scholarly journals Distinct cortical systems reinstate the content and context of episodic memories

2020 ◽  
Author(s):  
James E. Kragel ◽  
Youssef Ezzyat ◽  
Bradley C. Lega ◽  
Michael R. Sperling ◽  
Gregory A. Worrell ◽  
...  

AbstractEpisodic recall depends upon the reinstatement of cortical activity present during the formation of a memory. We identified dissociable cortical networks via functional connectivity that uniquely reinstated semantic content and temporal context of previously studied stimuli during free recall. Network-specific reinstatement predicted the temporal and semantic organization of recall sequences, demonstrating how specialized cortical systems enable the human brain to target specific memories.

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
James E. Kragel ◽  
Youssef Ezzyat ◽  
Bradley C. Lega ◽  
Michael R. Sperling ◽  
Gregory A. Worrell ◽  
...  

AbstractEpisodic recall depends upon the reinstatement of cortical activity present during the formation of a memory. Evidence from functional neuroimaging and invasive recordings in humans suggest that reinstatement organizes our memories by time or content, yet the neural systems involved in reinstating these unique types of information remain unclear. Here, combining computational modeling and intracranial recordings from 69 epilepsy patients, we show that two cortical systems uniquely reinstate the semantic content and temporal context of previously studied items during free recall. Examining either the posterior medial or anterior temporal networks, we find that forward encoding models trained on the brain’s response to the temporal and semantic attributes of items can predict the serial position and semantic category of unseen items. During memory recall, these models uniquely link reinstatement of temporal context and semantic content to these posterior and anterior networks, respectively. These findings demonstrate how specialized cortical systems enable the human brain to target specific memories.


2007 ◽  
Author(s):  
Sean M. Polyn ◽  
Kenneth A. Norman ◽  
Michael J. Kahana

2018 ◽  
Vol 29 (10) ◽  
pp. 4208-4222 ◽  
Author(s):  
Yuehua Xu ◽  
Miao Cao ◽  
Xuhong Liao ◽  
Mingrui Xia ◽  
Xindi Wang ◽  
...  

Abstract Individual variability in human brain networks underlies individual differences in cognition and behaviors. However, researchers have not conclusively determined when individual variability patterns of the brain networks emerge and how they develop in the early phase. Here, we employed resting-state functional MRI data and whole-brain functional connectivity analyses in 40 neonates aged around 31–42 postmenstrual weeks to characterize the spatial distribution and development modes of individual variability in the functional network architecture. We observed lower individual variability in primary sensorimotor and visual areas and higher variability in association regions at the third trimester, and these patterns are generally similar to those of adult brains. Different functional systems showed dramatic differences in the development of individual variability, with significant decreases in the sensorimotor network; decreasing trends in the visual, subcortical, and dorsal and ventral attention networks, and limited change in the default mode, frontoparietal and limbic networks. The patterns of individual variability were negatively correlated with the short- to middle-range connection strength/number and this distance constraint was significantly strengthened throughout development. Our findings highlight the development and emergence of individual variability in the functional architecture of the prenatal brain, which may lay network foundations for individual behavioral differences later in life.


2020 ◽  
Author(s):  
Steve Mehrkanoon

AbstractSynchronous oscillations of neuronal populations support resting-state cortical activity. Recent studies indicate that resting-state functional connectivity is not static, but exhibits complex dynamics. The mechanisms underlying the complex dynamics of cortical activity have not been well characterised. Here, we directly apply singular value decomposition (SVD) in source-reconstructed electroencephalography (EEG) in order to characterise the dynamics of spatiotemporal patterns of resting-state functional connectivity. We found that changes in resting-state functional connectivity were associated with distinct complex topological features, “Rich-Club organisation”, of the default mode network, salience network, and motor network. Rich-club topology of the salience network revealed greater functional connectivity between ventrolateral prefrontal cortex and anterior insula, whereas Rich-club topologies of the default mode networks revealed bilateral functional connectivity between fronto-parietal and posterior cortices. Spectral analysis of the dynamics underlying Rich-club organisations of these source-space network patterns revealed that resting-state cortical activity exhibit distinct dynamical regimes whose intrinsic expressions contain fast oscillations in the alpha-beta band and with the envelope-signal in the timescale of < 0.1 Hz. Our findings thus demonstrated that multivariate eigen-decomposition of source-reconstructed EEG is a reliable computational technique to explore how dynamics of spatiotemporal features of the resting-state cortical activity occur that oscillate at distinct frequencies.


2018 ◽  
Vol 3 ◽  
pp. 50 ◽  
Author(s):  
Takamitsu Watanabe ◽  
Geraint Rees

Background: Despite accumulated evidence for adult brain plasticity, the temporal relationships between large-scale functional and structural connectivity changes in human brain networks remain unclear. Methods: By analysing a unique richly detailed 19-week longitudinal neuroimaging dataset, we tested whether macroscopic functional connectivity changes lead to the corresponding structural alterations in the adult human brain, and examined whether such time lags between functional and structural connectivity changes are affected by functional differences between different large-scale brain networks. Results: In this single-case study, we report that, compared to attention-related networks, functional connectivity changes in default-mode, fronto-parietal, and sensory-related networks occurred in advance of modulations of the corresponding structural connectivity with significantly longer time lags. In particular, the longest time lags were observed in sensory-related networks. In contrast, such significant temporal differences in connectivity change were not seen in comparisons between anatomically categorised different brain areas, such as frontal and occipital lobes. These observations survived even after multiple validation analyses using different connectivity definitions or using parts of the datasets. Conclusions: Although the current findings should be examined in independent datasets with different demographic background and by experimental manipulation, this single-case study indicates the possibility that plasticity of macroscopic brain networks could be affected by cognitive and perceptual functions implemented in the networks, and implies a hierarchy in the plasticity of functionally different brain systems.


2015 ◽  
Vol 35 (15) ◽  
pp. 6068-6078 ◽  
Author(s):  
Carissa L. Philippi ◽  
Maia S. Pujara ◽  
Julian C. Motzkin ◽  
Joseph Newman ◽  
Kent A. Kiehl ◽  
...  

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