Emergence of Emotion Selectivity in Deep Neural Networks Trained to Recognize Visual Objects.

Recent neuroimaging studies have shown that the visual cortex plays an important role in representing the affective significance of visual input. The origin of these affect-specific visual representations is debated: they are intrinsic to the visual system versus they arise through reentry from frontal emotion processing structures such as the amygdala. We examined this problem by combining convolutional neural network (CNN) models of the human ventral visual cortex pre-trained on ImageNet with two datasets of affective images. Our results show that in all layers of the CNN models, there were artificial neurons that responded consistently and selectively to neutral, pleasant, or unpleasant images and lesioning these neurons by setting their output to zero or enhancing these neurons by increasing their gain led to decreased or increased emotion recognition performance respectively. These results support the idea that the visual system may have the intrinsic ability to represent the affective significance of visual input and suggest that CNNs offer a fruitful platform for testing neuroscientific theories.

A systems identification approach using Bayes factors to deconstruct the brain bases of emotion regulation.

Cognitive reappraisal is fundamental to cognitive therapies and everyday emotion regulation. Analyses using Bayes factors and an axiomatic systems identification approach identified four reappraisal-related components encompassing distributed neural activity patterns across two independent functional magnetic resonance imaging (fMRI) studies (n = 182 and n = 176): (1) an anterior prefrontal system selectively involved in cognitive reappraisal; (2) a fronto-parietal-insular system engaged by both reappraisal and emotion generation, demonstrating a general role in appraisal; (3) a largely subcortical system activated during negative emotion generation but unaffected by reappraisal, including amygdala, hypothalamus and periaqueductal gray; and (4) a posterior cortical system of negative emotion-related regions downregulated by reappraisal. These systems covaried with individual differences in reappraisal success and were differentially related to neurotransmitter binding maps, implicating cannabinoid and serotonin systems in reappraisal. These findings challenge 'limbic'-centric models of reappraisal and provide new systems-level targets for assessing and enhancing emotion regulation.

Emergence of Emotion Selectivity in Deep Neural Networks Trained to Recognize Visual Objects.

Recent neuroimaging studies have shown that the visual cortex plays an important role in representing the affective significance of visual input. The origin of these affect-specific visual representations is debated: they are intrinsic to the visual system versus they arise through reentry from frontal emotion processing structures such as the amygdala. We examined this problem by combining convolutional neural network (CNN) models of the human ventral visual cortex pre-trained on ImageNet with two datasets of affective images. Our results show that (1) in all layers of the CNN models, there were artificial neurons that responded consistently and selectively to neutral, pleasant, or unpleasant images and (2) lesioning these neurons by setting their output to 0 or enhancing these neurons by increasing their gain led to decreased or increased emotion recognition performance respectively. These results support the idea that the visual system may have the intrinsic ability to represent the affective significance of visual input and suggest that CNNs offer a fruitful platform for testing neuroscientific theories.

Decoding fMRI data with support vector machines and deep neural networks.

BACKGROUND: Multivoxel pattern analysis (MVPA) examines fMRI activation patterns associated with different cognitive conditions. Support vector machines (SVMs) are the predominant method in MVPA. While SVM is intuitive and easy to apply, it is mainly suitable for analyzing data that are linearly separable. Convolutional neural networks (CNNs) are known to have the ability to approximate nonlinear relationships. Applications of CNN to fMRI data are beginning to appear with increasing frequency, but our understanding of the similarities and differences between CNN models and SVM models is limited. NEW METHOD: We compared the two methods when they are applied to the same datasets. Two datasets were considered: (1) fMRI data collected from participants during a cued visual spatial attention task and (2) fMRI data collected from participants viewing natural images containing varying degrees of affective content. RESULTS: We found that (1) both SVM and CNN are able to achieve above-chance decoding accuracies for attention control and emotion processing in both the primary visual cortex and the whole brain, (2) the CNN decoding accuracies are consistently higher than that of the SVM, (3) the SVM and CNN decoding accuracies are generally not correlated, and (4) the heatmaps derived from SVM and CNN are not significantly overlapping. COMPARISON WITH EXISTING METHODS: By comparing SVM and CNN we pointed out the similarities and differences between the two methods. CONCLUSIONS: SVM and CNN rely on different neural features for classification. Applying both to the same data may yield a more comprehensive understanding of neuroimaging data.

Decoding fMRI Data: A Comparison Between Support Vector Machines and Deep Neural Networks.

Multivoxel pattern analysis (MVPA) examines the differences in fMRI activation patterns associated with different cognitive conditions and provides information not possible with the conventional univariate analysis. Support vector machines (SVMs) are the predominant machine learning method in MVPA. SVMs are intuitive and easy to apply. The limitation is that it is a linear method and mainly suitable for analyzing data that are linearly separable. Convolutional neural networks (CNNs), a class of AI models originally developed for object recognition, are known to have the ability to approximate nonlinear relationships. CNNs are rapidly becoming an alternative to SVMs. The purpose of this study is to compare the two methods when they are applied to the same datasets. Two datasets were considered: (1) fMRI data collected from participants during a cued visual spatial attention task (the attention dataset) and (2) fMRI data collected from participants viewing natural images containing varying degrees of affective content (the emotion dataset). We found that (1) both SVM and CNN are able to achieve above chance level decoding accuracies for attention control and emotion processing in both the primary visual cortex and the whole brain with, (2) the CNN decoding accuracies are consistently higher than that of the SVM, (3) the SVM and CNN decoding accuracies are generally not correlated with each other, and (4) the heatmaps derived from SVM and CNN are not significantly overlapping. These results suggest that (1) there are both linearly separable features and nonlinearly separable features in fMRI data that distinguish cognitive conditions and (2) applying both SVM and CNN to the same data may yield a more comprehensive understanding of neuroimaging data. Key points: We compared the performance and characteristics of SVM and CNN, two major methods in MVPA analysis of neuroimaging data, by applying them to the same two fMRI datasets.Both SVM and CNN achieved decoding accuracies above chance level for both datasets in the chosen ROIs and the CNN decoding accuracies were consistently higher than those of SVM.The heatmaps derived from SVM and CNN, which assess the contribution of voxels or brain regions to MVPA decoding performance, showed no significant overlap, providing evidence that the two methods depend on distinct brain activity patterns for decoding cognitive conditions.

Imaging the neural substrate of trigeminal neuralgia pain using deep learning.

Trigeminal neuralgia (TN) is a severe and disabling facial pain condition and is characterized by intermittent, severe, electric shock-like pain in one (or more) trigeminal subdivisions. This pain can be triggered by an innocuous stimulus or can be spontaneous. Presently available therapies for TN include both surgical and pharmacological management; however, the lack of a known etiology for TN contributes to the unpredictable response to treatment and the variability in long-term clinical outcomes. Given this, a range of peripheral and central mechanisms underlying TN pain remain to be understood. We acquired functional magnetic resonance imaging (fMRI) data from TN patients who (1) rested comfortably in the scanner during a resting state session and (2) rated their pain levels in real time using a calibrated tracking ball-controlled scale in a pain tracking session. Following data acquisition, the data was analyzed using the conventional correlation analysis and two artificial intelligence (AI)-inspired deep learning methods: convolutional neural network (CNN) and graph convolutional neural network (GCNN). Each of the three methods yielded a set of brain regions related to the generation and perception of pain in TN. There were 6 regions that were identified by all three methods, including the superior temporal cortex, the insula, the fusiform, the precentral gyrus, the superior frontal gyrus, and the supramarginal gyrus. Additionally, 17 regions, including dorsal anterior cingulate cortex (dACC) and the thalamus, were identified by at least two of the three methods. Collectively, these 23 regions are taken to represent signature centers of TN pain and provide target areas for future studies seeking to understand the central mechanisms of TN.

Aftereffects of frontoparietal theta tACS on verbal working memory: Behavioral and neurophysiological analysis.

Verbal working memory is supported by a left-lateralized frontoparietal theta oscillatory (4-8 Hz) network. We tested whether stimulating the left frontoparietal network at theta frequency during verbal working memory can produce observable after-stimulation effects in behavior and neurophysiology. Weak theta-band alternating electric currents were delivered via two 4 × 1 HD electrode arrays centered at F3 and P3. Three stimulation configurations, including in-phase, anti-phase, or sham, were tested on three different days in a cross-over (within-subject) design. On each test day, the subject underwent three experimental sessions: pre-, during- and post-stimulation sessions. In all sessions, the subject performed a Sternberg verbal working memory task with three levels of memory load (load 2, 4 and 6), imposing three levels of cognitive demand. Analyzing behavioral and EEG data from the post-stimulation session, we report two main observations. First, in-phase stimulation improved task performance in subjects with higher working memory capacity (WMC) under higher memory load (load 6). Second, in-phase stimulation enhanced frontoparietal theta synchrony during working memory retention in subjects with higher WMC under higher memory loads (load 4 and load 6), and the enhanced frontoparietal theta synchronization is mainly driven by enhanced frontal→parietal theta Granger causality. These observations suggest that (1) in-phase theta transcranial alternating current stimulation (tACS) during verbal working memory can result in observable behavioral and neurophysiological consequences post stimulation, (2) the short-term plasticity effects are state- and individual-dependent, and (3) enhanced executive control underlies improved behavioral performance.

Decoding the temporal dynamics of affective scene processing.

Natural images containing affective scenes are used extensively to investigate the neural mechanisms of visual emotion processing. Functional fMRI studies have shown that these images activate a large-scale distributed brain network that encompasses areas in visual, temporal, and frontal cortices. The underlying spatial and temporal dynamics, however, remain to be better characterized. We recorded simultaneous EEG-fMRI data while participants passively viewed affective images from the International Affective Picture System (IAPS). Applying multivariate pattern analysis to decode EEG data, and representational similarity analysis to fuse EEG data with simultaneously recorded fMRI data, we found that: (1) ∼80 ms after picture onset, perceptual processing of complex visual scenes began in early visual cortex, proceeding to ventral visual cortex at ∼100 ms, (2) between ∼200 and ∼300 ms (pleasant pictures: ∼200 ms; unpleasant pictures: ∼260 ms), affect-specific neural representations began to form, supported mainly by areas in occipital and temporal cortices, and (3) affect-specific neural representations were stable, lasting up to ∼2 s, and exhibited temporally generalizable activity patterns. These results suggest that affective scene representations in the brain are formed temporally in a valence-dependent manner and may be sustained by recurrent neural interactions among distributed brain areas.

Decoding Neural Representations of Affective Scenes in Retinotopic Visual Cortex.

The perception of opportunities and threats in complex visual scenes represents one of the main functions of the human visual system. The underlying neurophysiology is often studied by having observers view pictures varying in affective content. It has been shown that viewing emotionally engaging, compared with neutral, pictures (1) heightens blood flow in limbic, frontoparietal, and anterior visual structures and (2) enhances the late positive event-related potential (LPP). The role of retinotopic visual cortex in this process has, however, been contentious, with competing theories predicting the presence versus absence of emotion-specific signals in retinotopic visual areas. Recording simultaneous electroencephalography-functional magnetic resonance imaging while observers viewed pleasant, unpleasant, and neutral affective pictures, and applying multivariate pattern analysis, we found that (1) unpleasant versus neutral and pleasant versus neutral decoding accuracy were well above chance level in retinotopic visual areas, (2) decoding accuracy in ventral visual cortex (VVC), but not in early or dorsal visual cortex, was correlated with LPP, and (3) effective connectivity from amygdala to VVC predicted unpleasant versus neutral decoding accuracy, whereas effective connectivity from ventral frontal cortex to VVC predicted pleasant versus neutral decoding accuracy. These results suggest that affective scenes evoke valence-specific neural representations in retinotopic visual cortex and that these representations are influenced by reentry signals from anterior brain regions.

An experimental model of the epithelial to mesenchymal transition and pro-fibrogenesis in urothelial cells related to bladder pain syndrome/interstitial cystitis.

BACKGROUND: Suitable in vitro models are needed to investigate urothelial epithelial to mesenchymal transition (EMT) and pro-fibrogenesis phenotype in bladder pain syndrome/interstitial cystitis (BPS/IC). This study is to establish a novel experimental BPS/IC cell model and explore how different concentrations of tumor necrosis factor (TNF)-α influence the EMT and pro-fibrogenesis phenotype of urothelial cells. METHODS: SV-HUC-1 urothelial cells were cultured with 2, 10, or 50 ng/mL TNF-α to mimic chronic inflammatory stimulation. The EMT and pro-fibrogenesis phenotype, including production of collagen I and pro-fibrosis cytokines, were estimated after 72 h of culture. RESULTS: The bladder urothelial cells of BPS/IC exhibited upregulated vimentin, TNF-α and TNF receptor, downregulated E-cadherin, and increased collagen I. Higher concentrations of TNF-α (10 and 50 ng/mL) produced an obvious mesenchymal morphology, enhanced invasion and migratory capacity, increased expression of vimentin, and decreased expression of E-cadherin. Collagen I was increased in cells treated with 2 and 10 ng/mL TNF-α after 72 h. Secretion of interleukin (IL)-6 and IL-8 was promoted with 10 and 50 ng/mL TNF-α, while that of IL-1ß or transforming growth factor-ß was unaffected. Slug and Smad2 were upregulated by TNF-α after 72 h. The Smad pathway was activated most strongly with 10 ng/mL TNF-α and Slug pathway activation was positively correlated with the concentration of TNF-α. CONCLUSIONS: Sustained 10 ng/mL TNF-α stimulation induced the EMT and pro-fibrogenesis phenotype resembling BPS/IC in SV-HUC-1 cells. Minor inflammatory stimulation induced the pro-fibrogenesis phenotype while severe inflammatory stimulation was more likely to produce significant EMT changes. Different degrees of activation of the Slug and Smad pathways may underlie this phenomenon.

Fear conditioning prompts sparser representations of conditioned threat in primary visual cortex.

Repeated exposure to threatening stimuli alters sensory responses. We investigated the underlying neural mechanism by re-analyzing previously published simultaneous electroencephalogram-functional magnetic resonance imaging (EEG-fMRI) data from humans viewing oriented gratings during Pavlovian fear conditioning. In acquisition, one grating (CS+) was paired with a noxious noise, the unconditioned stimulus (US). The other grating (CS-) was never paired with the US. In habituation, which preceded acquisition, and in extinction, the same two gratings were presented without US. Using fMRI multivoxel patterns in primary visual cortex during habituation as reference, we found that during acquisition, aversive learning selectively prompted systematic changes in multivoxel patterns evoked by CS+. Specifically, CS+ evoked voxel patterns in V1 became sparser as aversive learning progressed, and the sparsified pattern appeared to be preserved in extinction. Concomitant with the voxel pattern changes, occipital alpha oscillations were increasingly more desynchronized during CS+ (but not CS-) trials. Across acquisition trials, the rate of change in CS+-related alpha desynchronization was correlated with the rate of change in multivoxel pattern representations of CS+. Furthermore, alpha oscillations co-varied with blood-oxygen-level-dependent (BOLD) data in the ventral attention network, but not with BOLD in the amygdala. Thus, fear conditioning prompts persistent sparsification of voxel patterns evoked by threat, likely mediated by attention-related mechanisms.

Decoding attention control and selection in visual spatial attention.

Event-related potentials (ERPs) are used extensively to investigate the neural mechanisms of attention control and selection. The univariate ERP approach, however, has left important questions inadequately answered. We addressed two questions by applying multivariate pattern classification to multichannel ERPs in two cued visual spatial attention experiments (N = 56): (a) impact of cueing strategies (instructional vs. probabilistic) on attention control and selection and (b) neural and behavioral effects of individual differences. Following cue onset, the decoding accuracy (cue left vs. cue right) began to rise above chance level earlier and remained higher in instructional cueing (~80 ms) than in probabilistic cueing (~160 ms), suggesting that unilateral attention focus leads to earlier and more distinct formation of the attention control set. A similar temporal sequence was also found for target-related processing (cued target vs. uncued target), suggesting earlier and stronger attention selection under instructional cueing. Across the two experiments: (a) individuals with higher cue-related decoding accuracy showed higher magnitude of attentional modulation of target-evoked N1 amplitude, suggesting that better formation of anticipatory attentional state leads to stronger modulation of target processing, and (b) individuals with higher target-related decoding accuracy showed faster reaction times (or larger cueing effects), suggesting that stronger selection of task-relevant information leads to better behavioral performance. Taken together, multichannel ERPs combined with machine learning decoding yields new insights into attention control and selection that complement the univariate ERP approach, and along with the univariate ERP approach, provides a more comprehensive methodology to the study of visual spatial attention.

Expression of Peroxiredoxin-6 Gene in Patients with Acute Myeloid Leukemia and Its Clinical Significance / 中国实验血液学杂志

OBJECTIVE@#To study the expression of Peroxiredoxin-6 (Prdx6) gene in elderly patients with acute myeloid leukemia (AML) and its clinical significance.@*METHODS@#The expression level of Prdx6 in bone marrow cells of 33 cases of AML, 8 cases of CML and 11 cases of other blood diseases was detected by PCR. The correlation of the abnormal expression of Prdx6 with patient age and blood routine parameters was further analyzed.@*RESULTS@#the expression level of Prdx6 in elderly patients with AML (≥60 years) was significantly lower than that in younger patients (＜60 years) (P＜0.05); the expression level of Prdx6 in low WBC (≤1×10/L) group was lower than that in medium WBC (1-10×10/L) group or high WBC (＞10×10/L) group (P＜0.05); the proportion of WBC count (≤1×10/L) in elderly patients with AML reached 38.5%, which was significantly higher than that in younger patients (5%) (P＜0.05); the overall survival (OS) rate of elderly patients was lower than that of younger patients (P＜0.05).@*CONCLUSION@#The expression of Prdx6 in elderly patients with AML is low, moreover, it relates with low value of WBC in peripheral blood, suggesting that it may be one of poor prognostic factors for the elderly patients with AML.

Working Memory Capacity Is Negatively Associated with Memory Load Modulation of Alpha Oscillations in Retention of Verbal Working Memory.

Working memory capacity (WMC) measures the amount of information that can be maintained online in the face of distraction. Past work has shown that the efficiency with which the frontostriatal circuit filters out task-irrelevant distracting information is positively correlated with WMC. Recent work has demonstrated a role of posterior alpha oscillations (8-13 Hz) in providing a sensory gating mechanism. We investigated the relationship between memory load modulation of alpha power and WMC in two verbal working memory experiments. In both experiments, we found that posterior alpha power increased with memory load during memory, in agreement with previous reports. Across individuals, the degree of alpha power modulation by memory load was negatively associated with WMC, namely, the higher the WMC, the less alpha power was modulated by memory load. After the administration of topiramate, a drug known to affect alpha oscillations and have a negative impact on working memory function, the negative correlation between memory load modulation of alpha power and WMC was no longer statistically significant but still somewhat detectable. These results suggest that (1) individuals with low WMC demonstrate stronger alpha power modulation by memory load, reflecting possibly an increased reliance on sensory gating to suppress task-irrelevant information in these individuals, in contrast to their high WMC counterparts who rely more on frontal areas to perform this function and (2) this negative association between memory load modulation of alpha oscillations and WMC is vulnerable to drug-related cognitive disruption.

The Effects of Neurokinin-1 Receptor Antagonist in an Experimental Autoimmune Cystitis Model Resembling Bladder Pain Syndrome/Interstitial Cystitis.

To identify the effects of the neurokinin-1 receptor (NK1R) antagonist aprepitant in treating pelvic pain, micturition symptoms, and bladder inflammation in mice with experimental autoimmune cystitis (EAC) similar to bladder pain syndrome/interstitial cystitis (BPS/IC). Female C57BL/6 mice were divided into the following three groups: normal control, EAC, and EAC plus aprepitant. EAC was induced in mice by duplicate immunization with bladder homogenate. In the EAC model group, EAC mice were given PBS by gavage once a day during the fourth week. In the EAC plus aprepitant group, aprepitant was administered instead of PBS in the same way. After 4 weeks, pelvic pain threshold and urination habits of mice were analyzed, as well as the bladder weight to body weight ratio, and histologic assessment of the expression of IL-1ß, TNF-α, intercellular adhesion molecule 1 (ICAM-1), and NK1R in bladder tissue. EAC mice mimicked the phenotype and pathophysiologic lesions of BPS/IC well. Compared to PBS-treated EAC mice, the mice treated with aprepitant exhibited higher pain threshold values, less number of total urine spots or small urine spots, lower bladder weight to body weight ratio, and reduced bladder inflammation with less mast cell infiltration and decreased expressions of IL-1ß, TNF-α, and ICAM-1 in bladder tissue. There was no difference in NK1R expression in bladders treated with or without aprepitant. The NK1R antagonist aprepitant relieved pelvic pain, urinary symptoms, and bladder inflammation in EAC mice. This indicated that NK1R may be a novel therapeutic target in BPS/IC treatment.

Establishment of a Novel Autoimmune Experimental Model of Bladder Pain Syndrome/Interstitial Cystitis in C57BL/6 Mice.

The aim of this study is to identify whether vaccinating twice with bladder homogenate can establish a new model of experimental autoimmune cystitis (EAC) in C57BL/6 strain mice. C57BL/6 mice were vaccinated with bladder homogenate in complete Freund's adjuvant (CFA) and boost immunized with bladder homogenate in incomplete Freund's adjuvant (IFA) after 2 weeks were used as the EAC model. Mice immunized with phosphate-buffered saline (PBS) in CFA or IFA were used as the control. Micturition habits and suprapubic-pelvic pain threshold were measured 4 weeks after primary immunization. Bladder to body weight ratios and expression of inflammatory cytokines and neurokinin 1 receptor (NK1R) were then examined. Histologic and immunohistochemical examination of the bladder was carried out, and IL-1ß, IFN-γ, and TNF-α production by the kidneys, liver, and lungs was also tested. Double-immunized mice were extensively sensitive to pressure applied on the pelvic area (P < 0.001). Compared to single-immunized mice or controls, double-immunized mice showed more micturition frequency, lower urine output per micturition, higher bladder to body weight ratio, and significant elevation in the expression of inflammatory cytokines, including IL-1ß, IL-4, IL-6, IL-10, IFN-γ, and TNF-α (all P < 0.05). NK1R gene expression was significantly increased in double-immunized mice compared to the other three groups (P < 0.001). A nonspecific immune response occurred in the liver but was much weaker than bladder inflammation. Our dual immunization EAC model in C57BL/6 mice can effectively mimic the symptoms and pathophysiologic characteristics of BPS/IC and thus can be widely used to investigate the pathogenesis and therapeutic strategies of BPS/IC.