex, a reduction of echo time and spatial resolution was strictly necessary to obtain robust Blood Oxygen Level Dependent (BOLD) sensitivity in the BG. An fMRI protocol at 3 T with identical resolution to the 7 T showed no robust BOLD sensitivity in any of the BG nuclei. The results suggest that the subthalamic nucleus, as well as the substantia nigra, red nucleus, and the internal and external parts of the globus pallidus show increased activation in failed stop trials compared with successful stop and go trials. Hum Brain Mapp 38:3226-3248, 2017. © 2017 Wiley Periodicals, Inc.

Multi-echo EPI of human fear conditioning reveals improved BOLD detection in ventromedial prefrontal cortex

Standard T₂^* weighted functional magnetic resonance imaging (fMRI) performed with echo-planar imaging (EPI) suffers from signal loss in the ventromedial prefrontal cortex (vmPFC) due to macroscopic field inhomogeneity. However, this region is of special interest to affective neuroscience and psychiatry. The Multi-echo EPI (MEPI) approach has several advantages over EPI but its performance against EPI in the vmPFC has not yet been examined in a study with sufficient statistical power using a task specifically eliciting activity in this region. We used a fear conditioning task with MEPI to compare the performance of MEPI and EPI in vmPFC and control regions in 32 healthy young subjects. We analyzed activity associated with short (12ms), standard (29ms) and long (46ms) echo times, and a voxel-wise combination of these three echo times. Behavioral data revealed successful differentiation of the conditioned versus safety stimulus; activity in the vmPFC was shown by the contrast "safety stimulus > conditioned stimulus" as in previous research and proved significantly stronger with the combined MEPI than standard single-echo EPI. Then, we aimed to demonstrate that the additional cluster extent (ventral extension) detected in the vmPFC with MEPI reflects activation in a relevant cluster (i.e., not just non-neuronal noise). To do this, we used resting state data from the same subjects to show that the time-course of this region was both connected to bilateral amygdala and the default mode network. Overall, we demonstrate that MEPI (by means of the weighted sum combination approach) outperforms standard EPI in vmPFC; MEPI performs always at least as good as the best echo time for a given brain region but provides all necessary echo times for an optimal BOLD sensitivity for the whole brain. This is relevant for affective neuroscience and psychiatry given the critical role of the vmPFC in emotion regulation.

Modeling the Dynamics of Human Brain Activity with Recurrent Neural Networks

Encoding models are used for predicting brain activity in response to sensory stimuli with the objective of elucidating how sensory information is represented in the brain. Encoding models typically comprise a nonlinear transformation of stimuli to features (feature model) and a linear convolution of features to responses (response model). While there has been extensive work on developing better feature models, the work on developing better response models has been rather limited. Here, we investigate the extent to which recurrent neural network models can use their internal memories for nonlinear processing of arbitrary feature sequences to predict feature-evoked response sequences as measured by functional magnetic resonance imaging. We show that the proposed recurrent neural network models can significantly outperform established response models by accurately estimating long-term dependencies that drive hemodynamic responses. The results open a new window into modeling the dynamics of brain activity in response to sensory stimuli.

Reference layer adaptive filtering (RLAF) for EEG artifact reduction in simultaneous EEG-fMRI

OBJECTIVE

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) combines advantages of both methods, namely high temporal resolution of EEG and high spatial resolution of fMRI. However, EEG quality is limited due to severe artifacts caused by fMRI scanners.

APPROACH

To improve EEG data quality substantially, we introduce methods that use a reusable reference layer EEG cap prototype in combination with adaptive filtering. The first method, reference layer adaptive filtering (RLAF), uses adaptive filtering with reference layer artifact data to optimize artifact subtraction from EEG. In the second method, multi band reference layer adaptive filtering (MBRLAF), adaptive filtering is performed on bandwidth limited sub-bands of the EEG and the reference channels.

MAIN RESULTS

The results suggests that RLAF outperforms the baseline method, average artifact subtraction, in all settings and also its direct predecessor, reference layer artifact subtraction (RLAS), in lower (<35 Hz) frequency ranges. MBRLAF is computationally more demanding than RLAF, but highly effective in all EEG frequency ranges. Effectivity is determined by visual inspection, as well as root-mean-square voltage reduction and power reduction of EEG provided that physiological EEG components such as occipital EEG alpha power and visual evoked potentials (VEP) are preserved. We demonstrate that both, RLAF and MBRLAF, improve VEP quality. For that, we calculate the mean-squared-distance of single trial VEP to the mean VEP and estimate single trial VEP classification accuracies. We found that the average mean-squared-distance is lowest and the average classification accuracy is highest after MBLAF. RLAF was second best.

SIGNIFICANCE

In conclusion, the results suggests that RLAF and MBRLAF are potentially very effective in improving EEG quality of simultaneous EEG-fMRI. Highlights We present a new and reusable reference layer cap prototype for simultaneous EEG-fMRI We introduce new algorithms for reducing EEG artifacts due to simultaneous fMRI The algorithms combine a reference layer and adaptive filtering Several evaluation criteria suggest superior effectivity in terms of artifact reduction We demonstrate that physiological EEG components are preserved.

A Hitchhiker's Guide to Functional Magnetic Resonance Imaging

Functional Magnetic Resonance Imaging (fMRI) studies have become increasingly popular both with clinicians and researchers as they are capable of providing unique insights into brain functions. However, multiple technical considerations (ranging from specifics of paradigm design to imaging artifacts, complex protocol definition, and multitude of processing and methods of analysis, as well as intrinsic methodological limitations) must be considered and addressed in order to optimize fMRI analysis and to arrive at the most accurate and grounded interpretation of the data. In practice, the researcher/clinician must choose, from many available options, the most suitable software tool for each stage of the fMRI analysis pipeline. Herein we provide a straightforward guide designed to address, for each of the major stages, the techniques, and tools involved in the process. We have developed this guide both to help those new to the technique to overcome the most critical difficulties in its use, as well as to serve as a resource for the neuroimaging community.

BOLD Imaging in Awake Wild-Type and Mu-Opioid Receptor Knock-Out Mice Reveals On-Target Activation Maps in Response to Oxycodone

Blood oxygen level dependent (BOLD) imaging in awake mice was used to identify differences in brain activity between wild-type, and Mu (μ) opioid receptor knock-outs (MuKO) in response to oxycodone (OXY). Using a segmented, annotated MRI mouse atlas and computational analysis, patterns of integrated positive and negative BOLD activity were identified across 122 brain areas. The pattern of positive BOLD showed enhanced activation across the brain in WT mice within 15 min of intraperitoneal administration of 2.5 mg of OXY. BOLD activation was detected in 72 regions out of 122, and was most prominent in areas of high μ opioid receptor density (thalamus, ventral tegmental area, substantia nigra, caudate putamen, basal amygdala, and hypothalamus), and focus on pain circuits indicated strong activation in major pain processing centers (central amygdala, solitary tract, parabrachial area, insular cortex, gigantocellularis area, ventral thalamus primary sensory cortex, and prelimbic cortex). Importantly, the OXY-induced positive BOLD was eliminated in MuKO mice in most regions, with few exceptions (some cerebellar nuclei, CA3 of the hippocampus, medial amygdala, and preoptic areas). This result indicates that most effects of OXY on positive BOLD are mediated by the μ opioid receptor (on-target effects). OXY also caused an increase in negative BOLD in WT mice in few regions (16 out of 122) and, unlike the positive BOLD response the negative BOLD was only partially eliminated in the MuKO mice (cerebellum), and in some case intensified (hippocampus). Negative BOLD analysis therefore shows activation and deactivation events in the absence of the μ receptor for some areas where receptor expression is normally extremely low or absent (off-target effects). Together, our approach permits establishing opioid-induced BOLD activation maps in awake mice. In addition, comparison of WT and MuKO mutant mice reveals both on-target and off-target activation events, and set an OXY brain signature that should, in the future, be compared to other μ opioid agonists.

Imaging the Addicted Brain: Alcohol

Alcohol use disorder (AUD) represents a major public health issue due to its prevalence and severe health consequences. It may affect several aspects of an individual's life including work and relationships, and it also increases risk for additional problems such as brain injury. The causes and outcomes of AUD are varied; thus, attempting to understand this complex phenomenon requires investigation from multiple perspectives. Magnetic resonance imaging (MRI) is a powerful means to investigate brain anatomical and functional alterations related to AUD. Recent advances in MRI methods allow better investigation of the alterations to structural and functional brain networks in AUD. Here, we focus on findings from studies using multiple MRI techniques, which converge to support the considerable vulnerability of frontal systems. Indeed, MRI studies provide evidence for a "disconnection syndrome" which could be involved in the poor behavioral control observed in AUD.

Functional magnetic resonance imaging in awake transgenic fragile X rats: evidence of dysregulation in reward processing in the mesolimbic/habenular neural circuit

Anxiety and social deficits, often involving communication impairment, are fundamental clinical features of fragile X syndrome. There is growing evidence that dysregulation in reward processing is a contributing factor to the social deficits observed in many psychiatric disorders. Hence, we hypothesized that transgenic fragile X mental retardation 1 gene (fmr1) KO (FX) rats would display alterations in reward processing. To this end, awake control and FX rats were imaged for changes in blood oxygen level dependent (BOLD) signal intensity in response to the odor of almond, a stimulus to elicit the innate reward response. Subjects were 'odor naive' to this evolutionarily conserved stimulus. The resulting changes in brain activity were registered to a three-dimensional segmented, annotated rat atlas delineating 171 brain regions. Both wild-type (WT) and FX rats showed robust brain activation to a rewarding almond odor, though FX rats showed an altered temporal pattern and tended to have a higher number of voxels with negative BOLD signal change from baseline. This pattern of greater negative BOLD was especially apparent in the Papez circuit, critical to emotional processing and the mesolimbic/habenular reward circuit. WT rats showed greater positive BOLD response in the supramammillary area, whereas FX rats showed greater positive BOLD response in the dorsal lateral striatum, and greater negative BOLD response in the retrosplenial cortices, the core of the accumbens and the lateral preoptic area. When tested in a freely behaving odor-investigation paradigm, FX rats failed to show the preference for almond odor which typifies WT rats. However, FX rats showed investigation profiles similar to WT when presented with social odors. These data speak to an altered processing of this highly salient novel odor in the FX phenotype and lend further support to the notion that altered reward systems in the brain may contribute to fragile X syndrome symptomology.

An Automated Motion Detection and Reward System for Animal Training

A variety of approaches has been used to minimize head movement during functional brain imaging studies in awake laboratory animals. Many laboratories expend substantial effort and time training animals to remain essentially motionless during such studies. We could not locate an “off-the-shelf” automated training system that suited our needs. 

We developed a time- and labor-saving automated system to train animals to hold still for extended periods of time. The system uses a personal computer and modest external hardware to provide stimulus cues, monitor movement using commercial video surveillance components, and dispense rewards. A custom computer program automatically increases the motionless duration required for rewards based on performance during the training session but allows changes during sessions. This system was used to train cynomolgus monkeys (Macaca fascicularis) for awake neuroimaging studies using positron emission tomography (PET) and functional magnetic resonance imaging (fMRI).

The automated system saved the trainer substantial time, presented stimuli and rewards in a highly consistent manner, and automatically documented training sessions. We have limited data to prove the training system's success, drawn from the automated records during training sessions, but we believe others may find it useful. The system can be adapted to a range of behavioral training/recording activities for research or commercial applications, and the software is freely available for non-commercial use.

A Review of Transcranial Magnetic Stimulation and Multimodal Neuroimaging to Characterize Post-Stroke Neuroplasticity

Following stroke, the brain undergoes various stages of recovery where the central nervous system can reorganize neural circuitry (neuroplasticity) both spontaneously and with the aid of behavioral rehabilitation and non-invasive brain stimulation. Multiple neuroimaging techniques can characterize common structural and functional stroke-related deficits, and importantly, help predict recovery of function. Diffusion tensor imaging (DTI) typically reveals increased overall diffusivity throughout the brain following stroke, and is capable of indexing the extent of white matter damage. Magnetic resonance spectroscopy (MRS) provides an index of metabolic changes in surviving neural tissue after stroke, serving as a marker of brain function. The neural correlates of altered brain activity after stroke have been demonstrated by abnormal activation of sensorimotor cortices during task performance, and at rest, using functional magnetic resonance imaging (fMRI). Electroencephalography (EEG) has been used to characterize motor dysfunction in terms of increased cortical amplitude in the sensorimotor regions when performing upper limb movement, indicating abnormally increased cognitive effort and planning in individuals with stroke. Transcranial magnetic stimulation (TMS) work reveals changes in ipsilesional and contralesional cortical excitability in the sensorimotor cortices. The severity of motor deficits indexed using TMS has been linked to the magnitude of activity imbalance between the sensorimotor cortices. In this paper, we will provide a narrative review of data from studies utilizing DTI, MRS, fMRI, EEG, and brain stimulation techniques focusing on TMS and its combination with uni- and multimodal neuroimaging methods to assess recovery after stroke. Approaches that delineate the best measures with which to predict or positively alter outcomes will be highlighted.

Changes in Cerebral Hemodynamics during Complex Motor Learning by Character Entry into Touch-Screen Terminals

Introduction

Studies of cerebral hemodynamics during motor learning have mostly focused on neurorehabilitation interventions and their effectiveness. However, only a few imaging studies of motor learning and the underlying complex cognitive processes have been performed.

Methods

We measured cerebral hemodynamics using near-infrared spectroscopy (NIRS) in relation to acquisition patterns of motor skills in healthy subjects using character entry into a touch-screen terminal. Twenty healthy, right-handed subjects who had no previous experience with character entry using a touch-screen terminal participated in this study. They were asked to enter the characters of a randomly formed Japanese syllabary into the touch-screen terminal. All subjects performed the task with their right thumb for 15 s alternating with 25 s of rest for 30 repetitions. Performance was calculated by subtracting the number of incorrect answers from the number of correct answers, and gains in motor skills were evaluated according to the changes in performance across cycles. Behavioral and oxygenated hemoglobin concentration changes across task cycles were analyzed using Spearman’s rank correlations.

Results

Performance correlated positively with task cycle, thus confirming motor learning. Hemodynamic activation over the left sensorimotor cortex (SMC) showed a positive correlation with task cycle, whereas activations over the right prefrontal cortex (PFC) and supplementary motor area (SMA) showed negative correlations.

Conclusions

We suggest that increases in finger momentum with motor learning are reflected in the activity of the left SMC. We further speculate that the right PFC and SMA were activated during the early phases of motor learning, and that this activity was attenuated with learning progress.

Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Ventral Stream

Converging evidence suggests that the primate ventral visual pathway encodes increasingly complex stimulus features in downstream areas. We quantitatively show that there indeed exists an explicit gradient for feature complexity in the ventral pathway of the human brain. This was achieved by mapping thousands of stimulus features of increasing complexity across the cortical sheet using a deep neural network. Our approach also revealed a fine-grained functional specialization of downstream areas of the ventral stream. Furthermore, it allowed decoding of representations from human brain activity at an unsurpassed degree of accuracy, confirming the quality of the developed approach. Stimulus features that successfully explained neural responses indicate that population receptive fields were explicitly tuned for object categorization. This provides strong support for the hypothesis that object categorization is a guiding principle in the functional organization of the primate ventral stream.

Distinct BOLD Activation Profiles Following Central and Peripheral Oxytocin Administration in Awake Rats

A growing body of literature has suggested that intranasal oxytocin (OT) or other systemic routes of administration can alter prosocial behavior, presumably by directly activating OT sensitive neural circuits in the brain. Yet there is no clear evidence that OT given peripherally can cross the blood-brain barrier at levels sufficient to engage the OT receptor. To address this issue we examined changes in blood oxygen level-dependent (BOLD) signal intensity in response to peripheral OT injections (0.1, 0.5, or 2.5 mg/kg) during functional magnetic resonance imaging (fMRI) in awake rats imaged at 7.0 T. These data were compared to OT (1 μg/5 μl) given directly to the brain via the lateral cerebroventricle. Using a 3D annotated MRI atlas of the rat brain segmented into 171 brain areas and computational analysis, we reconstructed the distributed integrated neural circuits identified with BOLD fMRI following central and peripheral OT. Both routes of administration caused significant changes in BOLD signal within the first 10 min of administration. As expected, central OT activated a majority of brain areas known to express a high density of OT receptors, e.g., lateral septum, subiculum, shell of the accumbens, bed nucleus of the stria terminalis. This profile of activation was not matched by peripheral OT. The change in BOLD signal to peripheral OT did not show any discernible dose-response. Interestingly, peripheral OT affected all subdivisions of the olfactory bulb, in addition to the cerebellum and several brainstem areas relevant to the autonomic nervous system, including the solitary tract nucleus. The results from this imaging study do not support a direct central action of peripheral OT on the brain. Instead, the patterns of brain activity suggest that peripheral OT may interact at the level of the olfactory bulb and through sensory afferents from the autonomic nervous system to influence brain activity.

Three-dimensional echo planar imaging with controlled aliasing: A sequence for high temporal resolution functional MRI

PURPOSE

In this work, we combine three-dimensional echo planar imaging (3D-EPI) with controlled aliasing to substantially increase temporal resolution in whole-brain functional MRI (fMRI) while minimizing geometry-factor (g-factor) losses.

THEORY AND METHODS

The study was performed on a 7 Tesla scanner equipped with a 32-channel receive coil. The proposed 3D-EPI-CAIPI sequence was evaluated for: (i) image quality, compared with a conventionally undersampled parallel imaging acquisition; (ii) temporal resolution, the ability to sample and remove physiological signal fluctuations from the fMRI signal of interest and (iii) the ability to distinguish small changes in hemodynamic responses in an event-related fMRI experiment.

RESULTS

Whole-brain fMRI data with a voxel size of 2 × 2 × 2 mm(3) and temporal resolution of 371 ms could be acquired with acceptable image quality. Ten-fold parallel imaging accelerated 3D-EPI-CAIPI data were shown to lower the maximum g-factor losses up to 62% with respect to a 10-fold accelerated 3D-EPI dataset. FMRI with 400 ms temporal resolution allowed the detection of time-to-peak variations in functional responses due to multisensory facilitation in temporal, occipital and frontal cortices.

CONCLUSION

3D-EPI-CAIPI allows increased temporal resolution that enables better characterization of physiological noise, thus improving sensitivity to signal changes of interest. Furthermore, subtle changes in hemodynamic response dynamics can be studied in shorter scan times by avoiding the need for jittering. Magn Reson Med 75:2350-2361, 2016. © 2015 Wiley Periodicals, Inc.

Advances in imaging explosive blast mild traumatic brain injury

In the past, direct physical evidence of mild traumatic brain injury (mTBI) from explosive blast has been difficult to obtain through conventional imaging modalities such as T1- and T2-weighted magnetic resonance imaging (MRI) and computed tomography (CT). Here, we review current progress in detecting evidence of brain injury from explosive blast using advanced imaging, including diffusion tensor imaging (DTI), functional MRI (fMRI), and the metabolic imaging methods such as positron emission tomography (PET) and magnetic resonance spectroscopic imaging (MRSI), where each targets different aspects of the pathology involved in mTBI. DTI provides a highly sensitive measure to detect primary changes in the microstructure of white matter tracts. fMRI enables the measurement of changes in brain activity in response to different stimuli or tasks. Remarkably, all three of these paradigms have found significant success in conventional mTBI where conventional clinical imaging frequently fails to provide definitive differences. Additionally, although used less frequently for conventional mTBI, PET has the potential to characterize a variety of neurotransmitter systems using target agents and will undoubtedly play a larger role, once the basic mechanisms of injury are better understood and techniques to identify the injury are more common. Finally, our MRSI imaging studies, although acquired at much lower spatial resolution, have demonstrated selectivity to different metabolic and physiologic processes, uncovering some of the most profound differences on an individual by individual basis, suggesting the potential for utility in the management of individual patients.

Special considerations/technical limitations of blood-oxygen-level-dependent functional magnetic resonance imaging

In this review, limitations affecting the results of presurgical mapping with blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) are discussed. There is a great need to standardize fMRI acquisition and analysis methods and establish guidelines to address quality control issues. Several national and international organizations are formulating guidelines and standards for both clinical and research applications of BOLD fMRI. Consensus regarding management of these issues will likely both improve the clinical standard of care and enhance future research applications of fMRI.

Studies on the Q175 Knock-in Model of Huntington's Disease Using Functional Imaging in Awake Mice: Evidence of Olfactory Dysfunction

Blood oxygen level dependent (BOLD) imaging in awake mice was used to identify differences in brain activity between wild-type, HETzQ175, and HOMzQ175 genotypes in response to the odor of almond. The study was designed to see how alterations in the huntingtin gene in a mouse model of Huntington’s disease would affect the perception and processing of almond odor, an evolutionarily conserved stimulus with high emotional and motivational valence. Moreover, the mice in this study were “odor naïve,” i.e., never having smelled almond or any nuts. Using a segmented, annotated MRI atlas of the mouse and computational analysis, 17 out of 116 brain regions were identified as responding differently to almond odor across genotypes. These regions included the glomerulus of the olfactory bulb, forebrain cortex, anterior cingulate, subiculum, and dentate gyrus of the hippocampus, and several areas of the hypothalamus. In many cases, these regions showed a gene-dose effect with HETzQ175 mice showing a reduction in brain activity from wild-type that is further reduced in HOMzQ175 mice. Conspicuously absent were any differences in brain activity in the caudate/putamen, thalamus, CA3, and CA1 of the hippocampus and much of the cortex. The glomerulus of the olfactory bulb in HOMzQ175 mice showed a reduced change in BOLD signal intensity in response to almond odor as compared to the other phenotypes suggesting a deficit in olfactory sensitivity.

General overview on the merits of multimodal neuroimaging data fusion

Multimodal neuroimaging has become a mainstay of basic and cognitive neuroscience in humans and animals, despite challenges to consider when acquiring and combining non-redundant imaging data. Multimodal data integration can yield important insights into brain processes and structures in addition to spatiotemporal resolution complementarity, including: a comprehensive physiological view on brain processes and structures, quantification, generalization and normalization, and availability of biomarkers. In this review, we discuss data acquisition and fusion in multimodal neuroimaging in the context of each of these potential merits. However, limitations - due to differences in the neuronal and structural underpinnings of each method - have to be taken into account when modeling and interpreting multimodal data using generative models. We conclude that when these challenges are adequately met, multimodal data fusion can create substantial added value for neuroscience applications making it an indispensable approach for studying the brain.

Single echo MRI

Purpose

Previous nonlinear gradient research has focused on trajectories that reconstruct images with a minimum number of echoes. Here we describe sequences where the nonlinear gradients vary in time to acquire the image in a single readout. The readout is designed to be very smooth so that it can be compressed to minimal time without violating peripheral nerve stimulation limits, yielding an image from a single 4 ms echo.

Theory and Methods

This sequence was inspired by considering the code of each voxel, i.e. the phase accumulation that a voxel follows through the readout, an approach connected to traditional encoding theory. We present simulations for the initial sequence, a low slew rate analog, and higher resolution reconstructions.

Results

Extremely fast acquisitions are achievable, though as one would expect, SNR is reduced relative to the slower Cartesian sampling schemes because of the high gradient strengths.

Conclusions

The prospect that nonlinear gradients can acquire images in a single <10 ms echo makes this a novel and interesting approach to image encoding.

The quest for developing new treatments from imaging techniques: promises, problems and future potential

Drug discovery and development in psychiatry is beset by many challenges, both those which are associated with the development process in general (and affecting all of medicine) and others, which are unique to psychiatry. Due to these factors, marginal progress has been achieved in the past as many features of serious mental illness remain untouched by existing treatments. Arguably, the most important of these drug targets is cognitive dysfunction, which strongly predicts clinical outcome in a number of major neuropsychiatric conditions. Therefore, a critical need exists for progress in the characterization of this and other targets for drug discovery and development. A key area, which is already showing promise, is the use of non-invasive functional neuroimaging to investigate both cognitive dysfunction and its remediation with novel agents. In this article, the authors describe the paradigmatic case of cognitive dysfunction in schizophrenia, and the prospects for using functional magnetic resonance imaging (fMRI) to investigate the effects of agents targeting cognition. The authors observe a number of advantages of this approach over other methodologies, as well as some significant issues to be resolved in the application of this technology. The authors propose that pharmaco-fMRI is emerging as a major tool to enhance the drug development process in order to bring truly novel treatments to patients with a range of neuropsychiatric disorders.

Simulated dive in rats lead to acute changes in cerebral blood flow on MRI, but no cerebral injuries to grey or white matter

In this study, the effect of a simulated dive on rat brain was investigated using several magnetic resonance imaging (MRI)-methods and immunohistochemistry. Rats were randomly assigned to a dive- or a control group. The dive group was exposed to a simulated air dive to 600 kPa for 45 min. Pulmonary artery was monitored for vascular gas bubbles by ultrasound. MRI was performed 1 h after decompression and at one and 2 weeks after the dive with a different combination of MRI sequences at each time point. Two weeks after decompression, rats were sacrificed and brains were prepared for histology. Dived rats had a different time-curve for the dynamic contrast-enhanced MRI signal than controls with higher relative signal intensity, a tendency towards longer time to peak and a larger area under the curve for the whole brain on the acute MRI scan. On MRI, 1 and 2 weeks after dive, T2-maps showed no signal abnormalities or morphological changes. However, region of interest based measurements of T2 showed higher T2 in the brain stem among decompressed animals than controls after one and 2 weeks. Microscopical examination including immunohistochemistry did not reveal apparent structural or cellular injuries in any part of the rat brains. These observations indicate that severe decompression does not seem to cause any structural or cellular injury to the brain tissue of the rat, but may cause circulatory changes in the brain perfusion in the acute phase.

Magnetic resonance imaging to visualize stroke and characterize stroke recovery: a review

The global burden of stroke continues to grow. Although stroke prevention strategies (e.g., medications, diet, and exercise) can contribute to risk reduction, options for acute interventions (e.g., thrombolytic therapy for ischemic stroke) are limited to the minority of patients. The remaining patients are often left with profound neurological disabilities that substantially impact quality of life, economic productivity, and increase caregiver burden. In the last decade, however, the future outlook for such patients has been tempered by movement toward the view that the brain is capable of reorganizing after injury. Many now view brain recovery after stroke as an area of scientific research with large potential for therapeutic advances, far into the future (Broderick and William, 2004). As a probe of brain anatomy, function and physiology, magnetic resonance imaging (MRI) is a non-invasive and highly versatile modality that promises to play a particularly important role in such research. Here we provide a basic review of MRI physical principles and applications for assessing stroke, looking toward the future role MRI may play in improving stroke rehabilitation methods and stroke recovery.

Brain responses to bladder filling in older women without urgency incontinence

AIMS

To investigate normal brain responses to bladder filling, especially when there is little or no sensation as in much of daily life.

METHODS

We performed an functional magnetic resonance imaging (fMRI) study of brain responses to bladder filling in normal female subjects, evoked by infusion and withdrawal of fluid in and out of the bladder. Using the contrast (infusion-withdrawal), we imaged brain activity at small bladder volumes with weak filling sensation and also with full bladder and strong desire to void.

RESULTS

Eleven women, average age 65 years (range: 60-71 years) were included. With full bladder and strong desire to void, filling provoked a well-known pattern of activation near the right insula and (as a trend) in the dorsal anterior cingulate cortex and supplementary motor area. There was no significant deactivation. With small bladder volume filling provoked widespread apparent deactivation and no significant activation. Apparent deactivation was associated with increased fMRI signal during withdrawal rather than decrease during infusion, suggesting artifact. A correction for global changes in cerebral blood flow eliminated it and revealed significant subcortical activation, although none in frontal or parietal cortex.

CONCLUSIONS

In older women with normal bladder function, infusion into an already full bladder resulted in strong sensation and brain activation near the insula and in the dorsal anterior cingulate/supplementary motor complex. With near-empty bladder and little sensation, the situation during much of daily life, these cortical areas were not detectably activated, but activation in midbrain and parahippocampal regions presumably indicated unconscious monitoring of ascending bladder signals.