Neurocomputing 70 (2007) 1630–1634 Neural response profile design: Reducing epileptogenic activity by modifying neuron responses to synchronized input using novel potassium channels obtained by parameter search optimization Erik Franse´n School of Computer Science and Communication, Royal Institute of Technology, SE-100 44 Stockholm, Sweden Available online 28 October 2006 Abstract Neurons obtain their dynamical electrical characteristics by a set of ion channels. These properties may not only affect the function of the neuron and the local network it forms part of, but it may also eventually affect behavior. We were interested to study whether epileptogenic activity could be reduced by adding an ion channel. In this work, we used computational search techniques to optimize ion channel properties for the goal of modifying neural response characteristics. Our results show that this type of parameter search is possible and reasonably efficient. Successful searches were generated using the direct method PRAXIS, and by systematic searches in low-dimensional sub-spaces. We also report on unsuccessful searches using a simplex-type method, a gradient-based method, and attempts to reduce goal function evaluation time. Importantly, using this search strategy, our study has shown that it is possible to change a neuron’s characteristics selectively with regard to response to degree of synchronicity in synaptic input. r 2006 Elsevier B.V. All rights reserved. Keywords: Optimization; Computational search; Biophysical modeling; Potassium channel; Synchronization; Epileptogenesis 1. Introduction Synchronous activity is an integral part of brain function. For instance, when solving a cognitive challen- ging task such as traversing a maze, human subjects show a correlation between task load and EEG gamma band power [7]. Further, the degree of synchronicity during encoding in a learning task correlates with subsequent recall [11]. It is, however, conceivable that there is an optimum with regard to synchronicity of brain activity, and that hyper synchronous firing, or increased neural spike response to synchronous input, leads to pathological states such as epileptic seizures. At the single neuron level, there may under normal conditions be mechanisms that maximizes processing while proving sufficient safety margins to undesirable hypersynchronous states. In patho- logical cases, these mechanisms may be compromised or insufficient. In a network of neurons, spike production is a key process. A spike is produced when the membrane potential passes the ‘‘spike threshold’’ region at sufficient slope. The potential trajectory leading to this point will be different if the input is highly synchronized or if it is weakly synchronized. Membrane ion channels provide neurons with properties affecting neural function, among other synaptic spatio-temporal summation. We hypothesized that it would be possible to find an ion channel that could selectively discriminate the potential trajectory from synchronized input showing e.g. large and fast variations from the trajectory by weakly synchronized input showing smaller slower and more frequent variations in amplitude. Parameter optimization has been used in computational neuroscience to find e.g. suitable parameters for Hodgkin– Huxley equations given voltage clamp and current clamp data [2,14]. The goal then is to produce a model that accurately describes experimental data. In this work we instead want to find optimal ion channel parameters that change the characteristics of a model neuron in order to change its response characteristics to synchronized input. ARTICLE IN PRESS www.elsevier.com/locate/neucom 0925-2312/$ - see front matter r 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.neucom.2006.10.046 E-mail address: erikf@csc.kth.se.