Quantifying Population-level Neural Tuning Functions Using Ricker Wavelets and the Bayesian Bootstrap.

Experience changes the tuning of sensory neurons, including neurons in retinotopic visual cortex, as evident from work in humans and non-human animals. In human observers, visuo-cortical re-tuning has been studied during aversive generalization learning paradigms, in which the similarity of generalization stimuli (GSs) with a conditioned threat cue (CS+) is used to quantify tuning functions. This work utilized pre-defined tuning shapes reflecting prototypical generalization (Gaussian) and sharpening (Difference-of-Gaussians) patterns. This approach may constrain the ways in which re-tuning can be characterized, for example if tuning patterns do not match the prototypical functions or represent a mixture of functions. The present study proposes a flexible and data-driven method for precisely quantifying changes in neural tuning based on the Ricker wavelet function and the Bayesian bootstrap. The method is illustrated using data from a study in which university students (n = 31) performed an aversive generalization learning task. Oriented gray-scale gratings served as CS+ and GSs and a white noise served as the unconditioned stimulus (US). Acquisition and extinction of the aversive contingencies were examined, while steady-state visual event potentials (ssVEP) and alpha-band (8-13 Hz) power were measured from scalp EEG. Results showed that the Ricker wavelet model fitted the ssVEP and alpha-band data well. The pattern of re-tuning in ssVEP amplitude across the stimulus gradient resembled a generalization (Gaussian) shape in acquisition and a sharpening (Difference-of-Gaussian) shape in an extinction phase. As expected, the pattern of re-tuning in alpha-power took the form of a generalization shape in both phases. The Ricker-based approach led to greater Bayes factors and more interpretable results compared to prototypical tuning models. The results highlight the promise of the current method for capturing the precise nature of visuo-cortical tuning functions, unconstrained by the exact implementation of prototypical a-priori models.

Influence of Heart Rate and Change in Wavefront Direction through Pacing on Conduction Velocity and Voltage Amplitude in a Porcine Model: A High-Density Mapping Study.

BACKGROUND: Understanding the dynamics of conduction velocity (CV) and voltage amplitude (VA) is crucial in cardiac electrophysiology, particularly for substrate-based catheter ablations targeting slow conduction zones and low voltage areas. This study utilizes ultra-high-density mapping to investigate the impact of heart rate and pacing location on changes in the wavefront direction, CV, and VA of healthy pig hearts. METHODS: We conducted in vivo electrophysiological studies on four healthy juvenile pigs, involving various pacing locations and heart rates. High-resolution electroanatomic mapping was performed during intrinsic normal sinus rhythm (NSR) and electrical pacing. The study encompassed detailed analyses at three levels: entire heart cavities, subregions, and localized 5-mm-diameter circular areas. Linear mixed-effects models were used to analyze the influence of heart rate and pacing location on CV and VA in different regions. RESULTS: An increase in heart rate correlated with an increase in conduction velocity and a decrease in voltage amplitude. Pacing influenced conduction velocity and voltage amplitude. Pacing also influenced conduction velocity and voltage amplitude, with varying effects observed based on the pacing location within different heart cavities. Pacing from the right atrium (RA) decreased CV in all heart cavities. The overall CV and VA changes in the whole heart cavities were not uniformly reflected in all subregions and subregional CV and VA changes were not always reflected in the overall analysis. Overall, there was a notable variability in absolute CV and VA changes attributed to pacing. CONCLUSIONS: Heart rate and pacing location influence CV and VA within healthy juvenile pig hearts. Subregion analysis suggests that specific regions of the heart cavities are more susceptible to pacing. High-resolution mapping aids in detecting regional changes, emphasizing the substantial physiological variations in CV and VA.

Neurophysiological and Autonomic Dynamics of Threat Processing During Sustained Social Fear Generalization.

Survival in dynamic environments requires that organisms learn to predict danger from situational cues. One key facet of threat prediction is generalization from a predictive cue to similar cues, ensuring that a cue-outcome contingency is applied beyond the original learning environment. Generalization has been observed in laboratory studies of aversive conditioning: behavioral and physiological processes generalize responses from a stimulus paired with threat (the CS+) to unpaired stimuli, with response magnitudes varying with CS+ similarity. In contrast, work focusing on sensory responses in visual cortex has found a sharpening pattern, in which responses to stimuli closely resembling the CS+ are maximally suppressed, potentially reflecting lateral inhibitory interactions with the CS+ representation. Originally demonstrated with simple visual cues, changes in visuocortical tuning have also been observed in threat generalization learning across facial identities. It is unclear to what extent these visuocortical changes represent transient or sustained effects and if generalization learning requires prior conditioning to the CS+. The present study addressed these questions using EEG and pupillometry in an aversive generalization paradigm involving hundreds of trials using a gradient of facial identities. Visuocortical ssVEP sharpening occurred after dozens of trials of generalization learning without prior differential conditioning, but diminished as learning continued. By contrast, generalization of alpha power suppression, pupil dilation, and self-reported valence and arousal was seen throughout the experiment. Findings are consistent with threat processing models emphasizing the role of changing visucocortical and attentional dynamics when forming, curating, and shaping fear memories as observers continue learning about stimulus-outcome contingencies.

Auditory aversive generalization learning prompts threat-specific changes in alpha-band activity.

Pairing a neutral stimulus with aversive outcomes prompts neurophysiological and autonomic changes in response to the conditioned stimulus (CS+), compared to cues that signal safety (CS-). One of these changes-selective amplitude reduction of parietal alpha-band oscillations-has been reliably linked to processing of visual CS+. It is, however, unclear to what extent auditory conditioned cues prompt similar changes, how these changes evolve as learning progresses, and how alpha reduction in the auditory domain generalizes to similar stimuli. To address these questions, 55 participants listened to three sine wave tones, with either the highest or lowest pitch (CS+) being associated with a noxious white noise burst. A threat-specific (CS+) reduction in occipital-parietal alpha-band power was observed similar to changes expected for visual stimuli. No evidence for aversive generalization to the tone most similar to the CS+ was observed in terms of alpha-band power changes, aversiveness ratings, or pupil dilation. By-trial analyses found that selective alpha-band changes continued to increase as aversive conditioning continued, beyond when participants reported awareness of the contingencies. The results support a theoretical model in which selective alpha power represents a cross-modal index of continuous aversive learning, accompanied by sustained sensory discrimination of conditioned threat from safety cues.

Coherent Off-Axis Terahertz Tomography with a Multi-Channel Array and f-theta Optics.

Terahertz tomography is a promising method among non-destructive inspection techniques to detect faults and defects in dielectric samples. Recently, image quality was improved significantly through the incorporation of a priori information and off-axis data. However, this improvement has come at the cost of increased measurement time. To aim toward industrial applications, it is therefore necessary to speed up the measurement by parallelizing the data acquisition employing multi-channel setups. In this work, we present two tomographic frequency-modulated continuous wave (FMCW) systems working at a bandwidth of 230-320 GHz, equipped with an eight-channel detector array, and we compare their imaging results with those of a single-pixel setup. While in the first system the additional channels are used exclusively to detect radiation refracted by the sample, the second system features an f-θ lens, focusing the beam at different positions on its flat focal plane, and thus utilizing the whole detector array directly. The usage of the f-θ lens in combination with a scanning mirror eliminates the necessity of the formerly used slow translation of a single-pixel transmitter. This opens up the potential for a significant increase in acquisition speed, in our case by a factor of four to five, respectively.

The emergence of the EEG dominant rhythm across the first year of life.

The spectral composition of EEG provides important information on the function of the developing brain. For example, the frequency of the dominant rhythm, a salient features of EEG data, increases from infancy to adulthood. Changes of the dominant rhythm during infancy are yet to be fully characterized, in terms of their developmental trajectory and spectral characteristics. In this study, the development of dominant rhythm frequency was examined during a novel sustained attention task across 6-month-old (n = 39), 9-month-old (n = 30), and 12-month-old (n = 28) infants. During this task, computer-generated objects and faces floated down a computer screen for 10 s after a 5-second fixation cross. The peak frequency in the range between 5 and 9 Hz was calculated using center of gravity (CoG) and examined in response to faces and objects. Results indicated that peak frequency increased from 6 to 9 to 12 months of age in face and object conditions. We replicated the same result for the baseline. There was high reliability between the CoGs in the face, object, and baseline conditions across all channels. The developmental increase in CoG was more reliable than measures of mode frequency across different conditions. These findings suggest that CoG is a robust index of brain development across infancy.

Groupwise structural sparsity for discriminative voxels identification.

This paper investigates the selection of voxels for functional Magnetic Resonance Imaging (fMRI) brain data. We aim to identify a comprehensive set of discriminative voxels associated with human learning when exposed to a neutral visual stimulus that predicts an aversive outcome. However, due to the nature of the unconditioned stimuli (typically a noxious stimulus), it is challenging to obtain sufficient sample sizes for psychological experiments, given the tolerability of the subjects and ethical considerations. We propose a stable hierarchical voting (SHV) mechanism based on stability selection to address this challenge. This mechanism enables us to evaluate the quality of spatial random sampling and minimizes the risk of false and missed detections. We assess the performance of the proposed algorithm using simulated and publicly available datasets. The experiments demonstrate that the regularization strategy choice significantly affects the results' interpretability. When applying our algorithm to our collected fMRI dataset, it successfully identifies sparse and closely related patterns across subjects and displays stable weight maps for three experimental phases under the fear conditioning paradigm. These findings strongly support the causal role of aversive conditioning in altering visual-cortical activity.

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.

CNN stability training improves robustness to scanner and IHC-based image variability for epithelium segmentation in cervical histology.

Background: In digital pathology, image properties such as color, brightness, contrast and blurriness may vary based on the scanner and sample preparation. Convolutional Neural Networks (CNNs) are sensitive to these variations and may underperform on images from a different domain than the one used for training. Robustness to these image property variations is required to enable the use of deep learning in clinical practice and large scale clinical research. Aims: CNN Stability Training (CST) is proposed and evaluated as a method to increase CNN robustness to scanner and Immunohistochemistry (IHC)-based image variability. Methods: CST was applied to segment epithelium in immunohistological cervical Whole Slide Images (WSIs). CST randomly distorts input tiles and factors the difference between the CNN prediction for the original and distorted inputs within the loss function. CNNs were trained using 114 p16-stained WSIs from the same scanner, and evaluated on 6 WSI test sets, each with 23 to 24 WSIs of the same tissue but different scanner/IHC combinations. Relative robustness (rAUC) was measured as the difference between the AUC on the training domain test set (i.e., baseline test set) and the remaining test sets. Results: Across all test sets, The AUC of CST models outperformed "No CST" models (AUC: 0.940-0.989 vs. 0.905-0.986, p < 1e - 8), and obtained an improved robustness (rAUC: [-0.038, -0.003] vs. [-0.081, -0.002]). At a WSI level, CST models showed an increase in performance in 124 of the 142 WSIs. CST models also outperformed models trained with random on-the-fly data augmentation (DA) in all test sets ([0.002, 0.021], p < 1e-6). Conclusion: CST offers a path to improve CNN performance without the need for more data and allows customizing distortions to specific use cases. A python implementation of CST is publicly available at https://github.com/TIGACenter/CST_v1.

Feature-based Attentional Amplitude Modulations of the Steady-state Visual Evoked Potentials Reflect Blood Oxygen Level Dependent Changes in Feature-sensitive Visual Areas.

Recent EEG studies have investigated basic principles of feature-based attention by means of frequency-tagged random dot kinematograms in which different colors are simultaneously presented at different temporal frequencies to elicit steady-state visual evoked potentials (SSVEPs). These experiments consistently showed global facilitation of the to-be-attended random dot kinematogram-a basic principle of feature-based attention. SSVEP source estimation suggested that posterior visual cortex from V1 to area hMT+/V5 is broadly activated by frequency-tagged stimuli. What is presently unknown is whether the feature-based attentional facilitation of SSVEPs is a rather unspecific neural response including all visual areas that follow the "on/off," or whether SSVEP feature-based amplitude enhancements are driven by activity in visual areas most sensitive to a specific feature, such as V4v in the case of color. Here, we leverage multimodal SSVEP-fMRI recordings in human participants and a multidimensional feature-based attention paradigm to investigate this question. Attending to shape produced significantly greater SSVEP-BOLD covariation in primary visual cortex compared with color. SSVEP-BOLD covariation during color selection increased along the visual hierarchy, with greatest values in areas V3 and V4. Importantly, in area hMT+/V5, we found no differences between shape and color selection. Results suggest that SSVEP amplitude enhancements in feature-based attention is not an unspecific enhancement of neural activity in all visual areas following the "on/off." These findings open new avenues to investigating neural dynamics of competitive interactions in specific visual areas sensitive to a certain feature in a more economical way and better temporal resolution compared with fMRI.

Quantum range-migration-algorithm for synthetic aperture radar applications.

The 3D range-migration algorithm (RMA) and its 2D equivalent, the omega-k algorithm, are employed in a wide range of applications where reconstruction of synthetic aperture data is required, from satellite radar imaging of planets over seismic imaging of the earth crust, down to phased-array ultrasound and ultrasonic application, and recently in-line synthetic aperture radar for non-destructive testing. These algorithms are based on Fourier transforms and share their time-complexity. This limits highly-resolved measurement data to be processed at high speeds which would be advantageous for modern production feed lines. In this publication, we present the development and implementation of the RMA on a quantum computer that scales favourably compared to the time complexity of the classical RMA. We compare reconstruction results of simulated and measured data of the classical and quantum RMA. Hereby, the quantum RMA is run on a quantum simulator backend as well as on IBM's Q System One quantum computer. The results show that real world applications and testing tasks may benefit from future quantum computers.

Effects of neurofeedback training on performance in laboratory tasks: A systematic review.

Neurofeedback procedures are attracting increasing attention in the neuroscience community. Based on the principle that participants, through suitable feedback, may learn to affect specific aspects of their brain activity, neurofeedback interventions have been applied to basic research, translational, and clinical science. A large segment of the available empirical research as well as review articles have focused on the extent to which neurofeedback interventions affect mental health outcomes, cognitive capacity, aging, and other complex behaviors. Another segment has aimed to characterize the extent to which neurofeedback affects the targeted neural processes. At this time, there is no current systematic review of the effects of neurofeedback on healthy participants' performance in experimental tasks. Such a review is relevant in this rapidly evolving field because changes in experimental task performance are traditionally considered a hallmark of changing neurocognitive processes, often established in neurotypical individuals. This systematic review addresses this gap in the literature using the PRISMA method, building on earlier reviews on the same topic. Empirical studies using EEG or fMRI to alter brain processes linked to established cognitive and affective laboratory tasks were reviewed. Systematic quality assessment and z-curve analyses were also conducted. Substantial variability was found regarding the study designs used, the implementation of the feedback, and the neural targets of feedback. Importantly, only a minority of the studies reported statistically meaningful effects of neurofeedback on performance in cognitive and affective tasks. The z-curve analyses found no evidence for reporting bias or unsound research practices. Quality control and effect size analyses showed few systematic relations between study characteristics such as sample size or experimental control on the one hand and outcome on the other. Overall, the present study does not support strong effects of NFT on performance in laboratory tasks. Implications for future work are discussed.

Higher amplitudes in steady-state visual evoked potentials driven by square-wave versus sine-wave contrast modulation - A dual-laboratory study.

Steady-state visual evoked potentials (ssVEPs) are an established tool for assessing visuocortical responses in visual perception and attention. They have the same temporal frequency characteristics as a periodically modulated stimulus (e.g., in contrast or luminance) that drives them. It has been hypothesized that the amplitude of a given ssVEP may depend on the shape of the stimulus modulation function, but the size and robustness of these effects is not well established. The current study systematically compared the effect of the two most common functions in the ssVEP literature, square-wave and sine-wave functions. Across two laboratories, we presented mid-complex color patterns to 30 participants with square-wave or sine-wave contrast modulation and at different driving frequencies (6 Hz, 8.57 Hz, 15 Hz). When ssVEPs were analyzed independently for the samples, with each laboratory's standard processing pipeline, ssVEP amplitudes in both samples decreased at higher driving frequencies and square-wave modulation evoked higher amplitudes at lower frequencies (i.e., 6 Hz, 8.57 Hz) compared to sine-wave modulation. These effects were replicated when samples were aggregated and analyzed with the same processing pipeline. In addition, when using signal-to-noise ratios as outcome measures, this joint analysis indicated a somewhat weaker effect of increased ssVEP amplitudes to square-wave modulation at 15 Hz. The present study suggests that square-wave modulation should be used in ssVEP research when the goal is to maximize signal amplitude or signal-to-noise ratio. Given effects of modulation function across laboratories, and data processing pipelines, the findings appear robust to differences in data collection and analysis.

Early visual perceptual processing is altered in obsessive-compulsive disorder.

OBJECTIVE: Existing studies have shown changes in attention and emotion processing of disorder-relevant visual stimuli in those with obsessive compulsive disorder (OCD). However, early visual processing in OCD has not been assessed, as previous studies did not examine the entire time course of visual processing but instead assessed potential differences in pre-determined visual evoked potentials (VEPs). This study investigates the entire visual processing stream in OCD compared to healthy age-matched controls (HC) using emotionally-neutral visual stimuli and a data-driven rather than hypothesis-driven approach. METHODS: 35 HC and 26 participants with OCD underwent EEG recording while completing a modified Eriksen flanker task. Permutation-controlled t-tests were used to identify group differences in the data's full time course of visual evoked potentials. Baseline-corrected amplitudes at time points where the groups were significantly different were analyzed using ANCOVAs with BDI, BAI, and SNAP-inattentiveness scores included as covariates. RESULTS: This analysis identified enhanced P1 amplitudes to two visual stimuli (the initial flanker and the stimulus), corresponding to time windows of 65-93 ms and 157-187 ms post-flanker presentation in the OCD group compared to controls. Group (OCD vs. HC) was the strongest predictor of VEP amplitude during both time windows, with no significant influences of any covariates. CONCLUSIONS: This study showed an enhanced P1 component in people with OCD to neutral visual stimuli, potentially reflecting either inefficient or excessive early visual processing in this population. Additional inquiry is necessary to determine whether altered visual processing is associated with the sensory hypervigilance observed in those with OCD. SIGNIFICANCE: This work identifies early visual processing alterations in OCD using neutral stimuli and a data-driven approach.

Behavioral and Physiological Reactions to a Sudden Novel Object in the Weanling Horse: Quantitative Phenotypes for Future GWAS.

The startle response can be defined as a reflexive reaction to the sudden appearance of a novel stimulus that influences the survival and resilience of animals. In domesticated species, the behavioral component of the startle response can, in some cases, cause serious injury to the animal or human handlers if inappropriately expressed. Here, we describe a longitudinal study in a population of stock-type horses that quantified behavioral startle responses elicited by the presentation of a sudden novel object (rapidly opening umbrella). The study was performed in weanling foals across four consecutive years (n = 74, mean age = 256 days). Behavioral assays for the startle response phenotype focused on six behavioral variables: latency to return to the feed pan (seconds), maximum distance fled (meters), proportion of time spent walking or trotting (seconds), and how long a horse spent standing facing away from or toward the novel object. We observed behavioral startle response variables in relation to cardiac response, age, and sex for each individual. Each horse's cardiac startle response pattern was determined and categorized into heart rate response cluster groups identified as accelerators and decelerators. Using principal component analysis (PCA) with a factor rotation, we identified "startle response" phenotypes that summarize the behavioral and physiological variables. The largest component of variation, Factor 1, comprised 32.5% of the behavioral variable with a positive correlation with latency and distance, and was not influenced by sex or age. Factor 2 comprised 23.2% of the variation, and was positively correlated with activity level performed such as proportion of time spent walking and/or trotting. Horses with the accelerator type cardiac response had significantly higher Factor 1 scores than decelerators but did not differ in Factor 2. Future work includes expanding our sample size to conduct a genome-wide association study (GWAS) to identify novel genetic loci influencing behavioral startle reactions using recorded behavioral and physiological phenotypes.

Sensing fear: fast and precise threat evaluation in human sensory cortex.

Animal models of threat processing have evolved beyond the amygdala to incorporate a distributed neural network. In human research, evidence has intensified in recent years to challenge the canonical threat circuitry centered on the amygdala, urging revision of threat conceptualization. A strong surge of research into threat processing in the sensory cortex in the past decade has generated particularly useful insights to inform the reconceptualization. Here, synthesizing findings from both animal and human research, we highlight sensitive, specific, and adaptable threat representations in the sensory cortex, arising from experience-based sculpting of sensory coding networks. We thus propose that the human sensory cortex can drive smart (fast and precise) threat evaluation, producing threat-imbued sensory afferents to elicit network-wide threat responses.