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Projekt Druckansicht

CORNET - Die Integration von top-down und bottom-up Einflüssen im Cortex von Marmosets und Makaken

Fachliche Zuordnung Kognitive, systemische und Verhaltensneurobiologie
Förderung Förderung von 2015 bis 2020
Projektkennung Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 287010018
 
Erstellungsjahr 2020

Zusammenfassung der Projektergebnisse

In experiments in anesthetized marmosets, hdECoG grids provided high-quality RFs from 240 sites over early and simultaneously 240 sites over higher visual areas. The additionally inserted laminar microelectrodes could record neuronal activity throughout the cortex. Optogenetic activation of neurons within and across areas was achieved in two animals, as confirmed with data analysis and histology. In experiments in awake marmosets, laminar probes recorded from a total of 192 channels in V1 and V4, combined with optogenetic control in V6. The latter had behavioral effects. DCM was able to provide excellent fits to the electrophysiological data and the effects of attention. The completed mouse connectivity study has proved to be surprising and we have been able to show that the published data in high profile Journals is incorrect. This makes the publication of this work very sensitive. This has forced us to move this project to a high priority and to complete the work much earlier than planned, and to complete these Deliverables more than 2-years earlier than planned. This work was presented at an international meeting on rodent neurobiology held in Suzhou, (China) in November 2016, where the major groups involved in developing rodent connectomes present their work. This work is now published in Neuron. Our overlapping interests in cortical processing and the high quality data that each lab has established opens the way to further collaborations that has been explored and developed in the Core-Net program. One particularly exciting possibility is the further development of the functional data from ESI using graph theoretic techniques that we have been applying to the structural data at SBRI.

Projektbezogene Publikationen (Auswahl)

  • (2015) Visual Areas Exert Feedforward and Feedback Influences through Distinct Frequency Channels. Neuron 85 (2): 390-401
    Bastos AM, Vezoli J, Bosman CA, Schoffelen JM, Oostenveld R, Dowdall JR, De Weerd P, Kennedy H, Fries P
    (Siehe online unter https://doi.org/10.1016/j.neuron.2014.12.018)
  • (2016) Alpha-Beta and Gamma Rhythms Subserve Feedback and Feedforward Influences among Human Visual Cortical Areas. Neuron, 89(2): 384-97
    Michalareas G, Vezoli J, van Pelt S, Schoffelen JM, Kennedy H, Fries P
    (Siehe online unter https://doi.org/10.1016/j.neuron.2015.12.018)
  • (2016) Gamma-Rhythmic Gain Modulation. Neuron 92:240-251
    Ni J, Wunderle T, Lewis CM, Desimone R, Diester I, Fries P
    (Siehe online unter https://doi.org/10.1016/j.neuron.2016.09.003)
  • (2017) In Vivo Magnetic recording of neuronal activity. Neuron, 95(6):1283-1291
    Caruso L, Wunderle T, Lewis CM, Valadeira J, Trauchessec V, Trejo Rosillo J, Amaral JP, Ni J, Jendritza P, Fermon C, Cardoso S, Freitas PP, Fries P, Pannetier-Lecoeur M
    (Siehe online unter https://doi.org/10.1016/j.neuron.2017.08.012)
  • (2017) Top-down beta enhances bottom-up gamma. J Neurosci. 37(28):6698-6711
    Richter CG, Thompson WH, Bosman CA, Fries P
    (Siehe online unter https://doi.org/10.1523/JNEUROSCI.3771-16.2017)
  • (2018) A theta rhythm in macaque visual cortex and its attentional modulation. Proc Nat Acad Sci USA. 115:E5614-E5623
    Spyropoulos G, Bosman CA, Fries P
    (Siehe online unter https://doi.org/10.1073/pnas.1719433115)
  • (2018) Cortical volume and sex influence visual gamma. Neuroimage, 178:702-712
    van Pelt S, Shumskaya E, Fries P
    (Siehe online unter https://doi.org/10.1016/j.neuroimage.2018.06.005)
  • (2018) Gamma synchronization between V1 and V4 improves behavioral performance. Neuron 100 (4), 953-963. e3
    Rohenkohl G, Bosman CA, Fries P
    (Siehe online unter https://doi.org/10.1016/j.neuron.2018.09.019)
  • (2019) Cortical layers, rhythms and BOLD signals. Neuroimage. 197, 689-698
    Scheeringa R, Fries P
    (Siehe online unter https://doi.org/10.1016/j.neuroimage.2017.11.002)
  • (2019) Human visual cortical gamma reflects natural image structure. NeuroImage 200, 635-643
    Brunet NM, Fries P
    (Siehe online unter https://doi.org/10.1016/j.neuroimage.2019.06.051)
  • (2019) Surface color and predictability determine contextual modulation of V1 firing and gamma oscillations. Elife 8, e42101
    Peter A, Uran C, Klon-Lipok J, Roese R, Van Stijn S, Barnes W, Dowdall JR, Singer W, Fries P, Vinck M
    (Siehe online unter https://doi.org/10.7554/eLife.42101)
  • (2020) Magnetoresistive Sensor in TwoDimension on a 25 μm Thick Silicon Substrate for In Vivo Neuronal Measurements. ACS sensors 5 (11), 3493-3500
    Chopin C, Torrejon J, Solignac A, Fermon C, Jendritza P, Fries P, Pannetier-Lecoeur M
    (Siehe online unter https://doi.org/10.1021/acssensors.0c01578)
  • (2020) Movement-related coupling of human subthalamic nucleus spikes to cortical gamma. Elife 9, e51956
    Fischer P, Lipski WJ, Neumann WJ, Turner RS, Fries P, Brown P, Richardson M
    (Siehe online unter https://doi.org/10.7554/eLife.51956)
  • (2020). Head-free eye tracking, and efficient receptive field mapping in the marmoset. bioRxiv
    Jendritza, P., Klein, F. J., Rohenkohl, G., & Fries, P.
    (Siehe online unter https://doi.org/10.1101/2020.10.30.361238)
 
 

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