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Brain oscillations and cross-frequency coupling as signatures of human working memory functions| title | Brain oscillations and cross-frequency coupling as signatures of human working memory functions |
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| start_date | 2026/06/08 |
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| schedule | 11h-12h |
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| online | no |
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| location_info | salle des Voûtes |
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| summary | Prior studies using Magnetoencephalography (MEG), Electroencephalography (EEG), and intracranial EEG (Stereo-EEG) have shown that both local brain oscillations and large-scale network connectivity across multiple frequency bands are associated with working memory (WM) functions in humans. However, it has been argued that these oscillatory signatures may be epiphenomenal. First, I will address this debated by discussing the causal relationship between fronto-parietal theta oscillations and WM performance. I will present our studies combining information-based neuromodulation (frequency-tuned Transcranial Magnetic Stimulation, visual rhythmic stimulation) with MEG/EEG recordings and longitudinal WM training. These approaches allow direct manipulation of task-relevant oscillatory dynamics, providing evidence that optimized non-invasive brain stimulation, targeting specific oscillatory metrics, can enhance brain plasticity and improve behavior. Second, I will turn to the question of how information is represented in working memory. WM functions cannot be explained solely by global increases in oscillatory power; instead, specific and distributed neural signatures should allow categorization of what is being integrated and maintained in memory. I willpresent a series of studies that aimed at identifying such content-specific representations, focusing on our recent work using SEEG during audio-visual associative learning and WM tasks based on learnedassociations. These studies seek to define large-scale network “fingerprints” underlying the maintenance and reactivation of feature-specific neural information and the contents of working memory. |
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| responsibles | Basques |
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Workflow history| from state (1) | to state | comment | date |
| submitted | published | | 2026/06/02 07:33 UTC |
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