Anxiety is a mental state characterized by an intense sense of tension, worry or apprehension, relative to something adverse that might happen in the future. Researchers differentiate aspects of ...anxiety into state and trait, respectively defined as a more transient reaction to an adverse situation, and as a more stable personality attribute in experiencing events. It is yet unclear whether brain structural and functional features may distinguish these aspects of anxiety. To study this, we assessed 42 healthy participants with the State-Trait Anxiety Inventory and then investigated with MRI to characterize structural grey matter covariance and resting-state functional connectivity (rs-FC). We found several differences in the structural-functional patterns across anxiety types: (1) trait anxiety was associated to both structural covariance of Default Mode Network (DMN), with an increase in dorsal nodes and a decrease in its ventral part, and to rs-FC of DMN within frontal regions; (2) state anxiety, instead, was widely related to rs-FC of Salience Network and of DMN, specifically in its ventral nodes, but not associated with any structural pattern. In conclusion, our study provides evidence of a neuroanatomical and functional distinction between state and trait anxiety. These neural features may be additional markers in future studies evaluating early diagnosis or treatment effects.
A successful method for removing artifacts from electroencephalogram (EEG) recordings is Independent Component Analysis (ICA), but its implementation remains largely user‐dependent. Here, we propose ...a completely automatic algorithm (ADJUST) that identifies artifacted independent components by combining stereotyped artifact‐specific spatial and temporal features. Features were optimized to capture blinks, eye movements, and generic discontinuities on a feature selection dataset. Validation on a totally different EEG dataset shows that (1) ADJUST's classification of independent components largely matches a manual one by experts (agreement on 95.2% of the data variance), and (2) Removal of the artifacted components detected by ADJUST leads to neat reconstruction of visual and auditory event‐related potentials from heavily artifacted data. These results demonstrate that ADJUST provides a fast, efficient, and automatic way to use ICA for artifact removal.
Diffusion MRI tractography allows in-vivo characterization of white matter architecture, including the localization and description of brain fibre bundles. However, some primary bundles are still ...only partially reconstructed, or not reconstructed at all. The acoustic radiation (AR) represents a primary sensory pathway that has been largely omitted in many tractography studies because its location and anatomical features make it challenging to reconstruct. In this study, we investigated the effects of acquisition and tractography parameters on the AR reconstruction using publicly available Human Connectome Project data. The aims of this study are: (i) using a subgroup of subjects and a reference AR for each subject, define an optimum set of parameters for AR reconstruction, and (ii) use the optimum parameters set on the full group to build a tractography-based atlas of the AR. Starting from the same data, the use of different acquisition and tractography parameters lead to very different AR reconstructions. Optimal results in terms of topographical accuracy and correspondence to the reference were obtained for probabilistic tractography, high b-values and default tractography parameters: these parameters were used to build an AR probabilistic tractography atlas. A significant left-hemispheric lateralization was found in the AR reconstruction of the 34 subjects.
Diffusion MRI (dMRI) has become one of the most important imaging modalities for noninvasively probing tissue microstructure. Diffusional Kurtosis MRI (DKI) quantifies the degree of non-Gaussian ...diffusion, which in turn has been shown to increase sensitivity towards, e.g., disease and orientation mapping in neural tissue. However, the specificity of DKI is limited as different sources can contribute to the total intravoxel diffusional kurtosis, including: variance in diffusion tensor magnitudes (Kiso), variance due to diffusion anisotropy (Kaniso), and microscopic kurtosis (μK) related to restricted diffusion, microstructural disorder, and/or exchange. Interestingly, μK is typically ignored in diffusion MRI signal modelling as it is assumed to be negligible in neural tissues. However, recently, Correlation Tensor MRI (CTI) based on Double-Diffusion-Encoding (DDE) was introduced for kurtosis source separation, revealing non negligible μK in preclinical imaging. Here, we implemented CTI for the first time on a clinical 3T scanner and investigated the sources of total kurtosis in healthy subjects. A robust framework for kurtosis source separation in humans is introduced, followed by estimation of μK (and the other kurtosis sources) in the healthy brain. Using this clinical CTI approach, we find that μK significantly contributes to total diffusional kurtosis both in grey and white matter tissue but, as expected, not in the ventricles. The first μK maps of the human brain are presented, revealing that the spatial distribution of μK provides a unique source of contrast, appearing different from isotropic and anisotropic kurtosis counterparts. Moreover, group average templates of these kurtosis sources have been generated for the first time, which corroborated our findings at the underlying individual-level maps. We further show that the common practice of ignoring μK and assuming the multiple Gaussian component approximation for kurtosis source estimation introduces significant bias in the estimation of other kurtosis sources and, perhaps even worse, compromises their interpretation. Finally, a twofold acceleration of CTI is discussed in the context of potential future clinical applications. We conclude that CTI has much potential for future in vivo microstructural characterizations in healthy and pathological tissue.
Recent evidence suggests that gains in performance observed while humans learn a novel motor sequence occur during the quiet rest periods interleaved with practice (micro-offline gains, MOGs). This ...phenomenon is reminiscent of memory replay observed in the hippocampus during spatial learning in rodents. Whether the hippocampus is also involved in the production of MOGs remains currently unknown. Using a multimodal approach in humans, here we show that activity in the hippocampus and the precuneus increases during the quiet rest periods and predicts the level of MOGs before asymptotic performance is achieved. These functional changes were followed by rapid alterations in brain microstructure in the order of minutes, suggesting that the same network that reactivates during the quiet periods of training undergoes structural plasticity. Our work points to the involvement of the hippocampal system in the reactivation of procedural memories
Longitudinal and multi-site clinical studies create the imperative to characterize and correct technological sources of variance that limit image reproducibility in high-resolution structural MRI ...studies, thus facilitating precise, quantitative, platform-independent, multi-site evaluation. In this work, we investigated the effects that imaging gradient non-linearity have on reproducibility of multi-site human MRI. We applied an image distortion correction method based on spherical harmonics description of the gradients and verified the accuracy of the method using phantom data. The correction method was then applied to the brain image data from a group of subjects scanned twice at multiple sites having different 1.5 T platforms. Within-site and across-site variability of the image data was assessed by evaluating voxel-based image intensity reproducibility. The image intensity reproducibility of the human brain data was significantly improved with distortion correction, suggesting that this method may offer improved reproducibility in morphometry studies. We provide the source code for the gradient distortion algorithm together with the phantom data.
Quantitative measurements of brain perfusion are influenced by perfusion-modifiers. Standardization of measurement conditions and correction for important modifiers is essential to improve accuracy ...and to facilitate the interpretation of perfusion-derived parameters. An extensive literature search was carried out for factors influencing quantitative measurements of perfusion in the human brain unrelated to medication use. A total of 58 perfusion modifiers were categorized into four groups. Several factors (e.g., caffeine, aging, and blood gases) were found to induce a considerable effect on brain perfusion that was consistent across different studies; for other factors, the modifying effect was found to be debatable, due to contradictory results or lack of evidence. Using the results of this review, we propose a standard operating procedure, based on practices already implemented in several research centers. Also, a theory of ‘deep MRI physiotyping’ is inferred from the combined knowledge of factors influencing brain perfusion as a strategy to reduce variance by taking both personal information and the presence or absence of perfusion modifiers into account. We hypothesize that this will allow to personalize the concept of normality, as well as to reach more rigorous and earlier diagnoses of brain disorders.
The auditory system of mammals is dedicated to encoding, elaborating and transporting acoustic information from the auditory nerve to the auditory cortex. The acoustic radiation (AR) constitutes the ...thalamo-cortical projection of this system, conveying the auditory signals from the medial geniculate nucleus (MGN) of the thalamus to the transverse temporal gyrus on the superior temporal lobe. While representing one of the major sensory pathways of the primate brain, the currently available anatomical information of this white matter bundle is quite limited in humans, thus constituting a notable omission in clinical and general studies on auditory processing and language perception. Tracing procedures in humans have restricted applications, and the
reconstruction of this bundle using diffusion tractography techniques remains challenging. Hence, a more accurate and reliable reconstruction of the AR is necessary for understanding the neurobiological substrates supporting audition and language processing mechanisms in both health and disease. This review aims to unite available information on the macroscopic anatomy and topography of the AR in humans and non-human primates. Particular attention is brought to the anatomical characteristics that make this bundle difficult to reconstruct using non-invasive techniques, such as diffusion-based tractography. Open questions in the field and possible future research directions are discussed.
In vivo MRI-derived measurements of human cerebral cortex thickness are providing novel insights into normal and abnormal neuroanatomy, but little is known about their reliability. We investigated ...how the reliability of cortical thickness measurements is affected by MRI instrument-related factors, including scanner field strength, manufacturer, upgrade and pulse sequence. Several data processing factors were also studied. Two test–retest data sets were analyzed: 1) 15 healthy older subjects scanned four times at 2-week intervals on three scanners; 2) 5 subjects scanned before and after a major scanner upgrade. Within-scanner variability of global cortical thickness measurements was <0.03 mm, and the point-wise standard deviation of measurement error was approximately 0.12 mm. Variability was 0.15 mm and 0.17 mm in average, respectively, for cross-scanner (Siemens/GE) and cross-field strength (1.5 T/3 T) comparisons. Scanner upgrade did not increase variability nor introduce bias. Measurements across field strength, however, were slightly biased (thicker at 3 T). The number of (single vs. multiple averaged) acquisitions had a negligible effect on reliability, but the use of a different pulse sequence had a larger impact, as did different parameters employed in data processing. Sample size estimates indicate that regional cortical thickness difference of 0.2 mm between two different groups could be identified with as few as 7 subjects per group, and a difference of 0.1 mm could be detected with 26 subjects per group. These results demonstrate that MRI-derived cortical thickness measures are highly reliable when MRI instrument and data processing factors are controlled but that it is important to consider these factors in the design of multi-site or longitudinal studies, such as clinical drug trials.
The BDNF Val66Met gene polymorphism is a relevant factor explaining inter-individual differences to TMS responses in studies of the motor system. However, whether this variant also contributes to ...TMS-induced memory effects, as well as their underlying brain mechanisms, remains unexplored. In this investigation, we applied rTMS during encoding of a visual memory task either over the left frontal cortex (LFC; experimental condition) or the cranial vertex (control condition). Subsequently, individuals underwent a recognition memory phase during a functional MRI acquisition. We included 43 young volunteers and classified them as 19 Met allele carriers and 24 as Val/Val individuals. The results revealed that rTMS delivered over LFC compared to vertex stimulation resulted in reduced memory performance only amongst Val/Val allele carriers. This genetic group also exhibited greater fMRI brain activity during memory recognition, mainly over frontal regions, which was positively associated with cognitive performance. We concluded that BDNF Val66Met gene polymorphism, known to exert a significant effect on neuroplasticity, modulates the impact of rTMS both at the cognitive as well as at the associated brain networks expression levels. This data provides new insights on the brain mechanisms explaining cognitive inter-individual differences to TMS, and may inform future, more individually-tailored rTMS interventions.
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