Biology subjects

Sable-Meyer, M.

Publications and source records attributed to Sable-Meyer, M..

4 recordsLinked to original sources

bioRxiv2025

A mechanistic theory of planning in prefrontal cortex

Planning is critical for adaptive behaviour in a changing world, because it lets us anticipate the future and adjust our actions accordingly. While prefrontal cortex is crucial for this process, it remains unknown how planning is implemented in neural circuits. Prefrontal representations were recently discovered in simpler sequence memory tasks, where different populations of neurons represent different future time points. We demonstrate that combining such representations with the ubiquitous principle of neural attractor dynamics allows circuits to solve much richer problems including planning. This is achieved by embedding the environment structure directly in synaptic connections to implement an attractor network that infers desirable futures. The resulting 'spacetime attractor' excels at planning in challenging tasks known to depend on prefrontal cortex. Recurrent neural networks trained by gradient descent on such tasks learn a solution that precisely recapitulates the spacetime attractor - in representation, in dynamics, and in connectivity. Analyses of networks trained across different environment structures reveal a generalisation mechanism that rapidly reconfigures the world model used for planning, without the need for synaptic plasticity. The spacetime attractor is a testable mechanistic theory of planning. If true, it would provide a path towards detailed mechanistic understanding of how prefrontal cortex structures adaptive behaviour.

neuroscience↗

bioRxiv2024

Two brain systems for the perception of geometric shapes

The perception and production of regular geometric shapes, a characteristic trait of human cultures since prehistory, has unknown neural mechanisms. Behavioral studies suggest that humans are attuned to discrete regularities such as symmetries and parallelism, and rely on their combinations to encode regular geometric shapes in a compressed form. To identify the brain systems underlying this ability, as well as their dynamics, we collected functional MRI in both adults and six-year-olds, and magnetoencephalography data in adults, during the perception of simple shapes such as hexagons, triangles and quadrilaterals. The results revealed that geometric shapes, relative to other visual categories, induce a hypoactivation of ventral visual areas and an overactivation of the intraparietal and inferior temporal regions also involved in mathematical processing, whose activation is modulated by geometric regularity. While convolutional neural networks captured the early visual activity evoked by geometric shapes, they failed to account for subsequent dorsal parietal and prefrontal signals, which could only be captured by discrete geometric features or by bigger deep-learning models of vision. We propose that the perception of abstract geometric regularities engages an additional symbolic mode of visual perception.

neuroscience↗

bioRxiv2024

Long-horizon associative learning explains human sensitivity to statistical and network structures in auditory sequences

Networks are a useful mathematical tool for capturing the complexity of the world. In a previous behavioral study, we showed that human adults were sensitive to the high-level network structure underlying auditory sequences, even when presented with incomplete information. Their performance was best explained by a mathematical model compatible with associative learning principles, based on the integration of the transition probabilities between adjacent and non-adjacent elements with a memory decay. In the present study, we explored the neural correlates of this hypothesis via magnetoencephalography (MEG). Participants passively listened to sequences of tones organized in a sparse community network structure comprising two communities. An early difference (~150 ms) was observed in the brain responses to tone transitions with similar transition probability but occurring either within or between communities. This result implies a rapid and automatic encoding of the sequence structure. Using time-resolved decoding, we estimated the duration and overlap of the representation of each tone. The decoding performance exhibited exponential decay, resulting in a significant overlap between the representations of successive tones. Based on this extended decay profile, we estimated a long-horizon associative learning novelty index for each transition and found a correlation of this measure with the MEG signal. Overall, our study sheds light on the neural mechanisms underlying human sensitivity to network structures and highlights the potential role of Hebbian-like mechanisms in supporting learning at various temporal scales.

neuroscience↗

bioRxiv2022

Graphicacy across age, education, and culture: a new tool to assess intuitive graphics skills

Data plots are widely used in science, journalism and politics, since they efficiently allow to depict a large amount of information. Graphicacy, the ability to understand graphs, thus became a fundamental cultural skill. Here, we introduce a new measure of graphicacy that assesses the ability to detect a trend in noisy scatterplots ("does this graph go up or down?"). In 3943 educated participants, responses vary as a sigmoid function of the t-value that a statistician would compute to detect a significant trend. We find a minimum level of core graphicacy even in unschooled participants living in remote Namibian villages (N=87) and 6-year-old 1st-graders who never read a graph (N=27). However, the sigmoid slope (the "graphicacy index") varies across participants, increases with education, and tightly correlates with statistical knowledge, showing that experience contributes to refining graphical intuitions. Our tool is publicly available online and allows to quickly evaluate intuitive graphics skills. STATEMENT OF RELEVANCEThe rising cost of gas, the number of Covid deaths, the evolution of temperatures during the summer months: we often face graphs depicting these phenomena. The scientific literature has shown that human adults can intuit, within milliseconds, the statistical trend of these graphs. However, we do not know if these intuitions generalized to unschooled people and, most importantly, how to measure their variations in the population. In this study we show that intuitive graphics skills are present even in 6-year-old children who never saw a graph and in the Himba of Namibia, an indigenous people with no access to formal schooling. Furthermore, we developed a quantitative assessment of such intuitive graphics skills (which we called the "graphicacy index"), that everyone can easily obtain for free, through a short (10 minutes) online test: https://neurospin-data.cea.fr/exp/lorenzo-ciccione/graphicacy-index/. In summary, our study provides the first attempt to formally quantify human intuitions of statistical graphs.

scientific communication and education↗