Deep non-rapid eye movement sleep (NREM) and general anesthesia with propofol are prominent states of reduced arousal linked to the occurrence of synchronized oscillations in the electroencephalogram (EEG). Although rapid eye movement (REM) sleep is also associated with diminished arousal levels, it is characterized by a desynchronized, 'wake-like' EEG. This observation implies that reduced arousal states are not necessarily only defined by synchronous oscillatory activity. Using intracranial and surface EEG recordings in four independent data sets, we demonstrate that the 1/f spectral slope of the electrophysiological power spectrum, which reflects the non-oscillatory, scale-free component of neural activity, delineates wakefulness from propofol anesthesia, NREM and REM sleep. Critically, the spectral slope discriminates wakefulness from REM sleep solely based on the neurophysiological brain state. Taken together, our findings describe a common electrophysiological marker that tracks states of reduced arousal, including different sleep stages as well as anesthesia in humans.
Source data files have been updated and are provided here:Lendner, Janna (2020), An Electrophysiological Marker of Arousal Level in Humans, UC Berkeley, Dataset, https://doi.org/10.6078/D1NX1V
An Electrophysiological Marker of Arousal Level in HumansDryad Digital Repository, doi:10.6078/D1NX1V.
- Janna Desiree Lendner
- Robert T Knight
- Randolph F Helfrich
- Matthew P Walker
- Matthew P Walker
- Matthew P Walker
- Bryce A Mander
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Human subjects: We collected four independent datasets for this study to assess the neurophysiological basis of states of reduced arousal, namely sleep and general anesthesia.Study 1 - Anesthesia scalp EEG: All participants were informed and provided written consent in accordance with the local ethics committee (Regional Committees for Medical and Health Research Ethics in Oslo case number 2012/2015 and extension 2012/2015-8).Study 2 - Anesthesia intracranial EEG: All participants were informed and provided written consent in accordance with the local ethics committee (Regional Committees for Medical and Health Research Ethics in Oslo case number 2012/2015 and extension 2012/2015-8).Study 3 - Sleep scalp EEG: All participants were informed and provided written consent in accordance with the local ethics committee (Berkeley Committee for Protection of Human Subjects Protocol Number 2010-01-595).Study 4 - Sleep intracranial EEG: All patients provided informed consent according to the local ethics committees of the University of California at Berkeley and at Irvine (University of California at Berkeley Committee for the Protection of Human Subjects Protocol Number 2010-01-520; University of California at Irvine Institutional Review Board Protocol Number 2014-1522, UCB relies on UCI Reliance Number 1817) and gave their written consent before data collection.
- Saskia Haegens, Columbia University College of Physicians and Surgeons, United States
© 2020, Lendner et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Resolving trajectories of axonal pathways in the primate prefrontal cortex remains crucial to gain insights into higher-order processes of cognition and emotion, which requires a comprehensive map of axonal projections linking demarcated subdivisions of prefrontal cortex and the rest of brain. Here, we report a mesoscale excitatory projectome issued from the ventrolateral prefrontal cortex (vlPFC) to the entire macaque brain by using viral-based genetic axonal tracing in tandem with high-throughput serial two-photon tomography, which demonstrated prominent monosynaptic projections to other prefrontal areas, temporal, limbic, and subcortical areas, relatively weak projections to parietal and insular regions but no projections directly to the occipital lobe. In a common 3D space, we quantitatively validated an atlas of diffusion tractography-derived vlPFC connections with correlative green fluorescent protein-labeled axonal tracing, and observed generally good agreement except a major difference in the posterior projections of inferior fronto-occipital fasciculus. These findings raise an intriguing question as to how neural information passes along long-range association fiber bundles in macaque brains, and call for the caution of using diffusion tractography to map the wiring diagram of brain circuits.
Background: Deep Brain Stimulation (DBS) electrode implant trajectories are stereotactically defined using preoperative neuroimaging. To validate the correct trajectory, microelectrode recordings (MER) or local field potential recordings (LFP) can be used to extend neuroanatomical information (defined by magnetic resonance imaging) with neurophysiological activity patterns recorded from micro- and macroelectrodes probing the surgical target site. Currently, these two sources of information (imaging vs. electrophysiology) are analyzed separately, while means to fuse both data streams have not been introduced.
Methods: Here we present a tool that integrates resources from stereotactic planning, neuroimaging, MER and high-resolution atlas data to create a real-time visualization of the implant trajectory. We validate the tool based on a retrospective cohort of DBS patients (𝑁 = 52) offline and present single use cases of the real-time platform. Results: We establish an open-source software tool for multimodal data visualization and analysis during DBS surgery. We show a general correspondence between features derived from neuroimaging and electrophysiological recordings and present examples that demonstrate the functionality of the tool.
Conclusions: This novel software platform for multimodal data visualization and analysis bears translational potential to improve accuracy of DBS surgery. The toolbox is made openly available and is extendable to integrate with additional software packages.
Funding: Deutsche Forschungsgesellschaft (410169619, 424778381), Deutsches Zentrum für Luftund Raumfahrt (DynaSti), National Institutes of Health (2R01 MH113929), Foundation for OCD Research (FFOR).