Masticationpedia

Store:Exel02

Store Discussion
Revision as of 17:53, 19 October 2022 by Gianfranco (talk | contribs) (Created page with "=== Introduction === An important but outstanding issue in contemporary cognitive neuroscience is understanding the organizational properties of neural activity. For instance, is there a fundamental structure to the spatial–temporal patterns neural brain activity across different conditions? One common approach used to address this question is to examine the brain at “rest”. Measures such as functional connectivity, independent component analysis and graph theoreti...")
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Go to top

Introduction

An important but outstanding issue in contemporary cognitive neuroscience is understanding the organizational properties of neural activity. For instance, is there a fundamental structure to the spatial–temporal patterns neural brain activity across different conditions? One common approach used to address this question is to examine the brain at “rest”. Measures such as functional connectivity, independent component analysis and graph theoretic metrics, have been applied to data recorded using different imaging techniques (e.g., functional magnetic resonance imaging (fMRI) and electroencephalography (EEG)), to cluster brain areas that exhibit similar activity patterns. Numerous studies have shown that brain activity during “rest” can be grouped into distinct networks across[1][2]; such as sensory (visual and auditory), default mode, executive, salience, and attentional (ventral and dorsal) networks that have been reliably reproduced across thousands of participants[3], and are predictive of phenotypic measures like cognition and clinical diagnoses[4][5][6]. These results suggest these networks may be an intrinsic aspect of neural activity.

Indeed, the same set of structured patterns of neural activity have been found during "active" states, such as, while completing different tasks[7][8][9]. For instance, there is a high degree of correspondence between networks extracted during rest and those extracted during tasks measuring sensorimotor[10][11] and higher-level cognitive abilities (i.e., working memory)[12][13].Even completing a task as complicated as following the plot of a movie elicits the same network architecture as observed in the resting brain[14]. The correspondence between task and rest-based networks is so strong that task-based fMRI network activity can be predicted from the resting state[15], and rest-task network pairs can be identified at the individual level[16]16. Together, these results suggest that rest and task-based patterns of brain activity likely share a similar underlying neural architecture, despite distinct experiences and cognitive processes[17].

There are, however, important differences between the patterns of brain activity elicited during rest and task-based paradigms, and the set of experiences and cognitive processes associated with each[18]. For instance, the presence or absence of a task is accompanied by increases in variability across different scales including neuronal firing rates changes in field potentials[19][20], variation in fMRI blood oxygen level dependent (BOLD signal)[21] and in EEG frequency bands[22] Furthermore, through transcranial direct current stimulation (tDCS) it has been shown that frontal-lobe stimulation increases one’s proclivity to mind wander [23][24]. Importantly, these differences are associated with changes in properties of neural activity but not in changes in the underlying neural architecture.

  1. ↑ Biswal, B., Zerrin Yetkin, F., Haughton, V. M. & Hyde, J. S. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn. Reson. Med. 34, 537–541 (1995).
  2. ↑ Hutchison,R.M.etal. Dynamic functional connectivity: Promise, issues, and interpretations. Neuroimage80,360–378(2013).
  3. ↑ Eickhoff,S.B.,Yeo,B.T.T.&Genon,S.Imaging-basedparcellationsofthehumanbrain.Nat.Rev.Neurosci.19,672–686(2018).
  4. ↑ Dajani DR, et al. Investigating functional brain network integrity using a traditional and novel categorical scheme for neurodevelopmental disorders. NeuroImage Clin. 2019;21:101678. doi: 10.1016/j.nicl.2019.101678. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
  5. ↑ Uddin LQ, Karlsgodt KH. Future directions for examination of brain networks in neurodevelopmental disorders. J. Clin. Child Adolesc. Psychol. 2018;47:483–497. doi: 10.1080/15374416.2018.1443461. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
  6. ↑ Sripada C, et al. Prediction of neurocognition in youth from resting state fMRI. Mol. Psychiatry. 2020;25:3413–3421. doi: 10.1038/s41380-019-0481-6. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
  7. ↑ Biswal BB, Eldreth DA, Motes MA, Rypma B. Task-dependent individual differences in prefrontal connectivity. Cereb. Cortex. 2010;20:2188–2197. doi: 10.1093/cercor/bhp284. [PMC free article][PubMed] [CrossRef] [Google Scholar]
  8. ↑ Fox MD, Raichle ME. Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat. Rev. Neurosci. 2007;8:700–711. doi: 10.1038/nrn2201. [PubMed] [CrossRef] [Google Scholar]
  9. ↑ Kraus BT, et al. Network variants are similar between task and rest states. Neuroimage. 2021;229:117743. doi: 10.1016/j.neuroimage.2021.117743. [PMC free article][PubMed] [CrossRef] [Google Scholar]
  10. ↑ Kristo G, et al. Task and task-free FMRI reproducibility comparison for motor network identification. Hum. Brain Mapp. 2014;35:340–352. doi: 10.1002/hbm.22180. [PMC free article][PubMed] [CrossRef] [Google Scholar]
  11. ↑ Sui J, Adali T, Pearlson GD, Calhoun VD. An ICA-based method for the identification of optimal FMRI features and components using combined group-discriminative techniques. Neuroimage. 2009;46:73–86. doi: 10.1016/j.neuroimage.2009.01.026.[PMC free article] [PubMed] [CrossRef] [Google Scholar]
  12. ↑ Calhoun VD, Kiehl KA, Pearlson GD. Modulation of temporally coherent brain networks estimated using ICA at rest and during cognitive tasks. Hum. Brain Mapp. 2008;29:828–838. doi: 10.1002/hbm.20581. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
  13. ↑ Xie H, et al. Whole-brain connectivity dynamics reflect both task-specific and individual-specific modulation: A multitask study. Neuroimage. 2018;180:495–504. doi: 10.1016/j.neuroimage.2017.05.050. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
  14. ↑ Naci L, Cusack R, Anello M, Owen AM. A common neural code for similar conscious experiences in different individuals. Proc. Natl. Acad. Sci. U. S. A. 2014;111:14277–14282. doi: 10.1073/pnas.1407007111. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
  15. ↑ Kannurpatti SS, Rypma B, Biswal BB. Prediction of task-related BOLD fMRI with amplitude signatures of resting-state fMRI. Front. Syst. Neurosci. 2012;6:7. doi: 10.3389/fnsys.2012.00007.[PMC free article] [PubMed] [CrossRef] [Google Scholar]
  16. ↑ Elliott ML, et al. General functional connectivity: Shared features of resting-state and task fMRI drive reliable and heritable individual differences in functional brain networks. Neuroimage. 2019;189:516–532. doi: 10.1016/j.neuroimage.2019.01.068. [PMC free article][PubMed] [CrossRef] [Google Scholar]
  17. ↑ Cole MW, Ito T, Cocuzza C, Sanchez-Romero R. The functional relevance of task-state functional connectivity. J. Neurosci. 2021 doi: 10.1523/JNEUROSCI.1713-20.2021. [PMC free article][PubMed] [CrossRef] [Google Scholar]
  18. ↑ Zhang S, et al. Characterizing and differentiating task-based and resting state fMRI signals via two-stage sparse representations. Brain Imaging Behav. 2016;10:21–32. doi: 10.1007/s11682-015-9359-7.[PMC free article] [PubMed] [CrossRef] [Google Scholar]
  19. ↑ Monier C, Chavane F, Baudot P, Graham LJ, Frégnac Y. Orientation and direction selectivity of synaptic inputs in visual cortical neurons: A diversity of combinations produces spike tuning. Neuron. 2003;37:663–680. doi: 10.1016/S0896-6273(03)00064-3.[PubMed] [CrossRef] [Google Scholar]
  20. ↑ Churchland MM, et al. Stimulus onset quenches neural variability: A widespread cortical phenomenon. Nat. Neurosci. 2010;13:369–378. doi: 10.1038/nn.2501. [PMC free article][PubMed] [CrossRef] [Google Scholar]
  21. ↑ He BJ. Spontaneous and task-evoked brain activity negatively interact. J. Neurosci. 2013;33:4672–4682. doi: 10.1523/JNEUROSCI.2922-12.2013. [PMC free article][PubMed] [CrossRef] [Google Scholar]
  22. ↑ Bonnard M, et al. Resting state brain dynamics and its transients: A combined TMS-EEG study. Sci. Rep. 2016;6:1–9. doi: 10.1038/srep31220. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
  23. ↑ Axelrod V, Zhu X, Qiu J. Transcranial stimulation of the frontal lobes increases propensity of mind-wandering without changing meta-awareness. Sci. Rep. 2018;8:1–14. doi: 10.1038/s41598-018-34098-z. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
  24. ↑ Axelrod V, Rees G, Lavidor M, Bar M. Increasing propensity to mind-wander with transcranial direct current stimulation. Proc. Natl. Acad. Sci. U. S. A. 2015;112:3314–3319. doi: 10.1073/pnas.1421435112. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Retrieved from "https://www.masticationpedia.org/index.php?title=Store:Exel02&oldid=13440"