Effect Of Bias Research Articles

The transport properties and new device design: A case of doped armchair blue phosphorene nanoribbons

We design two p-n nanojunctions based on S- and Si- atoms doped armchair blue phosphorene nanoribbons (aBPNRs) including two semi-infinite electrodes and a scattering region and investigate their electronic and transport properties. Our calculations are based on density functional theory incorporated non-equilibrium Green's function approach. In impure aBPNRs, S/Si atoms substituted doping could greatly enhance the conductivity, and the S/Si doped aBPNRs show metallic properties. Based on the doped aBPNRs, devies D1 and D2 are constructed where the scattering region of D1 is formed by direct expansion of two electrodes, while the scattering region of D2 includes two undoped unit cells as buffer. The transport calculations show that both of D1 and D2 show excellent negative differential resistance (NDR) effect at low bias and significant rectification effects at high bias. Moreover, whether there is buffer in the scattering region has a great influence on the magnitude of current of the devices. Although the current of the device D1 without buffer is generally higher than that of the device D2, the NDR and rectification effects of D2 are better than D1 in terms of peak-to-valley ratio and rectification rate. These transport behaviors can be explained by the evolution of the transmission spectra, frontier molecular orbital and the symmetry matching between the band structures of the electrodes. This indicates that aBPNRs are a promising candidate for the future application of multi-functional electronic devices.

Geographic bias effects on interpretations of secular trends of Hf isotope times series in zircons

The analysis of εHf(t) time series data from zircon reveals notable discrepancies based on sample type (igneous versus detrital), statistical weighting methodology, and geographic sampling bias. These differences warrant caution when interpreting data in the context of tectonic settings and the history of supercontinents. In terms of tectonic setting, accretionary orogens dominate in both sedimentary basins that host detrital zircons and in igneous zircon sources. Because of differences between the various time series, emphasis in this study is on peaks, valleys and secular trends and not on absolute εHf(t) values. Specifically, the igneous time series for εHf(t) in zircons shows more peaks and valleys than corresponding detrital time series for both weighted and unweighted data (weighting corrects for disproportionate geographic sampling). Also, sample-based (each sample considered separately) and site-based (samples grouped by geographic location and age) results align closely to the igneous time series, whereas the site-based detrital series displays more negative εHf(t) values. Regardless of the type of time series, the failure to compensate for disproportionate geographic sampling increases the prospects of producing an unrepresentative time-series. Nine zircon age peaks (both detrital and igneous) have corresponding εHf(t) peaks (3200, 2700, 2500, 2150, 1500, 1100, 750 Ma) and two have corresponding age valleys (1800–2000, 550 Ma). With exception of a geographically widespread 1500 Ma peak, most of the εHf(t) peaks and valleys are controlled by specific geographic regions and are likely not be global in extent.Two distinct periods (200–0 and 1800–1600 Ma) display εHf(t) signatures that rise steadily for 100–200 Myr, coinciding with the final stages of supercontinent assembly and the transition to the retreat of exterior orogens. An εHf(t) peak at 750 Ma and a high at 1400–1100 Ma partly overlap with supercontinent breakup and valleys at 550 Ma and 900 Ma with supercontinent assembly. A large εHf(t) valley at 2000–1800 Ma corresponds with the onset of craton collisions that led to the final assembly of Columbia at 1800–1600 Ma. The steep rise in εHf(t) in the last 200 Myr in both igneous and detrital zircons is controlled by sites in Circum-Pacific orogens in North and South America and Southwest Asia, and it parallels the breakup of Pangea. The general increase in zircon εHf(t) in the last 500 Myr in both detrital and igneous data reflects an increase in the proportion of isotopically juvenile components in accretionary orogens.

Lessons in clinical reasoning- pitfalls, myths, and pearls: a case of persistent dysphagia and patient partnership.

Diagnostic excellence underscores the patient-centered diagnosis and patient engagement in the diagnostic process. In contrast to a patient-centered diagnosis, adoctor-centered diagnosis with a lack of patient engagement may inhibit the diagnostic process due to the lack ofresponsibility, disrupted information, and increased effect of cognitive biases, particularly in a situation where multiple physicians are involved. In this paper, we suggest a promising idea to enhance patient engagement in the diagnostic process by using written information by a patient about their perspective and experience, which canfill the gaps needed for diagnosis that doctors cannot find alone. A 38-year-old woman developed chest pain, which gradually worsened during the following two years. For two years, she was evaluated in multiple departments; however, no definitive diagnosis was made, and her condition did not improve. During this evaluation, she searched her symptoms and image findings online. Shereached a possible diagnosis of 'esophageal achalasia.' Still, she could not tell her concerns to any physicians because she felt that her concerns were not correctly recognized, although she showed her notes that her symptoms were recorded. She finally consulted the department of internal medicine, where her notes and previous test results were thoroughly reviewed. The final diagnosis of esophageal achalasia was confirmed. Doctors must organize an environment where patients can freely express their thoughts, emotions, and ideas regarding their diagnosis. Cogenerating visit notes using patient input through written communication can be apromising idea to facilitate patient engagement in the diagnostic process.

Impact of psychological factors on investment decisions in Nepalese share market: A mediating role of financial literacy

Psychological factors such as emotional reactions, cognitive biases, and herd behavior influence investment decisions because they shape investor behavior, drive market dynamics, and affect rational decision-making. Similarly, financial literacy improves investment decisions by facilitating informed choices, minimizing biases, enhancing risk management, and promoting long-term financial planning. This study aims to examine the influence of psychological factors on investment decisions in the Nepalese share market, emphasizing the mediating role of financial literacy. Smart PLS 4.0 was used to analyze the structural relationships within the proposed theoretical model. Data were collected from the primary source using a structured questionnaire administered through a random sampling technique. The respondents included 410 active individual investors from the Nepal Stock Exchange (NEPSE). The study's findings reveal that psychological factors have a positive and significant effect on investment decisions among investors in the Nepalese stock market. Furthermore, the study revealed that financial literacy mediates the relationship between psychological factors and investment decisions by enhancing individuals' understanding and confidence, leading to more informed and rational investment choices. The results highlight the critical role of financial literacy in investment decisions in the share market. The findings indicate that investors with higher financial literacy levels are better equipped to mitigate the adverse effects of psychological biases, leading to more rational and informed investment decisions. By understanding the interplay between psychological factors and financial literacy, policymakers and financial institutions can develop targeted strategies to foster a more robust and resilient financial market in developing economies such as Nepal.

Assessing credibility in eWOM: a meta-analysis using the heuristic-systematic model

PurposeThe current research delves into how different cues in messages (such as argument quality, usefulness and informativeness) and cues related to the source (such as credibility and expertise) contribute to the perceived credibility of electronic word-of-mouth (eWOM). The investigation also explores whether source cues influence the overall impact of message cues.Design/methodology/approachThis study synthesizes findings from 100 previous empirical works through the application of meta-analysis.FindingsThe outcomes affirm the presence of both systematic and heuristic processing, the additive effects of both message and source cues and the bias effects of source cues. Moreover, the study identifies a connection between eWOM credibility and behavioral intention. Expanding on this, the research discovers that users’ tendency to avoid uncertainty moderates the impact of message and source cues on their judgment of eWoM credibility.Originality/valueThe research contributes to the eWOM literature by providing a heuristic-systematic model of eWoM credibility judgments. It provides new insights for online sellers, who can benefit from eWoM by fostering potential buyers' behavioral intention to purchase.

Neural network reconstruction of density and velocity fields from the 2MASS Redshift Survey

Aims. Our aim is to reconstruct the 3D matter density and peculiar velocity fields in the local Universe up to a distance of 200 h−1 Mpc from the Two-Micron All-Sky Redshift Survey (2MRS) using a neural network (NN). Methods. We employed an NN with a U-net autoencoder architecture and a weighted mean squared error loss function trained separately to output either the density or velocity field for a given input grid of galaxy number counts. The NN was trained on mocks derived from the Quijote N-body simulations, incorporating redshift-space distortions (RSDs), galaxy bias, and selection effects closely mimicking the characteristics of 2MRS. The trained NN was benchmarked against a standard Wiener filter (WF) on a validation set of mocks before applying it to 2MRS. Results. The NN reconstructions effectively approximate the mean posterior estimate of the true density and velocity fields conditioned on the observations. They consistently outperform the WF in terms of reconstruction accuracy and effectively capture the nonlinear relation between velocity and density. The NN-reconstructed bulk flow of the total survey volume exhibits a significant correlation with the true mock bulk flow, demonstrating that the NN is sensitive to information on “super-survey” scales encoded in the RSDs. When applied to 2MRS, the NN successfully recovers the main known clusters, some of which are partially in the Zone of Avoidance. The reconstructed bulk flows in spheres of different radii less than 100 h−1 Mpc are in good agreement with a previous 2MRS analysis that required an additional external bulk flow component inferred from directly observed peculiar velocities. The NN-reconstructed peculiar velocity of the Local Group closely matches the observed Cosmic Microwave Background dipole in amplitude and Galactic latitude, and only deviates by 18° in longitude. The NN-reconstructed fields are publicly available.

Opposite-Direction Spatial Working Memory Biases in People With Schizophrenia and Healthy Control Participants

BackgroundPeople with schizophrenia (PSZ) show impaired accuracy in spatial working memory (sWM), which is thought to reflect abnormalities in the sustained firing of feature selective neurons that are critical for successful encoding and maintenance processes. Recent research has documented a new source of variance in the accuracy of sWM: In healthy adults, sWM representations are unconsciously biased by previous trials such that current-trial responses are attracted to previous-trial responses (serial dependence). This opens a new window to examine how schizophrenia impacts both the sustained neural firing representing the current-trial target and the longer-term synaptic plasticity that stores previous-trial information. MethodsWe examined response accuracy in a single-item sWM test with delay intervals of 0, 2, 4, or 8 seconds in 41 PSZ and 32 demographically similar healthy control participants. Our main dependent variable was the bias index, which quantifies the extent to which the current-trial responses were biased toward or away from the previous-trial target. ResultsPSZ showed opposite-direction serial dependence bias effects: Healthy control participants showed an attractive bias that increased over increasing delays whereas PSZ showed a repulsion bias that increased over delays. In PSZ, the magnitude of the repulsion bias negatively correlated with broad measures of cognitive ability and WM capacity. ConclusionsPSZ show opposite-direction effects of previous trials on WM. Such qualitatively distinct differences in performance are extremely rare in psychopathology and may index a fundamental alteration in neural processing that could serve as a valuable biomarker for pathophysiology and treatment development research.

Exchange Bias Effects in Bismuth Ferrite Nanostructures Produced by Pulsed Laser Deposition

Exchange Bias Effects in Bismuth Ferrite Nanostructures Produced by Pulsed Laser Deposition

Exchange bias and topological Hall effect of Fe and Co intercalated NbS2 single crystals

In recent years, the topological Hall effect generated by noncoplanar magnetic structures has been studied extensively. Some two-dimensional chalcogenides with 3d transition metal intercalations also exhibit similar properties. In this study, we investigated the crystalline structure and the magnetic and transport properties of Fe and Co codoped NbS2 single crystals. The structural results indicate disorder between the Fe and Co atoms within the interlayers of NbS2. Magnetic measurements showed that the vertical exchange bias effect appeared below the Néel temperature (TN), with a maximum value of approximately 2.5 mμB/f.u. at 2 K, which can be ascribed to the appearance of a spin-glass state. Additionally, accompanying the antiferromagnetic phase transition, nontrivial electrical transport properties were observed. Below TN, the magnetoresistance became positive and exhibited an initial increase, followed by a decrease with decreasing temperature. The Hall resistivity shows a hump-like curve near TN, indicating a topological Hall effect. This behavior is related to fluctuations in the spin chirality, which affects the scattering of charge carriers. Based on the correlation between the magnetoresistance and Hall resistivity responses, it is believed that the magnetic moments of the doped Fe and Co atoms in a single crystal compete with each other near the Néel temperature, resulting in complex magnetic structures such as noncoplanar and noncollinear arrangements. Such a two-dimensional antiferromagnetic material system provides an ideal platform for studying unconventional transport mechanisms.

Effect of Gas Dispersion Properties and Bias in Scheelite Column Flotation

Effect of Gas Dispersion Properties and Bias in Scheelite Column Flotation

M[formula omitted]ixup: A multi-modal data augmentation approach for image captioning

Despite the great success, most models in image captioning (IC) are still stuck in the dilemma of generating simple and non-discriminative captions. In this paper, we study this problem from the perspective of data augmentation and propose a novel method called Multi-modal Mixup (M3ixup). Compared with the original Mixup strategy designed for image classification, the proposed M3ixup has three novel designs to mix IC samples from the aspects of visual features, sentence embeddings and loss values, respectively. In practice, M3ixup can not only enrich the diversity of IC training data, but also enforce the model to focus more on visual information for captioning, thereby alleviating the negative effect of dataset bias and addressing the issue of simple captioning. To validate M3ixup, we apply it to three baseline models and conduct extensive experiments on MS COCO. The experimental results demonstrate that our proposed M3ixup can not only improve the discriminability and quality of generated captions, but also help the baseline models obtain obvious performance gains, i.e., improving the CIDEr scores of the state-of-the-art model from 133.8 to 135.3 on off-line testing and 135.4 to 137.1 on online testing.

XSIM: A structural similarity index measure optimized for MRI QSM.

The structural similarity index measure (SSIM) has become a popular quality metric to evaluate QSM in a way that is closer to human perception than RMS error (RMSE). However, SSIM may overpenalize errors in diamagnetic tissues and underpenalize them in paramagnetic tissues, resulting in biasing. In addition, extreme artifacts may compress the dynamic range, resulting in unrealistically high SSIM scores (hacking). To overcome biasing and hacking, we propose XSIM: SSIM implemented in the native QSM range, and with internal parameters optimized for QSM. We used forward simulations from a COSMOS ground-truth brain susceptibility map included in the 2016 QSM Reconstruction Challenge to investigate the effect of QSM reconstruction errors on the SSIM, XSIM, and RMSE metrics. We also used these metrics to optimize QSM reconstructions of the in vivo challenge data set. We repeated this experiment with the QSM abdominal phantom. To validate the use of XSIM instead of SSIM for QSM quality assessment across a range of different reconstruction techniques/algorithms, we analyzed the reconstructions submitted to the 2019 QSM Reconstruction Challenge 2.0. Our experiments confirmed the biasing and hacking effects on the SSIM metric applied to QSM. The XSIM metric was robust to those effects, penalizing the presence of streaking artifacts and reconstruction errors. Using XSIM to optimize QSM reconstruction regularization weights returned less overregularization than SSIM and RMSE. XSIM is recommended over traditional SSIM to evaluate QSM reconstructions against a known ground truth, as it avoids biasing and hacking effects and provides a larger dynamic range of scores.

Disparities in fertility preservation discussions among sexual and gender minority cancer patients and their cancer care providers

Background Cancer providers are advised to inform their reproductive aged patients about fertility preservation given the potential for treatment-related infertility. How consistently fertility preservation discussions (FPDs) occur is understudied in sexual and gender minority (SGM) cancer patients. The effects of bias and heteronormativity may reduce the rate of FPDs. We identified the frequency and correlates of FPD in a sample of SGM cancer patients. Methods Data were from the cross-sectional 2020 OUT National Cancer Survey. The sample was restricted to those diagnosed with cancer between the ages of fifteen and forty-five. FPD was measured with a single item. Multivariable logistic regression was conducted to determine factors significantly associated with FPDs. Results Average age at cancer diagnosis was 34.97 (SD = 8.34). Respondents were mostly non-Hispanic white (77.6%) and college-educated (63.4%), and 32.6% reported FPDs. In the multivariable model, identifying as lesbian (Adjusted odds ratio [aOR] = 0.49; 95% CI: 0.24-0.99), pansexual (aOR = 0.34; 95% CI:0.12-0.94), or queer (aOR = 0.24; 95% CI: 0.08-0.70) was negatively associated with FPDs compared to bisexuals. Being treated more than ten years ago (aOR = 0.47; 95% CI:0.26-0.85) was also negatively associated with FPDs. Conclusion Findings suggest potential bias against some SGM patients based on sexual orientation identity in FPDs, though changes over the past decade may have increased the frequency of FPD with patients more broadly. More research is needed to investigate why some SGM patients of reproductive age are not being counseled about fertility preservation.

Age Bias & Female Leadership: Faulty Cheat Codes

This paper explores the intersection of age bias and gender bias in relation to female leadership. “Cheat codes” is a term originally applied to computer and video games to describe a code that, when used, allows the player to access features, level skips, or capabilities not otherwise available (Merriam-Webster, n.d.). As a metaphor, the term is meant to suggest a shortcut in decision-making toward a desired conclusion or outcome. In the context of this article, “faulty cheat codes” refer to society’s use of misinformed and unfair stereotypes as specious shortcuts to judge the abilities or qualifications of individuals based on their age, leading to incorrect conclusions or inappropriate actions. This piece highlights the detrimental effects of age bias on prominent female politicians, including Former Speaker Nancy Pelosi, and emphasizes the need for authentic conversations about cognitive abilities. The paper challenges the use of age as a flawed measure of competence and advocates for retiring negative stereotypes about aging. It also discusses the delayed entry of women into political office and the compounding effects of age and gender biases. By promoting positive narratives about aging and addressing ageism in our political discourse, society can create a more fair and inclusive political landscape that values the capabilities of individuals of all ages. The paper concludes by urging a shift in focus toward substantive political discussions and away from shallow indicators of competence based on age.

Effect of present state bias on minimal important change estimates: a simulation study.

The minimal important change (MIC) in a patient-reported outcome measure is often estimated using patient-reported transition ratings as anchor. However, transition ratings are often more heavily weighted by the follow-up state than by the baseline state, a phenomenon known as "present state bias" (PSB). It is unknown if and how PSB affects the estimation of MICs using various methods. We simulated 3240 samples in which the true MIC was simulated as the mean of individual MICs, and PSB was created by basing transition ratings on a "weighted change", differentially weighting baseline and follow-up states. In each sample we estimated MICs based on the following methods: mean change (MC), receiver operating characteristic (ROC) analysis, predictive modeling (PM), adjusted predictive modeling (APM), longitudinal item response theory (LIRT), and longitudinal confirmatory factor analysis (LCFA). The latter two MICs were estimated with and without constraints on the transition item slope parameters (LIRT) or factor loadings (LCFA). PSB did not affect MIC estimates based on MC, ROC, and PM but these methods were biased by other factors. PSB caused imprecision in the MIC estimates based on APM, LIRT and LCFA with constraints, if the degree of PSB was substantial. However, the unconstrained LIRT- and LCFA-based MICs recovered the true MIC without bias and with high precision, independent of the degree of PSB. We recommend the unconstrained LIRT- and LCFA-based MIC methods to estimate anchor-based MICs, irrespective of the degree of PSB. The APM-method is a feasible alternative if PSB is limited.

GrainSense: A Wireless Grain Moisture Sensing System Based on Wi-Fi Signals

Grain moisture sensing plays a critical role in ensuring grain quality and reducing grain losses. However, existing commercial off-the-shelf (COTS) grain moisture sensing systems are either expensive, inconvenient or inaccurate, which greatly limit their widespread deployment in real-world scenarios. To fill this gap, we develop a system called GrainSense which leverages COTS Wi-Fi devices to detect the grain moisture without the need for dedicated sensors. Specifically, we propose a wireless grain moisture detection model based on the refraction phenomenon of Wi-Fi signals and the Multiple-Input-Multiple-Output (MIMO) technology. On one hand, we correlate the grain moisture with the phase difference between two refracted Wi-Fi signals that propagate along different paths, based on which grain moisture can be deduced accordingly. On the other hand, to reduce the multi-path interference in indoor environments (e.g., the granary), we adopt Wi-Fi beamforming to enhance the refracted signal. In particular, a new signal feature (i.e., the Wi-Fi CSI beamforming ratio) is designed to eliminate the effect of sub-carrier frequency bias and cumulative phase bias. To validate the effectiveness of the developed system, we conduct extensive experiments with different types of grains in both the laboratory and the granary. Results show that the system can accurately estimate the grain moisture with an mean absolute error smaller than 5%, which meets the requirements for commercial usage. To the best of our knowledge, this is the first model-based work that achieves accurate grain moisture detection based on wireless sensing.

Micromagnetic study of exchange bias effect in sub-micron dots of Co2MnSi interfaced with uncompensated IrMn

Owing to its crucial role in spintronics devices, the exchange bias (EB) phenomenon has been extensively investigated in various ferromagnet (FM) and antiferromagnet (AFM) bilayers since its discovery in Co/CoO core–shell nanoparticles. In this study, we present the emergence of negative EB for the first time in the Co2MnSi Heusler alloy interfacing with an uncompensated AFM, exhibiting analogous anisotropy to the IrMn. Due to the high pinning and IrMn anisotropy values, EB is stronger here. Investigation into the influence of ferromagnetic layer thickness (tFM) on exchange bias reveals an inverse relationship, while coercivity displays a non-monotonic increase. The analysis of spin canting angles suggests the presence of a maximum canting angle in the Co2MnSi layer close to the interface. We thoroughly analyze the spin configurations at the interface as well as away from it in the Co2MnSi (25 nm)/IrMn (5 nm) bilayer to better understand the mechanism of magnetization reversal. Interestingly, our findings unveiled distinct spin behaviors for the first and second reversals. In cases of small AFM thicknesses (tAFM), the exchange field is proportionate to the tAFM, contrasting with large tAFM, where it scales as 1/tAFM. Notably, coercivity demonstrates an increasing behavior across all tAFM variations. The angular dependence of the Heusler alloy revealed a four-fold symmetry indicative of cubic anisotropy and a two-fold symmetry representative of uniaxial anisotropy. The angular dependency study of exchange bias indicated similar clockwise (CW) and counterclockwise (CCW) rotations, with cos (θ) unidirectional dependence. However, loop shifting revealed that the lower pinning ability at 0° was due to a low Meiklejohn-Bean parameter (R) value. Additionally, through the manipulation of the R-parameter, we can tune the magnitude of the coercive field and EB. All these results are crucial for the utilization of the Co2MnSi/IrMn heterostructures for various applications in spintronics-based devices.

Historical Bias in Mortgage Lending, Redlining, and Implications for the Uncertain Geographic Context Problem: A Study of Structural Housing Discrimination in Dallas and Boston.

According to the uncertain geographic context problem, a lack of temporal information can hinder measures of bias in mortgage lending. This study extends previous methods to: (1) measure the persistence of racial bias in mortgage lending for Black Americans by adding temporal trends and credit scores, and (2) evaluate the continuity of bias in discriminatory areas from 1990 to 2020. These additions create an indicator of persistent structural housing discrimination. We studied the Boston-Cambridge-Newton and Dallas-Fort Worth metropolitan statistical areas to examine distinct historical trajectories and urban development. We estimated the odds of mortgage denial for census tracts. Overall, all tracts in Boston-Cambridge-Newton (N = 1003) and Dallas-Fort Worth (N = 1312) displayed significant change, with greater odds of bias over time in Dallas-Fort Worth and lower odds in Boston-Cambridge-Newton. Historically redlined areas displayed the strongest persistence of bias. Results suggest that temporal data can identify persistence and improve sensitivity in measuring neighborhood bias. Understanding the temporality of residential exposure can increase research rigor and inform policy to reduce the health effects of racial bias.

Adolescents' trait mindfulness and psychological stress: The mediating role of attention.

Based on the Combined Cognitive Biases Hypothesis, the current study via two parallel studies aims to explore the potential mediating role of attention biases and attention control regarding the link between trait mindfulness and psychological stress in adolescents. For Study 1, we collected self-reported data from 2123 Chinese adolescents (mean age = 15.6 years, SD = 2.37; 52.8% female) in four schools. The participants completed measures of trait mindfulness, perceived stress, and attention bias. Mediation analysis was employed to investigate the potential mediating effect of attention bias. In Study 2, 123 participants (mean age = 17.7 years, SD = 2.68; 41.46% female) completed the attention network task after inducing attention bias. Then, trait mindfulness and perceived stress were measured. Mediation analysis was employed to investigate the potential mediating effect of attention control (alerting, orienting, and conflict monitoring) under attention bias. Study 1 demonstrated a significant mediating effect of negative attention bias ([-0.13, -0.07], p < .05) but not positive attention bias in the relationship between trait mindfulness and psychological stress. Study 2 revealed that conflict monitoring in negative attention bias ([-0.41, -0.16], p < .05), rather than alerting and orienting in negative attention bias, showed a significant mediating effect on the association between trait mindfulness and psychological stress. Findings from the two studies suggest that conflict monitoring during negative attention bias may be the underlying mechanism through which trait mindfulness helps mitigate psychological stress in adolescents.

Migraine versus tension-type headache in automatic emotional processing: A visual mismatch negativity study

ObjectiveIt is important to discriminate different headaches in clinical practice, and neurocognitive biomarkers may serve as objective tools. Several reports have suggested potential cognitive impairment for primary headaches, whereas cognitions within specific domains remain elusive, e.g., emotional processing. In this study, we aimed to characterize processing of facial expressions in migraine and tension-type headache (TTH) by analyzing expression-related visual mismatch negativity (EMMN) and explored whether their processing patterns were distinct. MethodsAltogether, 73 headache patients (20 migraine with aura (MA), 28 migraine without aura (MwoA), 25 TTH) and 27 age-matched healthy controls were recruited. After a battery of mood/neuropsychological evaluations, an expression-related oddball paradigm containing multiple models of neutral, happy and sad faces was used to investigate automatic emotional processing. ResultsWe observed cognitive impairment in all headache patients, especially in attention/execution subdomains, but no discrepancy existed among different headaches. Although analyses of P1/N170 did not reach significant levels, amplitude of early and late EMMN was markedly diminished in MA and MwoA compared with controls and TTH, regardless of happy or sad expression. Moreover, sad EMMN was larger (more negative) than happy EMMN only in controls, while not in all headache groups. ConclusionsOur findings implied that migraine, rather than TTH, might lead to more severe impairment of automatic emotional processing, which was manifested as no observable EMMN elicitation and disappearance of negative bias effect. The EMMN component could assist in discrimination of migraine from TTH and diagnosis of undefined headaches, and its availability needed further validations.