scholarly journals Neural signatures of loss of consciousness and its recovery by thalamic stimulation

2019 ◽  
Author(s):  
Jacob A. Donoghue ◽  
André M. Bastos ◽  
Jorge Yanar ◽  
Simon Kornblith ◽  
Meredith Mahnke ◽  
...  
Keyword(s):  
General Anesthesia ◽  
Local Field ◽  
Neural Activity ◽  
High Frequency ◽  
Loss Of Consciousness ◽  
Field Potentials ◽  
Thalamic Stimulation ◽  
Cortical Rhythms ◽  
Up States ◽  
Slow Frequency

AbstractWe know that general anesthesia produces unconsciousness but not quite how. We recorded neural activity from the frontal, parietal, and temporal cortices and thalamus while maintaining unconsciousness in non-human primates (NHPs) with propofol. Unconsciousness was marked by slow frequency (∼1 Hz) oscillations in local field potentials, entraining local spiking to Up states alternating with Down states of little spiking, and decreased higher frequency (>4 Hz) coherence. The thalamus contributed to cortical rhythms. Its stimulation “awakened” anesthetized NHPs and reversed the electrophysiologic features of unconsciousness. Unconsciousness thus resulted from slow frequency hypersynchrony and loss of high-frequency dynamics, partly mediated by the thalamus, that disrupts cortical communication/integration.

scholarly journals Neural effects of propofol-induced unconsciousness and its reversal using thalamic stimulation

2020 ◽  
Author(s):  
André M. Bastos ◽  
Jacob A. Donoghue ◽  
Scott L. Brincat ◽  
Meredith Mahnke ◽  
Jorge Yanar ◽  
...  
Keyword(s):  
Local Field ◽  
Neural Activity ◽  
Local Field Potentials ◽  
Field Potentials ◽  
Thalamic Stimulation ◽  
Up States ◽  
Slow Frequency

AbstractThe specific circuit mechanisms through which anesthetics induce unconsciousness have not been completely characterized. We recorded neural activity from the frontal, parietal, and temporal cortices and thalamus while maintaining unconsciousness in non-human primates (NHPs) with the anesthetic propofol. Unconsciousness was marked by slow frequency (~1 Hz) oscillations in local field potentials, entrainment of local spiking to Up states alternating with Down states of little spiking, and decreased coherence in frequencies above 4 Hz. Thalamic stimulation “awakened” anesthetized NHPs and reversed the electrophysiologic features of unconsciousness. Unconsciousness is linked to cortical and thalamic slow frequency synchrony coupled with decreased spiking, and loss of higher-frequency dynamics. This may disrupt cortical communication/integration.

scholarly journals Neural effects of propofol-induced unconsciousness and its reversal using thalamic stimulation

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
André M Bastos ◽  
Jacob A Donoghue ◽  
Scott L Brincat ◽  
Meredith Mahnke ◽  
Jorge Yanar ◽  
...  
Keyword(s):  
Local Field ◽  
Neural Activity ◽  
Local Field Potentials ◽  
Field Potentials ◽  
Thalamic Stimulation ◽  
Up States ◽  
Slow Frequency ◽  
Spiking Activity

The specific circuit mechanisms through which anesthetics induce unconsciousness have not been completely characterized. We recorded neural activity from the frontal, parietal, and temporal cortices and thalamus while maintaining unconsciousness in non-human primates (NHPs) with the anesthetic propofol. Unconsciousness was marked by slow frequency (~1 Hz) oscillations in local field potentials, entrainment of local spiking to Up states alternating with Down states of little or no spiking activity, and decreased coherence in frequencies above 4 Hz. Thalamic stimulation ‘awakened’ anesthetized NHPs and reversed the electrophysiologic features of unconsciousness. Unconsciousness is linked to cortical and thalamic slow frequency synchrony coupled with decreased spiking, and loss of higher-frequency dynamics. This may disrupt cortical communication/integration.

scholarly journals Ictal onset patterns of local field potentials, high frequency oscillations, and unit activity in human mesial temporal lobe epilepsy

Epilepsia ◽  
2015 ◽  
Vol 57 (1) ◽  
pp. 111-121 ◽  
Author(s):  
Shennan Aibel Weiss ◽  
Catalina Alvarado-Rojas ◽  
Anatol Bragin ◽  
Eric Behnke ◽  
Tony Fields ◽  
...  
Keyword(s):  
Temporal Lobe Epilepsy ◽  
Temporal Lobe ◽  
Local Field ◽  
Unit Activity ◽  
High Frequency ◽  
Local Field Potentials ◽  
Mesial Temporal Lobe Epilepsy ◽  
Field Potentials ◽  
High Frequency Oscillations ◽  
Mesial Temporal Lobe

scholarly journals Propofol-induced loss of consciousness is associated with a decrease in thalamocortical connectivity in humans

Brain ◽  
2019 ◽  
Vol 142 (8) ◽  
pp. 2288-2302 ◽  
Author(s):  
Mahsa Malekmohammadi ◽  
Collin M Price ◽  
Andrew E Hudson ◽  
Jasmine A T DiCesare ◽  
Nader Pouratian
Keyword(s):  
Local Field ◽  
Brain Networks ◽  
Local Field Potentials ◽  
Loss Of Consciousness ◽  
Local Power ◽  
Field Potentials ◽  
Intermediate Nucleus ◽  
Frontoparietal Cortex ◽  
Ventral Intermediate Nucleus

It is unclear how anaesthesia affects activity across brain networks. Using local field potentials recorded directly from the ventral intermediate nucleus of the thalamus and frontoparietal cortex in patients undergoing DBS surgery, Malekmohammadi et al. report the breakdown of α functional thalamocortical connectivity under propofol anaesthesia despite local power increases.

scholarly journals Gradual emergence of spontaneous correlated brain activity during fading of general anesthesia in rats: Evidences from fMRI and local field potentials

NeuroImage ◽  
2015 ◽  
Vol 114 ◽  
pp. 185-198 ◽  
Author(s):  
Ruggero G. Bettinardi ◽  
Núria Tort-Colet ◽  
Marcel Ruiz-Mejias ◽  
Maria V. Sanchez-Vives ◽  
Gustavo Deco
Keyword(s):  
General Anesthesia ◽  
Local Field ◽  
Brain Activity ◽  
Local Field Potentials ◽  
Field Potentials

scholarly journals Semisupervised definition of hippocampal ripples

2020 ◽  
Author(s):  
Yusuke Watanabe ◽  
Mami Okada ◽  
Yuji Ikegaya
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Local Field ◽  
High Frequency ◽  
Mixed Model ◽  
Slow Wave Sleep ◽  
Animal Movement ◽  
Local Field Potentials ◽  
Field Potentials ◽  
Weakly Supervised

AbstractHippocampal ripples are transient neuronal features observed in high-frequency oscillatory bands of local field potentials, and they occur primarily during periods of behavioral immobility and slow-wave sleep. Ripples have been defined based on mathematically engineered features, such as magnitudes, durations, and cycles per event. However, the “ripples” could vary from laboratory to laboratory because their definition is subject to human bias, including the arbitrary choice of parameters and thresholds. In addition, local field potentials are often influenced by myoelectric noise arising from animal movement, making it difficult to distinguish ripples from high-frequency noises. To overcome these problems, we extracted ripple candidates under few constraints and labeled them as binary or stochastic “true” or “false” ripples using Gaussian mixed model clustering and a deep convolutional neural network in a weakly supervised fashion. Our automatic method separated ripples and myoelectric noise and was able to detect ripples even when the animals were moving. Moreover, we confirmed that a convolutional neural network was able to detect ripples defined by our method. Leave-one-animal-out cross-validation estimated the area under the precision-recall curve for ripple detection to be 0.72. Finally, our model establishes an appropriate threshold for the ripple magnitude in the case of the conventional detection of ripples.

Sign in / Sign up

Export Citation Format

Share Document