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Background: Several functional magnetic resonance imaging (fMRI) studies investigated the brain correlates of psychogenic erectile dysfunction (PED) and premature ejaculation (PE), representing the most common sexual dysfunctions in men. These studies allowed a wide set of brain regions in PED and PE patients when compared to healthy men. In the present meta-analysis, we aim at assessing the presence of homogeneity in the cerebral underpinnings of PED and PE. Methods: Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and after the electronic search, duplicate removal and the application of pre-exclusion criteria, nine PED and ten PE studies were considered eligible with a Cohen’s k of 0.84 and 0.75, respectively. The effect sizes of the sociodemographic and psychological/urological dimensions were calculated. We extracted brain clusters from the retrieved studies, comparing patients and controls, and we calculated brain maps with Seed-Based D Mapping software. Results: We found a homogenous involvement of the frontal gyrus and insula in both dysfunctions, suggesting a common network. Conclusions: The anterior insula plays a key role in the processing of emotional features of stimuli, while the posterior insula in interoceptive information is relevant for sexual response. The prefrontal and inferior frontal cortices are important for sexual inhibition/disinhibition.

An emergent research area in software engineering and software reliability is the use of wearable biosensors to monitor the cognitive state of software developers during software development tasks. The goal is to gather physiologic manifestations that can be linked to error-prone scenarios related to programmers’ cognitive states. In this paper we investigate whether electroencephalography (EEG) can be applied to accurately identify programmers’ cognitive load associated with the comprehension of code with different complexity levels. Therefore, a controlled experiment involving 26 programmers was carried. We found that features related to Theta, Alpha, and Beta brain waves have the highest discriminative power, allowing the identification of code lines and demanding higher mental effort. The EEG results reveal evidence of mental effort saturation as code complexity increases. Conversely, the classic software complexity metrics do not accurately represent the mental effort involved in code comprehension. Finally, EEG is proposed as a reference, in particular, the combination of EEG with eye tracking information allows for an accurate identification of code lines that correspond to peaks of cognitive load, providing a reference to help in the future evaluation of the space and time accuracy of programmers’ cognitive state monitored using wearable devices compatible with software development activities.