scholarly journals Benchmarking of tools for axon length measurement in individually-labeled projection neurons

2021 ◽  
Vol 17 (12) ◽  
pp. e1009051
Author(s):  
Mario Rubio-Teves ◽  
Sergio Díez-Hermano ◽  
César Porrero ◽  
Abel Sánchez-Jiménez ◽  
Lucía Prensa ◽  
...  
Keyword(s):  
Single Neuron ◽  
Estimation Method ◽  
Brain Regions ◽  
Projection Neurons ◽  
Stereological Method ◽  
Tissue Sections ◽  
Length Estimation ◽  
Human Effort ◽  
Neuronal Type ◽  
Selection Of

Projection neurons are the commonest neuronal type in the mammalian forebrain and their individual characterization is a crucial step to understand how neural circuitry operates. These cells have an axon whose arborizations extend over long distances, branching in complex patterns and/or in multiple brain regions. Axon length is a principal estimate of the functional impact of the neuron, as it directly correlates with the number of synapses formed by the axon in its target regions; however, its measurement by direct 3D axonal tracing is a slow and labor-intensive method. On the contrary, axon length estimations have been recently proposed as an effective and accessible alternative, allowing a fast approach to the functional significance of the single neuron. Here, we analyze the accuracy and efficiency of the most used length estimation tools—design-based stereology by virtual planes or spheres, and mathematical correction of the 2D projected-axon length—in contrast with direct measurement, to quantify individual axon length. To this end, we computationally simulated each tool, applied them over a dataset of 951 3D-reconstructed axons (from NeuroMorpho.org), and compared the generated length values with their 3D reconstruction counterparts. The evaluated reliability of each axon length estimation method was then balanced with the required human effort, experience and know-how, and economic affordability. Subsequently, computational results were contrasted with measurements performed on actual brain tissue sections. We show that the plane-based stereological method balances acceptable errors (~5%) with robustness to biases, whereas the projection-based method, despite its accuracy, is prone to inherent biases when implemented in the laboratory. This work, therefore, aims to provide a constructive benchmark to help guide the selection of the most efficient method for measuring specific axonal morphologies according to the particular circumstances of the conducted research.

scholarly journals Benchmarking of tools for axon length measurement in individually-labeled projection neurons

2021 ◽  
Author(s):  
Mario Rubio-Teves ◽  
Sergio Díez-Hermano ◽  
César Porrero ◽  
Abel Sánchez-Jiménez ◽  
Lucía Prensa ◽  
...  
Keyword(s):  
Single Neuron ◽  
Estimation Method ◽  
Brain Regions ◽  
Projection Neurons ◽  
Tissue Sections ◽  
Length Estimation ◽  
Direct Measurements ◽  
Human Effort ◽  
Neuronal Type ◽  
Selection Of

Projection neurons are the commonest neuronal type in the mammalian forebrain and their individual characterization is a crucial step to understand how neural circuitry operates. These cells have an axon whose arborizations extend over long distances, branching in complex patterns and/or in multiple brain regions. Axon length is a principal estimate of the functional impact of the neuron, as it directly correlates with the number of synapses formed by the axon in its target regions; however, its measurement by direct 3D axonal tracing is a slow and labor-intensive method. On the contrary, axon length estimations have been recently proposed as an effective and accessible alternative, allowing a fast approach to the functional significance of the single neuron. Here, we analyze the accuracy and efficiency of the most used length estimation tools - design-based stereology by virtual planes or spheres, and mathematical correction of the 2D projected-axon length - in contrast with direct measurement, to quantify individual axon length. To this end, we computationally simulated each tool, applied them over a dataset of 951 3D-reconstructed axons (from NeuroMorpho.org), and compared the generated length values with their 3D reconstruction counterparts. Additionally, the computational results were compared with estimated and direct measurements of individual axon lengths performed on actual brain tissue sections, to analyze the practical difficulties and biases arising in real cases. The evaluated reliability of each axon length estimation method is then balanced with the required human effort, experience and know-how, and economic affordability. This work, therefore, aims to provide a constructive benchmark to help guide the selection of the most efficient method for measuring specific axonal morphologies according to the particular circumstances of the conducted research.

scholarly journals High-throughput mapping of single-cell molecular and projection architecture of neurons by retrograde barcoded labelling

2021 ◽  
Author(s):  
Peibo Xu ◽  
Jian Peng ◽  
Tingli Yuan ◽  
Zhaoqin Chen ◽  
Ziyan Wu ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Neuron ◽  
Neural Circuit ◽  
Brain Regions ◽  
Mammalian Brain ◽  
Projection Neurons ◽  
Proof Of Concept ◽  
Sequencing Technology ◽  
Modal Data ◽  
Projection Pattern

Deciphering mesoscopic connectivity of the mammalian brain is a pivotal step in neuroscience. Most imaging-based conventional neuroanatomical tracing methods identify area-to-area or sparse single neuronal labeling information. Although recently developed barcode-based connectomics has been able to map a large number of single-neuron projections efficiently, there is a missing link in single-cell connectome and transcriptome. Here, combining single-cell RNA sequencing technology, we established a retro-AAV barcode-based multiplexed tracing method called MEGRE-seq (Multiplexed projEction neuRons retroGrade barcodE), which can resolve projectome and transcriptome of source neurons simultaneously. Using the ventromedial prefrontal cortex (vmPFC) as a proof-of-concept neocortical region, we investigated projection patterns of its excitatory neurons targeting five canonical brain regions, as well as corresponding transcriptional profiles. Dedicated, bifurcated or collateral projection patterns were inferred by digital projectome. In combination with simultaneously recovered transcriptome, we find that certain projection pattern has a preferential layer or neuron subtype bias. Further, we fitted single-neuron two-modal data into a machine learning-based model and delineated gene importance by each projection target. In summary, we anticipate that the new multiplexed digital connectome technique is potential to understand the organizing principle of the neural circuit by linking projectome and transcriptome.

A Biomarker Combining Imaging and Neuropsychological Assessment for Tracking Early Alzheimer's Disease in Clinical Trials

2018 ◽  
Vol 15 (5) ◽  
pp. 429-442 ◽  
Author(s):  
Nishant Verma ◽  
S. Natasha Beretvas ◽  
Belen Pascual ◽  
Joseph C. Masdeu ◽  
Mia K. Markey ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Trials ◽  
Cognitive Impairment ◽  
Latent Variable ◽  
Brain Regions ◽  
Disease Assessment ◽  
Latent Variable Analysis ◽  
The Relationship ◽  
Selection Of

Background: Combining optimized cognitive (Alzheimer's Disease Assessment Scale- Cognitive subscale, ADAS-Cog) and atrophy markers of Alzheimer's disease for tracking progression in clinical trials may provide greater sensitivity than currently used methods, which have yielded negative results in multiple recent trials. Furthermore, it is critical to clarify the relationship among the subcomponents yielded by cognitive and imaging testing, to address the symptomatic and anatomical variability of Alzheimer's disease. Method: Using latent variable analysis, we thoroughly investigated the relationship between cognitive impairment, as assessed on the ADAS-Cog, and cerebral atrophy. A biomarker was developed for Alzheimer's clinical trials that combines cognitive and atrophy markers. Results: Atrophy within specific brain regions was found to be closely related with impairment in cognitive domains of memory, language, and praxis. The proposed biomarker showed significantly better sensitivity in tracking progression of cognitive impairment than the ADAS-Cog in simulated trials and a real world problem. The biomarker also improved the selection of MCI patients (78.8±4.9% specificity at 80% sensitivity) that will evolve to Alzheimer's disease for clinical trials. Conclusion: The proposed biomarker provides a boost to the efficacy of clinical trials focused in the mild cognitive impairment (MCI) stage by significantly improving the sensitivity to detect treatment effects and improving the selection of MCI patients that will evolve to Alzheimer’s disease.

scholarly journals Cortical neurons exhibit diverse myelination patterns that scale between mouse brain regions and regenerate after demyelination

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Cody L. Call ◽  
Dwight E. Bergles
Keyword(s):  
Cortical Neurons ◽  
Regional Differences ◽  
Brain Regions ◽  
Axon Diameter ◽  
Neuronal Identity ◽  
Cortical Areas ◽  
Myelin Sheaths ◽  
Parvalbumin Interneurons ◽  
Selection Of

ABSTRACTAxons in the cerebral cortex show a broad range of myelin coverage. Oligodendrocytes establish this pattern by selecting a cohort of axons for myelination; however, the distribution of myelin on distinct neurons and extent of internode replacement after demyelination remain to be defined. Here we show that myelination patterns of seven distinct neuron subtypes in somatosensory cortex are influenced by both axon diameter and neuronal identity. Preference for myelination of parvalbumin interneurons was preserved between cortical areas with varying myelin density, suggesting that regional differences in myelin abundance arises through local control of oligodendrogenesis. By imaging loss and regeneration of myelin sheaths in vivo we show that myelin distribution on individual axons was altered but overall myelin content on distinct neuron subtypes was restored. Our findings suggest that local changes in myelination are tolerated, allowing regenerated oligodendrocytes to restore myelin content on distinct neurons through opportunistic selection of axons.

A Kalman Filter-Based Queue Length Estimation Method with Low-Penetration Mobile Sensor Data at Signalized Intersections

2018 ◽  
Vol 2672 (45) ◽  
pp. 253-264 ◽  
Author(s):  
Juyuan Yin ◽  
Jian Sun ◽  
Keshuang Tang
Keyword(s):  
Kalman Filter ◽  
Queue Length ◽  
Estimation Method ◽  
Mobile Internet ◽  
Internet Technology ◽  
Sensor Data ◽  
Linear Regression Method ◽  
Mobile Sensor ◽  
Length Estimation ◽  
Queue Lengths

Queue length estimation is of great importance for signal performance measures and signal optimization. With the development of connected vehicle technology and mobile internet technology, using mobile sensor data instead of fixed detector data to estimate queue length has become a significant research topic. This study proposes a queue length estimation method using low-penetration mobile sensor data as the only input. The proposed method is based on the combination of Kalman Filtering and shockwave theory. The critical points are identified from raw spatiotemporal points and allocated to different cycles for subsequent estimation. To apply the Kalman Filter, a state-space model with two state variables and the system noise determined by queue-forming acceleration is established, which can characterize the stochastic property of queue forming. The Kalman Filter with joining points as measurement input recursively estimates real-time queue lengths; on the other hand, queue-discharging waves are estimated with a line fitted to leaving points. By calculating the crossing point of the queue-forming wave and the queue-discharging wave of a cycle, the maximum queue length is also estimated. A case study with DiDi mobile sensor data and ground truth maximum queue lengths at Huanggang-Fuzhong intersection, Shenzhen, China, shows that the mean absolute percentage error is only 11.2%. Moreover, the sensitivity analysis shows that the proposed estimation method achieves much better performance than the classical linear regression method, especially in extremely low penetration rates.

Organization of the primate face motor cortex as revealed by intracortical microstimulation and electrophysiological identification of afferent inputs and corticobulbar projections

1988 ◽  
Vol 59 (3) ◽  
pp. 796-818 ◽  
Author(s):  
C. S. Huang ◽  
M. A. Sirisko ◽  
H. Hiraba ◽  
G. M. Murray ◽  
B. J. Sessle
Keyword(s):  
Motor Cortex ◽  
Single Neuron ◽  
Primary Motor Cortex ◽  
General Pattern ◽  
Emg Activity ◽  
Projection Neurons ◽  
Intracortical Microstimulation ◽  
Facial Musculature ◽  
The Face ◽  
Afferent Inputs

1. The technique of intracortical microstimulation (ICMS), supplemented by single-neuron recording, was used to carry out an extensive mapping of the face primary motor cortex. The ICMS study involved a total of 969 microelectrode penetrations carried out in 10 unanesthetized monkeys (Macaca fascicularis). 2. Monitoring of ICMS-evoked movements and associated electromyographic (EMG) activity revealed a general pattern of motor cortical organization. This was characterized by a representation of the facial musculature, which partially enclosed and overlapped the rostral, medial, and caudal borders of the more laterally located cortical regions representing the jaw and tongue musculatures. Responses were evoked at ICMS thresholds as low as 1 microA, and the latency of the suprathreshold EMG responses ranged from 10 to 45 ms. 3. Although contralateral movements predominated, a representation of ipsilateral movements was found, which was much more extensive than previously reported and which was intermingled with the contralateral representations in the anterior face motor cortex. 4. In examining the fine organizational pattern of the representations, we found clear evidence for multiple representation of a particular muscle, thus supporting other investigations of the motor cortex, which indicate that multiple, yet discrete, efferent microzones represent an essential organizational principle of the motor cortex. 5. The close interrelationship of the representations of all three muscle groups, as well as the presence of a considerable ipsilateral representation, may allow for the necessary integration of unilateral or bilateral activities of the numerous face, jaw, and tongue muscles, which is a feature of many of the movement patterns in which these various muscles participate. 6. In six of these same animals, plus an additional two animals, single-neuron recordings were made in the motor and adjacent sensory cortices in the anesthetized state. These neurons were electrophysiologically identified as corticobulbar projection neurons or as nonprojection neurons responsive to superficial or deep orofacial afferent inputs. The rostral, medial, lateral, and caudal borders of the face motor cortex were delineated with greater definition by ICMS and these electrophysiological procedures than by cytoarchitectonic features alone. We noted that there was an approximate fit in area 4 between the extent of projection neurons and field potentials anti-dromically evoked from the brain stem and the extent of positive ICMS sites.(ABSTRACT TRUNCATED AT 400 WORDS)

scholarly journals Fault Diagnosis of Transmission Line using Feed Forward Neural Network

2019 ◽  
Vol 8 (9S2) ◽  
pp. 263-268
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Transmission Lines ◽  
Field Work ◽  
Neural Nets ◽  
Feed Forward Neural Network ◽  
Training Time ◽  
Optimum Result ◽  
Human Effort ◽  
Selection Of

The implementation of neural network for the fault diagnosis is to improve the dependability of the proposed scheme by providing a more accurate, faster diagnosis relaying scheme as compared with the conventional relaying schemes. It is important to improve the relaying schemes regarding the shortcoming of the system and increase the dependability of the system by using the proposed relaying scheme. It also provide more accurate, faster relaying scheme. It also gives selective schemes as compared to conventional system. The techniques for survey employed some methods for the collection of data which involved a literature review of journals, from review on books, newspaper, magazines as well as field work, additional data was collected from researchers who are working in this field. To achieve optimum result we have to improve following things: (i) Training time, (ii) Selection of training vector, (iii) Upgrading of trained neural nets and integration of technologies. AI with its promise of adaptive training and generalization deserves scope. As a result we obtain a system which is more reliable, more accurate, and faster, has more dependability as well as it will selective according to the proposed relaying scheme as compare to the conventional relaying scheme. This system helps us to reduce the shortcoming like major faults which we faced in the complex system of transmission lines which will helps in reducing human effort, saves cost for maintaining the transmission system.

scholarly journals With the Permission of Microtubules: An Updated Overview on Microtubule Function During Axon Pathfinding

2021 ◽  
Vol 14 ◽  
Author(s):  
Carlos Sánchez-Huertas ◽  
Eloísa Herrera
Keyword(s):  
Growth Cone ◽  
Intracellular Signaling ◽  
Expression Patterns ◽  
Brain Regions ◽  
Extracellular Proteins ◽  
Projection Neurons ◽  
Axon Pathfinding ◽  
Guidance Receptors ◽  
Spatio Temporal ◽  
Intracellular Cascades

During the establishment of neural circuitry axons often need to cover long distances to reach remote targets. The stereotyped navigation of these axons defines the connectivity between brain regions and cellular subtypes. This chemotrophic guidance process mostly relies on the spatio-temporal expression patterns of extracellular proteins and the selective expression of their receptors in projection neurons. Axon guidance is stimulated by guidance proteins and implemented by neuronal traction forces at the growth cones, which engage local cytoskeleton regulators and cell adhesion proteins. Different layers of guidance signaling regulation, such as the cleavage and processing of receptors, the expression of co-receptors and a wide variety of intracellular cascades downstream of receptors activation, have been progressively unveiled. Also, in the last decades, the regulation of microtubule (MT) assembly, stability and interactions with the submembranous actin network in the growth cone have emerged as crucial effector mechanisms in axon pathfinding. In this review, we will delve into the intracellular signaling cascades downstream of guidance receptors that converge on the MT cytoskeleton of the growing axon. In particular, we will focus on the microtubule-associated proteins (MAPs) network responsible of MT dynamics in the axon and growth cone. Complementarily, we will discuss new evidences that connect defects in MT scaffold proteins, MAPs or MT-based motors and axon misrouting during brain development.

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