Danilo Melges | UFMG - The Federal University of Minas Gerais (original) (raw)

Papers by Danilo Melges

Research paper thumbnail of Logistic Regression Models: Feature Selection for P300 Detection Improvement

Brain computer interfaces are devices that enable people to communicate using their brain activit... more Brain computer interfaces are devices that enable people to communicate using their brain activity, being useful for those suffering with neurodegenerative diseases. Many BCI use the P300 evoked response. However, the detection of this potential is very difficult, since it presents low signal-to-noise ratio. This paper studies which time features present in the electroencephalogram can improve the detection rates of this response. For this purpose, logistic regression models were used to assess the significance of the following features for P300 representation: most positive peak, most negative peak, latencies of these peaks, area and RMS value between them. These parameters were evaluated on averages of 600 ms windows that could or not contain the potential. The results showed that positive peak, RMS value and both latencies significantly improve P300 detection rates.

Research paper thumbnail of N1 response attenuation and the mismatch negativity (MMN) to within- and across-category phonetic contrasts

Psychophysiology, Apr 7, 2017

According to the neural adaptation model of the mismatch negativity (MMN), the sensitivity of thi... more According to the neural adaptation model of the mismatch negativity (MMN), the sensitivity of this event-related response to both acoustic and categorical information in speech sounds can be accounted for by assuming that (a) the degree of overlapping between neural representations of two sounds depends on both the acoustic difference between them and whether or not they belong to distinct phonetic categories, and (b) a release from stimulus-specific adaptation causes an enhanced N1 obligatory response to infrequent deviant stimuli. On the basis of this view, we tested in Experiment 1 whether the N1 response to the second sound of a pair (S2 ) would be more attenuated in pairs of identical vowels compared with pairs of different vowels, and in pairs of exemplars of the same vowel category compared with pairs of exemplars of different categories. The psychoacoustic distance between S1 and S2 was the same for all within-category and across-category pairs. While N1 amplitudes decreased...

Research paper thumbnail of Multiple Coherence vs Multiple Component Synchrony Measure for somatosensory evoked response detection

2010 Annual International Conference of the IEEE Engineering in Medicine and Biology, 2010

This work aims at comparing the performance of two Multivariate Objective Response Detection (MOR... more This work aims at comparing the performance of two Multivariate Objective Response Detection (MORD) techniques in the frequency domain, the Multiple Coherence (MC) and the Multiple Component Synchrony Measure (MCSM), for tibial nerve somatosensory evoked potential (SEP) detection. Electroencephalographic (EEG) signals during somatosensory stimulation were collected from forty adult volunteers using the 10-20 International System. The stimulation was carried out throughout current pulses (200 µs width) applied to the right posterior tibial nerve (motor threshold intensity level) at the rate of 5 Hz. The response detection was based on rejecting the null hypothesis of response absence (M = 100 and M = 800 epochs and significance level α = 0.05). The MORD techniques were applied to the pairs of derivations [Cz][Fz] and [C3][C4]. The MC outperforms the MCSM, regardless the pair of derivations or the number of epochs used for the estimates calculation. Hence, the MC should be used, if two derivations are available for SEP recording.

Research paper thumbnail of Long-latency event-related responses to vowels: N1-P2 decomposition by two-step principal component analysis

International Journal of Psychophysiology, 2019

The N1-P2 complex of the auditory event-related potential (ERP) has been used to examine neural a... more The N1-P2 complex of the auditory event-related potential (ERP) has been used to examine neural activity associated with speech sound perception. Since it is thought to reflect multiple generator processes, its functional significance is difficult to infer. In the present study, a temporospatial principal component analysis (PCA) was used to decompose the N1-P2 response into latent factors underlying covariance patterns in ERP data recorded during passive listening to pairs of successive vowels. In each trial, one of six sounds drawn from an /i/-/e/ vowel continuum was followed either by an identical sound, a different token of the same vowel category, or a token from the other category. Responses were examined as to how they were modulated by within- and across-category vowel differences and by adaptation (repetition suppression) effects. Five PCA factors were identified as corresponding to three well-known N1 subcomponents and two P2 subcomponents. Results added evidence that the N1 peak reflects both generators that are sensitive to spectral information and generators that are not. For later latency ranges, different patterns of sensitivity to vowel quality were found, including category-related effects. Particularly, a subcomponent identified as the Tb wave showed release from adaptation in response to an /i/ followed by an /e/ sound. A P2 subcomponent varied linearly with spectral shape along the vowel continuum, while the other was stronger the closer the vowel was to the category boundary, suggesting separate processing of continuous and category-related information. Thus, the PCA-based decomposition of the N1-P2 complex was functionally meaningful, revealing distinct underlying processes at work during speech sound perception.

Research paper thumbnail of N1 response attenuation and the mismatch negativity (MMN) to within- and across-category phonetic contrasts

Psychophysiology, Apr 7, 2017

According to the neural adaptation model of the mismatch negativity (MMN), the sensitivity of thi... more According to the neural adaptation model of the mismatch negativity (MMN), the sensitivity of this event-related response to both acoustic and categorical information in speech sounds can be accounted for by assuming that (a) the degree of overlapping between neural representations of two sounds depends on both the acoustic difference between them and whether or not they belong to distinct phonetic categories, and (b) a release from stimulus-specific adaptation causes an enhanced N1 obligatory response to infrequent deviant stimuli. On the basis of this view, we tested in Experiment 1 whether the N1 response to the second sound of a pair (S2 ) would be more attenuated in pairs of identical vowels compared with pairs of different vowels, and in pairs of exemplars of the same vowel category compared with pairs of exemplars of different categories. The psychoacoustic distance between S1 and S2 was the same for all within-category and across-category pairs. While N1 amplitudes decreased...

Research paper thumbnail of Application of Multivariate Spectral F Test for Somatosensory Evoked Response Detection

Somatosensory Evoked Potential (SEP) is an important tool for monitoring vascular and spine surge... more Somatosensory Evoked Potential (SEP) is an important tool for monitoring vascular and spine surgeries, and other clinical applications. However, morphological SEP identification is subjective. Then, statistical techniques, such as Local Spectral F Test (SFT), have been used for response detection. The multivariate extension of SFT employs more than one derivation and has been recently considered advantageous to identify response to visual stimulation. This work aims at evaluating the performance of Multivariate SFT (MSFT) applied to EEG signals from 40 volunteers during stimulation at 5 Hz and different numbers of derivations (N), comparing the detection rates (DR). Frequencies of interest fo1 = 15 Hz and fo2 = 100 Hz were used, as well as L = 6 neighbor components at the frequencies from 70 to 95 Hz and a 5%-significance level. The number of derivations varied from N = 1 to 6. The detection rates obtained using fo1 were higher than those with fo2, which corresponds to false positiv...

Research paper thumbnail of Long-latency event-related responses to vowels: N1-P2 decomposition by two-step principal component analysis

International Journal of Psychophysiology

The N1-P2 complex of the auditory event-related potential (ERP) has been used to examine neural a... more The N1-P2 complex of the auditory event-related potential (ERP) has been used to examine neural activity associatedwithspeechsoundperception.Sinceitisthoughttoreflectmultiplegeneratorprocesses,itsfunctional significanceisdifficulttoinfer.Inthepresentstudy,atemporospatialprincipalcomponentanalysis(PCA)was usedtodecomposetheN1-P2responseintolatentfactorsunderlyingcovariancepatternsinERPdatarecorded duringpassivelisteningtopairsofsuccessivevowels.Ineachtrial,oneofsixsoundsdrawnfroman/i/−/e/ vowelcontinuumwasfollowedeitherbyanidenticalsound,adifferenttokenofthesamevowelcategory,ora tokenfromtheothercategory.Responseswereexaminedastohowtheyweremodulatedbywithin-andacrosscategoryvoweldifferencesandbyadaptation(repetitionsuppression)effects.FivePCAfactorswereidentifiedas correspondingtothreewell-knownN1subcomponentsandtwoP2subcomponents.Resultsaddedevidencethat theN1peakreflectsbothgeneratorsthataresensitivetospectralinformationandgeneratorsthatarenot.For later latency ranges, different patterns of sensitivity to vowel quality were found, including category-related effects.Particularly,asubcomponentidentifiedastheTbwaveshowedreleasefromadaptationinresponsetoan /i/ followed by an /e/ sound. A P2 subcomponent varied linearly with spectral shape along the vowel continuum, whilethe otherwas stronger thecloser thevowelwas tothe categoryboundary,suggesting separate processing of continuous and category-related information. Thus, the PCA-based decomposition of the N1-P2 complex was functionally meaningful, revealing distinct underlying processes at work during speech sound perception.

Research paper thumbnail of Long-latency event-related responses to vowels: N1-P2 decomposition by two-step principal component analysis

International Journal of Psychophysiology, 2019

The N1-P2 complex of the auditory event-related potential (ERP) has been used to examine neural a... more The N1-P2 complex of the auditory event-related potential (ERP) has been used to examine neural activity associatedwithspeechsoundperception.Sinceitisthoughttoreflectmultiplegeneratorprocesses,itsfunctional significanceisdifficulttoinfer.Inthepresentstudy,atemporospatialprincipalcomponentanalysis(PCA)was usedtodecomposetheN1-P2responseintolatentfactorsunderlyingcovariancepatternsinERPdatarecorded duringpassivelisteningtopairsofsuccessivevowels.Ineachtrial,oneofsixsoundsdrawnfroman/i/−/e/ vowelcontinuumwasfollowedeitherbyanidenticalsound,adifferenttokenofthesamevowelcategory,ora tokenfromtheothercategory.Responseswereexaminedastohowtheyweremodulatedbywithin-andacrosscategoryvoweldifferencesandbyadaptation(repetitionsuppression)effects.FivePCAfactorswereidentifiedas correspondingtothreewell-knownN1subcomponentsandtwoP2subcomponents.Resultsaddedevidencethat theN1peakreflectsbothgeneratorsthataresensitivetospectralinformationandgeneratorsthatarenot.For later latency ranges, different patterns of sensitivity to vowel quality were found, including category-related effects.Particularly,asubcomponentidentifiedastheTbwaveshowedreleasefromadaptationinresponsetoan /i/ followed by an /e/ sound. A P2 subcomponent varied linearly with spectral shape along the vowel continuum, whilethe otherwas stronger thecloser thevowelwas tothe categoryboundary,suggesting separate processing of continuous and category-related information. Thus, the PCA-based decomposition of the N1-P2 complex was functionally meaningful, revealing distinct underlying processes at work during speech sound perception.

Research paper thumbnail of N1 response attenuation and the mismatch negativity (MMN) to within‐and across‐category phonetic contrasts

According to the neural adaptation model of the mismatch negativity (MMN), the sensitivity of thi... more According to the neural adaptation model of the mismatch negativity (MMN), the sensitivity of this event-related response to both acoustic and categorical information in speech sounds can be accounted for by assuming that (a) the degree of overlapping between neural representations of two sounds depends on both the acoustic difference between them and whether or not they belong to distinct phonetic categories, and (b) a release from stimulus-specific adaptation causes an enhanced N1 obligatory response to infrequent deviant stimuli. On the basis of this view, we tested in Experiment 1 whether the N1 response to the second sound of a pair (S2) would be more attenuated in pairs of identical vowels compared with pairs of different vowels, and in pairs of exemplars of the same vowel category compared with pairs of exemplars of different categories. The psychoacoustic distance between S1 and S2 was the same for all within-category and across-category pairs. While N1 amplitudes decreased markedly from S1 to S2, responses to S2 were quite similar across pair types, indicating that the attenuation effect in such conditions is not stimulus specific. In Experiment 2, a pronounced MMN was elicited by a deviant vowel sound in an across-category oddball sequence, but not when the exact same deviant vowel was presented in a within-category oddball sequence. This adds evidence that MMN reflects categorical phonetic processing. Taken together, the results suggest that different neural processes underlie the attenuation of the N1 response to S2 and the MMN to vowels.

Research paper thumbnail of A Variance-based Approach to Perform Single-Trial P300 Detection

P300 is an event-related potential (ERP) recorded in scalp by means of electroencephalography (EE... more P300 is an event-related potential (ERP) recorded in scalp by means of electroencephalography (EEG), commonly used for developing brain-computer interfaces (BCI). One of the main challenges of using P300 is presented by its low signal-to-noise ratio (SNR), making its detection a dificult task. Grand averaging is a technique commonly used to overcome the low SNR. However, it requires longer EEG recording periods, which hardens the implementation of P300-based BCI. Hence, single-trial detection (STD) of such potential is desirable for this application. In this paper, we propose a method which uses metrics based on EEG variance together with logistic regression model to perform STD. The proposed method was tested in 24 subjects and showed mean accuracy of 76.1%, a promising result that is compatible/better with/than other ones found in literature.

Research paper thumbnail of Identification of drowsiness and alertness conditions by means of Spectral F-Test applied to pupillometric signals

Journal of Physics: Conference Series, 2013

ABSTRACT The autonomous regulation of pupil size provides an objective physiological measure of a... more ABSTRACT The autonomous regulation of pupil size provides an objective physiological measure of alertness level. Pupil diameter decreases and its fluctuations increase during drowsiness. In this work, a statistical based technique in frequency domain, known as Spectral F-Test (SFT), was applied in order to compare the power of pupillometric signals measured in two conditions, wakefulness and sleepiness, from eleven volunteers. SFT was calculated based on Welch Periodograms of time series of pupil diameter (TSPD) signals. The median power for TSPD in two conditions and each volunteer at frequencies bellow 0.8 Hz were compared by means of the paired Wilcoxon signed-rank test. The percentages of volunteers for whom power during drowsiness were statistically higher than power during alertness achieved 100% for several frequencies bellow 0.2 Hz. For frequencies from 0.2 to 0.8 Hz, the percentages presented high variability, fluctuating from 40 to 90%. The Wilcoxon test indicated that median power of TSPD during drowsiness was higher than TSPD during alertness for frequencies bellow 0.2 Hz presented statistical difference. Hence, the SFT showed to be a suitable tool for drowsiness/alertness differentiation that could be applied to sleep studies.

Research paper thumbnail of DETECÇÃO DA RESPOSTA SOMATO-SENSITIVA: COERÊNCIA SIMPLES (DERIVAÇÕES BIPOLARES) vs MÚLTIPLA (UNIPOLARES)

In this work the detection performance of two objective response detection (ORD) techniques is co... more In this work the detection performance of two objective response detection (ORD) techniques is compared, the Magnitude-Squared Coherence (MSC) and the Multiple Coherence (MC), in detecting the somatosensory stimuli-response. The MSC was applied to the bipolar derivations (C4-C3) and (Cz-Fz) and the MC to the unipolar ((C4) (C3)) and ((Cz) (Fz)). The MC((C4)(C3)) presented statistically significant higher detection rates than MSC((C4-C3)) in the range 29.0 to 53.1 Hz (except 38.6 and 48.3 Hz). The MC((Cz)(Fz)) surpassed the MSC((Cz-CFz)) only for 14.5 Hz. Hence, as a general rule, if one have two derivations available, it is better to use the MC of the unipolar leads than the MSC of the bipolar derivation. Palavras-chave: Somatosensory evoked potential, objective response detection, Ordinary and Multiple Coherence, unipolar and bipolar derivation.

Research paper thumbnail of Principal Components Clustering through a Variance-Defined Metric

IFMBE Proceedings, 2010

ABSTRACT This work aims at proposing a clustering procedure through a new metric, a weighted Eucl... more ABSTRACT This work aims at proposing a clustering procedure through a new metric, a weighted Euclidean distance, in which the weights are the ratio of corresponding eigenvalues and the largest eigenvalue found after a Principal Components Analysis. In order to illustrate the method, the procedure was carried out on twenty-one newborn EEG segments, classified as TA (Tracé Alternant) or HVS (High Voltage Slow) patterns. The observed clustering structure was assessed by the cophenetic and agglomerative coefficients. Results showed that, despite its unlikely existence, a clustering structure was suggested by the traditional approach. This structure, however, was not confirmed by the proposed method. KeywordsCluster Analysis-EEG-Principal Components Analysis

Research paper thumbnail of Simples Coherence vs. Multiple Coherence: A Somatosensory Evoked Response Detection Investigation

IFMBE Proceedings, 2010

In this work the performance of two techniques useful for detecting the somatosensory evoked pote... more In this work the performance of two techniques useful for detecting the somatosensory evoked potential (SEP), namely the Magnitude-Squared Coherence (MSC or Simple Coherence) and its multivariate version, the Multiple Coherence (MC), was compared. Electroencephalographic (EEG) signals during somatosensory stimulation were collected from forty adult volunteers without history of neurological pathology using the 10-20 International System. All leads were referenced to the earlobe average. The stimulation was carried out throughout current pulses (200 μs width) applied to the right posterior tibial nerve (motor threshold intensity level) at the rate of 5 Hz. The response detection was based on rejecting the null hypothesis of response absence (M = 100 epochs and significance level α = 0.05). The MSC was applied to the derivations [Cz], [Fz], [C3] and [C4], usually employed in the SEP recordings when bipolar derivations are used. The MC was applied to the pairs [Cz][Fz] and [C3][C4]. The results indicated that if two derivations are available, it should be better to use the MC applied to both leads than the MSC applied to each one.

Research paper thumbnail of Detecting response of somatosensory evoked potentials from averages with small number of epochs using Self-Organizing Map

2011 Pan American Health Care Exchanges, 2011

The aim of this work was to use the Self-Organizing Map (SOM) algorithm to classify EEG signals c... more The aim of this work was to use the Self-Organizing Map (SOM) algorithm to classify EEG signals collected during somatosensory stimulation. Third-six volunteers participated and the signals were classified as containing or not cortical stimuli-response. Five features were used to characterize the signals, referring to the averages' amplitude, latency and power spectral density using 500, 100 and 50 epochs. The SOM results clearly showed an adequate distinction between the two classes for 500 and 100 epochs. The SOM grid's sizes were determined by applying non-parametric bootstrap technique.

Research paper thumbnail of A multiple coherence-based detector for evoked responses in the EEG during sensory stimulation

2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2008

The sampling distribution of the multiple coherence estimate between a periodic signal and a set ... more The sampling distribution of the multiple coherence estimate between a periodic signal and a set of filtered versions of evoked responses embedded in additive noise signals is derived for the zero-coherence case. For a fixed number of signals used in the estimation, the probability density function varies with the number of data segments. Analytical expressions for both bias and variance of the estimate were derived and together with the critical values constitute the statistical apparatus for the detector based on this multiple coherence estimate. An illustration of the technique as applied to detect evoked responses in the Electroencephalogram during sensory stimulation is also provided.

Research paper thumbnail of Using the Discrete Hilbert Transform for the comparison between Tracé Alternant and High Voltage Slow patterns extracted from full-term neonatal EEG

IFMBE Proceedings, 2007

ABSTRACT This work aims at statistically evaluating the differences between two quiet sleep patte... more ABSTRACT This work aims at statistically evaluating the differences between two quiet sleep patterns, Tracé Alternant (TA) and High Voltage Slow (HVS) of EEG signals collected from derivation F4–P4 of 25 full-term newborns. Firstly, 124 artifact-free segments (30 s duration) during TA and 46 during HVS were selected. Then, each segment was filtered (6th order Butterwoth, zero-phase) in three distinct bands: slow delta (0.25–2 Hz), fast delta (2–4 Hz) and theta (4–8 Hz). By applying the Discrete Hilbert Transform (DHT) to these filtered signals, the envelope (A[n]) and the modulus of the instantaneous frequency (|Fi[n]|) were estimated. From these DHT dynamic spectral parameters, the sample distributions were determined and the medians obtained for each data segment. Based on this procedure, the medianvectors of HVS (mHVS) and of TA (mTA) for each parameter and each frequency band were formed. The time evolution of A[n] and |Fi[n]| for any pattern resembles the same characteristics (amplitude and frequency) of the original EEG signal. Moreover, applying the Wilcoxon rank sum test to mHVS and mTA, showed statistically significant differences (α = 0.05) between TA and HVS for A[n] in the three frequency bands. On the other hand, when this test is applied to |Fi[n]|, only the slow delta band presents significant difference. Hence, these findings could be used for distinguishing between HVS and TA.

Research paper thumbnail of The somatosensory evoked response detection using coherence and different stimulation frequencies

IFMBE Proceedings, 2009

This work aims at investigating the effects of the stimulation frequency in the somatosensory evo... more This work aims at investigating the effects of the stimulation frequency in the somatosensory evoked response detection using coherence. Electroencephalographic (EEG) signals during somatosensory stimulation were collected from thirty-seven adult volunteers without ...

Research paper thumbnail of Topographical distribution of the somatosensory evoked potential: an objective response detection approach

IFMBE Proceedings, 2007

This work aims at investigating the somatosensory evoked potential topographical distribution by ... more This work aims at investigating the somatosensory evoked potential topographical distribution by applying the Magnitude Squared Coherence (MSC), an Objective Response Detection technique in the frequency domain. The EEG was collected from eight ...

Research paper thumbnail of Frequency-Domain Objective Response Detection Techniques Applied to Evoked Potentials: A Review

Applied Biological Engineering - Principles and Practice, 2012

Research paper thumbnail of Logistic Regression Models: Feature Selection for P300 Detection Improvement

Brain computer interfaces are devices that enable people to communicate using their brain activit... more Brain computer interfaces are devices that enable people to communicate using their brain activity, being useful for those suffering with neurodegenerative diseases. Many BCI use the P300 evoked response. However, the detection of this potential is very difficult, since it presents low signal-to-noise ratio. This paper studies which time features present in the electroencephalogram can improve the detection rates of this response. For this purpose, logistic regression models were used to assess the significance of the following features for P300 representation: most positive peak, most negative peak, latencies of these peaks, area and RMS value between them. These parameters were evaluated on averages of 600 ms windows that could or not contain the potential. The results showed that positive peak, RMS value and both latencies significantly improve P300 detection rates.

Research paper thumbnail of N1 response attenuation and the mismatch negativity (MMN) to within- and across-category phonetic contrasts

Psychophysiology, Apr 7, 2017

According to the neural adaptation model of the mismatch negativity (MMN), the sensitivity of thi... more According to the neural adaptation model of the mismatch negativity (MMN), the sensitivity of this event-related response to both acoustic and categorical information in speech sounds can be accounted for by assuming that (a) the degree of overlapping between neural representations of two sounds depends on both the acoustic difference between them and whether or not they belong to distinct phonetic categories, and (b) a release from stimulus-specific adaptation causes an enhanced N1 obligatory response to infrequent deviant stimuli. On the basis of this view, we tested in Experiment 1 whether the N1 response to the second sound of a pair (S2 ) would be more attenuated in pairs of identical vowels compared with pairs of different vowels, and in pairs of exemplars of the same vowel category compared with pairs of exemplars of different categories. The psychoacoustic distance between S1 and S2 was the same for all within-category and across-category pairs. While N1 amplitudes decreased...

Research paper thumbnail of Multiple Coherence vs Multiple Component Synchrony Measure for somatosensory evoked response detection

2010 Annual International Conference of the IEEE Engineering in Medicine and Biology, 2010

This work aims at comparing the performance of two Multivariate Objective Response Detection (MOR... more This work aims at comparing the performance of two Multivariate Objective Response Detection (MORD) techniques in the frequency domain, the Multiple Coherence (MC) and the Multiple Component Synchrony Measure (MCSM), for tibial nerve somatosensory evoked potential (SEP) detection. Electroencephalographic (EEG) signals during somatosensory stimulation were collected from forty adult volunteers using the 10-20 International System. The stimulation was carried out throughout current pulses (200 µs width) applied to the right posterior tibial nerve (motor threshold intensity level) at the rate of 5 Hz. The response detection was based on rejecting the null hypothesis of response absence (M = 100 and M = 800 epochs and significance level α = 0.05). The MORD techniques were applied to the pairs of derivations [Cz][Fz] and [C3][C4]. The MC outperforms the MCSM, regardless the pair of derivations or the number of epochs used for the estimates calculation. Hence, the MC should be used, if two derivations are available for SEP recording.

Research paper thumbnail of Long-latency event-related responses to vowels: N1-P2 decomposition by two-step principal component analysis

International Journal of Psychophysiology, 2019

The N1-P2 complex of the auditory event-related potential (ERP) has been used to examine neural a... more The N1-P2 complex of the auditory event-related potential (ERP) has been used to examine neural activity associated with speech sound perception. Since it is thought to reflect multiple generator processes, its functional significance is difficult to infer. In the present study, a temporospatial principal component analysis (PCA) was used to decompose the N1-P2 response into latent factors underlying covariance patterns in ERP data recorded during passive listening to pairs of successive vowels. In each trial, one of six sounds drawn from an /i/-/e/ vowel continuum was followed either by an identical sound, a different token of the same vowel category, or a token from the other category. Responses were examined as to how they were modulated by within- and across-category vowel differences and by adaptation (repetition suppression) effects. Five PCA factors were identified as corresponding to three well-known N1 subcomponents and two P2 subcomponents. Results added evidence that the N1 peak reflects both generators that are sensitive to spectral information and generators that are not. For later latency ranges, different patterns of sensitivity to vowel quality were found, including category-related effects. Particularly, a subcomponent identified as the Tb wave showed release from adaptation in response to an /i/ followed by an /e/ sound. A P2 subcomponent varied linearly with spectral shape along the vowel continuum, while the other was stronger the closer the vowel was to the category boundary, suggesting separate processing of continuous and category-related information. Thus, the PCA-based decomposition of the N1-P2 complex was functionally meaningful, revealing distinct underlying processes at work during speech sound perception.

Research paper thumbnail of N1 response attenuation and the mismatch negativity (MMN) to within- and across-category phonetic contrasts

Psychophysiology, Apr 7, 2017

According to the neural adaptation model of the mismatch negativity (MMN), the sensitivity of thi... more According to the neural adaptation model of the mismatch negativity (MMN), the sensitivity of this event-related response to both acoustic and categorical information in speech sounds can be accounted for by assuming that (a) the degree of overlapping between neural representations of two sounds depends on both the acoustic difference between them and whether or not they belong to distinct phonetic categories, and (b) a release from stimulus-specific adaptation causes an enhanced N1 obligatory response to infrequent deviant stimuli. On the basis of this view, we tested in Experiment 1 whether the N1 response to the second sound of a pair (S2 ) would be more attenuated in pairs of identical vowels compared with pairs of different vowels, and in pairs of exemplars of the same vowel category compared with pairs of exemplars of different categories. The psychoacoustic distance between S1 and S2 was the same for all within-category and across-category pairs. While N1 amplitudes decreased...

Research paper thumbnail of Application of Multivariate Spectral F Test for Somatosensory Evoked Response Detection

Somatosensory Evoked Potential (SEP) is an important tool for monitoring vascular and spine surge... more Somatosensory Evoked Potential (SEP) is an important tool for monitoring vascular and spine surgeries, and other clinical applications. However, morphological SEP identification is subjective. Then, statistical techniques, such as Local Spectral F Test (SFT), have been used for response detection. The multivariate extension of SFT employs more than one derivation and has been recently considered advantageous to identify response to visual stimulation. This work aims at evaluating the performance of Multivariate SFT (MSFT) applied to EEG signals from 40 volunteers during stimulation at 5 Hz and different numbers of derivations (N), comparing the detection rates (DR). Frequencies of interest fo1 = 15 Hz and fo2 = 100 Hz were used, as well as L = 6 neighbor components at the frequencies from 70 to 95 Hz and a 5%-significance level. The number of derivations varied from N = 1 to 6. The detection rates obtained using fo1 were higher than those with fo2, which corresponds to false positiv...

Research paper thumbnail of Long-latency event-related responses to vowels: N1-P2 decomposition by two-step principal component analysis

International Journal of Psychophysiology

The N1-P2 complex of the auditory event-related potential (ERP) has been used to examine neural a... more The N1-P2 complex of the auditory event-related potential (ERP) has been used to examine neural activity associatedwithspeechsoundperception.Sinceitisthoughttoreflectmultiplegeneratorprocesses,itsfunctional significanceisdifficulttoinfer.Inthepresentstudy,atemporospatialprincipalcomponentanalysis(PCA)was usedtodecomposetheN1-P2responseintolatentfactorsunderlyingcovariancepatternsinERPdatarecorded duringpassivelisteningtopairsofsuccessivevowels.Ineachtrial,oneofsixsoundsdrawnfroman/i/−/e/ vowelcontinuumwasfollowedeitherbyanidenticalsound,adifferenttokenofthesamevowelcategory,ora tokenfromtheothercategory.Responseswereexaminedastohowtheyweremodulatedbywithin-andacrosscategoryvoweldifferencesandbyadaptation(repetitionsuppression)effects.FivePCAfactorswereidentifiedas correspondingtothreewell-knownN1subcomponentsandtwoP2subcomponents.Resultsaddedevidencethat theN1peakreflectsbothgeneratorsthataresensitivetospectralinformationandgeneratorsthatarenot.For later latency ranges, different patterns of sensitivity to vowel quality were found, including category-related effects.Particularly,asubcomponentidentifiedastheTbwaveshowedreleasefromadaptationinresponsetoan /i/ followed by an /e/ sound. A P2 subcomponent varied linearly with spectral shape along the vowel continuum, whilethe otherwas stronger thecloser thevowelwas tothe categoryboundary,suggesting separate processing of continuous and category-related information. Thus, the PCA-based decomposition of the N1-P2 complex was functionally meaningful, revealing distinct underlying processes at work during speech sound perception.

Research paper thumbnail of Long-latency event-related responses to vowels: N1-P2 decomposition by two-step principal component analysis

International Journal of Psychophysiology, 2019

The N1-P2 complex of the auditory event-related potential (ERP) has been used to examine neural a... more The N1-P2 complex of the auditory event-related potential (ERP) has been used to examine neural activity associatedwithspeechsoundperception.Sinceitisthoughttoreflectmultiplegeneratorprocesses,itsfunctional significanceisdifficulttoinfer.Inthepresentstudy,atemporospatialprincipalcomponentanalysis(PCA)was usedtodecomposetheN1-P2responseintolatentfactorsunderlyingcovariancepatternsinERPdatarecorded duringpassivelisteningtopairsofsuccessivevowels.Ineachtrial,oneofsixsoundsdrawnfroman/i/−/e/ vowelcontinuumwasfollowedeitherbyanidenticalsound,adifferenttokenofthesamevowelcategory,ora tokenfromtheothercategory.Responseswereexaminedastohowtheyweremodulatedbywithin-andacrosscategoryvoweldifferencesandbyadaptation(repetitionsuppression)effects.FivePCAfactorswereidentifiedas correspondingtothreewell-knownN1subcomponentsandtwoP2subcomponents.Resultsaddedevidencethat theN1peakreflectsbothgeneratorsthataresensitivetospectralinformationandgeneratorsthatarenot.For later latency ranges, different patterns of sensitivity to vowel quality were found, including category-related effects.Particularly,asubcomponentidentifiedastheTbwaveshowedreleasefromadaptationinresponsetoan /i/ followed by an /e/ sound. A P2 subcomponent varied linearly with spectral shape along the vowel continuum, whilethe otherwas stronger thecloser thevowelwas tothe categoryboundary,suggesting separate processing of continuous and category-related information. Thus, the PCA-based decomposition of the N1-P2 complex was functionally meaningful, revealing distinct underlying processes at work during speech sound perception.

Research paper thumbnail of N1 response attenuation and the mismatch negativity (MMN) to within‐and across‐category phonetic contrasts

According to the neural adaptation model of the mismatch negativity (MMN), the sensitivity of thi... more According to the neural adaptation model of the mismatch negativity (MMN), the sensitivity of this event-related response to both acoustic and categorical information in speech sounds can be accounted for by assuming that (a) the degree of overlapping between neural representations of two sounds depends on both the acoustic difference between them and whether or not they belong to distinct phonetic categories, and (b) a release from stimulus-specific adaptation causes an enhanced N1 obligatory response to infrequent deviant stimuli. On the basis of this view, we tested in Experiment 1 whether the N1 response to the second sound of a pair (S2) would be more attenuated in pairs of identical vowels compared with pairs of different vowels, and in pairs of exemplars of the same vowel category compared with pairs of exemplars of different categories. The psychoacoustic distance between S1 and S2 was the same for all within-category and across-category pairs. While N1 amplitudes decreased markedly from S1 to S2, responses to S2 were quite similar across pair types, indicating that the attenuation effect in such conditions is not stimulus specific. In Experiment 2, a pronounced MMN was elicited by a deviant vowel sound in an across-category oddball sequence, but not when the exact same deviant vowel was presented in a within-category oddball sequence. This adds evidence that MMN reflects categorical phonetic processing. Taken together, the results suggest that different neural processes underlie the attenuation of the N1 response to S2 and the MMN to vowels.

Research paper thumbnail of A Variance-based Approach to Perform Single-Trial P300 Detection

P300 is an event-related potential (ERP) recorded in scalp by means of electroencephalography (EE... more P300 is an event-related potential (ERP) recorded in scalp by means of electroencephalography (EEG), commonly used for developing brain-computer interfaces (BCI). One of the main challenges of using P300 is presented by its low signal-to-noise ratio (SNR), making its detection a dificult task. Grand averaging is a technique commonly used to overcome the low SNR. However, it requires longer EEG recording periods, which hardens the implementation of P300-based BCI. Hence, single-trial detection (STD) of such potential is desirable for this application. In this paper, we propose a method which uses metrics based on EEG variance together with logistic regression model to perform STD. The proposed method was tested in 24 subjects and showed mean accuracy of 76.1%, a promising result that is compatible/better with/than other ones found in literature.

Research paper thumbnail of Identification of drowsiness and alertness conditions by means of Spectral F-Test applied to pupillometric signals

Journal of Physics: Conference Series, 2013

ABSTRACT The autonomous regulation of pupil size provides an objective physiological measure of a... more ABSTRACT The autonomous regulation of pupil size provides an objective physiological measure of alertness level. Pupil diameter decreases and its fluctuations increase during drowsiness. In this work, a statistical based technique in frequency domain, known as Spectral F-Test (SFT), was applied in order to compare the power of pupillometric signals measured in two conditions, wakefulness and sleepiness, from eleven volunteers. SFT was calculated based on Welch Periodograms of time series of pupil diameter (TSPD) signals. The median power for TSPD in two conditions and each volunteer at frequencies bellow 0.8 Hz were compared by means of the paired Wilcoxon signed-rank test. The percentages of volunteers for whom power during drowsiness were statistically higher than power during alertness achieved 100% for several frequencies bellow 0.2 Hz. For frequencies from 0.2 to 0.8 Hz, the percentages presented high variability, fluctuating from 40 to 90%. The Wilcoxon test indicated that median power of TSPD during drowsiness was higher than TSPD during alertness for frequencies bellow 0.2 Hz presented statistical difference. Hence, the SFT showed to be a suitable tool for drowsiness/alertness differentiation that could be applied to sleep studies.

Research paper thumbnail of DETECÇÃO DA RESPOSTA SOMATO-SENSITIVA: COERÊNCIA SIMPLES (DERIVAÇÕES BIPOLARES) vs MÚLTIPLA (UNIPOLARES)

In this work the detection performance of two objective response detection (ORD) techniques is co... more In this work the detection performance of two objective response detection (ORD) techniques is compared, the Magnitude-Squared Coherence (MSC) and the Multiple Coherence (MC), in detecting the somatosensory stimuli-response. The MSC was applied to the bipolar derivations (C4-C3) and (Cz-Fz) and the MC to the unipolar ((C4) (C3)) and ((Cz) (Fz)). The MC((C4)(C3)) presented statistically significant higher detection rates than MSC((C4-C3)) in the range 29.0 to 53.1 Hz (except 38.6 and 48.3 Hz). The MC((Cz)(Fz)) surpassed the MSC((Cz-CFz)) only for 14.5 Hz. Hence, as a general rule, if one have two derivations available, it is better to use the MC of the unipolar leads than the MSC of the bipolar derivation. Palavras-chave: Somatosensory evoked potential, objective response detection, Ordinary and Multiple Coherence, unipolar and bipolar derivation.

Research paper thumbnail of Principal Components Clustering through a Variance-Defined Metric

IFMBE Proceedings, 2010

ABSTRACT This work aims at proposing a clustering procedure through a new metric, a weighted Eucl... more ABSTRACT This work aims at proposing a clustering procedure through a new metric, a weighted Euclidean distance, in which the weights are the ratio of corresponding eigenvalues and the largest eigenvalue found after a Principal Components Analysis. In order to illustrate the method, the procedure was carried out on twenty-one newborn EEG segments, classified as TA (Tracé Alternant) or HVS (High Voltage Slow) patterns. The observed clustering structure was assessed by the cophenetic and agglomerative coefficients. Results showed that, despite its unlikely existence, a clustering structure was suggested by the traditional approach. This structure, however, was not confirmed by the proposed method. KeywordsCluster Analysis-EEG-Principal Components Analysis

Research paper thumbnail of Simples Coherence vs. Multiple Coherence: A Somatosensory Evoked Response Detection Investigation

IFMBE Proceedings, 2010

In this work the performance of two techniques useful for detecting the somatosensory evoked pote... more In this work the performance of two techniques useful for detecting the somatosensory evoked potential (SEP), namely the Magnitude-Squared Coherence (MSC or Simple Coherence) and its multivariate version, the Multiple Coherence (MC), was compared. Electroencephalographic (EEG) signals during somatosensory stimulation were collected from forty adult volunteers without history of neurological pathology using the 10-20 International System. All leads were referenced to the earlobe average. The stimulation was carried out throughout current pulses (200 μs width) applied to the right posterior tibial nerve (motor threshold intensity level) at the rate of 5 Hz. The response detection was based on rejecting the null hypothesis of response absence (M = 100 epochs and significance level α = 0.05). The MSC was applied to the derivations [Cz], [Fz], [C3] and [C4], usually employed in the SEP recordings when bipolar derivations are used. The MC was applied to the pairs [Cz][Fz] and [C3][C4]. The results indicated that if two derivations are available, it should be better to use the MC applied to both leads than the MSC applied to each one.

Research paper thumbnail of Detecting response of somatosensory evoked potentials from averages with small number of epochs using Self-Organizing Map

2011 Pan American Health Care Exchanges, 2011

The aim of this work was to use the Self-Organizing Map (SOM) algorithm to classify EEG signals c... more The aim of this work was to use the Self-Organizing Map (SOM) algorithm to classify EEG signals collected during somatosensory stimulation. Third-six volunteers participated and the signals were classified as containing or not cortical stimuli-response. Five features were used to characterize the signals, referring to the averages' amplitude, latency and power spectral density using 500, 100 and 50 epochs. The SOM results clearly showed an adequate distinction between the two classes for 500 and 100 epochs. The SOM grid's sizes were determined by applying non-parametric bootstrap technique.

Research paper thumbnail of A multiple coherence-based detector for evoked responses in the EEG during sensory stimulation

2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2008

The sampling distribution of the multiple coherence estimate between a periodic signal and a set ... more The sampling distribution of the multiple coherence estimate between a periodic signal and a set of filtered versions of evoked responses embedded in additive noise signals is derived for the zero-coherence case. For a fixed number of signals used in the estimation, the probability density function varies with the number of data segments. Analytical expressions for both bias and variance of the estimate were derived and together with the critical values constitute the statistical apparatus for the detector based on this multiple coherence estimate. An illustration of the technique as applied to detect evoked responses in the Electroencephalogram during sensory stimulation is also provided.

Research paper thumbnail of Using the Discrete Hilbert Transform for the comparison between Tracé Alternant and High Voltage Slow patterns extracted from full-term neonatal EEG

IFMBE Proceedings, 2007

ABSTRACT This work aims at statistically evaluating the differences between two quiet sleep patte... more ABSTRACT This work aims at statistically evaluating the differences between two quiet sleep patterns, Tracé Alternant (TA) and High Voltage Slow (HVS) of EEG signals collected from derivation F4–P4 of 25 full-term newborns. Firstly, 124 artifact-free segments (30 s duration) during TA and 46 during HVS were selected. Then, each segment was filtered (6th order Butterwoth, zero-phase) in three distinct bands: slow delta (0.25–2 Hz), fast delta (2–4 Hz) and theta (4–8 Hz). By applying the Discrete Hilbert Transform (DHT) to these filtered signals, the envelope (A[n]) and the modulus of the instantaneous frequency (|Fi[n]|) were estimated. From these DHT dynamic spectral parameters, the sample distributions were determined and the medians obtained for each data segment. Based on this procedure, the medianvectors of HVS (mHVS) and of TA (mTA) for each parameter and each frequency band were formed. The time evolution of A[n] and |Fi[n]| for any pattern resembles the same characteristics (amplitude and frequency) of the original EEG signal. Moreover, applying the Wilcoxon rank sum test to mHVS and mTA, showed statistically significant differences (α = 0.05) between TA and HVS for A[n] in the three frequency bands. On the other hand, when this test is applied to |Fi[n]|, only the slow delta band presents significant difference. Hence, these findings could be used for distinguishing between HVS and TA.

Research paper thumbnail of The somatosensory evoked response detection using coherence and different stimulation frequencies

IFMBE Proceedings, 2009

This work aims at investigating the effects of the stimulation frequency in the somatosensory evo... more This work aims at investigating the effects of the stimulation frequency in the somatosensory evoked response detection using coherence. Electroencephalographic (EEG) signals during somatosensory stimulation were collected from thirty-seven adult volunteers without ...

Research paper thumbnail of Topographical distribution of the somatosensory evoked potential: an objective response detection approach

IFMBE Proceedings, 2007

This work aims at investigating the somatosensory evoked potential topographical distribution by ... more This work aims at investigating the somatosensory evoked potential topographical distribution by applying the Magnitude Squared Coherence (MSC), an Objective Response Detection technique in the frequency domain. The EEG was collected from eight ...

Research paper thumbnail of Frequency-Domain Objective Response Detection Techniques Applied to Evoked Potentials: A Review

Applied Biological Engineering - Principles and Practice, 2012