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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.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.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.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.

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.

Statistical learning (SL) refers to the ability to extract statistical regularities from the environment. Previous research has suggested that regularity extraction is modality-specific, occurring within but not between sensory modalities (Frost et al., 2015). The present study investigates the circumstances under which SL can occur between modalities. In the first experiment, participants were presented with a stream of meaningless visual fractals and synthetic sounds while performing an oddball detection task. Stimuli were grouped into unimodal (AA, VV) or crossmodal (VA, AV) pairs based on higher transitional probability between the elements. Using implicit and explicit measures of SL, we found that participants only learned the unimodal pairs. In a second experiment, we presented the pairs in separate unimodal (VVVV, AAAA) and crossmodal (AVAV, VAVA) blocks, allowing participants to anticipate which modality would be presented next. We found that SL for the crossmodal pairs outperformed that of unimodal pairs. This result suggests that modality predictability facilitates a correct crossmodal attention deployment that is crucial for learning crossmodal transitional probabilities. Finally, a third experiment demonstrated that participants can explicitly learn the statistical regularities between crossmodal pairs even when the upcoming modality is not predictable, as long as the pairs contain semantic information. This finding suggests that SL between crossmodal pairs can occur when sensory-level limitations are bypassed, and when learning can unfold at a supramodal level of representation. This study demonstrates that SL is not a modality-specific mechanism and compels revision of the current neurobiological model of SL in which learning of statistical regularities between low-level stimuli features relies on hard-wired learning computations that take place in their respective sensory cortices.

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.

BackgroundDespite 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, evaluated through a Delay Discounting (DD) task, and to disentangle the underlying white matter correlates in HD.MethodsForty-seven HD individuals and thirty-six healthy controls conducted a DD task and complementary Sensitivity to Punishment and Sensitivity to Reward (SR) Questionnaire. Diffusion-tensor imaging was employed to characterize the structural connectivity of two limbic tracts: the uncinate fasciculus (UF) and the accumbofrontal tract (NAcc-OFC). Multiple linear regression analyses were applied to analyze the relationship between impulsive behavior and white-matter microstructural integrity.ResultsAltered structural connectivity in both the NAcc-OFC and UF in HD individuals was observed. Moreover, 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 predicted increased temporal impulsivity, while reduced connectivity in the left UF was associated with higher temporal impulsivity scores.LimitationsOther cognitive mechanisms and white matter tracts may play a role in temporal impulsivity.ConclusionsThis study provides evidence that individual differences observed in impulsivity may be explained by variability in limbic fronto-striatal tracts. We emphasize the importance of investigating the spectrum of impulsivity in HD, less prevalent than other psychiatric features, but impacting the quality of life of patients and their caregivers.

Published online: 09 December 2020 The current study examines how monolingual children and bilingual children with languages that are orthotactically similar and dissimilar learn novel words depending on their characteristics. We contrasted word learning for words that violate or respect the orthotactic legality of bilinguals’ languages investigating the impact of the similarity between those two languages. In Experiment 1, three groups of children around the age of 12 were tested: monolinguals, Spanish–Basque bilinguals (orthotactically dissimilar languages), and Spanish–Catalan bilinguals (orthotactically similar languages). After an initial word-learning phase, they were tested in a recognition task. While Spanish monolinguals and Spanish–Catalan bilingual children recognized illegal words worse than legal words, Spanish–Basque bilingual children showed equal performance in learning illegal and legal patterns. In Experiment 2, a replication study was conducted with two new groups of Spanish–Basque children (one group with high Basque proficiency and one group with a lower proficiency) and results indicated that the effects were not driven by the proficiency in the second language, as a similar performance on legal and illegal patterns was observed in both groups. These findings suggest that word learning is not affected by bilingualism as such, but rather depends on the specific language combinations spoken by the bilinguals. This research has been partially funded by Grants PGC2018-097145-B-I00 and RED2018-102615-T from the Spanish Government and H2019/HUM-5705 from the Comunidad de Madrid to J.A.D., by an individual grant from “la Caixa” Foundation (ID 100010434–LCF/BQ/ES16/ 11570003) to M.B., and by Grant Centro de Excelencia Severo Ochoa SEV-2015-0490 by the Spanish government.

Background HD is a suitable model to monitor the whole neurodegeneration process. Huntington’s disease (HD) affects primarily the striatum, but loss of white matter (WM) integrity and iron homeostasis disruption have been also described. These anomalies together with metabolite profiles could unveil the pathophysiologic mechanisms involved. Aims To assess the temporal and spatial progression of neurodegeneration on both anterior thalamic radiations (ATR). Methods Thirty-one HD gene carriers and twenty-four controls underwent neuropsychological evaluation and were scanned at 3T-MRI unit. A multimodal study was conducted to measure relaxometry, diffusivity and spectroscopy as proxies of iron, WM microstructure and metabolite composition, respectively. Three statistical approaches (average, segmental, along-the-tract) were performed, with MANOVA and post-hoc Tukey test to evaluate differences among groups and Pearson test to assess correlations. Results ATR disintegration began in premanifest individuals and progressed in extent and severity in manifest patients. WM damage was more extensive in the right ATR that could translate a higher vulnerability and showed a spatial gradient from subcortical to deep WM in favour of the dying-back hypothesis. Iron was increased in the left ATR in premanifest individuals that might uncover a dysregulated myelination or an abnormal ferritin accumulation. NAA and creatine decreased exclusively in manifest patients suggesting neuronal loss and mitochondrial dysfunction. Furthermore, imaging parameters could be used as biomarkers given their links with clinical scores. Conclusions The complex neurodegeneration pattern of ATR in HD can help to understand the pathophysiological mechanisms underlying HD progression. The multimodal approach and along-the-tract analysis allow for a more comprehensive evaluation of neurodegeneration.

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 statistical learning of language rules combined with computational modelling to show that online SL responds to reinforcement learning principles rooted in striatal function. Specifically, we demonstrate - on two 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 longstanding gap between language learning and reinforcement learning phenomena.

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. (c) 2021 International Parkinson and Movement Disorder Society

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.

The ability to extract regularities from the environment is arguably an adaptive characteristic of intelligent systems. In the context of speech, statistical learning is thought to be an important mechanism for language acquisition. By considering individual differences in speech auditory-motor synchronization, an independent component analysis of fMRI data revealed that the neural substrates of statistical word form learning are not fully shared across individuals. While a network of auditory and superior pre/motor regions is universally activated in the process of learning, a fronto-parietal network is instead additionally and selectively engaged by some individuals, boosting their performance. Furthermore, interfering with the use of this network via articulatory suppression (producing irrelevant speech during learning) normalizes performance across the entire sample. Our work provides novel insights on language-related statistical learning and reconciles previous contrasting findings, while highlighting the need to factor in fundamental individual differences for a precise characterization of cognitive phenomena.

Cognitive decline accompanying the clinically more salient motor symptoms of Hunting- ton's disease (HD) has been widely noted and can precede motor symptoms onset. Less clear is how such decline bears on language functions in everyday life, though a small number of experimental studies have revealed difficulties with the application of rule- based aspects of language in early stages of the disease. Here we aimed to determine whether there is a systematic linguistic profile that characterizes spontaneous narrative speech in both pre-manifest and/or early manifest HD, and how it is related to striatal degeneration and neuropsychological profiles. Twenty-eight early-stage patients (19 manifest and 9 gene-carriers in the pre-manifest stage), matched with 28 controls, participated in a story-telling task. Speech was blindly scored by independent raters ac- cording to fine-grained linguistic variables distributed over 5 domains for which composite scores were computed (Quantitative, Fluency, Reference, Connectivity, and Concordance). Voxel-based morphometry (VBM) was used to link specific brain degeneration patterns to loci of linguistic decline. In all of these domains, significant differences were observed between groups. Deficits in Reference and Connectivity were seen in the pre-manifest stage, where no other neuropsychological impairment was detected. Among HD patients, there was a significant positive correlation only between the values in the Quantitative domain and gray matter volume bilaterally in the putamen and pallidum. These results fill the gap of qualitative data of spontaneous narrative speech in HD and reveal that HD is characterized by systematic linguistic impairments leading to dysfluencies and disorga- nization in core domains of grammatical organization. This includes the referential use of noun phrases and the embedding of clauses, which mediate crucial dimensions of meaning in language in its normal social use. Moreover, such impairment is seen prior to motor symptoms onset and when standardized neuropsychological test profiles are otherwise normal

En una nueva lengua, aprender palabras es más fácil que aprender las reglas que las combinan. ¿Las aprenderemos mejor si nos focalizamos más en ellas? Mediante un paradigma artificial de aprendizaje de reglas creamos distintas condiciones de forma que hubiese reglas más atendidas que otras. Los resultados mostraron que la atención no afecta al aprendizaje implícito (automático) de las reglas, pero el conocimiento explícito (más consciente) sí difiere en función de la cantidad de atención prestada. La atención potencia la adquisición de un conocimiento más específico sobre la regla, aunque el conocimiento más abstracto sobre el orden de las palabras se aprende independientemente de la atención prestada.

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.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.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.

The ability to pick out a unique entity with a proper name is an important component of human language. It has been a primary focus of research in the philosophy of language since the nineteenth century. Brain-based evidence has shed new light on this capacity, and an extensive literature indicates the involvement of distinct fronto-temporal and temporo-occipito-parietal association cortices in proper-name retrieval. However, comparatively few efforts have sought to explain how memory encoding processes lead to the later recruitment of these distinct regions at retrieval. Here, we provide a unified account of proper-name encoding and retrieval, reviewing evidence that socio-emotional and unitized encoding subserve the retrieval of proper names via anterior-temporal-prefrontal activations. Meanwhile, non-unitized item-item and item-context encoding support subsequent retrieval, largely dependent on the temporo-occipito-parietal cortex. We contend that this well-established divergence in encoding systems can explain how proper names are later retrieved from distinct neural structures. Furthermore, we explore how evidence reviewed here can inform a century-and-a-half-old debate about proper names and the meanings they pick out.

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., European Research Council (ERC), Spanish Ministerio de Ciencia e Innovacio PRIME RdD-B, European Research Council (ERC) 727595, Juan de la Cierva Post-Doctorate Fellowship JCI-2012-12335, Ministerio de Economia y Competividad

We introduce a deceptively simple behavioral task that robustly identifies two qualitatively different groups within the general population. When presented with an isochronous train of random syllables, some listeners are compelled to align their own concurrent syllable production with the perceived rate, whereas others remain impervious to the external rhythm. Using both neurophysiological and structural imaging approaches, we show group differences with clear consequences for speech processing and language learning. When listening passively to speech, high synchronizers show increased brain-to-stimulus synchronization over frontal areas, and this localized pattern correlates with precise microstructural differences in the white matter pathways connecting frontal to auditory regions. Finally, the data expose a mechanism that underpins performance on an ecologically relevant word-learning task. We suggest that this task will help to better understand and characterize individual performance in speech processing and language learning. A simple behavioral task identifies two qualitatively different groups within the general population, according to their speech-to-speech synchronization abilities. Group pertinence predicts brain function and anatomy, as well as word-learning performance.

Background: Apathy is the neuropsychiatric syndrome that correlates most highly with Huntington's disease progression, and, like early patterns of neurodegeneration, is associated with lesions to cortico-striatal connections. However, due to its multidimensional nature and elusive etiology, treatment options are limited. Objectives: To disentangle underlying white matter microstructural correlates across the apathy spectrum in Huntington's disease. Methods: Forty-six Huntington's disease individuals (premanifest (N = 22) and manifest (N = 24)) and 35 healthy controls were scanned at 3-tesla and underwent apathy evaluation using the short-Problem Behavior Assessment and short-Lille Apathy Rating Scale, with the latter being characterized into three apathy domains, namely emotional, cognitive, and auto-activation deficit. Diffusion tensor imaging was used to study whether individual differences in specific cortico-striatal tracts predicted global apathy and its subdomains. Results: We elucidate that apathy profiles may develop along differential timelines, with the auto-activation deficit domain manifesting prior to motor onset. Furthermore, diffusion tensor imaging revealed that inter-individual variability in the disruption of discrete cortico-striatal tracts might explain the heterogeneous severity of apathy profiles. Specifically, higher levels of auto-activation deficit symptoms significantly correlated with increased mean diffusivity in the right uncinate fasciculus. Conversely, those with severe cognitive apathy demonstrated increased mean diffusivity in the right frontostriatal tract and left dorsolateral prefrontal cortex to caudate nucleus tract. Conclusions: The current study provides evidence that white matter correlates associated with emotional, cognitive, and auto-activation subtypes may elucidate the heterogeneous nature of apathy in Huntington's disease, as such opening a door for individualized pharmacological management of apathy as a multidimensional syndrome in other neurodegenerative disorders. Keywords: Apathy, Diffusion MRI, Huntington's disease, Individual differences, Neurodegeneration, White matter microstructure

Introduction It has long been posited that threat learning operates and forms under an affective and a cognitive learning system that is supported by different brain circuits. A primary drawback in exposure‐based therapies is the high rate of relapse that occurs when higher order areas fail to inhibit responses driven by the defensive circuit. It has been shown that implicit exposure of fearful stimuli leads to a long‐lasting reduction in avoidance behavior in patients with phobia. Despite the potential benefits of this approach in the treatment of phobias and posttraumatic stress disorder, implicit extinction is still underinvestigated. Methods Two groups of healthy participants were threat conditioned. The following day, extinction training was conducted using a stereoscope. One group of participants was explicitly exposed with the threat‐conditioned image, while the other group was implicitly exposed using a continuous flash suppression (CFS) technique. On the third day, we tested the spontaneous recovery of defensive responses using explicit presentations of the images. Results On the third day, we found that only the implicit extinction group showed reduced spontaneous recovery of defensive responses to the threat‐conditioned stimulus, measured by threat‐potentiated startle responses but not by the electrodermal activity. Conclusion Our results suggest that implicit extinction using CFS might facilitate the modulation of the affective component of fearful memories, attenuating its expression after 24 hr. The limitations of the CFS technique using threatful stimuli urge the development of new strategies to improve implicit presentations and circumvent such limitations. Our study encourages further investigations of implicit extinction as a potential therapeutic target to further advance exposure‐based psychotherapies.

It has long been posited that threat learning operates and forms under an affective and a cognitive learning system that are supported by different brain circuits. A primary drawback in exposure-based therapies is the high rate of relapse when higher order inhibitory structures failed to inhibit the emotional responses driven by the defensive circuit. It has been shown that implicit exposure of fearful stimuli leads to a long-lasting reduction of avoidance behavior in patients with phobia through the facilitation of fear processing areas in the absence of subjective fear. Despite the potential benefits of this approach in the treatment of phobias and PTSD, implicit exposure to fearful stimuli is still under-investigated. Here, we used unconscious presentation of threat-conditioned stimuli in healthy humans, using a continuous flash suppression technique. We found that implicit exposure of a conditioned stimulus reduced, on the following day, defensive responses to the conditioned stimulus measured by threat-potentiated startle responses but not by the electrodermal activity. Our results suggest that implicit exposure using CFS might facilitate the modulation of the affective component of fearful memories, representing an important therapeutic target to further advance exposure-based psychotherapies.

Highlights • Amount of attention to rules during artificial language learning was manipulated. • Indirect measures showed incidental rule learning irrespective of attention. • Explicit knowledge after learning was affected by the amount of attention. • The amount of attention at encoding did not affect consolidation after sleep., Incidental learning plays a crucial role in the initial phases of language acquisition. However the knowledge derived from implicit learning, which is based on prediction-based mechanisms, may become explicit. The role that attention plays in the formation of implicit and explicit knowledge of the learned material is unclear. In the present study, we investigated the role that attention plays in the acquisition of non-adjacent rule learning from speech. In addition, we also tested whether the amount of attention during learning changes the representation of the learned material after a 24 h delay containing sleep. For that, we developed an experiment run on two consecutive days consisting on the exposure to an artificial language that contained non-adjacent dependencies (rules) between words whereas different conditions were established to manipulate the amount of attention given to the rules (target and non-target conditions). Furthermore, we used both indirect and direct measures of learning that are more sensitive to implicit and explicit knowledge, respectively. Whereas the indirect measures indicated that learning of the rules occurred regardless of attention, more explicit judgments after learning showed differences in the type of learning reached under the two attention conditions. 24 hours later, indirect measures showed no further improvements during additional language exposure and explicit judgments indicated that only the information more robustly learned in the previous day, was consolidated.

Electric stimulation mapping (ESM) is frequently used during brain surgery to localise higher cognitive functions to avoid post-chirurgical disabilities. Experiments with brain imaging techniques and neuropsychological studies showed differences in the cortical representation and processing of nouns and verbs. The goal of the present study was to investigate whether electric stimulation in specific sites in the frontal cortex disrupted noun and verb production selectively. We found that most of the stimulated areas showed disruption of both verbs and nouns at the inferior frontal gyrus. However, when selective effects were obtained, verbs were more prone to disruption than nouns with important individual differences. The overall results indicate that selective impairments can be observed at inferior and middle frontal regions and the action naming task seems to be more suitable to avoid post-chirurgical language disabilities, as it shows a greater sensitivity to disruption with ESM than the classical object naming task.

A cognitive stimulating lifestyle has been observed to confer cognitive benefits in multiple neurodegenerative diseases. However, the underlying neurobiological basis of this phenomenon remains unclear. Huntington's disease can provide a suitable model to study the effects and neural mechanisms of cognitive engagement in neurodegeneration. In this study, we investigate the effect of lifestyle factors such as education, occupation and engagement in cognitive activities in Huntington's disease gene carriers on cognitive performance and age of onset as well as the underlying neural changes sustaining these effects, measured by magnetic resonance imaging. Specifically, we analyzed both gray matter volume and the strength of connectivity of the executive control resting-state network. High levels of cognitive engagement were significantly associated with more preserved executive functions, a delay in the appearance of symptoms, reduced volume loss of the left precuneus and the bilateral caudate and a modulation of connectivity strength of anterior cingulate cortex and left angular gyrus with the executive control network. These findings suggest that a cognitively stimulating lifestyle may promote brain maintenance by modulating the executive control resting-state network and conferring protection against neurodegeneration, which results in a delayed onset of symptoms and improved performance in executive functions.

We studied the initial acquisition and overnight consolidation of new spoken words that resemble words in the native language (L1) or in an unfamiliar, non-native language (L2). Spanish-speaking participants learned the spoken forms of novel words in their native language (Spanish) or in a different language (Hungarian), which were paired with pictures of familiar or unfamiliar objects, or no picture. We thereby assessed, in a factorial way, the impact of existing knowledge (schema) on word learning by manipulating both semantic (familiar vs unfamiliar objects) and phonological (L1- vs L2-like novel words) familiarity. Participants were trained and tested with a 12-hr intervening period that included overnight sleep or daytime awake. Our results showed (1) benefits of sleep to recognition memory that were greater for words with L2-like phonology and (2) that learned associations with familiar but not unfamiliar pictures enhanced recognition memory for novel words. Implications for complementary systems accounts of word learning are discussed.

Podeu consultar dades primàries associades a l'article a: http://hdl.handle.net/2445/113258, Anticipating both where and when an object will appear is a critical ability for adaptation. Research in the temporal domain in adults indicate that dissociable mechanisms relate to endogenous attention driven by the properties of the stimulus themselves (e.g. rhythmic, sequential, or trajectory cues) and driven by symbolic cues. In infancy, we know that the capacity to endogenously orient attention progressively develops through infancy. However, the above-mentioned distinction has not yet been explored since previous studies involved stimulus-driven cues. The current study tested 12- and 15-month-olds in an adaptation of the anticipatory eye movement procedure to determine whether infants were able to anticipate a specific location and temporal interval predicted only by symbolic pre-cues. In the absence of stimulus-driven cues, results show that only 15-month-olds could show anticipatory behavior based on the temporal information provided by the symbolic cues. Distinguishing stimulus-driven expectations from those driven by symbolic cues allowed dissecting more clearly the developmental progression of temporal endogenous attention.

La capacidad humana para aprender nuevas palabras es muy variable. En este trabajo mostramos que dicho aprendizaje se basa en una eficiente comunicación entre las regiones cerebrales que controlan el movimiento y las que procesan la información auditiva. Además, esta conexión anatómica, que tiene lugar a través del fascículo arqueado en el hemisferio izquierdo, no está igualmente desarrollada en todas las personas, lo que explicaría las diferencias individuales que existen a la hora de aprender las palabras de una lengua.

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.

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 STATEMENTConceptual 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.

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.