Understanding racial bias through electroencephalography.

Research on racial bias in social and cognitive psychology has focused on automatic cognitive processes such as categorisation or stereotyping. Neuroimaging has revealed differences in the neural circuit when processing social information about one's own or another's ethnicity. This review investigates the influence of racial bias on human behaviour by reviewing studies that examined changes in neural circuitry (i.e. ERP responses) during automatic and controlled processes elicited by specific tasks. This systematic analysis of specific ERP components across different studies provides a greater understanding of how social contexts are perceived and become associated with specific stereotypes and behavioural predictions. Therefore, investigating these related cognitive and neurobiological functions can further our understanding of how racial bias affects our cognition more generally and guide more effective programs and policies aimed at its mitigation.

Component mechanisms of executive function in schizophrenia and their contribution to functional outcomes

Objective: In schizophrenia, scores reflecting deficits in different cognitive processes are strongly correlated, making it difficult to establish a solid relationship between different cognitive mechanisms and other features of this disorder. The objective of this study was to explore whether three frequently postulated executive functions (updating, shifting, and inhibition) could be compared between groups and considered independently in terms of their respective roles in functional outcome. Methods: This study relied on confirmatory factor analysis of schizophrenia patients (n=141) and healthy controls (n=119). The main analyses examined the degree to which three executive functions (updating, set-shifting, and inhibition) could be separated in schizophrenia and compared this model among groups. Structural equation modeling analysis was also performed to examine the extent to which executive function components contribute to functional outcome in schizophrenia. Results: Multiple-group confirmatory factor analysis with unconstrained model parameters indicated that the full three-factor model may fit the data in both groups (χ2 = 61.48, degrees of freedom = 34, p < 0.001, comparative fit index = 0.95; standardized root mean square residual = 0.037; root mean square error of approximation = 0.04; Akaike's information criteria = 169.49; normed fit index = 0.90), although there was also a good data fit for the patient group with a two-factor model. In the patient group, structural equation modeling suggested that shifting and (principally) updating were associated with the general measure of functional outcome (regression path coefficients: 0.34, p < 0.005; 0.39, p < 0.005, respectively), although when combined the mechanisms fail to contribute. Conclusion: This data suggests that the factor structure may be similar but not identical between groups, and both updating and shifting may play an important role in functional outcome in schizophrenia.

Component mechanisms of executive function in schizophrenia and their contribution to functional outcomes.

OBJECTIVE: In schizophrenia, scores reflecting deficits in different cognitive processes are strongly correlated, making it difficult to establish a solid relationship between different cognitive mechanisms and other features of this disorder. The objective of this study was to explore whether three frequently postulated executive functions (updating, shifting, and inhibition) could be compared between groups and considered independently in terms of their respective roles in functional outcome. METHODS: This study relied on confirmatory factor analysis of schizophrenia patients (n=141) and healthy controls (n=119). The main analyses examined the degree to which three executive functions (updating, set-shifting, and inhibition) could be separated in schizophrenia and compared this model among groups. Structural equation modeling analysis was also performed to examine the extent to which executive function components contribute to functional outcome in schizophrenia. RESULTS: Multiple-group confirmatory factor analysis with unconstrained model parameters indicated that the full three-factor model may fit the data in both groups (χ2 = 61.48, degrees of freedom = 34, p < 0.001, comparative fit index = 0.95; standardized root mean square residual = 0.037; root mean square error of approximation = 0.04; Akaike's information criteria = 169.49; normed fit index = 0.90), although there was also a good data fit for the patient group with a two-factor model. In the patient group, structural equation modeling suggested that shifting and (principally) updating were associated with the general measure of functional outcome (regression path coefficients: 0.34, p < 0.005; 0.39, p < 0.005, respectively), although when combined the mechanisms fail to contribute. CONCLUSION: This data suggests that the factor structure may be similar but not identical between groups, and both updating and shifting may play an important role in functional outcome in schizophrenia.

tDCS in Addiction and Impulse Control Disorders.

The study of addiction and impulsion control disorders has shown that behaviors of seeking and consumption of addictive substances are subserved by neurobiological alterations specifically related to brain networks for reward, stress, and executive control, representing the brain's adaptation to the continued use of an addictive substance. In parallel, studies using neuromodulation techniques such as transcranial direct current stimulation (tDCS) have demonstrated promising effects in modulating cognitive and motor functions. This review aims to describe the neurobiology of addiction and some of the most relevant cognitive models of addictive behavior and to clarify how tDCS application modulates the intake and craving for several addictive substances, such as food, alcohol, nicotine, cocaine, crack, methamphetamine, and cannabis. We also discuss the positive and null outcomes of the use of this neuromodulatory technique in the treatment of addiction disorders resulting from the use of these substances. The reviewed findings lead us to conclude that tDCS interventions hold several promising clinical avenues in addiction and impulsive control. However, methodological investigations are necessary for undercover optimal parameters before implementing its clinical application.

Processing of fear and anger facial expressions: the role of spatial frequency.

Spatial frequency (SF) components encode a portion of the affective value expressed in face images. The aim of this study was to estimate the relative weight of specific frequency spectrum bandwidth on the discrimination of anger and fear facial expressions. The general paradigm was a classification of the expression of faces morphed at varying proportions between anger and fear images in which SF adaptation and SF subtraction are expected to shift classification of facial emotion. A series of three experiments was conducted. In Experiment 1 subjects classified morphed face images that were unfiltered or filtered to remove either low (<8 cycles/face), middle (12-28 cycles/face), or high (>32 cycles/face) SF components. In Experiment 2 subjects were adapted to unfiltered or filtered prototypical (non-morphed) fear face images and subsequently classified morphed face images. In Experiment 3 subjects were adapted to unfiltered or filtered prototypical fear face images with the phase component randomized before classifying morphed face images. Removing mid frequency components from the target images shifted classification toward fear. The same shift was observed under adaptation condition to unfiltered and low- and middle-range filtered fear images. However, when the phase spectrum of the same adaptation stimuli was randomized, no adaptation effect was observed. These results suggest that medium SF components support the perception of fear more than anger at both low and high level of processing. They also suggest that the effect at high-level processing stage is related more to high-level featural and/or configural information than to the low-level frequency spectrum.