scholarly journals Ramp-shaped neural tuning supports graded population-level representation of the object-to-scene continuum

2022 ◽  
Author(s):  
Jeongho Park ◽  
Emilie Josephs ◽  
Talia Konkle
Keyword(s):  
Spatial Scale ◽  
Neural Coding ◽  
Large Scale ◽  
Temporal Cortex ◽  
Population Level ◽  
Linear Representation ◽  
Small Region ◽  
Indoor Environments ◽  
Brain Responses ◽  
Class Room

We can easily perceive the spatial scale depicted in a picture, regardless of whether it is a small space (e.g., a close-up view of a chair) or a much larger space (e.g., an entire class room). How does the human visual system encode this continuous dimension? Here, we investigated the underlying neural coding of depicted spatial scale, by examining the voxel tuning and topographic organization of brain responses. We created naturalistic yet carefully-controlled stimuli by constructing virtual indoor environments, and rendered a series of snapshots to smoothly sample between a close-up view of the central object and far-scale view of the full environment (object-to-scene continuum). Human brain responses were measured to each position using functional magnetic resonance imaging. We did not find evidence for a smooth topographic mapping for the object-to-scene continuum on the cortex. Instead, we observed large swaths of cortex with opposing ramp-shaped profiles, with highest responses to one end of the object-to-scene continuum or the other, and a small region showing a weak tuning to intermediate scale views. Importantly, when we considered the multi-voxel patterns of the entire ventral occipito-temporal cortex, we found smooth and linear representation of the object-to-scene continuum. Thus, our results together suggest that depicted spatial scale is coded parametrically in large-scale population codes across the entire ventral occipito-temporal cortex.

scholarly journals Fast Readout of Object Identity from Macaque Inferior Temporal Cortex

Science ◽  
2005 ◽  
Vol 310 (5749) ◽  
pp. 863-866 ◽  
Author(s):  
Chou P. Hung ◽  
Gabriel Kreiman ◽  
Tomaso Poggio ◽  
James J. DiCarlo
Keyword(s):  
Neural Coding ◽  
Temporal Cortex ◽  
Population Level ◽  
Inferior Temporal Cortex ◽  
Object Identity ◽  
Neuronal Populations ◽  
Novel Objects ◽  
Coarse Information ◽  
Short Time

Understanding the brain computations leading to object recognition requires quantitative characterization of the information represented in inferior temporal (IT) cortex. We used a biologically plausible, classifier-based readout technique to investigate the neural coding of selectivity and invariance at the IT population level. The activity of small neuronal populations (∼100 randomly selected cells) over very short time intervals (as small as 12.5 milliseconds) contained unexpectedly accurate and robust information about both object “identity” and “category.” This information generalized over a range of object positions and scales, even for novel objects. Coarse information about position and scale could also be read out from the same population.

scholarly journals Large-scale hyperparameter search for predicting human brain responses in the Algonauts challenge

2019 ◽  
Author(s):  
Kamila M. Jozwik ◽  
Michael Lee ◽  
Tiago Marques ◽  
Martin Schrimpf ◽  
Pouya Bashivan
Keyword(s):  
Large Scale ◽  
Visual Stimuli ◽  
Temporal Cortex ◽  
Image Features ◽  
Inferior Temporal Cortex ◽  
Network Architectures ◽  
Image Preprocessing ◽  
Neural Representations ◽  
Brain Responses ◽  
Early Visual Cortex

Image features computed by specific convolutional artificial neural networks (ANNs) can be used to make state-of-the-art predictions of primate ventral stream responses to visual stimuli.However, in addition to selecting the specific ANN and layer that is used, the modeler makes other choices in preprocessing the stimulus image and generating brain predictions from ANN features. The effect of these choices on brain predictivity is currently underexplored.Here, we directly evaluated many of these choices by performing a grid search over network architectures, layers, image preprocessing strategies, feature pooling mechanisms, and the use of dimensionality reduction. Our goal was to identify model configurations that produce responses to visual stimuli that are most similar to the human neural representations, as measured by human fMRI and MEG responses. In total, we evaluated more than 140,338 model configurations. We found that specific configurations of CORnet-S best predicted fMRI responses in early visual cortex, and CORnet-R and SqueezeNet models best predicted fMRI responses in inferior temporal cortex. We found specific configurations of VGG-16 and CORnet-S models that best predicted the MEG responses.We also observed that downsizing input images to ~50-75% of the input tensor size lead to better performing models compared to no downsizing (the default choice in most brain models for vision). Taken together, we present evidence that brain predictivity is sensitive not only to which ANN architecture and layer is used, but choices in image preprocessing and feature postprocessing, and these choices should be further explored.

scholarly journals Species and characteristics of volatile organic compounds emitted from an auto-repair painting workshop

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
M. Y. Song ◽  
H. Chun
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Large Scale ◽  
Butyl Acetate ◽  
Small Scale ◽  
Indoor Environments ◽  
Voc Emissions ◽  
Volatile Organic ◽  
Before And After ◽  
Adsorption Systems

AbstractVolatile organic compounds (VOCs) are secondary pollutant precursors having adverse impacts on the environment and human health. Although VOC emissions, their sources, and impacts have been investigated, the focus has been on large-scale industrial sources or indoor environments; studies on relatively small-scale enterprises (e.g., auto-repair workshops) are lacking. Here, we performed field VOC measurements for an auto-repair painting facility in Korea and analyzed the characteristics of VOCs emitted from the main painting workshop (top coat). The total VOC concentration was 5069–8058 ppb, and 24–35 species were detected. The VOCs were mainly identified as butyl acetate, toluene, ethylbenzene, and xylene compounds. VOC characteristics differed depending on the paint type. Butyl acetate had the highest concentration in both water- and oil-based paints; however, its concentration and proportion were higher in the former (3256 ppb, 65.5%) than in the latter (2449 ppb, 31.1%). Comparing VOC concentration before and after passing through adsorption systems, concentrations of most VOCs were lower at the outlets than the inlets of the adsorption systems, but were found to be high at the outlets in some workshops. These results provide a theoretical basis for developing effective VOC control systems and managing VOC emissions from auto-repair painting workshops.

scholarly journals Neuroimaging Findings in Adolescents and Young Adults with Anorexia Nervosa: A Systematic Review

Children ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 137
Author(s):  
Kalliopi Kappou ◽  
Myrto Ntougia ◽  
Aikaterini Kourtesi ◽  
Eleni Panagouli ◽  
Elpis Vlachopapadopoulou ◽  
...  
Keyword(s):  
Systematic Review ◽  
Young Adults ◽  
Anorexia Nervosa ◽  
Large Scale ◽  
Temporal Cortex ◽  
Adolescents And Young Adults ◽  
Pubmed Central ◽  
Executive Control Network ◽  
Young Females ◽  
Weight Restoration

Background: Anorexia nervosa (AN) is a serious, multifactorial mental disorder affecting predominantly young females. This systematic review examines neuroimaging findings in adolescents and young adults up to 24 years old, in order to explore alterations associated with disease pathophysiology. Methods: Eligible studies on structural and functional brain neuroimaging were sought systematically in PubMed, CENTRAL and EMBASE databases up to 5 October 2020. Results: Thirty-three studies were included, investigating a total of 587 patients with a current diagnosis of AN and 663 healthy controls (HC). Global and regional grey matter (GM) volume reduction as well as white matter (WM) microstructure alterations were detected. The mainly affected regions were the prefrontal, parietal and temporal cortex, hippocampus, amygdala, insula, thalamus and cerebellum as well as various WM tracts such as corona radiata and superior longitudinal fasciculus (SLF). Regarding functional imaging, alterations were pointed out in large-scale brain networks, such as default mode network (DMN), executive control network (ECN) and salience network (SN). Most findings appear to reverse after weight restoration. Specific limitations of neuroimaging studies in still developing individuals are also discussed. Conclusions: Structural and functional alterations are present in the early course of the disease, most of them being partially or totally reversible. Nonetheless, neuroimaging findings have been open to many biological interpretations. Thus, more studies are needed to clarify their clinical significance.

scholarly journals 214 Longitudinal Changes in Sleep Duration, Timing, Variability, and Stages during the COVID-19 Pandemic: Large-Scale Fitbit Data

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A86-A86
Author(s):  
Michael Grandner ◽  
Naghmeh Rezaei
Keyword(s):  
New York ◽  
Los Angeles ◽  
San Francisco ◽  
Sleep Duration ◽  
Large Scale ◽  
Age Groups ◽  
Population Level ◽  
Sleep Stages ◽  
Longitudinal Changes ◽  
Timing Variability

Abstract Introduction The COVID-19 pandemic has resulted in societal-level changes to sleep and other behavioral patterns. Objective, longitudinal data would allow for a greater understanding of sleep-related changes at the population level. Methods N= 163,524 deidentified active Fitbit users from 6 major US cities contributed data, representing areas particularly hard-hit by the pandemic (Chicago, Houston, Los Angeles, New York, San Francisco, and Miami). Sleep variables extracted include nightly and weekly mean sleep duration and bedtime, variability (standard deviation) of sleep duration and bedtime, and estimated arousals and sleep stages. Deviation from similar timeframes in 2019 were examined. All analyses were performed in Python. Results These data detail how sleep duration and timing changed longitudinally, stratified by age group and gender, relative to previous years’ data. Overall, 2020 represented a significant departure for all age groups and both men and women (P<0.00001). Mean sleep duration increased in nearly all groups (P<0.00001) by 5-11 minutes, compared to a mean decrease of 5-8 minutes seen over the same period in 2019. Categorically, sleep duration increased for some and decreased for others, but more extended than restricted. Sleep phase shifted later for nearly all groups (p<0.00001). Categorically, bedtime was delayed for some and advanced for others, though more delayed than advanced. Duration and bedtime variability decreased, owing largely to decreased weekday-weekend differences. WASO increased, REM% increased, and Deep% decreased. Additional analyses show stratified, longitudinal changes to sleep duration and timing mean and variability distributions by month, as well as effect sizes and correlations to other outcomes. Conclusion The pandemic was associated with increased sleep duration on average, in contrast to 2019 when sleep decreased. The increase was most profound among younger adults, especially women. The youngest adults also experienced the greatest bedtime delay, in line with extensive school-start-times and chronotype data. When given the opportunity, the difference between weekdays and weekends became smaller, with occupational implications. Sleep staging data showed that slightly extending sleep minimally impacted deep sleep but resulted in a proportional increase in REM. Wakefulness during the night also increased, suggesting increased arousal despite greater sleep duration. Support (if any) This research was supported by Fitbit, Inc.

scholarly journals The PETLON Algorithm to Plan Efficiently for Task-Level-Optimal Navigation

2020 ◽  
Vol 69 ◽  
pp. 471-500
Author(s):  
Shih-Yun Lo ◽  
Shiqi Zhang ◽  
Peter Stone
Keyword(s):  
Mobile Robot ◽  
Motion Planning ◽  
Mobile Robots ◽  
Large Scale ◽  
Accurate Estimate ◽  
Indoor Environments ◽  
Task Planning ◽  
Trade Offs ◽  
High Level ◽  
Task Level

Intelligent mobile robots have recently become able to operate autonomously in large-scale indoor environments for extended periods of time. In this process, mobile robots need the capabilities of both task and motion planning. Task planning in such environments involves sequencing the robot’s high-level goals and subgoals, and typically requires reasoning about the locations of people, rooms, and objects in the environment, and their interactions to achieve a goal. One of the prerequisites for optimal task planning that is often overlooked is having an accurate estimate of the actual distance (or time) a robot needs to navigate from one location to another. State-of-the-art motion planning algorithms, though often computationally complex, are designed exactly for this purpose of finding routes through constrained spaces. In this article, we focus on integrating task and motion planning (TMP) to achieve task-level-optimal planning for robot navigation while maintaining manageable computational efficiency. To this end, we introduce TMP algorithm PETLON (Planning Efficiently for Task-Level-Optimal Navigation), including two configurations with different trade-offs over computational expenses between task and motion planning, for everyday service tasks using a mobile robot. Experiments have been conducted both in simulation and on a mobile robot using object delivery tasks in an indoor office environment. The key observation from the results is that PETLON is more efficient than a baseline approach that pre-computes motion costs of all possible navigation actions, while still producing plans that are optimal at the task level. We provide results with two different task planning paradigms in the implementation of PETLON, and offer TMP practitioners guidelines for the selection of task planners from an engineering perspective.

scholarly journals Nonlinear visuoauditory integration in the mouse superior colliculus

2021 ◽  
Author(s):  
Shinya Ito ◽  
Yufei Si ◽  
Alan M. Litke ◽  
David A. Feldheim
Keyword(s):  
Superior Colliculus ◽  
Sensory Integration ◽  
Large Scale ◽  
Temporal Dynamics ◽  
Critical Role ◽  
Sensory Information ◽  
Population Level ◽  
Object Identification ◽  
Response Properties ◽  
The Individual

AbstractSensory information from different modalities is processed in parallel, and then integrated in associative brain areas to improve object identification and the interpretation of sensory experiences. The Superior Colliculus (SC) is a midbrain structure that plays a critical role in integrating visual, auditory, and somatosensory input to assess saliency and promote action. Although the response properties of the individual SC neurons to visuoauditory stimuli have been characterized, little is known about the spatial and temporal dynamics of the integration at the population level. Here we recorded the response properties of SC neurons to spatially restricted visual and auditory stimuli using large-scale electrophysiology. We then created a general, population-level model that explains the spatial, temporal, and intensity requirements of stimuli needed for sensory integration. We found that the mouse SC contains topographically organized visual and auditory neurons that exhibit nonlinear multisensory integration. We show that nonlinear integration depends on properties of auditory but not visual stimuli. We also find that a heuristically derived nonlinear modulation function reveals conditions required for sensory integration that are consistent with previously proposed models of sensory integration such as spatial matching and the principle of inverse effectiveness.

scholarly journals Orientation and color tuning of the human visual gamma rhythm

2021 ◽  
Author(s):  
Ye Li ◽  
William Bosking ◽  
Michael S Beauchamp ◽  
Sameer A Sheth ◽  
Daniel Yoshor ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Large Scale ◽  
Brain Activity ◽  
Population Level ◽  
Gamma Oscillations ◽  
Cell Orientation ◽  
Population Activity ◽  
Color Tuning ◽  
Human Visual Cortex ◽  
Gamma Rhythm

Narrowband gamma oscillations (NBG: ~20-60Hz) in visual cortex reflect rhythmic fluctuations in population activity generated by underlying circuits tuned for stimulus location, orientation, and color. Consequently, the amplitude and frequency of induced NBG activity is highly sensitive to these stimulus features. For example, in the non-human primate, NBG displays biases in orientation and color tuning at the population level. Such biases may relate to recent reports describing the large-scale organization of single-cell orientation and color tuning in visual cortex, thus providing a potential bridge between measurements made at different scales. Similar biases in NBG population tuning have been predicted to exist in the human visual cortex, but this has yet to be fully examined. Using intracranial recordings from human visual cortex, we investigated the tuning of NBG to orientation and color, both independently and in conjunction. NBG was shown to display a cardinal orientation bias (horizontal) and also an end- and mid-spectral color bias (red/blue and green). When jointly probed, the cardinal bias for orientation was attenuated and an end-spectral preference for red and blue predominated. These data both elaborate on the close, yet complex, link between the population dynamics driving NBG oscillations and known feature selectivity biases in visual cortex, adding to a growing set of stimulus dependencies associated with the genesis of NBG. Together, these two factors may provide a fruitful testing ground for examining multi-scale models of brain activity, and impose new constraints on the functional significance of the visual gamma rhythm.

scholarly journals Use, awareness and willingness to self-test for HIV: An analysis of cross-sectional population-based surveys in Malawi and Zimbabwe

2020 ◽  
Author(s):  
Cheryl Case Johnson ◽  
Melissa Neuman ◽  
Peter MacPherson ◽  
Augustine Choko ◽  
Caitlin Quinn ◽  
...  
Keyword(s):  
Sexual Risk ◽  
Large Scale ◽  
Scale Up ◽  
Population Level ◽  
Sociodemographic Factors ◽  
Population Based ◽  
African Countries ◽  
Cross Sectional ◽  
Self Test ◽  
Result Analysis

Abstract Background Many southern African countries are nearing the global goal to diagnose 90% of people with HIV by 2020. In 2016, 84% and 86% of people with HIV knew their status in Malawi and Zimbabwe respectively. Despite this progress, gaps remain, particularly among men (≥25 years). We investigated awareness, use and willingness to HIV self-test (HIVST) prior to large scale implementation and explored sociodemographic associations. Methods We pooled responses from two of the first cross-sectional Demographic Health Surveys to include HIVST questions: Malawi and Zimbabwe in 2015-16. Sociodemographic factors and sexual risk behaviours associated with previously testing for HIV, and awareness, past use and future willingness to self-test were investigated using univariable and multivariable logistic regression, adjusting for the sample design and limiting analysis to participants with completed questionnaire and a valid HIV result. Analysis of willingness to self-test was restricted to Zimbabwean men, as Malawians and women were not asked this question. Results Of 31 385 individuals, the proportion never-tested was higher for men (31.2%) than women (16.5%), p<0.001. For men, having ever tested increased with age. Past use and awareness of HIVST was very low, 1.2% and 12.6% respectively. Awareness was lower among women than men (9.1% vs 15.3%, adjusted odds ratio (aOR)=1.55; 95% confidence interval [CI]: 1.37-1.75), and at younger ages, and lower education and literacy levels. Willingness to self-test among Zimbabwean men was high (84.5%), with having previously tested for HIV, high sexual risk, and being ≥25 years associated with greater willingness. Wealthier men had greater awareness of HIVST than poorer men (p<0.001). Men at higher HIV-related sexual risk, compared to men at lower HIV-related sexual risk, had the greatest willingness to self-test (aOR=3.74; 95%CI: 1.39-10.03, p<0.009).Conclusions In 2015-16 many Malawian and Zimbabwean men had never tested for HIV. Despite low awareness and minimal HIVST experience at that time, willingness to self-test was high among Zimbabwean men, especially in older men with moderate to high HIV-related sexual risk. These data provide a valuable baseline against which to investigate population-level uptake of HIVST as programmes scale-up. Programmes introducing, or planning to introduce HIVST, should consider including questions in population-based surveys.

scholarly journals Representational drift in the mouse visual cortex

2020 ◽  
Author(s):  
Daniel Deitch ◽  
Alon Rubin ◽  
Yaniv Ziv
Keyword(s):  
Large Scale ◽  
Activity Patterns ◽  
Population Level ◽  
Population Activity ◽  
Cortical Areas ◽  
Electrophysiological Recordings ◽  
The Face ◽  
Visual Cortical ◽  
Mouse Visual Cortex ◽  
Over Time

AbstractNeuronal representations in the hippocampus and related structures gradually change over time despite no changes in the environment or behavior. The extent to which such ‘representational drift’ occurs in sensory cortical areas and whether the hierarchy of information flow across areas affects neural-code stability have remained elusive. Here, we address these questions by analyzing large-scale optical and electrophysiological recordings from six visual cortical areas in behaving mice that were repeatedly presented with the same natural movies. We found representational drift over timescales spanning minutes to days across multiple visual areas. The drift was driven mostly by changes in individual cells’ activity rates, while their tuning changed to a lesser extent. Despite these changes, the structure of relationships between the population activity patterns remained stable and stereotypic, allowing robust maintenance of information over time. Such population-level organization may underlie stable visual perception in the face of continuous changes in neuronal responses.

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