Temporal-order judgment of visual and auditory stimuli: modulations in situations with and without stimulus discrimination

Temporal-order judgment (TOJ) tasks are an important paradigm to investigate processing times of information in different modalities. There are a lot of studies on how temporal order decisions can be influenced by stimuli characteristics. However, so far it has not been investigated whether the addition of a choice reaction time (RT) task has an influence on TOJ. Moreover, it is not known when during processing the decision about the temporal order of two stimuli is made. We investigated the first of these two questions by comparing a regular TOJ task with a dual task (DT). In both tasks, we manipulated different processing stages to investigate whether the manipulations have an influence on TOJ and to determine thereby the time of processing at which the decision about temporal order is made. The results show that the addition of a choice RT task does have an influence on the TOJ, but the influence seems to be linked to the kind of manipulation of the processing stages that is used. The results of the manipulations indicate that the temporal order decision in the DT paradigm is made after perceptual processing of the stimuli

The effect of task order predictability in audio-visual dual task performance: just a central capacity limitation?

In classic Psychological-Refractory-Period (PRP) dual-task paradigms, decreasing stimulus onset asynchronies (SOA) between the two tasks typically lead to increasing reaction times (RT) to the second task and, when task order is non-predictable, to prolonged RTs to the first task. Traditionally, both RT effects have been advocated to originate exclusively from the dynamics of a central bottleneck. By focusing on two specific electroencephalographic brain responses directly linkable to perceptual or motor processing stages, respectively, the present study aimed to provide a more detailed picture as to the origin(s) of these behavioral PRP effects. In particular, we employed 2-alternative forced-choice (2AFC) tasks requiring participants to identify the pitch of a tone (high versus low) in the auditory, and the orientation of a target object (vertical versus horizontal) in the visual, task, with task order being either predictable or non-predictable. Our findings show that task order predictability (TOP) and inter-task SOA interactively determine the speed of (visual) perceptual processes (as indexed by the PCN timing) for both the first and the second task. By contrast, motor response execution times (as indexed by the LRP timing) are influenced independently by TOP for the first, and SOA for the second, task. Overall, this set of findings complements classical as well as advanced versions of the central bottleneck model by providing electrophysiological evidence for modulations of both perceptual and motor processing dynamics that, in summation with central capacity limitations, give rise to the behavioral PRP outcome

Testing the limits of optimizing dual-task performance in younger and older adults

Impaired dual-task performance in younger and older adults can be improved with practice. Optimal conditions even allow for a (near) elimination of this impairment in younger adults. However, it is unknown whether such (near) elimination is the limit of performance improvements in older adults. The present study tests this limit in older adults under conditions of (a) a high amount of dual-task training and (b) training with simplified component tasks in dual-task situations. The data showed that a high amount of dual-task training in older adults provided no evidence for an improvement of dual-task performance to the optimal dual-task performance level achieved by younger adults. However, training with simplified component tasks in dual-task situations exclusively in older adults provided a similar level of optimal dual-task performance in both age groups. Therefore through applying a testing the limits approach, we demonstrated that older adults improved dual-task performance to the same level as younger adults at the end of training under very specific conditions

A Chromosomal Inversion Unique to the Northern White-Cheeked Gibbon

The gibbon family belongs to the superfamily Hominoidea and includes 15 species divided into four genera. Each genus possesses a distinct karyotype with chromosome numbers varying from 38 to 52. This diversity is the result of numerous chromosomal changes that have accumulated during the evolution of the gibbon lineage, a quite unique feature in comparison with other hominoids and most of the other primates. Some gibbon species and subspecies rank among the most endangered primates in the world. Breeding programs can be extremely challenging and hybridization plays an important role within the factors responsible for the decline of captive gibbons. With less than 500 individuals left in the wild, the northern white-cheeked gibbon (Nomascus leucogenys leucogenys, NLE) is the most endangered primate in a successful captive breeding program. We present here the analysis of an inversion that we show being specific for the northern white-cheeked gibbon and can be used as one of the criteria to distinguish this subspecies from other gibbon taxa. The availability of the sequence spanning for one of the breakpoints of the inversion allows detecting it by a simple PCR test also on low quality DNA. Our results demonstrate the important role of genomics in providing tools for conservation efforts

Genetic factors influencing a neurobiological substrate for psychiatric disorders

A retrospective meta-analysis of magnetic resonance imaging voxel-based morphometry studies proposed that reduced gray matter volumes in the dorsal anterior cingulate and the left and right anterior insular cortex-areas that constitute hub nodes of the salience network-represent a common substrate for major psychiatric disorders. Here, we investigated the hypothesis that the common substrate serves as an intermediate phenotype to detect genetic risk variants relevant for psychiatric disease. To this end, after a data reduction step, we conducted genome-wide association studies of a combined common substrate measure in four population-based cohorts (n = 2271), followed by meta-analysis and replication in a fifth cohort (n = 865). After correction for covariates, the heritability of the common substrate was estimated at 0.50 (standard error 0.18). The top single-nucleotide polymorphism (SNP) rs17076061 was associated with the common substrate at genome-wide significance and replicated, explaining 1.2% of the common substrate variance. This SNP mapped to a locus on chromosome 5q35.2 harboring genes involved in neuronal development and regeneration. In follow-up analyses, rs17076061 was not robustly associated with psychiatric disease, and no overlap was found between the broader genetic architecture of the common substrate and genetic risk for major depressive disorder, bipolar disorder, or schizophrenia. In conclusion, our study identified that common genetic variation indeed influences the common substrate, but that these variants do not directly translate to increased disease risk. Future studies should investigate gene-by-environment interactions and employ functional imaging to understand how salience network structure translates to psychiatric disorder risk

DenseNet and Support Vector Machine classifications of major depressive disorder using vertex-wise cortical features

Major depressive disorder (MDD) is a complex psychiatric disorder that affects the lives of hundreds of millions of individuals around the globe. Even today, researchers debate if morphological alterations in the brain are linked to MDD, likely due to the heterogeneity of this disorder. The application of deep learning tools to neuroimaging data, capable of capturing complex non-linear patterns, has the potential to provide diagnostic and predictive biomarkers for MDD. However, previous attempts to demarcate MDD patients and healthy controls (HC) based on segmented cortical features via linear machine learning approaches have reported low accuracies. In this study, we used globally representative data from the ENIGMA-MDD working group containing an extensive sample of people with MDD (N=2,772) and HC (N=4,240), which allows a comprehensive analysis with generalizable results. Based on the hypothesis that integration of vertex-wise cortical features can improve classification performance, we evaluated the classification of a DenseNet and a Support Vector Machine (SVM), with the expectation that the former would outperform the latter. As we analyzed a multi-site sample, we additionally applied the ComBat harmonization tool to remove potential nuisance effects of site. We found that both classifiers exhibited close to chance performance (balanced accuracy DenseNet: 51%; SVM: 53%), when estimated on unseen sites. Slightly higher classification performance (balanced accuracy DenseNet: 58%; SVM: 55%) was found when the cross-validation folds contained subjects from all sites, indicating site effect. In conclusion, the integration of vertex-wise morphometric features and the use of the non-linear classifier did not lead to the differentiability between MDD and HC. Our results support the notion that MDD classification on this combination of features and classifiers is unfeasible

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Naturalistic face adaptation: How we adapt to freckles fast and sustainably

While sunbathing, our skin becomes susceptible to quite remarkable changes in visual appearance, that is, freckles appear or increase in intensity—most obviously on the face. Research on face adaptation repeatedly showed that the inspection of manipulated versions of faces (so-called adaptor faces) leads to robust and sustainable changes in the perception of subsequently presented faces. Therefore, during the adaptation phase of the present study, participants saw faces with either strongly increased or decreased intensities of freckles. After a 5-minute break, during the test phase, participants had to identify the veridical (non-manipulated) face out of two faces (a slightly manipulated face combined with a non-manipulated face). Results showed strong adaptation effects to increased and decreased levels of freckles. We conclude that updating facial representations in memory is relatively fast, and these representation updates seem to sustain over a certain time span (at least 5 minutes). Face-specificity of our effects will be discussed. The results align with our everyday experience that the appearance of freckles in spring is a salient change in a familiar face; however, we seem to not register these changes after a few exposures due to a loss of information quality