Editorial Board Members’ Collection Series: Applied Affective and Cognitive Neuroscience

Affective neuroscience and cognitive neuroscience are two closely related subfields of neuroscience that explore distinct yet often overlapping dimensions of brain function. Cognitive neuroscience investigates the neural mechanisms underlying mental processes such as perception, memory, language, attention, learning, decision-making, and higher-order thinking [1]. In contrast, affective neuroscience centers on the neural substrates of emotions and mood, examining how emotional processes influence and interact with cognition and behavior [2].

Together, these fields have given rise to a vibrant interdisciplinary domain that extends far beyond traditional boundaries. Their insights now inform and reshape disciplines such as economics, philosophy, marketing, finance, education, and the arts. This convergence has fostered the emergence of novel subfields, including neuroeconomics, neuromarketing, neuroaesthetics, and neuroeducation, each grounded in the shared goal of understanding how the brain’s conscious and non-conscious mechanisms drive complex human behavior.

Recent advances in neuroscience methodologies, including electroencephalography (EEG), functional magnetic resonance imaging (fMRI), virtual reality (VR), machine learning, and brain–computer interfaces [3,4,5,6,7,8,9] have further deepened our ability to probe these mechanisms, linking neural data with both theoretical insights and practical applications. From clinical interventions to technological innovations, the fusion of affective and cognitive neuroscience continues to open new frontiers for understanding the human mind in real-world contexts.

This Special Issue brings together a diverse collection of nine original research articles and two review articles that illustrate the richness and breadth of this evolving field. These contributions highlight methodological progress and conceptual innovation, offering a comprehensive view of how affective and cognitive neuroscience together advance our understanding of the dynamic mind–brain relationship across varied domains.

One of the central themes of this Special Issue is the investigation of how emotional states influence cognitive functions, particularly attentional control and decision-making. In their electrophysiological study, Fuggetta et al. (contribution 1) explore how high levels of state depression impair selective attention by disrupting top-down control mechanisms. Using event-related potentials (ERPs) components such as early distractor suppression and attentional capture, they demonstrate that individuals with elevated depressive symptoms fail to suppress task-irrelevant stimuli effectively. This finding underscores the importance of integrating affective variables into cognitive models and highlights potential targets for therapeutic interventions aimed at improving attentional regulation in mood disorders.

Another compelling contribution comes from Taskov and Dushanova (contribution 2), who investigate sex differences in functional brain connectivity among children with developmental dyslexia (DD) using graph analysis of EEG data. Their work reveals distinct patterns of network organization between boys and girls, both in control groups and those diagnosed with DD. These findings suggest that developmental differences in brain connectivity may be sex-specific and call for more personalized approaches in diagnosing and treating learning disabilities. By highlighting the interaction between biological sex and neural network dynamics, this study contributes to the growing literature on individual variability in cognitive development.

SanMiguel et al. (contribution 3) examine the impact of brief mindfulness interventions on psychophysiological responses and performance in self-competitive tasks. Their experimental design demonstrates that even short mindfulness practices can significantly enhance self-efficacy, reduce perceived task difficulty, and improve cognitive performance. The observed increase in electrodermal activity suggests heightened physiological arousal during task execution, though no significant cardiovascular changes were noted. These results support the growing body of evidence indicating that brief mindfulness exercises can serve as practical tools for cognitive enhancement in real-world settings, such as education or professional environments.

In the realm of neuroaesthetics, Suhaili et al. (contribution 4) present a novel study exploring how the brain differentially processes abstract and figurative art styles. Using high-density EEG and functional connectivity analyses, they identify time- and frequency-dependent differences in neural network configurations associated with each artistic style. Their findings suggest that the perception of visual art involves complex, distributed networks whose dynamics vary based on the type of stimulus. This study not only advances our understanding of aesthetic cognition but also illustrates the utility of functional connectivity measures in capturing nuanced cognitive processes.

The application of VR in cognitive remediation is explored by Primavera et al. (contribution 5), who analyze secondary data from a randomized controlled trial involving patients with bipolar disorder. They report that VR-based training enhances cognitive performance, particularly in younger adults, possibly through the activation of mirror neuron systems. The age-related differential effects observed, where younger participants showed improvement in complex tasks while older ones improved in simpler ones, highlight the need for tailored interventions based on demographic factors.

Mainas et al. (contribution 6) tackle the challenge of diagnosing autism spectrum disorder (ASD) using machine learning techniques applied to fMRI data. Their comparison of traditional classifiers (SVMs, XGBoost) against deep learning models (TabNet, MLP) reveals that conventional methods outperform deep learning architectures in classifying ASD based on functional connectivity features. Moreover, the most relevant brain regions identified align with those known to be involved in sensory processing, spatial cognition, and attention modulation—key areas implicated in ASD. This study underscores the importance of feature interpretability in clinical applications and offers valuable insights for future diagnostic tool development.

Kavčič et al. (contribution 7) evaluate the efficacy of computerized cognitive training (CCT) in older workers, addressing the pressing societal issue of cognitive aging in the workforce. Their workplace-integrated intervention shows measurable improvements in executive functioning and helps stabilize productivity over time. These findings provide empirical support for implementing CCT programs in occupational settings, especially as populations age and cognitive demands in the workplace evolve.

Moro et al. (contribution 8) assess the role of transcranial magnetic stimulation (TMS) in psychiatric conditions such as obsessive–compulsive disorder (OCD), substance use disorder (SUD), and major depressive disorder (MDD). While TMS was found to significantly alleviate symptom severity, it did not result in consistent cognitive improvements. This suggests that while TMS holds promise as a symptomatic treatment, its full potential may be realized when combined with cognitive training or other complementary therapies.

Walla and Patschka (contribution 9) offer a groundbreaking perspective on non-conscious affective processing in financial decision-making. Using startle reflex modulation, they measure automatic emotional responses in asset managers during simulated investment scenarios. Their findings reveal that prior exposure to investments (exposure level) and the manager’s experience significantly modulate affective reactions, particularly in stable market conditions. This work offers new insights into the implicit emotional drivers of economic behavior and may inform strategies to improve decision-making in financial contexts.

Skierbiszewska et al. (contribution 10) provide a systematic review of canine fMRI studies, offering a comparative perspective on brain function across species. Their synthesis highlights key similarities and differences in neural activation patterns between dogs and humans, particularly in social cognition and sensory processing. This line of research has implications not only for veterinary medicine but also for translational neuroscience, including the development of animal-assisted therapies and the identification of biomarkers for cognitive and emotional health.

Finally, Amico et al. (contribution 11) conduct a systematic review of nonpharmacological treatments for tic disorders in youth, focusing on behavioral interventions such as Comprehensive Behavioral Intervention for Tics (CBIT) and Habit Reversal Therapy (HRT). Their findings confirm the efficacy of these interventions in reducing tic severity, with promising outcomes for both in-person and online delivery formats. However, they note that vocal tics remain less responsive than motor tics, pointing to areas for future refinement of treatment protocols.

The field of affective and cognitive neuroscience has evolved from its origins as a branch of basic brain science into a dynamic, multidisciplinary domain with far-reaching implications across psychology, medicine, education, finance, and even the arts. At its core lies the principle that human behavior (especially decision-making) is driven by neural processes occurring largely outside conscious awareness [10]. These non-conscious mechanisms shape our perceptions, emotions, and choices, often more accurately than self-reported experiences can convey. As such, neuroscience has become an essential tool for investigating and understanding complex behaviors across disciplines, giving rise to subfields such as neuroeconomics, neuromarketing, neurophilosophy, and neuroaesthetics [11].

To better understand the scope and interconnections among the studies featured in this Special Issue, we provide a systematic classification of the papers based on thematic domains, methodologies employed, and applications across fields. Figure 1 shows how each contribution fits into the broader landscape of applied affective and cognitive neuroscience, highlighting the interdisciplinary nature of the research and its real-world impact.

The contributions collected in this Special Issue exemplify the richness and relevance of applied affective and cognitive neuroscience. From the laboratory to the clinic, from the classroom to the boardroom, these studies illustrate how neuroscience is increasingly embedded in everyday life and decision-making. By integrating diverse methodologies, from classical electrophysiology to cutting-edge AI, we gain deeper insights into the hidden layers of cognition and emotion that drive human behavior.