Slow update of internal representations impedes synchronization in autism.
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ABSTRACT:
SUBMITTER: Vishne G
PROVIDER: S-EPMC8440645 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Spontaneous synchronization over large networks is ubiquitous in nature, ranging from inanimate to biological systems. In the human brain, neuronal synchronization and de-synchronization occur during sleep, with the greatest degree of neuronal synchronization during slow wave sleep (SWS). The current sleep classification schema is based on electroencephalography and provides common criteria for clinicians and researchers to describe stages of non-rapid eye movement (NREM) sleep as well as rapid eye movement (REM) sleep. These sleep stage classifications have been based on convenient heuristic criteria, with little consideration of the accompanying normal physiological changes across those same sleep stages. To begin to resolve those inconsistencies, first focusing only on NREM sleep, we propose a simple cluster synchronization model to explain the emergence of SWS in healthy people without sleep disorders. We apply the empirical mode decomposition (EMD) analysis to quantify slow wave activity in electroencephalograms, and provide quantitative evidence to support our model. Based on this synchronization model, NREM sleep can be classified as SWS and non-SWS, such that NREM sleep can be considered as an intrinsically bistable process. Finally, we develop an automated algorithm for SWS classification. We show that this new approach can unify brain wave dynamics and their corresponding physiologic changes.
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Project description:Autism is often described as a disorder of neural synchronization. However, it is unknown how early in development synchronization abnormalities emerge and whether they are related to the development of early autistic behavioral symptoms. Here, we show that disrupted synchronization is evident in the spontaneous cortical activity of naturally sleeping toddlers with autism, but not in toddlers with language delay or typical development. Toddlers with autism exhibited significantly weaker interhemispheric synchronization (i.e., weak "functional connectivity" across the two hemispheres) in putative language areas. The strength of synchronization was positively correlated with verbal ability and negatively correlated with autism severity, and it enabled identification of the majority of autistic toddlers (72%) with high accuracy (84%). Disrupted cortical synchronization, therefore, appears to be a notable characteristic of autism neurophysiology that is evident at very early stages of autism development.
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Project description:Hippocampal neurons exhibit spatially localized firing patterns that, at the population level, represent a particular environment or context. Many studies have examined how hippocampal neurons switch from an existing representation to a new one when the environment is changed, a process referred to as remapping. New representations were commonly thought to emerge rapidly, within a few minutes and then remain remarkably stable thereafter. However, a number of recent studies suggest that hippocampal representations may be more fluid than previously thought and most of the previous studies only required that subjects switch from a familiar environment to a novel one. In the present study, we examined the concurrent development of two distinct hippocampal representations by exposing rats to two distinct environmental contexts in an ABAB pattern and we recorded neuronal activity for eight daily training sessions. Hippocampal neurons exhibited normal place fields with typical firing properties during the initial exposure to each context on the first day. However, when the rats were returned to the original context after having spent 15 min in the second context, many of the neurons fired in new locations (i.e., they remapped) as if the rat had encountered a new environment. By the third day, the representations had stabilized and were highly consistent across visits to the same context. These results suggest that when subjects concurrently encode multiple contexts, hippocampal representations may require repeated experiences to fully stabilize. © 2016 Wiley Periodicals, Inc.
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Project description:Iterated ripple noise (IRN) is a type of pitch-evoking stimulus that is commonly used in neuroimaging studies of pitch processing. When contrasted with a spectrally matched Gaussian noise, it is known to produce a consistent response in a region of auditory cortex that includes an area antero-lateral to the primary auditory fields (lateral Heschl's gyrus). The IRN-related response has often been attributed to pitch, although recent evidence suggests that it is more likely driven by slowly varying spectro-temporal modulations not related to pitch. The present functional magnetic resonance imaging (fMRI) study showed that both pitch-related temporal regularity and slow modulations elicited a significantly greater response than a baseline Gaussian noise in an area that has been pre-defined as pitch-responsive. The region was sensitive to both pitch salience and slow modulation salience. The responses to pitch and spectro-temporal modulations interacted in a saturating manner, suggesting that there may be an overlap in the populations of neurons coding these features. However, the interaction may have been influenced by the fact that the two pitch stimuli used (IRN and unresolved harmonic complexes) differed in terms of pitch salience. Finally, the results support previous findings suggesting that the cortical response to IRN is driven in part by slow modulations, not by pitch.
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Project description:Autism is a psychiatric/neurological condition in which alterations in social interaction (among other symptoms) are diagnosed by behavioral psychiatric methods. The main goal of this study was to determine how the neural representations and meanings of social concepts (such as to insult) are altered in autism. A second goal was to determine whether these alterations can serve as neurocognitive markers of autism. The approach is based on previous advances in fMRI analysis methods that permit (a) the identification of a concept, such as the thought of a physical object, from its fMRI pattern, and (b) the ability to assess the semantic content of a concept from its fMRI pattern. These factor analysis and machine learning methods were applied to the fMRI activation patterns of 17 adults with high-functioning autism and matched controls, scanned while thinking about 16 social interactions. One prominent neural representation factor that emerged (manifested mainly in posterior midline regions) was related to self-representation, but this factor was present only for the control participants, and was near-absent in the autism group. Moreover, machine learning algorithms classified individuals as autistic or control with 97% accuracy from their fMRI neurocognitive markers. The findings suggest that psychiatric alterations of thought can begin to be biologically understood by assessing the form and content of the altered thought's underlying brain activation patterns.
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Project description:BackgroundThere is evidence that slow wave sleep (SWS) promotes the consolidation of memories that are subserved by mediotemporal- and hippocampo-cortical neural networks. In contrast to implicit memories, explicit memories are accompanied by conscious (attentive and controlled) processing. Awareness at pre-sleep encoding has been recognized as critical for the off-line memory consolidation. The present study elucidated the role of task-dependent cortical activation guided by attentional control at pre-sleep encoding for the consolidation of hippocampus-dependent memories during sleep.MethodologyA task with a hidden regularity was used (Number Reduction Task, NRT), in which the responses that can be implicitly predicted by the hidden regularity activate hippocampo-cortical networks more strongly than responses that cannot be predicted. Task performance was evaluated before and after early-night sleep, rich in SWS, and late-night sleep, rich in rapid eye movement (REM) sleep. In implicit conditions, slow cortical potentials (SPs) were analyzed to reflect the amount of controlled processing and the localization of activated neural task representations.Principal findingsDuring implicit learning before sleep, the amount of controlled processing did not differ between unpredictable and predictable responses, nor between early- and late-night sleep groups. A topographic re-distribution of SPs indicating a spatial reorganization occurred only after early, not after late sleep, and only for predictable responses. These SP changes correlated with the amount of SWS and were covert because off-line RT decrease did not differentiate response types or sleep groups.ConclusionsIt is concluded that SWS promotes the neural reorganization of task representations that rely on the hippocampal system despite absence of conscious access to these representations.SignificanceOriginal neurophysiologic evidence is provided for the role of SWS in the consolidation of memories encoded with hippocampo-cortical interaction before sleep. It is demonstrated that this SWS-mediated mechanism does not depend critically on explicitness at learning nor on the amount of controlled executive processing during pre-sleep encoding.
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Project description:Slow wave activity (SWA) is a characteristic brain oscillation in sleep and quiet wakefulness. Although the cell types contributing to SWA genesis are not yet identified, the principal role of neurons in the emergence of this essential cognitive mechanism has not been questioned. To address the possibility of astrocytic involvement in SWA, we used a transgenic rat line expressing a calcium sensitive fluorescent protein in both astrocytes and interneurons and simultaneously imaged astrocytic and neuronal activity in vivo. Here we demonstrate, for the first time, that the astrocyte network display synchronized recurrent activity in vivo coupled to UP states measured by field recording and neuronal calcium imaging. Furthermore, we present evidence that extensive synchronization of the astrocytic network precedes the spatial build-up of neuronal synchronization. The earlier extensive recruitment of astrocytes in the synchronized activity is reinforced by the observation that neurons surrounded by active astrocytes are more likely to join SWA, suggesting causality. Further supporting this notion, we demonstrate that blockade of astrocytic gap junctional communication or inhibition of astrocytic Ca2+ transients reduces the ratio of both astrocytes and neurons involved in SWA. These in vivo findings conclusively suggest a causal role of the astrocytic syncytium in SWA generation.
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