scholarly journals Unsupervised spike sorting for large scale, high density multielectrode arrays

2016 ◽  
Author(s):  
Gerrit Hilgen ◽  
Martino Sorbaro ◽  
Sahar Pirmoradian ◽  
Jens-Oliver Muthmann ◽  
Ibolya E. Kepiro ◽  
...  
Keyword(s):  
Large Scale ◽  
High Density ◽  
Spike Sorting ◽  
Multielectrode Arrays ◽  
Anatomical Imaging ◽  
Multiple Electrodes ◽  
Spike Shape ◽  
Low Dimensional ◽  
Dense Sampling ◽  
Better Than

AbstractA new method for automated spike sorting for recordings with high density, large scale multielectrode arrays is presented. Exploiting the dense sampling of single neurons by multiple electrodes, we obtain an efficient, low-dimensional representation of detected spikes consisting of estimated spatial spike locations and dominant spike shape features, which enables fast and reliable clustering into single units. Millions of events can be sorted in minutes, and the method is parallelized and scales better than quadratically with the number of detected spikes. We demonstrate this method using recordings with a 4,096 channel array, and present validation based on anatomical imaging, optogenetic stimulation and model-based quality control. A comparison with semi-automated, shape-based spike sorting exposes significant limitations of conventional methods. Our analysis shows that it is feasible to reliably isolate the activity of hundreds to thousands of neurons in a single recording, and that dense, multi-channel probes substantially aid reliable spike sorting.

scholarly journals Unsupervised Spike Sorting for Large-Scale, High-Density Multielectrode Arrays

Cell Reports ◽  
2017 ◽  
Vol 18 (10) ◽  
pp. 2521-2532 ◽  
Author(s):  
Gerrit Hilgen ◽  
Martino Sorbaro ◽  
Sahar Pirmoradian ◽  
Jens-Oliver Muthmann ◽  
Ibolya Edit Kepiro ◽  
...  
Keyword(s):  
Large Scale ◽  
High Density ◽  
Spike Sorting ◽  
Multielectrode Arrays

scholarly journals Kilosort: realtime spike-sorting for extracellular electrophysiology with hundreds of channels

2016 ◽  
Author(s):  
Marius Pachitariu ◽  
Nicholas Steinmetz ◽  
Shabnam Kadir ◽  
Matteo Carandini ◽  
Harris Kenneth D.
Keyword(s):  
Large Scale ◽  
Superior Performance ◽  
Spike Sorting ◽  
Electrode Arrays ◽  
Manual Curation ◽  
Electrophysiological Recordings ◽  
Dimensional Approximation ◽  
Low Dimensional ◽  
Channel Electrode

AbstractAdvances in silicon probe technology mean that in vivo electrophysiological recordings from hundreds of channels will soon become commonplace. To interpret these recordings we need fast, scalable and accurate methods for spike sorting, whose output requires minimal time for manual curation. Here we introduce Kilosort, a spike sorting framework that meets these criteria, and show that it allows rapid and accurate sorting of large-scale in vivo data. Kilosort models the recorded voltage as a sum of template waveforms triggered on the spike times, allowing overlapping spikes to be identified and resolved. Rapid processing is achieved thanks to a novel low-dimensional approximation for the spatiotemporal distribution of each template, and to batch-based optimization on GPUs. A novel post-clustering merging step based on the continuity of the templates substantially reduces the requirement for subsequent manual curation operations. We compare Kilosort to an established algorithm on data obtained from 384-channel electrodes, and show superior performance, at much reduced processing times. Data from 384-channel electrode arrays can be processed in approximately realtime. Kilosort is an important step towards fully automated spike sorting of multichannel electrode recordings, and is freely available (github.com/cortex-lab/Kilosort).

PENGEMBANGAN MEDIA BIG BOOK UNTUK MENINGKATKAN HASIL BELAJAR PECAHAN SENILAI SISWA SD

2018 ◽  
Vol 16 (1) ◽  
pp. 67-76
Author(s):  
Disyacitta Neolia Firdana ◽  
Trimurtini Trimurtini
Keyword(s):  
Learning Outcomes ◽  
Large Scale ◽  
Fourth Grade ◽  
Learning Activities ◽  
Equivalent Fractions ◽  
Fourth Grade Students ◽  
Teacher Needs ◽  
The Media ◽  
Test Result ◽  
Better Than

This research aimed to determine the properness and effectiveness of the big book media on learning equivalent fractions of fourth grade students. The method of research is Research and Development  (R&D). This study was conducted in fourth grade of SDN Karanganyar 02 Kota Semarang. Data sources from media validation, material validation, learning outcomes, and teacher and students responses on developed media. Pre-experimental research design with one group pretest-posttest design. Big book developed consist of equivalent fractions material, students learning activities sheets with rectangle and circle shape pictures, and questions about equivalent fractions. Big book was developed based on students and teacher needs. This big book fulfill the media validity of 3,75 with very good criteria and scored 3 by material experts with good criteria. In large-scale trial, the result of students posttest have learning outcomes completness 82,14%. The result of N-gain calculation with result 0,55 indicates the criterion “medium”. The t-test result 9,6320 > 2,0484 which means the average of posttest outcomes is better than the average of pretest outcomes. Based on that data, this study has produced big book media which proper and effective as a media of learning equivalent fractions of fourth grade elementary school.

scholarly journals Extracellular detection of neuronal coupling

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Elmer Guzman ◽  
Zhuowei Cheng ◽  
Paul K. Hansma ◽  
Kenneth R. Tovar ◽  
Linda R. Petzold ◽  
...  
Keyword(s):  
Action Potentials ◽  
Microelectrode Arrays ◽  
Short Latency ◽  
Spike Sorting ◽  
Neuronal Connectivity ◽  
Direct Stimulation ◽  
Multiple Electrodes

AbstractWe developed a method to non-invasively detect synaptic relationships among neurons from in vitro networks. Our method uses microelectrode arrays on which neurons are cultured and from which propagation of extracellular action potentials (eAPs) in single axons are recorded at multiple electrodes. Detecting eAP propagation bypasses ambiguity introduced by spike sorting. Our methods identify short latency spiking relationships between neurons with properties expected of synaptically coupled neurons, namely they were recapitulated by direct stimulation and were sensitive to changing the number of active synaptic sites. Our methods enabled us to assemble a functional subset of neuronal connectivity in our cultures.

scholarly journals Assessment of Numerical Methods for Plunging Breaking Wave Predictions

2021 ◽  
Vol 9 (3) ◽  
pp. 264
Author(s):  
Shanti Bhushan ◽  
Oumnia El Fajri ◽  
Graham Hubbard ◽  
Bradley Chambers ◽  
Christopher Kees
Keyword(s):  
Solitary Wave ◽  
Wave Breaking ◽  
Large Scale ◽  
Turbulence Models ◽  
Navier Stokes ◽  
Wave Crest ◽  
Breaking Wave ◽  
Rans Turbulence Models ◽  
Run Up ◽  
Better Than

This study evaluates the capability of Navier–Stokes solvers in predicting forward and backward plunging breaking, including assessment of the effect of grid resolution, turbulence model, and VoF, CLSVoF interface models on predictions. For this purpose, 2D simulations are performed for four test cases: dam break, solitary wave run up on a slope, flow over a submerged bump, and solitary wave over a submerged rectangular obstacle. Plunging wave breaking involves high wave crest, plunger formation, and splash up, followed by second plunger, and chaotic water motions. Coarser grids reasonably predict the wave breaking features, but finer grids are required for accurate prediction of the splash up events. However, instabilities are triggered at the air–water interface (primarily for the air flow) on very fine grids, which induces surface peel-off or kinks and roll-up of the plunger tips. Reynolds averaged Navier–Stokes (RANS) turbulence models result in high eddy-viscosity in the air–water region which decays the fluid momentum and adversely affects the predictions. Both VoF and CLSVoF methods predict the large-scale plunging breaking characteristics well; however, they vary in the prediction of the finer details. The CLSVoF solver predicts the splash-up event and secondary plunger better than the VoF solver; however, the latter predicts the plunger shape better than the former for the solitary wave run-up on a slope case.

scholarly journals Implantable computer-controlled adaptive multielectrode positioning system

2018 ◽  
Vol 119 (4) ◽  
pp. 1471-1484 ◽  
Author(s):  
E. Ferrea ◽  
L. Suriya-Arunroj ◽  
D. Hoehl ◽  
U. Thomas ◽  
A. Gail
Keyword(s):  
Cerebral Cortex ◽  
Large Scale ◽  
Nonhuman Primates ◽  
Tissue Response ◽  
High Signal ◽  
Signal Quality ◽  
Positioning System ◽  
Multielectrode Arrays ◽  
User Friendliness ◽  
Computer Controlled

Acute neuronal recordings performed with metal microelectrodes in nonhuman primates allow investigating the neural substrate of complex cognitive behaviors. Yet the daily reinsertion and positioning of the electrodes prevents recording from many neurons simultaneously, limiting the suitability of these types of recordings for brain-computer interface applications or for large-scale population statistical methods on a trial-by-trial basis. In contrast, chronically implanted multielectrode arrays offer the opportunity to record from many neurons simultaneously, but immovable electrodes prevent optimization of the signal during and after implantation and cause the tissue response to progressively impair the transduced signal quality, thereby limiting the number of different neurons that can be recorded over the lifetime of the implant. Semichronically implanted matrices of electrodes, instead, allow individually movable electrodes in depth and achieve higher channel count compared with acute methods, hence partially overcoming these limitations. Existing semichronic systems with higher channel count lack computerized control of electrode movements, leading to limited user-friendliness and uncertainty in depth positioning. Here we demonstrate a chronically implantable adaptive multielectrode positioning system with detachable drive for computerized depth adjustment of individual electrodes over several millimeters. This semichronic 16-channel system is designed to optimize the simultaneous yield of units in an extended period following implantation since the electrodes can be independently depth adjusted with minimal effort and their signal quality continuously assessed. Importantly, the electrode array is designed to remain within a chronic recording chamber for a prolonged time or can be used for acute recordings with high signal-to-noise ratio in the cerebral cortex of nonhuman primates. NEW & NOTEWORTHY We present a 16-channel motorized, semichronic multielectrode array with individually depth-adjustable electrodes to record in the cerebral cortex of nonhuman primates. Compared with fixed-geometry arrays, this system allows repeated reestablishing of single neuron isolation. Compared with manually adjustable arrays it benefits from computer-controlled positioning. Compared with motorized semichronic systems it allows higher channel counts due to a robotic single actuator approach. Overall the system is designed to optimize the simultaneous yield of units over the course of implantation.

scholarly journals SPAN512: A new mid-latitude pulsar survey with the Nançay Radio Telescope

2012 ◽  
Vol 8 (S291) ◽  
pp. 375-377 ◽  
Author(s):  
Gregory Desvignes ◽  
Ismaël Cognard ◽  
David Champion ◽  
Patrick Lazarus ◽  
Patrice Lespagnol ◽  
...  
Keyword(s):  
Radio Telescope ◽  
Large Scale ◽  
High Time ◽  
Frequency Resolution ◽  
Integration Time ◽  
Sensitivity Limit ◽  
Long Period ◽  
Large Bandwidth ◽  
L Band ◽  
Better Than

AbstractWe present an ongoing survey with the Nançay Radio Telescope at L-band. The targeted area is 74° ≲ l < 150° and 3.5° < |b| < 5°. This survey is characterized by a long integration time (18 min), large bandwidth (512 MHz) and high time and frequency resolution (64 μs and 0.5 MHz) giving a nominal sensitivity limit of 0.055 mJy for long period pulsars. This is about 2 times better than the mid-latitude HTRU survey, and is designed to be complementary with current large scale surveys. This survey will be more sensitive to transients (RRATs, intermittent pulsars), distant and faint millisecond pulsars as well as scintillating sources (or any other kind of radio faint sources) than all previous short-integration surveys.

Large‐scale high‐density culture of hepatocytes in a liver microsystem with mimicked sinusoid blood flow

2018 ◽  
Vol 12 (12) ◽  
pp. 2266-2276
Author(s):  
Jing Liu ◽  
Chengpan Li ◽  
Shaohui Cheng ◽  
Shengnan Ya ◽  
Dayong Gao ◽  
...  
Keyword(s):  
Blood Flow ◽  
Large Scale ◽  
High Density ◽  
High Density Culture ◽  
Culture Of Hepatocytes

scholarly journals Small-variance asymptotics for non-parametric online robot learning

2018 ◽  
Vol 38 (1) ◽  
pp. 3-22 ◽  
Author(s):  
Ajay Kumar Tanwani ◽  
Sylvain Calinon
Keyword(s):  
Mixture Models ◽  
Dirichlet Process ◽  
Large Scale ◽  
Principal Component ◽  
Small Variance ◽  
Remote Manipulation ◽  
State Duration ◽  
Duration Information ◽  
Low Dimensional ◽  
Non Parametric

Small-variance asymptotics is emerging as a useful technique for inference in large-scale Bayesian non-parametric mixture models. This paper analyzes the online learning of robot manipulation tasks with Bayesian non-parametric mixture models under small-variance asymptotics. The analysis yields a scalable online sequence clustering (SOSC) algorithm that is non-parametric in the number of clusters and the subspace dimension of each cluster. SOSC groups the new datapoint in low-dimensional subspaces by online inference in a non-parametric mixture of probabilistic principal component analyzers (MPPCA) based on a Dirichlet process, and captures the state transition and state duration information online in a hidden semi-Markov model (HSMM) based on a hierarchical Dirichlet process. A task-parameterized formulation of our approach autonomously adapts the model to changing environmental situations during manipulation. We apply the algorithm in a teleoperation setting to recognize the intention of the operator and remotely adjust the movement of the robot using the learned model. The generative model is used to synthesize both time-independent and time-dependent behaviors by relying on the principles of shared and autonomous control. Experiments with the Baxter robot yield parsimonious clusters that adapt online with new demonstrations and assist the operator in performing remote manipulation tasks.

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