Cited by 23Neural dynamics and brain functionNeuroscience and Neuropharmacology ResearchMemory and Neural Mechanisms

Spontaneous activity competes with externally evoked responses in sensory cortex

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Karvat, Golan, Alyahyay, Mansour, Diester, Ilka·2021·Proceedings of the National Academy of Sciences

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Abstract

Significance: Humans and animals recognize light tactile stimulations on some occasions while at others miss even stronger stimuli. The explanation of this apparent paradox lies in the competition between spontaneously and externally evoked responses in the brain. Brief bursts of beta-oscillations have been implicated in reduced detection rates, yet the underlying mechanism remained unknown. Here, we report that neural networks exhibit synchronization during beta-bursts, followed by reduced firing rates, thus explaining the diminished detection rate on the single trial level. Through monitoring the brain’s electrical activity before and during tactile stimulation, we found that the masking influence of burst occupancy on perception can be counterbalanced in real time by adjusting the stimulus intensity, thereby overcoming this active inhibition of sensory cortex.

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  • People with lower SES tend to have a shorter life expectancy and worse health-related outcomes compared with more affluent people.

    “There is a wide range of robust empirical evidence from many settings which indicates that people with lower SES tend to have a shorter life expectancy and worse health-related outcomes in comparison to more affluent people.1–4”

    From Health professionals implicit bias of patients with low socioeconomic status (SES) and its effects on clinical decision-making: a scoping review (2024) · cites this paper as [4]

    The Results passages concern sensory-cortex activity and stimulus detection, while Materials and Methods > Animals describes a study in rats; no page numbers are available in our copy. Searches for socioeconomic status, life expectancy, income, mortality, and related health outcomes found no passage addressing the claimed comparison between people of lower and higher SES. (LLM, conf=0.78)

    Experimental — accuracy not yet measured
  • Controlling for SES, people who are of Afro-Caribbean heritage are three times more likely to be diagnosed with diabetes than their counterparts of European heritage.

    “For example, there is evidence which shows that controlling for SES, people who are of Afro-Caribbean heritage are three times more likely to be diagnosed with diabetes than their counterparts of European heritage, while people who are lesbian, gay, bisexual, transgender or identify as queer are more likely to have multiple risks for cardiovascular disease than their heterosexual peers.4”

    From Health professionals implicit bias of patients with low socioeconomic status (SES) and its effects on clinical decision-making: a scoping review (2024) · cites this paper as [4]

    The Materials and Methods (Animals; page not provided) describe a study of rats, while the Results (Rats Detect Forepaw Vibration; page not provided) concern responses to sensory stimulation. Searches for Afro-Caribbean heritage, diabetes, socioeconomic status, and European heritage found no passage addressing the claimed comparison. (LLM, conf=0.78)

    Experimental — accuracy not yet measured
  • People who are lesbian, gay, bisexual, transgender or identify as queer are more likely to have multiple risks for cardiovascular disease than their heterosexual peers.

    “For example, there is evidence which shows that controlling for SES, people who are of Afro-Caribbean heritage are three times more likely to be diagnosed with diabetes than their counterparts of European heritage, while people who are lesbian, gay, bisexual, transgender or identify as queer are more likely to have multiple risks for cardiovascular disease than their heterosexual peers.4”

    From Health professionals implicit bias of patients with low socioeconomic status (SES) and its effects on clinical decision-making: a scoping review (2024) · cites this paper as [4]

    The Materials and Methods (Animals; page unavailable) describes a study of five female rats, and the Discussion (page unavailable) addresses neural beta-bursts and stimulus detection. Searches for LGBTQ identity, heterosexual peers, and cardiovascular risk factors found no passage addressing the claimed comparison. (LLM, conf=0.76)

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References 83 · Cited by 23

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  1. [1]G. Deco, V. K. Jirsa, A. R. McIntosh, Resting brains never rest: Computational insights into potential cognitive architectures. Trends Neurosci. 36, 268– 274 (2013). 23561718
  2. [2]J. S. Damoiseaux., Consistent resting-state networks across healthy subjects. Proc. Natl. Acad. Sci. U.S.A. 103, 13848– 13853 (2006). 16945915 PMC1564249
  3. [3]N. Afrashteh., Spatiotemporal structure of sensory-evoked and spontaneous activity revealed by mesoscale imaging in anesthetized and awake mice. bioRxiv [Preprint] (2020). 10.1101/2020.05.22.111021 (Accessed 30 July 2020). 34879278 · DOI
  4. [4]B. Biswal, F. Z. Yetkin, V. M. Haughton, J. S. Hyde, Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn. Reson. Med. 34, 537– 541 (1995). 8524021
  5. [5]M. D. Fox., The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc. Natl. Acad. Sci. U.S.A. 102, 9673– 9678 (2005). 15976020 PMC1157105
  6. [6]P. Fransson, Spontaneous low-frequency BOLD signal fluctuations: An fMRI investigation of the resting-state default mode of brain function hypothesis. Hum. Brain Mapp. 26, 15– 29 (2005). 15852468 PMC6871700
  7. [7]M. E. Raichle., A default mode of brain function. Proc. Natl. Acad. Sci. U.S.A. 98, 676– 682 (2001). 11209064 PMC14647
  8. [8]M. E. Raichle, The brain’s default mode network. Annu. Rev. Neurosci. 38, 433– 447 (2015). 25938726
  9. [10]Z. A. Seedat., The role of transient spectral ‘bursts’ in functional connectivity: A magnetoencephalography study. Neuroimage 209, 116537 (2020). 31935517
  10. [11]J. F. Hipp, D. J. Hawellek, M. Corbetta, M. Siegel, A. K. Engel, Large-scale cortical correlation structure of spontaneous oscillatory activity. Nat. Neurosci. 15, 884– 890 (2012). 22561454 PMC3861400
  11. [13]T. I. Panagiotaropoulos, V. Kapoor, N. K. Logothetis, Desynchronization and rebound of beta oscillations during conscious and unconscious local neuronal processing in the macaque lateral prefrontal cortex. Front. Psychol. 4, 603 (2013). 24062706 PMC3769623
  12. [14]J. Feingold, D. J. Gibson, B. DePasquale, A. M. Graybiel, Bursts of beta oscillation differentiate postperformance activity in the striatum and motor cortex of monkeys performing movement tasks. Proc. Natl. Acad. Sci. U.S.A. 112, 13687– 13692 (2015). 26460033 PMC4640760
  13. [15]F. van Ede, O. Jensen, E. Maris, Tactile expectation modulates pre-stimulus β-band oscillations in human sensorimotor cortex. Neuroimage 51, 867– 876 (2010). 20188186
  14. [16]M. Bauer, R. Oostenveld, M. Peeters, P. Fries, Tactile spatial attention enhances gamma-band activity in somatosensory cortex and reduces low-frequency activity in parieto-occipital areas. J. Neurosci. 26, 490– 501 (2006). 16407546 PMC6674422
  15. [17]G. Chen., Distinct inhibitory circuits orchestrate cortical beta and gamma band oscillations. Neuron 96, 1403– 1418.e6 (2017). 29268099 PMC5864125
  16. [18]M. Pesonen, C. H. Björnberg, H. Hämäläinen, C. M. Krause, Brain oscillatory 1-30 Hz EEG ERD/ERS responses during the different stages of an auditory memory search task. Neurosci. Lett. 399, 45– 50 (2006). 16490308
  17. [19]B. E. Kilavik, M. Zaepffel, A. Brovelli, W. A. MacKay, A. Riehle, The ups and downs of β oscillations in sensorimotor cortex. Exp. Neurol. 245, 15– 26 (2013). 23022918
  18. [20]G. Tinkhauser., The cumulative effect of transient synchrony states on motor performance in Parkinson’s disease. J. Neurosci. 40, 1571– 1580 (2020). 31919131 PMC7044725
  19. [21]H. Shin, R. Law, S. Tsutsui, C. I. Moore, S. R. Jones, The rate of transient beta frequency events predicts behavior across tasks and species. eLife 6, e29086 (2017). 29106374 PMC5683757
  20. [22]G. Karvat., Real-time detection of neural oscillation bursts allows behaviourally relevant neurofeedback. Commun. Biol. 3, 72 (2020). 32060396 PMC7021904
  21. [23]A. Luczak, B. L. McNaughton, K. D. Harris, Packet-based communication in the cortex. Nat. Rev. Neurosci. 16, 745– 755 (2015). 26507295
  22. [24]O. Donchin., Local field potentials related to bimanual movements in the primary and supplementary motor cortices. Exp. Brain Res. 140, 46– 55 (2001). 11500797
  23. [25]A. Grinvald, D. Sharon, D. Omer, I. Vanzetta, Imaging the neocortex functional architecture using multiple intrinsic signals: Implications for hemodynamic-based functional imaging. Cold Spring Harb. Protoc. 2016, pdb.top089375 (2016). 26933255
  24. [26]J. K. Chapin, C.-S. Lin, Mapping the body representation in the SI cortex of anesthetized and awake rats. J. Comp. Neurol. 229, 199– 213 (1984). 6438190
  25. [27]R. T. Narayanan, D. Udvary, M. Oberlaender, Cell type-specific structural organization of the six layers in rat barrel cortex. Front. Neuroanat. 11, 91 (2017). 29081739 PMC5645532
  26. [28]V. de Lafuente, R. Romo, Neural correlate of subjective sensory experience gradually builds up across cortical areas. Proc. Natl. Acad. Sci. U.S.A. 103, 14266– 14271 (2006). 16924098 PMC1551903
  27. [29]R. Romo, R. Rossi-Pool, Turning touch into perception. Neuron 105, 16– 33 (2020). 31917952
  28. [30]K. J. Sanderson, W. Welker, G. M. Shambes, Reevaluation of motor cortex and of sensorimotor overlap in cerebral cortex of albino rats. Brain Res. 292, 251– 260 (1984). 6692158
  29. [31]G. Buzsáki, A. Draguhn, Neuronal oscillations in cortical networks. Science 304, 1926– 1929 (2004). 15218136
  30. [32]G. Buzsáki, F. L. Silva, High frequency oscillations in the intact brain. Prog. Neurobiol. 98, 241– 249 (2012). 22449727 PMC4895831
  31. [33]M. Lundqvist., Gamma and beta bursts underlie working memory. Neuron 90, 152– 164 (2016). 26996084 PMC5220584
  32. [34]O. David, J. M. Kilner, K. J. Friston, Mechanisms of evoked and induced responses in MEG/EEG. Neuroimage 31, 1580– 1591 (2006). 16632378
  33. [35]S. Ray, N. E. Crone, E. Niebur, P. J. Franaszczuk, S. S. Hsiao, Neural correlates of high-gamma oscillations (60-200 Hz) in macaque local field potentials and their potential implications in electrocorticography. J. Neurosci. 28, 11526– 11536 (2008). 18987189 PMC2715840
  34. [36]R. T. Canolty, K. Ganguly, J. M. Carmena, Task-dependent changes in cross-level coupling between single neurons and oscillatory activity in multiscale networks. PLOS Comput. Biol. 8, e1002809 (2012). 23284276 PMC3527280
  35. [37]B. van Vugt., The threshold for conscious report: Signal loss and response bias in visual and frontal cortex. Science 360, 537– 542 (2018). 29567809
  36. [38]M. Stokes, E. Spaak, The importance of single-trial analyses in cognitive neuroscience. Trends Cogn. Sci. 20, 483– 486 (2016). 27237797
  37. [39]S. G. Heideman, A. J. Quinn, M. W. Woolrich, F. van Ede, A. C. Nobre, Dissecting beta-state changes during timed movement preparation in Parkinson’s disease. Prog. Neurobiol. 184, 101731 (2020). 31778771 PMC6977086
  38. [40]J. Confais, N. Malfait, T. Brochier, A. Riehle, B. E. Kilavik, Is there an intrinsic relationship between LFP beta oscillation amplitude and firing rate of individual neurons in macaque motor cortex? Cereb. Cortex Commun. 1, tgaa017 (2020). PMC8152857 34296095
  39. [41]V. N. Murthy, E. E. Fetz, Synchronization of neurons during local field potential oscillations in sensorimotor cortex of awake monkeys. J. Neurophysiol. 76, 3968– 3982 (1996). 8985893
  40. [42]M. E. Rule, C. E. Vargas-Irwin, J. P. Donoghue, W. Truccolo, Dissociation between sustained single-neuron spiking and transient β-LFP oscillations in primate motor cortex. J. Neurophysiol. 117, 1524– 1543 (2017). 28100654 PMC5376602
  41. [43]V. N. Murthy, E. E. Fetz, Coherent 25- to 35-Hz oscillations in the sensorimotor cortex of awake behaving monkeys. Proc. Natl. Acad. Sci. U.S.A. 89, 5670– 5674 (1992). 1608977 PMC49354
  42. [44]J. P. Donoghue, J. N. Sanes, N. G. Hatsopoulos, G. Gaál, Neural discharge and local field potential oscillations in primate motor cortex during voluntary movements. J. Neurophysiol. 79, 159– 173 (1998). 9425187
  43. [45]M. A. Sherman., Neural mechanisms of transient neocortical beta rhythms: Converging evidence from humans, computational modeling, monkeys, and mice. Proc. Natl. Acad. Sci. U.S.A. 113, E4885– E4894 (2016). 27469163 PMC4995995
  44. [46]E. Russo, D. Durstewitz, Cell assemblies at multiple time scales with arbitrary lag constellations. eLife 6, e19428 (2017). 28074777 PMC5226654
  45. [47]R. Schmidt., Beta oscillations in working memory, executive control of movement and thought, and sensorimotor function. J. Neurosci. 39, 8231– 8238 (2019). 31619492 PMC6794925
  46. [48]W. Singer, “ Putative functions of temporal correlations in neocortical processing” in Large-Scale Neuronal Theories of the Brain, (Computational Neuroscience, The MIT Press, 1994), pp. 201– 237.
  47. [49]P. M. Briley., Regional brain correlates of beta bursts in health and psychosis: A concurrent electroencephalography and functional magnetic resonance imaging study. Biol. Psychiatry Cogn. Neurosci. Neuroimaging, 10.1016/j.bpsc.2020.10.018 (2020). PMC8648891 33495122 · DOI
  48. [50]S. N. Baker, J. M. Kilner, E. M. Pinches, R. N. Lemon, The role of synchrony and oscillations in the motor output. Exp. Brain Res. 128, 109– 117 (1999). 10473748
  49. [51]C. M. Lewis., Cortical gamma-band resonance preferentially transmits coherent input. Cell Rep. 35, 109083 (2021). 33951439 PMC8200519
  50. [52]R. D. Traub, M. A. Whittington, E. H. Buhl, J. G. R. Jefferys, H. J. Faulkner, On the mechanism of the γ–> β frequency shift in neuronal oscillations induced in rat hippocampal slices by tetanic stimulation. J. Neurosci. 19, 1088– 1105 (1999). 9920671 PMC6782135
  51. [53]V. de Lafuente, R. Romo, Neuronal correlates of subjective sensory experience. Nat. Neurosci. 8, 1698– 1703 (2005). 16286929
  52. [54]D. Zaldivar, J. Goense, S. C. Lowe, N. K. Logothetis, S. Panzeri, Dopamine is signaled by mid-frequency oscillations and boosts output layers visual information in visual cortex. Curr. Biol. 28, 224– 235.e5 (2018). 29307559
  53. [55]M. Serafin, S. Williams, A. Khateb, P. Fort, M. Mühlethaler, Rhythmic firing of medial septum non-cholinergic neurons. Neuroscience 75, 671– 675 (1996). 8951863
  54. [56]S.-C. Lin, D. Gervasoni, M. A. L. Nicolelis, Fast modulation of prefrontal cortex activity by basal forebrain noncholinergic neuronal ensembles. J. Neurophysiol. 96, 3209– 3219 (2006). 16928796
  55. [57]T. F. Freund, V. Meskenaite, gamma-Aminobutyric acid-containing basal forebrain neurons innervate inhibitory interneurons in the neocortex. Proc. Natl. Acad. Sci. U.S.A. 89, 738– 742 (1992). 1731348 PMC48314
  56. [58]L. Pinto., Fast modulation of visual perception by basal forebrain cholinergic neurons. Nat. Neurosci. 16, 1857– 1863 (2013). 24162654 PMC4201942
  57. [59]K. I. van Aerde., Flexible spike timing of layer 5 neurons during dynamic beta oscillation shifts in rat prefrontal cortex. J. Physiol. 587, 5177– 5196 (2009). 19752121 PMC2790257
  58. [60]B. E. Alger, D. A. Nagode, A.-H. Tang, Muscarinic cholinergic receptors modulate inhibitory synaptic rhythms in hippocampus and neocortex. Front. Synaptic Neurosci. 6, 18 (2014). 25249974 PMC4155787
  59. [61]H. Cagnan., Temporal evolution of beta bursts in the parkinsonian cortical and basal ganglia network. Proc. Natl. Acad. Sci. U.S.A. 116, 16095– 16104 (2019). 31341079 PMC6690030
  60. [62]M. Deffains, L. Iskhakova, S. Katabi, Z. Israel, H. Bergman, Longer β oscillatory episodes reliably identify pathological subthalamic activity in Parkinsonism. Mov. Disord. 33, 1609– 1618 (2018). 30145811
  61. [63]G. Tinkhauser., The modulatory effect of adaptive deep brain stimulation on beta bursts in Parkinson’s disease. Brain 140, 1053– 1067 (2017). 28334851 PMC5382944
  62. [64]H. Cagnan, E. P. Duff, P. Brown, The relative phases of basal ganglia activities dynamically shape effective connectivity in Parkinson’s disease. Brain 138, 1667– 1678 (2015). 25888552 PMC4614137
  63. [65]S. Hardung., A functional gradient in the rodent prefrontal cortex supports behavioral inhibition. Curr. Biol. 27, 549– 555 (2017). 28190729
  64. [66]C. Risterucci, D. Terramorsi, A. Nieoullon, M. Amalric, Excitotoxic lesions of the prelimbic-infralimbic areas of the rodent prefrontal cortex disrupt motor preparatory processes. Eur. J. Neurosci. 17, 1498– 1508 (2003). 12713653
  65. [67]M. Pachitariu, N. A. Steinmetz, S. N. Kadir, M. Carandini, K. D. Harris, “ Fast and accurate spike sorting of high-channel count probes with KiloSort” in Advances in Neural Information Processing Systems, D. D. Lee, M. Sugiyama, U. V. Luxburg, I. Guyon, R. Garnett, Eds. (Curran Associates, Inc, 2016), vol. 29, pp. 4448– 4456.
  66. [68]R. Oostenveld, P. Fries, E. Maris, J.-M. Schoffelen, FieldTrip: Open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data. Comput. Intell Neurosci. 2011, 156869 (2011). 21253357 PMC3021840
  67. [69]S. A. Neymotin., Taxonomy of neural oscillation events in primate auditory cortex. bioRxiv [Preprint] (2020). 10.1101/2020.04.16.045021 (Accessed 19 January 2021). · DOI
  68. [71]M. P. Karlsson, D. G. R. Tervo, A. Y. Karpova, Network resets in medial prefrontal cortex mark the onset of behavioral uncertainty. Science 338, 135– 139 (2012). 23042898

Authors
Karvat, G., Alyahyay, M., & Diester, I.
Affiliations
University of Freiburg (DE)
Corresponding author
Diester, Ilka
Venue
Proceedings of the National Academy of Sciences
Published
2021-06-21
Volume
118
Issue
25
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W3173740426
Cited by
23
References
83
Citations by year
2026: 5 · 2025: 2 · 2024: 5 · 2023: 7 · 2022: 3 · 2021: 1
FWCI
2.09
Type
journal article
Language
en
Open access
Locations
  • Proceedings of the National Academy of Sciences (publishedVersion, cc-by-nc-nd)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
Funders
  • Deutsche Forschungsgemeinschaft (DI 1908/6-1, DI 1908/5-1, EXC‐1086, 1908/6-1)
  • Bundesministerium für Bildung und Forschung (01GQ1301)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
Keywords
spontaneous neuronal activity, beta oscillations, sensory evoked potentials, sensory masking, somatosensory cortex, vibrotactile perception, local field potentials, cortical synchronization
MeSH terms
Action Potentials, Animals, Beta Rhythm, Cues, Evoked Potentials, Somatosensory, Female, Physical Stimulation, Somatosensory Cortex, Vibration, Rats, Sprague-Dawley, Rats

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