Depth- and curvature-based quantitative susceptibility mapping analyses of cortical iron in Alzheimer's disease.

In addition to amyloid beta plaques and neurofibrillary tangles, Alzheimer's disease (AD) has been associated with elevated iron in deep gray matter nuclei using quantitative susceptibility mapping (QSM). However, only a few studies have examined cortical iron, using more macroscopic approaches that cannot assess layer-specific differences. Here, we conducted column-based QSM analyses to assess whether AD-related increases in cortical iron vary in relation to layer-specific differences in the type and density of neurons. We obtained global and regional measures of positive (iron) and negative (myelin, protein aggregation) susceptibility from 22 adults with AD and 22 demographically matched healthy controls. Depth-wise analyses indicated that global susceptibility increased from the pial surface to the gray/white matter boundary, with a larger slope for positive susceptibility in the left hemisphere for adults with AD than controls. Curvature-based analyses indicated larger global susceptibility for adults with AD versus controls; the right hemisphere versus left; and gyri versus sulci. Region-of-interest analyses identified similar depth- and curvature-specific group differences, especially for temporo-parietal regions. Finding that iron accumulates in a topographically heterogenous manner across the cortical mantle may help explain the profound cognitive deterioration that differentiates AD from the slowing of general motor processes in healthy aging.

Brain age vector: A measure of brain aging with enhanced neurodegenerative disorder specificity.

Neuroimaging-driven brain age estimation has become popular in measuring brain aging and identifying neurodegenerations. However, the single estimated brain age (gap) compromises regional variations of brain aging, losing spatial specificity across diseases which is valuable for early screening. In this study, we combined brain age modeling with Shapley Additive Explanations to measure brain aging as a feature contribution vector underlying spatial pathological aging mechanism. Specifically, we regressed age with volumetric brain features using machine learning to construct the brain age model, and model-agnostic Shapley values were calculated to attribute regional brain aging for each subject's age estimation, forming the brain age vector. Spatial specificity of the brain age vector was evaluated among groups of normal aging, prodromal Parkinson disease (PD), stable mild cognitive impairment (sMCI), and progressive mild cognitive impairment (pMCI). Machine learning methods were adopted to examine the discriminability of the brain age vector in early disease screening, compared with the other two brain aging metrics (single brain age gap, regional brain age gaps) and brain volumes. Results showed that the proposed brain age vector accurately reflected disorder-specific abnormal aging patterns related to the medial temporal and the striatum for prodromal AD (sMCI vs. pMCI) and PD (healthy controls [HC] vs. prodromal PD), respectively, and demonstrated outstanding performance in early disease screening, with area under the curves of 83.39% and 72.28% in detecting pMCI and prodromal PD, respectively. In conclusion, the proposed brain age vector effectively improves spatial specificity of brain aging measurement and enables individual screening of neurodegenerative diseases.

Critical factors in achieving fine-scale functional MRI: Removing sources of inadvertent spatial smoothing.

Ultra-high Field (≥7T) functional magnetic resonance imaging (UHF-fMRI) provides opportunities to resolve fine-scale features of functional architecture such as cerebral cortical columns and layers, in vivo. While the nominal resolution of modern fMRI acquisitions may appear to be sufficient to resolve these features, several common data preprocessing steps can introduce unwanted spatial blurring, especially those that require interpolation of the data. These resolution losses can impede the detection of the fine-scale features of interest. To examine quantitatively and systematically the sources of spatial resolution losses occurring during preprocessing, we used synthetic fMRI data and real fMRI data from the human visual cortex-the spatially interdigitated human V2 "thin" and "thick" stripes. The pattern of these cortical columns lies along the cortical surface and thus can be best appreciated using surface-based fMRI analysis. We used this as a testbed for evaluating strategies that can reduce spatial blurring of fMRI data. Our results show that resolution losses can be mitigated at multiple points in preprocessing pathway. We show that unwanted blur is introduced at each step of volume transformation and surface projection, and can be ameliorated by replacing multi-step transformations with equivalent single-step transformations. Surprisingly, the simple approaches of volume upsampling and of cortical mesh refinement also helped to reduce resolution losses caused by interpolation. Volume upsampling also serves to improve motion estimation accuracy, which helps to reduce blur. Moreover, we demonstrate that the level of spatial blurring is nonuniform over the brain-knowledge which is critical for interpreting data in high-resolution fMRI studies. Importantly, our study provides recommendations for reducing unwanted blurring during preprocessing as well as methods that enable quantitative comparisons between preprocessing strategies. These findings highlight several underappreciated sources of a spatial blur. Individually, the factors that contribute to spatial blur may appear to be minor, but in combination, the cumulative effects can hinder the interpretation of fine-scale fMRI and the detectability of these fine-scale features of functional architecture.

Complementing canonical fMRI with functional Quantitative Susceptibility Mapping (fQSM) in modern neuroimaging research.

Functional Quantitative Susceptibility Mapping (fQSM) allows for the quantitative measurement of time-varying magnetic susceptibility across cortical and subcortical brain structures with a potentially higher spatial specificity than conventional fMRI. While the usefulness of fQSM with General Linear Model and "On/Off" paradigms has been assessed, little is known about the potential applications and limitations of this technique in more sophisticated experimental paradigms and analyses, such as those currently used in modern neuroimaging. To thoroughly characterize fQSM activations, here we used 7T MRI, tonotopic mapping, as well as univariate (i.e., GLM and population Receptive Field) and multivariate (Representational Similarity Analysis; RSA) analyses. Although fQSM detected less tone-responsive voxels than fMRI, they were more consistently localized in gray matter. Also, the majority of active gray matter voxels exhibited negative fQSM response, signaling the expected oxyhemoglobin increase, whereas positive fQSM activations were mainly in white matter. Though fMRI- and fQSM-based tonotopic maps were overall comparable, the representation of frequency tunings in tone-sensitive regions was significantly more balanced for fQSM. Lastly, RSA revealed that frequency information from the auditory cortex could be successfully retrieved by using either methods. Overall, fQSM produces complementary results to conventional fMRI, as it captures small-scale variations in the activation pattern which inform multivariate measures. Although positive fQSM responses deserve further investigation, they do not impair the interpretation of contrasts of interest. The quantitative nature of fQSM, its spatial specificity and the possibility to simultaneously acquire canonical fMRI support the use of this technique for longitudinal and multicentric studies and pre-surgical mapping.

Spatial organization enhances versatility and specificity in cyclic di-GMP signaling.

The second messenger cyclic di-GMP regulates a variety of processes in bacteria, many of which are centered around the decision whether to adopt a sessile or a motile life style. Regulatory circuits include pathogenicity, biofilm formation, and motility in a wide variety of bacteria, and play a key role in cell cycle progression in Caulobacter crescentus. Interestingly, multiple, seemingly independent c-di-GMP pathways have been found in several species, where deletions of individual c-di-GMP synthetases (DGCs) or hydrolases (PDEs) have resulted in distinct phenotypes that would not be expected based on a freely diffusible second messenger. Several recent studies have shown that individual signaling nodes exist, and additionally, that protein/protein interactions between DGCs, PDEs and c-di-GMP receptors play an important role in signaling specificity. Additionally, subcellular clustering has been shown to be employed by bacteria to likely generate local signaling of second messenger, and/or to increase signaling specificity. This review highlights recent findings that reveal how bacteria employ spatial cues to increase the versatility of second messenger signaling.

Composition and Biosynthesis of Scent Compounds from Sterile Flowers of an Ornamental Plant Clematis florida cv. 'Kaiser'.

Clematis florida is a popular ornamental vine species known for diverse colors and shapes of its flowers but not for scent. Here we investigated the composition and biosynthesis of floral scent in 'Kaiser', a fragrant cultivar of C. florida that has sterile flowers. Volatile profiling revealed that flowers of 'Kaiser' emit more than 20 compounds, with monoterpenes being most abundant. Among the three floral organs, namely sepals, transformed-petals, and ovaries, ovaries had the highest rates of total volatile emission. To determine the molecular mechanism underlying floral scent biosynthesis in 'Kaiser', we sequenced a flower transcriptome and searched the transcriptome for terpene synthase genes (TPSs), which are key genes for terpene biosynthesis. Among the TPS genes identified, three were putative intact full-length genes and were designated CfTPS1, CfTPS2, and CfTPS3. Phylogenetic analysis placed CfTPS1, CfTPS2, and CfTPS3 to the TPS-g, TPS-b, and TPS-a subfamily, respectively. Through in vitro enzyme assays with Escherichia coli-expressed recombinant proteins, both CfTPS1 and CfTPS2 were demonstrated to catalyze the conversion of geranyl diphosphate to linalool, the most abundant constituent of C. florida floral scent. In addition, CfTPS1 and CfTPS2 produced the sesquiterpene nerolidol from (E,E)-farnesyl diphosphate. CfTPS3 showed sesquiterpene synthase activity and produced multiple products in vitro. All three CfTPS genes showed higher levels of expression in sepals than those in transformed-petals and ovaries. Our results show that despite being sterile, the flowers of 'Kaiser' have normal mechanisms for floral scent biosynthesis that make the flowers fragrant.

A cortical vascular model for examining the specificity of the laminar BOLD signal.

Blood oxygenation level dependent (BOLD) functional MRI has been used for inferring layer specific activation in humans. However, intracortical veins perpendicular to the cortical surface are suspected to degrade the laminar specificity as they drain blood from the microvasculature and BOLD signal is carried over from lower to upper cortical layers on its way to the pial surface. In this work, a vascular model of the cortex is developed to investigate the laminar specificity of the BOLD signal for Spin Echo (SE) and Gradient Echo (GE) following the integrative model presented by Uludag et al. (2009). The results of the simulation show that the laminar point spread function (PSF) of the BOLD signal presents similar features across all layers. The PSF for SE is highly localised whereas for GE there is a flat tail running to the pial surface, with amplitude less than a quarter of the response from the layer itself. Consequently the GE response at any layer will also contain a contribution accumulated from all lower layers.

Reliability of task-based fMRI in the dorsal horn of the human spinal cord.

The application of functional magnetic resonance imaging (fMRI) to the human spinal cord is still a relatively small field of research and faces many challenges. Here we aimed to probe the limitations of task-based spinal fMRI at 3T by investigating the reliability of spinal cord blood oxygen level dependent (BOLD) responses to repeated nociceptive stimulation across two consecutive days in 40 healthy volunteers. We assessed the test-retest reliability of subjective ratings, autonomic responses, and spinal cord BOLD responses to short heat pain stimuli (1s duration) using the intraclass correlation coefficient (ICC). At the group level, we observed robust autonomic responses as well as spatially specific spinal cord BOLD responses at the expected location, but no spatial overlap in BOLD response patterns across days. While autonomic indicators of pain processing showed good-to-excellent reliability, both ß-estimates and z-scores of task-related BOLD responses showed poor reliability across days in the target region (gray matter of the ipsilateral dorsal horn). When taking into account the sensitivity of gradient-echo echo planar imaging (GE-EPI) to draining vein signals by including the venous plexus in the analysis, we observed BOLD responses with fair reliability across days. Taken together, these results demonstrate that heat pain stimuli as short as one second are able to evoke a robust and spatially specific BOLD response, which is however strongly variable within participants across time, resulting in low reliability in the dorsal horn gray matter. Further improvements in data acquisition and analysis techniques are thus necessary before event-related spinal cord fMRI as used here can be reliably employed in longitudinal designs or clinical settings.

Optimizing spatial specificity and signal quality in fNIRS: an overview of potential challenges and possible options for improving the reliability of real-time applications.

The optical brain imaging method functional near-infrared spectroscopy (fNIRS) is a promising tool for real-time applications such as neurofeedback and brain-computer interfaces. Its combination of spatial specificity and mobility makes it particularly attractive for clinical use, both at the bedside and in patients' homes. Despite these advantages, optimizing fNIRS for real-time use requires careful attention to two key aspects: ensuring good spatial specificity and maintaining high signal quality. While fNIRS detects superficial cortical brain regions, consistently and reliably targeting specific regions of interest can be challenging, particularly in studies that require repeated measurements. Variations in cap placement coupled with limited anatomical information may further reduce this accuracy. Furthermore, it is important to maintain good signal quality in real-time contexts to ensure that they reflect the true underlying brain activity. However, fNIRS signals are susceptible to contamination by cerebral and extracerebral systemic noise as well as motion artifacts. Insufficient real-time preprocessing can therefore cause the system to run on noise instead of brain activity. The aim of this review article is to help advance the progress of fNIRS-based real-time applications. It highlights the potential challenges in improving spatial specificity and signal quality, discusses possible options to overcome these challenges, and addresses further considerations relevant to real-time applications. By addressing these topics, the article aims to help improve the planning and execution of future real-time studies, thereby increasing their reliability and repeatability.

Pre-processing of Sub-millimeter GE-BOLD fMRI Data for Laminar Applications.

Over the past 30 years, brain function has primarily been evaluated non-invasively using functional magnetic resonance imaging (fMRI) with gradient-echo (GE) sequences to measure blood-oxygen-level-dependent (BOLD) signals. Despite the multiple advantages of GE sequences, e.g., higher signal-to-noise ratio, faster acquisitions, etc., their relatively inferior spatial localization compromises the routine use of GE-BOLD in laminar applications. Here, in an attempt to rescue the benefits of GE sequences, we evaluated the effect of existing pre-processing methods on the spatial localization of signals obtained with EPIK, a GE sequence that affords voxel volumes of 0.25 mm3 with near whole-brain coverage. The methods assessed here apply to both task and resting-state fMRI data assuming the availability of reconstructed magnitude and phase images.

Attentional modulations of alpha power are sensitive to the task-relevance of auditory spatial information.

The topographical distribution of oscillatory power in the alpha band is known to vary depending on the current focus of spatial attention. Here, we investigated to what extend univariate and multivariate measures of post-stimulus alpha power are sensitive to the required spatial specificity of a task. To this end, we varied the perceptual load and the spatial demand in an auditory search paradigm. A centrally presented sound at the beginning of each trial indicated the to-be-localized target sound. This spatially unspecific pre-cue was followed by a sound array, containing either two (low perceptual load) or four (high perceptual load) simultaneously presented lateralized sound stimuli. In separate task blocks, participants were instructed either to report whether the target was located on the left or the right side of the sound array (low spatial demand) or to indicate the exact target location (high spatial demand). Univariate alpha lateralization magnitude was neither affected by perceptual load nor by spatial demand. However, an analysis of onset latencies revealed that alpha lateralization emerged earlier in low (vs high) perceptual load trials as well as in low (vs high) spatial demand trials. Finally, we trained a classifier to decode the specific target location based on the multivariate alpha power scalp topography. A comparison of decoding accuracy in the low and high spatial demand conditions suggests that the amount of spatial information present in the scalp distribution of alpha-band power increases as the task demands a higher degree of spatial specificity. Altogether, the results offer new insights into how the dynamic adaption of alpha-band oscillations in response to changing task demands is associated with post-stimulus attentional processing.

Selective Neuromodulation of the Vagus Nerve.

Vagus nerve stimulation (VNS) is an effective technique for the treatment of refractory epilepsy and shows potential for the treatment of a range of other serious conditions. However, until now stimulation has generally been supramaximal and non-selective, resulting in a range of side effects. Selective VNS (sVNS) aims to mitigate this by targeting specific fiber types within the nerve to produce functionally specific effects. In recent years, several key paradigms of sVNS have been developed-spatially selective, fiber-selective, anodal block, neural titration, and kilohertz electrical stimulation block-as well as various stimulation pulse parameters and electrode array geometries. sVNS can significantly reduce the severity of side effects, and in some cases increase efficacy of the treatment. While most studies have focused on fiber-selective sVNS, spatially selective sVNS has demonstrated comparable mitigation of side-effects. It has the potential to achieve greater specificity and provide crucial information about vagal nerve physiology. Anodal block achieves strong side-effect mitigation too, but is much less specific than fiber- and spatially selective paradigms. The major hurdle to achieving better selectivity of VNS is a limited knowledge of functional anatomical organization of vagus nerve. It is also crucial to optimize electrode array geometry and pulse shape, as well as expand the applications of sVNS beyond the current focus on cardiovascular disease.

Estimation of laminar BOLD activation profiles using deconvolution with a physiological point spread function.

BACKGROUND: The specificity of gradient echo (GE)-BOLD laminar fMRI activation profiles is degraded by intracortical veins that drain blood from lower to upper cortical layers, propagating activation signal in the same direction. This work describes an approach to obtain layer specific profiles by deconvolving the measured profiles with a physiological Point Spread Function (PSF). NEW METHOD: It is shown that the PSF can be characterised by a TE-dependent peak to tail (p2t) value that is independent of cortical depth and can be estimated by simulation. An experimental estimation of individual p2t values and the sensitivity of the deconvolved profiles to variations in p2t is obtained using laminar data measured with a multi-echo 3D-FLASH sequence. These profiles are echo time dependent, but the underlying neuronal response is the same, allowing a data-based estimation of the PSF. RESULTS: The deconvolved profiles are highly similar to the gold-standard obtained from extremely high resolution 3D-EPI data, for a range of p2t values of 5-9, which covers both the empirically determined value (6.8) and the value obtained by simulation (6.3). -Comparison with Existing Method(s) Corrected profiles show a flatter shape across the cortex and a high level of similarity with the gold-standard, defined as a subset of profiles that are unaffected by intracortical veins. CONCLUSIONS: We conclude that deconvolution is a robust approach for removing the effect of signal propagation through intracortical veins. This makes it possible to obtain profiles with high laminar specificity while benefitting from the higher efficiency of GE-BOLD sequences.

Forging a path to mesoscopic imaging success with ultra-high field functional magnetic resonance imaging.

Functional magnetic resonance imaging (fMRI) studies with ultra-high field (UHF, 7+ Tesla) technology enable the acquisition of high-resolution images. In this work, we discuss recent achievements in UHF fMRI at the mesoscopic scale, on the order of cortical columns and layers, and examine approaches to addressing common challenges. As researchers push to smaller and smaller voxel sizes, acquisition and analysis decisions have greater potential to degrade spatial accuracy, and UHF fMRI data must be carefully interpreted. We consider the impact of acquisition decisions on the spatial specificity of the MR signal with a representative dataset with 0.8 mm isotropic resolution. We illustrate the trade-offs in contrast with noise ratio and spatial specificity of different acquisition techniques and show that acquisition blurring can increase the effective voxel size by as much as 50% in some dimensions. We further describe how different sources of degradations to spatial resolution in functional data may be characterized. Finally, we emphasize that progress in UHF fMRI depends not only on scientific discovery and technical advancement, but also on informal discussions and documentation of challenges researchers face and overcome in pursuit of their goals. This article is part of the theme issue 'Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity'.

im6A-TS-CNN: Identifying the N6-Methyladenine Site in Multiple Tissues by Using the Convolutional Neural Network.

N6-methyladenosine (m6A) is the most abundant post-transcriptional modification and involves a series of important biological processes. Therefore, accurate detection of the m6A site is very important for revealing its biological functions and impacts on diseases. Although both experimental and computational methods have been proposed for identifying m6A sites, few of them are able to detect m6A sites in different tissues. With the consideration of the spatial specificity of m6A modification, it is necessary to develop methods able to detect the m6A site in different tissues. In this work, by using the convolutional neural network (CNN), we proposed a new method, called im6A-TS-CNN, that can identify m6A sites in brain, liver, kidney, heart, and testis of Homo sapiens, Mus musculus, and Rattus norvegicus. In im6A-TS-CNN, the samples were encoded by using the one-hot encoding scheme. The results from both a 5-fold cross-validation test and independent dataset test demonstrate that im6A-TS-CNN is better than the existing method for the same purpose. The command-line version of im6A-TS-CNN is available at https://github.com/liukeweiaway/DeepM6A_cnn.

Glia Promote Synaptogenesis through an IQGAP PES-7 in C. elegans.

Synapses are fundamental to the normal function of the nervous system. Glia play a pivotal role in regulating synaptic formation. However, how presynaptic neurons assemble synaptic structure in response to the glial signals remains largely unexplored. To address this question, we use cima-1 mutant C. elegans as an in vivo model, in which the astrocyte-like VCSC glial processes ectopically reach an asynaptic neurite region and promote presynaptic formation there. Through an RNAi screen, we find that the Rho GTPase CDC-42 and IQGAP PES-7 are required in presynaptic neurons for VCSC glia-induced presynaptic formation. In addition, we find that cdc-42 and pes-7 are also required for normal synaptogenesis during postembryonic developmental stages. PES-7 activated by CDC-42 promotes presynaptic formation, most likely through regulating F-actin assembly. Given the evolutionary conservation of CDC-42 and IQGAPs, we speculate that our findings in C. elegans apply to vertebrates.

Characterization and Comparison of Microbiota in the Gastrointestinal Tracts of the Goat (Capra hircus) During Preweaning Development.

Bacterial communities in gastrointestinal tracts (GIT) play an important role in animal health and performance. Despite its importance, little information is available on the establishment of microbial populations in the goat GIT or on changes occurring during early development. Therefore, this study investigated the bacterial community dynamics of the rumen, duodenum, jejunum, ileum, cecum, and colon in 15 goats at five developmental stages (0, 14, 28, 42, and 56 days old) by using 16S rDNA sequencing and quantitative real-time PCR technology. 940 genera were found to belong to 44 phyla distributed along the GIT. As a whole, the microbial richness and diversity showed a clear increasing trend as the kids aged and alpha diversity differed significantly among GIT compartments mainly occurring at middle day ages (14 and 28 days). Principal coordinate analysis indicated that the bacterial community displayed distinct temporal and spatial specificity along the GIT in preweaning goats. As kids aged, the phylum Firmicutes was replaced by Bacteroidetes in rumen, whereas Proteobacteria in the large intestine was displaced by Firmicutes. The phylum Proteobacteria was mainly present in the small intestine in older animals. In the rumen, taxa, such as Bacillus and Lactococcus decreased and Prevotella, Treponema, Ruminococcus, and unclassified Prevotellaceae increased with the age of kids. Furthermore, a lower proportion of taxa, such as Lactobacillus and Bacteroides was observed with higher abundances of both Christensenellaceae_R_7 and Ruminococcus in duodenum and jejunum in older animals. In the large intestine, the microbiota displayed taxonomic dynamics with increases of Ruminococcaceae UCG 005, unclassified Lachnospiraceae, Barnesiella, and Blautia as kids aged. Predicted pathway analysis suggested that genes involved in amino acid metabolism, and translation were abundant in both rumen and duodenum, while genes involved in membrane transport and carbohydrate metabolism were enriched in the large intestine. These results indicate that both the microbial colonization process and potential function exert a temporal-spatial specificity throughout the GIT of goats. This study provides new insight into the temporal dynamics of GIT microbiota development during preweaning and will aid to develop strategies for improving animal health and downstream production.

The Spatial Extent of Optogenetic Silencing in Transgenic Mice Expressing Channelrhodopsin in Inhibitory Interneurons.

Optogenetic stimulation of inhibitory interneurons has become a commonly used strategy for silencing neuronal activity. This is typically achieved using transgenic mice expressing excitatory opsins in inhibitory interneurons throughout the brain, raising the question of how spatially extensive the resulting inhibition is. Here, we characterize neuronal silencing in VGAT-ChR2 mice, which express channelrhodopsin-2 in inhibitory interneurons, as a function of light intensity and distance from the light source in several cortical and subcortical regions. We show that light stimulation, even at relatively low intensities, causes inhibition not only in brain regions targeted for silencing but also in their subjacent areas. In contrast, virus-mediated expression of an inhibitory opsin enables robust silencing that is restricted to the region of opsin expression. Our results reveal important constraints on using inhibitory interneuron activation to silence neuronal activity and emphasize the necessity of carefully controlling light stimulation parameters when using this silencing strategy.

Investigating the spatial specificity of S2-SSFP fMRI: A Monte Carlo simulation approach.

The desirable spatial specificity of spin echo (SE) fMRI cannot be efficiently utilized in high fields due to specific absorption rate (SAR) and B1 inhomogeneity problems. Consequently, S2-SSFP fMRI has been suggested as an alternative to mitigate these problems. Nevertheless, no accurate analysis has been performed thus far to evaluate spatial specificity of this technique. To study spatial specificity, we performed Monte Carlo simulations for evaluating the micro-vasculature contribution in functional contrast along with vessel size sensitivity estimations for a range of relevant imaging parameters. Results showed a spatial specificity at the level of SE fMRI. Simulations further revealed that similar to SE fMRI, an effective echo time (TE) close to the tissue T2 maximizes the micro-vasculature contribution in the obtained contrast. The amount of this contribution, however, showed a slight decrease at ultra-high fields compared to SE fMRI. As for vessel size sensitivity, simulations presented a pattern for S2-SSFP similar to SE fMRI but with a minor shift toward larger vessels. These results are in general agreement with reported experimental studies. Our findings also suggest that the effect of older pathways, rather than primary SE pathway, might be responsible for the observed discrepancies between S2 and SE. Based on this study, provided that optimum experimental parameters are used, S2, with its desirable micro-vasculature contribution and high sensitivity to small vessels, is a promising low SAR approach to replace SE fMRI in high field.

Optimized protocol for high resolution functional magnetic resonance imaging at 3T using single-shot echo planar imaging.

BACKGROUND: To translate highly accelerated EPI-fMRI protocols as commonly used at ultra-high field strengths to clinical 3T settings. NEW METHOD: EPI protocols with increasing matrix sizes and parallel imaging (PI) factors were tested in two separate fMRI studies, a simple motor-task and a complex motivation-task experiment with focus on the sensorimotor cortex (SMC) and the nucleus accumbens (NAcc), respectively. RESULTS: By increasing the matrix size and the PI-factor simultaneously, BOLD-sensitivity in terms of maximal t-values and numbers of activated clusters was uncompromised in single individuals in both fMRI experiments. In the SMC, the multi-subject analysis revealed an increase of 66% of the maximal t-value whereby the number of activated clusters was increased by a factor of 3.3 when the matrix size (PI-factor) was increased from 96×96 (R=2) to 192×192 (R=4). In the NAcc, the number of activated clusters increased from 5 to 7 whereby the maximal t-value remained unaffected when the matrix size (PI-factor) was increased from 96×96 (R=2) to 160×160 (R=3). COMPARISON WITH EXISTING METHOD: Using the proposed high-resolution EPI protocol, spatial blurring was clearly reduced. Further, BOLD sensitivity was clearly improved in multi-subject analyses and remained unaffected in single individuals compared to using the standard protocols. CONCLUSIONS: Conventionally used matrix sizes (PI-factors) might be non-optimal for some applications sacrificing BOLD spatial specificity. We recommend using the proposed high-resolution protocols applicable in detecting robust BOLD activation in fMRI.