We use psychophysics and neuroimaging (fMRI, M-EEG) in adults and children of different cultures and cognitive skills to study the relation between perception and symbolic cognition. Our research spans over two main areas: (1) semantic spaces and navigation, and (2) math skills and quantity processing. See a brief description of our work as well as some selected publications below:
(1) Semantic spaces and navigation
Description: we study how the meaning of concrete words is constructed, stored and retrieved. We use imaging and behavioral methods to test the hypothesis that word meaning is an emergent property of the simultaneous re-activation of both isolated and conjoint features of the objects implied by words. In our recent research, first we have shown that individual features defining the meaning of concrete words (e.g. single dimensions of the semantic space) are represented in sensory-specific cortical regions, and that they emerge very early (by 200 ms) and in parallel during word reading. Then we have shown that that different features of the semantic space are integrated in the brain and represented through a grid-like, a distance-dependent, and a direction-specific code within the same brain circuits that support spatial navigation (the entorhinal cortex, VPFC, RSC, ...).
People: M. Piazza
Collaborators: S. Viganò, M.Buiatti, V.Rubino
S. Viganò, V. Rubino, A. Di Soccio, M. Buiatti, & M. Piazza (2021). NeuroImage, 232 (2021), 117876
Relational information about items in memory is thought to be represented in our brain thanks to an internal comprehensive model, also referred to as a “cognitive map ”. In the human neuroimaging literature, two signatures of bi-dimensional cognitive maps have been reported: the grid-like code and the distance-dependent code. While these kinds of representation were previously observed during spatial navigation and, more recently, during processing of perceptual stimuli, it is still an open question whether they also underlie the representation of the most basic items of language: words. Here we taught human participants the meaning of novel words as arbitrary labels for a set of audiovisual objects varying orthogonally in size and sound. The novel words were therefore conceivable as points in a navigable 2D map of meaning. While subjects performed a word comparison task, we recorded their brain activity using functional magnetic resonance imaging (fMRI). 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 relative angular positions of words in the word space, and (ii) a distance-dependent code, in medial prefrontal, orbitofrontal, and mid-cingulate cortices, representing the Euclidean distance between words. Additionally, we found evidence that the brain also separately represents the single dimensions of word meaning: their implied size, encoded in visual areas, and their implied sound, in Heschl’s gyrus/Insula. These results support the idea that the meaning of words, when they are organized along two dimensions, is represented in the human brain across multiple maps of different dimensionality.
Figure 1: Stimulus space and experimental design
Figure 2: Grid-Like code, model, analyses (model-based RSA), and results
Figure 3: Distance code, model, analyses (fMRI adaptation), results
V. Borghesani, F. Pedregosa, A. Amadon, E. Eger, M. Buiatti, & M. Piazza. (2016). NeuroImage. 143, 128-140.
The meaning of words referring to concrete items is thought of as a multidimensional representation that includes both perceptual (e.g., average size, prototypical color) and conceptual (e.g., taxonomic class) dimensions. Are these different dimensions coded in different brain regions? In healthy human subjects, we tested the presence of a mapping between the implied real object size (a perceptual dimension) and the taxonomic categories at different levels of specificity (conceptual dimensions) of a series of words, and the patterns of brain activity recorded with functional magnetic resonance imaging in six areas along the ventral occipito–temporal cortical path. Combining multivariate pattern classification and representational similarity analysis, we found that the real object size implied by a word appears to be primarily encoded in early visual regions, while the taxonomic category and sub-categorical cluster in more anterior temporal regions. This anteroposterior gradient of information content indicates that different areas along the ventral stream encode complementary dimensions of the semantic space.
(2) Math skills and quantity processing
Description: Humans share with other animals the ability to extract and mentally represent discrete (number) and continuous (area, density) quantities from their physical environment. We study those skills, their neuronal correlates, their development, and their role in grounding higher level cognitive skills, such as formal symbolic maths. We also study dyscalculia with the aim of understanding whether and how impaired perceptual quantity-related skills may hinder the ability to properly acquire knowledge and skills in symbolic number processing.
People: M. Piazza, A. Karami, E. Eccher, M. Amalric
Collaborations: S. Dehaene, E. Eger, V. Izard, D. Hyde, G.Decarli
M. Piazza, V. De Feo, S. Panzeri, and S. Dehaene. (2018). Cognition, 181, 35-45.
With age and education, children become increasingly accurate in processing numerosity. This developmental trend is often interpreted as a progressive refinement of the mental representation of number. Here we provide empirical and theoretical support for an alternative possibility, the filtering hypothesis, which proposes that development primarily affects the ability to focus on the relevant dimension of number and to avoid interference from irrelevant but often co-varying quantitative dimensions. Data from the same numerical comparison task in adults and children of various levels of numeracy, including Mundurucú Indians and western dyscalculics, show that, as predicted by the filtering hypothesis, age and education primarily increase the ability to focus on number and filter out potentially interfering information on the non-numerical dimensions. These findings can be captured by a minimal computational model where learning consists in the training of a multivariate classifier whose discrimination boundaries get progressively aligned to the task-relevant dimension of number. This view of development has important consequences for education.
Figure 1. The filtering and sharpening hypotheses