Temporal Variabilities Provide Additional Category-Related Information in Object Category Decoding: A Systematic Comparison of Informative EEG Features

Abstract How does the human brain encode visual object categories? Our understanding of this has advanced substantially with the development of multivariate decoding analyses. However, conventional electroencephalography (EEG) decoding predominantly uses the mean neural activation within the analysis window to extract category information. Such temporal averaging overlooks the within-trial neural variability that is suggested to provide an additional channel for the encoding of information about the complexity and uncertainty of the sensory input. The richness of temporal variabilities, however, has not been systematically compared with the conventional mean activity. Here we compare the information content of 31 variability-sensitive features against the mean of activity, using three independent highly varied data sets. In whole-trial decoding, the classical event-related potential (ERP) components of P2a and P2b provided information comparable to those provided by original magnitude data (OMD) and wavelet coefficients (WC), the two most informative variability-sensitive features. In time-resolved decoding, the OMD and WC outperformed all the other features (including the mean), which were sensitive to limited and specific aspects of temporal variabilities, such as their phase or frequency. The information was more pronounced in the theta frequency band, previously suggested to support feedforward visual processing. We concluded that the brain might encode the information in multiple aspects of neural variabilities simultaneously such as phase, amplitude, and frequency rather than mean per se. In our active categorization data set, we found that more effective decoding of the neural codes corresponds to better prediction of behavioral performance. Therefore, the incorporation of temporal variabilities in time-resolved decoding can provide additional category information and improved prediction of behavior.

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Neural changes in early visual processing after 6 months of mindfulness training in older adults

Scientific Reports ◽

10.1038/s41598-020-78343-w ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Ben Isbel ◽

Jan Weber ◽

Jim Lagopoulos ◽

Kayla Stefanidis ◽

Hannah Anderson ◽

...

Keyword(s):

Older Adults ◽

Visual Processing ◽

Mindfulness Training ◽

Event Related Potential ◽

Perceptual Processing ◽

Control Group ◽

Neural Activation ◽

Visual Cue ◽

Age Related ◽

Attentional Performance

AbstractMindfulness has been shown to improve attentional performance, which is known to decline in aging. Long-latency electroencephalographic (EEG) event-related potential (ERP) changes have been reported immediately after mindfulness training, however the enduring stability of these effects is unknown. Furthermore, the ability of mindfulness to impact earlier stages of information processing is unclear. We examined neural activation using high density EEG in older adults engaged in mindfulness training to examine the long-term stability of training effects. After 6 months of training, mindfulness practitioners displayed enhanced neural activation during sensory encoding and perceptual processing of a visual cue. Enhanced perceptual processing of a visual cue was associated with increased neural activation during post-perceptual processing of a subsequent target. Similar changes were not observed in a control group engaged in computer-based attention training over the same period. Neural changes following mindfulness training were accompanied by behavioural improvements in attentional performance. Our results are suggestive of increased efficiency of the neural pathways subserving bottom-up visual processing together with an enhanced ability to mobilise top-down attentional processes during perceptual and post-perceptual processing following mindfulness training. These results indicate that mindfulness may enhance neural processes known to deteriorate in normal aging and age-related neurodegenerative diseases.

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How Native Background Affects Human Performance in Real-World Visual Object Detection: An Event-Related Potential Study

Frontiers in Neuroscience ◽

10.3389/fnins.2021.665084 ◽

2021 ◽

Vol 15 ◽

Author(s):

Yue Wang ◽

Jianpu Yan ◽

Zhongliang Yin ◽

Shenghan Ren ◽

Minghao Dong ◽

...

Keyword(s):

Object Detection ◽

Real World ◽

Visual Processing ◽

Event Related Potentials ◽

Event Related Potential ◽

Visual Object ◽

Detection Accuracy ◽

Natural Scenes ◽

Experimental Conditions ◽

Related Potentials

Visual processing refers to the process of perceiving, analyzing, synthesizing, manipulating, transforming, and thinking of visual objects. It is modulated by both stimulus-driven and goal-directed factors and manifested in neural activities that extend from visual cortex to high-level cognitive areas. Extensive body of studies have investigated the neural mechanisms of visual object processing using synthetic or curated visual stimuli. However, synthetic or curated images generally do not accurately reflect the semantic links between objects and their backgrounds, and previous studies have not provided answers to the question of how the native background affects visual target detection. The current study bridged this gap by constructing a stimulus set of natural scenes with two levels of complexity and modulating participants' attention to actively or passively attend to the background contents. Behaviorally, the decision time was elongated when the background was complex or when the participants' attention was distracted from the detection task, and the object detection accuracy was decreased when the background was complex. The results of event-related potentials (ERP) analysis explicated the effects of scene complexity and attentional state on the brain responses in occipital and centro-parietal areas, which were suggested to be associated with varied attentional cueing and sensory evidence accumulation effects in different experimental conditions. Our results implied that efficient visual processing of real-world objects may involve a competition process between context and distractors that co-exist in the native background, and extensive attentional cues and fine-grained but semantically irrelevant scene information were perhaps detrimental to real-world object detection.

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Temporal codes provide additional category-related information in object category decoding: a systematic comparison of informative EEG features

10.1101/2020.09.02.279042 ◽

2020 ◽

Cited By ~ 1

Author(s):

Hamid Karimi-Rouzbahani ◽

Mozhgan Shahmohammadi ◽

Ehsan Vahab ◽

Saeed Setayeshi ◽

Thomas Carlson

Keyword(s):

Visual Information ◽

Temporal Dynamics ◽

Principal Component ◽

Event Related Potential ◽

Neural Activation ◽

Object Category ◽

Category Information ◽

Related Information ◽

Distinct Features ◽

The Brain

AbstractHumans are remarkably efficent at recognizing objects. Understanding how the brain performs object recognition has been challenging. Our understanding has been advanced substantially in recent years with the development of multivariate decoding methods. Most start-of-the-art decoding procedures, make use of the ‘mean’ neural activation to extract object category information, which overlooks temporal variability in the signals. Here, we studied category-related information in 30 mathematically distinct features from electroencephalography (EEG) across three independent and highly-varied datasets using multivariate decoding. While the event-related potential (ERP) components of N1 and P2a were among the most informative features, the informative original signal samples and Wavelet coefficients, selected through principal component analysis, outperformed them. The four mentioned informative features showed more pronounced decoding in the Theta frequency band, which has been suggested to support feed-forward processing of visual information in the brain. Correlational analyses showed that the features, which were most informative about object categories, could predict participants’ behavioral performance (reaction time) more accurately than the less informative features. These results suggest a new approach for studying how the human brain encodes object category information and how we can read them out more optimally to investigate the temporal dynamics of the neural code. The codes are available online at https://osf.io/wbvpn/.

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Relationship between large-scale ionospheric field-aligned currents and electron/ion precipitations: DMSP observations

Earth Planets and Space ◽

10.1186/s40623-020-01286-z ◽

2020 ◽

Vol 72 (1) ◽

Author(s):

Chao Xiong ◽

Claudia Stolle ◽

Patrick Alken ◽

Jan Rauberg

Keyword(s):

Time Distribution ◽

Large Scale ◽

Particle Flux ◽

Particle Energy ◽

Lower Latitude ◽

Particle Precipitation ◽

Data Set ◽

The Mean ◽

Two Parameters ◽

Meteorological Satellite

Abstract In this study, we have derived field-aligned currents (FACs) from magnetometers onboard the Defense Meteorological Satellite Project (DMSP) satellites. The magnetic latitude versus local time distribution of FACs from DMSP shows comparable dependences with previous findings on the intensity and orientation of interplanetary magnetic field (IMF) By and Bz components, which confirms the reliability of DMSP FAC data set. With simultaneous measurements of precipitating particles from DMSP, we further investigate the relation between large-scale FACs and precipitating particles. Our result shows that precipitation electron and ion fluxes both increase in magnitude and extend to lower latitude for enhanced southward IMF Bz, which is similar to the behavior of FACs. Under weak northward and southward Bz conditions, the locations of the R2 current maxima, at both dusk and dawn sides and in both hemispheres, are found to be close to the maxima of the particle energy fluxes; while for the same IMF conditions, R1 currents are displaced further to the respective particle flux peaks. Largest displacement (about 3.5°) is found between the downward R1 current and ion flux peak at the dawn side. Our results suggest that there exists systematic differences in locations of electron/ion precipitation and large-scale upward/downward FACs. As outlined by the statistical mean of these two parameters, the FAC peaks enclose the particle energy flux peaks in an auroral band at both dusk and dawn sides. Our comparisons also found that particle precipitation at dawn and dusk and in both hemispheres maximizes near the mean R2 current peaks. The particle precipitation flux maxima closer to the R1 current peaks are lower in magnitude. This is opposite to the known feature that R1 currents are on average stronger than R2 currents.

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Pseudosparse neural coding in the visual system of primates

Communications Biology ◽

10.1038/s42003-020-01572-2 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Sidney R. Lehky ◽

Keiji Tanaka ◽

Anne B. Sereno

Keyword(s):

Neural Coding ◽

Macaque Monkey ◽

Implicit Assumption ◽

Data Set ◽

Efficient Coding ◽

Population Responses ◽

Lateral Intraparietal Cortex ◽

Neural Populations ◽

Neurophysiological Data ◽

The Mean

AbstractWhen measuring sparseness in neural populations as an indicator of efficient coding, an implicit assumption is that each stimulus activates a different random set of neurons. In other words, population responses to different stimuli are, on average, uncorrelated. Here we examine neurophysiological data from four lobes of macaque monkey cortex, including V1, V2, MT, anterior inferotemporal cortex, lateral intraparietal cortex, the frontal eye fields, and perirhinal cortex, to determine how correlated population responses are. We call the mean correlation the pseudosparseness index, because high pseudosparseness can mimic statistical properties of sparseness without being authentically sparse. In every data set we find high levels of pseudosparseness ranging from 0.59–0.98, substantially greater than the value of 0.00 for authentic sparseness. This was true for synthetic and natural stimuli, as well as for single-electrode and multielectrode data. A model indicates that a key variable producing high pseudosparseness is the standard deviation of spontaneous activity across the population. Consistently high values of pseudosparseness in the data demand reconsideration of the sparse coding literature as well as consideration of the degree to which authentic sparseness provides a useful framework for understanding neural coding in the cortex.

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An Electrophysiological Measure of Temporal Resolution in Normal Subjects Using Frequency Modulated Signals

American Journal of Audiology ◽

10.1044/1059-0889(2002/007) ◽

2002 ◽

Vol 11 (1) ◽

pp. 42-49

Author(s):

Devin L. McCaslin ◽

Lawrence L. Feth ◽

Gary P. Jacobson ◽

Pamela J. Mishler

Keyword(s):

Temporal Resolution ◽

Mismatch Negativity ◽

Normal Subjects ◽

Single Step ◽

Event Related Potential ◽

Frequency Range ◽

Temporal Properties ◽

Step Duration ◽

The Mean ◽

Modulated Signals

This investigation was conducted to determine whether an exogenous event-related potential called the mismatch negativity (MMN) would change systematically in response to frequency-modulated signals with varying temporal properties. Both N1 and P2 waveforms were recorded for 50-ms frequency-modulated signals from normal hearing listeners. The standard stimuli for this investigation were continuous sweep tones with center frequencies of 1000 Hz that traversed a frequency range of 200 Hz in a single step. The rare stimuli were signals that traversed the same frequency range in two, four, six, or eight discrete steps. Results suggest that for the 10 participants, 1) the mean MMN peak-to-peak amplitude and mean area decreased significantly with decreases in step duration, 2) MMN area amplitude was the best indicator of psychophysical performance for the two magnitude measures, and 3) MMN onsets and peak latencies did not show either a significant increase or decrease in latency as step duration decreased.

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Numerical simulations of spreading of the Persian Gulf outflow into the Oman Sea

Ocean Science ◽

10.5194/os-6-887-2010 ◽

2010 ◽

Vol 6 (4) ◽

pp. 887-900 ◽

Cited By ~ 15

Author(s):

M. Ezam ◽

A. A. Bidokhti ◽

A. H. Javid

Keyword(s):

Persian Gulf ◽

Bottom Topography ◽

World Ocean ◽

Monthly Precipitation ◽

Boundary Current ◽

Surface Salinity ◽

Data Set ◽

Open Boundaries ◽

The Mean ◽

The Persian Gulf

Abstract. A three dimensional numerical model namely POM (Princeton Ocean Model) and observational data are used to study the Persian Gulf outflow structure and its spreading pathways during 1992. In the model, the monthly wind speed data were taken from ICOADS (International Comprehensive Ocean-Atmosphere Data Set) and the monthly SST (sea surface temperatures) were taken from AVHRR (Advanced Very High Resolution Radiometer) with the addition of monthly net shortwave radiations from NCEP (National Center for Environmental Prediction). The mean monthly precipitation rates from NCEP data and the calculated evaporation rates are used to impose the surface salinity fluxes. At the open boundaries the temperature and salinity were prescribed from the mean monthly climatological values from WOA05 (World Ocean Atlas 2005). Also the four major components of the tide were prescribed at the open boundaries. The results show that the outflow mainly originates from two branches at different depths in the Persian Gulf. The permanent branch exists during the whole year deeper than 40 m along the Gulf axis and originates from the inner parts of the Persian Gulf. The other seasonal branch forms in the vicinity of the shallow southern coasts due to high evaporation rates during winter. Near the Strait of Hormuz the two branches join and form the main outflow source water. The results of simulations reveal that during the winter the outflow boundary current mainly detaches from the coast well before Ras Al Hamra Cape, however during summer the outflow seems to follow the coast even after this Cape. This is due to a higher density of the colder outflow that leads to more sinking near the coast in winter. Thus, the outflow moves to a deeper depth of about 500 m (for which some explanations are given) while the main part detaches and spreads at a depth of about 300 m. However in summer it all moves at a depth of about 200–250 m. During winter, the deeper, stronger and wider outflow is more affected by the steep topography, leading to separation from the coast. While during summer, the weaker and shallower outflow is less influenced by bottom topography and so continues along the boundary.

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EPID-22. CHARACTERIZATION OF RADIATION-INDUCED MENINGIOMAS IN A BRAIN TUMOR DATABASE

Neuro-Oncology ◽

10.1093/neuonc/noaa215.340 ◽

2020 ◽

Vol 22 (Supplement_2) ◽

pp. ii83-ii83

Author(s):

Nilan Vaghjiani ◽

Andrew Schwieder ◽

Sravya Uppalapati ◽

Zachary Kons ◽

Elizabeth Kazarian ◽

...

Keyword(s):

African American ◽

Brain Tumor ◽

Radiation Treatment ◽

Latency Period ◽

Data Set ◽

Who Grade ◽

Significant Difference ◽

Radiation Induced ◽

Grade Ii ◽

The Mean

Abstract PURPOSE Radiation-induced meningiomas (RIMs) are associated with previous exposure to therapeutic irradiation. RIMs are rare and have not been well characterized relative to spontaneous meningiomas (SMs). METHODS 1003 patients with proven or presumed meningiomas were identified from the VCU brain tumor database. Chart review classified RIM patients and their characteristics. RESULTS Of the 1003 total patients, 76.47% were female with a mean ± SD age of 67.55 ± 15.50 years. 15 RIM patients were identified (66.67% female), with a mean ± SD age of 52.67 ± 15.46 years, 5 were African American and 10 were Caucasian. The incidence of RIMs was 1.49% in our data set. The mean age at diagnosis was 43.27 ± 15.06 years. The mean latency was 356.27 ± 116.96 months. The mean initiating dose was 44.28 ± 14.68 Gy. There was a significant difference between mean latency period and ethnicity, 258.3 months for African American population, and 405.2 months for Caucasian population (p = 0.003). There was a significant difference between the mean number of lesions in females (2.8) versus males (1.2; p = 0.046). Of the RIMs with characterized histology, 6 (55%) were WHO grade II and 5 (45%) were WHO grade I, demonstrating a prevalence of grade II tumors approximately double that found with SMs. RIMs were treated with combinations of observation, surgery, radiation, and medical therapy. Of the 8 patients treated with radiation, 4 demonstrated response. 8 of the 15 patients (53%) demonstrated recurrence/progression despite treatment. CONCLUSION RIMs are important because of the associated higher grade histology, gender, and ethnic incidences, and increased recurrence/progression compared to SMs. Despite the presumed contributory role of prior radiation, RIMs demonstrate a significant rate of responsiveness to radiation treatment.

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Time-Resolved Reflectance Spectroscopy Applied to the Nondestructive Monitoring of the Internal Optical Properties in Apples

Applied Spectroscopy ◽

10.1366/0003702011953496 ◽

2001 ◽

Vol 55 (10) ◽

pp. 1368-1374 ◽

Cited By ~ 75

Author(s):

Rinaldo Cubeddu ◽

Cosimo D'Andrea ◽

Antonio Pifferi ◽

Paola Taroni ◽

Alessandro Torricelli ◽

...

Keyword(s):

Optical Properties ◽

Industrial Applications ◽

Nondestructive Monitoring ◽

Nondestructive Measurement ◽

Time Resolved ◽

Mean Values ◽

Scattering Coefficients ◽

Scattering Spectra ◽

The Mean ◽

Temporal Dispersion

Time-resolved reflectance has been used for the nondestructive measurement of optical properties in apples. The technique is based on the detection of the temporal dispersion of a short laser pulse injected into the probed medium. The time distribution of re-emitted photons interpreted with a solution of the diffusion equation yields the mean values of the absorption and reduced scattering coefficients of the medium. The proposed technique proved useful for the measurement of the absorption and scattering spectra of different varieties of apples, revealing the spectral shape of chlorophyll. No major variations were observed in the experimental data when the fruit was peeled, showing that the optical properties measured were those of the pulp. With this technique the change in chlorophyll absorption during storage and ripening could be followed. Finally, a compact prototype working at few selected wavelengths was designed and constructed, demonstrating potentialities of the technique for industrial applications.

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A MODIFIED RATIO TYPE ESTIMATOR OF FINITE POPULATION MEAN UNDER STRATIFIED RANDOM SAMPLING SCHEME

10.36106/4917049 ◽

2021 ◽

pp. 58-60

Author(s):

Naziru Fadisanku Haruna ◽

Ran Vijay Kumar Singh ◽

Samsudeen Dahiru

Keyword(s):

Mean Square Error ◽

Random Sampling ◽

Minimum Mean Square Error ◽

Real Life ◽

Population Data ◽

Auxiliary Variable ◽

Mean Square ◽

Data Set ◽

Population Mean ◽

The Mean

In This paper a modied ratio-type estimator for nite population mean under stratied random sampling using single auxiliary variable has been proposed. The expression for mean square error and bias of the proposed estimator are derived up to the rst order of approximation. The expression for minimum mean square error of proposed estimator is also obtained. The mean square error the proposed estimator is compared with other existing estimators theoretically and condition are obtained under which proposed estimator performed better. A real life population data set has been considered to compare the efciency of the proposed estimator numerically.

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