Schizophrenia is a disorder of cerebral disconnectivity whose lifetime course is modeled as both neurodevelopmental and neurodegenerative. The neurodevelopmental models attribute schizophrenia to ...alterations in the prenatal-to-early adolescent development. The neurodegenerative models identify progressive neurodegeneration as its core attribute. Historically, the physiology, pharmacology, and treatment targets in schizophrenia were conceptualized in terms of neurons, neurotransmitter levels, and synaptic receptors. Much of the evidence for both models was derived from studies of cortical and subcortical gray matter. We argue that the dynamics of the lifetime trajectory of white matter, and the consistency of connectivity deficits in schizophrenia, support white matter integrity as a promising phenotype to evaluate the competing evidence for and against neurodevelopmental and neurodegenerative heuristics. We develop this perspective by reviewing normal lifetime trajectories of white and gray matter changes. We highlighted the overlap between the age of peak of white matter development and the age of onset of schizophrenia and reviewed findings of white matter abnormalities prior to, at the onset, and at chronic stages of schizophrenia. We emphasized the findings of reduced white matter integrity at the onset and findings of accelerated decline in chronic stages, but the developmental trajectory that precedes the onset is largely unknown. We propose 4 probable lifetime white matter trajectory models that can be used as the basis for separation between the neurodevelopmental and neurodegenerative etiologies. We argue that a combination of the cross-sectional and longitudinal studies of white matter integrity in patients may be used to bridge the neurodevelopment and degeneration heuristics to advance schizophrenia research.
There is growing recognition that neural oscillations are important in a wide range of perceptual and cognitive functions. One of the key issues in electrophysiological studies of schizophrenia is ...whether high or low frequency oscillations, or both, are related to schizophrenia because many brain functions are modulated with frequency specificities. Many recent electrophysiological studies of schizophrenia have focused on high frequency oscillations at gamma band and in general support gamma band dysfunction in schizophrenia. We discuss the concept that gamma oscillation abnormalities in schizophrenia often occur in the background of oscillation abnormalities of lower frequencies. The review discusses the basic neurobiology for the emergence of oscillations of all frequency bands in association with networks of inhibitory interneurons and the convergence and divergence of such mechanisms in generating high vs low frequency oscillations. We then review the literature of oscillatory frequency abnormalities identified in each frequency band in schizophrenia. By describing some of the key functional roles exerted by gamma, low frequencies, and their cross-frequency coupling, we conceptualize that even isolated alterations in gamma or low frequency oscillations may impact the interactions of high and low frequency bands that are involved in key cognitive functions. The review concludes that studying the full spectrum and the interaction of gamma and low frequency oscillations may be critical for deciphering the complex electrophysiological abnormalities observed in schizophrenia patients.
During speech perception, a central task of the auditory cortex is to analyze complex acoustic patterns to allow detection of the words that encode a linguistic message 1. It is generally thought ...that this process includes at least one intermediate, phonetic, level of representations 2–6, localized bilaterally in the superior temporal lobe 7–9. Phonetic representations reflect a transition from acoustic to linguistic information, classifying acoustic patterns into linguistically meaningful units, which can serve as input to mechanisms that access abstract word representations 10, 11. While recent research has identified neural signals arising from successful recognition of individual words in continuous speech 12–15, no explicit neurophysiological signal has been found demonstrating the transition from acoustic and/or phonetic to symbolic, lexical representations. Here, we report a response reflecting the incremental integration of phonetic information for word identification, dominantly localized to the left temporal lobe. The short response latency, approximately 114 ms relative to phoneme onset, suggests that phonetic information is used for lexical processing as soon as it becomes available. Responses also tracked word boundaries, confirming previous reports of immediate lexical segmentation 16, 17. These new results were further investigated using a cocktail-party paradigm 18, 19 in which participants listened to a mix of two talkers, attending to one and ignoring the other. Analysis indicates neural lexical processing of only the attended, but not the unattended, speech stream. Thus, while responses to acoustic features reflect attention through selective amplification of attended speech, responses consistent with a lexical processing model reveal categorically selective processing.
•MEG responses to continuous speech analyzed at both acoustic and lexical level•Responses indicate phoneme level predictive coding and lexical competition•Phonetic information is processed lexically as early as ∼114 ms after phoneme onset•Lexical responses are restricted to attended speech in a selective attention paradigm
Analyzing MEG responses to continuous narrative speech, Brodbeck et al. find evidence of early lexical processing, involving both phoneme-level predictive coding and lexical competition. In a selective attention paradigm, involving two concurrent speakers, responses indicate that lexical processing is restricted to the attended speech.
Microbial life inhabits deeply buried marine sediments, but the extent of this vast ecosystem remains poorly constrained. Here we provide evidence for the existence of microbial communities in ∼40° ...to 60°C sediment associated with lignite coal beds at ∼1.5 to 2.5 km below the seafloor in the Pacific Ocean off Japan. Microbial methanogenesis was indicated by the isotopic compositions of methane and carbon dioxide, biomarkers, cultivation data, and gas compositions. Concentrations of indigenous microbial cells below 1.5 km ranged from <10 to ∼104 cells cm–3. Peak concentrations occurred in lignite layers, where communities differed markedly from shallower subseafloor communities and instead resembled organotrophic communities in forest soils. This suggests that terrigenous sediments retain indigenous community members tens of millions of years after burial in the seabed.
Nanoparticles can have profound effects on cell biology. Here, we show that after TiO2, SiO2, and hydroxyapatite nanoparticles treatment, TR146 epithelial cell sheet displayed slower migration. Cells ...after exposure to the nanoparticles showed increased cell contractility with significantly impaired wound healing capability however without any apparent cytotoxicity. We showed the mechanism is through nanoparticle-mediated massive disruption of the intracellular microtubule assembly, thereby triggering a positive feedback that promoted stronger substrate adhesions thus leading to limited cell motility.
On one hand, large-scale ranking and selection (R&S) problems require a large amount of computation. On the other hand, parallel computing environments that provide a large capacity for computation ...are becoming prevalent today, and they are accessible by ordinary users. Therefore, solving large-scale R&S problems in parallel computing environments has emerged as an important research topic in recent years. However, directly implementing traditional stagewise procedures and fully sequential procedures in parallel computing environments may encounter problems because either the procedures require too many simulation observations or the procedures’ selection structures induce too many comparisons and too frequent communications among the processors. In this paper, inspired by the knockout-tournament arrangement of tennis Grand Slam tournaments, we develop new R&S procedures to solve large-scale problems in parallel computing environments. We show that no matter whether the variances of the alternatives are known or not, our procedures can theoretically achieve the lowest growth rate on the expected total sample size with respect to the number of alternatives and thus, are optimal in rate. Moreover, common random numbers can be easily adopted in our procedures to further reduce the total sample size. Meanwhile, the comparison time in our procedures is negligible compared with the simulation time, and our procedures barely request for communications among the processors.
Humans are remarkably skilled at listening to one speaker out of an acoustic mixture of several speech sources. Two speakers are easily segregated, even without binaural cues, but the neural ...mechanisms underlying this ability are not well understood. One possibility is that early cortical processing performs a spectrotemporal decomposition of the acoustic mixture, allowing the attended speech to be reconstructed via optimally weighted recombinations that discount spectrotemporal regions where sources heavily overlap. Using human magnetoencephalography (MEG) responses to a 2-talker mixture, we show evidence for an alternative possibility, in which early, active segregation occurs even for strongly spectrotemporally overlapping regions. Early (approximately 70-millisecond) responses to nonoverlapping spectrotemporal features are seen for both talkers. When competing talkers' spectrotemporal features mask each other, the individual representations persist, but they occur with an approximately 20-millisecond delay. This suggests that the auditory cortex recovers acoustic features that are masked in the mixture, even if they occurred in the ignored speech. The existence of such noise-robust cortical representations, of features present in attended as well as ignored speech, suggests an active cortical stream segregation process, which could explain a range of behavioral effects of ignored background speech.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abnormal development can lead to deficits in adult brain function, a trajectory likely underlying adolescent-onset psychiatric conditions such as schizophrenia. Developmental manipulations yielding ...adult deficits in rodents provide an opportunity to explore mechanisms involved in a delayed emergence of anomalies driven by developmental alterations. Here we assessed whether oxidative stress during presymptomatic stages causes adult anomalies in rats with a neonatal ventral hippocampal lesion, a developmental rodent model useful for schizophrenia research. Juvenile and adolescent treatment with the antioxidant N-acetyl cysteine prevented the reduction of prefrontal parvalbumin interneuron activity observed in this model, as well as electrophysiological and behavioral deficits relevant to schizophrenia. Adolescent treatment with the glutathione peroxidase mimic ebselen also reversed behavioral deficits in this animal model. These findings suggest that presymptomatic oxidative stress yields abnormal adult brain function in a developmentally compromised brain, and highlight redox modulation as a potential target for early intervention.
•Presymptomatic antioxidant treatment prevents loss of parvalbumin in NVHL rats•Antioxidant treatment prevents altered prefrontal electrophysiology in NVHL rats•Prepulse inhibition deficits are prevented by antioxidants
Cabungcal et al. show that antioxidant treatment during juvenile and adolescent stages prevents the onset of electrophysiological and behavioral deficits in a developmental model for schizophrenia. The reversal of adolescent-onset deficits suggests redox modulation is a potential target for early intervention.
Robust optimization (RO) is a common approach to tractably obtain safeguarding solutions for optimization problems with uncertain constraints. In this paper, we study a statistical framework to ...integrate data into RO based on learning a prediction set using (combinations of) geometric shapes that are compatible with established RO tools and on a simple data-splitting validation step that achieves finite-sample nonparametric statistical guarantees on feasibility. We demonstrate how our required sample size to achieve feasibility at a given confidence level is independent of the dimensions of both the decision space and the probability space governing the stochasticity, and we discuss some approaches to improve the objective performances while maintaining these dimension-free statistical feasibility guarantees.
This paper was accepted by Yinyu Ye, optimization.