EEG is known to contain considerable inter-trial and inter-subject variability, which poses a challenge in any group-level EEG analyses. A true experimental effect must be reproducible even with ...variabilities in trials, sessions, and subjects. Extracting components that are reproducible across trials and subjects benefits both understanding common mechanisms in neural processing of cognitive functions and building robust brain-computer interfaces. This study extends our previous method (task-related component analysis, TRCA) by maximizing not only trial-by-trial reproducibility within single subjects but also similarity across a group of subjects, hence referred to as group TRCA (gTRCA). The problem of maximizing reproducibility of time series across trials and subjects is formulated as a generalized eigenvalue problem. We applied gTRCA to EEG data recorded from 35 subjects during a steady-state visual-evoked potential (SSVEP) experiment. The results revealed: (1) The group-representative data computed by gTRCA showed higher and consistent spectral peaks than other conventional methods; (2) Scalp maps obtained by gTRCA showed estimated source locations consistently within the occipital lobe; And (3) the high-dimensional features extracted by gTRCA are consistently mapped to a low-dimensional space. We conclude that gTRCA offers a framework for group-level EEG data analysis and brain-computer interfaces alternative in complement to grand averaging.
This review surveys physiological, behavioral, and morphological evidence converging to the view of the cerebro-cerebellum as loci of internal forward models. The cerebro-cerebellum, the ...phylogenetically newest expansion in the cerebellum, receives convergent inputs from cortical, subcortical, and spinal sources, and is thought to perform the predictive computation for both motor control, motor learning, and cognitive functions. This predictive computation is known as an internal forward model. First, we elucidate the theoretical foundations of an internal forward model and its role in motor control and motor learning within the framework of the optimal feedback control model. Then, we discuss a neural mechanism that generates various patterns of outputs from the cerebro-cerebellum. Three lines of supporting evidence for the internal-forward-model hypothesis are presented in detail. First, we provide physiological evidence that the cerebellar outputs (activities of dentate nucleus cells) are predictive for the cerebellar inputs activities of mossy fibers (MFs). Second, we provide behavioral evidence that a component of movement kinematics is predictive for target motion in control subjects but lags behind a target motion in patients with cerebellar ataxia. Third, we provide morphological evidence that the cerebellar cortex and the dentate nucleus receive separate MF projections, a prerequisite for optimal estimation. Finally, we speculate that the predictive computation in the cerebro-cerebellum could be deployed to not only motor control but also to non-motor, cognitive functions. This review concludes that the predictive computation of the internal forward model is the unifying algorithmic principle for understanding diverse functions played by the cerebro-cerebellum.
Background: Japan is one of the world’s largest tobacco epidemic countries but few studies have focused on socioeconomic inequalities. We aimed to examine whether socioeconomic inequalities in ...smoking have reduced in Japan in recent times. Methods: We analyzed data from the Comprehensive Survey of Living Conditions, a large nationally representative survey conducted every 3 years (n ≈ 700,000 per year) in Japan, during 2001–2016. Age-standardized smoking prevalence was computed based on occupational class and educational level. We calculated smoking prevalence difference (PD) and ratio (PR) of (a) manual workers versus upper non-manual workers and (b) low versus high educational level. The slope index of inequality (SII) and relative index inequality (RII) by educational level were used as inequality measures. Results: Overall smoking prevalence (25–64 years) decreased from 56.0% to 38.4% among men and from 17.0% to 13.0% among women during 2001–2016. The PD between manual and upper non-manual workers (25–64 years) increased from 11.9% (95% confidence interval CI, 11.0–12.9%) to 14.6% (95% CI, 13.5–15.6%) during 2001–2016. In 2016, smoking prevalence (25–64 years) for low, middle, and highly educated individuals were 57.8%, 43.9%, and 27.8% for men, and 34.7%, 15.9%, and 5.6% for women, respectively. SII and RII by educational level increased among both sexes. Larger socioeconomic differences in smoking prevalence were observed in younger generations, which suggests that socioeconomic inequalities in smoking evolve in a cohort pattern. Conclusions: Socioeconomic inequalities in smoking widened between 2001 and 2016 in Japan, which indicates that health inequalities will continue to exist in near future.
The ability to perceive and recognise a reflected mirror image as self (mirror self-recognition, MSR) is considered a hallmark of cognition across species. Although MSR has been reported in mammals ...and birds, it is not known to occur in any other major taxon. Potentially limiting our ability to test for MSR in other taxa is that the established assay, the mark test, requires that animals display contingency testing and self-directed behaviour. These behaviours may be difficult for humans to interpret in taxonomically divergent animals, especially those that lack the dexterity (or limbs) required to touch a mark. Here, we show that a fish, the cleaner wrasse Labroides dimidiatus, shows behaviour that may reasonably be interpreted as passing through all phases of the mark test: (i) social reactions towards the reflection, (ii) repeated idiosyncratic behaviours towards the mirror, and (iii) frequent observation of their reflection. When subsequently provided with a coloured tag in a modified mark test, fish attempt to remove the mark by scraping their body in the presence of a mirror but show no response towards transparent marks or to coloured marks in the absence of a mirror. This remarkable finding presents a challenge to our interpretation of the mark test—do we accept that these behavioural responses, which are taken as evidence of self-recognition in other species during the mark test, lead to the conclusion that fish are self-aware? Or do we rather decide that these behavioural patterns have a basis in a cognitive process other than self-recognition and that fish do not pass the mark test? If the former, what does this mean for our understanding of animal intelligence? If the latter, what does this mean for our application and interpretation of the mark test as a metric for animal cognitive abilities?
This Short Report received both positive and negative reviews by experts. The Academic Editor has written an accompanying Primer that we are publishing alongside this article (https://doi.org/10.1371/journal.pbio.3000112). The linked Primer presents a complementary expert perspective; it discusses how the current study should be interpreted in the context of evidence for and against self-awareness in a wide range of animals.
Background: The 2015 Japan Standard Population (JSP) was established in response to changes in the age structure. However, the effects of major updates, especially the recategorization of older age ...groups, for interpreting various health metrics have not been clarified.Methods: Population data were collected and estimated for older age categories (85–89, 90–94, and ≥95 years). Data on the number of deaths were also collected from the Vital Statistics. We recalculated the all-cause and leading cause-specific age-standardized mortality rate (ASMR) using the 2015 JSP by the direct standardization method for data from 1950 to 2020. We compared ASMRs calculated using the 2015 JSP with those calculated using the 1985 JSP. Pearson’s correlation coefficients were used to evaluate the consistency of mortality trends between the 2015 and 1985 JSPs.Results: The absolute all-cause ASMRs calculated using the 2015 JSP were 2.22–3.00 times higher than those calculated using the 1985 JSP. The ASMR ratios increased gradually over time. While trends in all-cause and cause-specific ASMRs calculated using the 2015 JSP and 1985 JSP were generally highly correlated (Pearson’s correlation coefficient r = 0.993 for all-cause), correlations were relatively low for malignant neoplasms (r = 0.720 for men and r = 0.581 for women) and pneumonia/bronchitis (r = 0.543 for men and r = 0.559 for women) due to non-monotonous trends over time and fluctuations in earlier time periods.Conclusion: The effect of introducing the new JSP for interpreting trends in all-cause mortality was considered minimal. However, caution is needed when interpreting trends in some cause-specific mortality rates.
•How exactly the motor cortex controls body movements remains an unresolved problem.•Electrophysiological findings support both kinematic and dynamic coding hypotheses.•Recent computational models ...explain characteristics of motor neuronal responses.
Specialization of motor function in the frontal lobe was first discovered in the seminal experiments by Fritsch and Hitzig and subsequently by Ferrier in the 19th century. It is, however, ironical that the functional and computational role of the motor cortex still remains unresolved. A computational understanding of the motor cortex equals to understanding what movement variables the motor neurons represent (movement representation problem) and how such movement variables are computed through the interaction with anatomically connected areas (neural computation problem). Electrophysiological experiments in the 20th century demonstrated that the neural activities in motor cortex correlated with a number of motor-related and cognitive variables, thereby igniting the controversy over movement representations in motor cortex. Despite substantial experimental efforts, the overwhelming complexity found in neural activities has impeded our understanding of how movements are represented in the motor cortex. Recent progresses in computational modeling have rekindled this controversy in the 21st century. Here, I review the recent developments in computational models of the motor cortex, with a focus on optimality models, recurrent neural network models and spatial dynamics models. Although individual models provide consistent pictures within their domains, our current understanding about functions of the motor cortex is still fragmented.
Reproducibility of experimental results lies at the heart of scientific disciplines. Here we propose a signal processing method that extracts task-related components by maximizing the reproducibility ...during task periods from neuroimaging data. Unlike hypothesis-driven methods such as general linear models, no specific time courses are presumed, and unlike data-driven approaches such as independent component analysis, no arbitrary interpretation of components is needed. Task-related components are constructed by a linear, weighted sum of multiple time courses, and its weights are optimized so as to maximize inter-block correlations (CorrMax) or covariances (CovMax). Our analysis method is referred to as task-related component analysis (TRCA). The covariance maximization is formulated as a Rayleigh–Ritz eigenvalue problem, and corresponding eigenvectors give candidates of task-related components. In addition, a systematic statistical test based on eigenvalues is proposed, so task-related and -unrelated components are classified objectively and automatically. The proposed test of statistical significance is found to be independent of the degree of autocorrelation in data if the task duration is sufficiently longer than the temporal scale of autocorrelation, so TRCA can be applied to data with autocorrelation without any modification. We demonstrate that simple extensions of TRCA can provide most distinctive signals for two tasks and can integrate multiple modalities of information to remove task-unrelated artifacts. TRCA was successfully applied to synthetic data as well as near-infrared spectroscopy (NIRS) data of finger tapping. There were two statistically significant task-related components; one was a hemodynamic response, and another was a piece-wise linear time course. In summary, we conclude that TRCA has a wide range of applications in multi-channel biophysical and behavioral measurements.
► Task-relatedness is defined by consistent appearance of a signal in task blocks. ► Task-related components are constructed by a weighted sum of multiple time courses. ► The weights are optimized to maximize covariance of components between blocks. ► Task-related component analysis (TRCA) is successfully applied to fNIRS data.
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