Nonlinear dendrites enable robust stimulus selectivity

Hubel and Wiesel discovered that some neurons in the visual cortex (1) respond selectively to elongated visual stimuli of a particular orientation, proposing an elegant feedforward model to account for this selectivity. Since then, there has been much experimental support for this model, however several unexpected results, from in vivo two photon imaging of the dendrites of layer 2/3 pyramidal neurons in visual (2) and somatosensory (3) cortex cast doubt on the basic form of the model. Firstly, the dendrites may have different stimulus tuning to that of the soma. Secondly, hyperpolarizing a cell can result in it losing its stimulus selectivity, while the dendritic tuning remains unaffected. These results demonstrate the importance of dendrites in generating stimulus selectivity (4). Here, we implement stimulus selectivity in a biophysical model based on the realistic morphology of a layer 2/3 neuron, that can account for both of these experimental observations, within the feedforward framework motivated by Hubel and Wiesel. We show that this new model of stimulus selectivity is robust to the loss of synapses or dendrites, with stimulus selectivity maintained up to losses of 1/2 of the synapses, or 2/7 of the dendrites, demonstrating that in addition to increasing the computational capacity of neurons (5–8), dendrites also increase the robustness of neuronal computation. As well as explaining experimental results not predicted by Hubel and Wiesel, our study shows that dendrites enhance the resilience of cortical information processing, and prompts the development of new neuromorphic chips incorporating dendritic processing into their architecture.