Exploring complex and integrated information during sleep
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PROVIDER: S-EPMC11227102 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:Non-threatening familiar sounds can go unnoticed during sleep despite the fact that they enter our brain by exciting the auditory nerves. Extracellular cortical recordings in the primary auditory cortex of rodents show that an increase in firing rate in response to pure tones during deep phases of sleep is comparable to those evoked during wakefulness. This result challenges the hypothesis that during sleep cortical responses are weakened through thalamic gating. An alternative explanation comes from the observation that the spatiotemporal spread of the evoked activity by transcranial magnetic stimulation in humans is reduced during non-rapid eye movement (NREM) sleep as compared to the wider propagation to other cortical regions during wakefulness. Thus, cortical responses during NREM sleep remain local and the stimulus only reaches nearby neuronal populations. We aim at understanding how this behavior emerges in the brain as it spontaneously shifts between NREM sleep and wakefulness. To do so, we have used a computational neural-mass model to reproduce the dynamics of the sensory auditory cortex and corresponding local field potentials in these two brain states. Following the synaptic homeostasis hypothesis, an increase in a single parameter, namely the excitatory conductance g¯AMPA, allows us to place the model from NREM sleep into wakefulness. In agreement with the experimental results, the endogenous dynamics during NREM sleep produces a comparable, even higher, response to excitatory inputs to the ones during wakefulness. We have extended the model to two bidirectionally connected cortical columns and have quantified the propagation of an excitatory input as a function of their coupling. We have found that the general increase in all conductances of the cortical excitatory synapses that drive the system from NREM sleep to wakefulness does not boost the effective connectivity between cortical columns. Instead, it is the inter-/intra-conductance ratio of cortical excitatory synapses that should raise to facilitate information propagation across the brain.
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Project description:How are memories transferred from short-term to long-term storage? Systems-level memory consolidation is thought to be dependent on the coordinated interplay of cortical slow waves, thalamo-cortical sleep spindles and hippocampal ripple oscillations. However, it is currently unclear how the selective interaction of these cardinal sleep oscillations is organized to support information reactivation and transfer. Here, using human intracranial recordings, we demonstrate that the prefrontal cortex plays a key role in organizing the ripple-mediated information transfer during non-rapid eye movement (NREM) sleep. We reveal a temporally precise form of coupling between prefrontal slow-wave and spindle oscillations, which actively dictates the hippocampal-neocortical dialogue and information transfer. Our results suggest a model of the human sleeping brain in which rapid bidirectional interactions, triggered by the prefrontal cortex, mediate hippocampal activation to optimally time subsequent information transfer to the neocortex during NREM sleep.
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Project description:How are brief encounters transformed into lasting memories? Previous research has established the role of non-rapid eye movement (NREM) sleep, along with its electrophysiological signatures of slow oscillations (SOs) and spindles, for memory consolidation [1-4]. In related work, experimental manipulations have demonstrated that NREM sleep provides a window of opportunity to selectively strengthen particular memory traces via the delivery of auditory cues [5-10], a procedure known as targeted memory reactivation (TMR). It has remained unclear, however, whether TMR triggers the brain's endogenous consolidation mechanisms (linked to SOs and/or spindles) and whether those mechanisms in turn mediate effective processing of mnemonic information. We devised a novel paradigm in which associative memories (adjective-object and adjective-scene pairs) were selectively cued during a post-learning nap, successfully stabilizing next-day retention relative to non-cued memories. First, we found that, compared to novel control adjectives, memory cues evoked an increase in fast spindles. Critically, during the time window of cue-induced spindle activity, the memory category linked to the verbal cue (object or scene) could be reliably decoded, with the fidelity of this decoding predicting the behavioral consolidation benefits of TMR. These results provide correlative evidence for an information processing role of sleep spindles in service of memory consolidation.
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Project description:Integrated information theory (IIT) has established itself as one of the leading theories for the study of consciousness. IIT essentially proposes that quantitative consciousness is identical to maximally integrated conceptual information, quantified by a measure called Φmax, and that phenomenological experience corresponds to the associated set of maximally irreducible cause-effect repertoires of a physical system being in a certain state. With the current work, we provide a general formulation of the framework, which comprehensively and parsimoniously expresses Φmax in the language of probabilistic models. Here, the stochastic process describing a system under scrutiny corresponds to a first-order time-invariant Markov process, and all necessary mathematical operations for the definition of Φmax are fully specified by a system's joint probability distribution over two adjacent points in discrete time. We present a detailed constructive rule for the decomposition of a system into two disjoint subsystems based on flexible marginalization and factorization of this joint distribution. Furthermore, we show that for a given joint distribution, virtualization is identical to a flexible factorization enforcing independence between variable subsets. We then validate our formulation in a previously established discrete example system, in which we also illustrate the previously unexplored theoretical issue of quale underdetermination due to non-unique maximally irreducible cause-effect repertoires. Moreover, we show that the current definition of Φ entails its sensitivity to the shape of the conceptual structure in qualia space, thus tying together IIT's measures of quantitative and qualitative consciousness, which we suggest be better disentangled. We propose several modifications of the framework in order to address some of these issues.
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Project description:Consciousness is one of the most complex aspects of human experience. Studying the mechanisms involved in the transitions among different levels of consciousness remains as one of the greatest challenges in neuroscience. In this study we use a measure of integrated information (ΦAR) to evaluate dynamic changes during consciousness transitions. We applied the measure to intracranial electroencephalography (SEEG) recordings collected from 6 patients that suffer from refractory epilepsy, taking into account inter-ictal, pre-ictal and ictal periods. We analyzed the dynamical evolution of ΦAR in groups of electrode contacts outside the epileptogenic region and compared it with the Consciousness Seizure Scale (CCS). We show that changes on ΦAR are significantly correlated with changes in the reported states of consciousness.
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Project description:Obstructive sleep apnea (OSA) is an upper airway disorder occurring during sleep and is associated with atherosclerosis (AS). AS is a cardiovascular disease caused by environmental and genetic factors, with a high global mortality rate. This study investigated common pathways and potential biomarkers of OSA and AS. Microarray data were downloaded from the Gene Expression Omnibus (GEO) database and used to screen for differentially expressed genes (DEGs) in the OSA and AS datasets. A weighted gene co-expression network analysis (WGCNA) was used to identify the co-expression modules of OSA and AS. The least absolute shrinkage and selection operators (LASSO) were used to determine critical biomarkers. Immune cell infiltration analysis was used to investigate the correlation between immune cell infiltration and common biomarkers of OSA and AS. Results revealed that differentially expressed genes may be involved in inflammatory processes, chemokine signaling pathways, and molecular changes in cell adhesion. ERBB receptor feedback inhibitor 1 (ERRFI1) was the best-shared biomarker for OSA and AS. Immune infiltration analysis showed that ERRFI1 expression was correlated with immune cell changes. Changes in immune pathways, inflammatory processes, and cell adhesion molecules may underlie the pathogenesis of both diseases, and ERRFI1 may be a potential diagnostic marker for patients with OSA and AS.
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Project description:We aimed at better understanding the brain mechanisms involved in the processing of alerting meaningful sounds during sleep, investigating alpha activity. During EEG acquisition, subjects were presented with a passive auditory oddball paradigm including rare complex sounds called Novels (the own first name - OWN, and an unfamiliar first name - OTHER) while they were watching a silent movie in the evening or sleeping at night. During the experimental night, the subjects' quality of sleep was generally preserved. During wakefulness, the decrease in alpha power (8-12 Hz) induced by Novels was significantly larger for OWN than for OTHER at parietal electrodes, between 600 and 900 ms after stimulus onset. Conversely, during REM sleep, Novels induced an increase in alpha power (from 0 to 1200 ms at all electrodes), significantly larger for OWN than for OTHER at several parietal electrodes between 700 and 1200 ms after stimulus onset. These results show that complex sounds have a different effect on the alpha power during wakefulness (decrease) and during REM sleep (increase) and that OWN induce a specific effect in these two states. The increased alpha power induced by Novels during REM sleep may 1) correspond to a short and transient increase in arousal; in this case, our study provides an objective measure of the greater arousing power of OWN over OTHER, 2) indicate a cortical inhibition associated with sleep protection. These results suggest that alpha modulation could participate in the selection of stimuli to be further processed during sleep.
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Project description:BackgroundInformation and communications technologies (ICTs) are recognized as critical enablers of integrated primary care to support patients with multiple chronic conditions. Although ICT-enabled integrated primary care holds promise in supporting patients with complex care needs through team-based and continued care, critical implementation factors regarding what ICTs are available and how they enable this model are yet to be mapped in the literature.ObjectiveThis scoping review addressed the current knowledge gap by answering the following research question: What ICTs are used in delivering integrated primary care to patients with complex care needs?MethodsThe Arksey and O'Malley method enhanced by the work by Levac et al was used to guide this scoping review. In total, 4 electronic medical databases were accessed-MEDLINE, Embase, CINAHL, and PsycINFO-collecting studies published between January 2000 and December 2021. Identified peer-reviewed articles were screened. Relevant studies were charted, collated, and analyzed using the Rainbow Model of Integrated Care and the eHealth Enhanced Chronic Care Model.ResultsA total of 52,216 articles were identified, of which 31 (0.06%) met the review's eligibility criteria. In the current literature, ICTs are used to serve the following functions in the integrated primary care setting: information sharing, self-management support, clinical decision-making, and remote service delivery. Integration efforts are supported by ICTs by promoting teamwork and coordinating clinical services across teams and organizations. Patient, provider, organizational, and technological implementation factors are considered important for ICT-based interventions in the integrated primary care setting.ConclusionsICTs play a critical role in enabling clinical and professional integration in the primary care setting to meet the health system-related needs of patients with complex care needs. Future research is needed to explore how to integrate technologies at an organizational and system level to create a health system that is well prepared to optimize technologies to support patients with complex care needs.
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Project description:PubChem (https://pubchem.ncbi.nlm.nih.gov) is a public chemical database that serves scientific communities as well as the general public. This database collects chemical information from hundreds of data sources and organizes them into multiple data collections, including Substance, Compound, BioAssay, Protein, Gene, Pathway, and Patent. These collections are interlinked with each other, allowing users to discover related records in the various collections (e.g., drugs targeting a protein or genes modulated by a chemical). PubChem can be searched by keyword (e.g., a chemical, protein, or gene name) as well as by chemical structure. The input structure can be provided using popular line notations or drawn with the PubChem Sketcher. PubChem supports various types of structure searches, including identity search, 2-D and 3-D similarity searches, and substructure and superstructure searches. Results from multiple searches can be combined using Boolean operators (i.e., AND, OR, and NOT) to formulate complex queries. PubChem allows the user to quickly retrieve a list of records annotated with a particular classification or ontological term. This paper provides step-by-step instructions on how to explore PubChem data with examples of commonly requested tasks. © 2021. This article is a U.S. Government work and is in the public domain in the USA. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Finding genes and proteins that interact with a given compound Basic Protocol 2: Finding drug-like compounds similar to a query compound through a two-dimensional (2-D) similarity search Basic Protocol 3: Finding compounds similar to a query compound through a three-dimensional (3-D) similarity search Support Protocol: Computing similarity scores between compounds Basic Protocol 4: Getting the bioactivity data for the hit compounds from substructure search Basic Protocol 5: Finding drugs that target a particular gene Basic Protocol 6: Getting bioactivity data of all chemicals tested against a protein. Basic Protocol 7: Finding compounds annotated with classifications or ontological terms Basic Protocol 8: Finding stereoisomers and isotopomers of a compound through identity search.
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Project description:Originally developed as a theory of consciousness, integrated information theory provides a mathematical framework to quantify the causal irreducibility of systems and subsets of units in the system. Specifically, mechanism integrated information quantifies how much of the causal powers of a subset of units in a state, also referred to as a mechanism, cannot be accounted for by its parts. If the causal powers of the mechanism can be fully explained by its parts, it is reducible and its integrated information is zero. Here, we study the upper bound of this measure and how it is achieved. We study mechanisms in isolation, groups of mechanisms, and groups of causal relations among mechanisms. We put forward new theoretical results that show mechanisms that share parts with each other cannot all achieve their maximum. We also introduce techniques to design systems that can maximize the integrated information of a subset of their mechanisms or relations. Our results can potentially be used to exploit the symmetries and constraints to reduce the computations significantly and to compare different connectivity profiles in terms of their maximal achievable integrated information.
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