Spatial information in large-scale neural recordings

Extracting spatial-temporal coherent patterns in large-scale neural recordings using dynamic mode decomposition.

BACKGROUND There is a broad need in neuroscience to understand and visualize large-scale recordings of neural activity, big data acquired by tens or hundreds of electrodes recording dynamic brain activity over minutes to hours. Such datasets are characterized by coherent patterns across both space and time, yet existing computational methods are typically restricted to analysis either in space ...

Geographical Origin Prediction of Folk Music Recordings from the United Kingdom

Field recordings from ethnomusicological research since the beginning of the 20th century are available today in large digitised music archives. The application of music information retrieval and data mining technologies can aid large-scale data processing leading to a better understanding of the history of cultural exchange. In this paper we focus on folk and traditional music from the United ...

تجمع بیماری در مقیاسی وسیع و کاربرد آن در مطالعات اپیدمیولوژی و بهداشت

Spatial autocorrelation statistics provide summary information about the spatial arrangement of data in a map. In fact, these statistics compare neighboring area values in order to assess the level of large scale clustering. Whenever a large number of neighboring areas have either relatively large or relatively small values, large scale clustering may be detected. Detecting such clustering is a...

Decentralized Interaction Estimators in Large Scale Power Systems with Neural Networks.

Large-Scale Bird Sound Classification using Convolutional Neural Networks

Identifying bird species in audio recordings is a challenging field of research. In this paper, we summarize a method for large-scale bird sound classification in the context of the LifeCLEF 2017 bird identification task. We used a variety of convolutional neural networks to generate features extracted from visual representations of field recordings. The BirdCLEF 2017 training dataset consist o...

Analysis and modeling of massively parallel neural signals - 2010 Special Issue

Uncovering how the brain processes information requires large-scale observations of neuronal activity. Recent progresses in experimental techniques provide novel methods to achieve massively parallel recordings of neuronal activity. For instance, multi-channel electrodes and fluorescent molecular sensors are now commonly used to simultaneously record the spiking activity of hundreds or thousand...