Individual Magnitudes of Neural Variability Quenching are Associated with Motion Perception Abilities

2021 ◽  
Author(s):  
Edan Daniel ◽  
Ilan Dinstein
Keyword(s):  
Stimulus Presentation ◽  
Coherent Motion ◽  
Eeg Data ◽  
Cortical Responses ◽  
Neural Populations ◽  
Perceptual Abilities ◽  
Contrast Discrimination ◽  
Visual Domain ◽  
Neural Variability ◽  
Consistent Support

Remarkable trial-by-trial variability is apparent in cortical responses to repeating stimulus presentations. This neural variability across trials is relatively high before stimulus presentation, and then reduced (i.e., quenched) ~0.2s after stimulus presentation. Individual subjects exhibit different magnitudes of variability quenching, and previous work from our lab has revealed that individuals with larger variability quenching exhibit lower (i.e., better) perceptual thresholds in a contrast discrimination task. Here, we examined whether similar findings were also apparent in a motion detection task, which is processed by distinct neural populations in the visual system. We recorded EEG data from 35 adult subjects as they detected the direction of coherent motion in random dot kinematograms. The results demonstrated that individual magnitudes of variability quenching were significantly correlated with coherent motion thresholds, particularly when presenting stimuli with low dot densities, where coherent motion was more difficult to detect. These findings provide consistent support for the hypothesis that larger magnitudes of neural variability quenching are associated with better perceptual abilities in multiple visual domain tasks.

scholarly journals Eliciting and Recording Event Related Potentials (ERPs) in Behaviourally Unresponsive Populations: A Retrospective Commentary on Critical Factors

2021 ◽  
Vol 11 (7) ◽  
pp. 835
Author(s):  
Alexander Rokos ◽  
Richard Mah ◽  
Rober Boshra ◽  
Amabilis Harrison ◽  
Tsee Leng Choy ◽  
...  
Keyword(s):  
Event Related Potentials ◽  
Stimulus Presentation ◽  
Event Related Potential ◽  
Critical Factors ◽  
Healthy Elderly ◽  
States Of Consciousness ◽  
Long Latency ◽  
Eeg Data ◽  
Related Potentials ◽  
The Relationship

A consistent limitation when designing event-related potential paradigms and interpreting results is a lack of consideration of the multivariate factors that affect their elicitation and detection in behaviorally unresponsive individuals. This paper provides a retrospective commentary on three factors that influence the presence and morphology of long-latency event-related potentials—the P3b and N400. We analyze event-related potentials derived from electroencephalographic (EEG) data collected from small groups of healthy youth and healthy elderly to illustrate the effect of paradigm strength and subject age; we analyze ERPs collected from an individual with severe traumatic brain injury to illustrate the effect of stimulus presentation speed. Based on these critical factors, we support that: (1) the strongest paradigms should be used to elicit event-related potentials in unresponsive populations; (2) interpretation of event-related potential results should account for participant age; and (3) speed of stimulus presentation should be slower in unresponsive individuals. The application of these practices when eliciting and recording event-related potentials in unresponsive individuals will help to minimize result interpretation ambiguity, increase confidence in conclusions, and advance the understanding of the relationship between long-latency event-related potentials and states of consciousness.

Encoding of graded changes in spatial specificity of prior cues in human visual cortex

2014 ◽  
Vol 112 (11) ◽  
pp. 2834-2849 ◽  
Author(s):  
Yuko Hara ◽  
Justin L. Gardner
Keyword(s):  
Prior Information ◽  
Prior Probability ◽  
Blood Oxygenation ◽  
Response Magnitude ◽  
Behavioral Performance ◽  
Significant Difference ◽  
Cortical Responses ◽  
Sensory Responses ◽  
Contrast Discrimination ◽  
Spatial Specificity

Prior information about the relevance of spatial locations can vary in specificity; a single location, a subset of locations, or all locations may be of potential importance. Using a contrast-discrimination task with four possible targets, we asked whether performance benefits are graded with the spatial specificity of a prior cue and whether we could quantitatively account for behavioral performance with cortical activity changes measured by blood oxygenation level-dependent (BOLD) imaging. Thus we changed the prior probability that each location contained the target from 100 to 50 to 25% by cueing in advance 1, 2, or 4 of the possible locations. We found that behavioral performance (discrimination thresholds) improved in a graded fashion with spatial specificity. However, concurrently measured cortical responses from retinotopically defined visual areas were not strictly graded; response magnitude decreased when all 4 locations were cued (25% prior probability) relative to the 100 and 50% prior probability conditions, but no significant difference in response magnitude was found between the 100 and 50% prior probability conditions for either cued or uncued locations. Also, although cueing locations increased responses relative to noncueing, this cue sensitivity was not graded with prior probability. Furthermore, contrast sensitivity of cortical responses, which could improve contrast discrimination performance, was not graded. Instead, an efficient-selection model showed that even if sensory responses do not strictly scale with prior probability, selection of sensory responses by weighting larger responses more can result in graded behavioral performance benefits with increasing spatial specificity of prior information.

scholarly journals Neural Variability Quenching Predicts Individual Perceptual Abilities

2016 ◽  
Vol 37 (1) ◽  
pp. 97-109 ◽  
Author(s):  
Ayelet Arazi ◽  
Nitzan Censor ◽  
Ilan Dinstein
Keyword(s):  
Perceptual Abilities ◽  
Neural Variability

scholarly journals Is predictability salient? A study of attentional capture by auditory patterns

2017 ◽  
Vol 372 (1714) ◽  
pp. 20160105 ◽  
Author(s):  
Rosy Southwell ◽  
Anna Baumann ◽  
Cécile Gal ◽  
Nicolas Barascud ◽  
Karl Friston ◽  
...  
Keyword(s):  
Attentional Capture ◽  
Predictive Coding ◽  
Visual Scene ◽  
Scene Analysis ◽  
Neural Responses ◽  
Eeg Data ◽  
Visual Domain ◽  
The Brain ◽  
Repeating Patterns

In this series of behavioural and electroencephalography (EEG) experiments, we investigate the extent to which repeating patterns of sounds capture attention. Work in the visual domain has revealed attentional capture by statistically predictable stimuli, consistent with predictive coding accounts which suggest that attention is drawn to sensory regularities. Here, stimuli comprised rapid sequences of tone pips, arranged in regular (REG) or random (RAND) patterns. EEG data demonstrate that the brain rapidly recognizes predictable patterns manifested as a rapid increase in responses to REG relative to RAND sequences. This increase is reminiscent of the increase in gain on neural responses to attended stimuli often seen in the neuroimaging literature, and thus consistent with the hypothesis that predictable sequences draw attention. To study potential attentional capture by auditory regularities, we used REG and RAND sequences in two different behavioural tasks designed to reveal effects of attentional capture by regularity. Overall, the pattern of results suggests that regularity does not capture attention. This article is part of the themed issue ‘Auditory and visual scene analysis’.

scholarly journals Increasing the Mobility of EEG Data Collection Using a Latte Panda Computer

2018 ◽  
Author(s):  
Jonathan W. P. Kuziek ◽  
Eden X. Redman ◽  
Graeme D. Splinter ◽  
Kyle E. Mathewson
Keyword(s):  
Data Collection ◽  
Low Cost ◽  
Event Related Potentials ◽  
Stimulus Presentation ◽  
Laptop Computer ◽  
Muscle Movement ◽  
Auditory Oddball ◽  
Processing Power ◽  
Eeg Data ◽  
Related Potentials

AbstractBackgroundElectroencephalography (EEG) experiments often require several computers to ensure accurate stimulus presentation and data collection. However, this requirement can make it more difficult to perform such experiments in mobile settings within, or outside, the laboratoryNew MethodComputer miniaturisation and increasing processing power allow for EEG experiments to become more portable. Our goal is to show that a Latte Panda, a small Windows 10 computer, can be used to accurately collect EEG data in a similar manner to a laptop. Using a stationary bike, we also demonstrate that the Latte Panda will allow for more portable EEG experiments.ResultsSignificant and reliable MMN and P3 responses, event-related potentials (ERPs) typically associated with auditory oddball tasks, were observed and were consistent when using either the laptop or Latte Panda for EEG data collection. Similar MMN and P3 ERPs were also measured in the sitting and stationary biking conditions while using a Latte Panda for data collection.Comparison with Existing MethodData recorded by the Latte Panda computer produced comparable and equally reliable results to the laptop. As well, similar ERPs during sitting and biking would suggest that EEG experiments can be conducted in more mobile situations despite the increased noise and artefacts associated with muscle movement.ConclusionsOur results show that the Latte Panda is a low-cost, more portable alternative to a laptop computer for recording EEG data. Such a device will further allow for more portable and mobile EEG experimentation in a wider variety of environments.

scholarly journals Comparing Neural Correlates of Human Emotions across Multiple Stimulus Presentation Paradigms

2021 ◽  
Vol 11 (6) ◽  
pp. 696
Author(s):  
Naveen Masood ◽  
Humera Farooq
Keyword(s):  
Emotion Recognition ◽  
Stimulus Presentation ◽  
Neural Correlates ◽  
Classification Performance ◽  
Emotional States ◽  
Common Spatial Pattern ◽  
Spatial Filters ◽  
Linear Discriminant ◽  
Spectral Bands ◽  
Eeg Data

Most electroencephalography (EEG)-based emotion recognition systems rely on a single stimulus to evoke emotions. These systems make use of videos, sounds, and images as stimuli. Few studies have been found for self-induced emotions. The question “if different stimulus presentation paradigms for same emotion, produce any subject and stimulus independent neural correlates” remains unanswered. Furthermore, we found that there are publicly available datasets that are used in a large number of studies targeting EEG-based human emotional state recognition. Since one of the major concerns and contributions of this work is towards classifying emotions while subjects experience different stimulus-presentation paradigms, we need to perform new experiments. This paper presents a novel experimental study that recorded EEG data for three different human emotional states evoked with four different stimuli presentation paradigms. Fear, neutral, and joy have been considered as three emotional states. In this work, features were extracted with common spatial pattern (CSP) from recorded EEG data and classified through linear discriminant analysis (LDA). The considered emotion-evoking paradigms included emotional imagery, pictures, sounds, and audio–video movie clips. Experiments were conducted with twenty-five participants. Classification performance in different paradigms was evaluated, considering different spectral bands. With a few exceptions, all paradigms showed the best emotion recognition for higher frequency spectral ranges. Interestingly, joy emotions were classified more strongly as compared to fear. The average neural patterns for fear vs. joy emotional states are presented with topographical maps based on spatial filters obtained with CSP for averaged band power changes for all four paradigms. With respect to the spectral bands, beta and alpha oscillation responses produced the highest number of significant results for the paradigms under consideration. With respect to brain region, the frontal lobe produced the most significant results irrespective of paradigms and spectral bands. The temporal site also played an effective role in generating statistically significant findings. To the best of our knowledge, no study has been conducted for EEG emotion recognition while considering four different stimuli paradigms. This work provides a good contribution towards designing EEG-based system for human emotion recognition that could work effectively in different real-time scenarios.

EEG electrodes selection for emotion recognition independent of stimulus presentation paradigms

2021 ◽  
pp. 1-17
Author(s):  
Naveen Masood ◽  
Humera Farooq
Keyword(s):  
Emotion Recognition ◽  
Stimulus Presentation ◽  
Setup Time ◽  
Majority Voting ◽  
Emotional States ◽  
Smart Systems ◽  
Eeg Data ◽  
Recognition Systems ◽  
Selection For ◽  
Set Up

Most of the electroencephalography (EEG) based emotion recognition systems rely on single stimulus to evoke emotions. EEG data is mostly recorded with higher number of electrodes that can lead to data redundancy and longer experimental setup time. The question “whether the configuration with lesser number of electrodes is common amongst different stimuli presentation paradigms” remains unanswered. There are publicly available datasets for EEG based human emotional states recognition. Since this work is focused towards classifying emotions while subjects are experiencing different stimuli, therefore we need to perform new experiments. Keeping aforementioned issues in consideration, this work presents a novel experimental study that records EEG data for three different human emotional states evoked with four different stimuli presentation paradigms. A methodology based on iterative Genetic Algorithm in combination with majority voting has been used to achieve configuration with reduced number of EEG electrodes keeping in consideration minimum loss of classification accuracy. The results obtained are comparable with recent studies. Stimulus independent configurations with lesser number of electrodes lead towards low computational complexity as well as reduced set up time for future EEG based smart systems for emotions recognition

scholarly journals Real brains in virtual worlds: Validating a novel oddball paradigm in virtual reality

2019 ◽  
Author(s):  
Jonathan W. P. Kuziek ◽  
Abdel R. Tayem ◽  
Jennifer I. Burrell ◽  
Eden X. Redman ◽  
Jeff Murray ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Virtual Worlds ◽  
Spectral Composition ◽  
Stimulus Presentation ◽  
Event Related Potential ◽  
Oddball Paradigm ◽  
Auditory Oddball ◽  
Oddball Task ◽  
Eeg Data ◽  
Head Mounted Displays

Electroencephalography (EEG) research is typically conducted in controlled laboratory settings. This limits the generalizability to real-world situations. Virtual reality (VR) sits as a transitional tool that provides tight experimental control with more realistic stimuli. To test the validity of using VR for event-related potential (ERP) research we used a well-established paradigm, the oddball task. For our first study, we compared VR to traditional, monitor-based stimulus presentation using visual and auditory oddball tasks while EEG data was recorded. We were able to measure ERP waveforms typically associated with such oddball tasks, namely the P3 and earlier N2 components, in both conditions. Our results suggest that ERPs collected using VR head mounted displays and typical monitors were comparable on measures of latency, amplitude, and spectral composition. In a second study, we implemented a novel depth-based oddball task and we were able to measure the typical oddball-related ERPs elicited by the presentation of near and far stimuli. Interestingly, we observed significant differences in early ERPs components between near and far stimuli, even after controlling for the effects of the oddball task. Current results suggest that VR can serve as a valid means of stimulus presentation in novel or otherwise inaccessible environments for EEG experimentation. We demonstrated the capability of a depth-based oddball in reliably eliciting a P3 waveform. We also found an interaction between the depth at which objects are presented and early ERP responses. Further research is warranted to better explain this influence of depth on the EEG and ERP activity.

scholarly journals Stimulus presentation can enhance spiking irregularity across subcortical and cortical regions

2021 ◽  
Author(s):  
Saleh Fayyaz ◽  
MohammadAmin Fakharian ◽  
Ali Ghazizadeh
Keyword(s):  
Stimulus Presentation ◽  
Fano Factor ◽  
Brain Regions ◽  
Accurate Estimation ◽  
Time Varying ◽  
Doubly Stochastic ◽  
Relative Contribution ◽  
Stochastic Point Process ◽  
Cortical Regions ◽  
Neural Variability

Stimulus presentation is believed to quench neural response variability as measured by fano-factor (FF). However, the relative contribution of within trial spike irregularity (nψ) and trial to trial rate variability (nRV) to FF reduction has remained elusive. Here, we introduce a principled approach for accurate estimation of variability components for a doubly stochastic point process which unlike previous methods allows for a time varying nψ (aka φ). Notably, analysis across multiple subcortical and cortical areas showed across the board reduction in rate variability. However, unlike what was previously thought, spiking irregularity was not constant in time and was even enhanced in some regions abating the quench in the post-stimulus FF. Simulations confirmed plausibility of a time varying nψ arising from within and between pool correlations of excitatory and inhibitory neural inputs. By accurate parsing of neural variability, our approach constrains candidate mechanisms that give rise to observed rate variability and spiking irregularity within brain regions.

scholarly journals Reading spike timing without a clock: intrinsic decoding of spike trains

2014 ◽  
Vol 369 (1637) ◽  
pp. 20120467 ◽  
Author(s):  
Stefano Panzeri ◽  
Robin A. A. Ince ◽  
Mathew E. Diamond ◽  
Christoph Kayser
Keyword(s):  
Reference Frames ◽  
Time Windows ◽  
Sensory Information ◽  
Low Frequency ◽  
Stimulus Presentation ◽  
Stimulus Onset ◽  
Spike Timing ◽  
Temporal Reference ◽  
Neural Populations ◽  
Spike Patterns

The precise timing of action potentials of sensory neurons relative to the time of stimulus presentation carries substantial sensory information that is lost or degraded when these responses are summed over longer time windows. However, it is unclear whether and how downstream networks can access information in precise time-varying neural responses. Here, we review approaches to test the hypothesis that the activity of neural populations provides the temporal reference frames needed to decode temporal spike patterns. These approaches are based on comparing the single-trial stimulus discriminability obtained from neural codes defined with respect to network-intrinsic reference frames to the discriminability obtained from codes defined relative to the experimenter's computer clock. Application of this formalism to auditory, visual and somatosensory data shows that information carried by millisecond-scale spike times can be decoded robustly even with little or no independent external knowledge of stimulus time. In cortex, key components of such intrinsic temporal reference frames include dedicated neural populations that signal stimulus onset with reliable and precise latencies, and low-frequency oscillations that can serve as reference for partitioning extended neuronal responses into informative spike patterns.

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