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Gonzalez-Garcia, C.

Publications and source records attributed to Gonzalez-Garcia, C..

At least 19 recordsLinked to original sources

Episodic memory adaptively expands retrieval through typicality-guided transformation while concrete details remain accessible

Memory faces a fundamental challenge. It has to become flexible enough to be accessed by novel cues without losing the specific information that defines each individual episode. Whether memory transformation solves this problem by sacrificing details or by adaptively expanding retrieval while preserving them is unclear. We tested this by manipulating the match between a memory and its retrieval cue. Participants retrieved object associations after 6, 24 and 48 hours using either the original encoded image or novel exemplars that were more typical or more distinctive of the same object category. Retrieval initially benefited from the originally encoded image, but this advantage was reduced across delay. By 48 hours, a never-seen, more typical exemplar triggered retrieval as effectively as the original one, while the same convergence was not evident for less-typical exemplars. Crucially, such cue expansion was not accompanied by a loss of perceptual specificity. Participants retained access to the originally encoded exemplar across delays, while errors increasingly favoured more typical alternatives. At the item level, stronger episodic memories predicted better access to perceptual detail, but did not predict the tendency of errors for category-like information, which instead increased with delay. This dissociation suggests that memory generalisation and the continued accessibility of visual detail reflect partly separable transformations rather than opposite ends of a single continuum.

neuroscience↗

Flexible predictive processing during face perception

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 StatementPerception 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.

neuroscience↗

Multiple-Demand Network encoding geometry balances generalization and dimensionality during novel task assembly.

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.

neuroscience↗

Bayesian surprise tracks the strength of perceptual insight

Suddenly finding the solution to a problem after a period of impasse often comes with a feeling of insight. This subjective experience is proposed to arise as a consequence of prediction errors. Accordingly, previous studies have revealed that more incorrect initial predictions result in more intense insights. Crucially however, prominent models of Bayesian inference suggest levels of computationally-defined surprise are not a simple feature of distance between predictions and inputs, but also their precision or certainty. Yet, how these two factors interact to give rise to insight experiences remains unknown. In this pre-registered study, participants were exposed to ambiguous images while they tried to guess the correct label of the image (to derive prediction accuracy) and rated their confidence in that label (for prediction uncertainty). We then measured the intensity of their insight when a solution was given. As predicted, we found that the intensity of insight was a result of both the prediction accuracy and the uncertainty awarded to it. More specifically, when initial predictions were far from the true label, those made with lower confidence induced weaker insights, while the opposite pattern was observed when predictions were closer to the reality. Trial-by-trial estimations of prediction errors from participants responses closely mirrored insight ratings. Finally, we analysed data from two additional independent datasets with different modalities and setups and replicated the interaction between prediction accuracy and uncertainty on the intensity of insight. Altogether, these findings suggest that insight experiences are read out from prediction errors and highlight the key role of uncertainty in characterising this relationship.

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Characterising semantic prioritisation in visual working memory

Cognitive operations require recently encountered information to remain available beyond the moment of sensory input. However, how such transient representations are accessed, and how they differ from sensory processing and long-term memory, remains unclear. Here, we combine hierarchical drift-diffusion modelling with behavioural manipulations to dissociate the decision processes underlying feature prioritisation in visual working memory. We first reanalysed a previously collected working memory dataset to characterise semantic and perceptual judgements at the level of latent decision processes. Semantic judgements were associated with reduced non-decision time across conditions, indicating faster access to task-relevant information, while advantages in evidence accumulation emerged selectively under higher cognitive demands. Two further experiments manipulated attentional prioritisation using retro-cues and dissociated the effects of interference from mere maintenance. Across manipulations, semantic prioritisation was selectively expressed in pre-accumulation processes and was amplified when representations fell outside the focus of attention or had to be maintained under interference. Together, these results suggest that semantic representations remain more readily accessible than perceptual details when working memory representations fall outside the focus of attention, consistent with a shift towards more abstract, long-term memory-like formats under conditions of limited attentional support.

neuroscience↗

Exogenously driven neural reactivation of spatially matching visual working-memory contents

Selective attention is often divided into voluntary (goal-directed) and involuntary (stimulus-driven) forms, a distinction extensively studied for attention to external sensory input. In contrast, internal selective attention--directed toward representations held in working memory (WM)--has been considered primarily for voluntary influences. Recent behavioral evidence suggests that task-irrelevant external stimuli can also influence internal selection of feature-matching WM representations involuntarily, yet the neural mechanisms underlying these effects remain unclear. Here, we tested whether an uninformative exogenous spatial retro-cue presented during a WM delay can act as a selective "ping" and reactivate spatially matching WM content at the level of its representational category. Male and female human participants memorized complex contents presented at distinct locations, followed by unpredictive and task-irrelevant spatial retro-cues that conveyed no category information. Using temporally resolved multivariate EEG decoding, we observed category-specific reactivation of spatially matching WM representations following these cues, providing direct neural evidence for stimulus-driven, involuntary attentional selection within WM, ahead of the memory test. Moreover, neural responses to the subsequent memory-probe were also modulated by cue congruency, consistent with the notion that exogenous influences begin early during sensory processing while also shaping later decision-related processes. Finally, drift-diffusion model analyses revealed that this involuntary cueing effect was primarily driven by increased evidence accumulation. Together, these findings illuminate the mechanisms by which external events can automatically and involuntarily penetrate the internal cognitive workspace. Significance StatementThe processes underlying involuntary attentional selection of internal information held in our working-memory system have been largely overlooked. Our study shows that external stimuli can automatically select information that is temporarily held in our mind. We found that uninformative, task-irrelevant visual cues can selectively "ping" and reactivate specific working-memory contents, despite carrying only spatial information. We demonstrate that these cues trigger category-specific neural reactivation and shape later decision-making by accelerating evidence accumulation. This extends current knowledge on how the outside world can transiently interact with our internal cognitive workspace.

neuroscience↗

Dynamic prioritization reshapes neural geometries for action in human working memory

Prior work has shown that control brain regions encode upcoming novel instructed actions. Similarly, visual working memory (WM) representations can reflect different priority states. However, it remains unknown whether the priority status of WM-guided novel actions similarly modulates their neural coding format, and how such dynamics unfold over time. We addressed these questions using EEG while human participants performed two consecutive choice reaction tasks. At the start of each trial, participants encoded two novel stimulus-response (S-R) mappings. A cue then indicated whether these mappings would be relevant immediately ("current" condition), later after an intervening task ("prospective"), or after a free delay ("delayed"). Using multivariate pattern analysis, we found that the S-R category was decodable in all conditions during relevant time windows. Critically, pattern similarity analyses revealed that while mere maintenance demands allow for temporary preservation of neural codes (i.e., between current and delayed trials), shielding from interference (i.e., prospective trials) induced significant alterations to the neural code. Further exploration of the representational geometry revealed that priority status gained prominence dynamically over S-R category coding when preparing for such shielding demands. Importantly, some of these changes emerged anticipatorily, prior to target onset. Overall, our results show that, similar to visual WM, the priority of intended actions dynamically and anticipatorily reshapes their neural format. They further reveal how different demands induce content geometries compatible with previously proposed coding schemes, and that such representational changes can be implemented flexibly in time. Significance statementSuccessfully translating visuomotor plans into action relies not only on maintaining such plans but also on prioritizing relevant information at the right time. While prior work has shown that working memory representations adapt to prioritize visual content, it remains unknown whether similar mechanisms apply to action-guiding content. Using EEG and multivariate analyses, we show that priority states--whether immediate, delayed, or prospectively relevant--modulate the representational geometry of novel stimulus-response mappings. Notably, the anticipation of interference compared to mere maintenance leads to greater alterations in the neural code during a retention interval. These results demonstrate that neural representations of novel instructed actions are shaped by their priority state and upcoming demands and reveal how goal- relevant information is restructured over time.

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Determinants of visual ambiguity resolution

Visual inputs during natural perception are highly ambiguous: objects are frequently occluded, lighting conditions vary, and object identification depends significantly on prior experiences. However, why do certain images remain unidentifiable while others can be recognized immediately, and what visual features drive subjective clarification? To address these critical questions, we developed a unique dataset of 1,854 ambiguous images and collected more than 100,000 ratings (from a total of 947 participants) evaluating their identifiability before and after seeing undistorted versions of the images. Relating the representations of a brain-inspired neural network model in response to our images with human ratings, we show that subjective identification depends largely on the extent to which higher-level visual features from the original images are preserved in their ambiguous counterparts. In line with these results, an image-level regression analysis showed that the subjective identification of ambiguous images was best explained by high-level visual dimensions. Notably, the predominance of higher-level features over lower-level ones softens after participants disambiguate the images, suggesting that the visual system flexibly shifts between top-down guessing to bottom-up matching after disambiguation. Moreover, we found that the process of ambiguity resolution was accompanied by a notable decrease in semantic distance and a greater consistency in object naming among participants. However, the relationship between information gained after disambiguation and subjective identification was non-linear, indicating that acquiring more information does not necessarily enhance subjective clarity. Instead, we observed a U-shaped relationship, suggesting that subjective identification improves when the acquired information either strongly matches or mismatches prior predictions. Collectively, these findings advance our understanding on how we resolve ambiguity and extract meaning from incomplete visual information.

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Novel verbal instructions recruit abstract neural patterns of time-variable information dimensionality

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 StatementThe 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.

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Context-dependent neural preparation for information relevance vs. probability

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.

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Concurrent response and action effect representations across the somatomotor cortices during novel task preparation.

Instructions allow us to fulfill novel and complex tasks on the first try. This skill has been linked to preparatory brain signals that encode upcoming demands in advance, facilitating novel performance. To deepen insight into these processes, we explored whether instructions pre-activated task-relevant motoric and perceptual neural states. Critically, we addressed whether these representations anticipated activity patterns guiding overt sensorimotor processing, which could reflect that internally simulating novel tasks facilitates the preparation. To do so, we collected functional magnetic resonance imaging data while female and male participants encoded and implemented novel stimulus-response associations. Participants also completed localizer tasks designed to isolate the neural representations of the mappings-relevant motor responses, perceptual consequences, and stimulus categories. Using canonical template tracking, we identified whether and where these sensorimotor representations were pre-activated. We found that response-related templates were encoded in advance in regions linked with action control, entailing not only the instructed responses but also their somatosensory consequences. This result was particularly robust in primary motor and somatosensory cortices. While, following our predictions, we found a systematic decrease in the irrelevant stimulus templates representational strength compared to the relevant ones, this difference was due to below-zero estimates linked to the irrelevant category activity patterns. Overall, our findings reflect that instruction processing relies on the sensorimotor cortices to anticipate motoric and kinesthetic representations of prospective action plans, suggesting the engagement of motor imagery during novel task preparation. More generally, they stress that the somatomotor system could participate with higher-level frontoparietal regions during anticipatory task control.

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The Temporal Dynamics of Metacognitive Experiences Track Rational Adaptations in Task Performance

Human task performance elicits diverse subjective metacognitive experiences, such as boredom, effort, fatigue and frustration, which are thought to play important roles in the monitoring and regulation of cognitive processes. Yet, their specific contributions to task performance remain poorly understood. Therefore, we investigated the temporal dynamics underlying these metacognitive experiences and the latent cognitive processes supporting task performance. We used a time-on-task design using a conflict Flanker task, and analyzed the data using a comprehensive approach encompassing behavioral, model-based, subjective, and neural measures. Our results show that the temporal dynamics in cognitive processes can be understood as a rational attempt to optimize task performance and that distinct metacognitive experiences track different aspects of this rational endeavor. These findings suggest that metacognitive experiences act as tools for humans to gain insights into the optimality of their cognitive performance.

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Preparatory neural activity differs between Selective Attention and Perceptual Expectations

SummaryProactive cognition brain models are mainstream nowadays. Within these, preparation is understood as an endogenous, top-down function that takes place prior to the actual perception of a stimulus and improves subsequent behavior. Neuroimaging has shown the existence of such preparatory activity separately in different cognitive domains, however no research to date has sought to uncover their potential similarities and differences. Two of these, often confounded in the literature, are Selective Attention (information relevance) and Perceptual Expectation (information probability). We used EEG to characterize the mechanisms that pre-activate specific contents in Attention and Expectation. In different blocks, participants were cued to the relevance or to the probability of target categories, faces vs. names, in a gender discrimination task. Multivariate Pattern (MVPA) and Representational Similarity Analyses (RSA) during the preparation window showed that both manipulations led to a significant, ramping-up prediction of the relevant or expected target category. However, classifiers trained on data from one condition did not generalize to the other, indicating the existence of unique anticipatory neural patterns. In addition, a Canonical Template Tracking procedure showed that there was stronger anticipatory perceptual reinstatement for relevance than for expectation blocks. Overall, results indicate that preparation during attention and expectation acts through distinguishable neural mechanisms. These findings have important implications for current models of brain functioning, as they are a first step towards characterizing and dissociating the neural mechanisms involved in top-down anticipatory processing.

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Effects of experiencing CS-US pairings on instructed fear reversal

Fear learning allows us to identify and anticipate aversive events, and adapt our behavior accordingly. This is often thought to rely on associative learning mechanisms where an initially neutral conditioned stimulus (CS) is repeatedly paired with an aversive unconditioned stimulus (US), eventually leading to the CS also being perceived as aversive and threatening. Importantly, however, humans also show verbal fear learning. Namely, they have the ability to change their responses to stimuli rapidly through verbal instructions about CS-US pairings. Past research on the link between experience-based and verbal fear learning indicated that verbal instructions about a reversal of CS-US pairings can fully override the effects of previously experienced CS-US pairings, as measured through fear ratings, skin conductance, and fear-potentiated startle. However, it remains an open question whether such instructions can also annul memory traces in the brain. Here, we used a fear reversal paradigm in conjunction with representational similarity analysis of fMRI data to test whether verbal instructions fully override the effects of experienced CS-US pairings in fear-related brain regions or not. Previous research suggests that only the right amygdala should show lingering representations of previously experienced threat (a so-called "Pavlovian trace"). Unexpectedly, we found evidence for the residual effect of prior CS-US experience to be much more widespread than anticipated, in the amygdala but also cortical regions like the dorsal anterior cingulate or dorso-lateral prefrontal cortex. This finding shines a new light on the interaction of different fear learning mechanisms, at times with unexpected consequences.

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Theta-phase connectivity between medial prefrontal and posterior areas underlies novel instructions implementation

Implementing novel instructions is a complex and uniquely human cognitive ability, that requires the rapid and flexible conversion of symbolic content into a format that enables the execution of the instructed behavior. Preparing to implement novel instructions, as opposed to their mere maintenance, involves the activation of the instructed motor plans, and the binding of the action information to the specific context in which this should be executed. Recent evidence and prominent computational models suggest that this efficient configuration of the system might involve a central role of frontal theta oscillations in establishing top-down long-range synchronization between distant and task-relevant brain areas. In the present EEG study (human subjects, 30 females, 4 males), we demonstrate that proactively preparing for the implementation of novels instructions, as opposed to their maintenance, involves a strengthened degree of connectivity in the theta frequency range between medial prefrontal and motor/visual areas. Moreover, we replicated previous results showing oscillatory features associated specifically with implementation demands, and extended on them demonstrating the role of theta oscillations in mediating the effect of task demands on behavioral performance. Taken together, these findings support our hypothesis that the modulation of connectivity patterns between frontal and task-relevant posterior brain areas is a core factor in the emergence of a behavior-guiding format from novel instructions. Significance statementEveryday life requires the use and manipulation of currently available information to guide behavior and reach specific goals. In the present study we investigate how the same instructed content elicits different neural activity depending on the task being performed. We show that medial prefrontal theta oscillations are larger when novel instructions have to be implemented, rather than simply maintained. Crucially, connectivity between medial prefrontal cortex and posterior areas is strengthened during instructions implementation, suggesting that theta oscillations play a role in setting up a dynamic and flexible network of task-relevant regions optimized for the execution of the instructed behavior.

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Adaptive coding of stimulus information in human fronto-parietal cortex during visual classification

The neural mechanisms of how frontal and parietal brain regions support flexible adaptation of behavior remain poorly understood. Here, we used functional magnetic resonance imaging (fMRI) and model-based representational similarity analysis (RSA) to investigate frontoparietal representations of stimulus information during visual classification under varying task demands. Based on prior research, we predicted that increasing perceptual task difficulty should lead to more categorical coding of stimulus information, and that exemplar-level stimulus coding would be restricted to posterior, sensory brain regions. Counter to our expectations, however, we found frontoparietal regions encoded exemplar-level stimulus information. Interestingly, the anterior intraparietal sulcus (aIPS) encoded stimuli equally well regardless of perceptual difficulty, and these representations were directly related to choice behavior (proportion of guessing). Overall, these findings reveal unexpected exemplar-level stimulus coding in frontoparietal cortex, and highlight the role of aIPS in supporting adaptive behavior.

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The effect of task demands on the neural patterns generated by novel instruction encoding

Verbal instructions allow fast and optimal implementation of novel behaviors. Previous research has shown that different control-related variables structure neural activity in frontoparietal regions during the encoding of novel instructed tasks. However, it is uncertain whether different task goals modulate the organizing effect of these variables. In this study, we investigated whether the neural encoding of three task-relevant variables (dimension integration, response set complexity and target category) is modulated by implementation and memorization demands. To do so, we combined functional Magnetic Resonance Imaging (fMRI), an instruction-following paradigm and multivariate analyses. We addressed how and where distributed activity patterns encoded the instructions variables and the impact of the implementation and memorization demands on the fidelity of these representations. We further explored the nature of the neural code underpinning this process. Our results reveal, first, that the content of to-be-implemented and to-be-memorized instructions is represented in overlapping brain regions, flexibly using a common neural code across tasks. Importantly, they also suggest that preparing to implement the instructions increases the decodability of task-relevant information in frontoparietal areas, in comparison with memorization demands. Overall, our work emphasizes both similarities and differences in task coding under the two contextual demands. These findings qualify the previous understanding of novel instruction processing, suggesting that representing task attributes in a generalizable code, together with the increase in encoding fidelity induced by the implementation goals, could be key mechanisms for proactive control in novel scenarios.

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Designing Topographically Textured Microparticles For Induction and Modulation of Osteogenesis in Mesenchymal Stem Cell Engineering

Mesenchymal stem cells have been the focus of intense research in bone development and regeneration. We demonstrate the potential of microparticles as modulating moieties of osteogenic response by utilizing their architectural features. Topographically textured microparticles of varying microscale features were produced by exploiting phase-separation of a readily-soluble sacrificial component from polylactic acid. The influence of varying topographical features on primary human mesenchymal stem cell attachment, proliferation and markers of osteogenesis was investigated. In the absence of osteoinductive supplements, cells cultured on textured microparticles exhibited notably increased expression of osteogenic markers relative to conventional smooth microparticles. They also exhibited varying morphological, attachment and proliferation responses. Significantly altered gene expression and metabolic profiles were observed, with varying histological characteristics in vivo. This study highlights how tailoring topographical design offers cell-instructive 3D microenvironments which allow manipulation of stem cell fate by eliciting the desired downstream response without use of exogenous osteoinductive factors.

bioengineering↗