Research

I hold a PhD in Computer Science from the University of Cyprus. My research area is Computational Neuroscience and specifically Neural Coding. My doctoral thesis, titled Understanding the neural code through exploration of the causes of firing is available from the UCy Library archive [PDF].

Research interests

  • Computational models of single neurons.
  • Understanding the role of time in neural processing: temporal and rate codes, timescales and precision of neural processing.
  • Understanding the function and signficance of synchrony in signal propagation through neural networks.

Academic background

My background is in Computer Science (BSc) and Intelligent Systems (MSc). I obtained both degrees from the School of Computer Science of the University of Birmingham. I remain interested in the field of Intelligent Systems and part of my future research goals is to integrate knowledge from relevant fields, such as Machine Learning and Artificial Intelligence to the study of neural systems.

Code

Simulations and data analysis

Most of the code I have written for my research and publications can be found on my GitHub page. The code is separated into multiple repositories, all of which are organised as submodules of a general research repository.

Spikerlib

Spikerlib is a Python (2.x) library of tools and functions for spiketrain analysis. Some features of the library depend on the Brian simulator (ver. 1x).

Publications

Journal Papers

  1. Koutsou, A., Kanev, J., Economidou, M., and Christodoulou C. Integrator or Coincidence Detector — What shapes the relation of stimulus synchrony and the operational mode of a neuron? Mathematical Biosciences and Engineering, 13(3), 521-535. doi:10.3934/mbe.2016005
  1. Koutsou, A., Bugmann G., and Christodoulou C. On learning time delays between the spikes from different input neurons in a biophysical model of a pyramidal neuron. Biosystems, 136, 80-89. doi:10.1016/j.biosystems.2015.08.005 [PDF]
  1. Koutsou, A., Kanev, J., and Christodoulou C. Measuring input synchrony in the Ornstein-Uhlenbeck neuronal model through input parameter estimation. Brain Research, 1536, 97-106. doi:10.1016/j.brainres.2013.05.012
  1. Koutsou, A., Christodoulou, C., Bugmann, G. and Kanev, J. Distinguishing the Causes of Firing with the Membrane Potential Slope. Neural Computation, 24 (9), 2318-2345. doi:10.1162/NECO_a_00323 [PDF]

Conference Proceedings

  1. Koutsou, A. and He, S. Study of ants' traffic organisation under crowded conditions using individual-based modelling and evolutionary computation. Proceedings of IEEE Congress on Evolutionary Computation 2009 (CEC '09), 3330-3337. doi:10.1109/CEC.2009.4983367