scholarly journals Phase-Amplitude Markers of Synchrony and Noise: A Resting-State and TMS-EEG Study of Schizophrenia

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Dominik Freche ◽  
Jodie Naim-Feil ◽  
Shmuel Hess ◽  
Avraham Peled ◽  
Alexander Grinshpoon ◽  
...  
Keyword(s):  
Resting State ◽  
Narrow Band ◽  
Signal To Noise Ratio ◽  
Phase Locking ◽  
Activity Patterns ◽  
Neuronal Populations ◽  
Correlated Activity ◽  
Amplitude Fluctuations ◽  
Phase Amplitude ◽  
External Stimuli

Abstract The electroencephalogram (EEG) of schizophrenia patients is known to exhibit a reduction of signal-to-noise ratio and of phase locking, as well as a facilitation of excitability, in response to a variety of external stimuli. Here, we demonstrate these effects in transcranial magnetic stimulation (TMS)-evoked potentials and in the resting-state EEG. To ensure veracity, we used 3 weekly sessions and analyzed both resting-state and TMS-EEG data. For the TMS responses, our analysis verifies known results. For the resting state, we introduce the methodology of mean-normalized variation to the EEG analysis (quartile-based coefficient of variation), which allows for a comparison of narrow-band EEG amplitude fluctuations to narrow-band Gaussian noise. This reveals that amplitude fluctuations in the delta, alpha, and beta bands of healthy controls are different from those in schizophrenia patients, on time scales of tens of seconds. We conclude that the EEG-measured cortical activity patterns of schizophrenia patients are more similar to noise, both in alpha- and beta-resting state and in TMS responses. Our results suggest that the ability of neuronal populations to form stable, locally, and temporally correlated activity is reduced in schizophrenia, a conclusion, that is, in accord with previous experiments on TMS-EEG and on resting-state EEG.

scholarly journals Phase-amplitude markers of synchrony and noise: A resting-state and TMS-EEG study of schizophrenia

2019 ◽  
Author(s):  
D Freche ◽  
J Naim-Feil ◽  
S Hess ◽  
A Peled ◽  
A Grinshpoon ◽  
...  
Keyword(s):  
Resting State ◽  
Narrow Band ◽  
Signal To Noise Ratio ◽  
Phase Locking ◽  
Activity Patterns ◽  
Neuronal Populations ◽  
Correlated Activity ◽  
Amplitude Fluctuations ◽  
Phase Amplitude ◽  
External Stimuli

AbstractThe electroencephalogram (EEG) of schizophrenia patients is known to exhibit a reduction of signal-to-noise ratio and of phase locking, as well as a facilitation of excitability, in response to a variety of external stimuli. Here we demonstrate these effects in transcranial magnetic stimulation (TMS)-evoked potentials and in the resting-state EEG. To ensure veracity we used three weekly sessions and analyzed both resting state and TMS-EEG data. For the TMS responses our analysis verifies known results. For the resting state we introduce the methodology of mean-normalized variation to the EEG analysis (quartile-based coefficient of variation), which allows for a comparison of narrow-band EEG amplitude fluctuations to narrow-band Gaussian noise. This reveals that amplitude fluctuations in the delta, alpha and beta bands of healthy controls are different from those in schizophrenia patients, on time scales of tens of seconds. We conclude that the EEG-measured cortical activity patterns of schizophrenia patients are more similar to noise, both in alpha and beta resting state and in TMS responses. Our results suggest that the ability of neuronal populations to form stable, locally and temporally correlated activity is reduced in schizophrenia, a conclusion that is in accord with previous experiments on TMS-EEG and on resting-state EEG.

scholarly journals Complexity and 1/f slope jointly reflect cortical states across different E/I balances

2020 ◽  
Author(s):  
V. Medel ◽  
M. Irani ◽  
T. Ossandón ◽  
G. Boncompte
Keyword(s):  
Resting State ◽  
Spectral Properties ◽  
Spectral Power ◽  
Activity Patterns ◽  
Brain Functioning ◽  
Human Eeg ◽  
Two Measures ◽  
External Stimuli ◽  
Monotonic Relation

AbstractCharacterization of cortical states is essential for understanding brain functioning in the absence of external stimuli. The balance between excitation and inhibition and the number of non-redundant activity patterns, indexed by the 1/f slope and LZc respectively, distinguish cortical states. However, the relation between these two measures has not been characterized. Here we analyzed the relation between 1/f slope and LZc with two modeling approaches and in empirical human EEG and monkey ECoG data. We contrasted resting state with propofol anesthesia, which is known to modulate the excitation-inhibition balance. We found convergent results among all strategies employed, showing an inverse and not trivial monotonic relation between 1/f slope and complexity. This behavior was observed even when the signals’ spectral properties were heavily manipulated, consistent at ECoG and EEG scales. Models also showed that LZc was strongly dependent on 1/f slope but independent of the signal’s spectral power law’s offset. Our results show that, although these measures have very distinct mathematical origins, they are closely related. We hypothesize that differentially entropic regimes could underlie the link between the excitation-inhibition balance and the vastness of repertoire of cortical systems.

scholarly journals Quantification of Phase-Amplitude Coupling in Neuronal Oscillations: Comparison of Phase-Locking Value, Mean Vector Length, and Modulation Index

2018 ◽  
Author(s):  
Mareike J. Hülsemann ◽  
Dr. rer. nat ◽  
Ewald Naumann ◽  
Dr. rer. nat ◽  
Björn Rasch
Keyword(s):  
Signal To Noise Ratio ◽  
Phase Locking ◽  
Sampling Rate ◽  
Modulation Index ◽  
Vector Length ◽  
The Mean ◽  
Phase Amplitude ◽  
Phase Locking Value ◽  
Mean Vector ◽  
Data Length

AbstractPhase-amplitude coupling is a promising construct to study cognitive processes in electroencephalography (EEG) and magnetencephalography (MEG). Due to the novelty of the concept, various measures are used in the literature to calculate phase-amplitude coupling. Here, performance of the three most widely used phase-amplitude coupling measures – phase-locking value (PLV), mean vector length (MVL), and modulation index (MI) – is thoroughly compared with the help of simulated data. We combine advantages of previous reviews and use a realistic data simulation, examine moderators and provide inferential statistics for the comparison of all three indices of phase-amplitude coupling. Our analyses show that all three indices successfully differentiate coupling strength and coupling width when monophasic coupling is present. While the mean vector length was most sensitive to modulations in coupling strengths and width, biphasic coupling can solely be detected by the modulation index. Coupling values of all three indices were influenced by moderators including data length, signal-to-noise-ratio, and sampling rate when approaching Nyquist frequencies. The modulation index was most robust against confounding influences of these moderators. Based on our analyses, we recommend the modulation index for noisy and short data epochs with unknown forms of coupling. For high quality and long data epochs with monophasic coupling and a high signal-to-noise ratio, the use of the mean vector length is recommended. Ideally, both indices are reported simultaneously for one data set.Highlightsmean vector length is most sensitive for differentiating coupling strengthmodulation index is most robust to differences in data length, sampling rate and SNRphase-locking value and mean vector length cannot detect biphasic phase-amplitude coupling

scholarly journals Signal-to-noise ratio in the membrane potential of the owl's auditory coincidence detectors

2012 ◽  
Vol 108 (10) ◽  
pp. 2837-2845 ◽  
Author(s):  
Go Ashida ◽  
Kazuo Funabiki ◽  
Paula T. Kuokkanen ◽  
Richard Kempter ◽  
Catherine E. Carr
Keyword(s):  
Neural Circuit ◽  
Signal To Noise Ratio ◽  
Phase Locking ◽  
Low Frequency ◽  
Membrane Potentials ◽  
Signal To Noise ◽  
Theoretical Predictions ◽  
Noise Ratio ◽  
Band Limited

Owls use interaural time differences (ITDs) to locate a sound source. They compute ITD in a specialized neural circuit that consists of axonal delay lines from the cochlear nucleus magnocellularis (NM) and coincidence detectors in the nucleus laminaris (NL). Recent physiological recordings have shown that tonal stimuli induce oscillatory membrane potentials in NL neurons (Funabiki K, Ashida G, Konishi M. J Neurosci 31: 15245–15256, 2011). The amplitude of these oscillations varies with ITD and is strongly correlated to the firing rate. The oscillation, termed the sound analog potential, has the same frequency as the stimulus tone and is presumed to originate from phase-locked synaptic inputs from NM fibers. To investigate how these oscillatory membrane potentials are generated, we applied recently developed signal-to-noise ratio (SNR) analysis techniques (Kuokkanen PT, Wagner H, Ashida G, Carr CE, Kempter R. J Neurophysiol 104: 2274–2290, 2010) to the intracellular waveforms obtained in vivo. Our theoretical prediction of the band-limited SNRs agreed with experimental data for mid- to high-frequency (>2 kHz) NL neurons. For low-frequency (≤2 kHz) NL neurons, however, measured SNRs were lower than theoretical predictions. These results suggest that the number of independent NM fibers converging onto each NL neuron and/or the population-averaged degree of phase-locking of the NM fibers could be significantly smaller in the low-frequency NL region than estimated for higher best-frequency NL.

scholarly journals Beyond the low frequency fluctuations morning and evening differences in human brain

2019 ◽  
Author(s):  
Magdalena Fafrowicz ◽  
Bartosz Bohaterewicz ◽  
Anna Ceglarek ◽  
Monika Cichocka ◽  
Koryna Lewandowska ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Human Performance ◽  
Brain Activity ◽  
Activity Patterns ◽  
Low Frequency ◽  
Basic Mechanism ◽  
Time Of Day ◽  
Resting State Functional Connectivity ◽  
Circadian Typology

Human performance, alertness, and most biological functions express rhythmic fluctuations across a 24-hour-period. This phenomenon is believed to originate from differences in both circadian and homeostatic sleep-wake regulatory processes. Interactions between these processes result in time-of-day modulations of behavioral performance as well as brain activity patterns. Although the basic mechanism of the 24-hour clock is conserved across evolution, there are interindividual differences in the timing of sleep-wake cycles, subjective alertness and functioning throughout the day. The study of circadian typology differences has increased during the last few years, especially research on extreme chronotypes, which provide a unique way to investigate the effects of sleep-wake regulation on cerebral mechanisms. Using functional magnetic resonance imaging (fMRI), we assessed the influence of chronotype and time-of-day on resting-state functional connectivity. 29 extreme morning- and 34 evening-type participants underwent two fMRI sessions: about one hour after wake-up time (morning) and about ten hours after wake-up time (evening), scheduled according to their declared habitual sleep-wake pattern on a regular working day. Analysis of obtained neuroimaging data disclosed only an effect of time of day on resting-state functional connectivity; there were different patterns of functional connectivity between morning and evening sessions. The results of our study showed no differences between extreme morning-type and evening-type individuals. We demonstrate that circadian and homeostatic influences on the resting-state functional connectivity have a universal character, unaffected by circadian typology.

scholarly journals Active Optical Signal Conditioning and Monitoring System

2021 ◽  
Author(s):  
Kalipada Chatterjee ◽  
Subrat Sahu ◽  
Venugopal Arumuru ◽  
Rajan jha
Keyword(s):  
Real Time ◽  
Signal To Noise Ratio ◽  
Optical Signal ◽  
Wide Frequency Range ◽  
Optical Systems ◽  
Signal Conditioning ◽  
Time Modulation ◽  
Response Enhancement ◽  
Signal Monitoring ◽  
External Stimuli

Abstract An optical signal conditioning technique for dynamic modulation of signals and real-time monitoring of events is pivotal for developing various optical systems at micro/nano dimensions. The utilities of such technique include controllable signal enhancement and distinctive response towards external stimuli, with reconfigurable operational range. Here, we propose and demonstrate an optical technique based on the parallel integration of fiber modal interferometers for optical response enhancement and multi-signal monitoring. Overlap of the interferometers’ characteristic spectra facilitates controllable signal filtering, attenuation, and amplification of interferometer’s response towards dynamic field over wide frequency range of 1 Hz – 1 kHz. Signal to noise ratio (SNR) enhancement of 9 dB is achieved by applying 1 volt about the reference interferometer. The system enables real-time modulation of optical signals and multipoint signal monitoring using machine learning for various applications such as mechanical vibrations, acoustic fields, biological samples, fluid movement, and other similar dynamic fields.

scholarly journals Thermal tuning capabilities of semiconductor metasurface resonators

Nanophotonics ◽  
2018 ◽  
Vol 8 (2) ◽  
pp. 331-338 ◽  
Author(s):  
Tomer Lewi ◽  
Nikita A. Butakov ◽  
Jon A. Schuller
Keyword(s):  
Optical Switching ◽  
Near Infrared ◽  
Large Temperature ◽  
Infrared Range ◽  
Thermal Excitation ◽  
Optical Elements ◽  
Silicon And Germanium ◽  
Phase Amplitude ◽  
External Stimuli ◽  
Thermal Tuning

AbstractMetasurfaces exploit optical phase, amplitude, and polarization engineering at subwavelength dimensions to achieve unprecedented control of light. The realization of all dielectric metasurfaces has led to low-loss flat optical elements with functionalities that cannot be achieved with metal elements. However, to reach their ultimate potential, metasurfaces must move beyond static operation and incorporate active tunability and reconfigurable functions. The central challenge is achieving large tunability in subwavelength resonator elements, which requires large optical effects in response to external stimuli. Here we study the thermal tunability of high-index silicon and germanium semiconductor resonators over a large temperature range. We demonstrate thermal tuning of Mie resonances due to the normal positive thermo-optic effect (dn/dT>0) over a wide infrared range. We show that at higher temperatures and longer wavelengths, the sign of the thermo-optic coefficient is reversed, culminating in a negative induced index due to thermal excitation of free carriers. We also demonstrate the tuning of high-order Mie resonances by several linewidths with a temperature swing of ΔT<100 K. Finally, we exploit the large near-infrared thermo-optic coefficient in Si metasurfaces to realize optical switching and tunable metafilters.

scholarly journals On the methods for reactivation and replay analysis

2020 ◽  
Vol 375 (1799) ◽  
pp. 20190231 ◽  
Author(s):  
David Tingley ◽  
Adrien Peyrache
Keyword(s):  
Neural Activity ◽  
Temporal Structure ◽  
Activity Patterns ◽  
Large Body ◽  
Neural Data ◽  
History Of ◽  
Methodological Approaches ◽  
Neuronal Patterns ◽  
External Stimuli ◽  
The Brain

A major task in the history of neurophysiology has been to relate patterns of neural activity to ongoing external stimuli. More recently, this approach has branched out to relating current neural activity patterns to external stimuli or experiences that occurred in the past or future. Here, we aim to review the large body of methodological approaches used towards this goal, and to assess the assumptions each makes with reference to the statistics of neural data that are commonly observed. These methods primarily fall into two categories, those that quantify zero-lag relationships without examining temporal evolution, termed reactivation , and those that quantify the temporal structure of changing activity patterns, termed replay . However, no two studies use the exact same approach, which prevents an unbiased comparison between findings. These observations should instead be validated by multiple and, if possible, previously established tests. This will help the community to speak a common language and will eventually provide tools to study, more generally, the organization of neuronal patterns in the brain. This article is part of the Theo Murphy meeting issue ‘Memory reactivation: replaying events past, present and future’.

scholarly journals Higher-Order Cumulants Drive Neuronal Activity Patterns, Inducing UP-DOWN States in Neural Populations

Entropy ◽  
2020 ◽  
Vol 22 (4) ◽  
pp. 477 ◽  
Author(s):  
Roman Baravalle ◽  
Fernando Montani
Keyword(s):  
Probability Distributions ◽  
Activity Patterns ◽  
Gaussian Model ◽  
Random Variable ◽  
Neural System ◽  
Higher Order ◽  
Second Order ◽  
Specific Information ◽  
Neuronal Populations ◽  
Binder Cumulant

A major challenge in neuroscience is to understand the role of the higher-order correlations structure of neuronal populations. The dichotomized Gaussian model (DG) generates spike trains by means of thresholding a multivariate Gaussian random variable. The DG inputs are Gaussian distributed, and thus have no interactions beyond the second order in their inputs; however, they can induce higher-order correlations in the outputs. We propose a combination of analytical and numerical techniques to estimate higher-order, above the second, cumulants of the firing probability distributions. Our findings show that a large amount of pairwise interactions in the inputs can induce the system into two possible regimes, one with low activity (“DOWN state”) and another one with high activity (“UP state”), and the appearance of these states is due to a combination between the third- and fourth-order cumulant. This could be part of a mechanism that would help the neural code to upgrade specific information about the stimuli, motivating us to examine the behavior of the critical fluctuations through the Binder cumulant close to the critical point. We show, using the Binder cumulant, that higher-order correlations in the outputs generate a critical neural system that portrays a second-order phase transition.

Enhancement of signal-to-noise ratio of ultracold polar NaCs molecular spectra by phase locking detection

2017 ◽  
Vol 26 (12) ◽  
pp. 123701 ◽  
Author(s):  
Wenhao Wang ◽  
Wenliang Liu ◽  
Jizhou Wu ◽  
Yuqing Li ◽  
Xiaofeng Wang ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Phase Locking ◽  
Molecular Spectra ◽  
Signal To Noise ◽  
Noise Ratio
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