Biology subjects

Buiatti, M.

Publications and source records attributed to Buiatti, M..

6 recordsLinked to original sources

bioRxiv2026

Neural evidence for an abstract sense of number in humans at birth

One of the most astonishing abilities documented in human newborns is that they can abstract numerosity - the number of items in sets - across sensory modalities. Its underlying neural mechanisms remain unknown. Using high-density EEG and a frequency-tagging paradigm, we measured neural entrainment to periodically presented visual arrays that were either numerically congruent or incongruent with previously familiarized and concurrently presented auditory sequences in 21 newborns (0-3 days old). The amplitude of neural entrainment to the visual arrays provided a robust index of cross-modal numerical congruency: it was significantly reduced for numerically congruent relative to incongruent stimuli, consistent with a cross-modal numerosity repetition-suppression mechanism. These findings identify a candidate neural mechanism supporting newborns ability to encode numerosity in an abstract supramodal format, and reinforce the view that number constitutes a foundational dimension of human perception since birth.

neuroscience↗

bioRxiv2025

A left-to-right bias in spatial numerical associations with dots and symbols

Number and space are intertwined in human and non-human cognition. A substantial body of research has shown that numerical magnitudes are mentally represented along a spatially oriented continuum, akin to a "mental number line". Some suggested that its directionality is determined by culture and context, an idea that was recently challenged by a study that showed that an implicit association between "left" and "small" emerges not only in literate adults, but also in unschooled indigenous adult populations and preschool Western children. This finding suggests that SNAs may originate from universal innate mechanisms rather than being solely a by-product of cultural learning. However, while the study reported a strong association between "left" and "decreasing" numerosity, there was only a very weak association between "right" and "increasing" numerosity. This asymmetry was not predicted and needs further investigation to be understood. Here, we investigated the number/space association in implicit tasks in educated Western adults in greater depth by using more variable and better-controlled stimuli compared to the ones used in the previous study, and also manipulating stimulus format, using both dot patterns and symbolic numbers. Fifty-one adult participants performed a numerical comparison task within a Go-No-Go paradigm on subsequent pairs of visual stimuli (with ratios spanning from 0.75 to 0.94) that could appear on the left or on the right of a fixation point and completed two different tasks: "press when more" and "press when less". Results revealed distinct response patterns depending on the symbolic/non-symbolic nature of the stimuli. When non-symbolic stimuli were used, a consistent association between small numerosities and the left side and large numerosities and the right side was observed. When symbolic stimuli were used, only an association between large numerosities and the right side was observed. These findings support the hypothesis that SNAs may reflect a biological predisposition associated with brain asymmetry and that task demands may interact with the underlying hemispheric specialisations.

neuroscience↗

bioRxiv2024

WTools: a MATLAB-based toolbox for time-frequency analysis

Electroencephalography (EEG) is an established method for investigating neurocognitive functions during human development. In cognitive neuroscience, time-frequency analysis of the EEG is a widely used analytical approach. This paper introduces WTools, a new MATLAB-based toolbox capable of performing time-frequency analysis of EEG signals using complex wavelet transformation. WTools features an intuitive GUI that guides users through the analysis steps, focusing on essential parameters. Being free and open-source, it can be integrated and expanded with new features, making it a handy tool that is growing its popularity in developmental cognitive neuroscience. Here, we provide a detailed description of the WTools algorithm for wavelet transformation and we compare it with state-of-the-art methods implemented in EEGLAB. Alongside the official tool release, we also offer a comprehensive illustrated tutorial to enhance accessibility and promote the transparent and reproducible usage of WTools by the scientific community. HighlightsO_LIWTools is a new MATLAB-based toolbox for time-frequency analysis of the EEG signal C_LIO_LIIt uses wavelet transformation and the algorithm is fully described C_LIO_LIIt is designed to be very user friendly through its simple GUI C_LIO_LIIt is open source and flexible as the code is freely available C_LIO_LIWe provide a step-by-step tutorial and an example dataset to learn the toolbox C_LI

neuroscience↗

bioRxiv2024

Estimating steady-state evoked potentials in the limit of short data duration and low stimulation frequency.

Because of their high signal-to-noise ratio and robustness to artifacts, Steady-State Evoked Potentials (SSEP) - the periodic responses elicited by periodic stimulation designs - are increasingly used in human neuroscience for measuring stimulus-specific brain responses in a short presentation time. While widely applied to measure sensory responses with stimulation frequencies higher than 8 Hz, they are also successful to investigate high-order processes and/or early development characterized by slower time scales, requiring very low stimulation frequencies around 1 Hz. However, applications of these low frequency paradigms on developmental or clinical populations, typically relying on very short data recordings, pose a methodological challenge for SSEP estimation. Here we tackled this challenge by investigating the method of analysis that most efficiently compute SSEP at low stimulation frequencies in the limit of short data, and by estimating the minimum data length necessary to obtain a reliable response. We compared the performance of the three most commonly used measures of SSEP (power spectrum (PS), evoked power spectrum (EPS) and inter-trial coherence (ITC)) at progressively shorter data segments both on simulated data and on EEG responses to on-off checkerboard stimulation at two low frequencies (4 Hz and 0.8 Hz). Results, consistent between simulated and real data, show that while for long data length EPS and ITC outperform PS, for short data length the three measures are equivalent, and the crucial parameter is the length of the sliding window over which each measure is computed: the longer the better for PS and EPS, whereas the opposite occurs for ITC. For the analysed dataset, the shortest data length required to estimate a reliable SSEP is as short as 8 cycles of stimulation, independently from the stimulation frequency. This study provides practical indications for reliable and efficient application of low-frequency SSEP designs on short data recordings.

neuroscience↗

bioRxiv2020

Multiple spatial codes for navigating 2-D semantic spaces

When mammals navigate in the physical environment, specific neurons such as grid-cells, head-direction cells, and place-cells activate to represent the navigable surface, the faced direction of movement, and the specific location the animal is visiting. Here we test the hypothesis that these codes are also activated when humans navigate abstract language-based representational spaces. Human participants learnt the meaning of novel words as arbitrary signs referring to specific artificial audiovisual objects varying in size and sound. Next, they were presented with sequences of words and asked to process them semantically while we recorded the activity of their brain using fMRI. Processing words in sequence was conceivable as movements in the semantic space, thus enabling us to systematically search for the different types of neuronal coding schemes known to represent space during navigation. By applying a combination of representational similarity and fMRI-adaptation analyses, we found evidence of i) a grid-like code in the right postero-medial entorhinal cortex, representing the general bidimensional layout of the novel semantic space; ii) a head-direction-like code in parietal cortex and striatum, representing the faced direction of movements between concepts; and iii) a place-like code in medial prefrontal, orbitofrontal, and mid cingulate cortices, representing the Euclidean distance between concepts. We also found evidence that the brain represents 1-dimensional distances between word meanings along individual sensory dimensions: implied size was encoded in secondary visual areas, and implied sound in Heschls gyrus/Insula. These results reveal that mentally navigating between 2D word meanings is supported by a network of brain regions hosting a variety of spatial codes, partially overlapping with those recruited for navigation in physical space.

neuroscience↗

bioRxiv2018

A cortical route for face-like pattern processing in human newborns

Humans are endowed with an exceptional ability for detecting faces, a competence that in adults is supported by a set of face-specific cortical patches. Human newborns already shortly after birth preferentially orient to faces even when they are presented in the form of highly schematic geometrical patterns, over perceptually equivalent non-face-like stimuli. The neural substrates underlying this early preference are still largely unexplored. Is the adult face-specific cortical circuit already active at birth, or does its specialization develop slowly as a function of experience and/or maturation? We measured EEG responses in 1-4 days old awake, attentive human newborns to schematic face-like patterns and non-face-like control stimuli, visually presented with a slow oscillatory \"peekaboo\" dynamics (0.8 Hz) in a frequency-tagging design. Despite the limited duration of newborns attention, reliable frequency-tagged responses could be estimated for each stimulus from the peak of the EEG power spectrum at the stimulation frequency. Upright face-like stimuli elicited a significantly stronger frequency-tagged response than inverted face-like controls in a large set of electrodes. Source reconstruction of the underlying cortical activity revealed the recruitment of a partially right-lateralized network comprising lateral occipito-temporal and medial parietal areas largely overlapping with the adult face-processing circuit. This result suggests that the cortical route specialized in face processing is already functional at birth.\n\nSignificance statementNewborns show a remarkable ability to detect faces even minutes after birth, an ecologically fundamental skill that is instrumental for interacting with their conspecifics. What are the neural bases of this expertise? Using EEG and a slow oscillatory visual stimulation, we identified a reliable response specific to face-like patterns in newborns, which underlying cortical sources largely overlap with the adult face-specific cortical circuit. This suggests that the development of face perception in infants might rely on an early cortical route specialized in face processing already shortly after birth.

neuroscience↗