Biology subjects

Ioannucci, S.

Publications and source records attributed to Ioannucci, S..

4 recordsLinked to original sources

bioRxiv2026

Decoding the ''bouba-kiki'' effect in early visual cortex

The "bouba-kiki" effect, or sound symbolism, is the non-arbitrary mapping between speech sounds and visual shapes, in which words like "bouba" are consistently associated with round shapes, and "kiki" with spiky shapes. Despite robust behavioral evidence for sound symbolic associations, it is still unclear whether they are a linguistic epiphenomenon or manifest themselves as distinct sensory representations in the human brain. Using fMRI and multivariate pattern analyses, we show that, in the absence of visual input, round and spiky sound symbolic words elicit distinct neural representations, not only in auditory and speech processing regions, but also in parietal and even early visual cortex including V1. These neural representations correlate with behavioural shape judgements of sound-symbolic words, as revealed by representational similarity analyses. Our findings suggest a potential functional mechanism for sound symbolism: phonological features of sound symbolic words are represented in auditory and speech processing regions and linked to cross-modal shape representations in parietal and early visual regions, which in turn lead to sound symbolic perceptual judgements. Thus, our results provide evidence for a neural mechanism underlying the "bouba-kiki" effect in the human brain.

neuroscience↗

bioRxiv2024

Benchmarking Stroke Outcome Prediction through Comprehensive Data Analysis - NeuralCup 2023

Stroke remains a leading cause of mortality and long-term disability worldwide, with variable recovery trajectories posing substantial challenges in anticipating post-event care and rehabilitation planning. To address these challenges, we established the NeuralCup consortium to benchmark predictive models of stroke outcome through a collaborative, data-driven approach. This study presents findings from 15 international teams who used a comprehensive dataset including clinical and imaging data, to identify and compare predictors of motor, cognitive, and emotional outcomes one year post-stroke. Our analyses integrated traditional statistical approaches and novel machine learning algorithms to uncover optimal recipes for predicting each domain. The differences in these optimal recipes reflect distinct brain mechanisms in response to different tasks. Key predictors across all domains included infarct characteristics, T1-weighted MRI sequences, and demographic factors. Additionally, integrating FLAIR imaging and white matter tract analysis significantly improved the prediction of cognitive and motor outcomes, respectively. These findings support a multifaceted approach to stroke outcome prediction, underscoring the potential of collaborative data science to develop personalized care strategies that enhance recovery and quality of life for stroke survivors. To encourage further model development and validation, we provide access to the training dataset at http://neuralcup.bcblab.com

neuroscience↗

bioRxiv2020

Neural fatigue by passive induction

Theories of mental fatigue disagree on whether performance decrement is caused by motivational or functional alterations. We tested the assumption that keeping neural networks active for an extensive period of time entrains consequences at the subjective and objective level - the defining characteristics of fatigue - when confounds such as motivation, boredom and level of skill are controlled. We reveal that passive visual stimulation affects the performance of a subsequent task that is carried out in the same portion of visual space. This outcome, consisting either in an enhancement or deterioration of performance, was determined by the participants level of cognitive load and arousal, which were manipulated through variations in the difficulty of concurrent auditory tasks. Thus, repeated stimulation of neural networks leads to their altered functional performance, a mechanism which may play a role in the development of global mental fatigue.

neuroscience↗

bioRxiv2017

White matter correlates of hemi-face dominance in emotional expression

The neural underpinnings of human emotional expression are thought to be unevenly distributed among the two brain hemispheres. However, little is known on the anatomy supporting this claim, particularly in the cerebral white matter. Here, we explored the relationship between hemi-face dominance in emotional expression and cerebral white matter asymmetries in 33 healthy participants. Measures of emotional expression were derived from pictures of the participants faces in a happy smiling and a sad frowning conditions. Chimeric faces were constructed by mirroring right and left hemi-faces, as done in previous studies, resulting in a left mirrored and right mirrored chimeric face per picture. To gain measures of hemi-face dominance per participant, a jury of 20 additional participants rated which chimeric face shows higher intensity of emotional expressivity, by marking a 155mm line between the two versions. Measures of the asymmetry of the uncinate, the cingulum and the three branches of superior longitudinal fasciculi were derived from diffusion weighted imaging tractography dissections. Group effect analyses indicated that the degree of asymmetry in emotional expression was not as prominent as reported in the literature and showed a large inter-individual variability. The degree of asymmetry in emotional expression was, however, significantly associated with the asymmetries in connective properties of the fronto-temporal and fronto-parietal tracts, specifically the uncinate fasciculus and the first branch of the superior longitudinal fasciculus. Therefore, this result raises novel hypotheses on the relationship of specific white matter tracts and emotional expression, especially their role in mood disorders. Ethical statementO_LINone of the authors have a conflict of interest C_LIO_LIData collection from human participants was approved by the Comite de Protection des Personnes "CPP Ile de France V" C_LIO_LIAll participants provided written informed consent C_LIO_LIFunding from ERC (grant agreement No. 818521) and "Agence Nationale de la Recherche" [grants numbers ANR-13-JSV4-0001-01 an ANR-10-IAIHU-06] C_LI

neuroscience↗