The asynchronous state's relation to large-scale potentials in cortex.

Understanding the relation between large-scale potentials (M/EEG) and their underlying neural activity can improve the precision of research and clinical diagnosis. Recent insights into cortical dynamics highlighted a state of strongly reduced spike count correlations, termed the asynchronous state (AS). The AS has received considerable attention from experimenters and theorists alike, regarding its implications for cortical dynamics and coding of information. However, how reconcilable are these vanishing correlations in the AS with large-scale potentials such as M/EEG observed in most experiments? Typically the latter are assumed to be based on underlying correlations in activity, in particular between subthreshold potentials. We survey the occurrence of the AS across brain states, regions, and layers and argue for a reconciliation of this seeming disparity: large-scale potentials are either observed, first, at transitions between cortical activity states, which entail transient changes in population firing rate, as well as during the AS, and, second, on the basis of sufficiently large, asynchronous populations that only need to exhibit weak correlations in activity. Cells with no or little spiking activity can contribute to large-scale potentials via their subthreshold currents, while they do not contribute to the estimation of spiking correlations, defining the AS. Furthermore, third, the AS occurs only within particular cortical regions and layers associated with the currently selected modality, allowing for correlations at other times and between other areas and layers.

Traveling waves shape neural population dynamics enabling predictions and internal model updating.

The brain generates predictions based on statistical regularities in our environment. However, it is unclear how predictions are optimized through iterative interactions with the environment. Because traveling waves (TWs) propagate across the cortex shaping neural excitability, they can carry information to serve predictive processing. Using human intracranial recordings, we show that anterior-to-posterior alpha TWs correlated with prediction strength. Learning about priors altered neural state space trajectories, and how much it altered correlated with trial-by-trial prediction strength. Learning involved mismatches between predictions and sensory evidence triggering alpha-phase resets in lateral temporal cortex, accompanied by stronger alpha phase-high gamma amplitude coupling and high-gamma power. The mismatch initiated posterior-to-anterior alpha TWs and change in the subsequent trial's state space trajectory, facilitating model updating. Our findings suggest a vital role of alpha TWs carrying both predictions to sensory cortex and mismatch signals to frontal cortex for trial-by-trial fine-tuning of predictive models.

Assessing the state of consciousness for individual patients using complex, statistical stimuli.

Patients with prolonged disorders of consciousness (PDOC) are often unable to communicate their state of consciousness. Determining the latter is essential for the patient's care and prospects of recovery. Auditory stimulation in combination with neural recordings is a promising technique towards an objective assessment of conscious awareness. Here, we investigated the potential of complex, acoustic stimuli to elicit EEG responses suitable for classifying multiple subject groups, from unconscious to responding. We presented naturalistic auditory textures with unexpectedly changing statistics to human listeners. Awake, active listeners were asked to indicate the change by button press, while all other groups (awake passive, asleep, minimally conscious state (MCS), and unresponsive wakefulness syndrome (UWS)) listened passively. We quantified the evoked potential at stimulus onset and change in stimulus statistics, as well as the complexity of neural response during the change of stimulus statistics. On the group level, onset and change potentials classified patients and healthy controls successfully but failed to differentiate between the UWS and MCS groups. Conversely, the Lempel-Ziv complexity of the scalp-level potential allowed reliable differentiation between UWS and MCS even for individual subjects, when compared with the clinical assessment aligned to the EEG measurements. The accuracy appears to improve further when taking the latest available clinical diagnosis into account. In summary, EEG signal complexity during onset and changes in complex acoustic stimuli provides an objective criterion for distinguishing states of consciousness in clinical patients. These results suggest EEG-recordings as a cost-effective tool to choose appropriate treatments for non-responsive PDOC patients.

Sorption of cholesterol and other bile components on ion-exchangers in vitro, and their influence on the cholesterol level in human serum in vivo.

The sorption of bile acids, bilirubin, bilirubin glucuronates and cholesterol on ion-exchange resin is described. After some successful attempts of sorption of these substances from human and animal bile in vitro, this exchanger has been used in human therapy. Positive results obtained showed the usefulness of the method. The purpose of the experiments was to study the usefulness of ion-exchangers for sorption of bile components of bile acids, bilirubin, bilirubin glucuronates and cholesterol. First sorption was carried out on human and animal bile, on Zerolit-FS-ip, in cycles (OH-) and (Cl-), by passing through glass columns downwards and some of them by mixing the bile with ion-exchange resin. Zerolit FS-ip is an organic sorbent, a scavenger, a strongly basic macroporous, anion exchanger. Positive results of these sorptions indicated the possibility of using this method in therapy of disturbed lipid conditions.