Search results for "ECoG"

showing 10 items of 3774 documents

Need of causal analysis for assessing phase relationships in closed loop interacting cardiovascular variability series

2003

The phase spectra obtained by the classical closed loop autoregressive model (2AR) and by an open loop autoregressive model (ARXAR) were compared to shed light on the need of introducing causality in the assessment of the delay between RR and arterial pressure oscillations. The reliability of the two approaches was tested in simulation and real data setting. In simulation, the coupling strength of a bivariate closed loop process was adjusted to obtain a range of working conditions from open to closed loop. In open loop condition, 2AR and ARXAR phases were comparable and in agreement with the imposed delay. In closed loop condition, ARXAR model returned the imposed delays, while 2AR showed a…

Causality (physics)Range (mathematics)Series (mathematics)Autoregressive modelControl theorySettore ING-INF/06 - Bioingegneria Elettronica E InformaticaPhase (waves)Open-loop controllerComputer Science Applications1707 Computer Vision and Pattern RecognitionBivariate analysisCardiology and Cardiovascular MedicineCross-spectrumMathematics
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OPETH: Open Source Solution for Real-Time Peri-Event Time Histogram Based on Open Ephys

2019

Single cell electrophysiology remains one of the most widely used approaches of systems neuroscience. Decisions made by the experimenter during electrophysiology recording largely determine recording quality, duration of the project and value of the collected data. Therefore, online feedback aiding these decisions can lower monetary and time investment, and substantially speed up projects as well as allow novel studies otherwise not possible due to prohibitively low throughput. Real-time feedback is especially important in studies that involve optogenetic cell type identification by enabling a systematic search for neurons of interest. However, such tools are scarce and limited to costly co…

Cell typeSpeedupComputer scienceBiomedical EngineeringNeuroscience (miscellaneous)peri-event time histogramOptogeneticsMachine learningcomputer.software_genreopen ephys050105 experimental psychologyNeuron typeslcsh:RC321-571Photostimulation03 medical and health sciencesSoftware0302 clinical medicineopen sourceHistogramMethods0501 psychology and cognitive sciencesoptogeneticslcsh:Neurosciences. Biological psychiatry. Neuropsychiatrycomputer.programming_language030304 developmental biologySystems neuroscience0303 health sciencesbusiness.industrybehavior05 social sciencesPattern recognitionPython (programming language)NeurophysiologyelectrophysiologyComputer Science ApplicationsElectrophysiologyOpen sourceCell electrophysiologyArtificial intelligencebusinesscomputer030217 neurology & neurosurgeryNeuroscienceFrontiers in Neuroinformatics
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GTVcut for neuro-radiosurgery treatment planning: an MRI brain cancer seeded image segmentation method based on a cellular automata model

2018

Despite of the development of advanced segmentation techniques, achieving accurate and reproducible gross tumor volume (GTV) segmentation results is still an important challenge in neuro-radiosurgery. Nowadays, magnetic resonance imaging (MRI) is the most prominent modality in radiation therapy for soft-tissue anatomical districts. Gamma Knife stereotactic neuro-radiosurgery is a minimally invasive technology for dealing with inaccessible or insufficiently treated tumors with traditional surgery or radiotherapy. During a treatment planning phase, the GTV is generally contoured by experienced neurosurgeons and radiation oncologists using fully manual segmentation procedures on MR images. Unf…

Cellular automataBrain cancersING-INF/06 - BIOINGEGNERIA ELETTRONICA E INFORMATICABrain cancers; Cellular automata; Computer-assisted segmentation; Gamma Knife neuro-radiosurgery; MR imagingComputer sciencemedicine.medical_treatment02 engineering and technologyBrain cancerRadiosurgeryING-INF/05 - SISTEMI DI ELABORAZIONE DELLE INFORMAZIONI030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicine0202 electrical engineering electronic engineering information engineeringmedicineSegmentationRadiation treatment planningModality (human–computer interaction)medicine.diagnostic_testbusiness.industryComputer Science ApplicationComputer-assisted segmentationINF/01 - INFORMATICAMagnetic resonance imagingPattern recognitionGamma Knife neuro-radiosurgeryComputer Science Applications1707 Computer Vision and Pattern RecognitionImage segmentationCellular automatonComputer Science ApplicationsRadiation therapy020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligencebusinessMR imaging
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Cerebellar learning of bio-mechanical functions of extra-ocular muscles: modeling by artificial neural networks

2003

A control circuit is proposed to model the command of saccadic eye movements. Its wiring is deduced from a mathematical constraint, i.e. the necessity, for motor orders processing, to compute an approximate inverse function of the bio-mechanical function of the moving plant, here the bio-mechanics of the eye. This wiring is comparable to the anatomy of the cerebellar pathways. A predicting element, necessary for inversion and thus for movement accuracy, is modeled by an artificial neural network whose structure, deduced from physical constraints expressing the mechanics of the eye, is similar to the cell connectivity of the cerebellar cortex. Its functioning is set by supervised reinforceme…

CerebellumEye MovementsArtificial neural networkbusiness.industryGeneral NeuroscienceMotor controlEye movementPattern recognitionSaccadic maskingBiomechanical Phenomenamedicine.anatomical_structureOculomotor MusclesCerebellumCerebellar cortexMotor systemmedicineLearningReinforcement learningNeural Networks ComputerArtificial intelligencebusinessNeuroscienceMathematicsNeuroscience
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Analysis of neuronal networks in the visual system of the cat using statistical signals--simple and complex cells. Part II.

1978

Superimposing additively a two-dimensional noise process to deterministic input signals (bars) the neurons of area 17 show a class-specific reaction for the task of signal extraction. Moving both parts of the signals simultaneously and varying the signal to noise ratio (S/N) the simple cells achieve the same performance as resulted from the psychophysical experiment. Type I complex cells extract moving deterministic signals (i.e. bars) from the stationary noise, whereas in the answers of Type II complex cells the statistical parts of the signals predominate. Considering the different cell types each as a series of a linear and a nonlinear system one obtains the cell specific space-time freq…

Cerebral CortexNeuronsGeneral Computer ScienceSeries (mathematics)Noise (signal processing)Computer scienceSpeech recognitionModels NeurologicalStatistics as TopicProcess (computing)Complex systemElectrophysiologyForm PerceptionNonlinear systemAmplitudeSignal-to-noise ratioPattern Recognition VisualSimple (abstract algebra)CatsAnimalsVisual PathwaysBiological systemMathematicsBiotechnologyBiological cybernetics
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Local symmetries of digital contours from their chain codes

1996

In this work symmetry is evaluated as a numeric feature for each point of a contour, using only the positions of a local vicinity of points. A measurement is defined, named as Local Symmetric Deficiency (LSD), so that the lower this quantity is, the higher the symmetry will be in the local region considered. This approach is very simple and it is based on a suitable manipulation of the chain code of the curve. Its computational cost is very low and it has the advantages of a parallel algorithm, since values for LSD can be computed for each point independently.

Chain codeFeature extractionParallel algorithmEdge detectionChain (algebraic topology)Artificial IntelligenceFeature (computer vision)Signal ProcessingPoint (geometry)Computer Vision and Pattern RecognitionSymmetry (geometry)AlgorithmSoftwareMathematicsPattern Recognition
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Modeling Multi-label Recurrence in Data Streams

2019

Most of the existing data stream algorithms assume a single label as the target variable. However, in many applications, each observation is assigned to several labels with latent dependencies among them, which their target function may change over time. Classification of such non-stationary multi-label streaming data with the consideration of dependencies among labels and potential drifts is a challenging task. The few existing studies mostly cope with drifts implicitly, and all learn models on the original label space, which requires a lot of time and memory. None of them consider recurrent drifts in multi-label streams and particularly drifts and recurrences visible in a latent label spa…

Change over timeMulti-label classificationData streambusiness.industryComputer scienceData stream miningSpace dimensionPattern recognitionComputingMethodologies_PATTERNRECOGNITIONStreaming dataArtificial intelligencebusinessClassifier (UML)Decoding methods2019 IEEE International Conference on Big Knowledge (ICBK)
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Variance Thresholded EMD-CCA Technique for Fast Eye Blink Artifacts Removal in EEG

2017

International audience; Eye blink (EB) artifacts generated during eye blinks often contaminate electroencephalogram (EEG) signal. Previously Empirical Mode Decomposition (EMD) and Canonical Correlation Analysis (CCA), hybrid EMD-CCA were developed for EB artifact removal in EEG. However, EMD restricts the hybrid algorithm for real time implementation due to its slow processing nature, hence the algorithm has to be enhanced so that it can be a viable solution for real-time EB artifact removal. In this research work, to avoid applying EMD repetitively as and when EB artifacts occur, a method to use EMD minimally is approached. A suitable EB artifact region is detected through a variance thres…

Channel (digital image)Computer scienceElectroencephalography[INFO] Computer Science [cs]Signal050105 experimental psychologyTime03 medical and health sciences0302 clinical medicineVariance ThresholdmedicineEMD0501 psychology and cognitive sciences[INFO]Computer Science [cs]EEGCCAArtifact (error)medicine.diagnostic_testEBbusiness.industry05 social sciencesOcular ArtifactPattern recognitionElectrooculographyFrequency-DomainRecordingsFrequency domainArtificial intelligencebusiness030217 neurology & neurosurgery
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Color encoding for polychromatic single-channel optical pattern recognition

2010

The common multichannel system for recognizing colored images is replaced by a color-encoded single-channel system. Amethod inspired by the Munsell color system is used for encoding the different colors as phase and amplitude functions. It is shown that for many practical cases the phase information part of the color code is sufficient for obtaining good results. An implementation based on a liquid-crystal television panel that works in a phase-modulation mode is suggested. Computer simulations that demonstrate the capabilities of the suggested method are given as well as a comparison with previously published multichannel performance.

Channel (digital image)Computer sciencebusiness.industryMaterials Science (miscellaneous)Pattern recognitionImage processingColor spaceIndustrial and Manufacturing EngineeringMunsell color systemEncoding (memory)Pattern recognition (psychology)Artificial intelligenceBusiness and International ManagementbusinessColor codeApplied Optics
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Nonlinear pattern recognition correlators based on color-encoding single-channel systems.

2004

In color pattern recognition, color channels are normally processed separately and afterward the correlation outputs are combined. This is the definition of multichannel processing. We combine a single-channel method with nonlinear filtering based on nonlinear correlations. These nonlinear correlations yield better discrimination than common matched filtering. The method codes color information as amplitude and phase distributions and is followed by correlations related to binary decompositions. The technique is based on binary decompositions of the red, green, and blue and the hue, saturation, and intensity monochromatic channels of the reference and of the input scene, after which the bin…

Channel (digital image)business.industryNoise (signal processing)Materials Science (miscellaneous)Pattern recognitionColor spaceIndustrial and Manufacturing EngineeringNonlinear systemOpticsPattern recognition (psychology)Monochromatic colorArtificial intelligenceBusiness and International ManagementbusinessLinear filterHueMathematicsApplied optics
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