Critical Changes in Cortical Neuronal Interactions in Anesthetized and Awake Rats

Background: Neuronal interactions are fundamental for information processing, cognition and consciousness. Anesthetics reduce spontaneous cortical activity; however, neuronal reactivity to sensory stimuli is often preserved or augmented. How sensory stimulus-related neuronal interactions change under anesthesia has not been elucidated. Here we investigated visual stimulus-related cortical neuronal interactions during stepwise emergence from desflurane anesthesia. Methods: Parallel spike trains were recorded with 64-contact extracellular microelectrode arrays from the primary visual cortex of chronically instrumented, unrestrained rats (N=6) at 8%, 6%, 4%, 2% desflurane anesthesia and wakefulness. Light flashes were delivered to the retina by transcranial illumination at 5-15s randomized intervals. Information theoretical indices, integration and interaction complexity, were calculated from the probability distribution of coincident spike patterns and used to quantify neuronal interactions before and after flash stimulation. Results: Integration and complexity showed significant negative associations with desflurane concentration (N=60). Flash stimulation increased integration and complexity at all anesthetic levels (N=60); the effect on complexity was reduced in wakefulness. During stepwise withdrawal of desflurane, the largest increase in integration (74%) and post-stimulus complexity (35%) occurred prior to reaching 4% desflurane concentration – a level associated with the recovery of consciousness according to the rats\u27 righting reflex. Conclusions: Neuronal interactions in the cerebral cortex are augmented during emergence from anesthesia. Visual flash stimuli enhance neuronal interactions in both wakefulness and anesthesia; the increase in interaction complexity is attenuated as post-stimulus complexity reaches plateau. The critical changes in cortical neuronal interactions occur during transition to consciousness

Nonlinear network identifiability: The static case

We analyze the problem of network identifiability with nonlinear functions associated with the edges. We consider a static model for the output of each node and by assuming a perfect identification of the function associated with the measurement of a node, we provide conditions for the identifiability of the edges in a specific class of functions. First, we analyze the identifiability conditions in the class of all nonlinear functions and show that even for a path graph, it is necessary to measure all the nodes except by the source. Then, we consider analytic functions satisfying $f(0)=0$ and we provide conditions for the identifiability of paths and trees. Finally, by restricting the problem to a smaller class of functions where none of the functions is linear, we derive conditions for the identifiability of directed acyclic graphs. Some examples are presented to illustrate the results.Comment: 6 pages, 3 figures, to appear in IEEE Conference on Decision and Control (CDC 2023

Monosynaptic Functional Connectivity in Cerebral Cortex During Wakefulness and Under Graded Levels of Anesthesia

The balance between excitation and inhibition is considered to be of significant importance for neural computation and cognitive function. Excitatory and inhibitory functional connectivity in intact cortical neuronal networks in wakefulness and graded levels of anesthesia has not been systematically investigated. We compared monosynaptic excitatory and inhibitory spike transmission probabilities using pairwise cross-correlogram (CCG) analysis. Spikes were measured at 64 sites in the visual cortex of rats with chronically implanted microelectrode arrays during wakefulness and three levels of anesthesia produced by desflurane. Anesthesia decreased the number of active units, the number of functional connections, and the strength of excitatory connections. Connection probability (number of connections per number of active unit pairs) was unaffected until the deepest anesthesia level, at which a significant increase in the excitatory to inhibitory ratio of connection probabilities was observed. The results suggest that the excitatory–inhibitory balance is altered at an anesthetic depth associated with unconsciousness

Critical Repetition Rates for Perceptual Segregation of Time-Varying Auditory, Visual and Vibrotactile Stimulation

What sound quality has led to exclude infrasound from sound in the conventional hearing range? We examined whether temporal segregation of pressure pulses is a distinctive property and evaluated this perceptual limit via an adaptive psychophysical procedure for pure tones and carriers of different envelopes. Further, to examine across-domain similarity and individual covariation of this limit, here called the critical segregation rate (CSR), it was also measured for various periodic visual and vibrotactile stimuli. Results showed that sequential auditory or vibrotactile stimuli separated by at least ~80‒90 ms (~11‒12-Hz repetition rates), will be perceived as perceptually segregated from one another. While this limit did not statistically differ between these two modalities, it was significantly lower than the ~150 ms necessary to perceptually segregate successive visual stimuli. For the three sensory modalities, stimulus periodicity was the main factor determining the CSR, which apparently reflects neural recovery times of the different sensory systems. Among all experimental conditions, significant within- and across-modality individual CSR correlations were observed, despite the visual CSR (mean: 6.8 Hz) being significantly lower than that of both other modalities. The auditory CSR was found to be significantly lower than the frequency above which sinusoids start to elicit a tonal quality (19 Hz; recently published for the same subjects). Returning to our initial question, the latter suggests that the cessation of tonal quality — not the segregation of pressure fluctuations — is the perceptual quality that has led to exclude infrasound (sound with frequencies < 20 Hz) from the conventional hearing range

Regionalized PM2.5 Community Multiscale Air Quality model performance evaluation across a continuous spatiotemporal domain

The regulatory Community Multiscale Air Quality (CMAQ) model is a means to understanding the sources, concentrations and regulatory attainment of air pollutants within a model's domain. Substantial resources are allocated to the evaluation of model performance. The Regionalized Air quality Model Performance (RAMP) method introduced here explores novel ways of visualizing and evaluating CMAQ model performance and errors for daily Particulate Matter ≤ 2.5 micrometers (PM2.5) concentrations across the continental United States. The RAMP method performs a non-homogenous, non-linear, non-homoscedastic model performance evaluation at each CMAQ grid. This work demonstrates that CMAQ model performance, for a well-documented 2001 regulatory episode, is non-homogeneous across space/time. The RAMP correction of systematic errors outperforms other model evaluation methods as demonstrated by a 22.1% reduction in Mean Square Error compared to a constant domain wide correction. The RAMP method is able to accurately reproduce simulated performance with a correlation of r = 76.1%. Most of the error coming from CMAQ is random error with only a minority of error being systematic. Areas of high systematic error are collocated with areas of high random error, implying both error types originate from similar sources. Therefore, addressing underlying causes of systematic error will have the added benefit of also addressing underlying causes of random error

Analysis of luxury resort hotels by using the Fuzzy Analytic Hierarchy Process and the Fuzzy Delphi Method

Experience Economy is an accelerator switching the experience process of consumption into eternal memory, perfecting value and promoting positive after-buying intention. This research uses the Fuzzy Delphi Method (FDM) and Fuzzy Analytic Hierarchy Process (FAHP) to construct a system of evaluation criteria focused on understanding the luxury resort hotels (LRHs) industry in Taiwan and Macao. One finding of this study is that objective hotels in these two territories exhibit different hotel operating characteristic (the unity LRHs mode in Taiwan vs involving casino LRHs in Macao) and customer markets. These Macanese LRHs define them as international operations, in contrast the Taiwanese position themselves as domestic businesses. The other finding is that Taiwan based evaluation criteria on consumer-orientation and operation and management, while Macao stressed evaluation based on operation and management to manage LRHs industry

A photoresponsive graphene oxide-C60 conjugate

[EN] An all-carbon donor–acceptor hybrid combining graphene oxide (GO) and C60 has been prepared. Laser flash photolysis measurements revealed the occurrence of photoinduced electron transfer from the GO electron donor to the C60 electron acceptor in the conjugate.This research was financially supported by the Spanish Ministry of Economy and Competitiveness of Spain (CTQ2010-17498, MAT2010-20843-C02-01 and PLE-2009-0038) and a Severo Ochoa operating grant from the Spanish Ministry of Economy and Competitiveness. We also acknowledge financial support from the Spanish Ministry of Economy and Competitiveness, Comunidad de Madrid (CAM 09-S2009_MAT-1467), Generalitat Valenciana (PROMETEO program), and VLC/Campus Microcluster "Nanomateriales Funcionales y Nanodispositivos".Barrejón, M.; Vizuete, M.; Gómez Escalonilla, M.; Fierro, J.; Berlanga, I.; Zamora, F.; Abellán, G.... (2014). A photoresponsive graphene oxide-C60 conjugate. Chemical Communications. 50(65):9053-9055. doi:10.1039/C3CC49589BS90539055506

Resource allocation in open multi-agent systems: an online optimization analysis

The resource allocation problem consists of the optimal distribution of a budget between agents in a group. We consider such a problem in the context of open systems, where agents can be replaced at some time instances. These replacements lead to variations in both the budget and the total cost function that hinder the overall network's performance. For a simple setting, we analyze the performance of the Random Coordinate Descent algorithm (RCD) using tools similar to those commonly used in online optimization. In particular, we study the accumulated errors that compare solutions issued from the RCD algorithm and the optimal solution or the non-collaborating selfish strategy and we derive some bounds in expectation for these accumulated errors.Comment: 7 pages, 3 figures, accepted for the 61st Conference on Decision and Control (CDC2022