An evolutionary disruption of the buzz pollination syndrome in neotropical montane plants.

PREMISE: Under pollinator limitations, specialized pollination syndromes may evolve toward contrasting responses: a generalized syndrome with increased pollinator attraction, pollinator reward, and pollen transfer capacity; or the selfing syndrome with increased self-pollen deposition, but reduced pollinator attraction and pollen transfer capacity. The buzz-pollination syndrome is specialized to explore female vibrating bees as pollinators. However, vibrating bees become less-active pollinators at montane areas of the Atlantic Forest (AF) domain. This study investigated whether the specialized buzz-pollination syndrome would evolve toward an alternative floral syndrome in montane areas of the AF domain, considering a generalized and the selfing syndromes as alternative responses. METHODS: We utilized a lineage within the buzz-pollinated Miconia as study system, contrasting floral traits between montane AF-endemic and non-endemic species. We measured and validated floral traits that were proxies for pollinator attraction, reward access, pollen transfer capacity, and self-pollen deposition. We inferred the evolution of floral trait via phylogenetic comparative methods. RESULTS: AF-endemic species have selectively evolved greater reward access and more frequently had generalist pollination. Nonetheless, AF-endemic species also have selectively evolved toward lower pollen transfer capacity and greater self pollination. These patterns indicated a complex evolutionary process that has jointly favored a generalized and the selfing syndromes. CONCLUSIONS: The buzz pollination syndrome can undergo an evolutionary disruption in montane areas of the AF domain. This floral syndrome is likely more labile than often assumed, allowing buzz-pollinated plants to reproduce in environments where vibrating bees are less-reliable pollinators.

Effects of Serial Multiple Exemplar Training on Bidirectional Naming in Children with Autism.

This study examined the effect of a serial multiple exemplar training (S-MET) procedure on bidirectional naming (BiN) in four preschool children diagnosed with autism spectrum disorder (ASD). A non-concurrent multiple baseline design was used to evaluate the effects of training listener and speaker behavior for one stimulus at a time until BiN occurred. When BiN occurred, probes were conducted to measure whether generalization occurred across settings and people. Three out of four participants' responding met the mastery criterion for BiN, while the fourth participant improved her performance. The results of this study suggest that S-MET may be a promising intervention and contribute to our knowledge about learning histories required for BiN.

Increased Generalization, Stronger Acquisition, or Reduced Extinction? Investigation of the Mechanisms Underlying the Acquisition-in-Multiple-Contexts Effect.

Prior research has demonstrated that conducting acquisition in multiple contexts results in more responding to the point that it can even nullify the benefit of subsequent extinction in multiple contexts on reducing renewal of excitatory responding. The underlying mechanism to explain why this happens has not been systematically examined. Using self-reported expectancy of the outcome, the current study investigates three mechanisms that potentially explain why acquisition in multiple contexts results in more responding-greater generalization, stronger acquisition learning, or slower extinction learning. Participants (N = 180) received discriminative training with a conditioned stimulus (CS+) and outcome pairing and a CS- → noOutcome pairing in either one or three contexts. This was followed by either extinction treatment in a novel context or no extinction. Finally, testing occurred in the acquisition context, the extinction context, or a novel context. Stronger renewal of extinguished conditioned expectation was observed for participants who received CS+ → Outcome pairings in three contexts relative to one context. There was no effect of the number of contexts on the strength of the excitatory CS+ → Outcome association or degree of inhibitory learning that occurred during extinction. This suggests that generalization is the mechanism responsible for the adverse impact to extinction learning when acquisition is conducted in multiple contexts.

SAMCF: Adaptive global style alignment and multi-color spaces fusion for joint optic cup and disc segmentation.

The optic cup (OC) and optic disc (OD) are two critical structures in retinal fundus images, and their relative positions and sizes are essential for effectively diagnosing eye diseases. With the success of deep learning in computer vision, deep learning-based segmentation models have been widely used for joint optic cup and disc segmentation. However, there are three prominent issues that impact the segmentation performance. First, significant differences among datasets collecting from various institutions, protocols, and devices lead to performance degradation of models. Second, we find that images with only RGB information struggle to counteract the interference caused by brightness variations, affecting color representation capability. Finally, existing methods typically ignored the edge perception, facing the challenges in obtaining clear and smooth edge segmentation results. To address these drawbacks, we propose a novel framework based on Style Alignment and Multi-Color Fusion (SAMCF) for joint OC and OD segmentation. Initially, we introduce a domain generalization method to generate uniformly styled images without damaged image content for mitigating domain shift issues. Next, based on multiple color spaces, we propose a feature extraction and fusion network aiming to handle brightness variation interference and improve color representation capability. Lastly, an edge aware loss is designed to generate fine edge segmentation results. Our experiments conducted on three public datasets, DGS, RIM, and REFUGE, demonstrate that our proposed SAMCF achieves superior performance to existing state-of-the-art methods. Moreover, SAMCF exhibits remarkable generalization ability across multiple retinal fundus image datasets, showcasing its outstanding generality.

Medial anterior prefrontal cortex stimulation downregulates implicit reactions to threats and prevents the return of fear.

Downregulating emotional overreactions toward threats is fundamental for developing treatments for anxiety and post-traumatic disorders. The prefrontal cortex (PFC) is critical for top-down modulatory processes, and despite previous studies adopting repetitive transcranial magnetic stimulation (rTMS) over this region provided encouraging results in enhancing extinction, no studies have hitherto explored the effects of stimulating the medial anterior PFC (aPFC, encompassing the Brodmann area 10) on threat memory and generalization. Here we showed that rTMS over the aPFC applied before threat memory retrieval immediately decreases implicit reactions to learned and novel stimuli in humans. These effects enduringly persisted 1 week later in the absence of rTMS. No effects were detected on explicit recognition. Critically, rTMS over the aPFC resulted in a more pronounced reduction of defensive responses compared to rTMS targeting the dorsolateral PFC. These findings reveal a previously unexplored prefrontal region, the modulation of which can efficiently and durably inhibit implicit reactions to learned threats. This represents a significant advancement toward the long-term deactivation of exaggerated responses to threats.

LJCD-Net: Cross-Domain Jamming Generalization Diagnostic Network Based on Deep Adversarial Transfer.

Global Navigation Satellite Systems (GNSS) offer comprehensive position, navigation, and timing (PNT) estimates worldwide. Given the growing demand for reliable location awareness in both indoor and outdoor contexts, the advent of fifth-generation mobile communication technology (5G) has enabled expansive coverage and precise positioning services. However, the power received by the signal of interest (SOI) at terminals is notably low. This can lead to significant jamming, whether intentional or unintentional, which can adversely affect positioning receivers. The diagnosis of jamming types, such as classification, assists receivers in spectrum sensing and choosing effective mitigation strategies. Traditional jamming diagnosis methodologies predominantly depend on the expertise of classification experts, often demonstrating a lack of adaptability for diverse tasks. Recently, researchers have begun utilizing convolutional neural networks to re-conceptualize a jamming diagnosis as an image classification issue, thereby augmenting recognition performance. However, in real-world scenarios, the assumptions of independent and homogeneous distributions are frequently violated. This discrepancy between the source and target distributions frequently leads to subpar model performance on the test set or an inability to procure usable evaluation samples during training. In this paper, we introduce LJCD-Net, a deep adversarial migration-based cross-domain jamming generalization diagnostic network. LJCD-Net capitalizes on a fully labeled source domain and multiple unlabeled auxiliary domains to generate shared feature representations with generalization capabilities. Initially, our paper proposes an uncertainty-guided auxiliary domain labeling weighting strategy, which estimates the multi-domain sample uncertainty to re-weight the classification loss and specify the gradient optimization direction. Subsequently, from a probabilistic distribution standpoint, the spatial constraint imposed on the cross-domain global jamming time-frequency feature distribution facilitates the optimization of collaborative objectives. These objectives include minimizing both the source domain classification loss and auxiliary domain classification loss, as well as optimizing the inter-domain marginal probability and conditional probability distribution. Experimental results demonstrate that LJCD-Net enhances the recognition accuracy and confidence compared to five other diagnostic methods.

The generalization of threat beliefs to novel safety stimuli induced by safety behaviors.

Safety behaviors are responses that can reduce or even prevent an expected threat. Moreover, empirical studies have shown that using safety behaviors to a learnt safety stimulus can induce threat beliefs to it. No research so far has examined whether threat beliefs induced this way generalize to other novel stimuli related to the safety stimulus. Using a fear and avoidance conditioning model, the current study (n=116) examined whether threat beliefs induced by safety behaviors generalize to other novel generalization stimuli (GSs). Participants first acquired safety behaviors to a threat predicting conditioned stimulus (CSthreat). Safety behaviors could then be performed in response to one safe stimulus (CSsafeShift) but not to another (CSsafe). In a following generalization test, participants showed a significant but small increase in threat expectancies to GSs related to CSsafeShift compared to GSs related to CSsafe. Interestingly, the degree of safety behaviors used to the CSsafeShift predicted the subsequent increase in generalized threat expectancies, and this link was elevated in trait anxious individuals. The findings suggest that threat beliefs induced by unnecessary safety behaviors generalize to other related stimuli. This study provides a potential explanation for the root of threat belief acquisition to a wide range of stimuli or situations.

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.

Sleep deprivation increases the generalization of perceptual and concept-based fear: An fNIRS study.

Insufficient sleep can initiate or exacerbate anxiety by triggering excessive fear generalization. In this study, a de novo paradigm was developed and used to examine the neural mechanisms governing the effects of sleep deprivation on processing perceptual and concept-based fear generalizations. A between-subject design was adopted, wherein a control group (who had a typical night's sleep) and a one-night sleep deprivation group completed a fear acquisition task at 9:00 PM on the first day and underwent a generalization test the following morning at 7:00 AM. In the fear acquisition task, navy blue and olive green were used as perceptual cues (P+ and P-, respectively), while animals and furniture items were used as conceptual cues (C+ and C-, respectively). Generalization was tested for four novel generalized categories (C+P+, C+P-, C-P+, and C-P-). Shock expectancy ratings, skin conductance responses, and functional near-infrared spectroscopy were recorded during the fear acquisition and generalization processes. Compared with the group who had a typical night's sleep, the sleep deprived group showed higher shock expectancy ratings (especially for P+ and C-), increased oxygenated hemoglobin in the dorsolateral prefrontal cortex, and increased activation in the triangular inferior frontal gyrus during the generalization test. These findings suggest that sleep deprivation increases the generalization of threat memories, thus providing insights into the overgeneralization characteristics of anxiety and fear-related disorders.

Secure attachment priming inhibits the generalization of conditioned fear.

BACKGROUND: Fear overgeneralization constitutes a susceptibility factor contributing to the development and maintenance of anxiety spectrum disorders. Extant research has demonstrated that exposure to positive and supportive social relationships attenuates fear acquisition and promotes the extinction of conditioned fear responses. However, the literature lacks investigation into the effect of secure attachment priming on inhibiting the generalization of conditioned fear. METHODS: In this study, college students were recruited via online platforms to voluntarily engage in the experimental procedures, resulting in 57 subjects whose data were deemed suitable for analysis. The experimental protocol consisted of four consecutive phases: pre-acquisition, acquisition, priming, and generalization. The priming phase consisted of two experimental conditions: secure attachment priming (experimental group) and positive emotion priming (control group). This study adopted the perceptual discrimination fear conditioning paradigm, employing subjective expectancy of shock ratings and skin conductance responses as primary assessment indices. Individual difference variables were measured using corresponding psychological measurement scales. RESULTS: In terms of generalization degree, a notable divergence surfaced in the skin conductance responses across various generalization materials between the secure attachment priming group and the control group. Similarly, during generalization extinction, a significant disparity emerged in the skin conductance responses across different generalization phases between the secure attachment priming group and the control group. In addition, individual differences analyses revealed that the inhibitory effect of secure attachment priming on fear generalization was not affected by intolerance of uncertainty and attachment orientations. Conversely, slope analyses confirmed that as intolerance of uncertainty increased, the inhibitory effect of positive emotion priming on fear generalization was attenuated. CONCLUSION: The findings suggest that activating participants' representations of secure attachment via imagination effectively attenuates the generalization of perceptual fear at the physiological level. The inhibitory effect of secure attachment priming appears to be distinct from positive emotional modulation and remains unaffected by individual trait attachment styles. These results offer novel insights and avenues for the prevention and clinical intervention of anxiety spectrum disorders.

Anhedonia is associated with overgeneralization of conditioned fear during late adolescence and early adulthood.

BACKGROUND: Pavlovian fear paradigms involve learning to associate cues with threat or safety. Aberrances in Pavlovian fear learning correlate with psychopathology, especially anxiety disorders. This study evaluated symptom dimensions of anxiety and depression in relation to Pavlovian fear acquisition and generalization. METHODS: 256 participants (70.31 % female) completed a Pavlovian fear acquisition and generalization paradigm at ages 18-19 and 21-22 years. Analyses focused on indices of learning (self-reported US expectancy, skin conductance). Multilevel models tested associations with orthogonal symptom dimensions (Anhedonia-Apprehension, Fears, General Distress) at each timepoint. RESULTS: All dimensions were associated with weaker acquisition of US expectancies at each timepoint. Fears was associated with overgeneralization only at age 21-22. General Distress was associated with overgeneralization only at age 18-19. Anhedonia-Apprehension was associated with overgeneralization at ages 18-19 and 21-22. CONCLUSIONS: Anhedonia-Apprehension disrupts Pavlovian fear acquisition and increases overgeneralization of fear. These effects may emerge during adolescence and remain into young adulthood. General Distress and Fears also contribute to overgeneralization of fear, but these effects may vary as prefrontal mechanisms of fear inhibition continue to develop during late adolescence. Targeting specific symptom dimensions, particularly Anhedonia-Apprehension, may decrease fear generalization and augment interventions built on Pavlovian principles, such as exposure therapy.

AMPA receptor potentiation alleviates NLRP3 knockout-induced fear generalization in mice.

Genetic knockout and pharmaceutical inhibition of the NLRP3 inflammasome enhances the extinction of contextual fear memory, which is attributed to its role in neuronal and synaptic dysregulation, concurrent with neurotransmitter function disturbances. This study aimed to determine whether NLRP3 plays a role in generalizing fear via the inflammatory axis. We established the NLRP3 KO mice model, followed by behavioral and biochemical analyses. The NLRP3 KO mice displayed impaired fear generalization, lower neuroinflammation levels, and dysregulated neurotransmitter function. Additionally, α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors, but not the inhibition of NMDA or 5-HT2C receptors, resulted in fear generalization in NLRP3 KO mice because TAT-GluA2 3Y, but not SB242084 and D-cycloserine, treated blocked NLRP3 deprivation effects on fear generalization. Thus, global knockout of NLRP3 is associated with aberrant fear generalization, possibly through AMPA receptor signaling.

Spaced conditioned stimulus presentation facilitates the extinction of strong fear memory in mice.

Inducing fear memory extinction by re-presenting a conditioned stimulus (CS) is the foundation of exposure therapy for post-traumatic stress disorder (PTSD). Investigating differences in the ability of different CS presentation patterns to induce extinction learning is crucial for improving this type of therapy. Using a trace fear conditioning paradigm in mice, we demonstrate that spaced presentation of the CS facilitated the extinction of a strong fear memory to a greater extent than continuous CS presentation. These results lay the groundwork for developing more effective exposure therapy techniques for PTSD.

Imagery rescripting and extinction: Effects on US expectancy, US revaluation, and the generalization of fear reduction.

Exposure therapy consists of exposing patients to their fears and thereby diminishing their harm expectancies (i.e., extinction or expectancy learning). Although effective for many anxiety patients, its long-term success depends on the generalization of these harm expectancies to other stimuli. However, research shows that this generalization of extinction is limited. Besides decreasing harm expectancies, fear reduction may also be achieved by changing the meaning of an aversive memory representation (US revaluation). Imagery rescripting (ImRs) may be more successful in generalizing fear reduction because it allegedly works through US revaluation. The current experiment aimed to test working mechanisms for ImRs and extinction (revaluation and expectancy learning, respectively), and to examine generalization of fear reduction. In a fear conditioning paradigm, 113 healthy participants watched an aversive film clip that was used as the US. The manipulation consisted of imagining a script with a positive ending to the film clip (ImRs-only), extinction (extinction-only), or both (ImRs + extinction). Results showed enhanced US revaluation in ImRs + extinction. US expectancy decreased more strongly in the extinction conditions. Generalization of fear reduction was found in all conditions. Our results suggest different working mechanisms for ImRs and exposure. Future research should replicate this in (sub)clinical samples.

Exploring the 'black box' of anxiety: An ERP study of non-consciously triggered fear generalization.

Individuals with anxiety disorders frequently display heightened fear responses, even in situations where there is no imminent danger. We hypothesize that these irrational fear responses are related to automatic processing of fear generalization. The initial automatic detection of stimuli often operates at a non-conscious level. However, whether fear generalization can occur when the cues are not perceived consciously remains unclear. The current study investigated the neurocognitive mechanisms underlying fear conditioning and its non-conscious and conscious generalization using a backward masking paradigm, combined with analysis of event-related potentials from electroencephalographic recordings. Behaviorally, participants showed heightened shock expectancy in response to non-conscious perceived generalization stimuli compared to those perceived consciously. Nonetheless, participants could not consciously distinguish between danger and safe cues in non-conscious trials. Physiologically, danger cues evoked larger frontal N1 amplitudes than safety cues in non-conscious trials, suggesting enhanced attention vigilance towards danger cues in the early sensory processing stage. Meanwhile, when fear generalization was conscious, it was accompanied by a larger P2 amplitude, indicating attention orientation or stimulus evaluation. In addition, fear conditioning was associated with sustained discrimination on P2, P3, and LPP. These findings collectively suggest that non-conscious fear generalization occurs at the neural level, yet additional control conditions are required to confirm this phenomenon on the US expectancy. Thus, non-consciously fear generalization may represent a mechanism that could trigger automatic irrational fear, highlighting the need for further research to explore therapeutic targets in anxiety disorders.

Exaggerated sensitivity to threat and reduced medial prefrontal engagement during threat generalization in reactive aggressive adolescents.

Aggressive adolescents tend to exhibit abnormal fear acquisition and extinction, and reactive aggressive adolescents are often more anxious. However, the relationship between fear generalization and reactive aggression (RA) remains unknown. According to Reactive-Proactive Aggression Questionnaire (RPQ) scores, 61 adolescents were divided into two groups, namely, a high RA group (N = 30) and a low aggression (LA) group (N = 31). All participants underwent three consecutive phases of the Pavlovian conditioning paradigm (i.e., habituation, acquisition, and generalization), and neural activation of the medial prefrontal cortex (mPFC) was assessed by functional near-infrared spectroscopy (fNIRS). The stimuli were ten circles with varying sizes, including two conditioned stimuli (CSs) and eight generalization stimuli (GSs). A scream at 85 dB served as the auditory unconditioned stimulus (US). The US expectancy ratings of both CSs and GSs were higher in the RA group than in the LA group. The fNIRS results showed that CSs and GSs evoked lower mPFC activation in the RA group compared to the LA group during fear generalization. These findings suggest that abnormalities in fear acquisition and generalization are prototypical dysregulations in adolescents with RA. They provide neurocognitive evidence for dysregulated fear learning in the mechanisms underlying adolescents with RA, highlighting the need to develop emotional regulation interventions for these individuals.

Generalization of a Deep Learning Model for Continuous Glucose Monitoring-Based Hypoglycemia Prediction: Algorithm Development and Validation Study.

Background: Predicting hypoglycemia while maintaining a low false alarm rate is a challenge for the wide adoption of continuous glucose monitoring (CGM) devices in diabetes management. One small study suggested that a deep learning model based on the long short-term memory (LSTM) network had better performance in hypoglycemia prediction than traditional machine learning algorithms in European patients with type 1 diabetes. However, given that many well-recognized deep learning models perform poorly outside the training setting, it remains unclear whether the LSTM model could be generalized to different populations or patients with other diabetes subtypes. Objective: The aim of this study was to validate LSTM hypoglycemia prediction models in more diverse populations and across a wide spectrum of patients with different subtypes of diabetes. Methods: We assembled two large data sets of patients with type 1 and type 2 diabetes. The primary data set including CGM data from 192 Chinese patients with diabetes was used to develop the LSTM, support vector machine (SVM), and random forest (RF) models for hypoglycemia prediction with a prediction horizon of 30 minutes. Hypoglycemia was categorized into mild (glucose=54-70 mg/dL) and severe (glucose<54 mg/dL) levels. The validation data set of 427 patients of European-American ancestry in the United States was used to validate the models and examine their generalizations. The predictive performance of the models was evaluated according to the sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). Results: For the difficult-to-predict mild hypoglycemia events, the LSTM model consistently achieved AUC values greater than 97% in the primary data set, with a less than 3% AUC reduction in the validation data set, indicating that the model was robust and generalizable across populations. AUC values above 93% were also achieved when the LSTM model was applied to both type 1 and type 2 diabetes in the validation data set, further strengthening the generalizability of the model. Under different satisfactory levels of sensitivity for mild and severe hypoglycemia prediction, the LSTM model achieved higher specificity than the SVM and RF models, thereby reducing false alarms. Conclusions: Our results demonstrate that the LSTM model is robust for hypoglycemia prediction and is generalizable across populations or diabetes subtypes. Given its additional advantage of false-alarm reduction, the LSTM model is a strong candidate to be widely implemented in future CGM devices for hypoglycemia prediction.

GABAergic interneurons in the hippocampal CA1 mediate contextual fear generalization in PTSD rats.

Fear overgeneralization is widely accepted as a pathogenic marker of post-traumatic stress disorder (PTSD). Recently, GABAergic interneurons have been regarded as key players in the regulation of fear memory. The role of hippocampal GABAergic interneurons in contextual fear generalization of PTSD remains incompletely understood. In the present study, we established a rat model of PTSD with inescapable foot shocks (IFS) and observed the loss of GABAergic interneuron phenotype in the hippocampal cornu ammonis-1 (CA1) subfield. To determine whether the loss of GABAergic interneuron phenotype was associated with fear generalization in PTSD rats, we used adeno-associated virus (AAV) to reduce the expression of GAD67 in CA1 and observed its effect on fear generalization. The results showed that the reduction of GAD67 in CA1 enhanced contextual fear generalization in rats. We investigated whether the PERK pathway was involved in the GABAergic interneuron injury. Increased expression of p-PERK, CHOP, and Caspase12 in GABAergic interneurons of PTSD rats was observed. Then, we used salubrinal, an endoplasmic reticulum stress inhibitor, to modulate the PERK pathway. The salubrinal treatment significantly protected the GABAergic interneurons and relieved fear generalization in PTSD rats. In addition, the results showed that salubrinal down-regulated the expression of CHOP and Caspase12 in GABAergic interneurons of PTSD rats. In conclusion, this study provided evidence that the loss of GABAergic interneuron phenotype in CA1 may contribute to contextual fear generalization in PTSD. The PERK pathway is involved in the GABAergic interneuron injury of PTSD rats and modulating it can protect GABAergic interneurons and constrain contextual fear generalization.

Causally Probing the Role of the Hippocampus in Fear Discrimination: A Precision Functional Mapping-Guided, Transcranial Magnetic Stimulation Study in Participants With Posttraumatic Stress Symptoms.

Background: Fear overgeneralization is a promising pathogenic mechanism of clinical anxiety. A dominant model posits that hippocampal pattern separation failures drive overgeneralization. Hippocampal network-targeted transcranial magnetic stimulation (HNT-TMS) has been shown to strengthen hippocampal-dependent learning/memory processes. However, no study has examined whether HNT-TMS can alter fear learning/memory. Methods: Continuous theta burst stimulation was delivered to individualized left posterior parietal stimulation sites derived via seed-based connectivity, precision functional mapping, and electric field modeling methods. A vertex control site was also stimulated in a within-participant, randomized controlled design. Continuous theta burst stimulation was delivered prior to 2 visual discrimination tasks (1 fear based, 1 neutral). Multilevel models were used to model and test data. Participants were undergraduates with posttraumatic stress symptoms (final n = 25). Results: Main analyses did not indicate that HNT-TMS strengthened discrimination. However, multilevel interaction analyses revealed that HNT-TMS strengthened fear discrimination in participants with lower fear sensitization (indexed by responses to a control stimulus with no similarity to the conditioned fear cue) across multiple indices (anxiety ratings: ß = 0.10, 95% CI, 0.04 to 0.17, p = .001; risk ratings: ß = 0.07, 95% CI, 0.00 to 0.13, p = .037). Conclusions: Overgeneralization is an associative process that reflects deficient discrimination of the fear cue from similar cues. In contrast, sensitization reflects nonassociative responding unrelated to fear cue similarity. Our results suggest that HNT-TMS may selectively sharpen fear discrimination when associative response patterns, which putatively implicate the hippocampus, are more strongly engaged.

Fear overgeneralization is a promising pathogenic mechanism of clinical anxiety that is thought to be driven by deficient hippocampal discrimination. Using hippocampal network­targeted transcranial magnetic stimulation (HNT-TMS) in healthy participants with symptoms of posttraumatic stress, Webler et al. report that HNT-TMS did not strengthen discrimination overall, but it did strengthen fear discrimination in participants with lower fear sensitization. Sensitization reflects nonassociative fear responding unrelated to fear cue similarity and therefore is not expected to engage the hippocampal discrimination function. These results suggest that HNT-TMS may selectively sharpen fear discrimination when the hippocampal discrimination function is more strongly engaged.

MedicalCLIP: Anomaly-Detection Domain Generalization with Asymmetric Constraints.

Medical data have unique specificity and professionalism, requiring substantial domain expertise for their annotation. Precise data annotation is essential for anomaly-detection tasks, making the training process complex. Domain generalization (DG) is an important approach to enhancing medical image anomaly detection (AD). This paper introduces a novel multimodal anomaly-detection framework called MedicalCLIP. MedicalCLIP utilizes multimodal data in anomaly-detection tasks and establishes irregular constraints within modalities for images and text. The key to MedicalCLIP lies in learning intramodal detailed representations, which are combined with text semantic-guided cross-modal contrastive learning, allowing the model to focus on semantic information while capturing more detailed information, thus achieving more fine-grained anomaly detection. MedicalCLIP relies on GPT prompts to generate text, reducing the demand for professional descriptions of medical data. Text construction for medical data helps to improve the generalization ability of multimodal models for anomaly-detection tasks. Additionally, during the text-image contrast-enhancement process, the model's ability to select and extract information from image data is improved. Through hierarchical contrastive loss, fine-grained representations are achieved in the image-representation process. MedicalCLIP has been validated on various medical datasets, showing commendable domain generalization performance in medical-data anomaly detection. Improvements were observed in both anomaly classification and segmentation metrics. In the anomaly classification (AC) task involving brain data, the method demonstrated a 2.81 enhancement in performance over the best existing approach.