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The insula is a multimodal sensory integration structure that, in addition to serving as a gateway between somatosensory areas and limbic structures, plays a crucial role in autonomic nervous system function. While anatomical studies following the development of the insula have been conducted, currently, no studies have been published in human fetuses tracking the development of neuronal migration or of white matter tracts in the cortex. In this study, we aimed to follow the neuronal migration and subsequent maturation of axons in and around the insula in human fetal ages. Using high-angular resolution diffusion magnetic resonance imaging tractography, major white matter pathways to/from the insula and its surrounding operculum were identified at a number of time points during human gestation. Pathways likely linked to neuronal migration from the ventricular zone to the inferior frontal gyrus, superior temporal region, and the insular cortex were detected in the earliest gestational age studied (15 GW). Tractography reveals neuronal migration to areas surrounding the insula occurred at different time points. These results, in addition to demonstrating key time points for neuronal migration, suggest that neurons and axonal fiber pathways underlying the insula and its surrounding gyri mature differentially despite their relationship during cortical folding.

The lack of multivariate methods for decoding the representational content of interregional neural communication has left it difficult to know what information is represented in distributed brain circuit interactions. Here we present Multi-Connection Pattern Analysis (MCPA), which works by learning mappings between the activity patterns of the populations as a factor of the information being processed. These maps are used to predict the activity from one neural population based on the activity from the other population. Successful MCPA-based decoding indicates the involvement of distributed computational processing and provides a framework for probing the representational structure of the interaction. Simulations demonstrate the efficacy of MCPA in realistic circumstances. In addition, we demonstrate that MCPA can be applied to different signal modalities to evaluate a variety of hypothesis associated with information coding in neural communications. We apply MCPA to fMRI and human intracranial electrophysiological data to provide a proof-of-concept of the utility of this method for decoding individual natural images and faces in functional connectivity data. We further use a MCPA-based representational similarity analysis to illustrate how MCPA may be used to test computational models of information transfer among regions of the visual processing stream. Thus, MCPA can be used to assess the information represented in the coupled activity of interacting neural circuits and probe the underlying principles of information transformation between regions.

The blood oxygen level dependent (BOLD) signal, as measured using functional magnetic resonance imaging (fMRI), is widely used as a proxy for changes in neural activity in the brain. Physiological variables such as heart rate (HR) and respiratory variation (RV) affect the BOLD signal in a way that may interfere with the estimation and detection of true task-related neural activity. This interference is of particular concern when these variables themselves show task-related modulations. We first establish that a simple movement task reliably induces a change in HR but not RV. In group data, the effect of HR on the BOLD response was larger and more widespread throughout the brain than were the effects of RV or phase regressors. The inclusion of HR regressors, but not RV or phase regressors, had a small but reliable effect on the estimated hemodynamic response function (HRF) in M1 and the cerebellum. We next asked whether the inclusion of a nested set of physiological regressors combining phase, RV, and HR significantly improved the model fit in individual participants' data sets. There was a significant improvement from HR correction in M1 for the greatest number of participants, followed by RV and phase correction. These improvements were more modest in the cerebellum. These results indicate that accounting for task-related modulation of physiological variables can improve the detection and estimation of true neural effects of interest.

Jiong Tao,1,2 Xianglan Wang,2 Zhiyong Zhong,1,2 Hongying Han,2 Sha Liu,3 Shenglin Wen,4 Nianhong Guan,2 Lingjiang Li1 1Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, 2Department of Psychiatry, The Third Affiliated Hospital of Sun Yat-sen University, 3Department of Radiology, Guangzhou Huiai Hospital, Guangzhou, 4Department of Psychiatry, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, People’s Republic of China Background: Abnormalities in white matter (WM) have previously been reported in patients with obsessive–compulsive disorder (OCD). However, there was some inconsistency in the results obtained for altered regions of WM. The aim of this study was to investigate fractional anisotropy (FA) in the WM of the whole brain in patients with OCD by using diffusion tensor imaging (DTI).Methods: In total, 28 unmedicated patients with OCD and 28 healthy volunteers underwent DTI scan. A voxel-based analysis was used to compare FA values in WM of the two groups at a voxel threshold of P<0.005 with an extent threshold of k>72 voxels (P<0.05; Alphasim correction). Subsequently, correlation analysis was conducted in order to find the correlation between the mean FA values in significantly altered brain regions and Yale–Brown Obsessive Compulsive Scale (Y-BOCS) scores of the OCD patients.Results: Compared with healthy volunteers, the OCD patients had lower FA value in the left lingual gyrus, right midbrain, and right precuneus. There were no regions with significantly higher FA values in OCD patients compared with healthy volunteers. The mean FA values in the above regions (left lingual, r=0.019, P=0.923; right midbrain, r=-0.208, P=0.289; and right precuneus, r=-0.273, P=0.161) had no significant correlation with the Y-BOCS scores of the OCD patients.Conclusion: The findings of this study suggest that alterations in WM of the left lingual gyrus, right midbrain, and right precuneus are associated with the pathophysiology mechanism of OCD, and these microstructural alterations do not correlate with symptom severity of OCD. Keywords: white matter, diffusion tensor imaging, fractional anisotropy, obsessive–compulsive disorder

© 2020, This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply. Purpose of Review: This paper aims to review novel trends in cholinergic neuroimaging in Alzheimer and Lewy body parkinsonian disorders. Recent Findings: The spectrum of cholinergic imaging is expanding with the availability of spatially more precise radioligands that allow assessment of previously less recognized subcortical and cortical structures with more dense cholinergic innervation. In addition, advances in MRI techniques now allow quantitative structural or functional assessment of both the cholinergic forebrain and the pedunculopontine nucleus, which may serve as non-invasive prognostic predictors. Multimodal imaging approaches, such as PET-MRI or multiligand PET, offer new insights into the dynamic and interactive roles of the cholinergic system at both local and larger-scale neural network levels. Summary: Our understanding of the heterogeneous roles of the cholinergic system in age-related diseases is evolving. Multimodal imaging approaches that provide complimentary views of the cholinergic system will be necessary to shed light on the impact of cholinergic degeneration on regional and large-scale neural networks that underpin clinical symptom manifestation in neurodegeneration.

To provide multidimensional control, we describe the first reported decoding of bilateral hand movements by using single-trial magnetoencephalography signals as a new approach to enhance a user's ability to interact with a complex environment through a multidimensional brain-machine interface. Ten healthy participants performed or imagined four types of bilateral hand movements during neuromagnetic measurements. By applying a support vector machine (SVM) method to classify the four movements regarding the sensor data obtained from the sensorimotor area, we found the mean accuracy of a two-class classification using the amplitudes of neuromagnetic fields to be particularly suitable for real-time applications, with accuracies comparable to those obtained in previous studies involving unilateral movement. The sensor data from over the sensorimotor cortex showed discriminative time-series waveforms and time-frequency maps in the bilateral hemispheres according to the four tasks. Furthermore, we used four-class classification algorithms based on the SVM method to decode all types of bilateral movements. Our results provided further proof that the slow components of neuromagnetic fields carry sufficient neural information to classify even bilateral hand movements and demonstrated the potential utility of decoding bilateral movements for engineering purposes such as multidimensional motor control.

Abstract Objective To assess the characteristics of twin fetal facial expressions at 30–33 + 6 weeks of gestation using four-dimensional (4D) ultrasound to clarify twin fetal brain development and maturation. Methods Frequencies of seven fetal facial expressions were studied using 4D ultrasound for 15 minutes in 30 singleton pregnancies and 18 twin pregnancies [four monochorionic diamniotic (MD) and 14 dichorionic diamniotic (DD) twins] at 30–33 + 6 weeks of gestation. Comparison of the frequency in each facial expression was performed between singleton and twin fetuses. Results Mouthing was the most frequent facial expression at 30–33 + 6 weeks of gestation, followed by blinking in twin and singleton fetuses. Both facial expressions were significantly more frequent than other expressions (P < 0.05). The frequencies of mouthing and scowling in twin fetuses were significantly lower than those in singleton fetuses, but there were no significant differences in the frequencies of the five other facial expressions between the fetal groups. Conclusion Our results suggest that restricted twin fetal behavior before 20 weeks of gestation may still affect the frequencies of twin facial expressions early in the third trimester of pregnancy. Moreover, the frequencies of facial expressions in twins are different from those of singleton fetuses.

In the treatment of brain tumors, surgical intervention remains a common and effective therapeutic option. Recent advances in neuroimaging have provided neurosurgeons with new tools to overcome the challenge of differentiating healthy tissue from tumor-infiltrated tissue, with the aim of increasing the likelihood of maximizing the extent of resection volume while minimizing injury to functionally important regions. Novel applications of diffusion tensor imaging (DTI), and DTI-derived tractography (DDT) have demonstrated that preoperative, non-invasive mapping of eloquent cortical regions and functionally relevant white matter tracts (WMT) is critical during surgical planning to reduce postoperative deficits, which can decrease quality of life and overall survival. In this review, we summarize the latest developments of applying DTI and tractography in the context of resective surgery and highlight its utility within each stage of the neurosurgical workflow: preoperative planning and intraoperative management to improve postoperative outcomes.