Classes Of Stimuli Research Articles

Single-Cell RNA Sequencing Reveals That Adaptation of Human Aortic Endothelial Cells to Antiproliferative Therapies Is Modulated by Flow-Induced Shear Stress.

Endothelial cells (ECs) are capable of quickly responding in a coordinated manner to a wide array of stresses to maintain vascular homeostasis. Loss of EC cellular adaptation may be a potential marker for cardiovascular disease and a predictor of poor response to endovascular pharmacological interventions such as drug-eluting stents. Here, we report single-cell transcriptional profiling of ECs exposed to multiple stimulus classes to evaluate EC adaptation. Human aortic ECs were costimulated with both pathophysiological flows mimicking shear stress levels found in the human aorta (laminar and turbulent, ranging from 2.5 to 30 dynes/cm2) and clinically relevant antiproliferative drugs, namely paclitaxel and rapamycin. EC state in response to these stimuli was defined using single-cell RNA sequencing. We identified differentially expressed genes and inferred the TF (transcription factor) landscape modulated by flow shear stress using single-cell RNA sequencing. These flow-sensitive markers differentiated previously identified spatially distinct subpopulations of ECs in the murine aorta. Moreover, distinct transcriptional modules defined flow- and drug-responsive EC adaptation singly and in combination. Flow shear stress was the dominant driver of EC state, altering their response to pharmacological therapies. We showed that flow shear stress modulates the cellular capacity of ECs to respond to paclitaxel and rapamycin administration, suggesting that while responding to different flow patterns, ECs experience an impairment in their transcriptional adaptation to other stimuli.

Conspiracy beliefs are associated with a reduction in frontal beta power and biases in categorizing ambiguous stimuli

Prior beliefs, such as conspiracy beliefs, significantly influence our perception of the natural world. However, the brain activity associated with perceptual decision-making in conspiracy beliefs is not well understood. To shed light on this topic, we conducted a study examining the EEG activity of believers, and skeptics during resting state with perceptual decision-making task. Our study shows that conspiracy beliefs are related to the reduced power of beta frequency band. Furthermore, skeptics tended to misclassify ambiguous face stimuli as houses more frequently than believers. These results help to explain the differences in brain activity between believers and skeptics, especially in how conspiracy beliefs impact the categorization of ambiguous stimuli.

Machine learning and EEG can classify passive viewing of discrete categories of visual stimuli but not the observation of pain

Previous studies have demonstrated the potential of machine learning (ML) in classifying physical pain from non-pain states using electroencephalographic (EEG) data. However, the application of ML to EEG data to categorise the observation of pain versus non-pain images of human facial expressions or scenes depicting pain being inflicted has not been explored. The present study aimed to address this by training Random Forest (RF) models on cortical event-related potentials (ERPs) recorded while participants passively viewed faces displaying either pain or neutral expressions, as well as action scenes depicting pain or matched non-pain (neutral) scenarios. Ninety-one participants were recruited across three samples, which included a model development group (n = 40) and a cross-subject validation group (n = 51). Additionally, 25 participants from the model development group completed a second experimental session, providing a within-subject temporal validation sample. The analysis of ERPs revealed an enhanced N170 component in response to faces compared to action scenes. Moreover, an increased late positive potential (LPP) was observed during the viewing of pain scenes compared to neutral scenes. Additionally, an enhanced P3 response was found when participants viewed faces displaying pain expressions compared to neutral expressions. Subsequently, three RF models were developed to classify images into faces and scenes, neutral and pain scenes, and neutral and pain expressions. The RF model achieved classification accuracies of 75%, 64%, and 69% for cross-validation, cross-subject, and within-subject classifications, respectively, along with reasonably calibrated predictions for the classification of face versus scene images. However, the RF model was unable to classify pain versus neutral stimuli above chance levels when presented with subsequent tasks involving images from either category. These results expand upon previous findings by externally validating the use of ML in classifying ERPs related to different categories of visual images, namely faces and scenes. The results also indicate the limitations of ML in distinguishing pain and non-pain connotations using ERP responses to the passive viewing of visually similar images.

A Convolutional Neural Network for Classification of Stimuli Based on Stretchable Mechanical Sensor

A Convolutional Neural Network for Classification of Stimuli Based on Stretchable Mechanical Sensor

Accentuate the positive: Evidence that context dependent self-reference drives self-bias

There is abundant evidence of a self-bias in cognition, with prioritised processing of information that is self-relevant. There is also abundant evidence of a positivity-bias in cognition, with prioritised processing of information that is positively valenced (e.g., positive emotional expressions, rewards). While the effects of self-bias and positivity-bias have been well documented in isolation, they have seldom been examined in parallel, so it is unclear whether one or other of these stimulus classes is prioritised or whether they interact. Addressing this gap, the current research aimed to establish the relative primacy of self-bias and positivity-bias using a classification task that paired self-relevant information with emotional expressions (i.e., Expt. 1) or reward information (i.e., Expt. 2). When the self was paired with relatively more positive information (i.e., smiling faces or high reward) we found evidence of a self-bias but no evidence of a positivity-bias. Whereas when the self was paired with relatively less positive information (i.e., neutral faces or low reward) we found evidence of a positivity-bias but no evidence of a self-bias. These results suggest the relative primacy of prioritised processing is flexible, context dependent and might be caused by a drive towards self-enhancement and the self-positivity bias.

Composite receptive fields in the mouse auditory cortex.

A central question in sensory neuroscience is how neurons represent complex natural stimuli. This process involves multiple steps of feature extraction to obtain a condensed, categorical representation useful for classification and behaviour. It has previously been shown that central auditory neurons in the starling have composite receptive fields composed of multiple features. Whether this property is an idiosyncratic characteristic of songbirds, a group of highly specialized vocal learners or a generic property of sensory processing is unknown. To address this question, we have recorded responses from auditory cortical neurons in mice, and characterized their receptive fields using mouse ultrasonic vocalizations (USVs) as a natural and ethologically relevant stimulus and pitch-shifted starling songs as a natural but ethologically irrelevant control stimulus. We have found that these neurons display composite receptive fields with multiple excitatory and inhibitory subunits. Moreover, this was the case with either the conspecific or the heterospecific vocalizations. We then trained the sparse filtering algorithm on both classes of natural stimuli to obtain statistically optimal features, and compared the natural and artificial features using UMAP, a dimensionality-reduction algorithm previously used to analyse mouse USVs and birdsongs. We have found that the receptive-field features obtained with both types of the natural stimuli clustered together, as did the sparse-filtering features. However, the natural and artificial receptive-field features clustered mostly separately. Based on these results, our general conclusion is that composite receptive fields are not a unique characteristic of specialized vocal learners but are likely a generic property of central auditorysystems. KEY POINTS: Auditory cortical neurons in the mouse have composite receptive fields with several excitatory and inhibitory features. Receptive-field features capture temporal and spectral modulations of natural stimuli. Ethological relevance of the stimulus affects the estimation of receptive-field dimensionality.

Sustained selective attention to chromatic information enhances visuocortical gain at the population level.

Prior work in selective attention research has shown that colour-selective attention enhances neural activity in visuocortical areas sensitive to the attended colour while suppressing activity in areas sensitive to ignored colours. However, it is currently unclear whether this effect is limited to attending to specific colour hues or extends to chromatic information more broadly. To investigate this question, we used steady-state visual evoked potentials (ssVEPs) frequency tagging to quantify participants' visuocortical responses to specific elements embedded in arrays of flickering, randomly moving mid-complex patterns. Participants were instructed to attend to either coloured or greyscale patterns while ignoring the others. We found that attending to either coloured or greyscale patterns produced robust increases in ssVEP amplitudes both compared to ignored stimuli and to baseline. There was however no evidence of suppressed responses to ignored patterns. These findings demonstrate that attentional selection based on the presence or absence of chromatic information prompts selectively enhanced visuocortical processing but this selective amplification is not accompanied by suppression of unattended stimuli. Findings are consistent with theoretical notions that predict strong competition between specific exemplars within a given feature dimension, such as red or green, but weak competition between broadly defined stimulus categories, such as chromatic versus non-chromatic.

Complex visual discrimination is impaired after right, but not left, anterior temporal lobectomy.

The prevailing view in human cognitive neuroscience associates the medial temporal lobes (MTLs) with declarative memory. Compelling experimental evidence has, however, demonstrated that these regions are specialized according to the representations processed, irrespective of the cognitive domain assessed. This account was supported by the study of patients with bilateral medial temporal amnesia, who exhibit impairments in perceptual tasks involving complex visual stimuli. Yet, little is known regarding the impact of unilateral MTL damage on complex visual abilities. To address this issue, we administered a visual matching task to 20 patients who underwent left (N = 12) or right (N = 8) anterior temporal lobectomy for drug-resistant epilepsy and to 38 healthy controls. Presentation viewpoint was manipulated to increase feature ambiguity, as this is critical to reveal impairments in perceptual tasks. Similar to control participants, patients with left-sided damage succeeded in all task conditions. In contrast, patients with right-sided damage had decreased accuracy compared with that of the other two groups, as well as increased response time. Notably, the accuracy of those with right-sided damage did not exceed chance level when feature ambiguity was high (i.e., when stimuli were presented from different viewpoints) for the most complex classes of stimuli (i.e., scenes and buildings, compared with single objects). The pattern reported in bilateral patients in previous studies was therefore reproduced in patients with right, but not left, resection. These results suggest that the complex visual-representation functions supported by the MTL are right-lateralized, and raise the question as to how the representational account of these regions applies to representations supported by left MTL regions.

Single- vs. combined-category preference assessments for edible, leisure, and social-interaction stimuli.

A concern when conducting combined-category preference assessments is the potential for displacement effects, a shift in the preference ranking from highly preferred to moderately or less preferred for stimuli in two of three stimulus categories (e.g., edible, leisure, or social-interaction). In this study, we evaluated potential displacement effects in combined-category arrays of edible, leisure, and social-interaction stimuli for five individuals with autism. First, single-category paired-stimulus preference assessments were implemented to identify two highly preferred stimuli from each category. When these stimuli were included in a combined-category preference assessment, displacement effects were observed for three of five participants. During a subsequent reinforcer assessment, stimuli identified as less preferred in the combined-category preference assessment functioned as reinforcers for two participants. Additionally, although social interaction was not identified as highly preferred for three of the five participants, it functioned as a reinforcer for four participants.

ISO-FLUCS: symmetrization of optofluidic manipulations in quasi-isothermal micro-environments

Recently, it has been demonstrated that thermoviscous flows can be used for a range of fine micromanipulations, such as moving the cytoplasm of cells and developing embryos, intracellular rheology, and femtonewton-range force measurements. These flows, also known as focused-light-induced cytoplasmic streaming (FLUCS), are induced by mid-infrared laser scanning of a temperature spot through the sample. However, localized laser scanning can inflict temperature perturbations of several Kelvins on the sample, potentially eliciting unspecific biological responses. In this study, we demonstrate how exploiting symmetry relations during laser scanning effectively disentangles laser heating and flow induction. We introduce flow-neutral scan sequences that use dynamic photothermal stimuli and spatiotemporal symmetry relations of scanning bridging up to three distinct time scales. We leverage further insights from a recently published analytical model of flow fields to present quasi-homogenous temperature distributions that leave flow lines and their local and directed character largely invariant. We present practical, intuitive solutions through predesigned sets of scan lines with near isothermal distributions and demonstrate that they are sufficient to generate and control flows in Caenorhabditis elegans embryos on a magnitude well in excess of endogenous flow velocities. Our results enable the separation of two previously tightly linked classes of physical stimuli, introduce a new, even less invasive standard for performing FLUCS perturbations, and pave the way for new unexplored avenues in the fields of soft matter and biomedicine.Graphical

Stop-signal delay reflects response selection duration in stop-signal task.

The stop-signal task (SST) is widely used for studying the speed of the latent process of response inhibition. The SST patterns are typically explained by a horse-race model (HRM) with supposed Go and Stop processes. However, HRM does not agree with the sequential-stage model of response control. As a result, the exact relationship between the response selection, the response execution stages, and the Stop process remains unclear. We propose that response selection occurs within the stop-signal delay (SSD) period, and that the competition between the Go and Stop processes occurs within the response execution period. To confirm this, we conducted two experiments. In Experiment 1, participants carried out a modified SST task with an additional stimulus category - Cued-Go. In the Cued-Go trials, cues were followed by imperative Go signals. The Cue-Go period duration was dynamically adjusted by an adaptive algorithm based on the response times reflecting the individual response selection duration. In Experiment 2, Cued-Go stimuli were followed by Stop Signals in half of the trials and response inhibition efficiency was calculated. The results of Experiment 1 indicate that SSD reflects the duration of the response selection process. The results of Experiment 2 show that this process has an independent and small effect on the effectiveness of controlled inhibition of the target response. Based on our findings, we propose a two-stage model of response inhibition in SST, with the first stage including response selection process and the second stage response inhibition following the SS presentation.

Increased N250 elicited by facial familiarity: An ERP study including the face inversion effect and facial emotion processing

The present study aims to explore how familiarity modulates the neural processing of faces under different conditions: upright or inverted, neutral or emotional. To this purpose, 32 participants (25 female; age: M = 27.7 years, SD = 9.3) performed two face/emotion identification tasks during EEG recording. In the first task, to study facial processing, three different categories of facial stimuli were presented during a target detection task: famous familiar faces, faces of loved ones, and unfamiliar faces. To explore the face inversion effect according to each level of familiarity, these facial stimuli were also presented upside down. In the second task, to study emotional face processing, an emotional identification task on personally familiar and unfamiliar faces was conducted. The behavioural results showed an improved performance in the identification of facial expressions of emotion with the increase of facial familiarity, consistent with the previous literature. Regarding electrophysiological results, we found increased amplitudes of the P100, N170, and N250 for inverted compared to upright faces, independently of their degree of familiarity. Moreover, we did not find familiarity effects at the P100 and N170 time-windows, but we found that N250 amplitude was larger for personally familiar compared to unfamiliar faces. This result supports the reasoning that the facial familiarity increases the neural activity during the N250 time-window, which may be explained by the processing of additional information prompted by the viewing of our loved ones faces, in contrast to what happens with unfamiliar individuals.

Food induced distractibility in restrictive anorexia nervosa: Different motor patterns for different foods as revealed by a mouse tracker evaluation.

An altered automatic processing of food stimuli may contribute to the maintenance of calorie restriction in patients with restrictive Anorexia Nervosa (AN-R). The present study aimed to assess whether task-irrelevant food distractors elicited a different interference effect in the motor actions of patients with AN-R compared to healthy controls (HC). 40 patients with acute AN-R and 40 HC performed an irrelevant distractor task in which they were required to perform a reaching movement from a starting point to a green dot, while an irrelevant distractor (a high-calorie food, low-calorie food, or neutral object) was presented in the middle of the screen. Mouse trajectories and response times (RT) were recorded. The analyses conducted on the kinematic variables revealed that while the trajectories of HC veered similarly toward the three categories of stimuli, AN-R patients showed an increased deviation toward low-calorie foods and a reduced deviation toward high-calorie foods compared to neutral objects. No significant results emerged as regards RT. The pattern of responses observed in patients with AN-R (deviation increased toward low-calorie and reduced toward high-calorie) is consistent with their eating habits and may thus represent an implicit mechanism sustaining calorie restriction in patients with AN-R.

Paradoxical evidence weighting in confidence judgments for detection and discrimination

When making discrimination decisions between two stimulus categories, subjective confidence judgments are more positively affected by evidence in support of a decision than negatively affected by evidence against it. Recent theoretical proposals suggest that this “positive evidence bias” may be due to observers adopting a detection-like strategy when rating their confidence—one that has functional benefits for metacognition in real-world settings where detectability and discriminability often go hand in hand. However, it is unknown whether, or how, this evidence-weighting asymmetry affects detection decisions about the presence or absence of a stimulus. In four experiments, we first successfully replicate a positive evidence bias in discrimination confidence. We then show that detection decisions and confidence ratings paradoxically suffer from an opposite “negative evidence bias” to negatively weigh evidence even when it is optimal to assign it a positive weight. We show that the two effects are uncorrelated and discuss our findings in relation to models that account for a positive evidence bias as emerging from a confidence-specific heuristic, and alternative models where decision and confidence are generated by the same, Bayes-rational process.

Neural evidence for advantaged representation of first items in memory

Visual areas activated during perception can retain specific information held in memory without the presence of physical stimuli via distributed activity patterns. Neuroimaging studies have shown that the delay-period representation of information in visual areas is modulated by factors such as memory load and task demands, raising the possibility of serial position as another potential modulator. Specifically, enhanced representation of first items during the post-encoding delay period may serve as a mechanism underlying the well-established but not well-understood primacy effect – the mnemonic advantage of first items. To test this hypothesis, 13 males and 16 females performed a human fMRI task, wherein each trial consisted of the sequential encoding of two stimuli (a famous face and landscape, order counterbalanced), followed by a distracting task, a delay period, and then a cued recall of one of the items. Participants exhibited the expected behavioral primacy effect, manifested as faster recall of the first items. In order to elucidate the still debated neural underpinnings of this effect, using multivariate decoding, a classifier was trained on data collected during encoding to differentiate stimulus categories (i.e., faces vs. landscapes) and tested on data collected during the post-encoding period. Greater reactivation of first versus second items was observed in the ventral occipito-temporal cortex during the entire post-encoding period but not during encoding. Moreover, trial-level analyses revealed that the degree of first-item neural advantage during the post-encoding delay predicted the behavioral primacy effect. These findings highlight the role of item reinstatement in ventral occipito-temporal cortex in the primacy effect and are discussed in the context of the uniqueness of the very first item and event boundaries, illuminating putative neural mechanisms underlying the effect.

In Memoriam: Peter J. Urcuioli (1952-2022).

In Memoriam: Peter J. Urcuioli (1952-2022).

Classification of EEG signals using Transformer based deep learning and ensemble models

A Brain-Computer Interface (BCI) is a communication and control system designed to provide interaction between a user and a computer device. This interaction is based on the brain's electrical signals that are generated when users do specific tasks. Different categories of visual stimuli evoke distinct activation patterns in the human brain. The generated patterns can be recorded with EEG signals for use in BCI applications. Recently, deep learning-based Transformer models have demonstrated significant potential for analyzing diverse data. In this paper, a new Transformer-based model has been presented that extracts temporal and spectral features from EEG signals for classification purposes. The proposed Spectral Transformer model converts the EEG signal to the frequency domain using PSD before applying Transformer models to extract frequency features. Deep ensemble learning models are used to enhance the generalization performance of the final model by combining the benefits of both deep learning models and ensemble learning. The proposed ensemble model combines Temporal and Spectral Transformers to simultaneously utilize the time and frequency features of the signal. The accuracy of 96.1 %, 94.20 %, and 93.60 % are achieved using an ensemble model, Temporal Transformer, and Spectral Transformer, respectively. These results demonstrate the effectiveness of the proposed model for accurately classifying EEG signals in BCI applications.

Mechanisms of spatial contextual cueing in younger and older adults.

The contextual cueing effect is the phenomenon observed when response time (RT) becomes faster in visual search in repeated context compared with a new one. In the present study, we explored whether the mechanisms involved in the effect are age dependent. We investigated it in younger (N = 20, 12 women, 21.2 ± 1.75 years) and older (N = 19, nine women, 67.05 ± 3.94 years) adults. We found a faster target identification in the repeated configurations with similar magnitude in the two age groups, which indicates that this contextual cueing effect remained intact even in the older participants. To shed light on the underlying mechanisms, we measured and compared the amplitude of three event-related potentials: N2pc, P3, and response-locked LRP. In the younger group, the larger contextual cueing effect (novel-minus-repeated RT difference) correlated positively with a larger difference in amplitude for repeated compared with novel configurations for both the N2pc and the P3 components, but there was no correlation with the response-locked lateralized readiness potential (rLRP) amplitude difference. However, in the older group, only the rLRP amplitude difference between novel and repeated configurations showed an enhancement with larger contextual cueing. These results suggest that different mechanisms are responsible for the contextual effect in the two age groups. It has both an early and an intermediate locus in younger adults: effective attentional allocation and successful stimulus categorization, or decision-making confidence are involved; while in older adults, a late locus was identified: a more efficient response organization led to a faster reaction.

Interhemispheric transfer of visual information: Meaningfulness and response formation

We examined whether Redundancy Gain (RG) can be dissociated from the response stage of a go/nogo paradigm, and whether the meaningfulness of a stimulus modulates the stage at which interhemispheric transfer occurs. Experiment 1 used a lateralized match-to-category paradigm, taken from categories with varying meaningfulness. Experiment 2 presented a novel design, which separates the perceptual stage from response formation, in examination of RG. A sequence of two stimuli was presented. Participants responded by matching the category of the second stimulus to that of the first. The redundant stimulus could appear at the first or the second stage, thus redundancy gain could be separated from the response. Experiment 1 revealed that redundancy gain occurs earlier in the process of stimulus identification for highly meaningful stimuli than for less meaningful stimuli. The results of Experiment 2 support the hypothesis that redundancy gain results from interhemispheric integration of perceptual information, rather than response-formation. Results from both experiments suggest that redundancy gain arises from interhemispheric integration in the perceptual stage, and the efficiency of this integration depends on the meaningfulness of the stimulus. These results are relevant to current hypotheses about the physiological mechanisms underlying RG.

Single-trial extraction of event-related potentials (ERPs) and classification of visual stimuli by ensemble use of discrete wavelet transform with Huffman coding and machine learning techniques

BackgroundPresentation of visual stimuli can induce changes in EEG signals that are typically detectable by averaging together data from multiple trials for individual participant analysis as well as for groups or conditions analysis of multiple participants. This study proposes a new method based on the discrete wavelet transform with Huffman coding and machine learning for single-trial analysis of evenal (ERPs) and classification of different visual events in the visual object detection task.MethodsEEG single trials are decomposed with discrete wavelet transform (DWT) up to the 4{th} level of decomposition using a biorthogonal B-spline wavelet. The coefficients of DWT in each trial are thresholded to discard sparse wavelet coefficients, while the quality of the signal is well maintained. The remaining optimum coefficients in each trial are encoded into bitstreams using Huffman coding, and the codewords are represented as a feature of the ERP signal. The performance of this method is tested with real visual ERPs of sixty-eight subjects.ResultsThe proposed method significantly discards the spontaneous EEG activity, extracts the single-trial visual ERPs, represents the ERP waveform into a compact bitstream as a feature, and achieves promising results in classifying the visual objects with classification performance metrics: accuracies 93.60pm {6.5}, sensitivities 93.55pm {4.5}, specificities 94.85pm {4.2}, precisions 92.50pm {5.5}, and area under the curve (AUC) 0.93pm {0.3} using SVM and k-NN machine learning classifiers.ConclusionThe proposed method suggests that the joint use of discrete wavelet transform (DWT) with Huffman coding has the potential to efficiently extract ERPs from background EEG for studying evoked responses in single-trial ERPs and classifying visual stimuli. The proposed approach has O(N) time complexity and could be implemented in real-time systems, such as the brain-computer interface (BCI), where fast detection of mental events is desired to smoothly operate a machine with minds.