scholarly journals Is the Imitative Competence an Asymmetrically Distributed Function?

2021 ◽  
Vol 15 ◽  
Author(s):  
Mara Fabri ◽  
Chiara Pierpaoli ◽  
Nicoletta Foschi ◽  
Gabriele Polonara
Keyword(s):  
White Matter ◽  
Corpus Callosum ◽  
Human Brain ◽  
Mental Rotation ◽  
Functional Data ◽  
Healthy Subjects ◽  
Interhemispheric Communication ◽  
Split Brain ◽  
Callosal Connections ◽  
Asymmetrically Distributed

This study reconsiders behavioral and functional data from studies investigating the anatomical imitation (AI) and the related mental rotation (MR) competence, carried out by our group in healthy subjects, with intact interhemispheric connections, and in split-brain patients, completely or partially lacking callosal connections. The results strongly point to the conclusion that AI and MR competence requires interhemispheric communication, mainly occurring through the corpus callosum, which is the largest white matter structure in the human brain. The results are discussed in light of previous studies and of future implications.

scholarly journals Non-local means based Rician noise filtering for diffusion tensor and kurtosis imaging in human brain and spinal cord

2020 ◽  
Author(s):  
Zhongping Zhang ◽  
Dhanashree Vernekar ◽  
Wenshu Qian ◽  
Mina Kim
Keyword(s):  
Spinal Cord ◽  
Corpus Callosum ◽  
Human Brain ◽  
Healthy Subjects ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
Chi Square ◽  
Lateral Column ◽  
Diffusion Weighted Images ◽  
The Brain

Abstract Background: To investigate the effect of using an Rician nonlocal means (NLM) filter on quantification of diffusion tensor (DT)- and diffusion kurtosis (DK)-derived metrics in various anatomical regions of the human brain and the spinal cord, when combined with a constrained linear least squares (CLLS) approach.Methods: Prospective brain data from 9 healthy subjects and retrospective spinal cord data from 5 healthy subjects from a 3T MRI scanner were included in the study. Prior to tensor estimation, registered diffusion weighted images were denoised by an optimized blockwise NLM filter with CLLS. Mean kurtosis (MK), radial kurtosis (RK), axial kurtosis (AK), mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD) and fractional anisotropy (FA), were determined in anatomical structures of the brain and the spinal cord. DTI and DKI metrics, signal-to-noise ratio (SNR) and Chi-square values were quantified in distinct anatomical regions for all subjects, with and without Rician denoising. Results: The averaged SNR significantly increased with Rician denoising by a factor of 2 while the averaged Chi-square values significantly decreased up to 61 % in the brain and up to 43% in the spinal cord after Rician NLM filtering. In the brain, the mean MK varied from 0.70 (putamen) to 1.27 (internal capsule) while AK and RK varied from 0.58 (corpus callosum) to 0.92 (cingulum) and from 0.70 (putamen) to 1.98 (corpus callosum), respectively. In the spinal cord, FA varied from 0.78 in lateral column to 0.81 in dorsal column while MD varied from 0.91 × 10−3 mm2/s (lateral) to 0.93 × 10−3 mm2/s (dorsal). RD varied from 0.34 × 10−3 mm2/s (dorsal) to 0.38 × 10−3 mm2/s (lateral) and AD varied from 1.96 × 10−3 mm2/s (lateral) to 2.11 × 10−3 mm2/s (dorsal).Conclusions: Our results show Rician denoising NLM filter incorporated with CLLS significantly increases SNR and reduces estimation errors of DT- and KT-derived metrics, providing the reliable metrics estimation with adequate SNR levels.

Self-Consciousness and "Split" Brains

2018 ◽  
Author(s):  
Elizabeth Schechter
Keyword(s):  
United States ◽  
Twentieth Century ◽  
Corpus Callosum ◽  
Human Brain ◽  
The United States ◽  
The Other ◽  
Cerebral Hemispheres ◽  
Experimental Conditions ◽  
Fiber Tract ◽  
Split Brain

The largest fiber tract in the human brain is the corpus callosum, which connects the two cerebral hemispheres. A number of surgeries severing this structure were performed on adults in the United States in the second half of the twentieth century. After they are surgically separated from each other in this way, a “split-brain” subject’s hemispheres begin to operate unusually independently of each other in the realms of perception, cognition, and the control of action—almost as if each had a mind of its own. But can a mere hemisphere really see? Speak? Feel? Know what it has done? The split-brain cases raise questions of psychological identity: How many subjects of experience are there within a split-brain subject? How many persons? How many minds? Under experimental conditions, split-brain subjects often act as though they were animated by two distinct conscious beings, evoking the duality intuition. On the other hand, a split-brain subject seems like one of us—not like two of us sharing one body. Split-brain subjects thus also evoke the unity intuition.This book is devoted to reconciling these two apparently opposing intuitions. The key to doing so are facts about the way self-consciousness operates in split-brain subjects. A split-brain subject is composed of two conscious psychological beings that fail to recognize each other’s existence and indeed cannot distinguish themselves from each other. Instead, each must first-personally identify with the split-brain subject as a whole, and in so doing, the two make themselves into one person.

scholarly journals Non-local means based Rician noise filtering for diffusion tensor and kurtosis imaging in human brain and spinal cord

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhongping Zhang ◽  
Dhanashree Vernekar ◽  
Wenshu Qian ◽  
Mina Kim
Keyword(s):  
Spinal Cord ◽  
Corpus Callosum ◽  
Human Brain ◽  
Healthy Subjects ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
Chi Square ◽  
Lateral Column ◽  
Diffusion Weighted Images ◽  
The Brain

Abstract Background To investigate the effect of using a Rician nonlocal means (NLM) filter on quantification of diffusion tensor (DT)- and diffusion kurtosis (DK)-derived metrics in various anatomical regions of the human brain and the spinal cord, when combined with a constrained linear least squares (CLLS) approach. Methods Prospective brain data from 9 healthy subjects and retrospective spinal cord data from 5 healthy subjects from a 3 T MRI scanner were included in the study. Prior to tensor estimation, registered diffusion weighted images were denoised by an optimized blockwise NLM filter with CLLS. Mean kurtosis (MK), radial kurtosis (RK), axial kurtosis (AK), mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD) and fractional anisotropy (FA), were determined in anatomical structures of the brain and the spinal cord. DTI and DKI metrics, signal-to-noise ratio (SNR) and Chi-square values were quantified in distinct anatomical regions for all subjects, with and without Rician denoising. Results The averaged SNR significantly increased with Rician denoising by a factor of 2 while the averaged Chi-square values significantly decreased up to 61% in the brain and up to 43% in the spinal cord after Rician NLM filtering. In the brain, the mean MK varied from 0.70 (putamen) to 1.27 (internal capsule) while AK and RK varied from 0.58 (corpus callosum) to 0.92 (cingulum) and from 0.70 (putamen) to 1.98 (corpus callosum), respectively. In the spinal cord, FA varied from 0.78 in lateral column to 0.81 in dorsal column while MD varied from 0.91 × 10−3 mm2/s (lateral) to 0.93 × 10−3 mm2/s (dorsal). RD varied from 0.34 × 10−3 mm2/s (dorsal) to 0.38 × 10−3 mm2/s (lateral) and AD varied from 1.96 × 10−3 mm2/s (lateral) to 2.11 × 10−3 mm2/s (dorsal). Conclusions Our results show a Rician denoising NLM filter incorporated with CLLS significantly increases SNR and reduces estimation errors of DT- and KT-derived metrics, providing the reliable metrics estimation with adequate SNR levels.

scholarly journals Non-local means based Rician noise filtering for diffusion tensor and kurtosis imaging in human brain and spinal cord

2020 ◽  
Author(s):  
Zhongping Zhang ◽  
Dhanashree Vernekar ◽  
Wenshu Qian ◽  
Mina Kim
Keyword(s):  
Spinal Cord ◽  
Corpus Callosum ◽  
Human Brain ◽  
Healthy Subjects ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
Chi Square ◽  
Lateral Column ◽  
Diffusion Weighted Images ◽  
The Brain

Abstract Background To investigate the effect of using an Rician nonlocal means (NLM) filter on quantification of diffusion tensor (DT)- and diffusion kurtosis (DK)-derived metrics in various anatomical regions of the human brain and the spinal cord, when combined with a constrained linear least squares (CLLS) approach. Methods Prospective brain data from 9 healthy subjects and retrospective spinal cord data from 5 healthy subjects from a 3T MRI scanner were included in the study. Prior to tensor estimation, registered diffusion weighted images were denoised by an optimized blockwise NLM filter with CLLS. Mean kurtosis (MK), radial kurtosis (RK), axial kurtosis (AK), mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD) and fractional anisotropy (FA), were determined in anatomical structures of the brain and the spinal cord. DTI and DKI metrics, signal-to-noise ratio (SNR) and Chi-square values were quantified in distinct anatomical regions for all subjects, with and without Rician denoising. Results The averaged SNR significantly increased with Rician denoising by a factor of 2 while the averaged Chi-square values significantly decreased up to 61% in the brain and up to 43% in the spinal cord after Rician NLM filtering. In the brain, the mean MK varied from 0.70 (putamen) to 1.27 (internal capsule) while AK and RK varied from 0.58 (corpus callosum) to 0.92 (cingulum) and from 0.70 (putamen) to 1.98 (corpus callosum), respectively. In the spinal cord, FA varied from 0.78 in lateral column to 0.81 in dorsal column while MD varied from 0.91 × 10− 3 mm2/s (lateral) to 0.93 × 10− 3 mm2/s (dorsal). RD varied from 0.34 × 10− 3 mm2/s (dorsal) to 0.38 × 10− 3 mm2/s (lateral) and AD varied from 1.96 × 10− 3 mm2/s (lateral) to 2.11 × 10− 3 mm2/s (dorsal). Conclusions Our results show Rician denoising NLM filter incorporated with CLLS significantly increases SNR and reduces estimation errors of DT- and KT-derived metrics, providing the reliable metrics estimation with adequate SNR levels.

Assessment of White Matter Lesions in Parkinson's Disease: Voxel-based Analysis and Tract-based Spatial Statistics Analysis of Parkinson's Disease with Mild Cognitive Impairment

2020 ◽  
Vol 17 (4) ◽  
pp. 480-486
Author(s):  
Wei Pu ◽  
Xudong Shen ◽  
Mingming Huang ◽  
Zhiqian Li ◽  
Xianchun Zeng ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
White Matter ◽  
Corpus Callosum ◽  
Fractional Anisotropy ◽  
Spatial Statistics ◽  
Diffusion Tensor ◽  
Tract Based Spatial Statistics

Objective: Application of diffusion tensor imaging (DTI) to explore the changes of FA value in patients with Parkinson's disease (PD) with mild cognitive impairment. Methods: 27 patients with PD were divided into PD with mild cognitive impairment (PD-MCI) group (n = 7) and PD group (n = 20). The original images were processed using voxel-based analysis (VBA) and tract-based spatial statistics (TBSS). Results: The average age of pd-mci group was longer than that of PD group, and the course of disease was longer than that of PD group. Compared with PD group, the voxel based analysis-fractional anisotropy (VBA-FA) values of PD-MCI group decreased in the following areas: bilateral frontal lobe, bilateral temporal lobe, bilateral parietal lobe, bilateral subthalamic nucleus, corpus callosum, and gyrus cingula. Tract-based spatial statistics-fractional anisotropy (TBSS-FA) values in PD-MCI group decreased in bilateral corticospinal tract, anterior cingulum, posterior cingulum, fornix tract, bilateral superior thalamic radiation, corpus callosum(genu, body and splenium), bilateral uncinate fasciculus, bilateral inferior longitudinal fasciculus, bilateral superior longitudinal fasciculus, bilateral superior fronto-occipital fasciculus, bilateral inferior fronto-occipital fasciculus, and bilateral parietal-occipital tracts. The mean age of onset in the PD-MCI group was greater than that in the PD group, and the disease course was longer than that in the PD group. Conclusion: DTI-based VBA and TBSS post-processing methods can detect abnormalities in multiple brain areas and white matter fiber tracts in PD-MCI patients. Impairment of multiple cerebral cortex and white matter fiber pathways may be an important causes of cognitive dysfunction in PD-MCI.

scholarly journals Topographic patterns of white matter hyperintensities are associated with multimodal neuroimaging biomarkers of Alzheimer’s disease

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Malo Gaubert ◽  
Catharina Lange ◽  
Antoine Garnier-Crussard ◽  
Theresa Köbe ◽  
Salma Bougacha ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
White Matter ◽  
Glucose Metabolism ◽  
Corpus Callosum ◽  
Gray Matter ◽  
Fdg Pet ◽  
White Matter Hyperintensities ◽  
Gray Matter Volume ◽  
Matter Volume

Abstract Background White matter hyperintensities (WMH) are frequently found in Alzheimer’s disease (AD). Commonly considered as a marker of cerebrovascular disease, regional WMH may be related to pathological hallmarks of AD, including beta-amyloid (Aβ) plaques and neurodegeneration. The aim of this study was to examine the regional distribution of WMH associated with Aβ burden, glucose hypometabolism, and gray matter volume reduction. Methods In a total of 155 participants (IMAP+ cohort) across the cognitive continuum from normal cognition to AD dementia, FLAIR MRI, AV45-PET, FDG-PET, and T1 MRI were acquired. WMH were automatically segmented from FLAIR images. Mean levels of neocortical Aβ deposition (AV45-PET), temporo-parietal glucose metabolism (FDG-PET), and medial-temporal gray matter volume (GMV) were extracted from processed images using established AD meta-signature templates. Associations between AD brain biomarkers and WMH, as assessed in region-of-interest and voxel-wise, were examined, adjusting for age, sex, education, and systolic blood pressure. Results There were no significant associations between global Aβ burden and region-specific WMH. Voxel-wise WMH in the splenium of the corpus callosum correlated with greater Aβ deposition at a more liberal threshold. Region- and voxel-based WMH in the posterior corpus callosum, along with parietal, occipital, and frontal areas, were associated with lower temporo-parietal glucose metabolism. Similarly, lower medial-temporal GMV correlated with WMH in the posterior corpus callosum in addition to parietal, occipital, and fontal areas. Conclusions This study demonstrates that local white matter damage is correlated with multimodal brain biomarkers of AD. Our results highlight modality-specific topographic patterns of WMH, which converged in the posterior white matter. Overall, these cross-sectional findings corroborate associations of regional WMH with AD-typical Aß deposition and neurodegeneration.

scholarly journals Structural brain signature of cognitive decline in Parkinson’s disease: DTI-based evidence from the LANDSCAPE study

2019 ◽  
Vol 12 ◽  
pp. 175628641984344 ◽  
Author(s):  
Martin Gorges ◽  
Hans-Peter Müller ◽  
Inga Liepelt-Scarfone ◽  
Alexander Storch ◽  
Richard Dodel ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
White Matter ◽  
Corpus Callosum ◽  
Cognitive Decline ◽  
Diffusion Tensor ◽  
Structural Connectivity ◽  
Structural Data ◽  
The Body ◽  
Normal Cognitive Function

Background: The nonmotor symptom spectrum of Parkinson’s disease (PD) includes progressive cognitive decline mainly in late stages of the disease. The aim of this study was to map the patterns of altered structural connectivity of patients with PD with different cognitive profiles ranging from cognitively unimpaired to PD-associated dementia. Methods: Diffusion tensor imaging and neuropsychological data from the observational multicentre LANDSCAPE study were analyzed. A total of 134 patients with PD with normal cognitive function (56 PD-N), mild cognitive impairment (67 PD-MCI), and dementia (11 PD-D) as well as 72 healthy controls were subjected to whole-brain-based fractional anisotropy mapping and covariance analysis with cognitive performance measures. Results: Structural data indicated subtle changes in the corpus callosum and thalamic radiation in PD-N, whereas severe white matter impairment was observed in both PD-MCI and PD-D patients including anterior and inferior fronto-occipital, uncinate, insular cortices, superior longitudinal fasciculi, corona radiata, and the body of the corpus callosum. These regional alterations were demonstrated for PD-MCI and were more pronounced in PD-D. The pattern of involved regions was significantly correlated with the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) total score. Conclusions: The findings in PD-N suggest impaired cross-hemispherical white matter connectivity that can apparently be compensated for. More pronounced involvement of the corpus callosum as demonstrated for PD-MCI together with affection of fronto-parieto-temporal structural connectivity seems to lead to gradual disruption of cognition-related cortico-cortical networks and to be associated with the onset of overt cognitive deficits. The increase of regional white matter damage appears to be associated with the development of PD-associated dementia.

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