Time estimation is critical for survival and control of a variety of behaviors, both in humans and other animals. Time processing in the few hundred milliseconds range, known as millisecond timing, is involved in motor control, speech generation and recognition, and sensorimotor synchronization like playing music or finger tapping to an external beat. In finger tapping, a mechanistic explanation in terms of neuronal activations of how the brain achieves average synchronization against inherent noise and perturbations in the stimulus sequence is still missing despite considerable research. In this work we show that nonlinear effects are important for the recovery of synchronization following a perturbation (a step change in stimulus period), even for perturbation magnitudes smaller than 10% of the period, which is well below the amount of perturbation needed to display other nonlinear effects like saturation. We build a mathematical model for the error correction mechanism and test its predictions, and further propose a framework that allows us to unify the description of the three common types of perturbations and all perturbation magnitudes with a single set of parameter values. While previous works have proposed that multiple mechanisms/strategies are used for correcting different perturbation conditions (based on fitting the model's parameters separately to different perturbation types and sizes), our results suggest that the synchronization behavior can be interpreted as the outcome of a single mechanism/strategy, and call for a revision of the idea of multiple strategies.

BackgroundThe dimensional approach to autism spectrum disorder (ASD) considers ASD as the extreme of a dimension traversing through the entire population. We explored the potential utility of electroencephalography (EEG) functional connectivity as a biomarker. We hypothesized that individual differences in autistic traits of typical subjects would involve a long-range connectivity diminution within the delta band.MethodsResting-state EEG functional connectivity was measured for 74 neurotypical subjects. All participants also provided a questionnaire (Social Responsiveness Scale, SRS) that was completed by an informant who knows the participant in social settings. We conducted multivariate regression between the SRS score and functional connectivity in all EEG frequency bands. We explored modulations of network graph metrics characterizing the optimality of a network using the SRS score.ResultsOur results show a decay in functional connectivity mainly within the delta and theta bands (the lower part of the EEG spectrum) associated with an increasing number of autistic traits. When inspecting the impact of autistic traits on the global organization of the functional network, we found that the optimal properties of the network are inversely related to the number of autistic traits, suggesting that the autistic dimension, throughout the entire population, modulates the efficiency of functional brain networks.ConclusionsEEG functional connectivity at low frequencies and its associated network properties may be associated with some autistic traits in the general population.

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Consolidated memories return to a labile state after the presentation of cues (reminders) associated with acquisition, followed by a period of stabilization (reconsolidation). However not all cues are equally effective in initiating the process, unpredictable cues triggered it, predictable cues do not. We hypothesize that the different effects observed by the different reminder types on memory labilization-reconsolidation depend on a differential neural involvement during reminder presentation. To test it, we developed a declarative task and compared the efficacy of three reminder types in triggering the process in humans (Experiment 1). Finally, we compared the brain activation patterns between the different conditions using functional magnetic resonance imaging (fMRI) (Experiment 2). We confirmed that the unpredictable reminder is the most effective in initiating the labilization-reconsolidation process. Furthermore, only under this condition there was differential left hippocampal activation during its presentation. We suggest that the left hippocampus is detecting the incongruence between actual and past events and allows the memory to be updated.

Learning novel words is a challenging process for our memory systems; we must be able to recall new word forms and meanings in order to communicate. However, the dynamics of the word memory formation is still unclear. Here, we addressed the temporal profile of two key cognitive markers of memory consolidation in the domain of word learning: i) the susceptibility of recently learned novel words to memory interference; ii) their lexical integration using a semantic judgment task while recording the ERPs responses. Young adults acquired a set of novel picture-label-meaning associations. In a first experiment, we performed a temporal gradient of retroactive interference (5 min, 30 min, 4 h and 24 h) and evaluated the memory retention 48 h after learning. In a second experiment, we studied the dynamics of the integration of these novel words, by measuring their N400 modulation when preceded by semantically related words, at 30 min or 48 h after learning. Our results showed that the word-form memory was affected by the interference treatment when it was presented 5 min after learning, but not at later times. On the other hand, only 48 h after learning it was possible to observe a neurophysiological index of semantic-priming (reduced N400 response). These results point to the existence of two contrasting processes that help to build the memory for word forms and meanings. A rapid mechanism would enable word learning while mitigating forgetting, while a slow consolidation would allow the novel meanings to be integrated into previous semantic networks.