Skip to main content

Optimal Fisher Decoding of Neural Activity Near Criticality

  • Chapter
  • First Online:
The Functional Role of Critical Dynamics in Neural Systems

Part of the book series: Springer Series on Bio- and Neurosystems ((SSBN,volume 11))

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Albert, N.B., Robertson, E.M., Mehta, P., Miall, R.C.: Resting state networks and memory consolidation. Commun. Integr. Biol. 2, 530–532 (2009)

    Article  Google Scholar 

  2. Alstrøm, P.: Mean-field exponents for self-organized critical phenomena. Phys. Rev. A 38, 4905–4906 (1988)

    Article  Google Scholar 

  3. 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)

    Article  Google Scholar 

  4. de Arcangelis, L., Perrone-Capano, C., Herrmann, H.J.: Self-organized criticality model for brain plasticity. Phys. Rev. Lett. 96, 28107 (2006)

    Article  Google Scholar 

  5. Benayoun, M., Cowan, J.D., van Drongelen, W., Wallace, E.: Avalanches in a stochastic model of spiking neurons. PLoS Comput. Biol. 6, e1000846 (2010)

    Article  Google Scholar 

  6. 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)

    Article  Google Scholar 

  7. Braitenberg, V., Schüz, A.: Cortex: statistics and geometry of neuronal connectivity (Springer, 2013)

    Google Scholar 

  8. Buonomano, D.V., Maass, W.: State-dependent computations: spatiotemporal processing in cortical networks. Nat. Rev. Neurosci. 10, 113–125 (2009)

    Article  CAS  Google Scholar 

  9. 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)

    Article  Google Scholar 

  10. Christensen, K., Olami, Z.: Sandpile models with and without an underlying spatial structure. Phys. Rev. E 48, 3361–3372 (1993)

    Article  CAS  Google Scholar 

  11. Clauset, A., Shalizi, C.R., Newman, M.E.: Power-law distributions in empirical data. SIAM Rev. 51, 661–703 (2009)

    Article  Google Scholar 

  12. 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)

    Article  Google Scholar 

  13. Cunningham, J.P., Yu, B.M.: Dimensionality reduction for large-scale neural recordings. Nat. Neurosci. 17, 1500–1509 (2014)

    Article  CAS  Google Scholar 

  14. 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)

    Article  Google Scholar 

  15. 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)

    Article  Google Scholar 

  16. 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)

    Article  Google Scholar 

  17. Harris, K.D.: Neural signatures of cell assembly organization. Nat. Rev. Neurosci. 6, 399–407 (2005)

    Article  CAS  Google Scholar 

  18. 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)

    Article  Google Scholar 

  19. Kelly, C., Castellanos, F.X.: Strengthening connections: functional connectivity and brain plasticity. Neuropsychol. Rev. 24, 63–76 (2014)

    Article  Google Scholar 

  20. 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)

    Article  CAS  Google Scholar 

  21. 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)

    Article  Google Scholar 

  22. 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)

    Article  Google Scholar 

  23. Lübeck, S.: Universal scaling behavior of non-equilibrium phase transitions. Int. J. Mod. Phys. B 18, 3977–4118 (2004)

    Article  Google Scholar 

  24. 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)

    Article  CAS  Google Scholar 

  25. McLachlan, G.: Discriminant Analysis and Statistical Pattern Recognition (Wiley, 2004)

    Google Scholar 

  26. 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)

    Article  Google Scholar 

  27. 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)

    Article  CAS  Google Scholar 

  28. 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)

    Article  CAS  Google Scholar 

  29. 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)

    Article  CAS  Google Scholar 

  30. Plenz, D., Thiagarajan, T.C.: The organizing principles of neuronal avalanches: cell assemblies in the cortex? Trends Neurosci. 30, 101–110 (2007)

    Article  CAS  Google Scholar 

  31. Rich, E.L., Wallis, J.D.: Decoding subjective decisions from orbitofrontal cortex. Nat. Neurosci. 19, 973–980 (2016)

    Article  CAS  Google Scholar 

  32. Shaukat, A., Thivierge, J.-P.: Statistical evaluation of waveform collapse reveals scale-free properties of neuronal avalanches. Front. Comput. Neurosci. 10, 29 (2016)

    Article  Google Scholar 

  33. 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)

    Article  CAS  Google Scholar 

  34. 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)

    Article  CAS  Google Scholar 

  35. 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)

    Article  CAS  Google Scholar 

  36. Thivierge, J.-P.: Scale-free and economical features of functional connectivity in neuronal networks. Phys. Rev. E 90, 22721 (2014)

    Article  Google Scholar 

  37. Thivierge, J.-P., Cisek, P.: Nonperiodic synchronization in heterogeneous networks of spiking neurons. J. Neurosci. 28, 7968–7978 (2008)

    Article  CAS  Google Scholar 

  38. Tomen, N., Rotermund, D., Ernst, U.: Marginally subcritical dynamics explain enhanced stimulus discriminability under attention. Front. Syst. Neurosci. 8, 151 (2014)

    Article  Google Scholar 

  39. Vincent, K., Tauskela, J.S., Thivierge, J.-P.: Extracting functionally feedforward networks from a population of spiking neurons. Front. Comput. Neurosci. 6, 86 (2012)

    Article  Google Scholar 

  40. Vincent, K., Tauskela, J.S., Mealing, G.A., Thivierge, J.-P.: Altered network communication following a neuroprotective drug treatment. PLoS One 8, e54478 (2013)

    Article  CAS  Google Scholar 

  41. Zapperi, S., Bækgaard, Lauritsen K., Stanley, H.E.: Self-organized branching processes: mean-field theory for avalanches. Phys. Rev. Lett. 75, 4071–4074 (1995)

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jean-Philippe Thivierge .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

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

Download citation

Publish with us

Policies and ethics