100 research outputs found

    The folding fingerprint of visual cortex reveals the timing of human V1 and V2

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    Primate neocortex contains over 30 visual areas. Recent techniques such as functional magnetic resonance imaging (fMRI) have successfully identified many of these areas in the human brain, but have been of limited value for revealing the temporal dynamics between adjacent visual areas, a critical component of understanding visual cognition. The voltages recorded at the scalp, electroencephalography (EEG), is a direct measure of neural activity that reflects the summed activity across all brain areas. Identifying the cortical sources that contribute to the EEG is a difficult problem. We developed an anatomically constrained dipole search method that solves the traditional problems by combining fMRI, EEG and many stimuli that activate small cortical regions. The method provides a means to validate the extracted waveforms. Both V1 and V2 waveforms have similar onset latencies as well as dynamics that can explain previous controversial findings about the responses of these areas

    Neural responses to apparent motion can be predicted by responses to non-moving stimuli

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    Funding: UK BBSRC grant BB/N018516/1 (JMA).When two objects are presented in alternation at two locations, they are seen as a single object moving from one location to the other. This apparent motion (AM) percept is experienced for objects located at short and also at long distances. However, current models cannot explain how the brain integrates information over large distances to create such long-range AM. This study investigates the neural markers of AM by parcelling out the contribution of spatial and temporal interactions not specific to motion. In two experiments, participants’ EEG was recorded while they viewed two stimuli inducing AM. Different combinations of these stimuli were also shown in a static context to predict an AM neural response where no motion is perceived. We compared the goodness of fit between these different predictions and found consistent results in both experiments. At short-range, the addition of the inhibitory spatial and temporal interactions not specific to motion improved the AM prediction. However, there was no indication that spatial or temporal non-linear interactions were present at long-range. This suggests that short- and long-range AM rely on different neural mechanisms. Importantly, our results also show that at both short- and long-range, responses generated by a moving stimulus could be well predicted from conditions in which no motion is perceived. That is, the EEG response to a moving stimulus is simply a combination of individual responses to non-moving stimuli. This demonstrates a dissociation between the brain response and the subjective percept of motion.Publisher PDFPeer reviewe

    Estimating neural activity from visual areas using functionally defined EEG templates

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    This work was supported by BBSRC grant BB/N018516/1 and Wellcome Trust ISSF 204821/Z/16/Z.Electroencephalography (EEG) is a common and inexpensive method to record neural activity in humans. However, it lacks spatial resolution making it difficult to determine which areas of the brain are responsible for the observed EEG response. Here we present a new easy-to-use method that relies on EEG topographical templates. Using MRI and fMRI scans of 50 participants, we simulated how the activity in each visual area appears on the scalp and averaged this signal to produce functionally defined EEG templates. Once created, these templates can be used to estimate how much each visual area contributes to the observed EEG activity. We tested this method on extensive simulations and on real data. The proposed procedure is as good as bespoke individual source localization methods, robust to a wide range of factors, and has several strengths. First, because it does not rely on individual brain scans, it is inexpensive and can be used on any EEG data set, past or present. Second, the results are readily interpretable in terms of functional brain regions and can be compared across neuroimaging techniques. Finally, this method is easy to understand, simple to use and expandable to other brain sources.Publisher PDFPeer reviewe

    The reliability of pseudoneglect is task dependent

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    Funding: This work was supported by the University of St. Andrews and by Wellcome Trust Institutional Strategic Support Funds (105621/Z/14/Z).Bisection tasks that require individuals to identify the midpoint of a line are often used to assess the presence of biases to spatial attention in both healthy and patient populations. These tasks have helped to uncover a phenomenon called pseudoneglect, a bias towards the left-side of space in healthy individuals. First identified in the tactile domain, pseudoneglect has been subsequently demonstrated in other sensory modalities such as vision. Despite this, the specific reliability of pseudoneglect within individuals across tasks and time has been investigated very little. In this study, we investigated the reliability of response bias within individuals across four separate testing sessions and during three line bisection tasks: landmark, line bisection and tactile rod bisection. Strong reliability was expected within individuals across task and session. Pseudoneglect was found when response bias was averaged across all tasks, for the entire sample. However, individual data showed biases to both left and right, with some participants showing no clear bias, demonstrating individual differences in bias. Significant, cross-session within-individual reliability was found for the landmark and tactile rod bisection tasks respectively, but no significant reliability was observed for the line bisection task. Alongside this, no significant cross-task within-individual reliability was observed. These results highlight the inconsistent nature of pseudoneglect within individuals, particularly across sensory modality. They also provide strong support for the use of the landmark task as the most reliable measure of pseudoneglect.Publisher PDFPeer reviewe

    Assessing direction-specific adaptation using the steady-state visual evoked potential: Results from EEG source imaging

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    Studying directional selectivity using neuroimaging in humans is difficult because the resolution is insufficient to directly access directionally selective activity. Here we used motion adaptation of the steady-state visual evoked potential (SSVEP) and source imaging in the frequency domain to detect brain areas that contain direction-selective cells. This study uses a definitive electrophysiological marker for direction-specific adaptation in the SSVEP to localize cortical areas that are direction selective. It has been shown previously that an oscillating stimulus produces an SSVEP response that is dominated by even harmonics of the stimulus frequency. This pattern of response is consistent with equal population responses to each direction of motion. Prolonged exposure to unidirectional motion induces an asymmetry in the population response that is consistent with adaptation of direction-selective cells. This asymmetry manifests itself in the presence of odd harmonic components after adaptation Critically, the feature that indicates the direction used for adaptation is the phase of the odd-harmonic responses. We recorded this signature of direction selectivity in a group of observers whose retinotopic visual areas had been defined from fMRI mapping. We find direction-specific responses throughout retinotopic cortex, with the largest effect in areas V1 (occipital pole) and V3/V3a (dorsal)

    Speed change discrimination for motion in depth using constant world and retinal speeds

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    This work was supported by the Biotechnology and Biological Sciences Research Council (BBSRC; https://bbsrc.ukri.org/) [grant number BB/M010996/1 to ARIL, BB/N018516/1 to JMA and BB/M001660/1 to JMH].Motion at constant speed in the world maps into retinal motion very differently for lateral motion and motion in depth. The former is close to linear, for the latter, constant speed objects accelerate on the retina as they approach. Motion in depth is frequently studied using speeds that are constant on the retina, and are thus not consistent with real-world constant motion. Our aim here was to test whether this matters: are we more sensitive to real-world motion? We measured speed change discrimination for objects undergoing accelerating retinal motion in depth (consistent with constant real-world speed), and constant retinal motion in depth (consistent with real-world deceleration). Our stimuli contained both looming and binocular disparity cues to motion in depth. We used a speed change discrimination task to obtain thresholds for conditions with and without binocular and looming motion in depth cues. We found that speed change discrimination thresholds were similar for accelerating retinal speed and constant retinal speed and were notably poor compared to classic speed discrimination thresholds. We conclude that the ecologically valid retinal acceleration in our stimuli neither helps, nor hinders, our ability to make judgements in a speed change discrimination task.Publisher PDFPeer reviewe

    The Time Course of Segmentation and Cue-Selectivity in the Human Visual Cortex

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    Texture discontinuities are a fundamental cue by which the visual system segments objects from their background. The neural mechanisms supporting texture-based segmentation are therefore critical to visual perception and cognition. In the present experiment we employ an EEG source-imaging approach in order to study the time course of texture-based segmentation in the human brain. Visual Evoked Potentials were recorded to four types of stimuli in which periodic temporal modulation of a central 3° figure region could either support figure-ground segmentation, or have identical local texture modulations but not produce changes in global image segmentation. The image discontinuities were defined either by orientation or phase differences across image regions. Evoked responses to these four stimuli were analyzed both at the scalp and on the cortical surface in retinotopic and functional regions-of-interest (ROIs) defined separately using fMRI on a subject-by-subject basis. Texture segmentation (tsVEP: segmenting versus non-segmenting) and cue-specific (csVEP: orientation versus phase) responses exhibited distinctive patterns of activity. Alternations between uniform and segmented images produced highly asymmetric responses that were larger after transitions from the uniform to the segmented state. Texture modulations that signaled the appearance of a figure evoked a pattern of increased activity starting at ∼143 ms that was larger in V1 and LOC ROIs, relative to identical modulations that didn't signal figure-ground segmentation. This segmentation-related activity occurred after an initial response phase that did not depend on the global segmentation structure of the image. The two cue types evoked similar tsVEPs up to 230 ms when they differed in the V4 and LOC ROIs. The evolution of the response proceeded largely in the feed-forward direction, with only weak evidence for feedback-related activity

    Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

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    Background: Detailed, comprehensive, and timely reporting on population health by underlying causes of disability and premature death is crucial to understanding and responding to complex patterns of disease and injury burden over time and across age groups, sexes, and locations. The availability of disease burden estimates can promote evidence-based interventions that enable public health researchers, policy makers, and other professionals to implement strategies that can mitigate diseases. It can also facilitate more rigorous monitoring of progress towards national and international health targets, such as the Sustainable Development Goals. For three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has filled that need. A global network of collaborators contributed to the production of GBD 2021 by providing, reviewing, and analysing all available data. GBD estimates are updated routinely with additional data and refined analytical methods. GBD 2021 presents, for the first time, estimates of health loss due to the COVID-19 pandemic. Methods: The GBD 2021 disease and injury burden analysis estimated years lived with disability (YLDs), years of life lost (YLLs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries using 100 983 data sources. Data were extracted from vital registration systems, verbal autopsies, censuses, household surveys, disease-specific registries, health service contact data, and other sources. YLDs were calculated by multiplying cause-age-sex-location-year-specific prevalence of sequelae by their respective disability weights, for each disease and injury. YLLs were calculated by multiplying cause-age-sex-location-year-specific deaths by the standard life expectancy at the age that death occurred. DALYs were calculated by summing YLDs and YLLs. HALE estimates were produced using YLDs per capita and age-specific mortality rates by location, age, sex, year, and cause. 95% uncertainty intervals (UIs) were generated for all final estimates as the 2·5th and 97·5th percentiles values of 500 draws. Uncertainty was propagated at each step of the estimation process. Counts and age-standardised rates were calculated globally, for seven super-regions, 21 regions, 204 countries and territories (including 21 countries with subnational locations), and 811 subnational locations, from 1990 to 2021. Here we report data for 2010 to 2021 to highlight trends in disease burden over the past decade and through the first 2 years of the COVID-19 pandemic. Findings: Global DALYs increased from 2·63 billion (95% UI 2·44–2·85) in 2010 to 2·88 billion (2·64–3·15) in 2021 for all causes combined. Much of this increase in the number of DALYs was due to population growth and ageing, as indicated by a decrease in global age-standardised all-cause DALY rates of 14·2% (95% UI 10·7–17·3) between 2010 and 2019. Notably, however, this decrease in rates reversed during the first 2 years of the COVID-19 pandemic, with increases in global age-standardised all-cause DALY rates since 2019 of 4·1% (1·8–6·3) in 2020 and 7·2% (4·7–10·0) in 2021. In 2021, COVID-19 was the leading cause of DALYs globally (212·0 million [198·0–234·5] DALYs), followed by ischaemic heart disease (188·3 million [176·7–198·3]), neonatal disorders (186·3 million [162·3–214·9]), and stroke (160·4 million [148·0–171·7]). However, notable health gains were seen among other leading communicable, maternal, neonatal, and nutritional (CMNN) diseases. Globally between 2010 and 2021, the age-standardised DALY rates for HIV/AIDS decreased by 47·8% (43·3–51·7) and for diarrhoeal diseases decreased by 47·0% (39·9–52·9). Non-communicable diseases contributed 1·73 billion (95% UI 1·54–1·94) DALYs in 2021, with a decrease in age-standardised DALY rates since 2010 of 6·4% (95% UI 3·5–9·5). Between 2010 and 2021, among the 25 leading Level 3 causes, age-standardised DALY rates increased most substantially for anxiety disorders (16·7% [14·0–19·8]), depressive disorders (16·4% [11·9–21·3]), and diabetes (14·0% [10·0–17·4]). Age-standardised DALY rates due to injuries decreased globally by 24·0% (20·7–27·2) between 2010 and 2021, although improvements were not uniform across locations, ages, and sexes. Globally, HALE at birth improved slightly, from 61·3 years (58·6–63·6) in 2010 to 62·2 years (59·4–64·7) in 2021. However, despite this overall increase, HALE decreased by 2·2% (1·6–2·9) between 2019 and 2021. Interpretation: Putting the COVID-19 pandemic in the context of a mutually exclusive and collectively exhaustive list of causes of health loss is crucial to understanding its impact and ensuring that health funding and policy address needs at both local and global levels through cost-effective and evidence-based interventions. A global epidemiological transition remains underway. Our findings suggest that prioritising non-communicable disease prevention and treatment policies, as well as strengthening health systems, continues to be crucially important. The progress on reducing the burden of CMNN diseases must not stall; although global trends are improving, the burden of CMNN diseases remains unacceptably high. Evidence-based interventions will help save the lives of young children and mothers and improve the overall health and economic conditions of societies across the world. Governments and multilateral organisations should prioritise pandemic preparedness planning alongside efforts to reduce the burden of diseases and injuries that will strain resources in the coming decades. Funding: Bill & Melinda Gates Foundation

    Prediction of second neurological attack in patients with clinically isolated syndrome using support vector machines

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    The aim of this study is to predict the conversion from clinically isolated syndrome to clinically definite multiple sclerosis using support vector machines. The two groups of converters and non-converters are classified using features that were calculated from baseline data of 73 patients. The data consists of standard magnetic resonance images, binary lesion masks, and clinical and demographic information. 15 features were calculated and all combinations of them were iteratively tested for their predictive capacity using polynomial kernels and radial basis functions with leave-one-out cross-validation. The accuracy of this prediction is up to 86.4% with a sensitivity and specificity in the same range indicating that this is a feasible approach for the prediction of a second clinical attack in patients with clinically isolated syndromes, and that the chosen features are appropriate. The two features gender and location of onset lesions have been used in all feature combinations leading to a high accuracy suggesting that they are highly predictive. However, it is necessary to add supporting features to maximise the accuracy. © 2013 IEEE
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