Spike removal through multiscale wavelet and entropy analysis of ocular motor noise: A case study in patients with cerebellar disease

Veneri, Giacomo; Federighi, Pamela; Rosini, Francesca; Federico, Antonio; Rufa, Alessandra

doi:10.1016/j.jneumeth.2011.01.006

Cited by 10 publications

(10 citation statements)

References 41 publications

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“…LOCA is a group of patients with degenerative, genetically unrecognized pure cerebellar ataxia associated with atrophy limited to the cerebellum at MRI. Demographic, clinical, and genetic data of a larger sample including the patients recruited here have been reported by Klockgether, Muzaimi et al, and us [35–38]. …”

Section: Methodsmentioning

confidence: 84%

“…To study this result, in depth, we calculated the J sacc parameter, which provided an estimate of saccadic energy; we have to note that it is not possible to compare J sacc of subjects and model due to noise on saccade's trajectory; indeed, in two recent papers [37, 38], we found that motor control noise of SCA2 reported a significant difference with CTRL and LOCA. Figure 8(b) shows the overall solutions domain varying parameters s , μ p , and w .…”

Section: Resultsmentioning

confidence: 99%

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Evaluating the Influence of Motor Control on Selective Attention through a Stochastic Model: The Paradigm of Motor Control Dysfunction in Cerebellar Patient

Veneri

Federico

Rufa

2014

BioMed Research International

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Attention allows us to selectively process the vast amount of information with which we are confronted, prioritizing some aspects of information and ignoring others by focusing on a certain location or aspect of the visual scene. Selective attention is guided by two cognitive mechanisms: saliency of the image (bottom up) and endogenous mechanisms (top down). These two mechanisms interact to direct attention and plan eye movements; then, the movement profile is sent to the motor system, which must constantly update the command needed to produce the desired eye movement. A new approach is described here to study how the eye motor control could influence this selection mechanism in clinical behavior: two groups of patients (SCA2 and late onset cerebellar ataxia LOCA) with well-known problems of motor control were studied; patients performed a cognitively demanding task; the results were compared to a stochastic model based on Monte Carlo simulations and a group of healthy subjects. The analytical procedure evaluated some energy functions for understanding the process. The implemented model suggested that patients performed an optimal visual search, reducing intrinsic noise sources. Our findings theorize a strict correlation between the “optimal motor system” and the “optimal stimulus encoders.”

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Section: Methodsmentioning

confidence: 84%

Section: Resultsmentioning

confidence: 99%

Evaluating the Influence of Motor Control on Selective Attention through a Stochastic Model: The Paradigm of Motor Control Dysfunction in Cerebellar Patient

Veneri

Federico

Rufa

2014

BioMed Research International

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“…b) were calculated using a dispersion distance algorithm (Veneri et al ., ) in which fixation was defined as a cluster of data points (x,y) near a point (x f ,y f ) having similar variance over x and y (covariance). A threshold value of ≥100 ms of gaze stability was considered as a fixation (Veneri et al ., ). The distribution of fixations was compared among tests.…”

Section: Methodsmentioning

confidence: 99%

Spatial ranking strategy and enhanced peripheral vision discrimination optimize performance and efficiency of visual sequential search

Veneri

Pretegiani

Fargnoli

et al. 2014

Eur J of Neuroscience

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Visual sequential search might use a peripheral spatial ranking of the scene to put the next target of the sequence in the correct order. This strategy, indeed, might enhance the discriminative capacity of the human peripheral vision and spare neural resources associated with foveation. However, it is not known how exactly the peripheral vision sustains sequential search and whether the sparing of neural resources has a cost in terms of performance. To elucidate these issues, we compared strategy and performance during an alpha-numeric sequential task where peripheral vision was modulated in three different conditions: normal, blurred, or obscured. If spatial ranking is applied to increase the peripheral discrimination, its use as a strategy in visual sequencing should differ according to the degree of discriminative information that can be obtained from the periphery. Moreover, if this strategy spares neural resources without impairing the performance, its use should be associated with better performance. We found that spatial ranking was applied when peripheral vision was fully available, reducing the number and time of explorative fixations. When the periphery was obscured, explorative fixations were numerous and sparse; when the periphery was blurred, explorative fixations were longer and often located close to the items. Performance was significantly improved by this strategy. Our results demonstrated that spatial ranking is an efficient strategy adopted by the brain in visual sequencing to highlight peripheral detection and discrimination; it reduces the neural cost by avoiding unnecessary foveations, and promotes sequential search by facilitating the onset of a new saccade.

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“…In this work, 19 wavelets were assessed: Coiflet (Coif) 2, 3, 4, and 5, Daubechies (DB) series 2, 3,4,5,6,8,10,and 20,discrete Meyer (Dmey), Reverse Bior 13 (RBior13), Haar, and Symlet (Sym) 2, 3, 4, and 5 (Adeli et al, 2007;Birot et al, 2013;Ercelebi and Subasi, 2006;Gajic et al, 2014;Indiradevi et al, 2008;Inuso et Ubeyli, 2009;Vavadi et al, 2010;Veneri et al, 2011;Wang et al, 2009;Xu and Song, 2008).…”

Section: Wavelets and Descriptormentioning

confidence: 99%

“…Other authors (Correa et al, 2015;Nunes et al, 2014;Ubeyli, 2009) concluded that the Daubechies series 2, with up to 5 decomposition levels is adequate for spike classification. Moreover, other wavelets such as Daubechies series 3,5,6,8,10,and 20,Coiflet 2,3,4, and 5, discrete Meyer, Symlet 2, 3, 4, and 5, Reverse Bior 13, and the Haar wavelet are also used (Ercelebi and Subasi, 2006;Mirzaei et al, 2011;Nunes et al, 2014;Ubeyli, 2009;Vavadi et al, 2010;Veneri et al, 2011;Xu and Song, 2008).…”

Section: Introductionmentioning

confidence: 99%

Influences of the signal border extension in the discrete wavelet transform in EEG spike detection

Pacola

Quandt

Liberalesso³

et al. 2016

Res. Biomed. Eng.

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Introduction: The discrete wavelet transform is used in many studies as signal preprocessor for EEG spike detection. An inherent process of this mathematical tool is the recursive wavelet convolution over the signal that is decomposed into detail and approximation coefficients. To perform these convolutions, firstly it is necessary to extend signal borders. The selection of an unsuitable border extension algorithm may increase the false positive rate of an EEG spike detector. Methods: In this study we analyzed nine different border extensions used for convolution and 19 mother wavelets commonly seen in other EEG spike detectors in the literature. Results: The border extension may degrade an EEG spike detector up to 44.11%. Furthermore, results behave differently for distinct number of wavelet coefficients. Conclusion: There is not a best border extension to be used with any EEG spike detector based on the discrete wavelet transform, but the selection of the most adequate border extension is related to the number of coefficients of a mother wavelet.

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Spike removal through multiscale wavelet and entropy analysis of ocular motor noise: A case study in patients with cerebellar disease

Cited by 10 publications

References 41 publications

Evaluating the Influence of Motor Control on Selective Attention through a Stochastic Model: The Paradigm of Motor Control Dysfunction in Cerebellar Patient

Evaluating the Influence of Motor Control on Selective Attention through a Stochastic Model: The Paradigm of Motor Control Dysfunction in Cerebellar Patient

Spatial ranking strategy and enhanced peripheral vision discrimination optimize performance and efficiency of visual sequential search

Influences of the signal border extension in the discrete wavelet transform in EEG spike detection

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