scholarly journals Assessment of optogenetically-driven strategies for prosthetic restoration of cortical vision in large-scale neural simulation of V1

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jan Antolik ◽  
Quentin Sabatier ◽  
Charlie Galle ◽  
Yves Frégnac ◽  
Ryad Benosman
Keyword(s):  
Large Scale ◽  
Spatial Configuration ◽  
Activity Patterns ◽  
Neural Encoding ◽  
External Stimulation ◽  
Light Pattern ◽  
Cortical Level ◽  
Model Combining ◽  
Strong Candidate ◽  
Functional Relevance

AbstractThe neural encoding of visual features in primary visual cortex (V1) is well understood, with strong correlates to low-level perception, making V1 a strong candidate for vision restoration through neuroprosthetics. However, the functional relevance of neural dynamics evoked through external stimulation directly imposed at the cortical level is poorly understood. Furthermore, protocols for designing cortical stimulation patterns that would induce a naturalistic perception of the encoded stimuli have not yet been established. Here, we demonstrate a proof of concept by solving these issues through a computational model, combining (1) a large-scale spiking neural network model of cat V1 and (2) a virtual prosthetic system transcoding the visual input into tailored light-stimulation patterns which drive in situ the optogenetically modified cortical tissue. Using such virtual experiments, we design a protocol for translating simple Fourier contrasted stimuli (gratings) into activation patterns of the optogenetic matrix stimulator. We then quantify the relationship between spatial configuration of the imposed light pattern and the induced cortical activity. Our simulations in the absence of visual drive (simulated blindness) show that optogenetic stimulation with a spatial resolution as low as 100 $$\upmu$$ μ m, and light intensity as weak as $$10^{16}$$ 10 16 photons/s/cm$$^2$$ 2 is sufficient to evoke activity patterns in V1 close to those evoked by normal vision.

scholarly journals Large-scale chromatin organisation in interphase, mitosis and meiosis

2019 ◽  
Vol 476 (15) ◽  
pp. 2141-2156 ◽  
Author(s):  
Isobel A. MacGregor ◽  
Ian R. Adams ◽  
Nick Gilbert
Keyword(s):  
Large Scale ◽  
Spatial Configuration ◽  
Three Dimensional ◽  
Cellular Division ◽  
Genome Wide ◽  
Contact Frequency ◽  
Chromatin Organisation ◽  
Functional Relevance ◽  
Mitosis And Meiosis ◽  
Mitotic Cells

Abstract The spatial configuration of chromatin is fundamental to ensure any given cell can fulfil its functional duties, from gene expression to specialised cellular division. Significant technological innovations have facilitated further insights into the structure, function and regulation of three-dimensional chromatin organisation. To date, the vast majority of investigations into chromatin organisation have been conducted in interphase and mitotic cells leaving meiotic chromatin relatively unexplored. In combination, cytological and genome-wide contact frequency analyses in mammalian germ cells have recently demonstrated that large-scale chromatin structures in meiotic prophase I are reminiscent of the sequential loop arrays found in mitotic cells, although interphase-like segmentation of transcriptionally active and inactive regions are also evident along the length of chromosomes. Here, we discuss the similarities and differences of such large-scale chromatin architecture, between interphase, mitotic and meiotic cells, as well as their functional relevance and the proposed modulatory mechanisms which underlie them.

Reconfigurable nonvolatile boolean logic with one-transistor-two-memristor for in-memory computing

2021 ◽  
Author(s):  
Ziling Wang ◽  
Li Luo ◽  
Jie Li ◽  
Lidan Wang ◽  
shukai duan
Keyword(s):  
Large Scale ◽  
Full Adder ◽  
Boolean Logic ◽  
Device Structure ◽  
Von Neumann ◽  
Computing Paradigm ◽  
Operation Process ◽  
Strong Candidate ◽  
High Flexibility ◽  
Logic Functions

Abstract In-memory computing is highly expected to break the von Neumann bottleneck and memory wall. Memristor with inherent nonvolatile property is considered to be a strong candidate to execute this new computing paradigm. In this work, we have presented a reconfigurable nonvolatile logic method based on one-transistor-two-memristor (1T2M) device structure, inhibiting the sneak path in the large-scale crossbar array. By merely adjusting the applied voltage signals, all 16 binary Boolean logic functions can be achieved in a single cell. More complex computing tasks including one-bit parallel full adder and Set-Reset latch have also been realized with optimization, showing simple operation process, high flexibility, and low computational complexity. The circuit verification based on cadence PSpice simulation is also provided, proving the feasibility of the proposed design. The work in this paper is intended to make progress in constructing architectures for in-memory computing paradigm.

An E2GPGP-GASA-Based Multi-Agent Job Shop Scheduling System

2012 ◽  
Vol 505 ◽  
pp. 65-74
Author(s):  
Lin Lin Lu ◽  
Xin Ma ◽  
Ya Xuan Wang
Keyword(s):  
Large Scale ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Simulation Software ◽  
Prototype System ◽  
Shop Scheduling ◽  
Model Combining ◽  
Proposed Model ◽  
Multi Agent ◽  
Global Planning

In this paper, a job shop scheduling model combining MAS (Multi-Agent System) with GASA (Simulated Annealing-Genetic Algorithm) is presented. The proposed model is based on the E2GPGP (extended extended generalized partial global planning) mechanism and utilizes the advantages of static intelligence algorithms with dynamic MAS. A scheduling process from ‘initialized macro-scheduling’ to ‘repeated micro-scheduling’ is designed for large-scale complex problems to enable to implement an effective and widely applicable prototype system for the job shop scheduling problem (JSSP). Under a set of theoretic strategies in the GPGP which is summarized in detail, E2GPGP is also proposed further. The GPGP-cooperation-mechanism is simulated by using simulation software DECAF for the JSSP. The results show that the proposed model based on the E2GPGP-GASA not only improves the effectiveness, but also reduces the resource cost.

scholarly journals Representational drift in the mouse visual cortex

2020 ◽  
Author(s):  
Daniel Deitch ◽  
Alon Rubin ◽  
Yaniv Ziv
Keyword(s):  
Large Scale ◽  
Activity Patterns ◽  
Population Level ◽  
Population Activity ◽  
Cortical Areas ◽  
Electrophysiological Recordings ◽  
The Face ◽  
Visual Cortical ◽  
Mouse Visual Cortex ◽  
Over Time

AbstractNeuronal representations in the hippocampus and related structures gradually change over time despite no changes in the environment or behavior. The extent to which such ‘representational drift’ occurs in sensory cortical areas and whether the hierarchy of information flow across areas affects neural-code stability have remained elusive. Here, we address these questions by analyzing large-scale optical and electrophysiological recordings from six visual cortical areas in behaving mice that were repeatedly presented with the same natural movies. We found representational drift over timescales spanning minutes to days across multiple visual areas. The drift was driven mostly by changes in individual cells’ activity rates, while their tuning changed to a lesser extent. Despite these changes, the structure of relationships between the population activity patterns remained stable and stereotypic, allowing robust maintenance of information over time. Such population-level organization may underlie stable visual perception in the face of continuous changes in neuronal responses.

scholarly journals Regression-Based Identification of Behavior-Encoding Neurons During Large-Scale Optical Imaging of Neural Activity at Cellular Resolution

2011 ◽  
Vol 105 (2) ◽  
pp. 964-980 ◽  
Author(s):  
Andrew Miri ◽  
Kayvon Daie ◽  
Rebecca D. Burdine ◽  
Emre Aksay ◽  
David W. Tank
Keyword(s):  
Time Series ◽  
Optical Imaging ◽  
Neural Activity ◽  
Laser Scanning ◽  
Large Scale ◽  
Neural Encoding ◽  
Quantitative Measurements ◽  
Cellular Resolution ◽  
Activity Measurements ◽  
General Regression

The advent of methods for optical imaging of large-scale neural activity at cellular resolution in behaving animals presents the problem of identifying behavior-encoding cells within the resulting image time series. Rapid and precise identification of cells with particular neural encoding would facilitate targeted activity measurements and perturbations useful in characterizing the operating principles of neural circuits. Here we report a regression-based approach to semiautomatically identify neurons that is based on the correlation of fluorescence time series with quantitative measurements of behavior. The approach is illustrated with a novel preparation allowing synchronous eye tracking and two-photon laser scanning fluorescence imaging of calcium changes in populations of hindbrain neurons during spontaneous eye movement in the larval zebrafish. Putative velocity-to-position oculomotor integrator neurons were identified that showed a broad spatial distribution and diversity of encoding. Optical identification of integrator neurons was confirmed with targeted loose-patch electrical recording and laser ablation. The general regression-based approach we demonstrate should be widely applicable to calcium imaging time series in behaving animals.

scholarly journals Near Real-Time Automated Early Mapping of the Perimeter of Large Forest Fires from the Aggregation of VIIRS and MODIS Active Fires in Mexico

2020 ◽  
Vol 12 (12) ◽  
pp. 2061 ◽  
Author(s):  
Carlos Ivan Briones-Herrera ◽  
Daniel José Vega-Nieva ◽  
Norma Angélica Monjarás-Vega ◽  
Jaime Briseño-Reyes ◽  
Pablito Marcelo López-Serrano ◽  
...  
Keyword(s):  
Real Time ◽  
Forest Fires ◽  
Large Scale ◽  
Infrared Imaging ◽  
Activity Patterns ◽  
Burned Area ◽  
Management Decision ◽  
Coarse Scale ◽  
Early Evaluation ◽  
Active Fire

In contrast with current operational products of burned area, which are generally available one month after the fire, active fires are readily available, with potential application for early evaluation of approximate fire perimeters to support fire management decision making in near real time. While previous coarse-scale studies have focused on relating the number of active fires to a burned area, some local-scale studies have proposed the spatial aggregation of active fires to directly obtain early estimate perimeters from active fires. Nevertheless, further analysis of this latter technique, including the definition of aggregation distance and large-scale testing, is still required. There is a need for studies that evaluate the potential of active fire aggregation for rapid initial fire perimeter delineation, particularly taking advantage of the improved spatial resolution of the Visible Infrared Imaging Radiometer (VIIRS) 375 m, over large areas and long periods of study. The current study tested the use of convex hull algorithms for deriving coarse-scale perimeters from Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) active fire detections, compared against the mapped perimeter of the MODIS collection 6 (MCD64A1) burned area. We analyzed the effect of aggregation distance (750, 1000, 1125 and 1500 m) on the relationships of active fire perimeters with MCD64A1, for both individual fire perimeter prediction and total burned area estimation, for the period 2012–2108 in Mexico. The aggregation of active fire detections from MODIS and VIIRS demonstrated a potential to offer coarse-scale early estimates of the perimeters of large fires, which can be available to support fire monitoring and management in near real time. Total burned area predicted from aggregated active fires followed the same temporal behavior as the standard MCD64A1 burned area, with potential to also account for the role of smaller fires detected by the thermal anomalies. The proposed methodology, based on easily available algorithms of point aggregation, is susceptible to be utilized both for near real-time and historical fire perimeter evaluation elsewhere. Future studies might test active fires aggregation between regions or biomes with contrasting fuel characteristics and human activity patterns against medium resolution (e.g., Landsat and Sentinel) fire perimeters. Furthermore, coarse-scale active fire perimeters might be utilized to locate areas where such higher-resolution imagery can be downloaded to improve the evaluation of fire extent and impact.

scholarly journals Simple models including energy and spike constraints reproduce complex activity patterns and metabolic disruptions

2020 ◽  
Author(s):  
Tanguy Fardet ◽  
Anna Levina
Keyword(s):  
Disease Progression ◽  
Neurological Disorders ◽  
Large Scale ◽  
Time Course ◽  
Neuronal Response ◽  
Activity Patterns ◽  
Complex Activity ◽  
Course Of Disease ◽  
New Models ◽  
Neuronal Disorders

AbstractIn this work, we introduce new phenomenological neuronal models (eLIF and mAdExp) that account for energy supply and demand in the cell as well as the inactivation of spike generation how these interact with subthreshold and spiking dynamics. Including these constraints, the new models reproduce a broad range of biologically-relevant behaviors that are identified to be crucial in many neurological disorders, but were not captured by commonly used phenomenological models. Because of their low dimensionality eLIF and mAdExp open the possibility of future large-scale simulations for more realistic studies of brain circuits involved in neuronal disorders. The new models enable both more accurate modeling and the possibility to study energy-associated disorders over the whole time-course of disease progression instead of only comparing the initially healthy status with the final diseased state. These models, therefore, provide new theoretical and computational methods to assess the opportunities of early diagnostics and the potential of energy-centered approaches to improve therapies.Author summaryNeurons, even “at rest”, require a constant supply of energy to function. They cannot sustain high-frequency activity over long periods because of regulatory mechanisms, such as adaptation or sodium channels inactivation, and metabolic limitations. These limitations are especially severe in many neuronal disorders, where energy can become insufficient and make the neuronal response change drastically, leading to increased burstiness, network oscillations, or seizures. Capturing such behaviors and impact of energy constraints on them is an essential prerequisite to study disorders such as Parkinson’s disease and epilepsy. However, energy and spiking constraints are not present in any of the standard neuronal models used in computational neuroscience. Here we introduce models that provide a simple and scalable way to account for these features, enabling large-scale theoretical and computational studies of neurological disorders and activity patterns that could not be captured by previously used models. These models provide a way to study energy-associated disorders over the whole time-course of disease progression, and they enable a better assessment of energy-centered approaches to improve therapies.

scholarly journals Human Sensory Neuron-like Cells and Glycated Collagen Matrix as a Model for the Screening of Analgesic Compounds

Cells ◽  
2022 ◽  
Vol 11 (2) ◽  
pp. 247
Author(s):  
Michelle Cristiane Bufalo ◽  
Maíra Estanislau Soares de Almeida ◽  
José Ricardo Jensen ◽  
Carlos DeOcesano-Pereira ◽  
Flavio Lichtenstein ◽  
...  
Keyword(s):  
Substance P ◽  
Sensory Neuron ◽  
Large Scale ◽  
Functional Model ◽  
Collagen Matrix ◽  
P Release ◽  
Model Combining ◽  
Glycation End Products ◽  
Substance P Release ◽  
Large Scale Screening

Increased collagen-derived advanced glycation end-products (AGEs) are consistently related to painful diseases, including osteoarthritis, diabetic neuropathy, and neurodegenerative disorders. We have recently developed a model combining a two-dimensional glycated extracellular matrix (ECM-GC) and primary dorsal root ganglion (DRG) that mimicked a pro-nociceptive microenvironment. However, culturing primary cells is still a challenge for large-scale screening studies. Here, we characterized a new model using ECM-GC as a stimulus for human sensory-like neurons differentiated from SH-SY5Y cell lines to screen for analgesic compounds. First, we confirmed that the differentiation process induces the expression of neuron markers (MAP2, RBFOX3 (NeuN), and TUBB3 (β-III tubulin), as well as sensory neuron markers critical for pain sensation (TRPV1, SCN9A (Nav1.7), SCN10A (Nav1.8), and SCN11A (Nav1.9). Next, we showed that ECM-GC increased c-Fos expression in human sensory-like neurons, which is suggestive of neuronal activation. In addition, ECM-GC upregulated the expression of critical genes involved in pain, including SCN9A and TACR1. Of interest, ECM-GC induced substance P release, a neuropeptide widely involved in neuroinflammation and pain. Finally, morphine, the prototype opiate, decreased ECM-GC-induced substance P release. Together, our results suggest that we established a functional model that can be useful as a platform for screening candidates for the management of painful conditions.

scholarly journals Selective entrainment of gamma subbands by different slow network oscillations

2017 ◽  
Vol 114 (17) ◽  
pp. 4519-4524 ◽  
Author(s):  
Weiwei Zhong ◽  
Mareva Ciatipis ◽  
Thérèse Wolfenstetter ◽  
Jakob Jessberger ◽  
Carola Müller ◽  
...  
Keyword(s):  
Large Scale ◽  
Dorsal Hippocampus ◽  
Activity Patterns ◽  
Specific Interaction ◽  
Brain Regions ◽  
Network Activity ◽  
Gamma Frequency ◽  
Cornu Ammonis ◽  
Oscillatory Coupling ◽  
Fast Oscillations

Theta oscillations (4–12 Hz) are thought to provide a common temporal reference for the exchange of information among distant brain networks. On the other hand, faster gamma-frequency oscillations (30–160 Hz) nested within theta cycles are believed to underlie local information processing. Whether oscillatory coupling between global and local oscillations, as showcased by theta-gamma coupling, is a general coding mechanism remains unknown. Here, we investigated two different patterns of oscillatory network activity, theta and respiration-induced network rhythms, in four brain regions of freely moving mice: olfactory bulb (OB), prelimbic cortex (PLC), parietal cortex (PAC), and dorsal hippocampus [cornu ammonis 1 (CA1)]. We report differential state- and region-specific coupling between the slow large-scale rhythms and superimposed fast oscillations. During awake immobility, all four regions displayed a respiration-entrained rhythm (RR) with decreasing power from OB to CA1, which coupled exclusively to the 80- to 120-Hz gamma subband (γ2). During exploration, when theta activity was prevailing, OB and PLC still showed exclusive coupling of RR with γ2 and no theta-gamma coupling, whereas PAC and CA1 switched to selective coupling of theta with 40- to 80-Hz (γ1) and 120- to 160-Hz (γ3) gamma subbands. Our data illustrate a strong, specific interaction between neuronal activity patterns and respiration. Moreover, our results suggest that the coupling between slow and fast oscillations is a general brain mechanism not limited to the theta rhythm.

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