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Scientific result | Health ＆ life sciences | Brain
NeuroSpin's Researchers (UNICOG) discovered how the brain integrates and filters information flows. By combining high-resolution temporal brain imaging (MEG) techniques and machine learning algorithms, neurobiologists have been able to determine the sequence of neuronal operations that allows the brain to specifically select relevant information. These observations are described in Nature Communications.
Humans can reliably detect a target picture even when tens of images are flashed every second. Here we use magnetoencephalography to dissect the neural mechanisms underlying the dynamics of temporal selection during a rapid serial visual presentation task. Multivariate decoding algorithms allow us to track the overlapping brain responses induced by each image in a rapid visual stream. The results show that temporal selection involves a sequence of gradual followed by all-or-none stages: (i) all images first undergo the same parallel processing pipeline; (ii) starting around 150 ms, responses to multiple images surrounding the target are continuously amplified in ventral visual areas; (iii) only the images that are subsequently reported elicit late all-or-none activations in visual and parietal areas around 350 ms. Thus, multiple images can cohabit in the brain and undergo efficient parallel processing, but temporal selection also isolates a single one for amplification and report.
Read the French version.
Marti S, Dehaene S. Discrete and continuous mechanisms of temporal selection in rapid visual streams. (2017) Nature Communications, sous pressehttp://dx.doi.org/10.1038/s41467-017-02079-x
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