scholarly journals Quantifying the signals contained in heterogeneous neural responses and determining their relationships with task performance

2014 ◽  
Vol 112 (6) ◽  
pp. 1584-1598 ◽  
Author(s):  
Marino Pagan ◽  
Nicole C. Rust
Keyword(s):  
Task Performance ◽  
Single Neuron ◽  
Weighted Sums ◽  
Neural Responses ◽  
Signal Modulation ◽  
Neural Data ◽  
Match To Sample ◽  
Neural Populations ◽  
Different Types ◽  
High Level

The responses of high-level neurons tend to be mixtures of many different types of signals. While this diversity is thought to allow for flexible neural processing, it presents a challenge for understanding how neural responses relate to task performance and to neural computation. To address these challenges, we have developed a new method to parse the responses of individual neurons into weighted sums of intuitive signal components. Our method computes the weights by projecting a neuron's responses onto a predefined orthonormal basis. Once determined, these weights can be combined into measures of signal modulation; however, in their raw form these signal modulation measures are biased by noise. Here we introduce and evaluate two methods for correcting this bias, and we report that an analytically derived approach produces performance that is robust and superior to a bootstrap procedure. Using neural data recorded from inferotemporal cortex and perirhinal cortex as monkeys performed a delayed-match-to-sample target search task, we demonstrate how the method can be used to quantify the amounts of task-relevant signals in heterogeneous neural populations. We also demonstrate how these intuitive quantifications of signal modulation can be related to single-neuron measures of task performance ( d′).

scholarly journals Inferotemporal cortex multiplexes behaviorally-relevant target match signals and visual representations in a manner that minimizes their interference

2017 ◽  
Author(s):  
Noam Roth ◽  
Nicole C. Rust
Keyword(s):  
Visual Information ◽  
Visual Representations ◽  
Target Object ◽  
Object Identity ◽  
Neural Responses ◽  
Inferotemporal Cortex ◽  
Match To Sample ◽  
Sample Object ◽  
High Level ◽  
Detrimental Impact

AbstractFinding a sought visual target object requires combining visual information about a scene with a remembered representation of the target to create a “target match” signal that indicates when a target is in view. Target match signals have been reported to exist within high-level visual brain areas including inferotemporal cortex (IT), where they are mixed with representations of image and object identity. However, these signals are not well understood, particularly in the context of the real-world challenge that the objects we search for typically appear at different positions, sizes, and within different background contexts. To investigate these signals, we recorded neural responses in IT as two rhesus monkeys performed a delayed-match-to-sample object search task in which target objects could appear at a variety of identity-preserving transformations. Consistent with the existence of behaviorally-relevant target match signals in IT, we found that IT contained a linearly separable target match representation that reflected behavioral confusions on trials in which the monkeys made errors. Additionally, target match signals were highly distributed across the IT population, and while a small fraction of units reflected target match signals as target match suppression, most units reflected target match signals as target match enhancement. Finally, we found that the potentially detrimental impact of target match signals on visual representations was mitigated by target match modulation that was approximately (albeit imperfectly) multiplicative. Together, these results support the existence of a robust, behaviorally-relevant target match representation in IT that is configured to minimally interfere with IT visual representations.

scholarly journals Music-selective cortex is sensitive to structure in both pitch and time

2021 ◽  
Author(s):  
Dana L Boebinger ◽  
Sam V Norman-Haignere ◽  
Josh H McDermott ◽  
Nancy G Kanwisher
Keyword(s):  
Auditory Cortex ◽  
Primary Auditory Cortex ◽  
Acoustic Properties ◽  
Musical Structure ◽  
Synthetic Control ◽  
Neural Responses ◽  
Wide Range ◽  
Neural Populations ◽  
Cortical Regions ◽  
High Level

Converging evidence suggests that neural populations within human non-primary auditory cortex respond selectively to music. These neural populations respond strongly to a wide range of music stimuli, and weakly to other natural sounds and to synthetic control stimuli matched to music in many acoustic properties, suggesting that they are driven by high-level musical features. What are these features? Here we used fMRI to test the extent to which musical structure in pitch and time contribute to music-selective neural responses. We used voxel decomposition to derive music-selective response components in each of 15 participants individually, and then measured the response of these components to synthetic music clips in which we selectively disrupted musical structure by scrambling either the note pitches and/or onset times. Both types of scrambling produced lower responses compared to when melodic or rhythmic structure was intact. This effect was much stronger in the music-selective component than in the other response components, even those with substantial spatial overlap with the music component. We further found no evidence for any cortical regions sensitive to pitch but not time structure, or vice versa. Our results suggest that the processing of melody and rhythm are intertwined within auditory cortex.

Using Histological and Chemical Methods for Detection of Unauthorized Tissues Addition in Emulsion Type Meat Product

2020 ◽  
Keyword(s):  
Vascular Tissue ◽  
Meat Product ◽  
Calcium Content ◽  
Processed Meat ◽  
Low Protein ◽  
Significant Difference ◽  
Different Types ◽  
Plant Stem ◽  
High Level ◽  
Reliable Methods

Total twenty different processed meat plant producing emulsion type sausage were histologically and chemically examined for detection of adulteration with unauthorized tissues. Results revealed that samples were adulterated with different types of animal tissues included; hyaline cartilage, tendon, spongy bone, peripheral nerve trunk, basophilic matrix, lymphatic tissue, fascia, fibrocartilage and vascular tissue. Moreover, these samples were adulterated Also, adulterated with plant tissue included; plant stem, leaves and root. Chemical analysis showed a significant difference in their chemical composition (moisture, fat, protein, ash and calcium) content. Moisture and fat content varied around the permissible limit of E.S.S. while low protein, high ash and calcium content was detected in the examined samples. Therefore, Histological and chemical examinations can be used as reliable methods to detect adultration using unauthorized addition of both animal and plant tissues in processed meat product samples which revealed a high level of falsification.

scholarly journals Cortical response to naturalistic stimuli is largely predictable with deep neural networks

2021 ◽  
Vol 7 (22) ◽  
pp. eabe7547
Author(s):  
Meenakshi Khosla ◽  
Gia H. Ngo ◽  
Keith Jamison ◽  
Amy Kuceyeski ◽  
Mert R. Sabuncu
Keyword(s):  
Brain Function ◽  
Deep Neural Networks ◽  
Neural Responses ◽  
Dynamic Interactions ◽  
Hierarchical Processing ◽  
Human Connectome Project ◽  
Neural Information ◽  
Neural Information Processing ◽  
Visual Interactions ◽  
High Level

Naturalistic stimuli, such as movies, activate a substantial portion of the human brain, invoking a response shared across individuals. Encoding models that predict neural responses to arbitrary stimuli can be very useful for studying brain function. However, existing models focus on limited aspects of naturalistic stimuli, ignoring the dynamic interactions of modalities in this inherently context-rich paradigm. Using movie-watching data from the Human Connectome Project, we build group-level models of neural activity that incorporate several inductive biases about neural information processing, including hierarchical processing, temporal assimilation, and auditory-visual interactions. We demonstrate how incorporating these biases leads to remarkable prediction performance across large areas of the cortex, beyond the sensory-specific cortices into multisensory sites and frontal cortex. Furthermore, we illustrate that encoding models learn high-level concepts that generalize to task-bound paradigms. Together, our findings underscore the potential of encoding models as powerful tools for studying brain function in ecologically valid conditions.

scholarly journals The Use of Fitness Testing to Predict Occupational Performance in Tactical Personnel: A Critical Review

2021 ◽  
Vol 18 (14) ◽  
pp. 7480
Author(s):  
Robin Orr ◽  
Takato Sakurai ◽  
Jordan Scott ◽  
Jason Movshovich ◽  
J. Jay Dawes ◽  
...  
Keyword(s):  
Task Performance ◽  
Cardiovascular Fitness ◽  
Fitness Testing ◽  
Occupational Performance ◽  
Occupational Tasks ◽  
Wide Range ◽  
Fitness Tests ◽  
Critical Appraisal Skills ◽  
High Level ◽  
Occupational Task

Tactical personnel work in an occupation that involves tasks requiring a high level of cardiovascular fitness as well as muscular strength and endurance. The aim of this literature review was to identify and critique studies investigating the relationship between physical fitness, quantified by fitness assessment measures, and occupational task performance. Databases were searched for relevant articles which assessed a fitness measure and a measure of occupational performance. A total of 15 articles were included and were deemed to be of acceptable methodological quality (8.4/12 on the Critical Appraisal Skills Programme checklist). Included articles assessed a variety of fitness attributes and occupational tasks. Across tactical groups, there appear to be no standardized fitness tests that can determine occupational performance, with aerobic fitness, anaerobic fitness, strength, endurance, power, and agility all being associated with occupational task performance. A wide range of fitness assessments appears to be required to predict occupational performance within tactical personnel. Efforts should be made to base fitness assessments on occupational demands unique to both the environment and requirements of each individual tactical unit.

The Costs of Ignoring High-Order Correlations in Populations of Model Neurons

2006 ◽  
Vol 18 (3) ◽  
pp. 660-682 ◽  
Author(s):  
Melchi M. Michel ◽  
Robert A. Jacobs
Keyword(s):  
Model Neuron ◽  
Joint Probability ◽  
High Order ◽  
Neural Population ◽  
Neural Responses ◽  
Significant Information ◽  
Statistical Correlations ◽  
Neural Populations ◽  
Simulation Results ◽  
Dependence Tree

Investigators debate the extent to which neural populations use pairwise and higher-order statistical dependencies among neural responses to represent information about a visual stimulus. To study this issue, three statistical decoders were used to extract the information in the responses of model neurons about the binocular disparities present in simulated pairs of left-eye and right-eye images: (1) the full joint probability decoder considered all possible statistical relations among neural responses as potentially important; (2) the dependence tree decoder also considered all possible relations as potentially important, but it approximated high-order statistical correlations using a computationally tractable procedure; and (3) the independent response decoder, which assumed that neural responses are statistically independent, meaning that all correlations should be zero and thus can be ignored. Simulation results indicate that high-order correlations among model neuron responses contain significant information about binocular disparities and that the amount of this high-order information increases rapidly as a function of neural population size. Furthermore, the results highlight the potential importance of the dependence tree decoder to neuroscientists as a powerful but still practical way of approximating high-order correlations among neural responses.

scholarly journals Space Precession Target Classification Based on Radar High-Resolution Range Profiles

2019 ◽  
Vol 2019 ◽  
pp. 1-9
Author(s):  
Yizhe Wang ◽  
Cunqian Feng ◽  
Yongshun Zhang ◽  
Sisan He
Keyword(s):  
Parameter Extraction ◽  
Classification Performance ◽  
Support Vector ◽  
Electromagnetic Data ◽  
Feature Extractor ◽  
Different Types ◽  
Radar Echo ◽  
High Level ◽  
Cone Target

Precession is a common micromotion form of space targets, introducing additional micro-Doppler (m-D) modulation into the radar echo. Effective classification of space targets is of great significance for further micromotion parameter extraction and identification. Feature extraction is a key step during the classification process, largely influencing the final classification performance. This paper presents two methods for classifying different types of space precession targets from the HRRPs. We first establish the precession model of space targets and analyze the scattering characteristics and then compute electromagnetic data of the cone target, cone-cylinder target, and cone-cylinder-flare target. Experimental results demonstrate that the support vector machine (SVM) using histograms of oriented gradient (HOG) features achieves a good result, whereas the deep convolutional neural network (DCNN) obtains a higher classification accuracy. DCNN combines the feature extractor and the classifier itself to automatically mine the high-level signatures of HRRPs through a training process. Besides, the efficiency of the two classification processes are compared using the same dataset.

scholarly journals Skew Superelevation Edge Rounding Design Improving Riding Comfort on Freeways

2019 ◽  
Vol 2673 (1) ◽  
pp. 343-357
Author(s):  
Konstantinos Apostoleris ◽  
Basil Psarianos ◽  
Ioannis-Alexandros Choupas ◽  
Vassilios Matragos
Keyword(s):  
Road Safety ◽  
Simulation Program ◽  
Heavy Vehicles ◽  
Parameter Change ◽  
Vehicle Simulation ◽  
Different Types ◽  
Vertical Accelerations ◽  
Design Speed ◽  
High Level ◽  
Traveling Speed

Skew superelevation has proven to be an efficient pavement constructional measure to address hydroplaning phenomena under specific critical superelevation runoff designs. However, this technique has raised concerns about user’s comfort when driving over the skewed edge of the pavement, especially for heavy vehicles and when the traveling speed is higher than the design speed. This paper aims to evaluate the driving comfort outcome on an improved skew superelevation design, where a rounding of the skew edge has been applied. This is achieved through the use of a simulation program which examines the vehicle and driver behavior when passing over it. The simulation program estimates many parameters including the lateral and vertical accelerations ( Gy and Gz) imposed on both elements, the vehicle and the driver. This evaluation is made for different alignment designs provided in the freeway design and for a broad range of especially high velocities ranging from 80 to 160 km/h (50–100 mph), as well as for different types of heavy vehicles. Also, the influence on the above parameters has been investigated in respect of the distance between two consecutive skew superelevations, concerning cases of entering and exiting a simple, low-length curve. The outcomes are classified in order to evaluate their variability as affected by each parameter change (speed, geometry, vehicle). Simulation results are compared with thresholds, as provided in the international literature, to ensure driver comfort and a high level of road safety.

scholarly journals Visual search for object categories is predicted by the representational architecture of high-level visual cortex

2017 ◽  
Vol 117 (1) ◽  
pp. 388-402 ◽  
Author(s):  
Michael A. Cohen ◽  
George A. Alvarez ◽  
Ken Nakayama ◽  
Talia Konkle
Keyword(s):  
Visual Cortex ◽  
Visual Search ◽  
Visual System ◽  
Visual Processing ◽  
Search Task ◽  
Visual Search Task ◽  
Visual Object ◽  
Neural Responses ◽  
Object Categories ◽  
High Level

Visual search is a ubiquitous visual behavior, and efficient search is essential for survival. Different cognitive models have explained the speed and accuracy of search based either on the dynamics of attention or on similarity of item representations. Here, we examined the extent to which performance on a visual search task can be predicted from the stable representational architecture of the visual system, independent of attentional dynamics. Participants performed a visual search task with 28 conditions reflecting different pairs of categories (e.g., searching for a face among cars, body among hammers, etc.). The time it took participants to find the target item varied as a function of category combination. In a separate group of participants, we measured the neural responses to these object categories when items were presented in isolation. Using representational similarity analysis, we then examined whether the similarity of neural responses across different subdivisions of the visual system had the requisite structure needed to predict visual search performance. Overall, we found strong brain/behavior correlations across most of the higher-level visual system, including both the ventral and dorsal pathways when considering both macroscale sectors as well as smaller mesoscale regions. These results suggest that visual search for real-world object categories is well predicted by the stable, task-independent architecture of the visual system. NEW & NOTEWORTHY Here, we ask which neural regions have neural response patterns that correlate with behavioral performance in a visual processing task. We found that the representational structure across all of high-level visual cortex has the requisite structure to predict behavior. Furthermore, when directly comparing different neural regions, we found that they all had highly similar category-level representational structures. These results point to a ubiquitous and uniform representational structure in high-level visual cortex underlying visual object processing.

Formation and Electrochemical Properties of the Hydrophobic Composite Coatings on Aluminum Alloy

2018 ◽  
Vol 386 ◽  
pp. 315-320
Author(s):  
Vladimir S. Egorkin ◽  
Igor E. Vyaliy ◽  
Nikolay S. Sviridov ◽  
Alexander N. Minaev ◽  
Sergey L. Sinebryukhov ◽  
...  
Keyword(s):  
Aluminum Alloy ◽  
Composite Coatings ◽  
Morphological Structure ◽  
Barrier Properties ◽  
Base Layer ◽  
Layer Composite ◽  
Electrolytic Oxidation ◽  
Different Types ◽  
Plasma Electrolytic ◽  
High Level

Plasma electrolytic oxidation (PEO) of 5754 aluminum alloy in a tartrate electrolyte was carried out to form a base layer. Composite fluoropolymer coatings were obtained on the base layers in two ways allowing the formation of two different types of morphological structure: a continuous polymer film and a multimodal islet relief. The resulted coatings exhibit substantially different wettability along with high level of barrier properties.

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