Publications by authors named "Ana Flo"

Networks are a useful mathematical tool for capturing the complexity of the world. In a previous behavioral study, we showed that human adults were sensitive to the high-level network structure underlying auditory sequences, even when presented with incomplete information. Their performance was best explained by a mathematical model compatible with associative learning principles, based on the integration of the transition probabilities between adjacent and nonadjacent elements with a memory decay.

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Successive auditory inputs are rarely independent, their relationships ranging from local transitions between elements to hierarchical and nested representations. In many situations, humans retrieve these dependencies even from limited datasets. However, this learning at multiple scale levels is poorly understood.

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Since speech is a continuous stream with no systematic boundaries between words, how do pre-verbal infants manage to discover words? A proposed solution is that they might use the transitional probability between adjacent syllables, which drops at word boundaries. Here, we tested the limits of this mechanism by increasing the size of the word-unit to four syllables, and its automaticity by testing asleep neonates. Using markers of statistical learning in neonates' EEG, compared to adult behavioral performances in the same task, we confirmed that statistical learning is automatic enough to be efficient even in sleeping neonates.

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Electroencephalography (EEG) is a non-invasive and painless recording of cerebral activity, particularly well-suited for studying young infants, allowing the inspection of cerebral responses in a constellation of different ways. Of particular interest for developmental cognitive neuroscientists is the use of rhythmic stimulation, and the analysis of steady-state evoked potentials (SS-EPs) - an approach also known as frequency tagging. In this paper we rely on the existing SS-EP early developmental literature to illustrate the important advantages of SS-EPs for studying the developing brain.

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Extracting statistical regularities from the environment is a primary learning mechanism that might support language acquisition. While it has been shown that infants are sensitive to transition probabilities between syllables in speech, it is still not known what information they encode. Here we used electrophysiology to study how full-term neonates process an artificial language constructed by randomly concatenating four pseudo-words and what information they retain after a few minutes of exposure.

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Infant electroencephalography (EEG) presents several challenges compared with adult data: recordings are typically short and heavily contaminated by motion artifacts, and the signal changes throughout development. Traditional data preprocessing pipelines, developed mainly for event-related potential analyses, require manual steps. However, larger datasets make this strategy infeasible.

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Creating invariant representations from an everchanging speech signal is a major challenge for the human brain. Such an ability is particularly crucial for preverbal infants who must discover the phonological, lexical, and syntactic regularities of an extremely inconsistent signal in order to acquire language. Within the visual domain, an efficient neural solution to overcome variability consists in factorizing the input into a reduced set of orthogonal components.

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Periodic and stable sensory input can result in rhythmic and stable neural responses, a phenomenon commonly referred to as neural entrainment. Although the use of neural entrainment to investigate the regularities the brain tracks has increased in recent years, the methods used for its quantification are not well-defined in the literature. Here we argue that some strategies used in previous papers, are inadequate for the study of steady-state response, and lead to methodological artefacts.

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One of the prominent ideas developed by Jacques Mehler and his colleagues was that perceptual tuning, present from birth on, enables infants, and language learners in general, to extract regularities from speech input. Here we discuss language learners'' ability to extract basic word order (VO or OV) structure from prosodic regularities in a language. The two are closely related: in phonological phrases of VO languages, the most prominent word is the rightmost one, and in OV languages, it is the leftmost one.

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Infants' capacity to extract statistical regularities from sequential information is impressive and well documented. However, statistical learning's underlying mechanism remains mostly unknown, and its role in language acquisition is still under debate. To shed light on these issues, here we address the question of which information human subjects extract and encode after familiarisation with a continuous sequence of stimuli and its dependence on the type of segmentation cues and on the stimuli modality.

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Before infants can learn words, they must identify those words in continuous speech. Yet, the speech signal lacks obvious boundary markers, which poses a potential problem for language acquisition (Swingley, Philos Trans R Soc Lond. Series B, Biol Sci 364(1536), 3617-3632, 2009).

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By exploiting a multichannel portable instrument for time-domain near-infrared spectroscopy (TD-NIRS), we characterized healthy neonates' brains in term of optical properties and hemodynamic parameters. In particular, we assessed the absolute values of the absorption and reduced scattering coefficients at two wavelengths, together with oxy-, deoxy- and total hemoglobin concentrations, and the blood oxygen saturation of the neonates' brains. In this study, 33 healthy full-term neonates were tested, obtaining the following median values: 0.

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UV rays may cause several degrees of skin damage, which makes sunscreen research necessary. In addition, skin sensitivity shows daily variations, which can interfere in the detection of the efficacy of the filters. Here, we studied the UV-induced erythema in hairless rats at two times of the day (light and darkness) using a colorimeter method.

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Melatonin is a neurohormone with multiple and different actions, such as chronobiotic or antioxidant. Melatonin is usually orally administered, but dermal administration is also useful in dermatological diseases or as adjuvant to certain skin treatments. Here, we studied the variability of the pharmacokinetics of melatonin and its metabolite AFMK, when melatonin is transdermally administered to Hairless rat at two different times of day (Zeitgeber Time 4 (ZT4) and ZT16).

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Purpose: Melatonin (MLT) could be candidate drug for treatment of several diseases because of its high antioxidant and anticarcinogenic activity and its important biological roles. The aim of this study was to assess the influence of different vehicles on the permeation of MLT through buccal and skin tissues.

Methods: Formulations were characterized in terms of rheology, drug release and permeation through human skin as well as porcine buccal mucosa.

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To understand language, humans must encode information from rapid, sequential streams of syllables - tracking their order and organizing them into words, phrases, and sentences. We used Near-Infrared Spectroscopy (NIRS) to determine whether human neonates are born with the capacity to track the positions of syllables in multisyllabic sequences. After familiarization with a six-syllable sequence, the neonate brain responded to the change (as shown by an increase in oxy-hemoglobin) when the two edge syllables switched positions but not when two middle syllables switched positions (Experiment 1), indicating that they encoded the syllables at the edges of sequences better than those in the middle.

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Circadian rhythms are present in most functions of living beings. We have demonstrated the presence of circadian rhythms in skin variables (transepidermal water loss, TEWL; stratum corneum hydration, SCH; and skin temperature) in hairless rats under different environmental conditions of light and temperature. Circadian rhythms in TEWL and SCH showed mean amplitudes of about 20% and 14% around the mean, respectively, and appeared under light-dark cycles as well as under constant darkness.

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Savings is a fundamental property of learning. In motor adaptation, it refers to the improvement in learning observed when adaptation to a perturbation A (A1) is followed by re-adaptation to the same perturbation (A2). A common procedure to equate the initial level of error across sessions consists of restoring native sensorimotor coordinates by inserting null--unperturbed--trials (N) just before re-adaptation (washout).

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