Anatomy and Neuroscience - Research Publications

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    EEG measures for clinical research in major vascular cognitive impairment: recommendations by an expert panel
    Babiloni, C ; Arakaki, X ; Bonanni, L ; Bujan, A ; Carrillo, MC ; Del Percio, C ; Edelmayer, RM ; Egan, G ; Elahh, FM ; Evans, A ; Ferri, R ; Frisoni, GB ; Guntekin, B ; Hainsworth, A ; Hampel, H ; Jelic, V ; Jeong, J ; Kim, DK ; Kramberger, M ; Kumar, S ; Lizio, R ; Nobili, F ; Noce, G ; Puce, A ; Ritter, P ; Smit, DJA ; Soricelli, A ; Teipel, S ; Tucci, F ; Sachdev, P ; Valdes-Sosa, M ; Valdes-Sosa, P ; Vergallo, A ; Yener, G (ELSEVIER SCIENCE INC, 2021-07)
    Vascular contribution to cognitive impairment (VCI) and dementia is related to etiologies that may affect the neurophysiological mechanisms regulating brain arousal and generating electroencephalographic (EEG) activity. A multidisciplinary expert panel reviewed the clinical literature and reached consensus about the EEG measures consistently found as abnormal in VCI patients with dementia. As compared to cognitively unimpaired individuals, those VCI patients showed (1) smaller amplitude of resting state alpha (8-12 Hz) rhythms dominant in posterior regions; (2) widespread increases in amplitude of delta (< 4 Hz) and theta (4-8 Hz) rhythms; and (3) delayed N200/P300 peak latencies in averaged event-related potentials, especially during the detection of auditory rare target stimuli requiring participants' responses in "oddball" paradigms. The expert panel formulated the following recommendations: (1) the above EEG measures are not specific for VCI and should not be used for its diagnosis; (2) they may be considered as "neural synchronization" biomarkers to enlighten the relationships between features of the VCI-related cerebrovascular lesions and abnormalities in neurophysiological brain mechanisms; and (3) they may be tested in future clinical trials as prognostic biomarkers and endpoints of interventions aimed at normalizing background brain excitability and vigilance in wakefulness.
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    Estimation of simultaneous BOLD and dynamic FDG metabolic brain activations using a multimodality concatenated ICA (mcICA) method
    Li, S ; Jamadar, SD ; Ward, PGD ; Egan, GF ; Chen, Z (ACADEMIC PRESS INC ELSEVIER SCIENCE, 2021-02-01)
    Simultaneous magnetic resonance and positron emission tomography provides an opportunity to measure brain haemodynamics and metabolism in a single scan session, and to identify brain activations from multimodal measurements in response to external stimulation. However, there are few analysis methods available for jointly analysing the simultaneously acquired blood-oxygen-level dependant functional MRI (fMRI) and 18-F-fluorodeoxyglucose functional PET (fPET) datasets. In this work, we propose a new multimodality concatenated ICA (mcICA) method to identify joint fMRI-fPET brain activations in response to a visual stimulation task. The mcICA method produces a fused map from the multimodal datasets with equal contributions of information from both modalities, measured by entropy. We validated the method in silico, and applied it to an in vivo visual stimulation experiment. The mcICA method estimated the activated brain regions in the visual cortex modulated by both BOLD and FDG signals. The mcICA provides a fully data-driven analysis approach to analyse cerebral haemodynamic response and glucose uptake signals arising from exogenously induced neuronal activity.
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    Magnetic Resonance Iron Imaging in Amyotrophic Lateral Sclerosis
    Bhattarai, A ; Egan, GF ; Talman, P ; Chua, P ; Chen, Z (WILEY, 2022-05)
    Amyotrophic lateral sclerosis (ALS) results in progressive impairment of upper and lower motor neurons. Increasing evidence from both in vivo and ex vivo studies suggest that iron accumulation in the motor cortex is a neuropathological hallmark in ALS. An in vivo neuroimaging marker of iron dysregulation in ALS would be useful in disease diagnosis and prognosis. Magnetic resonance imaging (MRI), with its unique capability to generate a variety of soft tissue contrasts, provides opportunities to image iron distribution in the human brain with millimeter to sub-millimeter anatomical resolution. Conventionally, MRI T1-weighted, T2-weighted, and T2*-weighted images have been used to investigate iron dysregulation in the brain in vivo. Susceptibility weighted imaging has enhanced contrast for para-magnetic materials that provides superior sensitivity to iron in vivo. Recently, the development of quantitative susceptibility mapping (QSM) has realized the possibility of using quantitative assessments of magnetic susceptibility measures in brain tissues as a surrogate measurement of in vivo brain iron. In this review, we provide an overview of MRI techniques that have been used to investigate iron dysregulation in ALS in vivo. The potential uses, strengths, and limitations of these techniques in clinical trials, disease diagnosis, and prognosis are presented and discussed. We recommend further longitudinal studies with appropriate cohort characterization to validate the efficacy of these techniques. We conclude that quantitative iron assessment using recent advances in MRI including QSM holds great potential to be a sensitive diagnostic and prognostic marker in ALS. The use of multimodal neuroimaging markers in combination with iron imaging may also offer improved sensitivity in ALS diagnosis and prognosis that could make a major contribution to clinical care and treatment trials. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 3.
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    Suppressing motion artefacts in MRI using an Inception-ResNet network with motion simulation augmentation
    Pawar, K ; Chen, Z ; Shah, NJ ; Egan, GF (WILEY, 2022-04)
    The suppression of motion artefacts from MR images is a challenging task. The purpose of this paper was to develop a standalone novel technique to suppress motion artefacts in MR images using a data-driven deep learning approach. A simulation framework was developed to generate motion-corrupted images from motion-free images using randomly generated motion profiles. An Inception-ResNet deep learning network architecture was used as the encoder and was augmented with a stack of convolution and upsampling layers to form an encoder-decoder network. The network was trained on simulated motion-corrupted images to identify and suppress those artefacts attributable to motion. The network was validated on unseen simulated datasets and real-world experimental motion-corrupted in vivo brain datasets. The trained network was able to suppress the motion artefacts in the reconstructed images, and the mean structural similarity (SSIM) increased from 0.9058 to 0.9338. The network was also able to suppress the motion artefacts from the real-world experimental dataset, and the mean SSIM increased from 0.8671 to 0.9145. The motion correction of the experimental datasets demonstrated the effectiveness of the motion simulation generation process. The proposed method successfully removed motion artefacts and outperformed an iterative entropy minimization method in terms of the SSIM index and normalized root mean squared error, which were 5-10% better for the proposed method. In conclusion, a novel, data-driven motion correction technique has been developed that can suppress motion artefacts from motion-corrupted MR images. The proposed technique is a standalone, post-processing method that does not interfere with data acquisition or reconstruction parameters, thus making it suitable for routine clinical practice.
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    Incorporation of anatomical MRI knowledge for enhanced mapping of brain metabolism using functional PET
    Sudarshan, VP ; Li, S ; Jamadar, SD ; Egan, GF ; Awate, SP ; Chen, Z (ACADEMIC PRESS INC ELSEVIER SCIENCE, 2021-06)
    Functional positron emission tomography (fPET) imaging using continuous infusion of [18F]-fluorodeoxyglucose (FDG) is a novel neuroimaging technique to track dynamic glucose utilization in the brain. In comparison to conventional static or dynamic bolus PET, fPET maintains a sustained supply of glucose in the blood plasma which improves sensitivity to measure dynamic glucose changes in the brain, and enables mapping of dynamic brain activity in task-based and resting-state fPET studies. However, there is a trade-off between temporal resolution and spatial noise due to the low concentration of FDG and the limited sensitivity of multi-ring PET scanners. Images from fPET studies suffer from partial volume errors and residual scatter noise that may cause the cerebral metabolic functional maps to be biased. Gaussian smoothing filters used to denoise the fPET images are suboptimal, as they introduce additional partial volume errors. In this work, a post-processing framework based on a magnetic resonance (MR) Bowsher-like prior was used to improve the spatial and temporal signal to noise characteristics of the fPET images. The performance of the MR guided method was compared with conventional denosing methods using both simulated and in vivo task fPET datasets. The results demonstrate that the MR-guided fPET framework denoises the fPET images and improves the partial volume correction, consequently enhancing the sensitivity to identify brain activation, and improving the anatomical accuracy for mapping changes of brain metabolism in response to a visual stimulation task. The framework extends the use of functional PET to investigate the dynamics of brain metabolic responses for faster presentation of brain activation tasks, and for applications in low dose PET imaging.
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    Individual differences in haemoglobin concentration influence bold fMRI functional connectivity and its correlation with cognition
    Ward, PGD ; Orchard, ER ; Oldham, S ; Arnatkeviciute, A ; Sforazzini, F ; Fornito, A ; Storey, E ; Egan, GF ; Jamadar, SD (ACADEMIC PRESS INC ELSEVIER SCIENCE, 2020-11-01)
    Resting-state connectivity measures the temporal coherence of the spontaneous neural activity of spatially distinct regions, and is commonly measured using BOLD-fMRI. The BOLD response follows neuronal activity, when changes in the relative concentration of oxygenated and deoxygenated haemoglobin cause fluctuations in the MRI T2* signal. Since the BOLD signal detects changes in relative concentrations of oxy/deoxy-haemoglobin, individual differences in haemoglobin levels may influence the BOLD signal-to-noise ratio in a manner independent of the degree of neural activity. In this study, we examined whether group differences in haemoglobin may confound measures of functional connectivity. We investigated whether relationships between measures of functional connectivity and cognitive performance could be influenced by individual variability in haemoglobin. Finally, we mapped the neuroanatomical distribution of the influence of haemoglobin on functional connectivity to determine where group differences in functional connectivity are manifest. In a cohort of 518 healthy elderly subjects (259 men), each sex group was median-split into two groups with high and low haemoglobin concentration. Significant differences were obtained in functional connectivity between the high and low haemoglobin groups for both men and women (Cohen's d 0.17 and 0.03 for men and women respectively). The haemoglobin connectome in males showed a widespread systematic increase in functional connectivity correlation values, whilst the female connectome showed predominantly parietal and subcortical increases and temporo-parietal decreases. Despite the haemoglobin groups having no differences in cognitive measures, significant differences in the linear relationships between cognitive performance and functional connectivity were obtained for all 5 cognitive tests in males, and 4 out of 5 tests in females. Our findings confirm that individual variability in haemoglobin levels that give rise to group differences are an important confounding variable in BOLD-fMRI-based studies of functional connectivity. Controlling for haemoglobin variability as a potentially confounding variable is crucial to ensure the reproducibility of human brain connectome studies, especially in studies that compare groups of individuals, compare sexes, or examine connectivity-cognition relationships.
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    Evidence for multiple bulbar and higher brain circuits processing sensory inputs from the respiratory system in humans
    Farrell, MJ ; Bautista, TG ; Liang, E ; Azzollini, D ; Egan, GF ; Mazzone, SB (WILEY, 2020-12)
    KEY POINTS: Unpleasant respiratory sensations contribute to morbidity in pulmonary disease. In rodents, these sensations are processed by nodose and jugular vagal sensory neurons, two distinct cell populations that differentially project to the airways and brainstem. Whether similar differences exist in bronchopulmonary sensory pathways in humans is unknown. We use functional magnetic resonance imaging during inhalation of capsaicin and ATP, showing that airway nodose pathways project centrally to the nucleus of the solitary tract, whereas jugular pathways input into the trigeminal brainstem nuclei. We also show differences between the efficacy of nodose and jugular stimuli to evoke cough and activity in motor control regions of the brain. Our data suggest that humans have two distinct vagal sensory neural systems governing airway sensations and this may have implications for the development of new antitussive therapies. ABSTRACT: In rodents, nodose vagal sensory neurons preferentially innervate the distal airways and terminate centrally in the nucleus of the solitary tract. By contrast, jugular vagal sensory neurons preferentially innervate the proximal airways and terminate in the paratrigeminal nucleus in the dorsolateral medulla. This differential organization suggests distinct roles for nodose and jugular pathways in respiratory sensory processing. However, it is unknown whether bronchopulmonary afferent pathways are similarly arranged in humans. We set out to investigate this using high resolution brainstem and whole brain functional magnetic resonance imaging in healthy human participants when they were inhaling stimuli known to differentially activate nodose and jugular pathways. Inhalation of capsaicin or ATP evoked respiratory sensations described as an urge-to-cough, although ATP was significantly less effective compared to capsaicin at evoking the motor act of coughing. The nodose and jugular neuron stimulant capsaicin increased blood oxygen level-dependent (BOLD) signals extending across the dorsomedial and dorsolateral medulla, encompassing regions containing both the nucleus of the solitary tract and the paratrigeminal nucleus. By contrast, at perceptually comparable stimulus intensities, the nodose-selective stimulant ATP resulted in BOLD signal intensity changes that were confined to the area of the nucleus of the solitary tract. During whole brain imaging, capsaicin demonstrated a wider distributed network of activity compared to ATP, with significantly increased activity in regions involved with motor control functions. These data suggest that functional and neuroanatomical differences in bronchopulmonary nodose and jugular sensory pathway organization are conserved in humans and also that this has implications for understanding the neurobiological mechanisms underpinning cough.
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    The effects of a single-session cathodal transcranial pulsed current stimulation on corticospinal excitability: A randomized sham-controlled double-blinded study
    Dissanayaka, T ; Zoghi, M ; Farrell, M ; Egan, G ; Jaberzadeh, S (WILEY, 2020-12)
    Transcranial pulsed current stimulation (tPCS) of the human motor cortex has received much attention in recent years. Although the effect of anodal tPCS with different frequencies has been investigated, the effect of cathodal tPCS (c-tPCS) has not been explored yet. Therefore, the aim of the present study was to investigate the effect of c-tPCS at 4 and 75 Hz frequencies on corticospinal excitability (CSE) and motor performance. In a randomized sham-controlled crossover design, fifteen healthy participants attended three experimental sessions and received either c-tPCS at 75 Hz, 4 Hz or sham with 1.5 mA for 15 min. Transcranial magnetic stimulation and grooved pegboard test were performed before, immediately after and 30 min after the completion of stimulation at rest. The findings indicate that c-tPCS at both 4 and 75 Hz significantly increased CSE compared to sham. Both c-tPCS at 75 and 4 Hz showed a significant increase in intracortical facilitation compared to sham, whereas the effect on short-interval intracortical inhibition was not significant. The c-tPCS at 4 Hz but not 75 Hz induced modulation of intracortical facilitation correlated with the CSE. Motor performance did not show any significant changes. These results suggest that, compared with sham stimulation, c-tPCS at both 4 and 75 Hz induces an increase in CSE.
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    Application of compressed sensing using chirp encoded 3D GRE and MPRAGE sequences
    Pawar, K ; Chen, Z ; Zhang, J ; Shah, NJ ; Egan, GF (WILEY, 2020-09)
    Abstract An implementation of Non‐Fourier chirp‐encoding in 3D Gradient Recalled Echo (GRE), susceptibility‐weighted imaging (SWI) and Magnetization Prepared Rapid Gradient Echo (MPRAGE) sequences is presented with compressive sensing reconstruction. 3D GRE and MPRAGE sequences were designed, in which the phase encoding (PE) direction was encoded with spatially selective chirp encoding Radio Frequency (RF) pulses, while the slice and the readout directions were Fourier encoded using gradients. During each excitation along the PE direction, a different spatially‐selective RF excitation pulse was used to encode the PE direction with a complete set of unitary chirp encoding basis. Multichannel compressive sensing reconstruction on the undersampled in vivo data demonstrated that images reconstructed from chirp encoded data were able to preserve the spatial resolution better than the Fourier encoding. The mean Structural Similarity (SSIM) across five subjects at the acceleration factor of 6, for chirp encoded MPRAGE was 0.934 compared to 0.912 for Fourier encoded MPRAGE. The implementation of prospective undersampling demonstrated the feasibility of using chirp encoding in clinical practice for accelerated imaging. The minimum intensity projection of the compressive sensing (CS) reconstructed susceptibility weighted images revealed that chirp encoding is able to delineate small vessels better than the Fourier encoding with the SSIM of 0.960 for chirp encoding compared to the SSIM of 0.949 for the Fourier encoding. Improved performance of chirp encoding for CS reconstruction and SWI, along with the feasibility of implementation makes them a practical candidate for clinical MRI scans.
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    A Standards Organization for Open and FAIR Neuroscience: the International Neuroinformatics Coordinating Facility
    Abrams, MB ; Bjaalie, JG ; Das, S ; Egan, GF ; Ghosh, SS ; Goscinski, WJ ; Grethe, JS ; Kotaleski, JH ; Ho, ETW ; Kennedy, DN ; Lanyon, LJ ; Leergaard, TB ; Mayberg, HS ; Milanesi, L ; Moucek, R ; Poline, JB ; Roy, PK ; Strother, SC ; Tang, TB ; Tiesinga, P ; Wachtler, T ; Wojcik, DK ; Martone, ME (HUMANA PRESS INC, 2022-01)
    There is great need for coordination around standards and best practices in neuroscience to support efforts to make neuroscience a data-centric discipline. Major brain initiatives launched around the world are poised to generate huge stores of neuroscience data. At the same time, neuroscience, like many domains in biomedicine, is confronting the issues of transparency, rigor, and reproducibility. Widely used, validated standards and best practices are key to addressing the challenges in both big and small data science, as they are essential for integrating diverse data and for developing a robust, effective, and sustainable infrastructure to support open and reproducible neuroscience. However, developing community standards and gaining their adoption is difficult. The current landscape is characterized both by a lack of robust, validated standards and a plethora of overlapping, underdeveloped, untested and underutilized standards and best practices. The International Neuroinformatics Coordinating Facility (INCF), an independent organization dedicated to promoting data sharing through the coordination of infrastructure and standards, has recently implemented a formal procedure for evaluating and endorsing community standards and best practices in support of the FAIR principles. By formally serving as a standards organization dedicated to open and FAIR neuroscience, INCF helps evaluate, promulgate, and coordinate standards and best practices across neuroscience. Here, we provide an overview of the process and discuss how neuroscience can benefit from having a dedicated standards body.