scholarly journals Periodic Forcing of Inhibition-Stabilized Networks: Nonlinear Resonances and Phase-Amplitude Coupling

2015 ◽  
Vol 27 (12) ◽  
pp. 2477-2509 ◽  
Author(s):  
Romain Veltz ◽  
Terrence J. Sejnowski
Keyword(s):  
Pyramidal Neurons ◽  
Phase Coupling ◽  
Periodic Forcing ◽  
Circuit Element ◽  
Damped Oscillations ◽  
Inhibitory Population ◽  
Multiple Frequencies ◽  
Phase Amplitude ◽  
Periodic Inputs ◽  
Phase Phase

Inhibition-stabilized networks (ISNs) are neural architectures with strong positive feedback among pyramidal neurons balanced by strong negative feedback from inhibitory interneurons, a circuit element found in the hippocampus and the primary visual cortex. In their working regime, ISNs produce damped oscillations in the [Formula: see text]-range in response to inputs to the inhibitory population. In order to understand the properties of interconnected ISNs, we investigated periodic forcing of ISNs. We show that ISNs can be excited over a range of frequencies and derive properties of the resonance peaks. In particular, we studied the phase-locked solutions, the torus solutions, and the resonance peaks. Periodically forced ISNs respond with (possibly multistable) phase-locked activity, whereas networks with sustained intrinsic oscillations respond more dynamically to periodic inputs with tori. Hence, the dynamics are surprisingly rich, and phase effects alone do not adequately describe the network response. This strengthens the importance of phase-amplitude coupling as opposed to phase-phase coupling in providing multiple frequencies for multiplexing and routing information.

scholarly journals On cross-frequency phase-phase coupling between theta and gamma oscillations in the hippocampus

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Robson Scheffer-Teixeira ◽  
Adriano BL Tort
Keyword(s):  
Phase Locking ◽  
Gamma Oscillations ◽  
Linear Phase ◽  
Phase Coupling ◽  
Neuronal Coding ◽  
Theoretical Support ◽  
Hippocampal Activity ◽  
Phase Amplitude ◽  
Phase Phase ◽  
Frequency Phase

Phase-amplitude coupling between theta and multiple gamma sub-bands is a hallmark of hippocampal activity and believed to take part in information routing. More recently, theta and gamma oscillations were also reported to exhibit phase-phase coupling, or n:m phase-locking, suggesting an important mechanism of neuronal coding that has long received theoretical support. However, by analyzing simulated and actual LFPs, here we question the existence of theta-gamma phase-phase coupling in the rat hippocampus. We show that the quasi-linear phase shifts introduced by filtering lead to spurious coupling levels in both white noise and hippocampal LFPs, which highly depend on epoch length, and that significant coupling may be falsely detected when employing improper surrogate methods. We also show that waveform asymmetry and frequency harmonics may generate artifactual n:m phase-locking. Studies investigating phase-phase coupling should rely on appropriate statistical controls and be aware of confounding factors; otherwise, they could easily fall into analysis pitfalls.

scholarly journals Lack of evidence for cross-frequency phase-phase coupling between theta and gamma oscillations in the hippocampus

2016 ◽  
Author(s):  
Robson Scheffer-Teixeira ◽  
Adriano BL Tort
Keyword(s):  
Phase Locking ◽  
Gamma Oscillations ◽  
Actual Data ◽  
Gamma Phase ◽  
Phase Coupling ◽  
Neuronal Coding ◽  
Theoretical Support ◽  
Hippocampal Activity ◽  
Phase Amplitude ◽  
Phase Phase

AbstractPhase-amplitude coupling between theta and multiple gamma sub-bands hallmarks hippocampal activity and is believed to take part in information routing. More recently, theta and gamma oscillations were also reported to exhibit reliable phase-phase coupling, or n:m phase-locking. The existence of n:m phase-locking suggests an important mechanism of neuronal coding that has long received theoretical support. However, here we show that n:m phase-locking (1) is much lower than previously reported, (2) highly depends on epoch length, (3) does not statistically differ from chance (when employing proper surrogate methods), and that (4) filtered white noise has similar n:m scores as actual data. Moreover, (5) the diagonal stripes in theta-gamma phase-phase histograms of actual data can be explained by theta harmonics. These results point to lack of theta-gamma phase-phase coupling in the hippocampus, and suggest that studies investigating n:m phase-locking should rely on appropriate statistical controls, otherwise they could easily fall into analysis pitfalls.

scholarly journals Seasonal synchronization of foodborne outbreaks in the United States, 1996–2017

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Ryan B. Simpson ◽  
Bingjie Zhou ◽  
Elena N. Naumova
Keyword(s):  
Food Systems ◽  
Negative Binomial ◽  
Phase Synchronization ◽  
Dynamic Networks ◽  
The United States ◽  
Foodborne Outbreaks ◽  
Seasonal Synchronization ◽  
Phase Amplitude ◽  
And Control ◽  
Phase Phase

Abstract Modern food systems represent complex dynamic networks vulnerable to foodborne infectious outbreaks difficult to track and control. Seasonal co-occurrences (alignment of seasonal peaks) and synchronization (similarity of seasonal patterns) of infections are noted, yet rarely explored due to their complexity and methodological limitations. We proposed a systematic approach to evaluate the co-occurrence of seasonal peaks using a combination of L-moments, seasonality characteristics such as the timing (phase) and intensity (amplitude) of peaks, and three metrics of serial, phase-phase, and phase-amplitude synchronization. We used public records on counts of nine foodborne infections abstracted from CDC’s FoodNet Fast online platform for the US and ten representative states from 1996 to 2017 (264 months). Based on annualized and trend-adjusted Negative Binomial Harmonic Regression (NBHR) models augmented with the δ-method, we determined that seasonal peaks of Campylobacter, Salmonella, and Shiga toxin-producing Escherichia Coli (STEC) were tightly clustered in late-July at the national and state levels. Phase-phase synchronization was observed between Cryptosporidium and Shigella, Listeria, and Salmonella (ρ = 0.51, 0.51, 0.46; p < 0.04). Later peak timing of STEC was associated with greater amplitude nationally (ρ = 0.50, p = 0.02) indicating phase-amplitude synchronization. Understanding of disease seasonal synchronization is essential for developing reliable outbreak forecasts and informing stakeholders on mitigation and preventive measures.

scholarly journals Gamma Entrainment Improves Synchronization Deficits in Dementia Patients

2021 ◽  
Author(s):  
Mojtaba Lahijanian ◽  
Hamid Aghajan ◽  
Zahra Vahabi ◽  
Arshia Afzal
Keyword(s):  
Oscillatory Activity ◽  
Therapeutic Effects ◽  
Phase Coupling ◽  
Non Invasive ◽  
Temporal Phase ◽  
Dementia Patients ◽  
Frequency Coupling ◽  
Phase Amplitude ◽  
Cross Frequency Coupling

AbstractNon-invasive gamma entrainment has shown promising results in alleviating cognitive symptoms of Alzheimer’s disease in mice and humans. In this study, we examine improvements in the synchronization characteristics of the brain’s oscillations induced by 40Hz auditory stimulation based on electroencephalography data recorded from a group of dementia patients. We observed that when the quality of entrainment surpasses a certain level, several indicators of brain synchronization significantly improve. Specifically, the entrained oscillatory activity maintains temporal phase stability in the frontal, parietal, and occipital regions, and persistent spatial phase coupling between them. In addition, notable theta-gamma phase-amplitude coupling is observed in these areas. Interestingly, a high theta power at rest predicts the quality of entrainment. We identify differentiating attributes of temporal/spatial synchronization and cross-frequency coupling in the data of two groups with entrained and non-entrained responses which point to enhanced network synchronization caused by entrainment and can explain its potential therapeutic effects.

scholarly journals Topology, cross-frequency, and same-frequency band interactions shape the generation of phase-amplitude coupling in a neural mass model of a cortical column

2015 ◽  
Author(s):  
Roberto C. Sotero
Keyword(s):  
Frequency Band ◽  
Clustering Coefficient ◽  
Neural Mass Model ◽  
Cortical Column ◽  
Phase Coupling ◽  
Mass Model ◽  
Important Indicator ◽  
Neuronal Populations ◽  
Neural Mass ◽  
Phase Amplitude

AbstractPhase-amplitude coupling (PAC), a type of cross-frequency coupling (CFC) where the phase of a low-frequency rhythm modulates the amplitude of a higher frequency, is becoming an important indicator of information transmission in the brain. However, the neurobiological mechanisms underlying its generation remain undetermined. A realistic, yet tractable computational model of the phenomenon is thus needed. Here we propose a neural mass model of a cortical column, comprising fourteen neuronal populations distributed across four layers (L2/3, L4, L5 and L6). The conditional transfer entropies (cTE) from the phases to the amplitudes of the generated oscillations are estimated by means of the conditional mutual information. This approach provides information regarding directionality by distinguishing PAC from APC (amplitude-phase coupling), i.e. the information transfer from amplitudes to phases, and can be used to estimate other types of CFC such as amplitude-amplitude coupling (AAC) and phase-phase coupling (PPC). While experiments often only focus on one or two PAC combinations (e.g., theta-gamma or alpha-gamma), we found that a cortical column can simultaneously generate almost all possible PAC combinations, depending on connectivity parameters, time constants, and external inputs. We found that the strength of PAC between two populations was strongly correlated with the strength of the effective connections between them and, on average, did not depend upon the presence or absence of a direct (anatomical) connection. When considering a cortical column circuit as a complex network, we found that neuronal populations making indirect PAC connections had, on average, higher local clustering coefficient, efficiency, and betweenness centrality than populations making direct connections and populations not involved in PAC connections. This suggests that their interactions were more efficient when transmitting information. Since more than 60% of the obtained interactions represented indirect connections, our results highlight the importance of the topology of cortical circuits for the generation on of the PAC phenomenon. Finally, our results demonstrated that indirect PAC interactions can be explained by a cascade of direct CFC and same-frequency band interactions, suggesting that PAC analysis of experimental data should be accompanied by the estimation of other types of frequency interactions for an integrative understanding of the phenomenon.

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