Radiation damping at clinical field strength: Characterization and compensation in quantitative measurements.

PURPOSE: In any MR experiment, the bulk magnetization acts on itself, caused by the induced current in the RF receiver circuit that generates an oscillating damping field. This effect, known as "radiation damping" (RD), is usually weak and, therefore, unconsidered in MRI, but can affect quantitative studies performed with dedicated coils that provide a high SNR. The current work examined RD in a setup for investigations of small tissue specimens including a quantitative characterization of the spin-coil system. THEORY AND METHODS: A custom-made Helmholtz coil (radius and spacing 16 mm) was interfaced to a transmit-receive (Tx/Rx) switch with integrated passive feedback for modulation or suppression of RD similar to preamplifier decoupling. Pulse sequences included pulse-width arrays to demonstrate the absence/ presence of RD and difference techniques employing gradient pulses or composite RF pulses to quantify RD effects during free precession and transmission, respectively. Experiments were performed at 3T in small samples of MnCl2 solution. RESULTS: Significant RD effects may impact RF pulse application and evolution periods. Effective damping time constants were comparable to typical T2 * times or echo spacings in multi-echo sequences. Measurements of the phase relation showed that deviations from the commonly assumed 90° angle between the damping field and the transverse magnetization may occur. CONCLUSION: Radiation damping may affect the accuracy of quantitative MR measurements performed with dedicated RF coils. Efficient mitigation can be achieved hardware-based or by appropriate consideration in the pulse sequence.

High angular resolution susceptibility imaging and estimation of fiber orientation distribution functions in primate brain.

Uncovering brain-tissue microstructure including axonal characteristics is a major neuroimaging research focus. Within this scope, anisotropic properties of magnetic susceptibility in white matter have been successfully employed to estimate primary axonal trajectories using mono-tensorial models. However, anisotropic susceptibility has not yet been considered for modeling more complex fiber structures within a voxel, such as intersecting bundles, or an estimation of orientation distribution functions (ODFs). This information is routinely obtained by high angular resolution diffusion imaging (HARDI) techniques. In applications to fixed tissue, however, diffusion-weighted imaging suffers from an inherently low signal-to-noise ratio and limited spatial resolution, leading to high demands on the performance of the gradient system in order to mitigate these limitations. In the current work, high angular resolution susceptibility imaging (HARSI) is proposed as a novel, phase-based methodology to estimate ODFs. A multiple gradient-echo dataset was acquired in an entire fixed chimpanzee brain at 61 orientations by reorienting the specimen in the magnetic field. The constant solid angle method was adapted for estimating phase-based ODFs. HARDI data were also acquired for comparison. HARSI yielded information on whole-brain fiber architecture, including identification of peaks of multiple bundles that resembled features of the HARDI results. Distinct differences between both methods suggest that susceptibility properties may offer complementary microstructural information. These proof-of-concept results indicate a potential to study the axonal organization in post-mortem primate and human brain at high resolution.

High-resolution magnetization-transfer imaging of post-mortem marmoset brain: Comparisons with relaxometry and histology.

Cell membranes and macromolecules or paramagnetic compounds interact with water proton spins, which modulates magnetic resonance imaging (MRI) contrast providing information on tissue composition. For a further investigation, quantitative magnetization transfer (qMT) parameters (at 3T), including the ratio of the macromolecular and water proton pools, F, and the exchange-rate constant as well as the (observed) longitudinal and the effective transverse relaxation rates (at 3T and 7T), R1obs and R2*, respectively, were measured at high spatial resolution (200 µm) in a slice of fixed marmoset brain and compared to histology results obtained with Gallyas' myelin stain and Perls' iron stain. R1obs and R2* were linearly correlated with the iron content for the entire slice, whereas distinct differences were obtained between gray and white matter for correlations of relaxometry and qMT parameters with myelin content. The combined results suggest that the macromolecular pool interacting with water consists of myelin and (less efficient) non-myelin contributions. Despite strong correlation of F and R1obs, none of these parameters was uniquely specific to myelination. Due to additional sensitivity to iron stores, R1obs and R2* were more sensitive for depicting microstructural differences between cortical layers than F.

Macromolecular background signal and non-Gaussian metabolite diffusion determined in human brain using ultra-high diffusion weighting.

PURPOSE: Definition of a macromolecular MR spectrum based on diffusion properties rather than relaxation time differences and characterization of non-Gaussian diffusion of brain metabolites with strongly diffusion-weighted MR spectroscopy. METHODS: Short echo time MRS with strong diffusion-weighting with b-values up to 25 ms/µm2 at two diffusion times was implemented on a Connectom system and applied in combination with simultaneous spectral and diffusion decay modeling. Motion-compensation was performed with a combined method based on the simultaneously acquired water and a macromolecular signal. RESULTS: The motion compensation scheme prevented spurious signal decay reflected in very small apparent diffusion constants for macromolecular signal. Macromolecular background signal patterns were determined using multiple fit strategies. Signal decay corresponding to non-Gaussian metabolite diffusion was represented by biexponential fit models yielding parameter estimates for human gray matter that are in line with published rodent data. The optimal fit strategies used constraints for the signal decay of metabolites with limited signal contributions to the overall spectrum. CONCLUSION: The determined macromolecular spectrum based on diffusion properties deviates from the conventional one derived from longitudinal relaxation time differences calling for further investigation before use as experimental basis spectrum when fitting clinical MR spectra. The biexponential characterization of metabolite signal decay is the basis for investigations into pathologic alterations of microstructure.

Modulation of premotor cortex response to sequence motor learning during escitalopram intake.

The contribution of selective serotonin reuptake inhibitors to motor learning by inducing motor cortical plasticity remains controversial given diverse findings from positive preclinical data to negative findings in recent clinical trials. To empirically address this translational disparity, we use functional magnetic resonance imaging in a double-blind, randomized controlled study to assess whether 20 mg escitalopram improves sequence-specific motor performance and modulates cortical motor response in 64 healthy female participants. We found decreased left premotor cortex responses during sequence-specific learning performance comparing single dose and steady escitalopram state. Escitalopram plasma levels negatively correlated with the premotor cortex response. We did not find evidence in support of improved motor performance after a week of escitalopram intake. These findings do not support the conclusion that one week escitalopram intake increases motor performance but could reflect early adaptive plasticity with improved neural processing underlying similar task performance when steady peripheral escitalopram levels are reached.

Reduced Olfactory Bulb Volume in Obesity and Its Relation to Metabolic Health Status.

Smell perception plays an important role in eating behavior and might be involved in body weight gain. Since a body of literature implies that olfactory perception and function is hampered in obesity, we here investigate neuroanatomical correlates of this phenomenon. We assessed olfactory bulb (OB) volume with magnetic resonance imaging in 67 healthy participants with a body mass index (BMI) from 18.9 to 45.4 kg/m2 (mean = 28.58 ± 6.64). Moreover, we obtained psychophysiological data on olfactory ability (Sniffin' Sticks, Food associated odor test) and self-report measurements on eating behavior. Additionally, we collected parameters associated with metabolic health in obesity (waist-hip ratio, waist-height ratio, leptin levels, body fat percentage, fat mass index, insulin resistance) to investigate recently proposed mechanistic explanatory models of why olfaction may be altered in obesity. We showed that OB volume was significantly lower in participants with obesity when compared to those of normal weight. Moreover, we found weak to moderate negative correlations between OB volume and BMI and related measures of metabolic health, especially leptin, body fat percentage, waist-height ratio and insulin resistance. However, neither OB volume nor BMI were related to olfactory function in our young and healthy sample. Nevertheless, our results provide first indications that obesity is associated with brain anatomical changes in the OBs.

Alexithymia and automatic processing of facial emotions: behavioral and neural findings.

BACKGROUND: Alexithymia is a personality trait characterized by difficulties identifying and describing feelings, an externally oriented style of thinking, and a reduced inclination to imagination. Previous research has shown deficits in the recognition of emotional facial expressions in alexithymia and reductions of brain responsivity to emotional stimuli. Using an affective priming paradigm, we investigated automatic perception of facial emotions as a function of alexithymia at the behavioral and neural level. In addition to self-report scales, we applied an interview to assess alexithymic tendencies. RESULTS: During 3 T fMRI scanning, 49 healthy individuals judged valence of neutral faces preceded by briefly shown happy, angry, fearful, and neutral facial expressions. Alexithymia was assessed using the 20-Item Toronto Alexithymia Scale (TAS-20), the Bermond-Vorst Alexithymia Questionnaire (BVAQ) and the Toronto Structured Interview for Alexithymia (TSIA). As expected, only negative correlations were found between alexithymic features and affective priming. The global level of self-reported alexithymia (as assessed by the TAS-20 and the BVAQ) was found to be related to less affective priming owing to angry faces. At the facet level, difficulties identifying feelings, difficulties analyzing feelings, and impoverished fantasy (as measured by the BVAQ) were correlated with reduced affective priming due to angry faces. Difficulties identifying feelings (BVAQ) correlated also with reduced affective priming due to fearful faces and reduced imagination (TSIA) was related to decreased affective priming due to happy faces. There was only one significant correlation between alexithymia dimensions and automatic brain response to masked facial emotions: TAS-20 alexithymia correlated with heightened brain response to masked happy faces in superior and medial frontal areas. CONCLUSIONS: Our behavioral results provide evidence that alexithymic features are related in particular to less sensitivity for covert facial expressions of anger. The perceptual alterations could reflect impaired automatic recognition or integration of social anger signals into judgemental processes and might contribute to the problems in interpersonal relationships associated with alexithymia. Our findings suggest that self-report measures of alexithymia may have an advantage over interview-based tests as research tools in the field of emotion perception at least in samples of healthy individuals characterized by rather low levels of alexithymia.

A mind-brain-body dataset of MRI, EEG, cognition, emotion, and peripheral physiology in young and old adults.

We present a publicly available dataset of 227 healthy participants comprising a young (N=153, 25.1±3.1 years, range 20-35 years, 45 female) and an elderly group (N=74, 67.6±4.7 years, range 59-77 years, 37 female) acquired cross-sectionally in Leipzig, Germany, between 2013 and 2015 to study mind-body-emotion interactions. During a two-day assessment, participants completed MRI at 3 Tesla (resting-state fMRI, quantitative T1 (MP2RAGE), T2-weighted, FLAIR, SWI/QSM, DWI) and a 62-channel EEG experiment at rest. During task-free resting-state fMRI, cardiovascular measures (blood pressure, heart rate, pulse, respiration) were continuously acquired. Anthropometrics, blood samples, and urine drug tests were obtained. Psychiatric symptoms were identified with Standardized Clinical Interview for DSM IV (SCID-I), Hamilton Depression Scale, and Borderline Symptoms List. Psychological assessment comprised 6 cognitive tests as well as 21 questionnaires related to emotional behavior, personality traits and tendencies, eating behavior, and addictive behavior. We provide information on study design, methods, and details of the data. This dataset is part of the larger MPI Leipzig Mind-Brain-Body database.

Semi-automated generation of individual computational models of the human head and torso from MR images.

PURPOSE: Simulating the interaction of the human body with electromagnetic fields is an active field of research. Individualized models are increasingly being used, as anatomical differences affect the simulation results. We introduce a processing pipeline for creating individual surface-based models of the human head and torso for application in simulation software based on unstructured grids. The pipeline is designed for easy applicability and is publicly released on figshare. METHODS: The pipeline covers image acquisition, segmentation, generation of segmentation masks, and surface mesh generation of the single, external boundary of each structure of interest. Two gradient-echo sequences are used for image acquisition. Structures of the head and body are segmented using several atlas-based approaches. They consist of bone/skull, subarachnoid cerebrospinal fluid, gray matter, white matter, spinal cord, lungs, the sinuses of the skull, and a combined class of all other structures including skin. After minor manual preparation, segmentation images are processed to segmentation masks, which are binarized images per segmented structure free of misclassified voxels and without an internal boundary. The proposed workflow is applied to 2 healthy subjects. RESULTS: Individual differences of the subjects are well represented. The models are proven to be suitable for simulation of the RF electromagnetic field distribution. CONCLUSION: Image segmentation, creation of segmentation masks, and surface mesh generation are highly automated. Manual interventions remain for preparing the segmentation images prior to segmentation mask generation. The generated surfaces exhibit a single boundary per structure and are suitable inputs for simulation software.

A new approach to Z-spectrum acquisition: prospective baseline enhancement (PROBE) for CEST/Nuclear Overhauser Effect.

PURPOSE: To develop a prospective baseline enhancement that compensates for intermingled background effects in Z-spectra to achieve sensitivity enhancement of peaks related to CEST and nuclear Overhauser effect. METHODS: An MRI sequence-specific compensation of background effects is achieved through variation of the pulsed saturation power, ω1,max , with the chemical shift, δ . After a "scout acquisition" of a standard Z-spectrum, the background is modeled through an appropriate spin system. Subsequently, an optimization procedure yields ω1,max(δ) values that compensate for background contributions yielding a flat baseline. Contributions from metabolites not considered in the optimization procedure are enhanced as distinct perturbations to the baseline. For experimental verification, mapping of the lactate concentration in the presence of cross-linked bovine serum albumin was performed in phantoms at 7 T. As proof of concept, explorative experiments were performed in healthy human subjects at 3 T. RESULTS: Nuisance contributions from direct water saturation, macromolecular magnetization transfer, and exchanging background protons were successfully removed from the Z-spectrum in phantoms and in brain tissue. The lactate methyl, methine, and hydroxyl peaks were readily observable in vitro. The peak areas correlated linearly with known concentrations. Improvement of the detection limit was achieved by a sparse distribution of saturation frequencies, allowing for more efficient signal averaging. CONCLUSION: An optimization framework for high-resolution metabolite mapping by means of CEST/nuclear Overhauser effect was developed. It offers full flexibility to select spin-pool moieties, whose influence on the Z-spectrum will be compensated. Deviations from this background model will provide a contrast at the respective offset frequencies.

Pathological glutamatergic neurotransmission in Gilles de la Tourette syndrome.

Gilles de la Tourette syndrome is a hereditary, neuropsychiatric movement disorder with reported abnormalities in the neurotransmission of dopamine and γ-aminobutyric acid (GABA). Spatially focalized alterations in excitatory, inhibitory and modulatory neurochemical ratios within specific functional subdivisions of the basal ganglia, may lead to the expression of diverse motor and non-motor features as manifested in Gilles de la Tourette syndrome. Current treatment strategies are often unsatisfactory thus provoking the need for further elucidation of the underlying pathophysiology. In view of (i) the close spatio-temporal synergy exhibited between excitatory, inhibitory and modulatory neurotransmitter systems; (ii) the crucial role played by glutamate (Glu) in tonic/phasic dopaminergic signalling; and (iii) the interdependent metabolic relationship exhibited between Glu and GABA via glutamine (Gln); we postulated that glutamatergic signalling is related to the pathophysiology of Gilles de la Tourette syndrome. As such, we examined the neurochemical profile of three cortico-striato-thalamo-cortical regions in 37 well-characterized, drug-free adult patients and 36 age/gender-matched healthy control subjects via magnetic resonance spectroscopy at 3 T. To interrogate the influence of treatment on metabolite concentrations, spectral data were acquired from 15 patients undergoing a 4-week treatment with aripiprazole. Test-retest reliability measurements in 23 controls indicated high repeatability of voxel localization and metabolite quantitation. We report significant reductions in striatal concentrations of Gln, Glu + Gln (Glx) and the Gln:Glu ratio, and thalamic concentrations of Glx in Gilles de la Tourette syndrome in comparison to controls. ON-treatment patients exhibited no significant metabolite differences when compared to controls but significant increases in striatal Glu and Glx, and trends for increases in striatal Gln and thalamic Glx compared to baseline measurements. Multiple regression analysis revealed a significant negative correlation between (i) striatal Gln and actual tic severity; and (ii) thalamic Glu and premonitory urges. Our results indicate that patients with Gilles de la Tourette syndrome exhibit an abnormality in the flux of metabolites in the GABA-Glu-Gln cycle, thus implying perturbations in astrocytic-neuronal coupling systems that maintain the subtle balance between excitatory and inhibitory neurotransmission within subcortical nuclei.

In-vivo Dynamics of the Human Hippocampus across the Menstrual Cycle.

Sex hormones fluctuate during the menstrual cycle. Evidence from animal studies suggests similar subtle fluctuations in hippocampal structure, predominantly linked to estrogen. Hippocampal abnormalities have been observed in several neuropsychiatric pathologies with prominent sexual dimorphism. Yet, the potential impact of subtle sex-hormonal fluctuations on human hippocampal structure in health is unclear. We tested the feasibility of longitudinal neuroimaging in conjunction with rigorous menstrual cycle monitoring to evaluate potential changes in hippocampal microstructure associated with physiological sex-hormonal changes. Thirty longitudinal diffusion weighted imaging scans of a single healthy female subject were acquired across two full menstrual cycles. We calculated hippocampal fractional anisotropy (FA), a measure sensitive to changes in microstructural integrity, and investigated potential correlations with estrogen. We observed a significant positive correlation between FA values and estrogen in the hippocampus bilaterally, revealing a peak in FA closely paralleling ovulation. This exploratory, single-subject study demonstrates the feasibility of a longitudinal DWI scanning protocol across the menstrual cycle and is the first to link subtle endogenous hormonal fluctuations to changes in FA in vivo. In light of recent attempts to neurally phenotype single humans, our findings highlight menstrual cycle monitoring in parallel with highly sampled individual neuroimaging data to address fundamental questions about the dynamics of plasticity in the adult brain.

"Eyes Open - Eyes Closed" EEG/fMRI data set including dedicated "Carbon Wire Loop" motion detection channels.

This data set contains electroencephalography (EEG) data as well as simultaneous EEG with functional magnetic resonance imaging (EEG/fMRI) data. During EEG/fMRI, the EEG cap was outfitted with a hardware-based add-on consisting of carbon-wire loops (CWL). These yielded six extra׳CWL׳ signals related to Faraday induction of these loops in the main magnetic field "Measurement and reduction of motion and ballistocardiogram artefacts from simultaneous EEG and fMRI recordings" (Masterton et al., 2007) [1]. In this data set, the CWL data make it possible to do a direct regression approach to deal with the BCG and specifically He artifact. The CWL-EEG/fMRI data in this paper has been recorded on two MRI scanners with different Helium pump systems (4 subjects on a 3 T TIM Trio and 4 subjects on a 3T VERIO). Separate EEG/fMRI data sets have been recorded for the helium pump ON as well as the helium pump OFF conditions. The EEG-only data (same subjects) has been recorded for a motion artifact-free reference EEG signal outside of the scanner. This paper also links to an EEGlab "EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis" (Delorme and Makeig, 2004) [2] plugin to perform a CWL regression approach to deal with the He pump artifact, as published in the main paper "Carbon-wire loop based artifact correction outperforms post-processing EEG/fMRI corrections-A validation of a real-time simultaneous EEG/fMRI correction method" (van der Meer et al., 2016) [3].

Carbon-wire loop based artifact correction outperforms post-processing EEG/fMRI corrections--A validation of a real-time simultaneous EEG/fMRI correction method.

Simultaneous EEG-fMRI combines two powerful neuroimaging techniques, but the EEG signal suffers from severe artifacts in the MRI environment that are difficult to remove. These are the MR scanning artifact and the blood-pulsation artifact--strategies to remove them are a topic of ongoing research. Additionally large, unsystematic artifacts are produced across the full frequency spectrum by the magnet's helium pump (and ventilator) systems which are notoriously hard to remove. As a consequence, experimenters routinely deactivate the helium pump during simultaneous EEG-fMRI acquisitions which potentially risks damaging the MRI system and necessitates more frequent and expensive helium refills. We present a novel correction method addressing both helium pump and ballisto-cardiac (BCG) artifacts, consisting of carbon-wire loops (CWL) as additional sensors to accurately track unpredictable artifacts related to subtle movements in the scanner, and an EEGLAB plugin to perform artifact correction. We compare signal-to-noise metrics of EEG data, corrected with CWL and three conventional correction methods, for helium pump off and on measurements. Because the CWL setup records signals in real-time, it fits requirements of applications where immediate correction is necessary, such as neuro-feedback applications or stimulation time-locked to specific sleep oscillations. The comparison metrics in this paper relate to: (1) the EEG signal itself, (2) the "eyes open vs. eyes closed" effect, and (3) an assessment of how the artifact corrections impacts the ability to perform meaningful correlations between EEG alpha power and the BOLD signal. Results show that the CWL correction corrects for He pump artifact and also produces EEG data more comparable to EEG obtained outside the magnet than conventional post-processing methods.

Orientation dependence of magnetization transfer parameters in human white matter.

Quantification of magnetization-transfer (MT) experiments is typically based on a model comprising a liquid pool "a" of free water and a semisolid pool "b" of motionally restricted macromolecules or membrane compounds. By a comprehensive fitting approach, high quality MT parameter maps of the human brain are obtained. In particular, a distinct correlation between the diffusion-tensor orientation with respect to the B0-magnetic field and the apparent transverse relaxation time, T2(b), of the semisolid pool (i.e., the width of its absorption line) is observed. This orientation dependence is quantitatively explained by a refined dipolar lineshape for pool b that explicitly considers the specific geometrical arrangement of lipid bilayers wrapped around a cylindrical axon. The model inherently reduces the myelin membrane to its lipid constituents, which is motivated by previous studies on efficient interaction sites (e.g., cholesterol or galactocerebrosides) in the myelin membrane and on the origin of ultrashort T2 signals in cerebral white matter. The agreement between MT orientation effects and corresponding forward simulations using empirical diffusion imaging results as input as well as results from fits employing the novel lineshape support previous suggestions that the fiber orientation distribution in a voxel can be modeled as a scaled Bingham distribution.

Automatic emotion processing as a function of trait emotional awareness: an fMRI study.

It is unclear whether reflective awareness of emotions is related to extent and intensity of implicit affective reactions. This study is the first to investigate automatic brain reactivity to emotional stimuli as a function of trait emotional awareness. To assess emotional awareness the Levels of Emotional Awareness Scale (LEAS) was administered. During scanning, masked happy, angry, fearful and neutral facial expressions were presented to 46 healthy subjects, who had to rate the fit between artificial and emotional words. The rating procedure allowed assessment of shifts in implicit affectivity due to emotion faces. Trait emotional awareness was associated with increased activation in the primary somatosensory cortex, inferior parietal lobule, anterior cingulate gyrus, middle frontal and cerebellar areas, thalamus, putamen and amygdala in response to masked happy faces. LEAS correlated positively with shifts in implicit affect caused by masked happy faces. According to our findings, people with high emotional awareness show stronger affective reactivity and more activation in brain areas involved in emotion processing and simulation during the perception of masked happy facial expression than people with low emotional awareness. High emotional awareness appears to be characterized by an enhanced positive affective resonance to others at an automatic processing level.

Alexithymic features and the labeling of brief emotional facial expressions - An fMRI study.

The ability to recognize subtle facial expressions can be valuable in social interaction to infer emotions and intentions of others. Research has shown that the personality trait of alexithymia is linked to difficulties labeling facial expressions especially when these are presented with temporal constraints. The present study investigates the neural mechanisms underlying this deficit. 50 young healthy volunteers had to label briefly presented (≤100ms) emotional (happy, angry, fearful) facial expressions masked by a neutral expression while undergoing functional magnetic resonance imaging (fMRI). A multi-method approach (20-Item Toronto Alexithymia Scale and Toronto Structured Interview for Alexithymia) was administered to assess alexithymic tendencies. Behavioral results point to a global deficit of alexithymic individuals in labeling brief facial expressions. Alexithymia was related to decreased response of the ventral striatum to negative facial expressions. Moreover, alexithymia was associated with lowered activation in frontal, temporal and occipital cortices. Our data suggest that alexithymic individuals have difficulties in creating appropriate representations of the emotional state of other persons under temporal constraints. These deficiencies could lead to problems in labeling other people׳s facial emotions.

Serotonergic modulation of intrinsic functional connectivity.

Serotonin functions as an essential neuromodulator that serves a multitude of roles, most prominently balancing mood. Serotonergic challenge has been observed to reduce intrinsic functional connectivity in brain regions implicated in mood regulation. However, the full scope of serotonergic action on functional connectivity in the human brain has not been explored. Here, we show evidence that a single dose of a serotonin reuptake inhibitor dramatically alters functional connectivity throughout the whole brain in healthy subjects (n = 22). Our network-centrality analysis reveals a widespread decrease in connectivity in most cortical and subcortical areas. In the cerebellum and thalamus, however, we find localized increases. These rapid and brain-encompassing connectivity changes linked to acute serotonin transporter blockade suggest a key role for the serotonin transporter in the modulation of the functional macroscale connectome.

Alexithymia and the labeling of facial emotions: response slowing and increased motor and somatosensory processing.

BACKGROUND: Alexithymia is a personality trait that is characterized by difficulties in identifying and describing feelings. Previous studies have shown that alexithymia is related to problems in recognizing others' emotional facial expressions when these are presented with temporal constraints. These problems can be less severe when the expressions are visible for a relatively long time. Because the neural correlates of these recognition deficits are still relatively unexplored, we investigated the labeling of facial emotions and brain responses to facial emotions as a function of alexithymia. RESULTS: Forty-eight healthy participants had to label the emotional expression (angry, fearful, happy, or neutral) of faces presented for 1 or 3 seconds in a forced-choice format while undergoing functional magnetic resonance imaging. The participants' level of alexithymia was assessed using self-report and interview. In light of the previous findings, we focused our analysis on the alexithymia component of difficulties in describing feelings. Difficulties describing feelings, as assessed by the interview, were associated with increased reaction times for negative (i.e., angry and fearful) faces, but not with labeling accuracy. Moreover, individuals with higher alexithymia showed increased brain activation in the somatosensory cortex and supplementary motor area (SMA) in response to angry and fearful faces. These cortical areas are known to be involved in the simulation of the bodily (motor and somatosensory) components of facial emotions. CONCLUSION: The present data indicate that alexithymic individuals may use information related to bodily actions rather than affective states to understand the facial expressions of other persons.

Impact of image acquisition on voxel-based-morphometry investigations of age-related structural brain changes.

A growing number of magnetic resonance imaging studies employ voxel-based morphometry (VBM) to assess structural brain changes. Recent reports have shown that image acquisition parameters may influence VBM results. For systematic evaluation, gray-matter-density (GMD) changes associated with aging were investigated by VBM employing acquisitions with different radiofrequency head coils (12-channel matrix coil vs. 32-channel array), different pulse sequences (MP-RAGE vs. MP2RAGE), and different voxel dimensions (1mm vs. 0.8mm). Thirty-six healthy subjects, classified as young, middle-aged, or elderly, participated in the study. Two-sample and paired t-tests revealed significant effects of acquisition parameters (coil, pulse sequence, and resolution) on the estimated age-related GMD changes in cortical and subcortical regions. Potential advantages in tissue classification and segmentation were obtained for MP2RAGE. The 32-channel coil generally outperformed the 12-channel coil, with more benefit for MP2RAGE. Further improvement can be expected from higher resolution if the loss in SNR is accounted for. Use of inconsistent acquisition parameters in VBM analyses is likely to introduce systematic bias. Overall, acquisition and protocol changes require careful adaptations of the VBM analysis strategy before generalized conclusion can be drawn.