María Ruz

Perceptual expectations facilitate perception of expected information by shaping neural coding. However, how the cognitive demands of different tasks may modulate this effect remains unclear. Here, we investigated whether and how expectations derived from sex/gender stereotypes impact behavioral and neural face processing as a function of task goals. Fifty-one participants categorized either the emotional expression (happy vs. angry) or the sex (male vs. female) of faces while mouse trajectories and electroencephalography (EEG) were recorded in separate sessions. Expectations were manipulated through the congruency between facial sex and emotional expression (congruent: angry male, happy female; incongruent: happy male, angry female). Behavioral analyses revealed that incongruent faces elicited larger trajectory deviations, longer movement dynamics and slower reaction times than congruent faces. Representational Similarity Analyses (RSA) showed that face congruency modulated coding geometries of both mouse trajectories and EEG, whereas multivariate classifiers revealed progressive impact of congruency from early stages of face neural coding. Importantly, all measurements revealed stronger congruency effects during emotion than during sex judgments, indicating that the influence of expectations is flexibly tailored to task demands. Furthermore, congruent faces exhibited enhanced decoding performance and reached peak neural discriminability earlier than incongruent ones. Finally, EEG–mouse fusion analyses revealed shared representational dynamics primarily explained by task demands. Together, these findings indicate that expectations facilitate face processing in a task-dependent manner and suggest that predictive facilitation operates, rather than by increasing the rate of evidence accumulation, by accelerating the emergence of neural coding patterns. Significance Statement: Perception is shaped by the combination of sensory input and prior expectations, including socially acquired sex/gender face stereotypes. Learning how these expectations influence perception and how they are flexibly adjusted to current behavioral goals is essential for predictive coding models. Combining EEG and mouse tracking, we show that emotion judgments are more susceptible to expectations than sex categorization, and that expectations accelerate the emergence of neural coding patterns rather than simply increasing the rate of evidence accumulation. These findings characterize the neural mechanism through which predictive processing adapts to task demands and demonstrate that the influence of social stereotypes on face perception is dynamically regulated rather than automatically imposed, providing new insights into when social biases are most likely to shape human perception.

Attention is a function that enables selection and integration of multiple sources of information. However, how these demands influence neural coding of information is not well understood. In this study we used EEG to examine how the selection vs. integration of stimuli shapes the content and geometry reflected on neural patterns, during both preparation and target processing. Participants performed a size judgement task in a cue-target paradigm that, depending on the block, required judging either the size of a selected item and ignoring the additional stimulus or integrating both to respond. Decoding analyses showed that under selection demands, categorical templates of the cued stimulus were active during preparation and target coding, contrasting with integration, where patterns linked to the cued category could be observed only during preparation. Notably, RSA suggested specific exemplar encoding during its processing, which was sustained also across the post-stimulus window during selection, yet was not observable under integration contexts. Our results also suggest that attentional demands shape the similarity between stimulus categories by increasing the distance between selected stimuli and distractors or by reducing it between to-be-integrated information. Overall, this study uncovers the dynamics of stimulus encoding under selection and integration demands, offering crucial advances to understand how top-down processes shape information representation in the human brain.

On the basis of verbal instructions, humans can accomplish novel and diverse demands on the very first try. This complex phenomenon recruits structured brain activity across the frontoparietal Multiple Demand Network (MDN), which is thought to encode upcoming task parameters and guide behavior. However, it is uncertain how novel instructions are translated into efficient neural task representations. To address this, we collected functional magnetic resonance imaging (fMRI) data while participants followed a rich set of novel verbal instructions. These varied along three core dimensions: the overarching task demand (to select or to integrate stimuli information), the relevant target category (animate or inanimate items), and the visual feature that participants responded to (color or shape). We used multivariate pattern analysis (MVPA) to examine whether and how each of these dimensions was reflected in MDN activity. We contrasted two alternative representational geometries that may underpin novel task coding: low-dimensional spaces based on abstract and generalizable representations, and high-dimensional architectures hosting context-unique, conjunctive neural codes. Our results showed that anticipatory MDN activity was sensitive to the content of instructions. While selection vs. integration task demands were broadly encoded across the MDN, coding of the relevant categories and features was restricted to lateral MDN regions, namely, the intraparietal sulcus and the inferior frontal junction. Critically, the representational spaces across the MDN displayed a mixture of geometrical motifs, partially supporting our two alternative hypotheses. On the one hand, Cross-Condition Generalization Performance revealed the presence of abstract and transferable neural codes for task demand information. On the other hand, Shattering Dimensionality showed complex, high dimensional coding spaces across the MDN, structured around both task-informative and non-informative axes. Despite this, no evidence of conjunctive neural codes was observed. Overall, these findings highlight that novel instructed behavior may recruit both abstraction and high dimensionality to promote generalization while maximizing the expressivity of MDN coding spaces. More broadly, they emphasize the importance of considering encoding geometry for a computational understanding of cognitive control processes.

Human performance is endowed by neural representations of information that is relevant for behavior, some of which are also activated in a preparatory fashion to optimize later execution. Most studies to date have focused on highly practiced actions, leaving largely unaddressed the novel reconfiguration of information to generate unique whole task sets. Using electroencephalography, this study investigated the dynamics of the content and geometry reflected on the neural patterns of control representations during reconfiguration of information. We designed a verbal instruction paradigm where each trial involved novel combinations of multicomponent task information. By manipulating three task-relevant factors in a sample of 40 participants (26 females, 14 males), we observed complex coding schemes throughout the trial, during both preparation and implementation stages. The temporal profiles were consistent with a hierarchical structure: whereas task information was active in a sustained manner, the coding of more concrete stimulus features was more transient. Data showed both high dimensionality and abstraction, particularly during instruction encoding and target processing. Our results suggest that whenever task content could be recovered from neural patterns of activity, there was evidence of abstract coding, with an underlying geometry that favored generalization. During target processing, where potential interference across stimulus and response factors increased, orthogonal configurations also appeared. Overall, our findings uncover the dynamic manner with which control representations operate during novel recombination unique scenarios, with changes in dimensionality and abstraction adjusting along processing stages.

Preparation is a top-down phenomenon known to improve performance across different situations. In light of recent electrophysiological findings that suggest that anticipatory neural preactivations linked to preparation are context-specific and do not generalize across domains, in the current study we used fMRI to investigate the brain regions involved in these differential patterns. We applied multivariate decoding to data obtained in a paradigm where, in different blocks, cues provided information about the relevance or probability of incoming target stimuli. Results showed that the anticipated stimulus category was preactivated in both conditions, mostly in different brain regions within the ventral visual cortex and with differential overlap with actual target perception. Crucially, there was scarce cross-classification across attention and expectation contexts except on a patch of the fusiform gyrus, indicating mostly differential neural coding of anticipated contents in relevance and probability scenarios. Finally, a model-based fMRI-EEG fusion showed that these regions differentially code for specific conditions during preparation, as well as specifically preparing for category anticipation in a ramping-up manner. Overall, our results stress the specificity of anticipatory neural processing depending on its informative role while highlighting a key hub of commonality in the fusiform gyrus.

Human performance is endowed by neural representations of information that is relevant for behavior, some of which are also activated in a preparatory fashion to optimize later execution. Most studies to date have focused on highly practiced actions, leaving largely unaddressed the novel re-configuration of information to generate unique whole task-sets. Using electroencephalography (EEG), this study investigated the dynamics of the content and geometry reflected on the neural patterns of control representations during re-configuration of information. We designed a verbal instruction paradigm where each trial involved novel combinations of multi-component task information. By manipulating three task-relevant factors in a sample of 40 participants (26 females, 14 males), we observed complex coding schemes throughout the trial, during both preparation and implementation stages. The temporal profiles were consistent with a hierarchical structure: whereas task information was active in a sustained manner, the coding of more concrete stimulus features was more transient. Data showed both high dimensionality and abstraction, particularly during instruction encoding and target processing. Our results suggest that whenever task content could be recovered from neural patterns of activity, there was evidence of abstract coding, with an underlying geometry that favored generalization. During target processing, where potential interference across stimulus and response factors increased, orthogonal configurations also appeared. Overall, our findings uncover the dynamic manner with which control representations operate during novel recombination unique scenarios, with changes in dimensionality and abstraction adjusting along processing stages. Significance Statement: The neural mechanisms that support task performance in novel contexts have been largely overlooked. Cognitive control is thought to enable complex behavior through the active maintenance of task sets, containing essential information for execution. However, how novel whole combinations of information are organized in neural patterns and their temporal dependencies remain unknown. Here, using a novel complex instruction paradigm, we observed that coding of informational content and its underlying geometry followed a dynamic temporal pattern. Our results reveal varying dimensionality and abstraction throughout the trial, with neural codes generally structured in a geometry favoring generalization of relevant information across task demands. These findings provide a first glimpse into the temporal computations engaged by the brain when encountering novel recombination settings.

Preparation is a top-down phenomenon known to improve performance across different situations. In light of recent electrophysiological findings that suggest that anticipatory neural preactivations linked to preparation are context-specific and do not generalize across domains, in the current study we used fMRI to investigate the brain regions involved in these differential patterns. We applied multivariate decoding to data obtained in a paradigm where, in different blocks, cues provided information about the relevance or probability of incoming target stimuli. Results showed that the anticipated stimulus category was pre-activated in both conditions, mostly in different brain regions within the ventral visual cortex and with differential overlap with actual target perception. Crucially, there was scarce cross-classification across attention and expectation contexts except on a patch of the fusiform gyrus, indicating mostly differential neural coding of anticipated contents in relevance and probability scenarios. Finally, a model-based fMRI-EEG fusion showed that these regions differentially code for specific conditions during preparation, as well as specifically preparing for category anticipation in a ramping-up manner. Overall, our results stress the specificity of anticipatory neural processing depending on its informative role while highlighting a key hub of commonality in the fusiform gyrus.

Selective attention is a cognitive function that helps filter out unwanted information. Theories such as the biased competition model (Desimone & Duncan, 1995) explain how attentional templates bias processing towards targets in contexts where multiple stimuli compete for resources. However, it is unclear how the anticipation of different levels of competition influences the nature of attentional templates, in a proactive fashion. In this study, we used EEG to investigate how the anticipated demands of attentional selection (either high or low stimuli competition contexts) modulate target-specific preparatory brain activity and its relationship with task performance. To do so, participants performed a sex judgement task in a cue-target paradigm where, depending on the block, target and distractor stimuli appeared simultaneously (high competition) or sequentially (low competition). Multivariate Pattern Analysis (MVPA) showed that, in both competition contexts, there was a preactivation of the target category to select with a ramping-up profile at the end of the preparatory interval. However, cross-classification showed no generalization across competition conditions, suggesting different preparatory formats. Notably, time-frequency analyses showed differences between anticipated competition demands, reflecting higher theta band power for high than low competition, which mediated the impact of subsequent stimuli competition on behavioral performance. Overall, our results show that, whereas preactivation of the internal templates associated with the category to select are engaged in advance in both competition contexts, their underlying neural patterns differ. In addition, these codes could not be associated with theta power, suggesting different preparatory processes. The implications of these findings are crucial to increase our understanding of the nature of top-down processes across different contexts.