LIVIVO - Search results -

Search results

Result 1 - 10 of total 31

Search options

Article ; Online: Learning with Precise Spike Times: A New Decoding Algorithm for Liquid State Machines.

Florescu, Dorian / Coca, Daniel

2019 Volume 31, Issue 9, Page(s) 1825–1852

Abstract: There is extensive evidence that biological neural networks encode information in the precise timing of the spikes generated and transmitted by neurons, which offers several advantages over rate-based codes. Here we adopt a vector space formulation of ... ...

Abstract	There is extensive evidence that biological neural networks encode information in the precise timing of the spikes generated and transmitted by neurons, which offers several advantages over rate-based codes. Here we adopt a vector space formulation of spike train sequences and introduce a new liquid state machine (LSM) network architecture and a new forward orthogonal regression algorithm to learn an input-output signal mapping or to decode the brain activity. The proposed algorithm uses precise spike timing to select the presynaptic neurons relevant to each learning task. We show that using precise spike timing to train the LSM and selecting the readout presynaptic neurons leads to a significant increase in performance on binary classification tasks, in decoding neural activity from multielectrode array recordings, as well as in a speech recognition task, compared with what is achieved using the standard architecture and training methods.
MeSH term(s)	Action Potentials/physiology ; Algorithms ; Humans ; Machine Learning/trends ; Models, Neurological ; Neural Networks, Computer ; Speech Recognition Software/trends
Language	English
Publishing date	2019-07-23
Publishing country	United States
Document type	Letter ; Research Support, Non-U.S. Gov't
ZDB-ID	1025692-1
ISSN	1530-888X ; 0899-7667
ISSN (online)	1530-888X
ISSN	0899-7667
DOI	10.1162/neco_a_01218
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 2914: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (2.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

Details ▾
- See ZB MED holdings
- Order with fees

Article ; Online: Identification of Linear and Nonlinear Sensory Processing Circuits from Spiking Neuron Data.

Florescu, Dorian / Coca, Daniel

Neural computation

2018 Volume 30, Issue 3, Page(s) 670–707

Abstract: Inferring mathematical models of sensory processing systems directly from input-output observations, while making the fewest assumptions about the model equations and the types of measurements available, is still a major issue in computational ... ...

Abstract	Inferring mathematical models of sensory processing systems directly from input-output observations, while making the fewest assumptions about the model equations and the types of measurements available, is still a major issue in computational neuroscience. This letter introduces two new approaches for identifying sensory circuit models consisting of linear and nonlinear filters in series with spiking neuron models, based only on the sampled analog input to the filter and the recorded spike train output of the spiking neuron. For an ideal integrate-and-fire neuron model, the first algorithm can identify the spiking neuron parameters as well as the structure and parameters of an arbitrary nonlinear filter connected to it. The second algorithm can identify the parameters of the more general leaky integrate-and-fire spiking neuron model, as well as the parameters of an arbitrary linear filter connected to it. Numerical studies involving simulated and real experimental recordings are used to demonstrate the applicability and evaluate the performance of the proposed algorithms.
MeSH term(s)	Action Potentials/physiology ; Algorithms ; Animals ; Computer Simulation ; Mice ; Models, Neurological ; Neural Pathways/physiology ; Neurons/physiology ; Nonlinear Dynamics ; Perception/physiology ; Sensation/physiology ; Signal Processing, Computer-Assisted ; Tissue Culture Techniques ; Visual Cortex/physiology
Language	English
Publishing date	2018-01-17
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1025692-1
ISSN	1530-888X ; 0899-7667
ISSN (online)	1530-888X
ISSN	0899-7667
DOI	10.1162/neco_a_01051
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 2914: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (2.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾
- See ZB MED holdings
- Order with fees

Article: A matrix-based approach to solving the inverse Frobenius-Perron problem using sequences of density functions of stochastically perturbed dynamical systems.

Nie, Xiaokai / Coca, Daniel

Communications in nonlinear science & numerical simulation

2018 Volume 54, Page(s) 248–266

Abstract: The paper introduces a matrix-based approach to estimate the unique one-dimensional discrete-time dynamical system that generated a given sequence of probability density functions whilst subjected to an additive stochastic perturbation with known density. ...

Abstract	The paper introduces a matrix-based approach to estimate the unique one-dimensional discrete-time dynamical system that generated a given sequence of probability density functions whilst subjected to an additive stochastic perturbation with known density.
Language	English
Publishing date	2018-01-03
Publishing country	China
Document type	Journal Article
ISSN	1007-5704
ISSN	1007-5704
DOI	10.1016/j.cnsns.2017.05.011
Database	MEDical Literature Analysis and Retrieval System OnLINE

Full text online

Accessible to users with ZB MED library card

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Details ▾
- Full text online
- Order with fees

Article: Communication Sparsity in Distributed Spiking Neural Network Simulations to Improve Scalability.

Fernandez-Musoles, Carlos / Coca, Daniel / Richmond, Paul

Frontiers in neuroinformatics

2019 Volume 13, Page(s) 19

Abstract: In the last decade there has been a surge in the number of big science projects interested in achieving a comprehensive understanding of the functions of the brain, using Spiking Neuronal Network (SNN) simulations to aid discovery and experimentation. ... ...

Abstract	In the last decade there has been a surge in the number of big science projects interested in achieving a comprehensive understanding of the functions of the brain, using Spiking Neuronal Network (SNN) simulations to aid discovery and experimentation. Such an approach increases the computational demands on SNN simulators: if natural scale brain-size simulations are to be realized, it is necessary to use parallel and distributed models of computing. Communication is recognized as the dominant part of distributed SNN simulations. As the number of computational nodes increases, the proportion of time the simulation spends in useful computing (computational efficiency) is reduced and therefore applies a limit to scalability. This work targets the three phases of communication to improve overall computational efficiency in distributed simulations: implicit synchronization, process handshake and data exchange. We introduce a connectivity-aware allocation of neurons to compute nodes by modeling the SNN as a
Language	English
Publishing date	2019-04-02
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2452979-5
ISSN	1662-5196
ISSN	1662-5196
DOI	10.3389/fninf.2019.00019
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: Aging-related defects in macrophage function are driven by MYC and USF1 transcriptional programs.

Moss, Charlotte E / Johnston, Simon A / Kimble, Joshua V / Clements, Martha / Codd, Veryan / Hamby, Stephen / Goodall, Alison H / Deshmukh, Sumeet / Sudbery, Ian / Coca, Daniel / Wilson, Heather L / Kiss-Toth, Endre

Cell reports

2024 Volume 43, Issue 4, Page(s) 114073

Abstract: Macrophages are central innate immune cells whose function declines with age. The molecular mechanisms underlying age-related changes remain poorly understood, particularly in human macrophages. We report a substantial reduction in phagocytosis, ... ...

Abstract	Macrophages are central innate immune cells whose function declines with age. The molecular mechanisms underlying age-related changes remain poorly understood, particularly in human macrophages. We report a substantial reduction in phagocytosis, migration, and chemotaxis in human monocyte-derived macrophages (MDMs) from older (>50 years old) compared with younger (18-30 years old) donors, alongside downregulation of transcription factors MYC and USF1. In MDMs from young donors, knockdown of MYC or USF1 decreases phagocytosis and chemotaxis and alters the expression of associated genes, alongside adhesion and extracellular matrix remodeling. A concordant dysregulation of MYC and USF1 target genes is also seen in MDMs from older donors. Furthermore, older age and loss of either MYC or USF1 in MDMs leads to an increased cell size, altered morphology, and reduced actin content. Together, these results define MYC and USF1 as key drivers of MDM age-related functional decline and identify downstream targets to improve macrophage function in aging.
MeSH term(s)	Humans ; Macrophages/metabolism ; Aging ; Proto-Oncogene Proteins c-myc/metabolism ; Proto-Oncogene Proteins c-myc/genetics ; Adult ; Upstream Stimulatory Factors/metabolism ; Upstream Stimulatory Factors/genetics ; Middle Aged ; Adolescent ; Phagocytosis/genetics ; Young Adult ; Transcription, Genetic ; Aged ; Chemotaxis/genetics
Chemical Substances	Proto-Oncogene Proteins c-myc ; Upstream Stimulatory Factors ; USF1 protein, human ; MYC protein, human
Language	English
Publishing date	2024-04-04
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2649101-1
ISSN	2211-1247 ; 2211-1247
ISSN (online)	2211-1247
ISSN	2211-1247
DOI	10.1016/j.celrep.2024.114073
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Book ; Online: Learning with precise spike times

Florescu, Dorian / Coca, Daniel

A new decoding algorithm for liquid state machines

2018

Abstract	There is extensive evidence that biological neural networks encode information in the precise timing of the spikes generated and transmitted by neurons, which offers several advantages over rate-based codes. Here we adopt a vector space formulation of spike train sequences and introduce a new liquid state machine (LSM) network architecture and a new forward orthogonal regression algorithm to learn an input-output signal mapping or to decode the brain activity. The proposed algorithm uses precise spike timing to select the presynaptic neurons relevant to each learning task. We show that using precise spike timing to train the LSM and selecting the readout neurons leads to a significant increase in performance on binary classification tasks as well as in decoding neural activity from multielectrode array recordings, compared with what is achieved using the standard architecture and training method. Comment: 34 pages, 7 figures
Keywords	Quantitative Biology - Neurons and Cognition
Subject code	612
Publishing date	2018-05-24
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Linear and Nonlinear Estimated GFR Slopes in ADPKD Patients Reaching ESRD.

Neagu, Matei / Coca, Daniel / Ong, Albert C M

American journal of kidney diseases : the official journal of the National Kidney Foundation

2018 Volume 71, Issue 6, Page(s) 912–913

MeSH term(s)	Creatinine ; Glomerular Filtration Rate ; Humans ; Kidney Failure, Chronic ; Polycystic Kidney, Autosomal Dominant
Chemical Substances	Creatinine (AYI8EX34EU)
Language	English
Publishing date	2018-03-30
Publishing country	United States
Document type	Letter ; Comment
ZDB-ID	604539-x
ISSN	1523-6838 ; 0272-6386
ISSN (online)	1523-6838
ISSN	0272-6386
DOI	10.1053/j.ajkd.2018.01.052
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 1669: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (1.OG) ab Jg. 2022: Lesesaal (EG)
Zs.MO 468: Show issues

Order via subito

Details ▾
- See ZB MED holdings
- Order with fees

Article ; Online: A Novel Reconstruction Framework for Time-Encoded Signals with Integrate-and-Fire Neurons.

Florescu, Dorian / Coca, Daniel

Neural computation

2015 Volume 27, Issue 9, Page(s) 1872–1898

Abstract: Integrate-and-fire neurons are time encoding machines that convert the amplitude of an analog signal into a nonuniform, strictly increasing sequence of spike times. Under certain conditions, the encoded signals can be reconstructed from the nonuniform ... ...

Abstract	Integrate-and-fire neurons are time encoding machines that convert the amplitude of an analog signal into a nonuniform, strictly increasing sequence of spike times. Under certain conditions, the encoded signals can be reconstructed from the nonuniform spike time sequences using a time decoding machine. Time encoding and time decoding methods have been studied using the nonuniform sampling theory for band-limited spaces, as well as for generic shift-invariant spaces. This letter proposes a new framework for studying IF time encoding and decoding by reformulating the IF time encoding problem as a uniform sampling problem. This framework forms the basis for two new algorithms for reconstructing signals from spike time sequences. We demonstrate that the proposed reconstruction algorithms are faster, and thus better suited for real-time processing, while providing a similar level of accuracy, compared to the standard reconstruction algorithm.
MeSH term(s)	Action Potentials/physiology ; Animals ; Humans ; Models, Neurological ; Neurons/physiology ; Signal Processing, Computer-Assisted ; Time Factors
Language	English
Publishing date	2015-09
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1025692-1
ISSN	1530-888X ; 0899-7667
ISSN (online)	1530-888X
ISSN	0899-7667
DOI	10.1162/NECO_a_00764
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 2914: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (2.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾
- See ZB MED holdings
- Order with fees

Book ; Online: Recovery of Missing Data in Correlated Smart Grid Datasets

Genes, Cristian / Esnaola, Iñaki / Perlaza, Samir / Coca, Daniel

2019

Abstract: We study the recovery of missing data from multiple smart grid datasets within a matrix completion framework. The datasets contain the electrical magnitudes required for monitoring and control of the electricity distribution system. Each dataset is ... ...

Abstract	We study the recovery of missing data from multiple smart grid datasets within a matrix completion framework. The datasets contain the electrical magnitudes required for monitoring and control of the electricity distribution system. Each dataset is described by a low rank matrix. Different datasets are correlated as a result of containing measurements of different physical magnitudes generated by the same distribution system. To assess the validity of matrix completion techniques in the recovery of missing data, we characterize the fundamental limits when two correlated datasets are jointly recovered. We then proceed to evaluate the performance of Singular Value Thresholding (SVT) and Bayesian SVT (BSVT) in this setting. We show that BSVT outperforms SVT by simulating the recovery for different correlated datasets. The performance of BSVT displays the tradeoff behaviour described by the fundamental limit, which suggests that BSVT exploits the correlation between the datasets in an efficient manner. Comment: Extended version of submission to IEEE Data Science Workshop 2019
Keywords	Electrical Engineering and Systems Science - Signal Processing
Publishing date	2019-06-02
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article: Analysing the performance of low-cost air quality sensors, their drivers, relative benefits and calibration in cities—a case study in Sheffield

Munir, Said / Mayfield, Martin / Coca, Daniel / Jubb, Stephen A / Osammor, Ogo

Environmental monitoring and assessment. 2019 Feb., v. 191, no. 2

2019

Abstract: Traditional real-time air quality monitoring instruments are expensive to install and maintain; therefore, such existing air quality monitoring networks are sparsely deployed and lack the measurement density to develop high-resolution spatiotemporal air ... ...

Abstract	Traditional real-time air quality monitoring instruments are expensive to install and maintain; therefore, such existing air quality monitoring networks are sparsely deployed and lack the measurement density to develop high-resolution spatiotemporal air pollutant maps. More recently, low-cost sensors have been used to collect high-resolution spatial and temporal air pollution data in real-time. In this paper, for the first time, Envirowatch E-MOTEs are employed for air quality monitoring as a case study in Sheffield. Ten E-MOTEs were deployed for a year (October 2016 to September 2017) monitoring several air pollutants (NO, NO2, CO) and meteorological parameters. Their performance was compared to each other and to a reference instrument installed nearby. E-MOTEs were able to successfully capture the temporal variability such as diurnal, weekly and annual cycles in air pollutant concentrations and demonstrated significant similarity with reference instruments. NO2 concentrations showed very strong positive correlation between various sensors. Mostly, correlation coefficients (r values) were greater than 0.92. CO from different sensors also had r values mostly greater than 0.92; however, NO showed r value less than 0.5. Furthermore, several multiple linear regression models (MLRM) and generalised additive models (GAM) were developed to calibrate the E-MOTE data and reproduce NO and NO2 concentrations measured by the reference instruments. GAMs demonstrated significantly better performance than linear models by capturing the non-linear association between the response and explanatory variables. The best GAM developed for reproducing NO2 concentrations returned values of 0.95, 3.91, 0.81, 0.005 and 0.61 for factor of two (FAC2), root mean square error (RMSE), coefficient of determination (R2), normalised mean biased (NMB) and coefficient of efficiency (COE), respectively. The low-cost sensors offer a more affordable alternative for providing real-time high-resolution spatiotemporal air quality and meteorological parameter data with acceptable performance.
Keywords	air pollutants ; air pollution ; air quality ; carbon monoxide ; case studies ; linear models ; meteorological parameters ; monitoring ; nitric oxide ; nitrogen dioxide ; regression analysis ; temporal variation
Language	English
Dates of publication	2019-02
Size	p. 94.
Publishing place	Springer International Publishing
Document type	Article
ZDB-ID	782621-7
ISSN	1573-2959 ; 0167-6369
ISSN (online)	1573-2959
ISSN	0167-6369
DOI	10.1007/s10661-019-7231-8
Database	NAL-Catalogue (AGRICOLA)

Full text online

Accessible to users with ZB MED library card

In stock of ZB MED Bonn / Germany

Z 5186: Show issues

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Details ▾

To top

Your last searches

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

Full text online

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

Full text online

More links

Kategorien

Inter-library loan at ZB MED

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

In stock of ZB MED Bonn / Germany

Order via subito

Inter-library loan at ZB MED