methods in neuronal modeling from ions to networks is available in our digital library an online access to it is set as public so you can get it instantly. Our books collection spans in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Merely said, the methods in neuronal modeling from ions to networks is universally compatible with any devices to read.

Methods In Neuronal Modeling From Ions To Networks

Based on the Hodgkin-Huxley model, the present study established a fully connected structural neural network to simulate the neural activity and energy consumption of the network by neural energy coding theory. The numerical simulation result showed that the periodicity of the network energy distribution was positively correlated to the number of neurons and coupling strength, but negatively correlated to signal transmitting delay. Moreover, a relationship was established between the energy distribution feature and the synchronous oscillation of the neural network, which showed that when the proportion of negative energy in power consumption curve was high, the synchronous oscillation of the neural network was apparent. In addition, comparison with the simulation result of structural neural network based on the Wang-Zhang biophysical model of neurons showed that both models were essentially consistent.

/pdf/the-energy-coding-of-a-structural-neural-network-based-on-tv3f1c5txl.pdf

The Energy Coding of a Structural Neural Network Based on the Hodgkin-Huxley Model.

Measures of spike train synchrony for data with multiple time scales

Researchers have used eye-tracking methods to infer cognitive processes during decision making in choice tasks involving visual materials. Gaze likelihood analysis has shown a cascading effect, suggestive of a causal role for the gaze in preference formation during evaluative decision making. According to the gaze bias hypothesis, the gaze serves to build commitment gradually towards a choice. Here, we applied gaze likelihood analysis in a two-choice version of the well-known Iowa Gambling Task. This task requires active learning of the value of different choice options. As such, it does not involve visual preference formation, but choice optimization through learning. In Experiment 1 we asked subjects to choose between two decks with different payoff structures, and to give their responses using mouse clicks. Two groups of subjects were exposed to stable versus varying outcome contingencies. The analysis revealed a pronounced gaze bias towards the chosen stimuli in both groups of subjects, plateauing at more than 400 ms before the choice. The early plateauing suggested that the gaze effect partially reflected eye-hand coordination. In Experiment 2 we asked subjects to give responses using a key press. The results again showed a clear gaze bias towards the chosen deck, this time without any influence from eye-hand coordination. In both experiments, there was a clear gaze bias towards the choice even though the gaze fixations did not narrowly focus on the spatial positions of choice options. Taken together, the data suggested a role for gaze in coarse spatial indexing during non-perceptual decision making.

A gaze bias with coarse spatial indexing during a gambling task

We propose a simple method to measure synchronization and time delay patterns between signals. It is based on the relative timings of events in the time series, defined e.g. as local maxima. The degree of synchronization is obtained from the number of quasi-simultaneous appearances of events, and the delay is calculated from the precedence of events in one signal with respect to the other. Moreover, we can easily visualize the time evolution of the delay and synchronization level with an excellent resolution. 
We apply the algorithm to short rat EEG signals, some of them containing spikes. We also apply it to an intracranial human EEG recording containing an epileptic seizure, and we propose that the method might be useful for the detection of foci and for seizure prediction. It can be easily extended to other types of data and it is very simple and fast, thus being suitable for on-line implementations.

Event synchronization: a simple and fast method to measure synchronicity and time delay patterns

In this paper, the dynamics of a map-based model is proposed firstly. It is a simple model which can not only reproduce rich behaviors of biological neurons but also compute efficiently. Then, the dynamics of two coupled maps that model the behavior of two electrically coupled neurons is discussed. By tuning the coupling strength, synchronization of two spiking or bursting neurons are simulated. Furthermore, the spatiotemporal behavior of a small-world neuronal network using map-based model is studied. Detailed investigations reveal that the collective dynamics of neuronal activity will be affected by varying some key parameters, such as the coupling strength of neurons, connection probability and the number of nearest neighbor in small-world topology. Our study suggests that the map-based model will give us a new opportunity to reproduce the real biological network containing a large number of neurons.

Spatiotemporal Behavior of Small-World Neuronal Networks Using a Map-Based Model

In both experimental and computational neuroscience, it is a frequent task to estimate the degree of synchrony or reliability between two or multiple spike trains. ISI-distance method is one of the most common used methods based on the coefficient of variation, which is parameter free and time scale independent. However, it can only measure regular spiking synchronization well while not good at measuring bursting synchronization. In this paper, an improved method of measuring multiple spike train synchrony is proposed, which can measure both regular and burst spike trains well. Using a simulated neuronal network of Hindmarsh–Rose neurons, it is demonstrated that the performance of our methods in distinguish different levels of multiple neuron spike train synchrony performs as well as previous methods. We expect that the method proposed in this paper will be an overall tool for measuring the synchrony of all kinds of spike trains and applications.

An Improved Method of Measuring Multiple Spike Train Synchrony

Extensive experiments on rats have shown that environmental cues play an important role in goal locating and navigation. Major studies about locating and navigation are carried out based only on place cells. Nevertheless, it is known that navigation may also rely on grid cells. Therefore, we model locating and navigation based on both, thus developing a novel grid-cell model, from which firing fields of grid cells can be obtained. We found a continuous-time dynamic system to describe learning and direction selection. In our simulation experiment, according to the results from physiology experiments, we successfully rebuild place fields of place cells and firing fields of grid cells. We analyzed the factors affecting the locating accuracy. Results show that the learning rate, firing threshold and cell number can influence the outcomes from various tasks. We used our system model to perform a goal navigation task and showed that paths that are changed for every run in one experiment converged to a stable one after several runs.

/pdf/locating-and-navigation-mechanism-based-on-place-cell-and-2vklyt0v9k.pdf

Locating and navigation mechanism based on place-cell and grid-cell models

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Chuankui Yan

Author Tools

Chat about Author

Papers

Spatiotemporal Behavior of Small-World Neuronal Networks Using a Map-Based Model

An Improved Method of Measuring Multiple Spike Train Synchrony

Locating and navigation mechanism based on place-cell and grid-cell models