Alejandra Figueroa-Vargas

Background: Cognitive impairment poses a significant challenge to healthcare systems worldwide, impacting patient autonomy, social participation, and quality of life, while placing a considerable burden on caregivers. Non pharmacological interventions, particularly cognitive training and non invasive brain stimulation, have emerged as promising therapeutic strategies. Objective: This study aims to quantify the synergistic effects of transcranial direct current stimulation (tDCS) with cognitive training on cognitive function across a spectrum of pathologies that induce cognitive impairment. Methods: We conducted a systematic review and metaanalysis following PRISMA guidelines. We searched PubMed for randomized controlled trials that investigated the effect of combined tDCS and cognitive training compared with cognitive training alone. The analysis was based on the GRADE framework for systematic reviews and metaanalyses. Results: Across 27 studies including 1,012 participants, tDCS combined with cognitive training showed a small effect compared with cognitive training alone (SMD = 0.36, 95% CI: 0.15 0.56). The effect was found only immediately after the intervention and declined during follow-up. Conclusion: tDCS combined with cognitive training may provide a small, short term benefit for cognitive function, but high heterogeneity across studies and loss of effect at follow up underscore the need for larger, better standardized trials to clarify its clinical value.

Summary: Adaptive behavior requires weighting incoming feedback against more stable action policies, but the neural dynamics controlling this balance during social interaction remain unclear. Across 296 experimental sessions in 219 participants, we combined computational modeling, EEG, fMRI, diffusion MRI, and fMRI-guided rhythmic TMS during repeated social bargaining. Behavior was captured by complementary feedback-based updating and reputation-based adjustment, with reproducible individual differences in how instructed social context reweighted feedback. Feedback-based updating showed the clearest convergent neural signature: trial-by-trial updating was associated with alpha–beta dynamics and multivoxel representational structure in right temporoparietal cortex. Critically, rhythmic alpha-TMS over individually localized TPJ sites selectively reduced feedback-based updating relative to active arrhythmic stimulation, while increasing baseline offers and modulating anticipatory alpha activity. Functional and structural connectivity analyses further implicated a distributed temporoparietal–frontal network. Together, these findings link a specific computational operation—feedback weighting—to temporoparietal alpha dynamics and show that rhythmic perturbation alters its behavioral expression.

Fluctuations in attentional states, such as mind-wandering (MW), are associated with critical variability in task performance. While fMRI studies highlight the opposing roles of task-positive (e.g., dorsal attention network) and task-negative (e.g., default mode network) systems, the electrophysiological mechanisms underlying these dynamics remain poorly understood. Using intracranial electrocorticography in humans performing a sustained attention task, we identified global oscillatory dynamics linked to attentional shifts. MW was characterized by (i) reduced theta and alpha power, (ii) decreased aperiodic signal components, indicating a shift toward cortical inhibition, (iii) enhanced phase synchronization across networks, and (iv) strengthened theta phase-behavior correlations. These features support a non-network-specific framework in which low-frequency theta dynamics are associated with attentional fluctuations, while aperiodic offset relates to attentional state indirectly through its association with theta phase-behavior correlations. Our study provides a unified neurophysiological framework for understanding how spontaneous neural activity can drive attentional fluctuations and performance variability, with implications for research on attention, learning, and neuropsychiatric disorders.

Background: Sedentarism is prevalent and associated with poorer mental and physical health. Whether everyday physical activity (PA) maps onto computational decision strategies and brain structure/function in non-elderly adults remains unclear. Methods: Seventy-one healthy adults (39 women; 18–45 years) completed the Multi-Source Interference Task (MSIT) during fMRI. PA was quantified with the short IPAQ and participants were classified as Active or Sedentary. Behavior (RT, accuracy) was analyzed with frequentist models and a hierarchical Bayesian drift–diffusion model (DDM) estimating drift rate ( v ), boundary separation ( α ), and non-decision time (τ). First-level fMRI modeled congruent/incongruent trials; group-level analyses used FLAME1 with cluster-wise FWE correction (z>3.1, p <.05). Structural MRI was processed with FreeSurfer 7.4.1 (cortical thickness, hippocampal subfields); surface-based GLMs tested group and DDM effects. Results: Active participants responded faster overall; incongruent accuracy showed a speed– accuracy trade-off (accuracy increased with slower RTs), with a significant RT × group interaction. In the DDM, boundary separation ( α ) was higher in sedentary individuals (greater caution), whereas drift rate ( v ) differed by sex (males > females). Structurally, the active group showed larger left hippocampal subfields and thicker cortex in posterior temporal & anterior cingulate regions that are negatively related to α . Functionally, boundary-related BOLD modulation encompassed fusiform, posterior cingulate, superior temporal cortex, and SMA; Active > Sedentary contrasts highlighted left occipital and inferior parietal lobe. Conclusions: Everyday PA aligns with lower decision thresholds, select structural advantages, and more efficient task-engaged networks, suggesting PA fosters adaptive, resource-efficient cognitive control. These mechanistic links support PA-based strategies to mitigate risks of sedentarism.

Docosahexaenoic acid (DHA) is a polyunsaturated fatty acid enriched in neuronal membranes and myelin and associated with cognitive performance. However, nutritional interventions show inconsistent cognitive effects, partly due to limited knowledge of the neural pathways linking DHA status to human cognition during sensitive periods of white-matter maturation, such as adolescence. We addressed this gap by studying 99 adolescents drawn from both extremes of performance on a national scholastic examination. Participants completed assessments of scholastic achievement (SA) and intellectual ability (IA), provided erythrocyte DHA samples, and underwent multimodal MRI, including diffusion, T1-weighted, and T2-weighted imaging. Independent component analysis and Bayesian multivariate LASSO models identified brain components jointly associated with DHA and cognition. Across four MRI modalities, a single deep white-matter component consistently emerged as the strongest shared pathway linking DHA with cognition. Tract-resolved analyses highlighted predominant contributions from the fornix and thalamus–temporal fasciculus, with additional subcortical and cortical involvement. In joint models, these components predicted SA and IA after accounting for DHA and other fatty acids, consistent with an indirect, mediation-like pathway. These findings move beyond DHA–behavior correlations by identifying specific neuroanatomical pathways through which a modifiable dietary factor relates to adolescent learning and intellectual performance, offering mechanistic insight relevant to neuroscience, nutrition, and education. Significance Statement: Adolescence is a sensitive period for the maturation of white-matter pathways that support learning and reasoning. Docosahexaenoic acid (DHA), an essential dietary fatty acid enriched in neuronal membranes and myelin, has been linked to cognitive performance, yet the neural mechanisms underlying this association remain unclear. Using multimodal MRI and Bayesian multivariate modeling in adolescents with high or low scholastic performance, identify a specific deep white-matter pathway—centered on the fornix and the thalamus–temporal fasciculus—as the principal route connecting DHA status with scholastic achievement and intellectual ability. Additional subcortical and cortical contributions reveal a coordinated system-level architecture. These findings move beyond correlations by providing mechanistic insight into how a modifiable nutritional factor relates to cognitive development, with implications for neuroscience, public health, and education.

Persistent cognitive symptoms following SARS-CoV-2 infection have been widely reported, yet their underlying neural mechanisms remain poorly understood. Here, we applied an integrative framework—combining EEG, diffusion MRI, and computational cognitive modeling—to investigate brain–behavior relationships in patients recovered from COVID-19 (n=70) and other non-COVID respiratory infections (n=26). Participants completed tasks probing cognitive control, working memory, and decision-making. Across tasks, individuals with prior COVID-19 showed altered low-frequency oscillatory activity and performance deficits, despite mild or moderate acute illness. These oscillatory alterations were linked to reduced white matter integrity in distinct long-range tracts, including the cingulum and thalamo-occipital fasciculi, depending on the cognitive computation involved. Crucially, model-based clustering revealed two distinct neurophysiological profiles among post-COVID participants, reflecting different combinations of structural and functional alterations. These profiles were not explained by clinical severity markers or other symptoms like anosmia, suggesting the emergence of neurocognitive phenotypes beyond binary classifications. Our findings identify a generalizable principle whereby specific brain network disruptions underlie cognitive dysfunction, highlighting biomarkers that may guide personalized intervention strategies. Beyond COVID-19, this multimodal framework offers a scalable approach for uncovering structure–function–computation coupling in other post-infectious or neuroinflammatory conditions, with broad relevance for the prevention and treatment of cognitive impairment.

Multiple sclerosis (MS) is a prevalent neurological disorder marked by inflammation and demyelination, with fatigue being one of the most reported and debilitating symptoms. While fatigue occurs across various neurological conditions and even in healthy individuals, the specific mechanisms contributing to fatigue in each context remain unclear. In this study, we conducted a cross-sectional analysis involving 32 people with relapsing MS (PwRMS) and 29 healthy controls who reported fatigue. Participants underwent MRI scans, including T1-weighted and diffusion-weighted imaging. Additionally, the Modified Fatigue Impact Scale was utilized. We employed Bayesian LASSO and Spike-and-Slab LASSO regression models to investigate the hypothesis that fatigue correlates differently with brain structures in PwRMS. Our findings revealed brain regions associated with general and cognitive fatigue. In particular, reduced white matter volume and compromised microstructural integrity in specific areas—such as the cingulate gyrus, inferior frontal gyrus, and the banks of the superior temporal sulcus—showed significant associations with fatigue scores in PwRMS. These results suggest that alterations in specific brain regions may play a critical role in the clinical manifestation of fatigue in MS. Understanding these insights could help differentiate general mechanisms of fatigue from those affecting people with relapsing MS, which may guide future therapeutic strategies.

Adapting our behavior to environmental demands relies on our capacity to perceive and manage potential conflicts within our surroundings. While evidence implicates the involvement of the lateral prefrontal cortex and theta oscillations in detecting conflict stimuli, their causal role in conflict expectation remains elusive. Consequently, the exact computations and neural mechanisms underlying these cognitive processes still need to be determined. We employed an integrative approach involving cognitive computational modeling, fMRI, TMS, and EEG to establish a causal link between oscillatory brain function, its neurocomputational role, and the resulting conflict processing and adaptation behavior. Our results reveal a computational process underlying conflict expectation, which correlates with BOLD-fMRI and theta activity in the superior frontal gyrus (SFG). Modulation of theta activity via rhythmic TMS applied over the SFG induces endogenous theta activity, which in turn enhances computations associated with conflict expectation. These findings provide evidence for the causal involvement of SFG theta activity in learning and allocating cognitive resources to address forthcoming conflict stimuli.

Patients recovering from COVID-19 commonly exhibit cognitive and brain alterations, yet the specific neuropathological mechanisms and risk factors that underlie these alterations remain elusive. Given the significant global incidence of COVID-19, identifying factors that can distinguish individuals at risk of developing medium or long-term brain alterations is crucial for prioritizing follow-up care. Here, we report findings from a sample of 100 patients who were affected by a respiratory infection during the COVID-19 pandemic. This sample comprised 73 adults with a mild to moderate SARS-CoV-2 infection (who did not require invasive ventilatory assistance) and 27 with infections attributed to other agents and no history of COVID-19. The participants underwent cognitive screening, a decision-making task to measure cognitive flexibility, and magnetic resonance imaging evaluations. We assessed two clinical factors during infection: the presence of anosmia and the requirement for hospitalization due to respiratory symptoms. Groups did not differ in age or cognitive performance, but clinical factors differentially affected task performance. Patients who presented anosmia during the acute episode exhibited more impulsive changes in alternatives after a shift in probabilities in the decision-making task, while patients who required hospitalization showed more perseverative choices. Interestingly, the presence of anosmia during SARS-CoV-2 infection correlated with several brain measures, including decreases in functional activity during the decision-making task, thinning of cortical thickness in parietal regions, and loss in white matter integrity in corticospinal tracts and parietal-thalamic fasciculi, among others. These results suggest that anosmia could be a risk factor for developing brain alterations after SARS-CoV-2 infection and may serve to identify at-risk populations for follow-up.

Adapting our behavior to environmental demands relies on our capacity to perceive and manage potential conflicts within our surroundings. While evidence implicates the involvement of the lateral prefrontal cortex and theta oscillations in detecting conflict stimuli, their roles in conflict expectation remain elusive. Consequently, the exact computations and neural mechanisms underlying these cognitive processes still need to be determined. To address this gap, we employed an integrative approach involving cognitive computational modeling, fMRI, TMS, and EEG. Our results revealed a computational process underlying conflict expectation, which correlated with activity in the superior frontal gyrus (SFG). Furthermore, rhythmic TMS in the theta range applied over the SFG, but not over the inferior frontal junction, induced endogenous theta activity, enhancing computations associated with conflict expectation. These findings provide compelling evidence for the causal involvement of SFG theta activity in learning and allocating cognitive resources to address forthcoming conflict stimuli. Significant Statement Alterations in the processing of expectations of conflict events have been associated with several neuropsychiatric disorders that significantly affect the quality of life for many individuals. This article describes a cognitive computation underlying the conflict expectation and its causal neural mechanism involving theta brain activity in the superior frontal gyrus (SFG). Thus, unraveling this mechanism holds promise for developing interventions to address cognitive alterations related to anticipation of conflict events in neuropsychiatric disorders, improving overall cognitive function and quality of life.