Search Results (44)

Background/Objectives: Since high frequencies are susceptible to disruption in various types of hearing loss, a symptom which is common in people with tinnitus, the aim of the study was to investigate EEG cortical auditory evoked and P300 responses to both a high- and low frequency-centered oddball paradigm to begin to establish the most suitable cognitive physiologic testing conditions for those with both unimpaired hearing and those with hearing impairments. Methods: Cortical auditory evoked potential (CAEP) P1, N1, P2 and P300 (subtraction wave) peaks were identified in response to high- (standard: 6000 Hz, deviant: 8000 Hz) and low frequency (Standard: 375 Hz, Deviant: 500 Hz) oddball paradigms. Each paradigm was presented at various intensity levels. Latencies and amplitudes were then computed for each condition to assess the effects of frequency and intensity. Results: Stimulus intensity had no effect on either the high- or low frequency paradigms of P300 characteristics. In contrast, for the low frequency paradigm, intensity influenced the N1 latency and P2 amplitude, while for the high frequency paradigm intensity influenced P1 and P2 latency and P2 amplitude. Conclusions: Obligatory CAEP components responded more readily to stimulus frequency and intensity changes, and one possible consideration is that higher frequencies could play a role in the response characteristics exhibited by N1 (except for N1 amplitude) and P2, given their involvement in attentional processes linked to the detection of warning cues. P300 latency and amplitude were not influenced by such factors. These findings support the hypothesis that disentangling the cognitive from the more sensory-based response is possible, even in those with hearing loss, provided that the patient’s hearing loss is considered when determining the presentation level. While the present study was performed in participants with unimpaired hearing, these data set up future studies investigating the effectiveness of using similar methods in hearing-impaired persons. Full article

Background/Objectives: Coma prognosis is challenging, as patient presentation can be misleading or uninformative when using behavioral assessments only. Event-related potentials have been shown to provide valuable information about a patient’s chance of survival and emergence from coma. Our prior work revealed that the mismatch negativity (MMN) in particular waxes and wanes across 24 h in some coma patients. This “cycling” aspect of the presence/absence of neurophysiological responses may require fine-grained tools to increase the chances of detecting levels of neural processing in coma. This study implements multivariate pattern analysis (MVPA) to automatically quantify patterns of neural discrimination between duration deviant and standard tones over time at the single-subject level in seventeen healthy controls and in three comatose patients. Methods: One EEG recording, containing up to five blocks of an auditory oddball paradigm, was performed in controls over a 12 h period. For patients, two EEG sessions were conducted 3 days apart for up to 24 h, denoted as day 0 and day 3, respectively. MVPA was performed using a support-vector machine classifier. Results: Healthy controls exhibited reliable discrimination or classification performance during the latency intervals associated with MMN and P3a components. Two patients showed some intervals with significant discrimination around the second half of day 0, and all had significant results on day 3. Conclusions: These findings suggest that decoding analyses can accurately classify neural responses at a single-subject level in healthy controls and provide evidence of small but significant changes in auditory discrimination over time in coma patients. Further research is needed to confirm whether this approach represents an improved technology for assessing cognitive processing in coma. Full article

P300 detection is a difficult task in brain–computer interface (BCI) systems due to the low signal-to-noise ratio (SNR). In BCI systems, P300 waves are generated in electroencephalogram (EEG) signals using various oddball paradigms. Convolutional neural networks (CNNs) have previously shown excellent results for P300 detection compared to different machine learning models. However, current CNN architectures limit P300 detection accuracy because these models usually only extract single-scale features. Aiming to enhance P300 detection accuracy, an inception module-based CNN architecture, namely Inception-CNN, is introduced. Inception-CNN effectively learns discriminative features from both spatial and temporal information to reduce overfitting and computational complexity. Furthermore, it can extract multi-scale features, which effectively improves P300 detection accuracy and increases character spelling accuracy. To analyze the effect of the inception layer, two additional models are proposed: Inception-CNN-S, which uses the inception layer with a spatial convolution layer, and Inception-CNN-T, which uses the inception layer with a temporal convolution layer. The proposed model was evaluated on dataset II of BCI Competition III and dataset IIb of BCI Competition II. The experimental results show that Inception-CNN provides a promising solution for improving the accuracy of P300 detection, with F1 scores of 47.14%, 55.28%, and 78.94% for dataset II of BCI Competition III (Subject A and Subject B) and dataset IIb of BCI Competition II, respectively. Full article

Background/Objectives: Previous studies have examined the role of working memory in cognitive tasks such as syntactic, semantic, and phonological processing, thereby contributing to our understanding of linguistic information management and retrieval. However, the real-time processing of phonological information—particularly in relation to suprasegmental features like tone, where its contour represents a time-varying signal—remains a relatively underexplored area within the framework of Information Processing Theory (IPT). This study aimed to address this gap by investigating the real-time processing of similar tonal information by native Cantonese speakers, thereby providing a deeper understanding of how IPT applies to auditory processing. Methods: Specifically, this study combined assessments of cognitive functions, an AX discrimination task, and electroencephalography (EEG) to investigate the discrimination results and real-time processing characteristics of native Macau Cantonese speakers perceiving three pairs of similar tones. Results: The behavioral results confirmed the completed merging of T2–T5 in Macau Cantonese, and the ongoing merging of T3–T6 and T4–T6, with perceptual merging rates of 45.46% and 27.28%, respectively. Mismatch negativity (MMN) results from the passive oddball experiment revealed distinct temporal processing patterns for the three tone pairs. Cognitive functions, particularly attention and working memory, significantly influenced tone discrimination, with more pronounced effects observed in the mean amplitude of MMN during T4–T6 discrimination. Differences in MMN peak latency between T3–T6 and T4–T6 further suggested the use of different perceptual strategies for these contour-related tones. Specifically, the T3–T6 pair can be perceived through early signal input, whereas the perception of T4–T6 relies on constant signal input. Conclusions: This distinction in cognitive resource allocation may explain the different merging rates of the two tone pairs. This study, by focusing on the perceptual difficulty of tone pairs and employing EEG techniques, revealed the temporal processing of similar tones by native speakers, providing new insights into tone phoneme processing and speech variation. Full article

Background: In the oddball paradigm, the dorsolateral prefrontal cortex (DLPFC) is often associated with active cognitive responses, such as maintaining information in working memory or adapting response strategies. While some evidence points to the DLPFC’s role in passive auditory deviance perception, a detailed understanding of the spatiotemporal neurodynamics involved remains unclear. Methods: In this study, event-related optical signals (EROS) and event-related potentials (ERPs) were simultaneously recorded for the first time over the prefrontal cortex using a 64-channel electroencephalography (EEG) system, during passive auditory deviance perception in 12 right-handed young adults (7 women and 5 men). In this oddball paradigm, deviant stimuli (a 1500 Hz pure tone) elicited a negative shift in the N1 ERP component, related to mismatch negativity (MMN), and a significant positive deflection associated with the P300, compared to standard stimuli (a 1000 Hz tone). Results: We hypothesize that the DLPFC not only participates in active tasks but also plays a critical role in processing deviant stimuli in passive conditions, shifting from pre-attentive to attentive processing. We detected enhanced neural activity in the left middle frontal gyrus (MFG), at the same timing of the MMN component, followed by later activation at the timing of the P3a ERP component in the right MFG. Conclusions: Understanding these dynamics will provide deeper insights into the DLPFC’s role in evaluating the novelty or unexpectedness of the deviant stimulus, updating its cognitive value, and adjusting future predictions accordingly. However, the small number of subjects could limit the generalizability of the observations, in particular with respect to the effect of handedness, and additional studies with larger and more diverse samples are necessary to validate our conclusions. Full article

Electroencephalography (EEG) is a non-invasive method used to track human brain activity over time. The time-locked EEG to an external event is known as event-related potential (ERP). ERP can be a biomarker of human perception and other cognitive processes. The success of ERP research depends on the laboratory conditions and attentiveness of the test subjects. Specifically, the inability to control experimental variables has reduced ERP research in the real world. This study collected EEG data under various experimental circumstances within an auditory oddball paradigm experiment to enable the use of ERP as an active biomarker in normal laboratory conditions. Then, ERP epochs were analyzed to identify unfocused epochs, affected by typical artifacts and external distortion. For the initial comparison, the ability of four unsupervised machine learning algorithms (MLAs) was evaluated to identify unfocused epochs. Then, their accuracy was compared with the human inspection and a current EEG analysis tool (EEGLab). All four MLAs were typically 95–100% accurate. In summary, our analysis finds that humans might miss subtle differences in the regular ERP patterns, but MLAs could efficiently identify those. Thus, our analysis suggests that unsupervised MLAs perform better for detecting unfocused ERP epochs compared with the other two standard methods. Full article

Earlier research has suggested gender differences in event-related potentials/oscillations (ERPs/EROs). Yet, the alteration in event-related oscillations (EROs) in the delta and theta frequency bands have not been explored between genders across the three age groups of adulthood, i.e., 18–50, 51–65, and >65 years. Data from 155 healthy elderly participants who underwent a neurological examination, comprehensive neuropsychological assessment (including attention, memory, executive function, language, and visuospatial skills), and magnetic resonance imaging (MRI) from past studies were used. The delta and theta ERO powers across the age groups and between genders were compared and correlational analyses among the ERO power, age, and neuropsychological tests were performed. The results indicated that females displayed higher theta ERO responses than males in the frontal, central, and parietal regions but not in the occipital location between 18 and 50 years of adulthood. The declining theta power of EROs in women reached that of men after the age of 50 while the theta ERO power was more stable across the age groups in men. Our results imply that the cohorts must be recruited at specified age ranges across genders, and clinical trials using neurophysiological biomarkers as an intervention endpoint should take gender into account in the future. Full article

Developmental changes in functional neural networks are sensitive to environmental influences. This EEG study investigated how infant brain responses relate to the social context that their families live in. Event-related potentials of 255 healthy, awake infants between six and fourteen months were measured during a passive auditory oddball paradigm. Infants were presented with 200 standard tones and 48 randomly distributed deviants. All infants are part of a longitudinal study focusing on families with socioeconomic and/or cultural challenges (Bremen Initiative to Foster Early Childhood Development; BRISE; Germany). As part of their familial socioeconomic status (SES), parental level of education and infant’s migration background were assessed with questionnaires. For 30.6% of the infants both parents had a low level of education (≤10 years of schooling) and for 43.1% of the infants at least one parent was born abroad. The N2–P3a complex is associated with unintentional directing of attention to deviant stimuli and was analysed in frontocentral brain regions. Age was utilised as a control variable. Our results show that tone deviations in infants trigger an immature N2–P3a complex. Contrary to studies with older children or adults, the N2 amplitude was more positive for deviants than for standards. This may be related to an immature superposition of the N2 with the P3a. For infants whose parents had no high-school degree and were born abroad, this tendency was increased, indicating that facing multiple challenges as a young family impacts on the infant’s early neural development. As such, attending to unexpected stimulus changes may be important for early learning processes. Variations of the infant N2–P3a complex may, thus, relate to early changes in attentional capacity and learning experiences due to familial challenges. This points towards the importance of early prevention programs. Full article

Background/Objectives: Tourette Syndrome (TS), Obsessive Compulsive Disorder (OCD), and Body-Focused Repetitive Behaviors (BFRB) are three disorders that share many similarities in terms of phenomenology, neuroanatomy, and functionality. However, despite the literature pointing toward a plausible spectrum of these disorders, only a few studies have compared them. Studying the neurocognitive processes using Event-Related Potentials (ERPs) offers the advantage of assessing brain activity with excellent temporal resolution. The ERP components can then reflect specific processes known to be potentially affected by these disorders. Our first goal is to characterize ‘when’ in the processing stream group differences are the most prominent. The second goal is to identify ‘where’ in the brain the group discrepancies could be. Methods: Participants with TS (n = 24), OCD (n = 18), and BFRB (n = 16) were matched to a control group (n = 59) and were recorded with 58 EEG electrodes during a visual counting oddball task. Three ERP components were extracted (i.e., P200, N200, and P300), and generating sources were modelized with Standardized Low-Resolution Electromagnetic Tomography. Results: We showed no group differences for the P200 and N200 when controlling for anxiety and depressive symptoms, suggesting that the early cognitive processes reflected by these components are relatively intact in these populations. Our results also showed a decrease in the later anterior P300 oddball effect for the TS and OCD groups, whereas an intact oddball effect was observed for the BFRB group. Source localization analyses with sLORETA revealed activations in the lingual and middle occipital gyrus for the OCD group, distinguishing it from the other two clinical groups and the controls. Conclusions: It seems that both TS and OCD groups share deficits in anterior P300 activation but reflect distinct brain-generating source activations. Full article

Understanding pedestrians’ cognitive processes in traffic environments is crucial for developing strategies to enhance safety and reduce accidents. This study assesses the efficacy of virtual reality (VR) in evaluating pedestrian behavior in simulated road-crossing scenarios. It investigates VR’s capability to realistically mimic the cognitive load experienced in real-world settings. It examines the technical integration of VR with psychophysiological recording to capture cognitive demand indicators accurately. Utilizing a dedicated VR application and electroencephalogram (EEG) measurements, this research aims to elicit significant Event-Related Potentials (ERP), like P3 and Contingent Negative Variation (CNV), associated with decision-making processes. The initial results demonstrate VR’s effectiveness in creating realistic environments for investigating cognitive mechanisms and the balance between induced immersion and experienced discomfort. Additionally, the tasks involving time-to-arrival estimations and oddball scenarios elicited the anticipated components related to attentional and decision-making processes. Despite increased discomfort with extended VR exposure, our results show that it did not negatively impact the cognitive workload. These outcomes highlight VR’s efficacy in replicating the cognitive demands of real-world settings and provide evidence to understand the neurophysiological and behavioral dynamics of vulnerable road users (VRUs) in traffic scenarios. Furthermore, these findings support VR’s role in behavioral and neurophysiological research to design specific safety interventions for VRUs. Full article

The birth and following growth of social media platforms has influenced a lot. In addition to beneficial features, it has long-been noticed that heavy consumption of social media can have negative effects beyond a simple lack of time for other things. Of particular interest is the idea that consuming short videos lasting only fractions of a minute and watched one after another can lead to deficits in concentration and attention. Completing the existing literature that already reports evidence for attention deficits related to heavy social media use, the present study aims to contribute to this acute topic by adding neurophysiological data to it. In particular, this study made use of a well-known experimental paradigm, which is able to detect attention-related changes on a neurophysiological level. The so-called oddball paradigm was applied and the hypothesis that heavy social media users mainly consuming short videos show a reduced P300 event-related potential (ERP) component was tested, which has been found to reflect attention-related brain functions. For this, we invited twenty-nine participants and designed a visual oddball experiment including a white circle on black background as the low-frequency target stimulus and a white triangle on black background as the high-frequency non-target stimulus. On the basis of their self-reported short-video-based social media usage habits, all participants were grouped into heavy (more than 4 h daily usage) and regular (below 3 h daily usage) users, and finally data from 14 heavy and 15 regular users were further analyzed. It was found that only regular users show a clear P300 ERP component, while this particular brain potential amplitude reflecting attentional processes was significantly reduced in heavy users. This result provides empirical brain imaging evidence that heavy short-video-based social media use indeed affects attentional brain processes in a negative way. Full article

Lacticaseibacillus paracasei strain Shirota (LcS) modulates psychological homeostasis via the gut–brain axis. To explore the possible efficacy of LcS for improving daytime performance, we conducted a double-blind, randomized, crossover, placebo-controlled study of 12 healthy office workers with sleep complaints. The participants received fermented milk containing viable LcS (daily intake of 1 × 10¹¹ colony-forming units) and non-fermented placebo milk, each for a 4-week period. In the last week of each period, the participants underwent assessments of their subjective mood and measurements of physiological state indicators via an electroencephalogram (EEG) and heart rate variability in the morning and afternoon. The attention score in the afternoon as assessed by the visual analog scale was higher in the LcS intake period than in the placebo intake period (p = 0.041). Theta power on EEG measured at rest or during an auditory oddball task in the afternoon was significantly lower in the LcS period than in the placebo period (p = 0.025 and 0.009, respectively). The change rate of theta power was associated with the change in attention score. Treatment-associated changes were also observed in heart rate and the sympathetic nerve activity index. These results indicate that LcS has possible efficacy for improving daytime performance, supported by observations of the related physiological state indicators. Full article

Characterizing the brain’s dynamic pattern of response to an input in electroencephalography (EEG) is not a trivial task due to the entanglement of the complex spontaneous brain activity. In this context, the brain’s response can be defined as (1) the additional neural activity components generated after the input or (2) the changes in the ongoing spontaneous activities induced by the input. Moreover, the response can be manifested in multiple features. Three commonly studied examples of features are (1) transient temporal waveform, (2) time–frequency representation, and (3) phase dynamics. The most extensively used method of average event-related potentials (ERPs) captures the first one, while the latter two and other more complex features are attracting increasing attention. However, there has not been much work providing a systematic illustration and guidance for how to effectively exploit multifaceted features in neural cognitive research. Based on a visual oddball ERPs dataset with 200 participants, this work demonstrates how the information from the above-mentioned features are complementary to each other and how they can be integrated based on stereotypical neural-network-based machine learning approaches to better exploit neural dynamic information in basic and applied cognitive research. Full article

Accumulating efforts have been made to investigate cognitive impairment in stroke patients, but little has been focused on mild stroke. Research on the impact of mild stroke and different lesion locations on cognitive impairment is still limited. To investigate the underlying mechanisms of cognitive dysfunction in mild stroke at different lesion locations, electroencephalograms (EEGs) were recorded in three groups (40 patients with cortical stroke (CS), 40 patients with subcortical stroke (SS), and 40 healthy controls (HC)) during a visual oddball task. Power envelope connectivity (PEC) was constructed based on EEG source signals, followed by graph theory analysis to quantitatively assess functional brain network properties. A classification framework was further applied to explore the feasibility of PEC in the identification of mild stroke. The results showed worse behavioral performance in the patient groups, and PECs with significant differences among three groups showed complex distribution patterns in frequency bands and the cortex. In the delta band, the global efficiency was significantly higher in HC than in CS (p = 0.011), while local efficiency was significantly increased in SS than in CS (p = 0.038). In the beta band, the small-worldness was significantly increased in HC compared to CS (p = 0.004). Moreover, the satisfactory classification results (76.25% in HC vs. CS, and 80.00% in HC vs. SS) validate the potential of PECs as a biomarker in the detection of mild stroke. Our findings offer some new quantitative insights into the complex mechanisms of cognitive impairment in mild stroke at different lesion locations, which may facilitate post-stroke cognitive rehabilitation. Full article

Acute aerobic exercise exerts a small beneficial effect on cognition. Previous research primarily examines cognitive changes following a bout of exercise, while little is currently known about changes in cognitive performance during exercise. The primary purpose of this study was to examine the effects of low-intensity cycling on cognitive function indexed by behavioral (response accuracy; reaction time) and neurocognitive (P3 mean amplitude; P3 centroid latency) responses. Twenty-seven (M_age = 22.9 ± 3.0 years old) individuals were counterbalanced into low-intensity exercise (EX) and seated control (SC) conditions spread across two testing sessions. During each condition, participants completed a 10 min resting baseline period, 20 min of either sustained cycling or seated rest, and a 20 min recovery period. Primary outcomes were assessed at 10 min intervals (five blocks total) throughout each condition via a modified visual oddball task while electroencephalography (EEG) responses were measured. Across time blocks, both conditions exhibited faster reaction times on frequent trials but reduced accuracy to rare trials, suggesting a speed–accuracy tradeoff. There were no differences between conditions in P3 centroid latency, whereas a significant reduction in P3 amplitude was observed during the 20 min exercise period compared to the control condition. Taken together, results suggest that exercise at lower doses may have minimal influence on behavioral outcomes of cognitive performance but may impact more basic measures of brain function. Information gathered from this study may aid in the development of appropriate exercise prescriptions for populations looking to specifically target cognitive function deficits. Full article