As a consequence, EAP amplitude is approximately proportional to the sum of the dendritic cross-sectional areas of all dendritic branches connected to the soma. Therefore, neurons with thick dendrites connected to the soma produce large EAPs and have the largest “radius of visibility” (Pettersen and Einevoll, 2008). At the same time, PSCs are mainly located along thin dendrites (i.e., much higher

axial resistance), preventing return currents from spreading along the whole neural morphology. Another important observation stemming from our simulations is the input specificity of the LFP composition. Although the LFP during the first 50–80 ms from UP onset is dominated by K currents originating from L5 pyramids for temporally coordinated input (Figure 7B), this switches to K currents from L4 pyramids for uncorrelated input SB431542 purchase (Figure 7A). Moreover, basket cells generally do not contribute markedly to the LFP, but this changes briefly 50 to 70 ms after UP onset. Thus, the LFP composition is not static but time- and state-dependent and is crucially impacted by the impinging input and the sort of

subthreshold and spiking activity it induces (especially proximally to the recording site). What are the functional (computational) ramifications of these observations? Coherence between spiking and specific LFP bands has been used to infer the relationship between synaptic input (hitherto considered to be reflected in the LFP) and neural output (spiking) and thereby specific mechanisms of information processing Dasatinib molecular weight within and across brain regions (Fries

et al., 1997, Lee et al., 2005, Montgomery et al., 2008, O’Keefe GBA3 and Recce, 1993, Rutishauser et al., 2010 and Womelsdorf et al., 2006). This raises the question of the extent to which the locally generated LFP (or particular bandwidths of it) represent actual synaptic input impinging on local neurons rather than spiking output (Buzsáki et al., 2012). For example, it was recently shown that spiking coherence to ripples during sharp waves in CA1 is partly attributed to spiking currents shaping the ripple signal (Belluscio et al., 2012 and Schomburg et al., 2012). Another question arises regarding how perturbing rhythmic LFP activity such as theta with tetanic stimulation at particular phases of theta induces potentiation or depression of synaptic strength (Hölscher et al., 1997, Hyman et al., 2003 and Pavlides et al., 1988). Other studies relate cognitive alteration to perturbation of neocortical UP-DOWN states (Marshall et al., 2006) or hippocampal sharp waves (Girardeau et al., 2009). Our population model does not attempt to reproduce any particular LFP rhythm, but it does link the LFP to biophysical processing. Thus, it can become a useful tool toward addressing the involvement of particular mechanisms during particular LFP bandwidths and phases and how perturbing them crucially alters other processing and, ultimately, cognitive function.