Stimulus Selection with Synaptic Clustering

It is becoming technically feasible to map the detailed pattern of synaptic enervation in the dendrites of pyramidal cells (Petreanu et al., 2009), and this has revealed that there is clustering of synapses from presynaptic neurons onto sub-domains of the dendrites. The question examined in this thesis is whether the clustering of synapses can be utilized to produce or enhance stimulus selection for rapidly varying signals in a model of a layer 2/3 pyramidal neuron (Traub et al., 2003).

This dissertation examines three variations on the theme of stimulus selection ex- ploiting the location of synapses. The simplest is the colocation case, where inhibitory and excitatory neurons driven by the same signal are located in the same dendritic sub-domain. In the baseline case, inhibition and excitation are balanced so that the neuron does not produce any spikes, and to “select” a stimulus, the inhibitory firing

rate is reduced, allowing the neuron to fire. In the second case, inhibition and exci- tation following a given signal are contralocated - that is, excitation is located on one dendritic sub-branch, while inhibition is located on another. In the presence of two signals, inhibition following signal 2, for instance, will be located with the excitatory activity representing signal 1 and vice versa. I finally examined the case where there is no specificity at all in either inhibitory or excitatory synaptic activity. Although I do present a significant difference in the ability of inhibition to modulate the output firing rate of a neuron depending on whether it is colocated or contralocated with excitation (see Figure 5.6), these results depend on the inhibited branch being unexcited, and only occur with numerical significance when averaged over long time intervals. When driven simultaneously by two signals, there is not a statistically significant difference between the selection in the colocated or contralocated cases. These results indicate that while receiving time varying signals and background firing, the Traub model neuron is too electronically compact for synaptic location to be a significant factor in selecting signals varying on a timescale of 250 ms or below.

Comparison to Previous Simulation Results and Limitations of This Study

The implications of synaptic clustering in dendritic sub-domains of the dendrites are not well characterized. Archie and Mel (2000) examined the question in a similar model neuron for constant firing rate stimuli and found that using a contralaterally arranged set of synaptic inputs, modulations were observed that were consistent with experimental studies of firing rate modulations and attention. The results of this present study are consistent with those reported in Archie and Mel (2000), with the novel addition that stimulus selection is accomplished for time varying signals. Alternative synaptic layout strategies were not examined in the Archie and Mel (2000) study. This dissertation also contributes the novel result that, at least for time varying signals, the

layout of synapses in dendritic subdomains is unimportant for selection, which depends only on maintaining or selectively perturbing the balance of inhibition and excitation. The small effect of the location of synapses on the response properties of the neuron during stimulation by multiple sources of input raises the question of why clustering of synapses in the dendrites is observed at all (Petreanu et al., 2009). One answer may be that the model neuron used in this dissertation, originally described by Traub et al. (2003), is not appropriate for the examination of this question. The Traub model was constructed to reproduce fast and slow dendritic Ca2+ _{spikes, with the goal of studying}

experimentally observed bursting behavior. Neither behavior is examined explicitly in this dissertation. The choice of the Traub model was motivated by a desire to use a biophysically motivated Layer 2/3 pyramidal cell model. Nevertheless, there are two limitations to this model. First, the nature and distribution of ion channels in the dendrites of Layer 2/3 pyramidal neurons is not well understood. In pyramidal cells in L5 or CA1 where the distribution of channels is better studied, the character of the dendrites varies between cell types (Gasparini and Magee, 2006; Schaefer et al., 2007; Migliore et al., 1995; Prescott and De Koninck, 2003)), suggesting that the results from other cell types cannot be easily generalized to Layer 2/3 cells. Secondly, the morphology of the basal dendrites is highly idealized in the Traub model. Either of these limitations may restrict the usefulness of the results reported here. Future research on the subject of selection by modulation of neural populations with selective synaptic locations should examine the question of dendritic electrophysiology and morphology more carefully.

Future Work

Future work in this area would be advanced by examining the model of the Layer 2/3 pyramidal cell and by examining the same question in the context of other pyramidal

cell varieties. Although there are other mechanisms which explain the discrepancy between the results reported for time varying signals, and the ability of contralocated inhibition to lower the firing rate of a neuron more effectively than colocated inhibition, one factor may be the relatively high variability of the output spike trains in these results. Specifically, when the input frequency varies rapidly in time, the firing rate variability in a short time interval may be large enough to obscure differences in rate which are obvious at longer time scales. As a consequence, one possible mechanism which may illuminate differences between synaptic layout strategies is the addition of an oscillatory component to some or all of the inhibitory inputs arriving at the neuron. Although this would introduce a time scale limit on the possible frequency content of the selected stimuli similar to the one reported for oscillatory selection, it would also reduce spike count variability by synchronizing spikes to the oscillation, which may reveal significant differences in selection strategies. On a related note, a combination of this method with oscillatory selection may reveal that the two combined produce better selection than either mechanism in isolation.