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...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2014-01-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1003422 |
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| author | Rosalyn J Moran Mkael Symmonds Raymond J Dolan Karl J Friston |
| author_facet | Rosalyn J Moran Mkael Symmonds Raymond J Dolan Karl J Friston |
| author_sort | Rosalyn J Moran |
| collection | DOAJ |
| 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 | Article |
| id | doaj-art-c71f403d332b49259ab2f72389cd07a1 |
| institution | DOAJ |
| issn | 1553-734X 1553-7358 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj-art-c71f403d332b49259ab2f72389cd07a12025-08-20T03:10:06ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582014-01-01101e100342210.1371/journal.pcbi.1003422The brain ages optimally to model its environment: evidence from sensory learning over the adult lifespan.Rosalyn J MoranMkael SymmondsRaymond J DolanKarl J FristonThe 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.https://doi.org/10.1371/journal.pcbi.1003422 |
| spellingShingle | Rosalyn J Moran Mkael Symmonds Raymond J Dolan Karl J Friston The brain ages optimally to model its environment: evidence from sensory learning over the adult lifespan. PLoS Computational Biology |
| 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 |
| url | https://doi.org/10.1371/journal.pcbi.1003422 |
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