Inducing a mental context for associative memory formation with real-time fMRI neurofeedback

Memory, one of the hallmarks of human cognition, can be modified when humans voluntarily modulate neural population activity using neurofeedback. However, it is currently unknown whether neurofeedback can influence the integration of memories, and whether memory is facilitated or impaired after such neural perturbation. In this study, participants memorized objects while we provided them with abstract neurofeedback based on their brain activity patterns in the ventral visual stream. This neurofeedback created an implicit face or house context in the brain while memorizing the objects. The results revealed that participants created associations between each memorized object and its implicit context solely due to the neurofeedback manipulation. Our findings shed light onto how memory formation can be influenced by synthetic memory tags with neurofeedback and advance our understanding of mnemonic processing

The Role of Visual Feedback and Creative Exploration for the Improvement of Timing Accuracy in Performing Musical Ornaments

IN DEVELOPING A VISUAL FEEDBACK SYSTEM FOR A CREATIVE activity such as music performance, the objective is not just to reinforce one particular manner of performing. Instead, a desirable characteristic might be that the visual feedback enhances flexibility and originality, in addition to contributing to performance precision. In an experimental study focused on the timing of a musical ornament, we examined whether the instruction to explore ornament timing in training trials with or without visual feedback leads to improved temporal precision in imitating target performances of the ornament, and whether visual feedback enhances the performance diversity during training. The study uncovered distinct strategies of exploration of the performance of the musical ornament and highlighted the dynamics of exploration behavior during training. Visual feedback enhanced exploration of temporal characteristics and influenced imitation accuracy. This study opens up educational possibilities for the training of performance skills and provides direction for further investigation of creative processes in performance

Multi-PheWAS intersection approach to identify sex differences across comorbidities in 59 140 pediatric patients with autism spectrum disorder

[EN] Objective: To identify differences related to sex and define autism spectrum disorder (ASD) comorbidities female-enriched through a comprehensive multi-PheWAS intersection approach on big, real-world data. Although sex difference is a consistent and recognized feature of ASD, additional clinical correlates could help to identify potential disease subgroups, based on sex and age. Materials and Methods: We performed a systematic comorbidity analysis on 1860 groups of comorbidities exploring all spectrum of known disease, in 59 140 individuals (11 440 females) with ASD from 4 age groups. We explored ASD sex differences in 2 independent real-world datasets, across all potential comorbidities by comparing (1) females with ASD vs males with ASD and (2) females with ASD vs females without ASD. Results: We identified 27 different comorbidities that appeared significantly more frequently in females with ASD. The comorbidities were mostly neurological (eg, epilepsy, odds ratio [OR]>1.8, 3-18 years of age), congenital (eg, chromosomal anomalies, OR>2, 3-18 years of age), and mental disorders (eg, intellectual disability, OR>1.7, 6-18 years of age). Novel comorbidities included endocrine metabolic diseases (eg, failure to thrive, OR=2.5, ages 0-2), digestive disorders (gastroesophageal reflux disease: OR=1.7, 6-11 years of age; and constipation: OR>1.6, 3-11 years of age), and sense organs (strabismus: OR>1.8, 3-18 years of age). Discussion: A multi-PheWAS intersection approach on real-world data as presented in this study uniquely contributes to the growing body of research regarding sex-based comorbidity analysis in ASD population. Conclusions: Our findings provide insights into female-enriched ASD comorbidities that are potentially important in diagnosis, as well as the identification of distinct comorbidity patterns influencing anticipatory treatment or referrals.This work has been supported by the National Institutes of Health BD2K grant U54HG007963. JMZ received grants from Stichting de Drie Lichten and Stichting Sophia Kinderziekenhuis Fonds for a research internship at Harvard Medical School.Gutiérrez-Sacristán, A.; Sáez Silvestre, C.; De Niz, C.; Jalali, N.; Desain, TN.; Kumar, R.; Zachariasse, JM.... (2021). Multi-PheWAS intersection approach to identify sex differences across comorbidities in 59 140 pediatric patients with autism spectrum disorder. Journal of the American Medical Informatics Association. 29(2):230-238. https://doi.org/10.1093/jamia/ocab14423023829

Stress Priming in Reading and the Selective Modulation of Lexical and Sub-Lexical Pathways

Four experiments employed a priming methodology to investigate different mechanisms of stress assignment and how they are modulated by lexical and sub-lexical mechanisms in reading aloud in Italian. Lexical stress is unpredictable in Italian, and requires lexical look-up. The most frequent stress pattern (Dominant) is on the penultimate syllable [laVOro (work)], while stress on the antepenultimate syllable [MAcchina (car)] is relatively less frequent (non-Dominant). Word and pseudoword naming responses primed by words with non-dominant stress – which require whole-word knowledge to be read correctly – were compared to those primed by nonwords. Percentage of errors to words and percentage of dominant stress responses to nonwords were measured. In Experiments 1 and 2 stress errors increased for non-dominant stress words primed by nonwords, as compared to when they were primed by words. The results could be attributed to greater activation of sub-lexical codes, and an associated tendency to assign the dominant stress pattern by default in the nonword prime condition. Alternatively, they may have been the consequence of prosodic priming, inducing more errors on trials in which the stress pattern of primes and targets was not congruent. The two interpretations were investigated in Experiments 3 and 4. The results overall suggested a limited role of the default metrical pattern in word pronunciation, and showed clear effect of prosodic priming, but only when the sub-lexical mechanism prevailed

The Clustering of Expressive Timing Within a Phrase in Classical Piano Performances by Gaussian Mixture Models

In computational musicology research, clustering is a common approach to the analysis of expression. Our research uses mathematical model selection criteria to evaluate the performance of clustered and non-clustered models applied to intra-phrase tempo variations in classical piano performances. By engaging different standardisation methods for the tempo variations and engaging different types of covariance matrices, multiple pieces of performances are used for evaluating the performance of candidate models. The results of tests suggest that the clustered models perform better than the non-clustered models and the original tempo data should be standardised by the mean of tempo within a phrase

A Neurodynamic Account of Spontaneous Behaviour

The current article suggests that deterministic chaos self-organized in cortical dynamics could be responsible for the generation of spontaneous action sequences. Recently, various psychological observations have suggested that humans and primates can learn to extract statistical structures hidden in perceptual sequences experienced during active environmental interactions. Although it has been suggested that such statistical structures involve chunking or compositional primitives, their neuronal implementations in brains have not yet been clarified. Therefore, to reconstruct the phenomena, synthetic neuro-robotics experiments were conducted by using a neural network model, which is characterized by a generative model with intentional states and its multiple timescales dynamics. The experimental results showed that the robot successfully learned to imitate tutored behavioral sequence patterns by extracting the underlying transition probability among primitive actions. An analysis revealed that a set of primitive action patterns was embedded in the fast dynamics part, and the chaotic dynamics of spontaneously sequencing these action primitive patterns was structured in the slow dynamics part, provided that the timescale was adequately set for each part. It was also shown that self-organization of this type of functional hierarchy ensured robust action generation by the robot in its interactions with a noisy environment. This article discusses the correspondence of the synthetic experiments with the known hierarchy of the prefrontal cortex, the supplementary motor area, and the primary motor cortex for action generation. We speculate that deterministic dynamical structures organized in the prefrontal cortex could be essential because they can account for the generation of both intentional behaviors of fixed action sequences and spontaneous behaviors of pseudo-stochastic action sequences by the same mechanism

Expectation in Melody: The Influence of Context and Learning

The Implication-Realization (IR) theory (Narmour, 1990) posits two cognitive systems involved in the generation of melodic expectations: The first consists of a limited number of symbolic rules that are held to be innate and universal; the second reflects the top-down influences of acquired stylistic knowledge. Aspects of both systems have been implemented as quantitative models in research which has yielded empirical support for both components of the theory (Cuddy & Lunny, 1995; Krumhansl, 1995a, 1995b; Schellenberg, 1996, 1997). However, there is also evidence that the implemented bottom-up rules constitute too inflexible a model to account for the influence of the musical experience of the listener and the melodic context in which expectations are elicited. A theory is presented, according to which both bottom-up and top-down descriptions of observed patterns of melodic expectation may be accounted for in terms of the induction of statistical regularities in existing musical repertoires. A computational model that embodies this theory is developed and used to reanalyze existing experimental data on melodic expectancy. The results of three experiments with increasingly complex melodic stimuli demonstrate that this model is capable of accounting for listeners’ expectations as well as or better than the two-factor model of Schellenberg (1997)