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000909873 0247_ $$2doi$$a10.12751/NNCN.BC2022.268
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000909873 037__ $$aFZJ-2022-03482
000909873 041__ $$aEnglish
000909873 1001_ $$0P:(DE-Juel1)190767$$aShimoura, Renan$$b0$$eCorresponding author$$ufzj
000909873 1112_ $$aBernstein Conference 2022$$cBerlin$$d2022-09-13 - 2022-09-16$$wGermany
000909873 245__ $$aAlpha rhythm generators in a full-density spiking thalamocortical microcircuit model
000909873 260__ $$c2022
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000909873 500__ $$aReferences: [1] Clayton, M. S., Yeung, N., & Cohen Kadosh, R. (2017). The many characters of visual alpha oscillations. European Journal of Neuroscience., 10.1111/ejn.13747; [2] Silva, L., Amitai, Y., & Connors, B. (1991). Intrinsic oscillations of neocortex generated by layer 5 pyramidal neurons. Science, 251(4992), 432–435., 10.1126/science.1824881; [3] Roberts, J. A., & Robinson, P. A. (2008). Modeling absence seizure dynamics: implications for basic mechanisms and measurement of thalamocortical and corticothalamic latencies. Journal of Theoretical Biology, 253(1), 189–201., 10.1016/j.jtbi.2008.03.005; [4] Van Kerkoerle, T., Self, M. W., Dagnino, B., Gariel-Mathis, M. A., Poort, J., Van Der Togt, C., & Roelfsema, P. R. (2014). Alpha and gamma oscillations characterize feedback and feedforward processing in monkey visual cortex. Proceedings of the National Academy of Sciences, 111(40), 14332-14341., 10.1073/pnas.1402773111; [5] Bollimunta, A., Mo, J., Schroeder, C. E., & Ding, M. (2011). Neuronal mechanisms and attentional modulation of corticothalamic alpha oscillations. Journal of Neuroscience, 31(13), 4935-4943., 10.1523/JNEUROSCI.5580-10.2011
000909873 520__ $$aThe alpha rhythm (~10 Hz) is one of the most studied oscillations in the brain and is mainly related to spontaneous ongoing activity. It particularly occurs over occipitoparietal regions of a variety of mammals during the eyes-closed condition. Classically, the alpha rhythm is associated with reductions in visual attention, but more recently other functions such as facilitation of the communication of top-down predictions to the visual cortex and stabilization of visual processing [1] have been suggested. An important step toward elucidating these functions is exploring how and where this oscillation originates. Several hypotheses point to thalamic and cortical circuits as the main source of the alpha rhythm, but the precise substrate and mechanism remain to be determined.The aim of this work is to build a cellularly resolved thalamocortical model involving the primary visual cortex and the lateral geniculate nucleus and study possible alpha generator hypotheses. The cortical component covers 1 mm2 of cortical surface and is divided into four layers (L2/3, L4, L5, and L6) each containing the full density of excitatory and inhibitory spiking neurons modeled by the adaptive exponential integrate-and-fire model. Cortical neurons in L4 and L6 receive thalamocortical connections. In turn, L6 neurons send feedback to thalamus. Two potential candidates for generating alpha were studied: 1) pyramidal neurons in L5 that produce rhythmic bursts around 10 Hz [2]; 2) a thalamocortical loop delay of around 100 ms previously suggested in mean-field models [3]. Current source density signals were estimated from the simulated spiking activity for direct comparison of spectra and Granger causality (GC) with experimental data [4, 5]. All network simulations were performed using the NEST simulator.The spontaneous activity of the cortical microcircuit was analyzed, and the two hypotheses were separately tested in the model. Our results show that both mechanisms are able to support alpha oscillations, but with different laminar patterns. Hypothesis 1 points to GC in the alpha range originating mainly in L5 and L2/3, while Hypothesis 2 points to L4 and L6 as the main source layers. These laminar patterns qualitatively reproduce empirical observations in monkey visual cortex from [4] and [5], respectively. Thus, the two proposed mechanisms may contribute differentially to alpha rhythms expressed in different individuals, brain states, or behavioral conditions.
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000909873 536__ $$0G:(GEPRIS)347572269$$aDFG project 347572269 - Heterogenität von Zytoarchitektur, Chemoarchitektur und Konnektivität in einem großskaligen Computermodell der menschlichen Großhirnrinde (347572269)$$c347572269$$x3
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000909873 650_7 $$2Other$$aComputational Neuroscience
000909873 650_7 $$2Other$$aNetworks, dynamical systems
000909873 7001_ $$0P:(DE-HGF)0$$aRoque, Antonio C.$$b1
000909873 7001_ $$0P:(DE-Juel1)138512$$avan Albada, Sacha$$b2$$ufzj
000909873 773__ $$a10.12751/NNCN.BC2022.268
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000909873 9101_ $$0I:(DE-HGF)0$$6P:(DE-HGF)0$$a University of Sao Paulo$$b1
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000909873 9101_ $$0I:(DE-HGF)0$$6P:(DE-Juel1)138512$$a University of Cologne$$b2
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