Daniel Rojas-Líbano

Background: Neuropsychological Rehabilitation has traditionally relied on models that conceptualize cognition primarily as a property of the individual brain. However, many established rehabilitation practices extend beyond the individual, involving cognitive artifacts (e.g., tools), modifications of the physical environment, and the coordinated contribution of other people. This creates a potential mismatch between how cognition is theoretically conceptualized and how rehabilitation is practiced. Objective: In this conceptual article, we examine how Extended and Distributed Cognition may help address this discrepancy. Drawing on the historical work of Kurt Goldstein, contemporary cognitive science, and evidence-based rehabilitation practice, we distinguish Extended Cognition , which emphasizes how external resources can become integrated into an individual's cognitive processes, from Distributed Cognition , which examines how cognitive activity is organized across people, artifacts, and environments. Implications: We argue that these perspectives broaden both the unit of analysis and the potential targets of rehabilitation: intervention may involve not only changing cognitive processes within the individual, but also introducing or reorganizing cognitive artifacts, modifying environments, and changing how other people interact with the person. Established practices including external compensatory strategies, communication partner training, environmental modification, and the coordinated organization of rehabilitation teams illustrate the clinical relevance of this perspective. Conclusion: Extended and Distributed Cognition may therefore provide a complementary theoretical framework for understanding how cognition is supported and reorganized in everyday life after brain injury, helping to bridge the persistent gap between neuropsychological mechanisms and everyday functioning.

Objective: To test whether relational context under minimal co-presence (i.e., being alone versus co-present with a friend or an unfamiliar (non-threatening) stranger) modulates stimulus-locked EEG/ERP dynamics during apparent gaze-motion perception.Methods: Fifty healthy adults completed a classic apparent-motion gaze task across three counterbalanced sessions (i.e., Alone, Friend, Stranger) with minimal interactivity. Using identical stimuli, participants performed two instruction framings: self-referential (i.e., toward-me vs away-from-me) and spatial (i.e., left vs right). ERPs time-locked to gaze-motion change were analyzed using mass-univariate TFCE within a non-parametric permutation framework (3×2 repeated-measures design). Behavior was analyzed at the trial level using mixed-effects models (LMM on logRT for correct trials; binomial-logit GLMM for accuracy) with maximal convergent random-effects structure.Results: Relational context produced robust posterior ERP modulations that were characterized by reduced amplitudes in the Friend condition relative to Stranger and Alone. No reliable ERP effects of instruction framing and no reliable interaction were observed. In behavior, instruction framing was associated with higher accuracy and slower responses in the spatial condition relative to the self-referential condition. Relational context and the interaction were not reliable in either model.Conclusions: Even with minimal interactivity and identical stimulus input, who is co-present modulates posterior stimulus-locked ERP dynamics during gaze-motion perception, whereas overt performance primarily reflects instruction framing.Significance: These findings provide an exploratory psychophysiological characterization showing that minimal co-presence is not a neutral baseline for ERPs and should be modeled explicitly in EEG paradigms where social context varies across sessions.

Attentional deployment (AD) constitutes an emotion regulation (ER) strategy that shifts the attentional focus to modulate the emotional experience. There are very few experimental paradigms that can study AD. One such task studies AD by using emotional images with zones of focus within them, to manipulate visual attention toward arousing or non-arousing portions of the scene. However, this task has only been implemented with participants inside a scanner and has no replications beyond the work of the original research group. In the present study, we replicated and extended a previously introduced AD task, implementing it with a sample of 55 adult participants. Our sample performed the task in a regular laboratory setting, including eye-tracking to monitor instruction following, and in addition, participants completed an attentional test. We replicated the original AD effect in a new population sample, although we found a lower effect size. We conceived and computed an estimate of AD abilities by comparing intensity and valence ratings across attentional conditions. We also analyzed the association between attention measured through the Attention Network Test (ANT) and AD capacities and found no relationship. The task can be used in the laboratory to analyze the AD process. Our replication and expansion of the AD task provide valuable insights into the behavioral and neuropsychological correlates of ER strategies.

Emotion-based decision making (EBDM) is the capacity to make decisions based on prior emotional consequences of actions. Several neuropsychological tasks, using different gambling paradigms and with different levels of complexity, have been designed to assess EBDM. The Bangor Gambling Task (BGT) was created as a brief and simple card gambling-task to assess EBDM. BGT contains a single-card deck and requires participants to decide whether to gamble or not, which can result in wins or losses. Unknown to the participant, the winning probabilities decrease throughout the task (from 0.75 in the first block to 0.25 in the fifth block), requiring participants to reduce their gambling probability to avoid long-term losses. A few studies have offered evidence regarding the BGT convergent validity. However, there are no computerized versions of BGT available, thus slowing the process of gathering information to explore the EBDM mechanisms behind the task, its validity, and clinical usefulness. In this article, we present a computerized version of the BGT using the Matlab environment and make all our code available. We explore BGT’s replicability and analyze its probabilistic structure, providing trial-level and block-level analyses. Eighty-one participants performed the computerized version, which followed the same structure as the original version. It took participants 8.5 ± 3.3 minutes to complete the task, which is faster than the paper version. Replicating previous studies, participants diminished their gambling probability throughout the task, learning to inhibit the initially rewarded gambling behavior. This change in gambling probability could be considered a proxy for EBDM. Our analyses suggest that the last blocks are especially sensitive to capturing deficits in EBDM, and we propose some modifications to BGT’s original version to enhance the initial exploratory and learning phase. Our results show that the BGT constitutes a quick and simple task to evaluate EBDM capacities.

Drift-diffusion models (DDM) have been proposed as a way to study unobservable cognitive processes underlying decision-making. DDM have been widely used and developed in psychology and cognitive neuroscience, but there are no general references in Spanish on the subject. The purpose of this review is to develop reference materials for Spanish-speaking researchers, professionals and scholars in the area of cognitive sciences who are interested in the experimental study of decision-making in the psychology and neuroscience fields. It will also explore the standard description of DDM, its parameters, mathematical expression and applications in cognitive tasks. Recent publications in the fields of cognitive psychology and neuroscience that use DDM are reviewed, and their prospects for new and future applications are discussed, in light of current discussions of cognitive processes.

Previous research has shown that the autonomic nervous system provides essential constraints over ongoing cognitive function. However, there is currently a relative lack of direct empirical evidence for how this interaction manifests in the brain at the macroscale level. Here, we examine the role of ascending arousal and attentional load on large-scale network dynamics by combining pupillometry, functional MRI, and graph theoretical analysis to analyze data from a visual motion-tracking task with a parametric load manipulation. We found that attentional load effects were observable in measures of pupil diameter and in a set of brain regions that parametrically modulated their BOLD activity and mesoscale network-level integration. In addition, the regional patterns of network reconfiguration were correlated with the spatial distribution of the α2a adrenergic receptor. Our results further solidify the relationship between ascending noradrenergic activity, large-scale network integration, and cognitive task performance.