Abstract
Anatomical similarity across the neocortex has led to the common assumption that the circuitry is modular and performs stereotyped computations. Layer 5 pyramidal neurons (L5PNs) in particular are thought to be central to cortical computation because of their extensive arborisation and nonlinear dendritic operations. Here, we demonstrate that computations associated with dendritic Ca2+ plateaus in mouse L5PNs vary substantially between the primary and secondary visual cortices. L5PNs in the secondary visual cortex show reduced dendritic excitability and smaller propensity for burst firing. This reduced excitability is correlated with shorter apical dendrites. Using numerical modelling, we uncover a universal principle underlying the influence of apical length on dendritic backpropagation and excitability, based on a Na+ channel-dependent broadening of backpropagating action potentials. In summary, we provide new insights into the modulation of dendritic excitability by apical dendrite length and show that the operational repertoire of L5PNs is not universal throughout the brain.
Highlights
The neocortex is thought to have a modular structure composed of ‘canonical circuits’ performing stereotyped computations (Harris and Shepherd, 2015; Markram et al, 2015; Miller, 2016)
To ensure consistency in cell type, recordings were restricted to Layer 5 pyramidal neurons (L5PNs) projecting to the lateral posterior nucleus of thalamus (n = 117), identified using retrograde labelling with cholera toxin subunit B (CTB, Figure 1—figure supplement 1A–E), or to neurons labelled in the Colgalt2-Cre mouse line (n = 12) known to be tufted layer 5 pyramidal neurons (ttL5) PNs (Groh et al, 2010; Kim et al, 2015)
While dendritic signals typically attenuate with distance, these results suggest that there may be a counterintuitive interaction between apical trunk length and dendritic Ca2+ electrogenesis in ttL5s – the further backpropagating action potential (bAP) need to travel along the trunk, the more they can trigger Ca2+ plateaus
Summary
The neocortex is thought to have a modular structure composed of ‘canonical circuits’ performing stereotyped computations (Harris and Shepherd, 2015; Markram et al, 2015; Miller, 2016). Layer 5 pyramidal neurons (L5PNs) in particular provide a striking example of how dendritic properties can underlie circuit-level computations in a laminar circuit. Their dendritic nonlinearities enable signal amplification and coincidence detection of inputs – a crucial operation to integrate feedforward and feedback streams that often send projections onto separate dendritic domains. It is often assumed that pyramidal neurons have robust enough properties across cortical areas and brain structures to support similar computations (Bastos et al, 2012; Hawkins et al, 2017; Larkum, 2013; Shipp, 2016). Our results question the notion of a common operational repertoire in pyramidal neurons and of cortical canonical computations more generally
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