Abstract
We investigated the relevance of single-unit recordings in the context of dynamical neural systems with recurrent synapses. The present study focuses on modeling a relatively small, biologically-plausible network of neurons. In the absence of any input, the network activity is self-sustained due to the resonating properties of the neurons. Recording of single units reveals an increasingly complex response to stimulation as one proceeds higher into the processing stream hierarchy. Results suggest that classical analysis methods, using rate and averaging over trials, fail to describe the dynamics of the system, and instead hide the relevant information embedded in the complex states of the network. We conclude that single-unit recordings, which are still extensively used in experimental neuroscience, need to be more carefully interpreted.
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References
Dayan, P., Abbott, L.F.: Theoretical Neuroscience. MIT Press, Cambridge (2001)
Fellous, J.M., Houweling, A.R., Modi, R.H., Rao, R.P.N., Tiesinga, P.H.E., Sejnowski, T.J.: Frequency dependence of spike timing reliability in cortical pyramidal cells and in-terneurons. J. Neurophysiol. 85, 1782–1787 (2001)
Gerstner, W., Kistler, W.M.: Spiking Neuron Models: Single Neurons, Populations, Plasticity. Cambridge University Press, New York (2002)
Izhikevich, E.M.: Resonate-and-Fire Neurons. Neural Networks 14, 883–894 (2001)
Izhikevich, E.M.: Resonance and Selective Communication Via Bursts in Neurons Having Subthreshold Oscillations. BioSystems 67, 95–102 (2002)
Izhikevich, E.M.: Simple Model of Spiking Neurons. IEEE Transactions on Neural Networks 14, 1569–1572 (2003)
Maass, W., Natschläger, T., Markram, H.: Computational models for generic cortical microcircuits. In: Feng, J. (ed.) Computational Neuroscience: A Comprehensive Approach, ch. 18, pp. 575–605. Chapman & Hall/CRC, Boca Raton (2004)
Natschläger T., Maass W., Zador A. Efficient temporal processing with biologically realistic dynamic synapses. Network: Computation in Neural Systems, 2001, 12:75-87.
Singer, W.: Response synchronization: a universal coding strategy for the definition of relations. In: Gazzaniga, M.S. (ed.) The Cognitive Neurosciences. MIT Press, Cambridge (1999)
Super, H., Roelfsema, P.: Chronic multiunit recordings in behaving animals: advantages and limitations. Progress in Brain Research 147, 263–281 (2005)
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Mureşan, R.C., Pipa, G., Wheeler, D.W. (2005). Single-Unit Recordings Revisited: Activity in Recurrent Microcircuits. In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds) Artificial Neural Networks: Biological Inspirations – ICANN 2005. ICANN 2005. Lecture Notes in Computer Science, vol 3696. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550822_25
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DOI: https://doi.org/10.1007/11550822_25
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