Abstract
Studies on the functional role of criticality in the brain have thus far mainly examined the role of neural dynamics on stimulus encoding, with scant attention devoted to the impact of these dynamics on downstream decoding. Here, we consider the question of how a linear decoder may classify spontaneous cortical activity both near and away from a critical state. We show that accurate performance of the decoder is obtained only when network activity is near criticality. Simulations of a branching process capture these results and argue for a potential role of the critical state in providing a format for neural activity that can be adequately processed by downstream brain structures.
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References
Albert, N.B., Robertson, E.M., Mehta, P., Miall, R.C.: Resting state networks and memory consolidation. Commun. Integr. Biol. 2, 530–532 (2009)
Alstrøm, P.: Mean-field exponents for self-organized critical phenomena. Phys. Rev. A 38, 4905–4906 (1988)
de Arcangelis, L., Herrmann, H.J.: Learning as a phenomenon occurring in a critical state. Proc. Natl. Acad. Sci. U. S. A. 107, 3977–3981 (2010)
de Arcangelis, L., Perrone-Capano, C., Herrmann, H.J.: Self-organized criticality model for brain plasticity. Phys. Rev. Lett. 96, 28107 (2006)
Benayoun, M., Cowan, J.D., van Drongelen, W., Wallace, E.: Avalanches in a stochastic model of spiking neurons. PLoS Comput. Biol. 6, e1000846 (2010)
Berberian, N., MacPherson, A., Giraud, E., Richardson, L., Thivierge, J.-P.: Neuronal pattern separation of motion-relevant input in LIP activity. J. Neurophysiol. 117, 738–755 (2017)
Braitenberg, V., Schüz, A.: Cortex: statistics and geometry of neuronal connectivity (Springer, 2013)
Buonomano, D.V., Maass, W.: State-dependent computations: spatiotemporal processing in cortical networks. Nat. Rev. Neurosci. 10, 113–125 (2009)
Calderini, M., Zhang, S., Berberian, N., Thivierge, J.-P.: Optimal readout of correlated neural activity in a decision-making circuit. Neural Comput. 30, 1573–1611 (2018)
Christensen, K., Olami, Z.: Sandpile models with and without an underlying spatial structure. Phys. Rev. E 48, 3361–3372 (1993)
Clauset, A., Shalizi, C.R., Newman, M.E.: Power-law distributions in empirical data. SIAM Rev. 51, 661–703 (2009)
Clawson, W.P., Wright, N.C., Wessel, R., Shew, W.L.: Adaptation towards scale-free dynamics improves cortical stimulus discrimination at the cost of reduced detection. PLoS Comput. Biol. 13, e1005574 (2017)
Cunningham, J.P., Yu, B.M.: Dimensionality reduction for large-scale neural recordings. Nat. Neurosci. 17, 1500–1509 (2014)
Friedman, N., Ito, S., Brinkman, B.A.W., Shimono, M., DeVille, R.E.L., Dahmen, K.A., Beggs, J.M., Butler, T.C.: Universal critical dynamics in high resolution neuronal avalanche data. Phys. Rev. Lett. 108, 208102 (2012)
Gautam, S.H., Hoang, T.T., McClanahan, K., Grady, S.K., Shew, W.L.: Maximizing sensory dynamic range by tuning the cortical state to criticality. PLoS Comput. Biol. 11, e1004576 (2015)
Hahn, G., Ponce-Alvarez, A., Monier, C., Benvenuti, G., Kumar, A., Chavane, F., Deco, G., Frégnac, Y.: Spontaneous cortical activity is transiently poised close to criticality. PLoS Comput. Biol. 13, e1005543 (2017)
Harris, K.D.: Neural signatures of cell assembly organization. Nat. Rev. Neurosci. 6, 399–407 (2005)
Ihlen, E.A.F., Vereijken, B.: Interaction-dominant dynamics in human cognition: beyond 1/f(alpha) fluctuation. J. Exp. Psychol. Gen. 139, 436–463 (2010)
Kelly, C., Castellanos, F.X.: Strengthening connections: functional connectivity and brain plasticity. Neuropsychol. Rev. 24, 63–76 (2014)
Kuebler, E.S., Tauskela, J.S., Aylsworth, A., Zhao, X., Thivierge, J.-P.: Burst predicting neurons survive an in vitro glutamate injury model of cerebral ischemia. Sci. Rep. 5, 17718 (2015)
Langlois, D., Cousineau, D., Thivierge, J.P.: Maximum likelihood estimators for truncated and censored power-law distributions show how neuronal avalanches may be misevaluated. Phys. Rev. E 89, 12709 (2014)
LeBlanc, M., Angheluta, L., Dahmen, K., Goldenfeld, N.: Universal fluctuations and extreme statistics of avalanches near the depinning transition. Phys. Rev. E 87, 22126 (2013)
Lübeck, S.: Universal scaling behavior of non-equilibrium phase transitions. Int. J. Mod. Phys. B 18, 3977–4118 (2004)
Martin, K.A.C., Schröder, S.: Functional heterogeneity in neighboring neurons of cat primary visual cortex in response to both artificial and natural stimuli. J. Neurosci. 33, 7325–7344 (2013)
McLachlan, G.: Discriminant Analysis and Statistical Pattern Recognition (Wiley, 2004)
Mehta, A.P., Mills, A.C., Dahmen, K.A., Sethna, J.P.: Universal pulse shape scaling function and exponents: critical test for avalanche models applied to Barkhausen noise. Phys. Rev. E 65, 46139 (2002)
Ngodup, T., Goetz, J.A., McGuire, B.C., Sun, W., Lauer, A.M., Xu-Friedman, M.A.: Activity-dependent, homeostatic regulation of neurotransmitter release from auditory nerve fibers. Proc. Natl. Acad. Sci. U. S. A. 112, 6479–6484 (2015)
Ohki, K., Chung, S., Ch’ng, Y.H., Kara, P., Reid, R.C.: Functional imaging with cellular resolution reveals precise micro-architecture in visual cortex. Nature 433, 597–603 (2005)
Panzeri, S., Harvey, C.D., Piasini, E., Latham, P.E., Fellin, T.: Cracking the neural code for sensory perception by combining statistics, intervention, and behavior. Neuron 93, 491–507 (2017)
Plenz, D., Thiagarajan, T.C.: The organizing principles of neuronal avalanches: cell assemblies in the cortex? Trends Neurosci. 30, 101–110 (2007)
Rich, E.L., Wallis, J.D.: Decoding subjective decisions from orbitofrontal cortex. Nat. Neurosci. 19, 973–980 (2016)
Shaukat, A., Thivierge, J.-P.: Statistical evaluation of waveform collapse reveals scale-free properties of neuronal avalanches. Front. Comput. Neurosci. 10, 29 (2016)
Shew, W.L., Yang, H., Yu, S., Roy, R., Plenz, D.: Information capacity and transmission are maximized in balanced cortical networks with neuronal avalanches. J. Neurosci. 31, 55–63 (2011)
Tan, A.Y.Y., Chen, Y., Scholl, B., Seidemann, E., Priebe, N.J.: Sensory stimulation shifts visual cortex from synchronous to asynchronous states. Nature 509, 226–229 (2014)
Tang, A., Jackson, D., Hobbs, J., Chen, W., Smith, J.L., Patel, H., Prieto, A., Petrusca, D., Grivich, M.I., Sher, A., et al.: A maximum entropy model applied to spatial and temporal correlations from cortical networks in vitro. J. Neurosci. 28, 505–518 (2008)
Thivierge, J.-P.: Scale-free and economical features of functional connectivity in neuronal networks. Phys. Rev. E 90, 22721 (2014)
Thivierge, J.-P., Cisek, P.: Nonperiodic synchronization in heterogeneous networks of spiking neurons. J. Neurosci. 28, 7968–7978 (2008)
Tomen, N., Rotermund, D., Ernst, U.: Marginally subcritical dynamics explain enhanced stimulus discriminability under attention. Front. Syst. Neurosci. 8, 151 (2014)
Vincent, K., Tauskela, J.S., Thivierge, J.-P.: Extracting functionally feedforward networks from a population of spiking neurons. Front. Comput. Neurosci. 6, 86 (2012)
Vincent, K., Tauskela, J.S., Mealing, G.A., Thivierge, J.-P.: Altered network communication following a neuroprotective drug treatment. PLoS One 8, e54478 (2013)
Zapperi, S., Bækgaard, Lauritsen K., Stanley, H.E.: Self-organized branching processes: mean-field theory for avalanches. Phys. Rev. Lett. 75, 4071–4074 (1995)
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Kuebler, E.S., Calderini, M., Lambert, P., Thivierge, JP. (2019). Optimal Fisher Decoding of Neural Activity Near Criticality. In: Tomen, N., Herrmann, J., Ernst, U. (eds) The Functional Role of Critical Dynamics in Neural Systems . Springer Series on Bio- and Neurosystems, vol 11. Springer, Cham. https://doi.org/10.1007/978-3-030-20965-0_9
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DOI: https://doi.org/10.1007/978-3-030-20965-0_9
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