scholarly journals A wake-active locomotion circuit depolarizes a sleep-active neuron to switch on sleep

PLoS Biology ◽  
2020 ◽  
Vol 18 (2) ◽  
pp. e3000361 ◽  
Author(s):  
Elisabeth Maluck ◽  
Inka Busack ◽  
Judith Besseling ◽  
Florentin Masurat ◽  
Michal Turek ◽  
...  
Keyword(s):  
Active Neuron ◽  
Active Locomotion

scholarly journals Biological modelling of a computational spiking neural network with neuronal avalanches

2017 ◽  
Vol 375 (2096) ◽  
pp. 20160286 ◽  
Author(s):  
Xiumin Li ◽  
Qing Chen ◽  
Fangzheng Xue
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Critical State ◽  
Spike Timing ◽  
Spiking Neural Networks ◽  
Mathematical Methods ◽  
Computational Accuracy ◽  
Active Neuron ◽  
Computational Performance ◽  
Neuronal Avalanches

In recent years, an increasing number of studies have demonstrated that networks in the brain can self-organize into a critical state where dynamics exhibit a mixture of ordered and disordered patterns. This critical branching phenomenon is termed neuronal avalanches. It has been hypothesized that the homeostatic level balanced between stability and plasticity of this critical state may be the optimal state for performing diverse neural computational tasks. However, the critical region for high performance is narrow and sensitive for spiking neural networks (SNNs). In this paper, we investigated the role of the critical state in neural computations based on liquid-state machines, a biologically plausible computational neural network model for real-time computing. The computational performance of an SNN when operating at the critical state and, in particular, with spike-timing-dependent plasticity for updating synaptic weights is investigated. The network is found to show the best computational performance when it is subjected to critical dynamic states. Moreover, the active-neuron-dominant structure refined from synaptic learning can remarkably enhance the robustness of the critical state and further improve computational accuracy. These results may have important implications in the modelling of spiking neural networks with optimal computational performance. This article is part of the themed issue ‘Mathematical methods in medicine: neuroscience, cardiology and pathology’.

scholarly journals An AP2 Transcription Factor Is Required for a Sleep-Active Neuron to Induce Sleep-like Quiescence in C. elegans

2013 ◽  
Vol 23 (22) ◽  
pp. 2215-2223 ◽  
Author(s):  
Michal Turek ◽  
Ines Lewandrowski ◽  
Henrik Bringmann
Keyword(s):  
Transcription Factor ◽  
Active Neuron ◽  
C Elegans ◽  
Ap2 Transcription Factor

scholarly journals Human Creativity and Consciousness: Unintended Consequences of the Brain’s Extraordinary Energy Efficiency?

2020 ◽  
Author(s):  
Tim Palmer
Keyword(s):  
Energy Efficiency ◽  
Human Brain ◽  
Quantum Physics ◽  
Unintended Consequences ◽  
Large Network ◽  
Active Neuron ◽  
Available Energy ◽  
Human Creativity ◽  
The One ◽  
The Brain

It is proposed that both human creativity and human consciousness are (unintended) consequences of the human brain’s extraordinary energy efficiency. The topics of creativity and consciousness are treated separately, though have a common sub-structure. It is argued that creativity arises from a synergy between two cognitive modes of the human brain (which broadly coincide with Kahneman’s Systems 1 and 2). In the first, available energy is spread across a relatively large network of neurons. As such, the amount of energy per active neuron is so small that the operation of such neurons is susceptible to thermal (ultimately quantum decoherent) noise. In the second, available energy is focussed on a small enough subset of neurons to guarantee a deterministic operation. An illustration of how this synergy can lead to creativity with implications for computing in silicon are discussed. Starting with a discussion of the concept of free will, the notion of consciousness is defined in terms of an awareness of what are perceived to be nearby counterfactual worlds in state space. It is argued that such awareness arises from an interplay between our memories on the one hand, and quantum physical mechanisms (where, unlike in classical physics, nearby counterfactual worlds play an indispensable dynamical role) in the ion channels of neural networks. As with the brain’s susceptibility to noise, it is argued that in situations where quantum physics plays a role in the brain, it does so for reasons of energy efficiency. As an illustration of this definition of consciousness, a novel proposal is outlined as to why quantum entanglement appears so counter-intuitive.

scholarly journals A New Active Locomotion Capsule Endoscopy under Magnetic Control and Automated Reading Program

2020 ◽  
Vol 53 (4) ◽  
pp. 395-401
Author(s):  
Dong Jun Oh ◽  
Kwang Seop Kim ◽  
Yun Jeong Lim
Keyword(s):  
Capsule Endoscopy ◽  
Reading Program ◽  
Magnetic Control ◽  
Active Locomotion

Using Depth Vision for Terrain Detection during Active Locomotion*

2021 ◽  
Author(s):  
Ali H. A. Al-dabbagh ◽  
Renaud Ronsse
Keyword(s):  
Depth Vision ◽  
Active Locomotion

scholarly journals Fast and robust active neuron segmentation in two-photon calcium imaging using spatiotemporal deep learning

2019 ◽  
Vol 116 (17) ◽  
pp. 8554-8563 ◽  
Author(s):  
Somayyeh Soltanian-Zadeh ◽  
Kaan Sahingur ◽  
Sarah Blau ◽  
Yiyang Gong ◽  
Sina Farsiu
Keyword(s):  
Real Time ◽  
Calcium Imaging ◽  
Large Scale ◽  
Cortical Layer ◽  
Fast Method ◽  
Active Neuron ◽  
Neuronal Coding ◽  
Two Photon ◽  
Neuron Density

Calcium imaging records large-scale neuronal activity with cellular resolution in vivo. Automated, fast, and reliable active neuron segmentation is a critical step in the analysis workflow of utilizing neuronal signals in real-time behavioral studies for discovery of neuronal coding properties. Here, to exploit the full spatiotemporal information in two-photon calcium imaging movies, we propose a 3D convolutional neural network to identify and segment active neurons. By utilizing a variety of two-photon microscopy datasets, we show that our method outperforms state-of-the-art techniques and is on a par with manual segmentation. Furthermore, we demonstrate that the network trained on data recorded at a specific cortical layer can be used to accurately segment active neurons from another layer with different neuron density. Finally, our work documents significant tabulation flaws in one of the most cited and active online scientific challenges in neuron segmentation. As our computationally fast method is an invaluable tool for a large spectrum of real-time optogenetic experiments, we have made our open-source software and carefully annotated dataset freely available online.

Superelastic leg design optimization for an endoscopic capsule with active locomotion

2008 ◽  
Vol 18 (1) ◽  
pp. 015001 ◽  
Author(s):  
Elisa Buselli ◽  
Pietro Valdastri ◽  
Marco Quirini ◽  
Arianna Menciassi ◽  
Paolo Dario
Keyword(s):  
Design Optimization ◽  
Endoscopic Capsule ◽  
Leg Design ◽  
Active Locomotion

scholarly journals Development and Verification of Mechanism for Enhancement of Steering Angle and Active Locomotion for Magnetic Micro Active-Guidewire

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 31103-31113
Author(s):  
Guk-Hong Jeon ◽  
Sung Hoon Kim
Keyword(s):  
Steering Angle ◽  
Active Locomotion

scholarly journals Quantification of the locomotive behavior of polymorphonuclear leukocytes in clot preparations

Blood ◽  
1982 ◽  
Vol 59 (5) ◽  
pp. 946-951 ◽  
Author(s):  
TH Howard
Keyword(s):  
Polymorphonuclear Leukocytes ◽  
Normal Subjects ◽  
Time Lapse ◽  
Turning Behavior ◽  
Multiple Parameters ◽  
Human Pmns ◽  
Direction Distance ◽  
Active Locomotion ◽  
Locomotive Behavior

Abstract Time-lapse videotape recordings of polymorphonuclear leukocytes (PMNs) from clot preparations were used to quantify the locomotive behavior of individual PMNs from normal subjects. Tracings derived from the videotapes allow one to quantify multiple parameters of the locomotive behavior of PMNs--direction, distance, rate, and angle of turn. The results obtained are reproducible from subject-to-subject and from preparation-to-preparation. The method allows the investigator to record the locomotive behavior of 100 cells simultaneously within a 5- min period and analyze the recording as time permits. We utilized this technique to compare the locomotive behavior of slow and fast PMNs (arbitrarily defined as cells that move less than or equal to 7.0 micrometer/min and greater than 7.0 micrometer/min mean rate of locomotion, respectively). The studies show that slow and fast PMNs, thus defined, differ not only in mean rate of locomotion but also in their rate of locomotion during periods of active locomotion, in the number of periods of inactivity/PMN/5 min (slow = 1.65 +/- 0.31; fast = 0.36 +/- 0.12), and in their turning behavior as measured by angle of turn (slow = 92 degrees +/- 39 degrees; fast = 39 degrees +/- 35 degrees). These results show that human PMNs from clot preparations are remarkably heterogeneous in their locomotive behavior, and the results suggest this heterogeneity is due to endogenous differences within cells.

scholarly journals Photo-Controlled Waves and Active Locomotion

2017 ◽  
Vol 23 (47) ◽  
pp. 11181-11188 ◽  
Author(s):  
Irving R. Epstein ◽  
Qingyu Gao
Keyword(s):  
Active Locomotion
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