Synaptic Noise and Physiological Coupling Generate High-Frequency Oscillations in a Hippocampal Computational Model

There is great interest in the role of coherent oscillations in the brain. In some cases, high-frequency oscillations (HFOs) are integral to normal brain function, whereas at other times they are implicated as markers of epileptic tissue. Mechanisms underlying HFO generation, especially in abnormal tissue, are not well understood. Using a physiological computer model of hippocampus, we investigate random synaptic activity (noise) as a potential initiator of HFOs. We explore parameters necessary to produce these oscillations and quantify the response using the tools of stochastic resonance (SR) and coherence resonance (CR). As predicted by SR, when noise was added to the network the model was able to detect a subthreshold periodic signal. Addition of basket cell interneurons produced two novel SR effects: 1) improved signal detection at low noise levels and 2) formation of coherent oscillations at high noise that were entrained to harmonics of the signal frequency. The periodic signal was then removed to study oscillations generated only by noise. The combined effects of network coupling and synaptic noise produced coherent, periodic oscillations within the network, an example of CR. Our results show that, under normal coupling conditions, synaptic noise was able to produce gamma (30–100 Hz) frequency oscillations. Synaptic noise generated HFOs in the ripple range (100–200 Hz) when the network had parameters similar to pathological findings in epilepsy: increased gap junctions or recurrent synaptic connections, loss of inhibitory interneurons such as basket cells, and increased synaptic noise. The model parameters that generated these effects are comparable with published experimental data. We propose that increased synaptic noise and physiological coupling mechanisms are sufficient to generate gamma oscillations and that pathologic changes in noise and coupling similar to those in epilepsy can produce abnormal ripples.

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Network and synaptic mechanisms underlying high frequency oscillations in the rat and cat olfactory bulb under ketamine-xylazine anesthesia

10.1101/2020.07.23.217604 ◽

2020 ◽

Author(s):

Władysław Średniawa ◽

Jacek Wróbel ◽

Ewa Kublik ◽

Daniel Krzysztof Wójcik ◽

Miles Adrian Whittington ◽

...

Keyword(s):

Olfactory Bulb ◽

High Frequency ◽

Piriform Cortex ◽

Field Potential ◽

Gamma Oscillations ◽

Synaptic Activity ◽

Surgical Removal ◽

Nasal Airflow ◽

High Frequency Oscillations ◽

Subcortical Regions

AbstractHigh frequency oscillations (HFO) are receiving increased attention for their role in health and disease. Ketamine-dependent HFO have been identified in cortical and subcortical regions in rodents, however, the mechanisms underlying their generation and whether they occur in higher mammals is unclear. Here, we show under ketamine-xylazine anesthesia, classical gamma oscillations diminish and a prominent > 80 Hz oscillation emerges in the olfactory bulb of rats and cats. In cats negligible HFO was observed in the thamalus and visual cortex indicating the OB was a suitable site for further investigation. Simultaneous local field potential and thermocouple recordings demonstrated HFO was dependent on nasal airflow. Silicon probe mapping studies spanning almost the entire dorsal ventral aspect of the OB revealed this rhythm was strongest in ventral areas of the bulb and associated with microcurrent sources about the mitral layer. Pharmacological microinfusion studies revealed HFO was dependent on excitatory-inhibitory synaptic activity, but not gap junctions. Finally, we showed HFO was preserved despite surgical removal of the piriform cortex. We conclude that ketamine-dependent HFO in the OB are driven by nasal airflow and local dendrodendritic interactions. The relevance of our findings to ketamine’s model of psychosis in awake state are also discussed.

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Phase Coupled Firing of Prefrontal Parvalbumin Interneuron With High Frequency Oscillations

Frontiers in Cellular Neuroscience ◽

10.3389/fncel.2020.610741 ◽

2020 ◽

Vol 14 ◽

Author(s):

Yanting Yao ◽

Mengmeng Wu ◽

Lina Wang ◽

Longnian Lin ◽

Jiamin Xu

Keyword(s):

High Frequency ◽

Pyramidal Neurons ◽

Temporal Dynamics ◽

Gamma Oscillations ◽

Cognitive Behaviors ◽

Firing Rates ◽

High Frequency Oscillations ◽

Electrophysiological Recordings ◽

Parvalbumin Interneuron

The prefrontal cortex (PFC) plays a central role in executive functions and inhibitory control over many cognitive behaviors. Dynamic changes in local field potentials (LFPs), such as gamma oscillation, have been hypothesized to be important for attentive behaviors and modulated by local interneurons such as parvalbumin (PV) cells. However, the precise relationships between the firing patterns of PV interneurons and temporal dynamics of PFC activities remains elusive. In this study, by combining in vivo electrophysiological recordings with optogenetics, we investigated the activities of prefrontal PV interneurons and categorized them into three subtypes based on their distinct firing rates under different behavioral states. Interestingly, all the three subtypes of interneurons showed strong phase-locked firing to cortical high frequency oscillations (HFOs), but not to theta or gamma oscillations, despite of behavior states. Moreover, we showed that sustained optogenetic stimulation (over a period of 10 s) of PV interneurons can consequently modulate the activities of local pyramidal neurons. Interestingly, such optogenetic manipulations only showed moderate effects on LFPs in the PFC. We conclude that prefrontal PV interneurons are consist of several subclasses of cells with distinct state-dependent modulation of firing rates, selectively coupled to HFOs.

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High-frequency oscillations in scalp EEG mirror seizure frequency in pediatric focal epilepsy

Scientific Reports ◽

10.1038/s41598-019-52700-w ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 4

Author(s):

Ece Boran ◽

Johannes Sarnthein ◽

Niklaus Krayenbühl ◽

Georgia Ramantani ◽

Tommaso Fedele

Keyword(s):

Seizure Frequency ◽

Epilepsy Surgery ◽

High Frequency ◽

Focal Epilepsy ◽

Low Noise ◽

Drug Resistant ◽

Scalp Eeg ◽

High Frequency Oscillations ◽

Custom Made ◽

Active Epilepsy

Abstract High-frequency oscillations (HFO) are promising EEG biomarkers of epileptogenicity. While the evidence supporting their significance derives mainly from invasive recordings, recent studies have extended these observations to HFO recorded in the widely accessible scalp EEG. Here, we investigated whether scalp HFO in drug-resistant focal epilepsy correspond to epilepsy severity and how they are affected by surgical therapy. In eleven children with drug-resistant focal epilepsy that underwent epilepsy surgery, we prospectively recorded pre- and postsurgical scalp EEG with a custom-made low-noise amplifier (LNA). In four of these children, we also recorded intraoperative electrocorticography (ECoG). To detect clinically relevant HFO, we applied a previously validated automated detector. Scalp HFO rates showed a significant positive correlation with seizure frequency (R2 = 0.80, p < 0.001). Overall, scalp HFO rates were higher in patients with active epilepsy (19 recordings, p = 0.0066, PPV = 86%, NPV = 80%, accuracy = 84% CI [62% 94%]) and decreased following successful epilepsy surgery. The location of the highest HFO rates in scalp EEG matched the location of the highest HFO rates in ECoG. This study is the first step towards using non-invasively recorded scalp HFO to monitor disease severity in patients affected by epilepsy.

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Pathological high frequency oscillations associate with increased GABA synaptic activity in pediatric epilepsy surgery patients

Neurobiology of Disease ◽

10.1016/j.nbd.2019.104618 ◽

2020 ◽

Vol 134 ◽

pp. 104618 ◽

Cited By ~ 4

Author(s):

Carlos Cepeda ◽

Simon Levinson ◽

Hiroki Nariai ◽

Vannah-Wila Yazon ◽

Conny Tran ◽

...

Keyword(s):

Epilepsy Surgery ◽

High Frequency ◽

Synaptic Activity ◽

Pediatric Epilepsy ◽

High Frequency Oscillations ◽

Pediatric Epilepsy Surgery

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MODELING OF NOISE BEHAVIOR OF GRADED BAND GAP CHANNEL MOSFET AT GHz FREQUENCIES

Fluctuation and Noise Letters ◽

10.1142/s0219477507004185 ◽

2007 ◽

Vol 07 (04) ◽

pp. L507-L517

Author(s):

ALI ABOU-ELNOUR ◽

OSSAMA ABO-ELNOR ◽

HAMDY ABDELHAMEED ◽

ADEL EL-HENAWY

Keyword(s):

Band Gap ◽

High Frequency ◽

Noise Figure ◽

Low Noise ◽

Noise Model ◽

Superior Performance ◽

Model Parameters ◽

Short Channel ◽

Suggested Structure ◽

Graded Band Gap

A novel graded band gap channel Si - SiGe MOSFET structure has been suggested and its characteristics have been investigated. The investigations indicated that the suggested structure reduces the short-channel effects, increases the cut-off frequency, and hence makes its usage at high frequency and Low noise applications possible. To show the superior performance of the suggested structure at GHz frequencies, and as an example, the noise behavior of the structure is determined. First the device noise model parameters are calculated from D.C. and A.C. characteristics. The extracted noise model parameters are then used to determine the minimum noise figure at GHz frequencies. The effects of the different device parameters on the noise performance are determined. Finally, the results are compared with those of conventional MOSFET structure to show the superior performance of graded band gap Si - SiGe MOSFETs at high frequency ranges.

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Emergence of Narrowband High Frequency Oscillations from Asynchronous, Uncoupled Neural Firing

International Journal of Neural Systems ◽

10.1142/s0129065716500490 ◽

2016 ◽

Vol 27 (01) ◽

pp. 1650049 ◽

Cited By ~ 5

Author(s):

Stephen V. Gliske ◽

William C. Stacey ◽

Eugene Lim ◽

Katherine A. Holman ◽

Christian G. Fink

Keyword(s):

High Frequency ◽

Feedback Inhibition ◽

Experimental Studies ◽

Field Potential ◽

Epileptic Seizures ◽

Spike Timing ◽

Normal Brain ◽

Neural Firing ◽

Similar Frequency ◽

High Frequency Oscillations

Previous experimental studies have demonstrated the emergence of narrowband local field potential oscillations during epileptic seizures in which the underlying neural activity appears to be completely asynchronous. We derive a mathematical model explaining how this counterintuitive phenomenon may occur, showing that a population of independent, completely asynchronous neurons may produce narrowband oscillations if each neuron fires quasi-periodically, without requiring any intrinsic oscillatory cells or feedback inhibition. This quasi-periodicity can occur through cells with similar frequency–current ([Formula: see text]–[Formula: see text]) curves receiving a similar, high amount of uncorrelated synaptic noise. Thus, this source of oscillatory behavior is distinct from the usual cases (pacemaker cells entraining a network, or oscillations being an inherent property of the network structure), as it requires no oscillatory drive nor any specific network or cellular properties other than cells that repetitively fire with continual stimulus. We also deduce bounds on the degree of variability in neural spike-timing which will permit the emergence of such oscillations, both for action potential- and postsynaptic potential-dominated LFPs. These results suggest that even an uncoupled network may generate collective rhythms, implying that the breakdown of inhibition and high synaptic input often observed during epileptic seizures may generate narrowband oscillations. We propose that this mechanism may explain why so many disparate epileptic and normal brain mechanisms can produce similar high frequency oscillations.

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Network and synaptic mechanisms underlying high frequency oscillations in the rat and cat olfactory bulb under ketamine-xylazine anesthesia

Scientific Reports ◽

10.1038/s41598-021-85705-5 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Władysław Średniawa ◽

Jacek Wróbel ◽

Ewa Kublik ◽

Daniel Krzysztof Wójcik ◽

Miles Adrian Whittington ◽

...

Keyword(s):

Olfactory Bulb ◽

High Frequency ◽

Piriform Cortex ◽

Surgical Excision ◽

Synaptic Activity ◽

High Frequency Oscillations ◽

Gamma Power ◽

Subcortical Regions ◽

Inhibitory Interactions ◽

Synaptic Mechanisms

AbstractWake-related ketamine-dependent high frequency oscillations (HFO) can be recorded in local field potentials (LFP) from cortical and subcortical regions in rodents. The mechanisms underlying their generation and occurrence in higher mammals are unclear. Unfortunately, anesthetic doses of pure ketamine attenuate HFO, which has precluded their investigation under anesthesia. Here, we show ketamine-xylazine (KX) anesthesia is associated with a prominent 80–130 Hz rhythm in the olfactory bulb (OB) of rats, whereas 30–65 Hz gamma power is diminished. Simultaneous LFP and thermocouple recordings revealed the 80–130 Hz rhythm was dependent on nasal respiration. This rhythm persisted despite surgical excision of the piriform cortex. Silicon probes spanning the dorsoventral aspect of the OB revealed this rhythm was strongest in ventral areas and associated with microcurrent sources about the mitral layer. Pharmacological microinfusion studies revealed dependency on excitatory-inhibitory synaptic activity, but not gap junctions. Finally, a similar rhythm occurred in the OB of KX-anesthetized cats, which shared key features with our rodent studies. We conclude that the activity we report here is driven by nasal airflow, local excitatory-inhibitory interactions, and conserved in higher mammals. Additionally, KX anesthesia is a convenient model to investigate further the mechanisms underlying wake-related ketamine-dependent HFO.

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Network recruitment to coherent oscillations in a hippocampal computer model

Journal of Neurophysiology ◽

10.1152/jn.00643.2010 ◽

2011 ◽

Vol 105 (4) ◽

pp. 1464-1481 ◽

Cited By ~ 14

Author(s):

William C. Stacey ◽

Abba Krieger ◽

Brian Litt

Keyword(s):

Brain Activity ◽

Synaptic Activity ◽

Therapeutic Approaches ◽

Physiological Noise ◽

Neuronal Populations ◽

High Frequency Oscillations ◽

Synaptic Noise ◽

Human Disorders ◽

Cell Firing ◽

Network Synchrony

Coherent neural oscillations represent transient synchronization of local neuronal populations in both normal and pathological brain activity. These oscillations occur at or above gamma frequencies (>30 Hz) and often are propagated to neighboring tissue under circumstances that are both normal and abnormal, such as gamma binding or seizures. The mechanisms that generate and propagate these oscillations are poorly understood. In the present study we demonstrate, via a detailed computational model, a mechanism whereby physiological noise and coupling initiate oscillations and then recruit neighboring tissue, in a manner well described by a combination of stochastic resonance and coherence resonance. We develop a novel statistical method to quantify recruitment using several measures of network synchrony. This measurement demonstrates that oscillations spread via preexisting network connections such as interneuronal connections, recurrent synapses, and gap junctions, provided that neighboring cells also receive sufficient inputs in the form of random synaptic noise. “Epileptic” high-frequency oscillations (HFOs), produced by pathologies such as increased synaptic activity and recurrent connections, were superior at recruiting neighboring tissue. “Normal” HFOs, associated with fast firing of inhibitory cells and sparse pyramidal cell firing, tended to suppress surrounding cells and showed very limited ability to recruit. These findings point to synaptic noise and physiological coupling as important targets for understanding the generation and propagation of both normal and pathological HFOs, suggesting potential new diagnostic and therapeutic approaches to human disorders such as epilepsy.

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High frequency oscillations in epileptic and non-epileptic human hippocampus during a cognitive task

Scientific Reports ◽

10.1038/s41598-020-74306-3 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Martin Pail ◽

Jan Cimbálník ◽

Robert Roman ◽

Pavel Daniel ◽

Daniel J. Shaw ◽

...

Keyword(s):

High Frequency ◽

Focal Epilepsy ◽

Cognitive Task ◽

Normal Brain ◽

High Frequency Oscillations ◽

Depth Electrodes ◽

Hippocampal Activity ◽

Normal Brain Function ◽

The Impact ◽

Resting Period

Abstract Hippocampal high-frequency electrographic activity (HFOs) represents one of the major discoveries not only in epilepsy research but also in cognitive science over the past few decades. A fundamental challenge, however, has been the fact that physiological HFOs associated with normal brain function overlap in frequency with pathological HFOs. We investigated the impact of a cognitive task on HFOs with the aim of improving differentiation between epileptic and non-epileptic hippocampi in humans. Hippocampal activity was recorded with depth electrodes in 15 patients with focal epilepsy during a resting period and subsequently during a cognitive task. HFOs in ripple and fast ripple frequency ranges were evaluated in both conditions, and their rate, spectral entropy, relative amplitude and duration were compared in epileptic and non-epileptic hippocampi. The similarity of HFOs properties recorded at rest in epileptic and non-epileptic hippocampi suggests that they cannot be used alone to distinguish between hippocampi. However, both ripples and fast ripples were observed with higher rates, higher relative amplitudes and longer durations at rest as well as during a cognitive task in epileptic compared with non-epileptic hippocampi. Moreover, during a cognitive task, significant reductions of HFOs rates were found in epileptic hippocampi. These reductions were not observed in non-epileptic hippocampi. Our results indicate that although both hippocampi generate HFOs with similar features that probably reflect non-pathological phenomena, it is possible to differentiate between epileptic and non-epileptic hippocampi using a simple odd-ball task.

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Smell-induced gamma oscillations in human olfactory cortex are required for accurate perception of odor identity

PLoS Biology ◽

10.1371/journal.pbio.3001509 ◽

2022 ◽

Vol 20 (1) ◽

pp. e3001509

Author(s):

Qiaohan Yang ◽

Guangyu Zhou ◽

Torben Noto ◽

Jessica W. Templer ◽

Stephan U. Schuele ◽

...

Keyword(s):

High Frequency ◽

Olfactory System ◽

Piriform Cortex ◽

Low Frequency ◽

Gamma Oscillations ◽

Odor Identification ◽

Identification Accuracy ◽

Electrophysiological Response ◽

Electrophysiological Properties ◽

High Frequency Oscillations

Studies of neuronal oscillations have contributed substantial insight into the mechanisms of visual, auditory, and somatosensory perception. However, progress in such research in the human olfactory system has lagged behind. As a result, the electrophysiological properties of the human olfactory system are poorly understood, and, in particular, whether stimulus-driven high-frequency oscillations play a role in odor processing is unknown. Here, we used direct intracranial recordings from human piriform cortex during an odor identification task to show that 3 key oscillatory rhythms are an integral part of the human olfactory cortical response to smell: Odor induces theta, beta, and gamma rhythms in human piriform cortex. We further show that these rhythms have distinct relationships with perceptual behavior. Odor-elicited gamma oscillations occur only during trials in which the odor is accurately perceived, and features of gamma oscillations predict odor identification accuracy, suggesting that they are critical for odor identity perception in humans. We also found that the amplitude of high-frequency oscillations is organized by the phase of low-frequency signals shortly following sniff onset, only when odor is present. Our findings reinforce previous work on theta oscillations, suggest that gamma oscillations in human piriform cortex are important for perception of odor identity, and constitute a robust identification of the characteristic electrophysiological response to smell in the human brain. Future work will determine whether the distinct oscillations we identified reflect distinct perceptual features of odor stimuli.

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