scholarly journals Automatic substantia nigra segmentation in neuromelanin-sensitive MRI by deep neural network in patients with prodromal and manifest synucleinopathy

2019 ◽  
pp. S453-S458
Author(s):  
R. Krupička ◽  
S. Mareček ◽  
C. Malá ◽  
M. Lang ◽  
O. Klempíř ◽  
...  
Keyword(s):  
Neural Network ◽  
Substantia Nigra ◽  
Signal Intensity ◽  
Substantia Nigra Pars Compacta ◽  
The Neural Network ◽  
Intensity Information ◽  
Ideal Tool ◽  
Magnetic Resonance Imaging Mri ◽  
The Brain

Neuromelanin (NM) is a black pigment located in the brain in substantia nigra pars compacta (SN) and locus coeruleus. Its loss is directly connected to the loss of nerve cells in this part of the brain, which plays a role in Parkinson’s Disease. Magnetic resonance imaging (MRI) is an ideal tool to monitor the amount of NM in the brain in vivo. The aim of the study was the development of tools and methodology for the quantification of NM in a special neuromelanin-sensitive MRI images. The first approach was done by creating regions of interest, corresponding to the anatomical position of SN based on an anatomical atlas and determining signal intensity threshold. By linking the anatomical and signal intensity information, we were able to segment the SN. As a second approach, the neural network U-Net was used for the segmentation of SN. Subsequently, the volume characterizing the amount of NM in the SN region was calculated. To verify the method and the assumptions, data available from various patient groups were correlated. The main benefit of this approach is the observer-independency of quantification and facilitation of the image processing process and subsequent quantification compared to the manual approach. It is ideal for automatic processing many image sets in one batch.

scholarly journals Protective effect of Curcumin against rotenone-induced Substantia nigra pars compacta neuronal dysfunction

2021 ◽  
Author(s):  
Lilit Vahan Darbinyan ◽  
Lilia Eduard Hambardzumyan ◽  
Larisa Paylak Manukyan ◽  
Karen Vazgen Simonyan ◽  
Carlos Augusto Carvalho de Vasconcelos ◽  
...  
Keyword(s):  
Substantia Nigra ◽  
Dopaminergic Neurons ◽  
Therapeutic Agent ◽  
Male Rats ◽  
Substantia Nigra Pars Compacta ◽  
Nissl Staining ◽  
Histological Changes ◽  
Naturally Occurring ◽  
The Brain

Abstract Rotenone is involved in the degeneration of dopaminergic neurons, and curcumin may prevent or effectively slow the progression of Parkinson disease (PD). Previous research has shown that the naturally occurring phenolic compound curcumin can reduce inflammation and oxidation, making it a potential therapeutic agent for neurodegenerative diseases. The present study involves investigation of rotenone induced histological changes in the brain areas, hippocampus using Nissl staining after 35 day of subcutaneous injection administration of rotenone in adult male rats. In this study, we investigated whether curcumin protects against rotenone-induced dopaminergic neurotoxicity in a rat model by in vivo electrical recording from Substantia nigra pars compacta (SNc). Curcumin treatment significantly improved electrical activity of neurons in the SNc of rotenone-induced PD model rats. The pattern of histological alterations corresponds with electrophysiological manifestations.

Muscarine Reduces Calcium-Dependent Electrical Activity in Substantia Nigra Dopaminergic Neurons

2001 ◽  
Vol 86 (6) ◽  
pp. 2966-2972 ◽  
Author(s):  
Reese S. Scroggs ◽  
Carla G. Cardenas ◽  
Joseph A. Whittaker ◽  
Stephen T. Kitai
Keyword(s):  
Substantia Nigra ◽  
Electrical Activity ◽  
Dopaminergic Neurons ◽  
Brain Slices ◽  
Oscillatory Potentials ◽  
Substantia Nigra Pars Compacta ◽  
Pontine Nucleus ◽  
Calcium Dependent ◽  
The Brain

The effect of muscarine on Ca2+ dependent electrical activity was studied in dopamine (DA) neurons located in the substantia nigra pars compacta (SNc) in brain slices from young rats, using sharp electrodes. In most DA neurons tested, muscarine (50 μM) reduced the amplitude of spontaneous oscillatory potentials and evoked Ca2+-dependent potentials recorded in the presence of TTX. Muscarine also reduced the amplitude of the slow afterhyperpolarization (sAHP) following action potentials in most DA neurons. These data suggest that muscarine reduces Ca2+ entry in SNc DA neurons. The reduction of the amplitude of the sAHP by muscarine in DA neurons may facilitate bursting initiated by glutamatergic input by increasing the frequency at which DA neurons can fire. The reduction of the sAHP via activation of muscarinic receptors in vivo may provide a mechanism whereby cholinergic inputs to DA neurons from the tegmental peduncular pontine nucleus could modulate dopamine release at dopaminergic targets in the brain.

scholarly journals Substantia nigra neuromelanin magnetic resonance imaging in patients with different subtypes of Parkinson disease

2021 ◽  
Author(s):  
Lu Wang ◽  
Yayun Yan ◽  
Liyao Zhang ◽  
Yan Liu ◽  
Ruirui Luo ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Substantia Nigra ◽  
Parkinson Disease ◽  
Clinical Symptoms ◽  
Dopamine Neurons ◽  
Substantia Nigra Pars Compacta ◽  
Resonance Imaging ◽  
Mean Values

AbstractNeuromelanin (NM) is a dark pigment that mainly exists in neurons of the substantia nigra pars compacta (SNc). In Parkinson disease (PD) patients, NM concentration decreases gradually with degeneration and necrosis of dopamine neurons, suggesting potential use as a PD biomarker. We aimed to evaluate associations between NM concentration in in vivo SN and PD progression and different motor subtypes using NM magnetic resonance imaging (NM-MRI). Fifty-four patients with idiopathic PD were enrolled. Patients were divided into groups by subtypes with different clinical symptoms: tremor dominant (TD) group and postural instability and gait difficulty (PIGD) group. Fifteen healthy age-matched volunteers were enrolled as controls. All subjects underwent clinical assessment and NM-MRI examination. PD patients showed significantly decreased contrast-to-noise ratio (CNR) values in medial and lateral SN (P < 0.05) compared to controls. CNR values in lateral SN region decreased linearly with PD progression (P = 0.001). PIGD patients showed significant decreases in CNR mean values in lateral SN compared to TD patients (P = 0.004). Diagnostic accuracy of using lateral substantia nigra (SN) in TD and PIGD groups was 79% (sensitivity 76.5%, specificity 78.6%). NM concentration in PD patients decreases gradually during disease progression and differs significantly between PD subtypes. NM may be a reliable biomarker for PD severity and subtype identification.

scholarly journals Machine learning estimation of tissue optical properties

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Brett H. Hokr ◽  
Joel N. Bixler
Keyword(s):  
Neural Network ◽  
Optical Properties ◽  
Biological Tissues ◽  
Homogeneous Layer ◽  
In Vivo Measurement ◽  
Tissue Optical Properties ◽  
The Neural Network ◽  
Spatio Temporal ◽  
Fully Connected

AbstractDynamic, in vivo measurement of the optical properties of biological tissues is still an elusive and critically important problem. Here we develop a technique for inverting a Monte Carlo simulation to extract tissue optical properties from the statistical moments of the spatio-temporal response of the tissue by training a 5-layer fully connected neural network. We demonstrate the accuracy of the method across a very wide parameter space on a single homogeneous layer tissue model and demonstrate that the method is insensitive to parameter selection of the neural network model itself. Finally, we propose an experimental setup capable of measuring the required information in real time in an in vivo environment and demonstrate proof-of-concept level experimental results.

scholarly journals Artificial Neural Network in Drug Delivery and Pharmaceutical Research

2013 ◽  
Vol 7 (1) ◽  
pp. 49-62 ◽  
Author(s):  
Vijaykumar Sutariya ◽  
Anastasia Groshev ◽  
Prabodh Sadana ◽  
Deepak Bhatia ◽  
Yashwant Pathak
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Drug Delivery ◽  
Pattern Recognition ◽  
Analytical Data ◽  
Pharmaceutical Research ◽  
Artificial Neural ◽  
The Brain

Artificial neural networks (ANNs) technology models the pattern recognition capabilities of the neural networks of the brain. Similarly to a single neuron in the brain, artificial neuron unit receives inputs from many external sources, processes them, and makes decisions. Interestingly, ANN simulates the biological nervous system and draws on analogues of adaptive biological neurons. ANNs do not require rigidly structured experimental designs and can map functions using historical or incomplete data, which makes them a powerful tool for simulation of various non-linear systems.ANNs have many applications in various fields, including engineering, psychology, medicinal chemistry and pharmaceutical research. Because of their capacity for making predictions, pattern recognition, and modeling, ANNs have been very useful in many aspects of pharmaceutical research including modeling of the brain neural network, analytical data analysis, drug modeling, protein structure and function, dosage optimization and manufacturing, pharmacokinetics and pharmacodynamics modeling, and in vitro in vivo correlations. This review discusses the applications of ANNs in drug delivery and pharmacological research.

scholarly journals Detection of Parkinson’s Disease from 3T T1 Weighted MRI Scans Using 3D Convolutional Neural Network

Diagnostics ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 402
Author(s):  
Sabyasachi Chakraborty ◽  
Satyabrata Aich ◽  
Hee-Cheol Kim
Keyword(s):  
Neural Network ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Convolutional Neural Network ◽  
Dopaminergic Neurons ◽  
Aging Population ◽  
Substantia Nigra Pars Compacta ◽  
Progressive Loss ◽  
Mri Scans ◽  
Magnetic Resonance Imaging Mri

Parkinson’s Disease is a neurodegenerative disease that affects the aging population and is caused by a progressive loss of dopaminergic neurons in the substantia nigra pars compacta (SNc). With the onset of the disease, the patients suffer from mobility disorders such as tremors, bradykinesia, impairment of posture and balance, etc., and it progressively worsens in the due course of time. Additionally, as there is an exponential growth of the aging population in the world the number of people suffering from Parkinson’s Disease is increasing and it levies a huge economic burden on governments. However, until now no therapeutic method has been discovered for completely eradicating the disease from a person’s body after it’s onset. Therefore, the early detection of Parkinson’s Disease is of paramount importance to tackle the progressive loss of dopaminergic neurons in patients to serve them with a better life. In this study, 3T T1-weighted MRI scans were acquired from the Parkinson’s Progression Markers Initiative (PPMI) database of 406 subjects from baseline visit, where 203 were healthy and 203 were suffering from Parkinson’s Disease. Following data pre-processing, a 3D convolutional neural network (CNN) architecture was developed for learning the intricate patterns in the Magnetic Resonance Imaging (MRI) scans for the detection of Parkinson’s Disease. In the end, it was observed that the developed 3D CNN model performed superiorly by completely aligning with the hypothesis of the study and plotted an overall accuracy of 95.29%, average recall of 0.943, average precision of 0.927, average specificity of 0.9430, f1-score of 0.936, and Receiver Operating Characteristic—Area Under Curve (ROC-AUC) score of 0.98 for both the classes respectively.

scholarly journals Pedunculopontine glutamatergic neurons control spike patterning in substantia nigra dopaminergic neurons

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Daniel J Galtieri ◽  
Chad M Estep ◽  
David L Wokosin ◽  
Stephen Traynelis ◽  
D James Surmeier
Keyword(s):  
Substantia Nigra ◽  
Dopaminergic Neurons ◽  
Substantia Nigra Pars Compacta ◽  
Glutamatergic Synapses ◽  
Glutamatergic Neurons ◽  
Oscillatory Mechanisms ◽  
Goal Directed Behavior ◽  
Stimulation Of

Burst spiking in substantia nigra pars compacta (SNc) dopaminergic neurons is a key signaling event in the circuitry controlling goal-directed behavior. It is widely believed that this spiking mode depends upon an interaction between synaptic activation of N-methyl-D-aspartate receptors (NMDARs) and intrinsic oscillatory mechanisms. However, the role of specific neural networks in burst generation has not been defined. To begin filling this gap, SNc glutamatergic synapses arising from pedunculopotine nucleus (PPN) neurons were characterized using optical and electrophysiological approaches. These synapses were localized exclusively on the soma and proximal dendrites, placing them in a good location to influence spike generation. Indeed, optogenetic stimulation of PPN axons reliably evoked spiking in SNc dopaminergic neurons. Moreover, burst stimulation of PPN axons was faithfully followed, even in the presence of NMDAR antagonists. Thus, PPN-evoked burst spiking of SNc dopaminergic neurons in vivo may not only be extrinsically triggered, but extrinsically patterned as well.

Research on Underwater Polarization Image Segmentation Inspired by Biological Optic Nerve

2013 ◽  
Vol 347-350 ◽  
pp. 2178-2184
Author(s):  
Hui Bin Wang ◽  
Yu Rong Wu ◽  
Jie Shen ◽  
Zhe Chen
Keyword(s):  
Neural Network ◽  
Image Segmentation ◽  
Network Model ◽  
Neural Network Model ◽  
Underwater Image ◽  
The Neural Network ◽  
Intensity Information ◽  
Segmentation Methods ◽  
Polarization Image ◽  
Feedback Neural Network

Due to effects of the light by water and other particles, the quality of underwater image will degrade. The traditional underwater image segmentation methods based on intensity and spectrum have difficulty in determining boundary. Inspired by the visual system of mantis shrimps, this paper constructed a feedback neural network model, in which the parameters were optimized using machine learning method. Based on this model, we combine the polarization and intensity information to achieve the underwater polarization image segmentation. The results of experiment prove that the neural network model designed in this paper can improve the accuracy of underwater image segmentation.

Cognitive Enhancement Mediated Through Postsynaptic Actions of Norepinephrine on Ongoing Cortical Activity

2005 ◽  
Vol 17 (8) ◽  
pp. 1739-1775 ◽  
Author(s):  
Osamu Hoshino
Keyword(s):  
Neural Network ◽  
Cognitive Performance ◽  
Neuronal Activity ◽  
Dynamic Property ◽  
Cognitive Enhancement ◽  
Cortical Activity ◽  
Sensory Stimuli ◽  
The Neural Network ◽  
Higher Doses ◽  
The Brain

We propose two distinct types of norepinephrine (NE)-neuromodulatory systems: an enhanced-excitatory and enhanced-inhibitory (E-E/E-I) system and a depressed-excitatory and enhanced-inhibitory (D-E/E-I) system. In both systems, inhibitory synaptic efficacies are enhanced, but excitatory ones are modified in a contradictory manner: the E-E/E-I system enhances excitatory synaptic efficacies, whereas the D-E/E-I system depresses them. The E-E/E-I and D-E/E-I systems altered the dynamic property of ongoing (background) neuronal activity and greatly influenced the cognitive performance (S/N ratio) of a cortical neural network. The E-E/E-I system effectively enhanced S/N ratio for weaker stimuli with lower doses of NE, whereas the D-E/E-I system enhanced stronger stimuli with higher doses of NE. The neural network effectively responded to weaker stimuli if brief γ-bursts were involved in ongoing neuronal activity that is controlled under the E-E/E-I neuromodulatory system. If the E-E/E-I and the D-E/E-I systems interact within the neural network, depressed neurons whose activity is depressed by NE application have bimodal property. That is, S/N ratio can be enhanced not only for stronger stimuli as its original property but also for weaker stimuli, for which coincidental neuronal firings among enhanced neurons whose activity is enhanced by NE application are essential. We suggest that the recruitment of the depressed neurons for the detection of weaker (subthreshold) stimuli might be advantageous for the brain to cope with a variety of sensory stimuli.

Imaging

2017 ◽  
Author(s):  
Robert Laureno
Keyword(s):  
Resonance Imaging ◽  
Cross Sectional ◽  
Advantages And Disadvantages ◽  
Mri Scans ◽  
Cross Sectional Imaging ◽  
Magnetic Resonance Imaging Mri ◽  
Cellular Pathology ◽  
Brain And Spinal Cord ◽  
The Brain

This chapter on “Imaging” examines the relative advantages and disadvantages of computed tomography (CT) and magnetic resonance imaging (MRI) scans. It compares the modalities to each other and to gross neuropathology. For several decades, neurologists have been able to view cross-sectional images of living patients. Analogous to gross neuropathology, cross-sectional imaging displays the brain as an entire organ but does not demonstrate microscopic tissue or cellular pathology. By allowing practitioners to view sections of brain and spinal cord in vivo, imaging has improved neurologic practice and facilitated clinical research. This chapter deals with imaging topics that are important to the neurologist. The timing of scans, the effects of gravity, and the importance of plane of section are considered. Imaging is compared to gross neuropathology, and MRI is compared to CT.

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