Task Paradigm Research Articles

Rest-fMRI—A Potential Substitute for Task-fMRI?

Abstract Objective The aim of this study was to assess the reliability of resting-state functional magnetic resonance imaging (rest-fMRI) in mapping language areas for preoperative planning, versus standard task-based techniques, which are at times difficult to perform in clinical settings. Our study also aimed to evaluate the overlap between language areas identified through rest-fMRI and the standard task-fMRI, in neurosurgical cases. Materials and Methods Using a seed-based analysis of rest-fMRI with multiple template seeds, we identified functionally connected language regions in patients undergoing preoperative language mapping. Four language task paradigms (word, verb, picture, and semantics) were evaluated. We quantified the degree of overlap between language areas identified on rest-fMRI and task-fMRI, categorizing the results as more than 50% or less than 50% overlap. Results Seventy-seven percent of patients demonstrated an overlap exceeding 50% between rest- and task-fMRI maps, with the left Broca's area being the most frequently observed region of overlap. This finding was noted even in cases with lesions in Broca's or Wernicke's areas, highlighting the method's robustness. The verb task showed the best blood-oxygen-level dependent activity and overlap with rest-fMRI, highlighting its reliability. To identify a specific language area, the contralateral seed of the same area most commonly displayed connectivity with the area of interest. Conclusion Our findings demonstrate the potential of using rest-fMRI in accurately mapping eloquent language areas, in clinical settings The strong concordance observed, especially in the left Broca's area, underscores the reliability of this method. Further research and larger studies are essential to validate these results, potentially establishing the use of routine rest-fMRI, in clinical preoperative workup.

Attention capture by own name decreases with speech compression

Auditory stimuli that are relevant to a listener have the potential to capture focal attention even when unattended, the listener’s own name being a particularly effective stimulus. We report two experiments to test the attention-capturing potential of the listener’s own name in normal speech and time-compressed speech. In Experiment 1, 39 participants were tested with a visual word categorization task with uncompressed spoken names as background auditory distractors. Participants’ word categorization performance was slower when hearing their own name rather than other names, and in a final test, they were faster at detecting their own name than other names. Experiment 2 used the same task paradigm, but the auditory distractors were time-compressed names. Three compression levels were tested with 25 participants in each condition. Participants’ word categorization performance was again slower when hearing their own name than when hearing other names; the slowing was strongest with slight compression and weakest with intense compression. Personally relevant time-compressed speech has the potential to capture attention, but the degree of capture depends on the level of compression. Attention capture by time-compressed speech has practical significance and provides partial evidence for the duplex-mechanism account of auditory distraction.

RETRACTED: Left hemisphere lateralization of the limbic system and frontoparietal network (FPN) correlates with positive and negative symptom improvement following cannabidiol (CBD) administration in psychosis and ultra-high risk (UHR) populations: A voxel-wise meta-analysis

This voxel-wise meta-analysis assesses current findings about the neural correlates of cannabidiol on the positive and negative symptoms among individuals with psychosis or ultra-high risk (UHR) for psychosis. We used PubMed, EMBASE, and ScienceDirect as primary databases and initially retrieved 157 studies. After applying our eligibility criteria, 13 studies remained for inclusion. Ten studies focused on psychosis. Three studies focused on UHR. Quality assessment was performed for included articles using the RoB2 instrument. Statistical analysis implicated a voxel-wise meta-analysis of different task paradigms (emotion recognition, verbal memory recall, and inhibitory control) with a jackknife sensitivity measure, Egger's test of random effects, and a meta-regression with relevant covariates. Article quality was determined to be primarily low risk of bias, with some elements of unclear bias figuring across studies. Our results showed robust, convergent correlations between CBD administration and left hemisphere lateralization of limbic system and frontoparietal network (FPN) subregions across task paradigms in psychosis and UHR populations. Our meta-regression revealed that decreased limbic system activity correlated with positive symptom improvements, and decreased FPN activity correlated with negative symptom improvements. Lastly, sensitivity analyses determined that there was minimal risk bias or risk of confounding variables unduly influencing our meta-analyses (p > 0.05).

Role of the prefrontal cortex in musical and verbal short-term memory: A functional near-infrared spectroscopy study

Abstract Auditory short-term memory (STM) is a key process in auditory cognition, with evidence for partly distinct networks subtending musical and verbal STM. The delayed matching-to-sample task (DMST) paradigm has been found suitable for comparing musical and verbal STM and for manipulating memory load. In this study, musical and verbal DMSTs were investigated with measures of activity in frontal areas with functional near-infrared spectroscopy (fNIRS): Experiment 1 compared musical and verbal DMSTs with a low-level perception task (that does not entail encoding, retention, or retrieval of information), to identify frontal regions involved in memory processes. Experiment 2 manipulated memory load for musical and verbal materials to uncover frontal brain regions showing parametric changes in activity with load and their potential differences between musical and verbal materials. A FIR model was used to deconvolute fNIRS signals across successive trials without making assumptions with respect to the shape of the hemodynamic response in a DMST. Results revealed the involvement of the dorsolateral prefrontal cortex (dlPFC) and inferior frontal gyri (IFG), but not of the superior frontal gyri (SFG) in both experiments, in keeping with previously reported neuroimaging data (including fMRI). Experiment 2 demonstrated a parametric variation of activity with memory load in bilateral IFGs during the maintenance period, with opposite directions for musical and verbal materials. Activity in the IFGs increased with memory load for verbal sound sequences, in keeping with previous results with n-back tasks. The decreased activity with memory load observed with musical sequences is discussed in relation to previous research on auditory STM rehearsal strategies. This study highlights fNIRS as a promising tool for investigating musical and verbal STM not only for typical populations, but also for populations with developmental language disorders associated with functional alterations in auditory STM.

Differential neural correlates underlying visuospatial versus semantic reasoning in autistic children.

While fronto-posterior underconnectivity has often been reported in autism, it was shown that different contexts may modulate between-group differences in functional connectivity. Here, we assessed how different task paradigms modulate functional connectivity differences in a young autistic sample relative to typically developing children. Twenty-three autistic and 23 typically developing children aged 6 to 15years underwent functional magnetic resonance imaging (fMRI) scanning while completing a reasoning task with visuospatial versus semantic content. We observed distinct connectivity patterns in autistic versus typical children as a function of task type (visuospatial vs. semantic) and problem complexity (visual matching vs. reasoning), despite similar performance. For semantic reasoning problems, there was no significant between-group differences in connectivity. However, during visuospatial reasoning problems, we observed occipital-occipital, occipital-temporal, and occipital-frontal over-connectivity in autistic children relative to typical children. Also, increasing the complexity of visuospatial problems resulted in increased functional connectivity between occipital, posterior (temporal), and anterior (frontal) brain regions in autistic participants, more so than in typical children. Our results add to several studies now demonstrating that the connectivity alterations in autistic relative to neurotypical individuals are much more complex than previously thought and depend on both task type and task complexity and their respective underlying cognitive processes.

Abnormalities in motor adaptation to different types of perturbations in schizophreniaperturbations in schizophrenia

Schizophrenia is a mental health disorder that often includes psychomotor disturbances, impacting how individuals adjust their motor output based on the cause of motor errors. While previous motor adaptation studies on individuals with schizophrenia have largely focused on large and consistent perturbations induced by abrupt experimental manipulations, such as donning prism goggles, the adaptation process to random perturbations, either caused by intrinsic motor noise or external disturbances, has not been examined – despite its ecological relevance. Here, we used a unified behavioral task paradigm to examine motor adaptation to perturbations of three causal structures among individuals in the remission stage of schizophrenia, youth with ultra-high risk of psychosis, adults with active symptoms, and age-matched controls. Results showed that individuals with schizophrenia had reduced trial-by-trial adaptation and large error variance when adapting to their own motor noise. When adapting to random but salient perturbations, they showed intact adaptation and normal causal inference of errors. This contrasted with reduced adaptation to large yet consistent perturbations, which could reflect difficulties in forming cognitive strategies rather than the often-assumed impairments in procedural learning or sense of agency. Furthermore, the observed adaptation effects were correlated with the severity of positive symptoms across the diagnosis groups. Our findings suggest that individuals with schizophrenia face challenges in accommodating intrinsic perturbations when motor errors are ambiguous but adapt with intact causal attribution when errors are salient.

Effect of spectral degradation on speech intelligibility and cortical representation.

Noise-vocoded speech has long been used to investigate how acoustic cues affect speech understanding. Studies indicate that reducing the number of spectral channel bands diminishes speech intelligibility. Despite previous studies examining the channel band effect using earlier event-related potential (ERP) components, such as P1, N1, and P2, a clear consensus or understanding remains elusive. Given our hypothesis that spectral degradation affects higher-order processing of speech understanding beyond mere perception, we aimed to objectively measure differences in higher-order abilities to discriminate or interpret meaning. Using an oddball paradigm with speech stimuli, we examined how neural signals correlate with the evaluation of speech stimuli based on the number of channel bands measuring N2 and P3b components. In 20 young participants with normal hearing, we measured speech intelligibility and N2 and P3b responses using a one-syllable task paradigm with animal and non-animal stimuli across four vocoder conditions with 4, 8, 16, or 32 channel bands. Behavioral data from word repetition clearly affected the number of channel bands, and all pairs were significantly different (p < 0.001). We also observed significant effects of the number of channels on the peak amplitude [F(2.006, 38.117) = 9.077, p < 0.001] and peak latency [F(3, 57) = 26.642, p < 0.001] of the N2 component. Similarly, the P3b component showed significant main effects of the number of channel bands on the peak amplitude [F(2.231, 42.391) = 13.045, p < 0.001] and peak latency [F(3, 57) = 2.968, p = 0.039]. In summary, our findings provide compelling evidence that spectral channel bands profoundly influence cortical speech processing, as reflected in the N2 and P3b components, a higher-order cognitive process. We conclude that spectrally degraded one-syllable speech primarily affects cortical responses during semantic integration.

READ-PVLA: Recurrent Adapter with Partial Video-Language Alignment for Parameter-Efficient Transfer Learning in Low-Resource Video-Language Modeling

Fully fine-tuning pretrained large-scale transformer models has become a popular paradigm for video-language modeling tasks, such as temporal language grounding and video-language summarization. With a growing number of tasks and limited training data, such full fine-tuning approach leads to costly model storage and unstable training. To overcome these shortcomings, we introduce lightweight adapters to the pre-trained model and only update them at fine-tuning time. However, existing adapters fail to capture intrinsic temporal relations among video frames or textual words. Moreover, they neglect the preservation of critical task-related information that flows from the raw video-language input into the adapter’s low-dimensional space. To address these issues, we first propose a novel REcurrent ADapter (READ) that employs recurrent computation to enable temporal modeling capability. Second, we propose Partial Video-Language Alignment (PVLA) objective via the use of partial optimal transport to maintain task-related information flowing into our READ modules. We validate our READ-PVLA framework through extensive experiments where READ-PVLA significantly outperforms all existing fine-tuning strategies on multiple low-resource temporal language grounding and video-language summarization benchmarks.

Learning from History: Task-agnostic Model Contrastive Learning for Image Restoration

Contrastive learning has emerged as a prevailing paradigm for high-level vision tasks, which, by introducing properly negative samples, has also been exploited for low-level vision tasks to achieve a compact optimization space to account for their ill-posed nature. However, existing methods rely on manually predefined and task-oriented negatives, which often exhibit pronounced task-specific biases. To address this challenge, our paper introduces an innovative method termed 'learning from history', which dynamically generates negative samples from the target model itself. Our approach, named Model Contrastive Learning for Image Restoration (MCLIR), rejuvenates latency models as negative models, making it compatible with diverse image restoration tasks. We propose the Self-Prior guided Negative loss (SPN) to enable it. This approach significantly enhances existing models when retrained with the proposed model contrastive paradigm. The results show significant improvements in image restoration across various tasks and architectures. For example, models retrained with SPN outperform the original FFANet and DehazeFormer by 3.41 and 0.57 dB on the RESIDE indoor dataset for image dehazing. Similarly, they achieve notable improvements of 0.47 dB on SPA-Data over IDT for image deraining and 0.12 dB on Manga109 for a 4x scale super-resolution over lightweight SwinIR, respectively. Code and retrained models are available at https://github.com/Aitical/MCLIR.

GSO-Net: Grid Surface Optimization via Learning Geometric Constraints

In the context of surface representations, we find a natural structural similarity between grid surface and image data. Motivated by this inspiration, we propose a novel approach: encoding grid surfaces as geometric images and using image processing methods to address surface optimization-related problems. As a result, we have created the first dataset for grid surface optimization and devised a learning-based grid surface optimization network specifically tailored to geometric images, addressing the surface optimization problem through a data-driven learning of geometric constraints paradigm. We conduct extensive experiments on developable surface optimization, surface flattening, and surface denoising tasks using the designed network and datasets. The results demonstrate that our proposed method not only addresses the surface optimization problem better than traditional numerical optimization methods, especially for complex surfaces, but also boosts the optimization speed by multiple orders of magnitude. This pioneering study successfully applies deep learning methods to the field of surface optimization and provides a new solution paradigm for similar tasks, which will provide inspiration and guidance for future developments in the field of discrete surface optimization. The code and dataset are available at https://github.com/chaoyunwang/GSO-Net.

Leveraging distant supervision and deep learning for twitter sentiment and emotion classification

Nowadays, various applications across industries, healthcare, and security have begun adopting automatic sentiment analysis and emotion detection in short texts, such as posts from social media. Twitter stands out as one of the most popular online social media platforms due to its easy, unique, and advanced accessibility using the API. On the other hand, supervised learning is the most widely used paradigm for tasks involving sentiment polarity and fine-grained emotion detection in short and informal texts, such as Twitter posts. However, supervised learning models are data-hungry and heavily reliant on abundant labeled data, which remains a challenge. This study aims to address this challenge by creating a large-scale real-world dataset of 17.5 million tweets. A distant supervision approach relying on emojis available in tweets is applied to label tweets corresponding to Ekman’s six basic emotions. Additionally, we conducted a series of experiments using various conventional machine learning models and deep learning, including transformer-based models, on our dataset to establish baseline results. The experimental results and an extensive ablation analysis on the dataset showed that BiLSTM with FastText and an attention mechanism outperforms other models in both classification tasks, achieving an F1-score of 70.92% for sentiment classification and 54.85% for emotion detection.

Developmental Changes in Executive Control: Investigating Dual-Task Interference During Motor and Central Cognitive Processing with the Overlapping Task Paradigm

ABSTRACT Previous studies demonstrated that dual-task impairments are higher in children than in young adults. A previous study systematically assessed the sources of these larger dual-task impairments by identifying age-related differences in capacity limitations during dual-task processing. Capacity limitations in central cognitive processes were present in both age groups, while perceptual capacity limitations were larger in children than in young adults. However, the literature lacks further confirmations and explanations for increased dual-task impairments in children. Moreover, this previous study was not informative regarding age-related differences in potential capacity limitations during central cognitive processing in relation to limitations during motor processing. Therefore, in a German context, the present study investigated children (N = 32) and young adults (N = 32) by combining visual (Task 1) and auditory (Task 2) sensorimotor tasks, separated by a varying stimulus onset asynchrony, in dual tasks of the psychological refractory period (PRP) type. Performance differences were assessed by manipulations of task difficulty in Task 1. The results replicated the finding of increased dual-task impairments in children compared with young adults. Furthermore, the manipulations in the PRP dual task resulted in similar effects in both age groups. Thus, these findings confirmed the presence of capacity limitations during central cognitive processing, while there were no processing limitations in motor processing between children and young adults.

The influence of pain and kinesiophobia on motor control of the upper limb: how pointing task paradigms can point to new avenues of understanding.

People experiencing kinesiophobia are more likely to develop persistent disabilities and chronic pain. However, the impact of kinesiophobia on the motor system remains poorly understood. We investigated whether kinesiophobia could modulate shoulder pain-induced changes in (1) kinematic parameters and muscle activation during functional movement and (2) corticospinal excitability. Thirty healthy, pain-free subjects took part in the study. Shoulder, elbow, and finger kinematics, as well as electromyographic activity of the upper trapezius and anterior deltoid muscles, were recorded while subjects performed a pointing task before and during pain induced by capsaicin at the shoulder. Anterior deltoid cortical changes in excitability were assessed through the slope of transcranial magnetic stimulation input-output curves obtained before and during pain. Results revealed that pain reduced shoulder electromyographic activity and had a variable effect on finger kinematics, with individuals with higher kinesiophobia showing greater reduction in finger target traveled distance. Kinesiophobia scores were also correlated with the changes in deltoid corticospinal excitability, suggesting that the latter can influence motor activity as soon as the motor signal emerges. Taken together, these results suggest that pain and kinesiophobia interact with motor control adaptation.

Cognitive-Motor Dual-Task Performance of the Landing Error Scoring System.

The Landing Error Scoring System (LESS) is a common assessment used to determine biomechanical landing errors. However, this assessment is completed as a single motor task, which does not require additional attentional resources. It is unclear if the LESS can be used to detect cognitive-motor interference (i.e., dual-task cost) in biomechanical errors associated with lower extremity injury. To determine if the LESS is a suitable clinical assessment of dual-task performance in uninjured females and to evaluate whether specific landing criteria are more affected by an additional cognitive load than others. Observational Cross-Sectional Design. Setting: University research laboratory. Twenty uninjured, physically active females participated. Intervention(s): Participants performed the LESS under three different conditions: baseline landing with no cognitive distraction (Single), a visual-based dual-task (Visual), and a number-based dual-task (Number). Mean sagittal, frontal, and total LESS scores were compared between conditions using a one-way repeated measures analysis of variance with Tukey post hoc corrections. Cohen's d effect sizes with 95% confidence intervals were used to determine the magnitude of differences. The frequency of errors for each individual LESS item under the three conditions were compared using Chi-Squared analyses. Participants exhibited greater sagittal plane (P=.013, d=0.91 [0.26, 1.56]) and total (P=.008, d=1.03 [0.37, 1.69]) errors during the Visual condition compared to the Single condition. Frontal plane errors were significantly greater during the Number condition compared to the Single condition (P=.008, d=1.03 [0.37, 1.69]). The frequency of errors observed for each LESS item did not statistically differ between conditions (all P>.05). The LESS was able to detect a dual-task cost in landing errors during both the Visual and Number conditions. We recommend developing clinically-oriented solutions to incorporate similar dual- task paradigms in traditional injury risk reduction programs.

Diverging neural dynamics for syntactic structure building in naturalistic speaking and listening

The neural correlates of sentence production are typically studied using task paradigms that differ considerably from the experience of speaking outside of an experimental setting. In this fMRI study, we aimed to gain a better understanding of syntactic processing in spontaneous production versus naturalistic comprehension in three regions of interest (BA44, BA45, and left posterior middle temporal gyrus). A group of participants (n = 16) was asked to speak about the events of an episode of a TV series in the scanner. Another group of participants (n = 36) listened to the spoken recall of a participant from the first group. To model syntactic processing, we extracted word-by-word metrics of phrase-structure building with a top-down and a bottom-up parser that make different hypotheses about the timing of structure building. While the top-down parser anticipates syntactic structure, sometimes before it is obvious to the listener, the bottom-up parser builds syntactic structure in an integratory way after all of the evidence has been presented. In comprehension, neural activity was found to be better modeled by the bottom-up parser, while in production, it was better modeled by the top-down parser. We additionally modeled structure building in production with two strategies that were developed here to make different predictions about the incrementality of structure building during speaking. We found evidence for highly incremental and anticipatory structure building in production, which was confirmed by a converging analysis of the pausing patterns in speech. Overall, this study shows the feasibility of studying the neural dynamics of spontaneous language production.

Toward Robust Self-Training Paradigm for Molecular Prediction Tasks.

Molecular prediction tasks normally demand a series of professional experiments to label the target molecule, which suffers from the limited labeled data problem. One of the semisupervised learning paradigms, known as self-training, utilizes both labeled and unlabeled data. Specifically, a teacher model is trained using labeled data and produces pseudo labels for unlabeled data. These labeled and pseudo-labeled data are then jointly used to train a student model. However, the pseudo labels generated from the teacher model are generally not sufficiently accurate. Thus, we propose a robust self-training strategy by exploring robust loss function to handle such noisy labels in two paradigms, that is, generic and adaptive. We have conducted experiments on three molecular biology prediction tasks with four backbone models to gradually evaluate the performance of the proposed robust self-training strategy. The results demonstrate that the proposed method enhances prediction performance across all tasks, notably within molecular regression tasks, where there has been an average enhancement of 41.5%. Furthermore, the visualization analysis confirms the superiority of our method. Our proposed robust self-training is a simple yet effective strategy that efficiently improves molecular biology prediction performance. It tackles the labeled data insufficient issue in molecular biology by taking advantage of both labeled and unlabeled data. Moreover, it can be easily embedded with any prediction task, which serves as a universal approach for the bioinformatics community.

Fundamental dimensions of real-time spoken word recognition in cochlear implant users

Spoken word recognition is a sophisticated cognitive process that maps incoming speech to meaning. For young, normal-hearing adults, word recognition is served by a competition process which plays out incrementally as speech unfolds. Candidates that match the input are activated and compete as mismatching candidates are suppressed. It remains unclear how this process changes in other listeners. Previous results from small-scale studies suggest three dimensions: 1) the speed of activating words (Activation Rate), affected by development and aging; 2) the degree of ultimate competitor suppression (Sustained Activation), affected by hearing loss; and 3) the delay of competition entirely (Wait-and-See), affected by severe hearing loss. To investigate these dimensions, a large, heterogenous group of cochlear implant users (N = 101) completed a Visual World Paradigm task. A principal component analysis supported these three dimensions. Each dimension was predicted by different demographic or auditory factors (onset of deafness, auditory fidelity, age), and each predicted outcomes over and above auditory fidelity. This suggests that these are orthogonal dimensions along which listeners vary, not all-or-nothing strategies. This work identifies the degrees of freedom that can extend theories of word recognition to account for a range of experiences and contexts.

Self-reported strategy use in working memory tasks

Mnemonic strategies can facilitate working memory performance, but our knowledge on strategy use as a function of task characteristics remains limited. We examined self-reported strategy use in several working memory tasks with pretest data from two large-scale online training experiments. A three-level measure of strategy sophistication (no strategy, maintenance, manipulation) was coded based on participants’ open-ended strategy reports. A considerable portion of participants reported some memory strategy, and strategy sophistication was associated with objective task performance. We found a consistent effect of stimulus type: verbal stimuli (letters or digits) elicited higher strategy sophistication than nonverbal ones (colours or spatial positions). In contrast, the association between task paradigm and strategy sophistication was less consistent in the two experiments. The present results highlight the importance of self-generated strategies in understanding individual differences in working memory performance and the role of stimulus characteristics as one of the task-related determinants of strategy use.

Procedural Memory Deficits in Preschool Children with Developmental Language Disorder in a Spanish-Speaking Population.

This study aimed to compare procedural learning skills between Spanish-speaking preschool children (ages 4 years to 4 years, 11 months) with developmental language disorder (DLD) and their chronologically matched typically developing (TD) peers. Using the serial reaction time (SRT) task, participants (30 children with DLD and 30 TD children) responded to visual stimuli in a sequenced manner over four blocks, followed by a random order block. The task assessed reaction time (RT) and accuracy. The results showed a significant interaction between group and block for RT and accuracy, with children with DLD exhibiting longer RTs and accuracy deficits across blocks. In contrast, the TD group showed higher RT efficiency and accuracy in the sequential blocks and, as expected, decreased performance in the random block according to the experimental manipulation. Overall, the results of this investigation suggest that there was no implicit learning in the DLD group, as indicated by the SRT task paradigms of procedural memory. These findings align with some aspects of the procedural deficit hypothesis (PDH), which suggests that linguistic deficits in the DLD population may derive from a deficit in sequential learning from the procedural memory system domain in the Spanish context.

Процессы когнитивного контроля в тесте Струпа и их отражение в связанных с событиями потенциалах (обзор)

The review summarizes the data of Russian and foreign studies on the psychophysiological parameters of the Stroop task execution. In addition, the article considers the main modifications of the task and similar paradigms as well as the key hypotheses explaining the causes of the interference effect and the increase in reaction time to stimuli containing conflicting information. Further, the paper presents data on eventrelated potential (ERP) waves, which are supposed to reflect cognitive control processes, such as conflict detection, overcoming of interference and conflict resolution. The frontocentral N2 wave characterizes the processes of conflict detection and overcoming of interference, and its main neural generator is the anterior cingulate cortex. The N450 wave is primarily generated in the anterior cingulate cortex and prefrontal cortex and is thought to reflect interference suppression. The centroparietal P300 wave and the late positive complex, which appears to be generated in the middle or inferior frontal gyrus and in the extrastriate cortex, are associated with the conflict resolution process. The readiness potential is, supposedly, generated in the motor cortex and reflects the process of selecting and preparing a motor response. Moreover, the review presents the main directions of studies that use the Stroop test paradigm and its modifications. Despite a significant number of existing psychophysical and neurophysiological papers, the question of the brain mechanisms of cognitive control in tasks that cause cognitive conflict remains open, and the neuropsychological role of the ERP waves recorded in such tasks is still not fully explored. Studies into the influence of different types of competing information and the degree of conflict on the psychophysiological indicators in the Stroop task are of considerable interest.