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The attention mechanism, central to the transformer architecture, has emerged as a powerful and scalable computational motif underlying many recent advances in machine learning. Beyond its success in AI, attention offers a compelling framework for building interpretable, mechanistically grounded models of brain function. In this talk, I will present a line of work exploring this potential across encoding and decoding. I will begin with Transformer brain encoders, in which attention is used to model how retinotopic visual features are dynamically routed to category-selective areas in high-level visual cortex, achieving state of the art encoding performance. I will then describe how this framework was extended to construct a digital twin of the visual system, enabling in silico experiments that reveal categorical visual selectivity across the whole brain. A third line of work leverages the in-context learning property of transformers to build encoding models that generalize across subjects and datasets. Finally, I will present our work on interpretable decoding models that reconstruct images from brain activity using attention-based architectures. [mehr]

How the brain tells time is fundamental for the individuation, the coincidence, the integration, and the ordering of events in time, but also for the feeling that time passes, that things exist for a while (duration), or that we can, at will, mentally travel to our vanished past and our not yet existing future. An epistemological difficulty stands in the way of understanding the status of 'time' in the neurosciences: temporalities emerge from the brain's perspective (the generator, actuator, and observer), not from the external observer. Yet, how neural circuits code, use, and represent temporal information is largely debated. I will discuss the role of neural rhythms from the basic feeling that time passes to the elicitation of, and the mental navigation in, temporal cognitive maps. [mehr]

Language is an unique communicative system involving hemispheric lateralization of the brain. Such a lateralization is visible at the structural level, even at birth, in key cortical language areas, such as the perisylvian Planum Temporale, its main connecting fiber track with Broca’s area - the arcuate fasciculus and the STS. To discuss the question of language origins, the studies of the communicative gestural system of our primate cousins, including our own research in baboons, have showed similar key intentional and referential properties of language as well as some similar underlying structural hemispheric specialization. In the present talk, I will present our behavioral and in vivo MRI brain imaging studies in baboons Papio anubis reporting not domain general cognitive properties of language found in gestural communication in baboons but also human-like structural brain asymmetries of some language-homolog regions in both 93 adults and 30 newborns as well as its correlates with the communicative gestures lateralization. [mehr]

Please join online: https://eu02web.zoom-x.de/j/91383057579?pwd=RDJQNkllaEJRYTV3VTlJTHprSjZodz09 [mehr]

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