Face-gender discrimination is possible in the near-absence of attention

The attentional cost associated with the visual discrimination of the gender of a face was investigated. Participants performed a face-gender discrimination task either alone (single-task) or concurrently (dual-task) with a known attentional demanding task (5-letter T/L discrimination). Overall performance on face-gender discrimination suffered remarkably little under the dual-task condition compared to the single-task condition. Similar results were obtained in experiments that controlled for potential training effects or the use of low-level cues in this discrimination task. Our results provide further evidence against the notion that only low-level representations can be accessed outside the focus of attention

Face identification in the near-absence of focal attention

In contrast to artificial geometric shapes, natural scenes and face-gender can be processed even when spatial attention is not fully available. In this study, we investigate whether a finer discrimination, at the level of the individual, is possible in the near-absence of focal attention. Using the paradigm, subjects performed face identification on faces of celebrities and relatively unfamiliar individual, along with a task that is known to engage spatial attention. We find that face-identification performance is only modestly impaired under dual-task conditions. These results suggest that the visual system is well able to make complex judgments of natural stimuli, even when attention is not full available

The Continuous Wagon Wheel Illusion Is Associated with Changes in Electroencephalogram Power at ~13 Hz

Continuously moving objects sometimes appear to spontaneously reverse their motion direction. The mechanisms underlying this bistable phenomenon (the “continuous wagon wheel illusion”) are heavily debated, but one interpretation suggests that motion information is perceived in discrete episodes at a rate between 10 and 15 Hz. Here, we asked observers to report the perceived direction of a continuously rotating wheel while 32-channel electroencephalogram (EEG) was recorded. We then separated periods of perceived true from illusory (reversed) motion and compared the EEG power spectrum under these two perceptually distinct yet physically identical conditions. The only reliable difference was observed ∼13 Hz over centroparietal electrodes, independent of the temporal frequency of the wheel. Thus, it is likely to reflect internal processes rather than purely stimulus-driven activity. EEG power (13 Hz) decreased before the onset of illusory motion and increased before transitions back to real motion. Using this relationship, it was possible to predict above chance, on a trial-by-trial basis, the direction of the upcoming perceptual transition. These data are compatible with the idea that motion perception occurs in snapshots <100 ms in duration

A Single-Neuron Correlate of Change Detection and Change Blindness in the Human Medial Temporal Lobe

Observers are often unaware of changes in their visual environment when attention is not focused at the location of the change [1,2,3,4]. Because of its rather intriguing nature, this phenomenon, known as change blindness, has been extensively studied with psychophysics [5,6,7] as well as with fMRI [8,9,10,11]. However, whether change blindness can be tracked in the activity of single cells is not clear. To explore the neural correlates of change detection and change blindness, we recorded from single neurons in the human medial temporal lobe (MTL) during a change-detection paradigm. The preferred pictures of the visually responsive units elicited significantly higher firing rates on the attended trials when subjects correctly identified a change (change detection) compared to the unattended trials when they missed it (change blindness). On correct trials, the firing activity of individual units allowed us to predict the occurrence of a change, on a trial-by-trial basis, with 67% accuracy. In contrast, this prediction was at chance for incorrect, unattended trials. The firing rates of visually selective MTL cells thus constitute a neural correlate of change detection

Reading the mind's eye: Decoding category information during mental imagery

Category information for visually presented objects can be read out from multi-voxel patterns of fMRI activity in ventral–temporal cortex. What is the nature and reliability of these patterns in the absence of any bottom–up visual input, for example, during visual imagery? Here, we first ask how well category information can be decoded for imagined objects and then compare the representations evoked during imagery and actual viewing. In an fMRI study, four object categories (food, tools, faces, buildings) were either visually presented to subjects, or imagined by them. Using pattern classification techniques, we could reliably decode category information (including for non-special categories, i.e., food and tools) from ventral–temporal cortex in both conditions, but only during actual viewing from retinotopic areas. Interestingly, in temporal cortex when the classifier was trained on the viewed condition and tested on the imagery condition, or vice versa, classification performance was comparable to within the imagery condition. The above results held even when we did not use information in the specialized category-selective areas. Thus, the patterns of representation during imagery and actual viewing are in fact surprisingly similar to each other. Consistent with this observation, the maps of “diagnostic voxels” (i.e., the classifier weights) for the perception and imagery classifiers were more similar in ventral–temporal cortex than in retinotopic cortex. These results suggest that in the absence of any bottom–up input, cortical back projections can selectively re-activate specific patterns of neural activity

Theta-phase dependent neuronal coding during sequence learning in human single neurons

This work was supported by grants from the French Agence Nationale de la Recherche (ANR-12-JSH2-0004-01 and ANR AI-REPS–18-CE37-0007-01), the Fyssen foundation, and the Université Paul Sabatier, Toulouse, France (BQR, 2009 and Appel à Projets de Recherche Labellisés, 2013), to L.R., the European Research Council (ERC Consolidator Grant P-Cycles number 614244), the French Agence Nationale de la Recherche (ANR OSCI-DEEP ANR-19-NEUC-0004), and an ANITI (Artificial and Natural Intelligence Toulouse Institute) Research Chair (ANR-19-PI3A-0004) to R.V., the Studienstiftung des Deutschen Volkes (German Academic Scholarship Foundation) to B.Z., the European Union (ERC Grant Agreement n. 339490 “Cortic_al_gorithms” and grant agreements 720270 and 785907 “Human Brain Project SGA1 and SGA2’) and the Friends Foundation of the Netherlands Institute for Neuroscience to P.R.R.The ability to maintain a sequence of items in memory is a fundamental cognitive function. In the rodent hippocampus, the representation of sequentially organized spatial locations is reflected by the phase of action potentials relative to the theta oscillation (phase precession). We investigated whether the timing of neuronal activity relative to the theta brain oscillation also reflects sequence order in the medial temporal lobe of humans. We used a task in which human participants learned a fixed sequence of pictures and recorded single neuron and local field potential activity with implanted electrodes. We report that spikes for three consecutive items in the sequence (the preferred stimulus for each cell, as well as the stimuli immediately preceding and following it) were phase-locked at distinct phases of the theta oscillation. Consistent with phase precession, spikes were fired at progressively earlier phases as the sequence advanced. These findings generalize previous findings in the rodent hippocampus to the human temporal lobe and suggest that encoding stimulus information at distinct oscillatory phases may play a role in maintaining sequential order in memory.Publisher PDFPeer reviewe

Local Field Potentials and Spikes in the Human Medial Temporal Lobe are Selective to Image Category

Local field potentials (LFPs) reflect the averaged dendrosomatic activity of synaptic signals of large neuronal populations. In this study, we investigate the selectivity of LFPs and single neuron activity to semantic categories of visual stimuli in the medial temporal lobe of nine neurosurgical patients implanted with intracranial depth electrodes for clinical reasons. Strong selectivity to the category of presented images was found for the amplitude of LFPs in 8% of implanted microelectrodes and for the firing rates of single and multiunits in 14% of microelectrodes. There was little overlap between the LFP- and spike-selective microelectrodes. Separate analysis of the power and phase of LFPs revealed that the mean phase was category-selective around the θ frequency range and that the power of the LFPs was category-selective for high frequencies around the γ rhythm. Of the 36 microelectrodes with amplitude-selective LFPs, 30 were found in the hippocampus. Finally, it was possible to readout information about the category of stimuli presented to the patients with both spikes and LFPs. Combining spiking and LFP activity enhanced the decoding accuracy in comparison with the accuracy obtained with each signal alone, especially for short time intervals

Invariant visual representation by single neurons in the human brain

It takes a fraction of a second to recognize a person or an object even when seen under strikingly different conditions. How such a robust, high-level representation is achieved by neurons in the human brain is still unclear. In monkeys, neurons in the upper stages of the ventral visual pathway respond to complex images such as faces and objects and show some degree of invariance to metric properties such as the stimulus size, position and viewing angle. We have previously shown that neurons in the human medial temporal lobe (MTL) fire selectively to images of faces, animals, objects or scenes. Here we report on a remarkable subset of MTL neurons that are selectively activated by strikingly different pictures of given individuals, landmarks or objects and in some cases even by letter strings with their names. These results suggest an invariant, sparse and explicit code, which might be important in the transformation of complex visual percepts into long-term and more abstract memories

Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980-2017 : a systematic analysis for the Global Burden of Disease Study 2017

Background Global development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017. Methods The causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODErn), to generate cause fractions and cause specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised. Findings At the broadest grouping of causes of death (Level 1), non-communicable diseases (NC Ds) comprised the greatest fraction of deaths, contributing to 73.4% (95% uncertainty interval [UI] 72.5-74.1) of total deaths in 2017, while communicable, maternal, neonatal, and nutritional (CMNN) causes accounted for 186% (17.9-19.6), and injuries 8.0% (7.7-8.2). Total numbers of deaths from NCD causes increased from 2007 to 2017 by 22.7% (21.5-23.9), representing an additional 7.61 million (7. 20-8.01) deaths estimated in 2017 versus 2007. The death rate from NCDs decreased globally by 7.9% (7.08.8). The number of deaths for CMNN causes decreased by 222% (20.0-24.0) and the death rate by 31.8% (30.1-33.3). Total deaths from injuries increased by 2.3% (0-5-4-0) between 2007 and 2017, and the death rate from injuries decreased by 13.7% (12.2-15.1) to 57.9 deaths (55.9-59.2) per 100 000 in 2017. Deaths from substance use disorders also increased, rising from 284 000 deaths (268 000-289 000) globally in 2007 to 352 000 (334 000-363 000) in 2017. Between 2007 and 2017, total deaths from conflict and terrorism increased by 118.0% (88.8-148.6). A greater reduction in total deaths and death rates was observed for some CMNN causes among children younger than 5 years than for older adults, such as a 36.4% (32.2-40.6) reduction in deaths from lower respiratory infections for children younger than 5 years compared with a 33.6% (31.2-36.1) increase in adults older than 70 years. Globally, the number of deaths was greater for men than for women at most ages in 2017, except at ages older than 85 years. Trends in global YLLs reflect an epidemiological transition, with decreases in total YLLs from enteric infections, respirator}, infections and tuberculosis, and maternal and neonatal disorders between 1990 and 2017; these were generally greater in magnitude at the lowest levels of the Socio-demographic Index (SDI). At the same time, there were large increases in YLLs from neoplasms and cardiovascular diseases. YLL rates decreased across the five leading Level 2 causes in all SDI quintiles. The leading causes of YLLs in 1990 neonatal disorders, lower respiratory infections, and diarrhoeal diseases were ranked second, fourth, and fifth, in 2017. Meanwhile, estimated YLLs increased for ischaemic heart disease (ranked first in 2017) and stroke (ranked third), even though YLL rates decreased. Population growth contributed to increased total deaths across the 20 leading Level 2 causes of mortality between 2007 and 2017. Decreases in the cause-specific mortality rate reduced the effect of population growth for all but three causes: substance use disorders, neurological disorders, and skin and subcutaneous diseases. Interpretation Improvements in global health have been unevenly distributed among populations. Deaths due to injuries, substance use disorders, armed conflict and terrorism, neoplasms, and cardiovascular disease are expanding threats to global health. For causes of death such as lower respiratory and enteric infections, more rapid progress occurred for children than for the oldest adults, and there is continuing disparity in mortality rates by sex across age groups. Reductions in the death rate of some common diseases are themselves slowing or have ceased, primarily for NCDs, and the death rate for selected causes has increased in the past decade. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.Peer reviewe

Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017.

The Global Burden of Diseases, Injuries and Risk Factors 2017 includes a comprehensive assessment of incidence, prevalence, and years lived with disability (YLDs) for 354 causes in 195 countries and territories from 1990 to 2017. Previous GBD studies have shown how the decline of mortality rates from 1990 to 2016 has led to an increase in life expectancy, an ageing global population, and an expansion of the non-fatal burden of disease and injury. These studies have also shown how a substantial portion of the world's population experiences non-fatal health loss with considerable heterogeneity among different causes, locations, ages, and sexes. Ongoing objectives of the GBD study include increasing the level of estimation detail, improving analytical strategies, and increasing the amount of high-quality data. METHODS: We estimated incidence and prevalence for 354 diseases and injuries and 3484 sequelae. We used an updated and extensive body of literature studies, survey data, surveillance data, inpatient admission records, outpatient visit records, and health insurance claims, and additionally used results from cause of death models to inform estimates using a total of 68 781 data sources. Newly available clinical data from India, Iran, Japan, Jordan, Nepal, China, Brazil, Norway, and Italy were incorporated, as well as updated claims data from the USA and new claims data from Taiwan (province of China) and Singapore. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring consistency between rates of incidence, prevalence, remission, and cause of death for each condition. YLDs were estimated as the product of a prevalence estimate and a disability weight for health states of each mutually exclusive sequela, adjusted for comorbidity. We updated the Socio-demographic Index (SDI), a summary development indicator of income per capita, years of schooling, and total fertility rate. Additionally, we calculated differences between male and female YLDs to identify divergent trends across sexes. GBD 2017 complies with the Guidelines for Accurate and Transparent Health Estimates Reporting