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Shennan A Weiss - One of the best experts on this subject based on the ideXlab platform.
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Ripples have distinct spectral properties and phase amplitude coupling with slow waves but indistinct unit firing in human epileptogenic hippocampus
Frontiers in Neurology, 2020Co-Authors: Shennan A Weiss, Inkyung Song, Mei Leng, Tomas Pastore, Diego Fernandez Slezak, Zachary J Waldman, Iren Orosz, Richard Gorniak, Mustafa Donmez, Ashwini SharanAbstract:Ripple oscillations in the normal hippocampus are involved in memory consolidation during rest and sleep. In the epileptic brain, increased ripple and fast ripple (200-600 Hz) rates serve as a biomarker of epileptogenic brain. We report that both Ripples and fast Ripples exhibit a preferred phase angle of coupling with the trough-peak (On-Off state transition) of the sleep slow wave in the hippocampal seizure onset zone (SOZ). Ripples on slow waves in the hippocampal SOZ also had a lower power, greater spectral frequency, and shorter duration than those in the non-SOZ. We found that slow waves in the mesial temporal lobe modulated the baseline firing rate of excitatory neurons, but did not significantly influence the increased firing rate associated with Ripples. In summary, pathological Ripples and fast Ripples occur preferentially during the On-Off state transition in the epileptogenic hippocampus, but Ripples do not require the increased recruitment of excitatory neurons.
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Ripples on spikes show increased phase amplitude coupling in mesial temporal lobe epilepsy seizure onset zones
Epilepsia, 2016Co-Authors: Shennan A Weiss, Iren Orosz, Noriko Salamon, Stephanie Moy, Linqing Wei, Maryse Vant A Klooster, Robert T Knight, Ronald M HarperAbstract:SummaryObjective Ripples (80–150 Hz) recorded from clinical macroelectrodes have been shown to be an accurate biomarker of epileptogenic brain tissue. We investigated coupling between epileptiform spike phase and ripple amplitude to better understand the mechanisms that generate this type of pathologic ripple (pRipple) event. Methods We quantified phase amplitude coupling (PAC) between epileptiform electroencephalography (EEG) spike phase and ripple amplitude recorded from intracranial depth macroelectrodes during episodes of sleep in 12 patients with mesial temporal lobe epilepsy. PAC was determined by (1) a phasor transform that corresponds to the strength and rate of Ripples coupled with spikes, and a (2) ripple-triggered average to measure the strength, morphology, and spectral frequency of the modulating and modulated signals. Coupling strength was evaluated in relation to recording sites within and outside the seizure-onset zone (SOZ). Results Both the phasor transform and ripple-triggered averaging methods showed that ripple amplitude was often robustly coupled with epileptiform EEG spike phase. Coupling was found more regularly inside than outside the SOZ, and coupling strength correlated with the likelihood a macroelectrode's location was within the SOZ (p < 0.01). The ratio of the rate of Ripples coupled with EEG spikes inside the SOZ to rates of coupled Ripples in non-SOZ was greater than the ratio of rates of Ripples on spikes detected irrespective of coupling (p < 0.05). Coupling strength correlated with an increase in mean normalized ripple amplitude (p < 0.01), and a decrease in mean ripple spectral frequency (p < 0.05). Significance Generation of low-frequency (80–150 Hz) pRipples in the SOZ involves coupling between epileptiform spike phase and ripple amplitude. The changes in excitability reflected as epileptiform spikes may also cause clusters of pathologically interconnected bursting neurons to grow and synchronize into aberrantly large neuronal assemblies.
Alexander Ya Supin - One of the best experts on this subject based on the ideXlab platform.
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Rippled Depth Thresholds: Estimates Obtained by Discrimination From Rippled and Nonrippled Reference Signals
Acta Acustica united with Acustica, 2019Co-Authors: Alexander Ya Supin, Olga N. Milekhina, Dmitry I. NechaevAbstract:The objective of the study was to better understand of contribution of excitation-pattern and temporal-processing mechanisms of frequency analysis to discrimination of complex-spectrum signals in various discrimination tasks. Using rippled-spectrum signals, the ripple depth thresholds were measured as functions of ripple density under conditions of rippled or non-rippled reference signals. With rippled reference signals, the ripple depth thresholds were as low as 0.11 at low ripple densities (2–3 cycles/oct) and rose to 1.0 at a ripple density of 8.9 cycles/oct. For non-rippled reference signals, ripple depth thresholds were nearly the same as for rippled reference signals at ripple densities of up to 7 cycles/oct; at ripple densities of 10 cycles/oct and higher, ripple depth thresholds rose slowly and reached 1.0 at a ripple density of 26 cycles/oct. The results hypothetically suggest contributions of the excitation-pattern processing and temporal-processing mechanisms of frequency analysis to discrimination of rippled signals. The excitation-pattern mechanism featured low depth thresholds at low ripple densities but could not function at ripple densities above 10 cycles/oct. The temporal-processing mechanism manifested at higher ripple densities and non-rippled reference stimuli.
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Estimates of Ripple-Density Resolution Based on the Discrimination From Rippled and Nonrippled Reference Signals.
Trends in hearing, 2019Co-Authors: Dmitry I. Nechaev, Olga N. Milekhina, Alexander Ya SupinAbstract:: Rippled-spectrum stimuli are used to evaluate the resolution of the spectro-temporal structure of sounds. Measurements of spectrum-pattern resolution imply the discrimination between the test and reference stimuli. Therefore, estimates of rippled-pattern resolution could depend on both the test stimulus and the reference stimulus type. In this study, the ripple-density resolution was measured using combinations of two test stimuli and two reference stimuli. The test stimuli were rippled-spectrum signals with constant phase or rippled-spectrum signals with ripple-phase reversals. The reference stimuli were rippled-spectrum signals with opposite ripple phase to the test or nonrippled signals. The spectra were centered at 2 kHz and had an equivalent rectangular bandwidth of 1 oct and a level of 70 dB sound pressure level. A three-alternative forced-choice procedure was combined with an adaptive procedure. With rippled reference stimuli, the mean ripple-density resolution limits were 8.9 Ripples/oct (phase-reversals test stimulus) or 7.7 Ripples/oct (constant-phase test stimulus). With nonrippled reference stimuli, the mean resolution limits were 26.1 Ripples/oct (phase-reversals test stimulus) or 22.2 Ripples/oct (constant-phase test stimulus). Different contributions of excitation-pattern and temporal-processing mechanisms are assumed for measurements with rippled and nonrippled reference stimuli: The excitation-pattern mechanism is more effective for the discrimination of rippled stimuli that differ in their ripple-phase patterns, whereas the temporal-processing mechanism is more effective for the discrimination of rippled and nonrippled stimuli.
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Discrimination of rippled spectra: Contribution of excitation-pattern and temporal-processing mechanisms
The Journal of the Acoustical Society of America, 2019Co-Authors: Olga N. Milekhina, Dmitry I. Nechaev, Alexander Ya SupinAbstract:Rippled-spectrum signals are used for measurements of signal resolution in hearing-impaired listeners and cochlear-implant users. Two mechanisms may be responsible for rippled-spectrum resolution. The excitation-pattern mechanism determines the ripple density resolution (Ripples/oct). The temporal-processing mechanism determines the ripple frequency spacing limit (kHz). Contributions of the mechanisms can be assessed by comparison of resolutions of band-limited rippled spectra with different center frequencies, because the ratio of rippe spacing to ripple density is frequency-proportional. Ripple-density resolutions of half-octave rippled spectra were measured at center frequencies from 0.5 to 4 kHz. The measurements were performed either by discrimination between rippled-spectrum test and reference signals differing by ripple phases or by discrimination between a rippled-spectrum test and non-rippled reference signal. For discrimination between rippled-spectrum test and reference signals, resolution specified in Ripples/oct little depended on center frequency, as predicted by the excitation-pattern model. For discrimination between rippled test and non-rippled reference signals, the resolution specified in ripple frequency spacing little depended on center frequency, as predicted by the temporal-processing model. It was concluded that contributions of the excitation-pattern and temporal-processing mechanism depend on the discrimination task. Rippled-spectrum signals are used for measurements of signal resolution in hearing-impaired listeners and cochlear-implant users. Two mechanisms may be responsible for rippled-spectrum resolution. The excitation-pattern mechanism determines the ripple density resolution (Ripples/oct). The temporal-processing mechanism determines the ripple frequency spacing limit (kHz). Contributions of the mechanisms can be assessed by comparison of resolutions of band-limited rippled spectra with different center frequencies, because the ratio of rippe spacing to ripple density is frequency-proportional. Ripple-density resolutions of half-octave rippled spectra were measured at center frequencies from 0.5 to 4 kHz. The measurements were performed either by discrimination between rippled-spectrum test and reference signals differing by ripple phases or by discrimination between a rippled-spectrum test and non-rippled reference signal. For discrimination between rippled-spectrum test and reference signals, resolution spe...
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Discrimination of rippled spectra at various frequencies: Contribution of excitation-pattern and temporal-processing mechanisms
178th Meeting of the Acoustical Society of America, 2019Co-Authors: Alexander Ya Supin, Dmitry I. Nechaev, Olga N. Milekhina, Evgenia V. SysuevaAbstract:Rippled-spectrum signals are used for signal-resolution measurements in hearing-impaired listeners and cochlear implant users. Two mechanisms are presumably responsible for rippled-spectrum resolution. The excitation-pattern mechanism determines the ripple-density resolution (Ripples/oct). The temporal-processing mechanism determines the ripple frequency spacing limit (kHz). The contributions of these two mechanisms can be assessed by comparing the resolutions of band-limited rippled spectra with different center frequencies. Ripple-density resolutions of half-octave rippled spectra were measured at center frequencies ranging from 0.5 to 4 kHz. The measurements were performed either by discrimination between a rippled-spectrum test and reference signals differing by ripple phases or by discrimination between a rippled-spectrum test and a nonrippled reference signal. For discrimination between rippled-spectrum tests and reference signals, the resolution specified in Ripples/oct depended very little on the center frequency, as predicted by the excitation-pattern model. For discrimination between rippled tests and nonrippled reference signals, the resolution specified in the ripple frequency spacing depended very little on the center frequency, as predicted by the temporal-processing model. This study concluded that contributions of the excitation-pattern and temporal-processing mechanisms depend on the discrimination task.Rippled-spectrum signals are used for signal-resolution measurements in hearing-impaired listeners and cochlear implant users. Two mechanisms are presumably responsible for rippled-spectrum resolution. The excitation-pattern mechanism determines the ripple-density resolution (Ripples/oct). The temporal-processing mechanism determines the ripple frequency spacing limit (kHz). The contributions of these two mechanisms can be assessed by comparing the resolutions of band-limited rippled spectra with different center frequencies. Ripple-density resolutions of half-octave rippled spectra were measured at center frequencies ranging from 0.5 to 4 kHz. The measurements were performed either by discrimination between a rippled-spectrum test and reference signals differing by ripple phases or by discrimination between a rippled-spectrum test and a nonrippled reference signal. For discrimination between rippled-spectrum tests and reference signals, the resolution specified in Ripples/oct depended very little on the ...
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Discrimination of ripple depth in rippled spectra: Contributions of spectral and temporal mechanisms
178th Meeting of the Acoustical Society of America, 2019Co-Authors: Alexander Ya Supin, Dmitry I. Nechaev, Olga N. Milekhina, Evgenia V. SysuevaAbstract:Rippled-spectrum signals are used to measure signal resolution in hearing-impaired listeners and cochlear implant users. Two mechanisms are believed to be responsible for rippled-spectrum resolution. The excitation-pattern mechanism determines the ripple density resolution (Ripples/oct). The temporal processing mechanism determines the ripple frequency spacing limit (kHz). The contributions of these two mechanisms can be assessed by comparing the resolutions of band-limited rippled spectra with different center frequencies. Ripple-density resolutions of half-octave rippled spectra were measured at center frequencies from 0.5 to 4 kHz. Measurements were performed either by discrimination between the rippled-spectrum test and reference signals differing by ripple phases or by discrimination between the rippled-spectrum test and a non-rippled reference signal. For discrimination between the rippled-spectrum test and reference signals, resolutions specified in Ripples/oct minimally depended on the center frequency, as predicted by the excitation-pattern model. For discrimination between the rippled test and non-rippled reference signals, the resolution specified by the ripple frequency spacing minimally depended on the center frequency, as predicted by the temporal processing model. It was concluded that the contributions of the excitation-pattern and temporal processing mechanisms depended on the discrimination task.
Jonas C. Bruder - One of the best experts on this subject based on the ideXlab platform.
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Physiological Ripples Associated with Sleep Spindles Differ in Waveform Morphology from Epileptic Ripples.
International Journal of Neural Systems, 2016Co-Authors: Jonas C. Bruder, Matthias Dümpelmann, Daniel Lachner Piza, Malenka Mader, Andreas Schulze-bonhage, Julia Jacobs-le VanAbstract:High frequency oscillations (HFOs, 80–500Hz) serve as novel electroencephalography (EEG) markers of epileptic tissue. The differentiation of physiological and epileptic HFO is an important challenge and is complicated by the fact that both types are generated in mesiotemporal structures. This study aimed to identify oscillation features that serve to distinguish physiological Ripples associated with sleep spindles and epileptic Ripples. We studied 19 patients with chronic intracranial EEG(iEEG) with mesiotemporal implantation and simultaneous scalp EEG. Sleep spindles, Ripples and spikes were visually marked during nonrapid eye movement sleep stage 2. Ripples co-occurring with spikes and in seizure onset zone (SOZ) channels but outside of spindles were considered epileptic. The SOZ is defined by the origin of clinical seizures in iEEG. Ripples co-occurring with spindles were considered as models for physiological Ripples. A correlation analysis showed a significant ripple amplitude peak — spindle trough — coupling, thus proving their physiological linkage. Epileptic Ripples showed significantly higher values in all amplitude features than spindle Ripples. All amplitude features and peaks per sample length showed a predictive value for the classification between model physiological Ripples and epileptic Ripples but indicate that the specificity is not sufficient for a reliable discrimination of single ripple events. The presented results suggest that a secure identification of epileptic Ripples may be available to help identify the epileptic focus in the future.
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Physiological Ripples Associated with Sleep Spindles Differ in Waveform Morphology from Epileptic Ripples.
International journal of neural systems, 2016Co-Authors: Jonas C. Bruder, Matthias Dümpelmann, Daniel Lachner Piza, Malenka Mader, Andreas Schulze-bonhage, Julia Jacobs-le VanAbstract:High frequency oscillations (HFOs, 80-500[Formula: see text]Hz) serve as novel electroencephalography (EEG) markers of epileptic tissue. The differentiation of physiological and epileptic HFO is an important challenge and is complicated by the fact that both types are generated in mesiotemporal structures. This study aimed to identify oscillation features that serve to distinguish physiological Ripples associated with sleep spindles and epileptic Ripples. We studied 19 patients with chronic intracranial EEG(iEEG) with mesiotemporal implantation and simultaneous scalp EEG. Sleep spindles, Ripples and spikes were visually marked during nonrapid eye movement sleep stage 2. Ripples co-occurring with spikes and in seizure onset zone (SOZ) channels but outside of spindles were considered epileptic. The SOZ is defined by the origin of clinical seizures in iEEG. Ripples co-occurring with spindles were considered as models for physiological Ripples. A correlation analysis showed a significant ripple amplitude peak - spindle trough - coupling, thus proving their physiological linkage. Epileptic Ripples showed significantly higher values in all amplitude features than spindle Ripples. All amplitude features and peaks per sample length showed a predictive value for the classification between model physiological Ripples and epileptic Ripples but indicate that the specificity is not sufficient for a reliable discrimination of single ripple events. The presented results suggest that a secure identification of epileptic Ripples may be available to help identify the epileptic focus in the future.
Dmitry I. Nechaev - One of the best experts on this subject based on the ideXlab platform.
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Rippled Depth Thresholds: Estimates Obtained by Discrimination From Rippled and Nonrippled Reference Signals
Acta Acustica united with Acustica, 2019Co-Authors: Alexander Ya Supin, Olga N. Milekhina, Dmitry I. NechaevAbstract:The objective of the study was to better understand of contribution of excitation-pattern and temporal-processing mechanisms of frequency analysis to discrimination of complex-spectrum signals in various discrimination tasks. Using rippled-spectrum signals, the ripple depth thresholds were measured as functions of ripple density under conditions of rippled or non-rippled reference signals. With rippled reference signals, the ripple depth thresholds were as low as 0.11 at low ripple densities (2–3 cycles/oct) and rose to 1.0 at a ripple density of 8.9 cycles/oct. For non-rippled reference signals, ripple depth thresholds were nearly the same as for rippled reference signals at ripple densities of up to 7 cycles/oct; at ripple densities of 10 cycles/oct and higher, ripple depth thresholds rose slowly and reached 1.0 at a ripple density of 26 cycles/oct. The results hypothetically suggest contributions of the excitation-pattern processing and temporal-processing mechanisms of frequency analysis to discrimination of rippled signals. The excitation-pattern mechanism featured low depth thresholds at low ripple densities but could not function at ripple densities above 10 cycles/oct. The temporal-processing mechanism manifested at higher ripple densities and non-rippled reference stimuli.
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Estimates of Ripple-Density Resolution Based on the Discrimination From Rippled and Nonrippled Reference Signals.
Trends in hearing, 2019Co-Authors: Dmitry I. Nechaev, Olga N. Milekhina, Alexander Ya SupinAbstract:: Rippled-spectrum stimuli are used to evaluate the resolution of the spectro-temporal structure of sounds. Measurements of spectrum-pattern resolution imply the discrimination between the test and reference stimuli. Therefore, estimates of rippled-pattern resolution could depend on both the test stimulus and the reference stimulus type. In this study, the ripple-density resolution was measured using combinations of two test stimuli and two reference stimuli. The test stimuli were rippled-spectrum signals with constant phase or rippled-spectrum signals with ripple-phase reversals. The reference stimuli were rippled-spectrum signals with opposite ripple phase to the test or nonrippled signals. The spectra were centered at 2 kHz and had an equivalent rectangular bandwidth of 1 oct and a level of 70 dB sound pressure level. A three-alternative forced-choice procedure was combined with an adaptive procedure. With rippled reference stimuli, the mean ripple-density resolution limits were 8.9 Ripples/oct (phase-reversals test stimulus) or 7.7 Ripples/oct (constant-phase test stimulus). With nonrippled reference stimuli, the mean resolution limits were 26.1 Ripples/oct (phase-reversals test stimulus) or 22.2 Ripples/oct (constant-phase test stimulus). Different contributions of excitation-pattern and temporal-processing mechanisms are assumed for measurements with rippled and nonrippled reference stimuli: The excitation-pattern mechanism is more effective for the discrimination of rippled stimuli that differ in their ripple-phase patterns, whereas the temporal-processing mechanism is more effective for the discrimination of rippled and nonrippled stimuli.
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Discrimination of rippled spectra: Contribution of excitation-pattern and temporal-processing mechanisms
The Journal of the Acoustical Society of America, 2019Co-Authors: Olga N. Milekhina, Dmitry I. Nechaev, Alexander Ya SupinAbstract:Rippled-spectrum signals are used for measurements of signal resolution in hearing-impaired listeners and cochlear-implant users. Two mechanisms may be responsible for rippled-spectrum resolution. The excitation-pattern mechanism determines the ripple density resolution (Ripples/oct). The temporal-processing mechanism determines the ripple frequency spacing limit (kHz). Contributions of the mechanisms can be assessed by comparison of resolutions of band-limited rippled spectra with different center frequencies, because the ratio of rippe spacing to ripple density is frequency-proportional. Ripple-density resolutions of half-octave rippled spectra were measured at center frequencies from 0.5 to 4 kHz. The measurements were performed either by discrimination between rippled-spectrum test and reference signals differing by ripple phases or by discrimination between a rippled-spectrum test and non-rippled reference signal. For discrimination between rippled-spectrum test and reference signals, resolution specified in Ripples/oct little depended on center frequency, as predicted by the excitation-pattern model. For discrimination between rippled test and non-rippled reference signals, the resolution specified in ripple frequency spacing little depended on center frequency, as predicted by the temporal-processing model. It was concluded that contributions of the excitation-pattern and temporal-processing mechanism depend on the discrimination task. Rippled-spectrum signals are used for measurements of signal resolution in hearing-impaired listeners and cochlear-implant users. Two mechanisms may be responsible for rippled-spectrum resolution. The excitation-pattern mechanism determines the ripple density resolution (Ripples/oct). The temporal-processing mechanism determines the ripple frequency spacing limit (kHz). Contributions of the mechanisms can be assessed by comparison of resolutions of band-limited rippled spectra with different center frequencies, because the ratio of rippe spacing to ripple density is frequency-proportional. Ripple-density resolutions of half-octave rippled spectra were measured at center frequencies from 0.5 to 4 kHz. The measurements were performed either by discrimination between rippled-spectrum test and reference signals differing by ripple phases or by discrimination between a rippled-spectrum test and non-rippled reference signal. For discrimination between rippled-spectrum test and reference signals, resolution spe...
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Discrimination of rippled spectra at various frequencies: Contribution of excitation-pattern and temporal-processing mechanisms
178th Meeting of the Acoustical Society of America, 2019Co-Authors: Alexander Ya Supin, Dmitry I. Nechaev, Olga N. Milekhina, Evgenia V. SysuevaAbstract:Rippled-spectrum signals are used for signal-resolution measurements in hearing-impaired listeners and cochlear implant users. Two mechanisms are presumably responsible for rippled-spectrum resolution. The excitation-pattern mechanism determines the ripple-density resolution (Ripples/oct). The temporal-processing mechanism determines the ripple frequency spacing limit (kHz). The contributions of these two mechanisms can be assessed by comparing the resolutions of band-limited rippled spectra with different center frequencies. Ripple-density resolutions of half-octave rippled spectra were measured at center frequencies ranging from 0.5 to 4 kHz. The measurements were performed either by discrimination between a rippled-spectrum test and reference signals differing by ripple phases or by discrimination between a rippled-spectrum test and a nonrippled reference signal. For discrimination between rippled-spectrum tests and reference signals, the resolution specified in Ripples/oct depended very little on the center frequency, as predicted by the excitation-pattern model. For discrimination between rippled tests and nonrippled reference signals, the resolution specified in the ripple frequency spacing depended very little on the center frequency, as predicted by the temporal-processing model. This study concluded that contributions of the excitation-pattern and temporal-processing mechanisms depend on the discrimination task.Rippled-spectrum signals are used for signal-resolution measurements in hearing-impaired listeners and cochlear implant users. Two mechanisms are presumably responsible for rippled-spectrum resolution. The excitation-pattern mechanism determines the ripple-density resolution (Ripples/oct). The temporal-processing mechanism determines the ripple frequency spacing limit (kHz). The contributions of these two mechanisms can be assessed by comparing the resolutions of band-limited rippled spectra with different center frequencies. Ripple-density resolutions of half-octave rippled spectra were measured at center frequencies ranging from 0.5 to 4 kHz. The measurements were performed either by discrimination between a rippled-spectrum test and reference signals differing by ripple phases or by discrimination between a rippled-spectrum test and a nonrippled reference signal. For discrimination between rippled-spectrum tests and reference signals, the resolution specified in Ripples/oct depended very little on the ...
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Discrimination of ripple depth in rippled spectra: Contributions of spectral and temporal mechanisms
178th Meeting of the Acoustical Society of America, 2019Co-Authors: Alexander Ya Supin, Dmitry I. Nechaev, Olga N. Milekhina, Evgenia V. SysuevaAbstract:Rippled-spectrum signals are used to measure signal resolution in hearing-impaired listeners and cochlear implant users. Two mechanisms are believed to be responsible for rippled-spectrum resolution. The excitation-pattern mechanism determines the ripple density resolution (Ripples/oct). The temporal processing mechanism determines the ripple frequency spacing limit (kHz). The contributions of these two mechanisms can be assessed by comparing the resolutions of band-limited rippled spectra with different center frequencies. Ripple-density resolutions of half-octave rippled spectra were measured at center frequencies from 0.5 to 4 kHz. Measurements were performed either by discrimination between the rippled-spectrum test and reference signals differing by ripple phases or by discrimination between the rippled-spectrum test and a non-rippled reference signal. For discrimination between the rippled-spectrum test and reference signals, resolutions specified in Ripples/oct minimally depended on the center frequency, as predicted by the excitation-pattern model. For discrimination between the rippled test and non-rippled reference signals, the resolution specified by the ripple frequency spacing minimally depended on the center frequency, as predicted by the temporal processing model. It was concluded that the contributions of the excitation-pattern and temporal processing mechanisms depended on the discrimination task.
Julia Jacobs-le Van - One of the best experts on this subject based on the ideXlab platform.
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Physiological Ripples Associated with Sleep Spindles Differ in Waveform Morphology from Epileptic Ripples.
International Journal of Neural Systems, 2016Co-Authors: Jonas C. Bruder, Matthias Dümpelmann, Daniel Lachner Piza, Malenka Mader, Andreas Schulze-bonhage, Julia Jacobs-le VanAbstract:High frequency oscillations (HFOs, 80–500Hz) serve as novel electroencephalography (EEG) markers of epileptic tissue. The differentiation of physiological and epileptic HFO is an important challenge and is complicated by the fact that both types are generated in mesiotemporal structures. This study aimed to identify oscillation features that serve to distinguish physiological Ripples associated with sleep spindles and epileptic Ripples. We studied 19 patients with chronic intracranial EEG(iEEG) with mesiotemporal implantation and simultaneous scalp EEG. Sleep spindles, Ripples and spikes were visually marked during nonrapid eye movement sleep stage 2. Ripples co-occurring with spikes and in seizure onset zone (SOZ) channels but outside of spindles were considered epileptic. The SOZ is defined by the origin of clinical seizures in iEEG. Ripples co-occurring with spindles were considered as models for physiological Ripples. A correlation analysis showed a significant ripple amplitude peak — spindle trough — coupling, thus proving their physiological linkage. Epileptic Ripples showed significantly higher values in all amplitude features than spindle Ripples. All amplitude features and peaks per sample length showed a predictive value for the classification between model physiological Ripples and epileptic Ripples but indicate that the specificity is not sufficient for a reliable discrimination of single ripple events. The presented results suggest that a secure identification of epileptic Ripples may be available to help identify the epileptic focus in the future.
