scholarly journals Neurophysiological Correlates of Asymmetries in Vowel Perception: An English-French Cross-Linguistic Event-Related Potential Study

2021 ◽  
Vol 15 ◽  
Author(s):  
Linda Polka ◽  
Monika Molnar ◽  
T. Christina Zhao ◽  
Matthew Masapollo
Keyword(s):  
Short Term Memory ◽  
Time Window ◽  
Stimulus Presentation ◽  
Event Related Potential ◽  
Oscillatory Activity ◽  
Processing Efficiency ◽  
Stimulus Interval ◽  
Vowel Perception ◽  
Time Frequency ◽  
Auditory Change Detection

Behavioral studies examining vowel perception in infancy indicate that, for many vowel contrasts, the ease of discrimination changes depending on the order of stimulus presentation, regardless of the language from which the contrast is drawn and the ambient language that infants have experienced. By adulthood, linguistic experience has altered vowel perception; analogous asymmetries are observed for non−native contrasts but are mitigated for native contrasts. Although these directional effects are well documented behaviorally, the brain mechanisms underlying them are poorly understood. In the present study we begin to address this gap. We first review recent behavioral work which shows that vowel perception asymmetries derive from phonetic encoding strategies, rather than general auditory processes. Two existing theoretical models–the Natural Referent Vowel framework and the Native Language Magnet model–are invoked as a means of interpreting these findings. Then we present the results of a neurophysiological study which builds on this prior work. Using event-related brain potentials, we first measured and assessed the mismatch negativity response (MMN, a passive neurophysiological index of auditory change detection) in English and French native-speaking adults to synthetic vowels that either spanned two different phonetic categories (/y/vs./u/) or fell within the same category (/u/). Stimulus presentation was organized such that each vowel was presented as standard and as deviant in different blocks. The vowels were presented with a long (1,600-ms) inter-stimulus interval to restrict access to short-term memory traces and tap into a “phonetic mode” of processing. MMN analyses revealed weak asymmetry effects regardless of the (i) vowel contrast, (ii) language group, and (iii) MMN time window. Then, we conducted time-frequency analyses of the standard epochs for each vowel. In contrast to the MMN analysis, time-frequency analysis revealed significant differences in brain oscillations in the theta band (4–8 Hz), which have been linked to attention and processing efficiency. Collectively, these findings suggest that early-latency (pre-attentive) mismatch responses may not be a strong neurophysiological correlate of asymmetric behavioral vowel discrimination. Rather, asymmetries may reflect differences in neural processing efficiency for vowels with certain inherent acoustic-phonetic properties, as revealed by theta oscillatory activity.

Distinction between Perceptual and Attentional Processing in Working Memory Tasks: A Study of Phase-locked and Induced Oscillatory Brain Dynamics

2007 ◽  
Vol 19 (1) ◽  
pp. 158-172 ◽  
Author(s):  
Marie-Pierre Deiber ◽  
Pascal Missonnier ◽  
Olivier Bertrand ◽  
Gabriel Gold ◽  
Lara Fazio-Costa ◽  
...  
Keyword(s):  
Working Memory ◽  
Memory Load ◽  
Stimulus Presentation ◽  
Theta Activity ◽  
Oscillatory Activity ◽  
Focused Attention ◽  
Attentional Processing ◽  
Time Frequency ◽  
The Neural Network ◽  
Topographical Distribution

Working memory involves the short-term storage and manipulation of information necessary for cognitive performance, including comprehension, learning, reasoning and planning. Although electroencephalogram (EEG) rhythms are modulated during working memory, the temporal relationship of EEG oscillations with the eliciting event has not been well studied. In particular, the dynamics of the neural network supporting memory processes may be best captured in induced oscillations, characterized by a loose temporal link with the stimulus. In order to differentiate induced from evoked functional processes, the present study proposes a time-frequency analysis of the 3 to 30 Hz EEG oscillatory activity in a verbal n-back working memory paradigm. Control tasks were designed to identify oscillatory activity related to stimulus presentation (passive task) and focused attention to the stimulus (detection task). Evoked theta activity (4–8 Hz) phase-locked to the visual stimulus was evidenced in the parieto-occipital region for all tasks. In parallel, induced theta activity was recorded in the frontal region for detection and n-back memory tasks, but not for the passive task, suggesting its dependency on focused attention to the stimulus. Sustained induced oscillatory activity was identified in relation to working memory in the theta and beta (15–25 Hz) frequency bands, larger for the highest memory load. Its late occurrence limited to nonmatched items suggests that it could be related to item retention and active maintenance for further task requirements. Induced theta and beta activities displayed respectively a frontal and parietal topographical distribution, providing further functional information on the fronto-posterior network supporting working memory.

scholarly journals The Electrophysiological Dynamics of Interference during the Stroop Task

2008 ◽  
Vol 20 (2) ◽  
pp. 215-225 ◽  
Author(s):  
Simon Hanslmayr ◽  
Bernhard Pastötter ◽  
Karl-Heinz Bäuml ◽  
Sieglinde Gruber ◽  
Maria Wimber ◽  
...  
Keyword(s):  
Prefrontal Cortex ◽  
Stroop Task ◽  
Time Window ◽  
Word Meaning ◽  
Color Naming ◽  
Event Related Potential ◽  
Anterior Cingulate ◽  
Control Mechanisms ◽  
Phase Coupling ◽  
Time Frequency

If subjects are required to name the color of the word red printed in blue ink, interference between word meaning and ink color occurs, which slows down reaction time. This effect is well known as the Stroop effect. It is still an unresolved issue how the brain deals with interference in this type of task. To explore this question, an electroencephalogram (EEG) study was carried out. By analyzing several measures of EEG activity, two main findings emerged. First, the event-related potential (ERP) showed increased fronto-central negativity in a time window around 400 msec for incongruent items in contrast to congruent and neutral items. Source localization analysis revealed that a source in the anterior cingulate cortex (ACC) contributed most to the difference. Second, time-frequency analysis showed that theta oscillations (4–7 Hz) in the ACC increased linearly with increasing interference and that phase coupling between the ACC and the left prefrontal cortex was longer persistent for incongruent items compared to congruent and neutral items. These effects occurred at a time window around 600 msec. We conclude that interference between color naming and word meaning in the Stroop task manifests itself at around 400 msec and mainly activates the ACC. Thereafter, sustained phase coupling between the ACC and the prefrontal cortex occurs, which most likely reflects the engagement of cognitive control mechanisms.

scholarly journals Pre-stimulus beta-band activity is a signature of statistical learning

2020 ◽  
Author(s):  
Louisa Bogaerts ◽  
Craig G. Richter ◽  
Ayelet N. Landau ◽  
Ram Frost
Keyword(s):  
Statistical Learning ◽  
Time Window ◽  
Stimulus Presentation ◽  
Learning Performance ◽  
Predictive Processing ◽  
Oscillatory Activity ◽  
Beta Band ◽  
Behavioral Learning ◽  
Primary Means ◽  
Highly Correlated

AbstractStatistical learning (SL) is taken to be the main mechanism by which cognitive systems discover the underlying regularities of the environment. We document, in the context of a classical visual SL task, divergent rhythmic EEG activity during the anticipation of stimuli within patterns versus pattern transitions. Our findings reveal differential pre-stimulus oscillatory activity in the beta band (∼20 Hz) that indexes learning: it emerges with increased pattern repetitions, and importantly, it is highly correlated with behavioral learning outcomes. These findings hold the promise of converging on an online measure of learning regularities and provide important theoretical insights regarding the mechanisms of SL and prediction.Significance StatementSL has become a major theoretical construct in cognitive science, providing the primary means by which organisms learn about regularities in the environment. As such it is a critical building block for basic and higher-order cognitive functions.Here we identify for the first time a spectral neural index in the time window prior to stimulus presentation, which evolves with increased pattern exposure, and is predictive of learning performance.The manifestation of learning that is revealed not in stimulus processing but in anticipatory moments of the learning episode, makes a direct link between the fields of statistical learning and predictive processing, and suggests a possible mechanistic account of visual SL.

Sensory and Cognitive Components of Auditory Processing in Individuals With Tinnitus

2019 ◽  
Vol 28 (4) ◽  
pp. 834-842
Author(s):  
Harini Vasudevan ◽  
Hari Prakash Palaniswamy ◽  
Ramaswamy Balakrishnan
Keyword(s):  
Selective Attention ◽  
Auditory Processing ◽  
Function Analysis ◽  
Event Related Potential ◽  
Oscillatory Activity ◽  
Default Mode ◽  
Auditory Selective Attention ◽  
Cognitive Components ◽  
Mode Function ◽  
Related Potentials

Purpose The main purpose of the study is to explore the auditory selective attention abilities (using event-related potentials) and the neuronal oscillatory activity in the default mode network sites (using electroencephalogram [EEG]) in individuals with tinnitus. Method Auditory selective attention was measured using P300, and the resting state EEG was assessed using the default mode function analysis. Ten individuals with continuous and bothersome tinnitus along with 10 age- and gender-matched control participants underwent event-related potential testing and 5 min of EEG recording (at wakeful rest). Results Individuals with tinnitus were observed to have larger N1 and P3 amplitudes along with prolonged P3 latency. The default mode function analysis revealed no significant oscillatory differences between the groups. Conclusion The current study shows changes in both the early sensory and late cognitive components of auditory processing. The change in the P3 component is suggestive of selective auditory attention deficit, and the sensory component (N1) suggests an altered bottom-up processing in individuals with tinnitus.

Feel Thine Own Self – Mood Congruency Evaluation of Emotional State Adjectives

2020 ◽  
pp. 1-17
Author(s):  
Szczepan J. Grzybowski ◽  
Miroslaw Wyczesany ◽  
Jan Kaiser
Keyword(s):  
Mood Induction ◽  
Semantic Analysis ◽  
Emotional State ◽  
Time Window ◽  
Event Related Potential ◽  
Negativity Bias ◽  
Positive Potential ◽  
Semantic Access ◽  
Current Mood ◽  
Component Time

Abstract. The goal of the study was to explore event-related potential (ERP) differences during the processing of emotional adjectives that were evaluated as congruent or incongruent with the current mood. We hypothesized that the first effects of congruence evaluation would be evidenced during the earliest stages of semantic analysis. Sixty mood adjectives were presented separately for 1,000 ms each during two sessions of mood induction. After each presentation, participants evaluated to what extent the word described their mood. The results pointed to incongruence marking of adjective’s meaning with current mood during early attention orientation and semantic access stages (the P150 component time window). This was followed by enhanced processing of congruent words at later stages. As a secondary goal the study also explored word valence effects and their relation to congruence evaluation. In this regard, no significant effects were observed on the ERPs; however, a negativity bias (enhanced responses to negative adjectives) was noted on the behavioral data (RTs), which could correspond to the small differences traced on the late positive potential.

Time Window from Visual Images to Visual Short-Term Memory: Consolidation or Integration?

2004 ◽  
Vol 51 (1) ◽  
pp. 45-51 ◽  
Author(s):  
Yuhong Jiang
Keyword(s):  
Short Term Memory ◽  
Time Window ◽  
Short Interval ◽  
Visual Images ◽  
Short Term ◽  
Temporal Window ◽  
Term Memory ◽  
Visual Short Term Memory ◽  
Probe Task ◽  
Long Time

Abstract. When two dot arrays are briefly presented, separated by a short interval of time, visual short-term memory of the first array is disrupted if the interval between arrays is shorter than 1300-1500 ms ( Brockmole, Wang, & Irwin, 2002 ). Here we investigated whether such a time window was triggered by the necessity to integrate arrays. Using a probe task we removed the need for integration but retained the requirement to represent the images. We found that a long time window was needed for performance to reach asymptote even when integration across images was not required. Furthermore, such window was lengthened if subjects had to remember the locations of the second array, but not if they only conducted a visual search among it. We suggest that a temporal window is required for consolidation of the first array, which is vulnerable to disruption by subsequent images that also need to be memorized.

scholarly journals Electrophysiological aftereffects of high-frequency transcranial random noise stimulation (hf-tRNS): an EEG investigation

2021 ◽  
Author(s):  
Filippo Ghin ◽  
Louise O’Hare ◽  
Andrea Pavan
Keyword(s):  
High Frequency ◽  
Discrimination Task ◽  
Temporal Dynamics ◽  
Random Noise ◽  
Decomposition Analysis ◽  
Oscillatory Activity ◽  
Motion Direction ◽  
Time Frequency ◽  
Direction Discrimination ◽  
Transcranial Random Noise Stimulation

AbstractThere is evidence that high-frequency transcranial random noise stimulation (hf-tRNS) is effective in improving behavioural performance in several visual tasks. However, so far there has been limited research into the spatial and temporal characteristics of hf-tRNS-induced facilitatory effects. In the present study, electroencephalogram (EEG) was used to investigate the spatial and temporal dynamics of cortical activity modulated by offline hf-tRNS on performance on a motion direction discrimination task. We used EEG to measure the amplitude of motion-related VEPs over the parieto-occipital cortex, as well as oscillatory power spectral density (PSD) at rest. A time–frequency decomposition analysis was also performed to investigate the shift in event-related spectral perturbation (ERSP) in response to the motion stimuli between the pre- and post-stimulation period. The results showed that the accuracy of the motion direction discrimination task was not modulated by offline hf-tRNS. Although the motion task was able to elicit motion-dependent VEP components (P1, N2, and P2), none of them showed any significant change between pre- and post-stimulation. We also found a time-dependent increase of the PSD in alpha and beta bands regardless of the stimulation protocol. Finally, time–frequency analysis showed a modulation of ERSP power in the hf-tRNS condition for gamma activity when compared to pre-stimulation periods and Sham stimulation. Overall, these results show that offline hf-tRNS may induce moderate aftereffects in brain oscillatory activity.

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.

scholarly journals Time–frequency time–space LSTM for robust classification of physiological signals

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tuan D. Pham
Keyword(s):  
Time Series ◽  
Network Architecture ◽  
Time Series Data ◽  
Short Term Memory ◽  
Physiological Signals ◽  
Series Data ◽  
Time Frequency ◽  
Time Space ◽  
Deep Recurrent Neural Network

AbstractAutomated analysis of physiological time series is utilized for many clinical applications in medicine and life sciences. Long short-term memory (LSTM) is a deep recurrent neural network architecture used for classification of time-series data. Here time–frequency and time–space properties of time series are introduced as a robust tool for LSTM processing of long sequential data in physiology. Based on classification results obtained from two databases of sensor-induced physiological signals, the proposed approach has the potential for (1) achieving very high classification accuracy, (2) saving tremendous time for data learning, and (3) being cost-effective and user-comfortable for clinical trials by reducing multiple wearable sensors for data recording.

scholarly journals Time-frequency time-space long short-term memory networks for image classification of histopathological tissue

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tuan D. Pham
Keyword(s):  
Image Analysis ◽  
Short Term Memory ◽  
Disease Diagnosis ◽  
Short Term ◽  
Term Memory ◽  
Time Frequency ◽  
Time Space ◽  
Histopathological Images ◽  
Long Short Term Memory

AbstractImage analysis in histopathology provides insights into the microscopic examination of tissue for disease diagnosis, prognosis, and biomarker discovery. Particularly for cancer research, precise classification of histopathological images is the ultimate objective of the image analysis. Here, the time-frequency time-space long short-term memory network (TF-TS LSTM) developed for classification of time series is applied for classifying histopathological images. The deep learning is empowered by the use of sequential time-frequency and time-space features extracted from the images. Furthermore, unlike conventional classification practice, a strategy for class modeling is designed to leverage the learning power of the TF-TS LSTM. Tests on several datasets of histopathological images of haematoxylin-and-eosin and immunohistochemistry stains demonstrate the strong capability of the artificial intelligence (AI)-based approach for producing very accurate classification results. The proposed approach has the potential to be an AI tool for robust classification of histopathological images.

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