AIMC Topic:
Neurons
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Soma Detection in 3D Images of Neurons using Machine Learning Technique.
Neuroinformatics
Jan 1, 2018
Computing and analyzing the neuronal structure is essential to studying connectome. Two important tasks for such analysis are finding the soma and constructing the neuronal structure. Finding the soma is considered more important because it is requir...
SPICODYN: A Toolbox for the Analysis of Neuronal Network Dynamics and Connectivity from Multi-Site Spike Signal Recordings.
Neuroinformatics
Jan 1, 2018
We implemented an automated and efficient open-source software for the analysis of multi-site neuronal spike signals. The software package, named SPICODYN, has been developed as a standalone windows GUI application, using C# programming language with...
Robotic Automation of In Vivo Two-Photon Targeted Whole-Cell Patch-Clamp Electrophysiology.
Neuron
Aug 30, 2017
Whole-cell patch-clamp electrophysiological recording is a powerful technique for studying cellular function. While in vivo patch-clamp recording has recently benefited from automation, it is normally performed "blind," meaning that throughput for sa...
Neuromorphic neural interfaces: from neurophysiological inspiration to biohybrid coupling with nervous systems.
Journal of neural engineering
Aug 1, 2017
OBJECTIVE: Computation in nervous systems operates with different computational primitives, and on different hardware, than traditional digital computation and is thus subjected to different constraints from its digital counterpart regarding the use ...
Localizing neuronal somata from Multi-Electrode Array in-vivo recordings using deep learning.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2017
With the latest development in the design and fabrication of high-density Multi-Electrode Arrays (MEA) for in-vivo neural recordings, the spatiotemporal information in the recorded signals allows for refined estimation of a neuron's location around t...
NEUROPROTECTIVE EFFECT OF BOSWELLIA SERRATA AND ITS ACTIVE CONSTITUENT ACETYL 11-KETO-β-BOSWELLIC ACID AGAINST OXYGEN-GLUCOSE-SERUM DEPRIVATION-INDUCED CELL INJURY.
Acta poloniae pharmaceutica
May 1, 2017
Oxidative stress plays a key role in pathophysiology of brain ischemia. This study aimed to test whether B. serrata hydroalcoholic extract (BSE) and its active constituent 3-acetyl-1 1-keto-β-boswellic acid (AKBA) could protect neurons against ischem...
Computing by Robust Transience: How the Fronto-Parietal Network Performs Sequential, Category-Based Decisions.
Neuron
Mar 22, 2017
Decision making involves dynamic interplay between internal judgements and external perception, which has been investigated in delayed match-to-category (DMC) experiments. Our analysis of neural recordings shows that, during DMC tasks, LIP and PFC ne...
Computational Architecture of the Granular Layer of Cerebellum-Like Structures.
Cerebellum (London, England)
Feb 1, 2017
In the adaptive filter model of the cerebellum, the granular layer performs a recoding which expands incoming mossy fibre signals into a temporally diverse set of basis signals. The underlying neural mechanism is not well understood, although various...
A Dual Targeting Drug Delivery System for Penetrating Blood-Brain Barrier and Selectively Delivering siRNA to Neurons for Alzheimer's Disease Treatment.
Current pharmaceutical biotechnology
Jan 1, 2017
BACKGROUND: Alzheimer's disease (AD) is one of most serious threats to human beings, however, the treatment is hindered by blood-brain barrier and poor intra-brain cell selectivity.
Feedforward Chemical Neural Network: An In Silico Chemical System That Learns xor.
Artificial life
Jan 1, 2017
Inspired by natural biochemicals that perform complex information processing within living cells, we design and simulate a chemically implemented feedforward neural network, which learns by a novel chemical-reaction-based analogue of backpropagation....
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