Cargando…

The Brain Ages Optimally to Model Its Environment: Evidence from Sensory Learning over the Adult Lifespan

The aging brain shows a progressive loss of neuropil, which is accompanied by subtle changes in neuronal plasticity, sensory learning and memory. Neurophysiologically, aging attenuates evoked responses—including the mismatch negativity (MMN). This is accompanied by a shift in cortical responsivity f...

Descripción completa

Detalles Bibliográficos
Autores principales: Moran, Rosalyn J., Symmonds, Mkael, Dolan, Raymond J., Friston, Karl J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3900375/
https://www.ncbi.nlm.nih.gov/pubmed/24465195
http://dx.doi.org/10.1371/journal.pcbi.1003422
_version_ 1782300681724493824
author Moran, Rosalyn J.
Symmonds, Mkael
Dolan, Raymond J.
Friston, Karl J.
author_facet Moran, Rosalyn J.
Symmonds, Mkael
Dolan, Raymond J.
Friston, Karl J.
author_sort Moran, Rosalyn J.
collection PubMed
description The aging brain shows a progressive loss of neuropil, which is accompanied by subtle changes in neuronal plasticity, sensory learning and memory. Neurophysiologically, aging attenuates evoked responses—including the mismatch negativity (MMN). This is accompanied by a shift in cortical responsivity from sensory (posterior) regions to executive (anterior) regions, which has been interpreted as a compensatory response for cognitive decline. Theoretical neurobiology offers a simpler explanation for all of these effects—from a Bayesian perspective, as the brain is progressively optimized to model its world, its complexity will decrease. A corollary of this complexity reduction is an attenuation of Bayesian updating or sensory learning. Here we confirmed this hypothesis using magnetoencephalographic recordings of the mismatch negativity elicited in a large cohort of human subjects, in their third to ninth decade. Employing dynamic causal modeling to assay the synaptic mechanisms underlying these non-invasive recordings, we found a selective age-related attenuation of synaptic connectivity changes that underpin rapid sensory learning. In contrast, baseline synaptic connectivity strengths were consistently strong over the decades. Our findings suggest that the lifetime accrual of sensory experience optimizes functional brain architectures to enable efficient and generalizable predictions of the world.
format Online
Article
Text
id pubmed-3900375
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-39003752014-01-24 The Brain Ages Optimally to Model Its Environment: Evidence from Sensory Learning over the Adult Lifespan Moran, Rosalyn J. Symmonds, Mkael Dolan, Raymond J. Friston, Karl J. PLoS Comput Biol Research Article The aging brain shows a progressive loss of neuropil, which is accompanied by subtle changes in neuronal plasticity, sensory learning and memory. Neurophysiologically, aging attenuates evoked responses—including the mismatch negativity (MMN). This is accompanied by a shift in cortical responsivity from sensory (posterior) regions to executive (anterior) regions, which has been interpreted as a compensatory response for cognitive decline. Theoretical neurobiology offers a simpler explanation for all of these effects—from a Bayesian perspective, as the brain is progressively optimized to model its world, its complexity will decrease. A corollary of this complexity reduction is an attenuation of Bayesian updating or sensory learning. Here we confirmed this hypothesis using magnetoencephalographic recordings of the mismatch negativity elicited in a large cohort of human subjects, in their third to ninth decade. Employing dynamic causal modeling to assay the synaptic mechanisms underlying these non-invasive recordings, we found a selective age-related attenuation of synaptic connectivity changes that underpin rapid sensory learning. In contrast, baseline synaptic connectivity strengths were consistently strong over the decades. Our findings suggest that the lifetime accrual of sensory experience optimizes functional brain architectures to enable efficient and generalizable predictions of the world. Public Library of Science 2014-01-23 /pmc/articles/PMC3900375/ /pubmed/24465195 http://dx.doi.org/10.1371/journal.pcbi.1003422 Text en http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Moran, Rosalyn J.
Symmonds, Mkael
Dolan, Raymond J.
Friston, Karl J.
The Brain Ages Optimally to Model Its Environment: Evidence from Sensory Learning over the Adult Lifespan
title The Brain Ages Optimally to Model Its Environment: Evidence from Sensory Learning over the Adult Lifespan
title_full The Brain Ages Optimally to Model Its Environment: Evidence from Sensory Learning over the Adult Lifespan
title_fullStr The Brain Ages Optimally to Model Its Environment: Evidence from Sensory Learning over the Adult Lifespan
title_full_unstemmed The Brain Ages Optimally to Model Its Environment: Evidence from Sensory Learning over the Adult Lifespan
title_short The Brain Ages Optimally to Model Its Environment: Evidence from Sensory Learning over the Adult Lifespan
title_sort brain ages optimally to model its environment: evidence from sensory learning over the adult lifespan
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3900375/
https://www.ncbi.nlm.nih.gov/pubmed/24465195
http://dx.doi.org/10.1371/journal.pcbi.1003422
work_keys_str_mv AT moranrosalynj thebrainagesoptimallytomodelitsenvironmentevidencefromsensorylearningovertheadultlifespan
AT symmondsmkael thebrainagesoptimallytomodelitsenvironmentevidencefromsensorylearningovertheadultlifespan
AT dolanraymondj thebrainagesoptimallytomodelitsenvironmentevidencefromsensorylearningovertheadultlifespan
AT fristonkarlj thebrainagesoptimallytomodelitsenvironmentevidencefromsensorylearningovertheadultlifespan
AT moranrosalynj brainagesoptimallytomodelitsenvironmentevidencefromsensorylearningovertheadultlifespan
AT symmondsmkael brainagesoptimallytomodelitsenvironmentevidencefromsensorylearningovertheadultlifespan
AT dolanraymondj brainagesoptimallytomodelitsenvironmentevidencefromsensorylearningovertheadultlifespan
AT fristonkarlj brainagesoptimallytomodelitsenvironmentevidencefromsensorylearningovertheadultlifespan