Telencephalon: Neocortex

doi:10.1007/978-3-540-34686-9_15

Cited by 8 publications

(4 citation statements)

References 737 publications

(1,026 reference statements)

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“…Based on prior source estimation work in young adults ( Tamaki et al, 2013 ; Brancaccio et al, 2020 ) and evidence that motor learning regions are active during the SRTT in young and older adults (e.g., King et al, 2017b ), we predicted that sleep oscillatory activity following motor sequence learning would contain contributions from multiple cortical regions, including motor cortices (premotor cortex, primary motor cortex, pre-SMA, SMA), in both young and older adults. Consistent with this prediction, we observed significant estimated contributions to delta, theta, and sigma activity during sleep after motor sequence learning from all regions of the modified Desikan-Killiany atlas, including caudal superior frontal gyrus, caudal middle frontal gyrus, precentral gyrus, and paracentral lobule (which collectively encompass premotor cortex, primary motor cortex, pre-SMA, and SMA; Nieuwenhuys et al, 2008 ).…”

Section: Discussionsupporting

confidence: 77%

“…motor cortices (premotor cortex, primary motor cortex, pre-SMA, SMA), in both young and older adults. Consistent with this prediction, we observed significant estimated contributions to delta, theta, and sigma activity during sleep after motor sequence learning from all regions of the modified Desikan-Killiany atlas, including caudal superior frontal gyrus, caudal middle frontal gyrus, precentral gyrus, and paracentral lobule (which collectively encompass premotor cortex, primary motor cortex, pre-SMA, and SMA; Nieuwenhuys et al, 2008).…”

Section: Estimated Cortical Sources Of Sleep Oscillatory Activitysupporting

confidence: 77%

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Aging-Related Changes in Cortical Sources of Sleep Oscillatory Neural Activity Following Motor Learning Reflect Contributions of Cortical Thickness and Pre-sleep Functional Activity

Fitzroy

Jones

Kainec

et al. 2022

Front. Aging Neurosci.

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Oscillatory neural activity during sleep, such as that in the delta and sigma bands, is important for motor learning consolidation. This activity is reduced with typical aging, and this reduction may contribute to aging-related declines in motor learning consolidation. Evidence suggests that brain regions involved in motor learning contribute to oscillatory neural activity during subsequent sleep. However, aging-related differences in regional contributions to sleep oscillatory activity following motor learning are unclear. To characterize these differences, we estimated the cortical sources of consolidation-related oscillatory activity using individual anatomical information in young and older adults during non-rapid eye movement sleep after motor learning and analyzed them in light of cortical thickness and pre-sleep functional brain activation. High-density electroencephalogram was recorded from young and older adults during a midday nap, following completion of a functional magnetic resonance imaged serial reaction time task as part of a larger experimental protocol. Sleep delta activity was reduced with age in a left-weighted motor cortical network, including premotor cortex, primary motor cortex, supplementary motor area, and pre-supplementary motor area, as well as non-motor regions in parietal, temporal, occipital, and cingulate cortices. Sleep theta activity was reduced with age in a similar left-weighted motor network, and in non-motor prefrontal and middle cingulate regions. Sleep sigma activity was reduced with age in left primary motor cortex, in a non-motor right-weighted prefrontal-temporal network, and in cingulate regions. Cortical thinning mediated aging-related sigma reductions in lateral orbitofrontal cortex and frontal pole, and partially mediated delta reductions in parahippocampal, fusiform, and lingual gyri. Putamen, caudate, and inferior parietal cortex activation prior to sleep predicted frontal and motor cortical contributions to sleep delta and theta activity in an age-moderated fashion, reflecting negative relationships in young adults and positive or absent relationships in older adults. Overall, these results support the local sleep hypothesis that brain regions active during learning contribute to consolidation-related neural activity during subsequent sleep and demonstrate that sleep oscillatory activity in these regions is reduced with aging.

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Section: Discussionsupporting

confidence: 77%

Section: Estimated Cortical Sources Of Sleep Oscillatory Activitysupporting

confidence: 77%

Aging-Related Changes in Cortical Sources of Sleep Oscillatory Neural Activity Following Motor Learning Reflect Contributions of Cortical Thickness and Pre-sleep Functional Activity

Fitzroy

Jones

Kainec

et al. 2022

Front. Aging Neurosci.

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“…SAF make up almost 90 % of all white matter connections in the human brain [9]. They mediate local cortico–cortical connectivity by linking different cortical hierarchy levels [2, 10] over distances of up to approximately 30 mm [9].…”

Section: Introductionmentioning

confidence: 99%

Connectivity at fine scale: mapping structural connective fields by tractography of short association fibresin vivo

Attar,

Kirilina,

Edwards

et al. 2024

Preprint

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The extraordinary number of short association fibres (SAF) connecting neighbouring cortical areas is a prominent feature of the large gyrified human brain. The contribution of SAF to the human connectome is largely unknown because of methodological challenges in mapping them. We present a method to characterise cortico–cortical connectivity mediated by SAF in topologically organised cortical areas. We introduce the 'structural connective fields' (sCF) metric which specifically quantifies neuronal signal propagation and integration mediated by SAF. This new metric complements functional connective field metrics integrating across contributions from short- and long-range white matter and intracortical fibres. Applying the method in the human early visual processing stream, we show that SAF preserve cortical functional topology. Retinotopic maps of V2 and V3 could be predicted from retinotopy in V1 and SAF connectivity. The sCF sizes increased along the cortical hierarchy and were smaller than their functional counterparts, in line with the latter being additionally broadened by long-range and intracortical connections.In vivosCF mapping provides insights into short-range cortico–cortical connectivity in humans comparable to tract tracing studies in animal research and is an essential step towards creating a complete human connectome.

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“…The layers in the neocortex are generally described as 6 horizontally superimposed stripes of gray matter with characteristic features such as size, type, and density of the neurons, which can again be differentiated into multiple sublayers [ 1 , 4 ]. From the pial to the gray-white matter interface, they include layer I, which contains mostly dendrites and axon terminals and has a low cellular density; layers II and III, which mainly contain pyramidal cells, with a size gradient in neurons of layer III that become larger towards its lower extent; layer IV, which consists of densely packed small pyramidal and non-pyramidal neurons; layer V, which is composed of pyramidal neurons that are small and intratelencephalic (layer Va) or large and sparse (layer Vb); and layer VI with corticothalamic pyramidal cells and heterogeneously shaped neurons [ 2 , 4 , 12 , 13 ]. One of the prominent cytoarchitectural features that vary across the cerebral cortex is its laminar structure, with respect to laminar thickness, as well as neuronal size and density of each layer.…”

Section: Introductionmentioning

confidence: 99%

The regional variation of laminar thickness in the human isocortex is related to cortical hierarchy and interregional connectivity

Saberi,

Paquola,

Wagstyl

et al. 2023

PLoS Biol

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The human isocortex consists of tangentially organized layers with unique cytoarchitectural properties. These layers show spatial variations in thickness and cytoarchitecture across the neocortex, which is thought to support function through enabling targeted corticocortical connections. Here, leveraging maps of the 6 cortical layers based on 3D human brain histology, we aimed to quantitatively characterize the systematic covariation of laminar structure in the cortex and its functional consequences. After correcting for the effect of cortical curvature, we identified a spatial pattern of changes in laminar thickness covariance from lateral frontal to posterior occipital regions, which differentiated the dominance of infra- versus supragranular layer thickness. Corresponding to the laminar regularities of cortical connections along cortical hierarchy, the infragranular-dominant pattern of laminar thickness was associated with higher hierarchical positions of regions, mapped based on resting-state effective connectivity in humans and tract-tracing of structural connections in macaques. Moreover, we show that regions with similar laminar thickness patterns have a higher likelihood of structural connections and strength of functional connections. In sum, here, we characterize the organization of laminar thickness in the human isocortex and its association with cortico-cortical connectivity, illustrating how laminar organization may provide a foundational principle of cortical function.

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Telencephalon: Neocortex

Cited by 8 publications

References 737 publications

Aging-Related Changes in Cortical Sources of Sleep Oscillatory Neural Activity Following Motor Learning Reflect Contributions of Cortical Thickness and Pre-sleep Functional Activity

Aging-Related Changes in Cortical Sources of Sleep Oscillatory Neural Activity Following Motor Learning Reflect Contributions of Cortical Thickness and Pre-sleep Functional Activity

Connectivity at fine scale: mapping structural connective fields by tractography of short association fibresin vivo

The regional variation of laminar thickness in the human isocortex is related to cortical hierarchy and interregional connectivity

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