Both in Neuroscience and in AI, the input-output transfer function of the units composing a large network is a pivotal element. Known as "activation function" (in Machine Learning) or as the frequency-current curve (in Neurobiology), it is a known mechanism of non-linearity as well as a biophysical primitive for neural computation.

We also know that its knowledge is instrumental (in Computational Neuroscience) to analyse and predict the collective behavior of real neuronal circuits by mean-field theories. Finally, in experimental Neuroscience, the estimate of the frequency-current curve of nerve cells has been used for over three decades to classify and make sense of neuronal diversitys. 

However, such a static description is inadequate to interpret how microcircuits and large networks of the brain process time-varying stimuli. Early theoretical studies and late experimental work from our group and others revealed how probing single-cell dynamical response properties is necessary to interpret of ultra-fast ensemble responses and other collective network phenomena. 

In this talk, I will review the results on dynamical response properties of neurons and neuronal ensembles and put them into context of the findings of unexpected differences between rodent and human cortical neurons.

Whethere these generalised biological features should be also considered for (Neuromorphic) implementation of AI systems, based on spiking neural models, is a question I will leave open to the audience.

Reference:

Linaro D, Ocker GK, Doiron B, Giugliano M (2019) Correlation transfer by layer 5 cortical neurons under recreated synaptic inputs in vitro, J Neuroscience, 39 (39) 7648-7663, https://doi.org/10.1523/JNEUROSCI.3169-18.2019  

Linaro D, Biró I, Giugliano M (2018) Dynamical response properties of neocortical neurons to conductance-driven time-varying inputs, European Journal of Neuroscience 47(1):17–32, https://doi.org/10.1111/ejn.13761 

Testa-Silva, G., Verhoog, M.B., de Kock, C.P.J., Baayen, J.C., Meredith, R.M., Giugliano, M.*, Mansvelder, H.D.* (2014) High bandwidth synaptic communication and frequency tracking in human neocortex. PLoS Biology 12(11):e1002007. http://dx.doi.org/10.1371/journal.pbio.1002007 

Köndgen, H., Geisler, C., Fusi, S., X.-J. Wang, Lüscher, H.-R., Giugliano, M. (2008) The dynamical response properties of neocortical neurons to temporally modulated noisy inputs in vitro, Cerebral Cortex 18(9), 665-670. http://dx.doi.org/10.1093/cercor/bhm235http://dx.doi.org/10.1093/cercor/bhm235