Language statistical learning responds to reinforcement learning principles rooted in the striatum.

Statistical learning (SL) is the ability to extract regularities from the environment. In the domain of language, this ability is fundamental in the learning of words and structural rules. In lack of reliable online measures, statistical word and rule learning have been primarily investigated using offline (post-familiarization) tests, which gives limited insights into the dynamics of SL and its neural basis. Here, we capitalize on a novel task that tracks the online SL of simple syntactic structures combined with computational modeling to show that online SL responds to reinforcement learning principles rooted in striatal function. Specifically, we demonstrate-on 2 different cohorts-that a temporal difference model, which relies on prediction errors, accounts for participants' online learning behavior. We then show that the trial-by-trial development of predictions through learning strongly correlates with activity in both ventral and dorsal striatum. Our results thus provide a detailed mechanistic account of language-related SL and an explanation for the oft-cited implication of the striatum in SL tasks. This work, therefore, bridges the long-standing gap between language learning and reinforcement learning phenomena.

Integrating when and what information in the left parietal lobe allows language rule generalization.

A crucial aspect when learning a language is discovering the rules that govern how words are combined in order to convey meanings. Because rules are characterized by sequential co-occurrences between elements (e.g., "These cupcakes are unbelievable"), tracking the statistical relationships between these elements is fundamental. However, purely bottom-up statistical learning alone cannot fully account for the ability to create abstract rule representations that can be generalized, a paramount requirement of linguistic rules. Here, we provide evidence that, after the statistical relations between words have been extracted, the engagement of goal-directed attention is key to enable rule generalization. Incidental learning performance during a rule-learning task on an artificial language revealed a progressive shift from statistical learning to goal-directed attention. In addition, and consistent with the recruitment of attention, functional MRI (fMRI) analyses of late learning stages showed left parietal activity within a broad bilateral dorsal frontoparietal network. Critically, repetitive transcranial magnetic stimulation (rTMS) on participants' peak of activation within the left parietal cortex impaired their ability to generalize learned rules to a structurally analogous new language. No stimulation or rTMS on a nonrelevant brain region did not have the same interfering effect on generalization. Performance on an additional attentional task showed that this rTMS on the parietal site hindered participants' ability to integrate "what" (stimulus identity) and "when" (stimulus timing) information about an expected target. The present findings suggest that learning rules from speech is a two-stage process: following statistical learning, goal-directed attention-involving left parietal regions-integrates "what" and "when" stimulus information to facilitate rapid rule generalization.

Violation of non-adjacent rule dependencies elicits greater attention to a talker's mouth in 15-month-old infants.

Infants start tracking auditory-only non-adjacent dependencies (NAD) between 15 and 18 months of age. Given that audiovisual speech, normally available in a talker's mouth, is perceptually more salient than auditory speech and that it facilitates speech processing and language acquisition, we investigated whether 15-month-old infants' NAD learning is modulated by attention to a talker's mouth. Infants performed an audiovisual NAD learning task while we recorded their selective attention to the eyes, mouth, and face of an actress while she spoke an artificial language that followed an AXB structure (tis-X-bun; nal-X-gor) during familiarization. At test, the actress spoke the same language (grammatical trials; tis-X-bun; nal-X-gor) or a novel one that violated the AXB structure (ungrammatical trials; tis-X-gor; nal-X-bun). Overall, total duration of looking did not differ during the familiar and novel test trials but the time-course of selective attention to the talker's face and mouth revealed that the novel trials maintained infants' attention to the face more than did the familiar trials. Crucially, attention to the mouth increased during the novel test trials while it did not change during the familiar test trials. These results indicate that the multisensory redundancy of audiovisual speech facilitates infants' discrimination of non-adjacent dependencies.

Gray Matter Vulnerabilities Predict Longitudinal Development of Apathy in Huntington's Disease.

BACKGROUND: Apathy, a common neuropsychiatric disturbance in Huntington's disease (HD), is subserved by a complex neurobiological network. However, no study has yet employed a whole-brain approach to examine underlying regional vulnerabilities that may precipitate apathy changes over time. OBJECTIVES: To identify whole-brain gray matter volume (GMV) vulnerabilities that may predict longitudinal apathy development in HD. METHODS: Forty-five HD individuals (31 female) were scanned and evaluated for apathy and other neuropsychiatric features using the short-Problem Behavior Assessment for a maximum total of six longitudinal visits (including baseline). In order to identify regions where changes in GMV may describe changes in apathy, we performed longitudinal voxel-based morphometry (VBM) on those 33 participants with a magnetic resonance imaging (MRI) scan on their second visit at 18 ± 6 months follow-up (78 MRI datasets). We next employed a generalized linear mixed-effects model (N = 45) to elucidate whether initial and specific GMV may predict apathy development over time. RESULTS: Utilizing longitudinal VBM, we revealed a relationship between increases in apathy and specific GMV atrophy in the right middle cingulate cortex (MCC). Furthermore, vulnerability in the right MCC volume at baseline successfully predicted the severity and progression of apathy over time. CONCLUSIONS: This study highlights that individual differences in apathy in HD may be explained by variability in atrophy and initial vulnerabilities in the right MCC, a region implicated in action-initiation. These findings thus serve to facilitate the prediction of an apathetic profile, permitting targeted, time-sensitive interventions in neurodegenerative disease with potential implications in otherwise healthy populations. © 2021 International Parkinson and Movement Disorder Society.

Rethinking attention in time: Expectancy violations reconcile contradictory developmental evidence.

Temporal expectations critically influence perception and action. Previous research reports contradictory results in children's ability to endogenously orient attention in time as well as the developmental course. To reconcile this seemingly conflicting evidence, we put forward the hypothesis that expectancy violations-through the use of invalid trials-are the source of the mixed evidence reported in the literature. With the aim of offering new results that could reconcile previous findings, we tested a group of young children (4- to 7-year-olds), an older group (8- to 12-year-olds), and a group of adults. Temporal cues provided expectations about target onset time, and invalid trials were used such that the target appeared at the unexpected time in 25% of the trials. In both experiments, the younger children responded faster in valid trials than in invalid trials, showing that they benefited from the temporal cue. These results show that young children rely on temporal expectations to orient attention in time endogenously. Importantly, younger children exhibited greater validity effects than older children and adults, and these effects correlated positively with participants' performance in the invalid (unexpected) trials. We interpret the reduction of validity effects with age as an index of better adaptation to the invalid (unexpected) condition. By using invalid trials and testing three age groups, we demonstrate that previous findings are not inconsistent. Rather, evidence converges when considering the presence of expectancy violations that require executive control mechanisms, which develop progressively during childhood. We propose a distinction between rigid and flexible mechanisms of temporal orienting to accommodate all findings.

Targeted Memory Reactivation during Sleep Adaptively Promotes the Strengthening or Weakening of Overlapping Memories.

System memory consolidation is conceptualized as an active process whereby newly encoded memory representations are strengthened through selective memory reactivation during sleep. However, our learning experience is highly overlapping in content (i.e., shares common elements), and memories of these events are organized in an intricate network of overlapping associated events. It remains to be explored whether and how selective memory reactivation during sleep has an impact on these overlapping memories acquired during awake time. Here, we test in a group of adult women and men the prediction that selective memory reactivation during sleep entails the reactivation of associated events and that this may lead the brain to adaptively regulate whether these associated memories are strengthened or pruned from memory networks on the basis of their relative associative strength with the shared element. Our findings demonstrate the existence of efficient regulatory neural mechanisms governing how complex memory networks are shaped during sleep as a function of their associative memory strength.SIGNIFICANCE STATEMENT Numerous studies have demonstrated that system memory consolidation is an active, selective, and sleep-dependent process in which only subsets of new memories become stabilized through their reactivation. However, the learning experience is highly overlapping in content and thus events are encoded in an intricate network of related memories. It remains to be explored whether and how memory reactivation has an impact on overlapping memories acquired during awake time. Here, we show that sleep memory reactivation promotes strengthening and weakening of overlapping memories based on their associative memory strength. These results suggest the existence of an efficient regulatory neural mechanism that avoids the formation of cluttered memory representation of multiple events and promotes stabilization of complex memory networks.

Semantic Congruence Accelerates the Onset of the Neural Signals of Successful Memory Encoding.

As the stream of experience unfolds, our memory system rapidly transforms current inputs into long-lasting meaningful memories. A putative neural mechanism that strongly influences how input elements are transformed into meaningful memory codes relies on the ability to integrate them with existing structures of knowledge or schemas. However, it is not yet clear whether schema-related integration neural mechanisms occur during online encoding. In the current investigation, we examined the encoding-dependent nature of this phenomenon in humans. We showed that actively integrating words with congruent semantic information provided by a category cue enhances memory for words and increases false recall. The memory effect of such active integration with congruent information was robust, even with an interference task occurring right after each encoding word list. In addition, via electroencephalography, we show in 2 separate studies that the onset of the neural signals of successful encoding appeared early (∼400 ms) during the encoding of congruent words. That the neural signals of successful encoding of congruent and incongruent information followed similarly ∼200 ms later suggests that this earlier neural response contributed to memory formation. We propose that the encoding of events that are congruent with readily available contextual semantics can trigger an accelerated onset of the neural mechanisms, supporting the integration of semantic information with the event input. This faster onset would result in a long-lasting and meaningful memory trace for the event but, at the same time, make it difficult to distinguish it from plausible but never encoded events (i.e., related false memories). SIGNIFICANCE STATEMENT: Conceptual or schema congruence has a strong influence on long-term memory. However, the question of whether schema-related integration neural mechanisms occur during online encoding has yet to be clarified. We investigated the neural mechanisms reflecting how the active integration of words with congruent semantic categories enhances memory for words and increases false recall of semantically related words. We analyzed event-related potentials during encoding and showed that the onset of the neural signals of successful encoding appeared early (∼400 ms) during the encoding of congruent words. Our findings indicate that congruent events can trigger an accelerated onset of neural encoding mechanisms supporting the integration of semantic information with the event input.

Reduced striato-cortical and inhibitory transcallosal connectivity in the motor circuit of Huntington's disease patients.

Huntington's disease (HD) is a neurodegenerative disorder which is primarily associated with striatal degeneration. However, the alterations in connectivity of this structure in HD have been underinvestigated. In this study, we analyzed the functional and structural connectivity of the left putamen, while participants performed a finger-tapping task. Using fMRI and DW-MRI, 30 HD gene expansion carriers (HDGEC) and 29 healthy participants were scanned. Psychophysiological interaction analysis and DTI-based tractography were employed to examine functional and structural connectivity, respectively. Manifest HDGEC exhibited a reduced functional connectivity of the left putamen with the left and the right primary sensorimotor areas (SM1). Based on this result, the inhibitory functional connectivity between the left SM1 and the right SM1 was explored, appearing to be also decreased. In addition, the tract connecting these areas (motor corpus callosum), and the tract connecting the left putamen with the left SM1 appeared disrupted in HDGEC compared to controls. Significant correlations were found between measures of functional and structural connectivity of the motor corpus callosum, showing a coupling of both types of alterations in this tract. The observed reduction of functional and structural connectivity was associated with worse motor scores, which highlights the clinical relevance of these results. Hum Brain Mapp 39:54-71, 2018. © 2017 Wiley Periodicals, Inc.

Neuroimaging as a tool to study the sources of phenotypic heterogeneity in Huntington's disease.

PURPOSE OF REVIEW: Huntington's disease is a neurodegenerative disorder characterized by a triad of motor, cognitive and psychiatric disturbances. There is great variability regarding the prominence and evolution of each type of clinical sign. One possible source of phenotypic heterogeneity could be the more prominent degeneration of specific brain circuits. The scope of this review is to highlight the most recent neuroimaging studies that have analysed the relationship between brain changes and motor, cognitive and psychiatric alterations in Huntington's disease. RECENT FINDINGS: The results from recent neuroimaging studies are heterogeneous. Although there is a great overlap between the different regions associated with each symptomatic domain, there is some degree of differentiation. For example, the motor network is associated with motor impairment, whereas the ventral striatum is especially involved in emotional deficits related with psychiatric problems. SUMMARY: Motor, cognitive and psychiatric impairments are associated with structural and functional brain biomarkers. However, the specificity of the regions involved remains unknown, because these studies focused on specific regions and symptoms. In order to tease apart the neural substrates that underlie the phenotypic heterogeneity in Huntington's disease, multivariate approaches combining brain and behavioural measures related to all symptomatic domains should be considered in the future.

Motivated encoding selectively promotes memory for future inconsequential semantically-related events.

Neurobiological models of long-term memory explain how memory for inconsequential events fades, unless these happen before or after other relevant (i.e., rewarding or aversive) or novel events. Recently, it has been shown in humans that retrospective and prospective memories are selectively enhanced if semantically related events are paired with aversive stimuli. However, it remains unclear whether motivating stimuli, as opposed to aversive, have the same effect in humans. Here, participants performed a three phase incidental encoding task where one semantic category was rewarded during the second phase. A memory test 24h after, but not immediately after encoding, revealed that memory for inconsequential items was selectively enhanced only if items from the same category had been previously, but not subsequently, paired with rewards. This result suggests that prospective memory enhancement of reward-related information requires, like previously reported for aversive memories, of a period of memory consolidation. The current findings provide the first empirical evidence in humans that the effects of motivated encoding are selectively and prospectively prolonged over time.

Word learning is mediated by the left arcuate fasciculus.

Human language requires constant learning of new words, leading to the acquisition of an average vocabulary of more than 30,000 words in adult life. The ability to learn new words is highly variable and may rely on the integration between auditory and motor information. Here, we combined diffusion imaging tractography and functional MRI to study whether the strength of anatomical and functional connectivity between auditory and motor language networks is associated with word learning ability. Our results showed that performance in word learning correlates with microstructural properties and strength of functional connectivity of the direct connections between Broca's and Wernicke's territories in the left hemisphere. This study suggests that our ability to learn new words relies on an efficient and fast communication between temporal and frontal areas. The absence of these connections in other animals may explain the unique ability of learning words in humans.

Multiple brain networks underpinning word learning from fluent speech revealed by independent component analysis.

Although neuroimaging studies using standard subtraction-based analysis from functional magnetic resonance imaging (fMRI) have suggested that frontal and temporal regions are involved in word learning from fluent speech, the possible contribution of different brain networks during this type of learning is still largely unknown. Indeed, univariate fMRI analyses cannot identify the full extent of distributed networks that are engaged by a complex task such as word learning. Here we used Independent Component Analysis (ICA) to characterize the different brain networks subserving word learning from an artificial language speech stream. Results were replicated in a second cohort of participants with a different linguistic background. Four spatially independent networks were associated with the task in both cohorts: (i) a dorsal Auditory-Premotor network; (ii) a dorsal Sensory-Motor network; (iii) a dorsal Fronto-Parietal network; and (iv) a ventral Fronto-Temporal network. The level of engagement of these networks varied through the learning period with only the dorsal Auditory-Premotor network being engaged across all blocks. In addition, the connectivity strength of this network in the second block of the learning phase correlated with the individual variability in word learning performance. These findings suggest that: (i) word learning relies on segregated connectivity patterns involving dorsal and ventral networks; and (ii) specifically, the dorsal auditory-premotor network connectivity strength is directly correlated with word learning performance.

ERP evidence of adaptive changes in error processing and attentional control during rhythm synchronization learning.

The ability to detect and use information from errors is essential during the acquisition of new skills. There is now a wealth of evidence about the brain mechanisms involved in error processing. However, the extent to which those mechanisms are engaged during the acquisition of new motor skills remains elusive. Here we examined rhythm synchronization learning across 12 blocks of practice in musically naïve individuals and tracked changes in ERP signals associated with error-monitoring and error-awareness across distinct learning stages. Synchronization performance improved with practice, and performance improvements were accompanied by dynamic changes in ERP components related to error-monitoring and error-awareness. Early in learning, when performance was poor and the internal representations of the rhythms were weaker we observed a larger error-related negativity (ERN) following errors compared to later learning. The larger ERN during early learning likely results from greater conflict between competing motor responses, leading to greater engagement of medial-frontal conflict monitoring processes and attentional control. Later in learning, when performance had improved, we observed a smaller ERN accompanied by an enhancement of a centroparietal positive component resembling the P3. This centroparietal positive component was predictive of participant's performance accuracy, suggesting a relation between error saliency, error awareness and the consolidation of internal templates of the practiced rhythms. Moreover, we showed that during rhythm learning errors led to larger auditory evoked responses related to attention orientation which were triggered automatically and which were independent of the learning stage. The present study provides crucial new information about how the electrophysiological signatures related to error-monitoring and error-awareness change during the acquisition of new skills, extending previous work on error processing and cognitive control mechanisms to a more ecologically valid context.

Atypical language organization in temporal lobe epilepsy revealed by a passive semantic paradigm.

BACKGROUND: Mesial temporal lobe epilepsy (MTLE) is the most common type of focal epilepsy in adults and can be successfully cured by surgery. One of the main complications of this surgery however is a decline in language abilities. The magnitude of this decline is related to the degree of language lateralization to the left hemisphere. Most fMRI paradigms used to determine language dominance in epileptic populations have used active language tasks. Sometimes, these paradigms are too complex and may result in patient underperformance. Only a few studies have used purely passive tasks, such as listening to standard speech. METHODS: In the present study we characterized language lateralization in patients with MTLE using a rapid and passive semantic language task. We used functional magnetic resonance imaging (fMRI) to study 23 patients [12 with Left (LMTLE), 11 with Right mesial temporal lobe epilepsy (RMTLE)] and 19 healthy right-handed controls using a 6 minute long semantic task in which subjects passively listened to groups of sentences (SEN) and pseudo sentences (PSEN). A lateralization index (LI) was computed using a priori regions of interest of the temporal lobe. RESULTS: The LI for the significant contrasts produced activations for all participants in both temporal lobes. 81.8% of RMTLE patients and 79% of healthy individuals had a bilateral language representation for this particular task. However, 50% of LMTLE patients presented an atypical right hemispheric dominance in the LI. More importantly, the degree of right lateralization in LMTLE patients was correlated with the age of epilepsy onset. CONCLUSIONS: The simple, rapid, non-collaboration dependent, passive task described in this study, produces a robust activation in the temporal lobe in both patients and controls and is capable of illustrating a pattern of atypical language organization for LMTLE patients. Furthermore, we observed that the atypical right-lateralization patterns in LMTLE patients was associated to earlier age at epilepsy onset. These results are in line with the idea that early onset of epileptic activity is associated to larger neuroplastic changes.

Disentangling the neurobiological bases of temporal impulsivity in Huntington's disease.

BACKGROUND: Despite its impact on daily life, impulsivity in Huntington's disease (HD) is understudied as a neuropsychiatric symptom. Our aim is to characterize temporal impulsivity in HD and to disentangle the white matter correlate associated with impulsivity. METHODS: Forty-seven HD individuals and 36 healthy controls were scanned and evaluated for temporal impulsivity using a delay-discounting (DD) task and complementary Sensitivity to Punishment and Sensitivity to Reward Questionnaire. Diffusion tensor imaging was employed to characterize the structural connectivity of three limbic tracts: the uncinate fasciculus (UF), the accumbofrontal tract (NAcc-OFC), and the dorsolateral prefrontal cortex connectig the caudate nucleus (DLPFC-cn). Multiple linear regression analyses were applied to analyze the relationship between impulsive behavior and white matter microstructural integrity. RESULTS: Our results revealed altered structural connectivity in the DLPC-cn, the NAcc-OFC and the UF in HD individuals. At the same time, the variability in structural connectivity of these tracts was associated with the individual differences in temporal impulsivity. Specifically, increased structural connectivity in the right NAcc-OFC and reduced connectivity in the left UF were associated with higher temporal impulsivity scores. CONCLUSIONS: The present findings highlight the importance of investigating the spectrum of temporal impulsivity in HD. As, while less prevalent than other psychiatric features, this symptom is still reported to significantly impact the quality of life of patients and caregivers. This study provides evidence that individual differences observed in temporal impulsivity may be explained by variability in limbic frontostriatal tracts, while shedding light on the role of sensitivity to reward in modulating impulsive behavior through the selection of immediate rewards.

Prosodic cues enhance infants' sensitivity to nonadjacent regularities.

In language, grammatical dependencies often hold between items that are not immediately adjacent to each other. Acquiring these nonadjacent dependencies is crucial for learning grammar. However, there are potentially infinitely many dependencies in the language input. How does the infant brain solve this computational learning problem? Here, we demonstrate that while rudimentary sensitivity to nonadjacent regularities may be present relatively early, robust and reliable learning can only be achieved when convergent statistical and perceptual, specifically prosodic cues, are both present, helping the infant brain detect the building blocks that form a nonadjacent dependency. This study contributes to our understanding of the neural foundations of rule learning that pave the way for language acquisition.

Language learning under working memory constraints correlates with microstructural differences in the ventral language pathway.

The present study combined behavioral measures and diffusion tensor imaging to investigate the neuroanatomical basis of language learning in relation to phonological working memory (WM). Participants were exposed to simplified artificial languages under WM constraints. The results underscore the role of the rehearsal subcomponent of WM in successful speech segmentation and rule learning. Moreover, when rehearsal was blocked task performance was correlated to the white matter microstructure of the left ventral pathway connecting frontal and temporal language-related cortical areas through the extreme/external capsule. This ventral pathway may therefore play an important additional role in language learning when the main dorsal pathway-dependent rehearsal mechanisms are not available.

Delineating apathy profiles in Huntington's disease with the short-Lille Apathy Rating Scale.

INTRODUCTION: Apathy, a prevalent feature in neurological disorders including Huntington's disease (HD), is characterized by a reduction in goal-directed behavior across cognitive, auto-activation (i.e., self-activating thoughts/behavior), and emotional domains. Nonetheless, current diagnostic criteria are incapable of distinguishing multidimensional apathy profiles. Meanwhile, the short-Lille Apathy Rating Scale (LARS-s) bears potential as an operative diagnostic tool to disentangle apathy dimensions in clinical practice. The present study thereby examines the psychometric properties and factor structure of the LARS-s to tap into apathy profiles and their underlying neural correlates in HD. METHODS: Forty HD individuals were scanned and evaluated for apathy using the LARS-s, assessed for reliability and validity in HD, and the short-Problem Behavior Assessment (PBA-s). To study the dimensional structure of apathy, principal component analysis (PCA) of the LARS-s was implemented. Resulting factors were associated with gray matter volume through whole-brain voxel-based morphometry. RESULTS: The LARS-s demonstrated satisfactory psychometric properties, sharing convergent validity with PBA-s apathy and discriminant validity against depression. PCA resulted in three factors representative of apathy profiles across cognitive, auto-activation, and emotional domains. Anatomically, global apathy was significantly related with large-scale motor, cognitive, and limbic networks. Exploratory analyses of apathy profiles revealed correspondence between each factor and distinct cortical and subcortical nodes. CONCLUSION: The LARS-s is capable of capturing the multidimensional spectrum of apathy. At the same time, apathy profiles in HD are underpinned by functionally diverse neural networks. Such findings promote the continued study of apathy domains to pinpoint personalized therapeutic targets in neurologic disorders in addition to HD.

Brain dynamics sustaining rapid rule extraction from speech.

Language acquisition is a complex process that requires the synergic involvement of different cognitive functions, which include extracting and storing the words of the language and their embedded rules for progressive acquisition of grammatical information. As has been shown in other fields that study learning processes, synchronization mechanisms between neuronal assemblies might have a key role during language learning. In particular, studying these dynamics may help uncover whether different oscillatory patterns sustain more item-based learning of words and rule-based learning from speech input. Therefore, we tracked the modulation of oscillatory neural activity during the initial exposure to an artificial language, which contained embedded rules. We analyzed both spectral power variations, as a measure of local neuronal ensemble synchronization, as well as phase coherence patterns, as an index of the long-range coordination of these local groups of neurons. Synchronized activity in the gamma band (20-40 Hz), previously reported to be related to the engagement of selective attention, showed a clear dissociation of local power and phase coherence between distant regions. In this frequency range, local synchrony characterized the subjects who were focused on word identification and was accompanied by increased coherence in the theta band (4-8 Hz). Only those subjects who were able to learn the embedded rules showed increased gamma band phase coherence between frontal, temporal, and parietal regions.

Do Bilinguals Outperform Monolinguals in Switching Tasks? Contrary Evidence for Nonlinguistic and Linguistic Switching Tasks.

The benefits of bilingualism in executive functions are highly debated. Even so, in switching tasks, these effects seem robust, although smaller than initially thought (Gunnerud et al., 2020; Ware et al., 2020). By handling two languages throughout their lifespan, bilinguals appear to train their executive functions and show benefits in nonlinguistic switching tasks compared to monolinguals. Nevertheless, because bilinguals need to control for the interference of another language, they may show a disadvantage when dealing with task-switching paradigms requiring language control, particularly when those are performed in their less dominant language. The present work explored this issue by studying bilingualism's effects on task switching within the visual and language domains. On the one hand, our results show that bilinguals were overall faster and presented reduced switch costs compared to monolinguals when performing perceptual geometric judgments with no time for task preparation. On the other hand, no bilingual advantage was found when a new sample of comparable bilinguals and monolinguals completed a within-language switching task. Our results provide clear evidence favoring the bilingual advantage, yet only when the task imposes greater executive demands and does not involve language control.