Cortical high gamma network oscillations and connectivity: a translational index for antipsychotics to normalize aberrant neurophysiological activity

Ahnaou, A.; Huysmans, H.; Casteele, Tom Van de; Drinkenburg, W.H.I.M.

doi:10.1038/s41398-017-0002-9

Cited by 53 publications

(42 citation statements)

References 103 publications

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“…Additionally, antipsychotics could have had an effect on the low-frequency alpha and higher gamma network. 81 Dominance of theta and delta activity during olanzapine use was observed in a previous study. 82 Because patients in the present study were administered several antipsychotics, confounding pharmacological effects might have affected the results; the effects of specific drugs are, however, difficult to estimate.…”

Section: Discussionmentioning

confidence: 53%

Unsuccessful reduction of high‐frequency alpha activity during cognitive activation in schizophrenia

Jang

Jung

et al. 2019

Psychiatry Clin Neurosci

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Aims: Electroencephalogram (EEG) alpha activity during resting state reflects the 'readiness' of an individual to respond to the environment; this includes the performance of cognitive processes. Alpha activity is reported to be attenuated in schizophrenia (SCZ). Understanding the interaction between alpha activity during rest and when cognitively engaged may provide insights into the neural circuitry, which is dysfunctional in SCZ. This study investigated the changes of alpha activity between resting state and cognitive engagement in SCZ patients.Methods: Thirty-four SCZ patients and 29 healthy controls (HC) were recruited. EEG was performed in the resting state and during an auditory P300 task. All experimental procedures followed the relevant institutional guidelines and regulations.Results: In SCZ, high-frequency alpha activity was reduced in the resting state. High-frequency alpha source density was decreased in both the resting-state and a P300 task condition in patients, compared to HC. HC, but not SCZ patients, showed a reduction in high-frequency alpha source density during the P300 task compared to the resting state. The negative correlation between high-frequency alpha source density in the resting state and positive symptoms was significant.Conclusions: High-frequency alpha activity in SCZ patients and its unsuccessful reduction during cognitive processing may be biological markers of SCZ.

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Section: Discussionmentioning

confidence: 53%

Unsuccessful reduction of high‐frequency alpha activity during cognitive activation in schizophrenia

Jang

Jung

et al. 2019

Psychiatry Clin Neurosci

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“…Wavelets express a signal as a linear combination of a distinct set of functions, obtained by shifting and scaling a single function (mother wavelet). Although the preprocessed MEG signals were in 1 kHz sampling frequency range, functional brain oscillations are believed to exist up to the high-gamma frequency range (<∼ 125 Hz) (Ahnaou et al, 2017). Thus, we employed the Daubechies (db)-4 wavelet with a 7 level decomposition to perform discrete wavelet transform (DWT) for denoising and decomposing the MEG signals to specific neural oscillations.…”

Section: Wavelet Analysismentioning

confidence: 99%

Decoding Imagined and Spoken Phrases From Non-invasive Neural (MEG) Signals

2020

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Speech production is a hierarchical mechanism involving the synchronization of the brain and the oral articulators, where the intention of linguistic concepts is transformed into meaningful sounds. Individuals with locked-in syndrome (fully paralyzed but aware) lose their motor ability completely including articulation and even eyeball movement. The neural pathway may be the only option to resume a certain level of communication for these patients. Current brain-computer interfaces (BCIs) use patients' visual and attentional correlates to build communication, resulting in a slow communication rate (a few words per minute). Direct decoding of imagined speech from the neural signals (and then driving a speech synthesizer) has the potential for a higher communication rate. In this study, we investigated the decoding of five imagined and spoken phrases from single-trial, non-invasive magnetoencephalography (MEG) signals collected from eight adult subjects. Two machine learning algorithms were used. One was an artificial neural network (ANN) with statistical features as the baseline approach. The other was convolutional neural networks (CNNs) applied on the spatial, spectral and temporal features extracted from the MEG signals. Experimental results indicated the possibility to decode imagined and spoken phrases directly from neuromagnetic signals. CNNs were found to be highly effective with an average decoding accuracy of up to 93% for the imagined and 96% for the spoken phrases.

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“…Since gamma oscillations are known to be associated with selective attention, memory formation, and sensory perception (Buzsáki and Draguhn, 2004;Colgin, 2016;Colgin and Moser, 2010;Paulsen and Moser, 1998;Uhlhaas and Singer, 2010), it is not surprising that disturbances in gamma oscillations are observed in many brain disorders. This includes AD (Hidisoglu et al, 2018;Hollnagel et al, 2019), schizophrenia (Hamm et al, 2017), ischemia (Barth and Mody, 2011), psychosis (Ahnaou et al, 2017), and depression (Fitzgerald and Watson, 2018). The question remains in these diseases, whether alterations of gamma oscillations are a by-product or are contributing to cognitive impairments.…”

Section: Gamma Oscillations and Brain Disordersmentioning

confidence: 99%

Mild metabolic stress is sufficient to disturb the formation of pyramidal cell ensembles during gamma oscillations

Elzoheiry

Lewen

Schneider

et al. 2019

J Cereb Blood Flow Metab

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Disturbances of cognitive functions occur rapidly during acute metabolic stress. However, the underlying mechanisms are not fully understood. Cortical gamma oscillations (30–100 Hz) emerging from precise synaptic transmission between excitatory principal neurons and inhibitory interneurons, such as fast-spiking GABAergic basket cells, are associated with higher brain functions, like sensory perception, selective attention and memory formation. We investigated the alterations of cholinergic gamma oscillations at the level of neuronal ensembles in the CA3 region of rat hippocampal slice cultures. We combined electrophysiology, calcium imaging (CamKII.GCaMP6f) and mild metabolic stress that was induced by rotenone, a lipophilic and highly selective inhibitor of complex I in the respiratory chain of mitochondria. The detected pyramidal cell ensembles showing repetitive patterns of activity were highly sensitive to mild metabolic stress. Whereas such synchronised multicellular activity diminished, the overall activity of individual pyramidal cells was unaffected. Additionally, mild metabolic stress had no effect on the rate of action potential generation in fast-spiking neural units. However, the partial disinhibition of slow-spiking neural units suggests that disturbances of ensemble formation likely result from alterations in synaptic inhibition. Our study bridges disturbances on the (multi-)cellular and network level to putative cognitive impairment on the system level.

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Cortical high gamma network oscillations and connectivity: a translational index for antipsychotics to normalize aberrant neurophysiological activity

Cited by 53 publications

References 103 publications

Unsuccessful reduction of high‐frequency alpha activity during cognitive activation in schizophrenia

Unsuccessful reduction of high‐frequency alpha activity during cognitive activation in schizophrenia

Decoding Imagined and Spoken Phrases From Non-invasive Neural (MEG) Signals

Mild metabolic stress is sufficient to disturb the formation of pyramidal cell ensembles during gamma oscillations

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