Dendritic excitability modulates dendritic information processing in a Purkinje cell model

can be done using with statistical tools derived from information theory (Shannon, 1948; Shannon and Weaver, 1949; Rieke, 1997). Particularly, determining mutual information (Foffani and Priori, 2007; Maffezzoli et al., 2008; Quian Quiroga and Panzeri, 2009) between synaptic activity and specifi c dendritic currents could result in a quantitative method to measure the contribution of individual dendritic currents on synaptic processing (Stemmler and Koch, 1999; London et al., 2002). Furthermore, the calculation of the entropy, conditional entropy and mutual information can help elucidate how much variability observed in the dendritic currents is due to the nature of the synaptic input or due to intrinsic properties of the dendrite. We present the results of calculating mutual information between the net excitatory input and different dendritic currents using a detailed biophysical model of a Purkinje cell (De Schutter and Bower, 1994a,b). The model was stimulated with randomly distributed excitatory and inhibitory synapses that resembled granule cell and interneuron activity. We found that the calcium (CaP) and a calcium activated potassium (Kc) currents carried the largest amount of information. While the fi ring rate of the Purkinje cell remained constant for different combinations of synaptic input, mutual information was sensitive to such changes, thus disambiguating synaptic activity in dendrites. Our results suggest that dendritic excitability modulated by CaP and Kc channels is most effective in regulating the mutual information, and INTRODUCTION The contribution of the passive dendritic properties of neurons on processing of synaptic activity is well established (Rall, 1962a,b; Marr, 1969; Pellionisz and Szentagothai, 1973, 1974); however, possibly all central nervous system neurons express voltage sensitive dendritic conductances (Llinas and Yarom, 1981; Hirst and McLachlan, 1986; Hockberger et al., 1989; Huguenard et al., 1989; Masukawa et al., 1991; Segev and London, 1999). Active conductances can carry more current than passive conductances and, thus, have a stronger contribution to the processing and transfer of synaptic activity in dendritic trees (Gollo et al., 2009). Furthermore, the multiple types of conductances found in dendrites could differentially fi lter synaptic activity depending on its temporal and spatial distribution (Poirazi and Mel, 2001; Migliore and Shepherd, 2002). Unfortunately, the lack of experimental access to determine the distribution and kinetics of active membrane conductances in dendrites has not allowed a thorough study of their infl uence on processing of synaptic activity. In order to track the transformation of synaptic activity, and thus obtain a representation of the transfer function of the dendrite, it is necessary to determine how synaptic activity is distributed over different dendritic currents. In many cases the variability observed in dendritic currents is driven by synaptic activity and can be regulated by interactions among conductances. Quantifying the amount of variability due to synaptic activity or due to internal interactions Dendritic excitability modulates dendritic information processing in a Purkinje cell model