Scientific Understanding of Consciousness
Dendritic Discrimination of Temporal Input Sequences
Science 24 September 2010: Vol. 329 no. 5999 pp. 1671-1675
Dendritic Discrimination of Temporal Input Sequences in Cortical Neurons
Tiago Branco, Beverley A. Clark and Michael Häusser
Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology, and Pharmacology, University College London, Gower Street, London WC1E 6BT, UK.
The detection and discrimination of temporal sequences is fundamental to brain function and underlies perception, cognition, and motor output. By applying patterned, two-photon glutamate uncaging, we found that single dendrites of cortical pyramidal neurons exhibit sensitivity to the sequence of synaptic activation. This sensitivity is encoded by both local dendritic calcium signals and somatic depolarization, leading to sequence-selective spike output. The mechanism involves dendritic impedance gradients and nonlinear synaptic NMDA receptor activation and is generalizable to dendrites in different neuronal types. This enables discrimination of patterns delivered to a single dendrite, as well as patterns distributed randomly across the dendritic tree. Pyramidal cell dendrites can thus act as processing compartments for the detection of synaptic sequences, thereby implementing a fundamental cortical computation.
In sensory pathways, the relative timing of spikes from different neuronal populations can represent features of stimuli. A fundamental problem in cortical sensory processing is, thus, the discrimination of different spatiotemporal sequences of inputs. Although networks composed of simple neurons can, in principle, decode temporal sequences, the size and complexity of such networks can be greatly reduced if individual neurons can perform temporal decoding. Dendritic trees might contribute to this decoding, because they are highly nonlinear devices that can locally process and integrate synaptic signals. For example, spatiotemporally clustered inputs trigger dendritic spikes, which can generate independent functional subunits, enhancing the computational potential of the neuron and encoding spatial and temporal input synchrony. Whether these nonlinear dendritic properties can be exploited to perform higher-order computations such as temporal sequence detection is unknown. In 1964, Wilfrid Rall predicted that, because dendrites act as a delay line, activation of synapses along a dendrite in different directions should produce different responses at the soma. Although the dendrites of retinal neurons exhibit such direction selectivity, experimental investigation of the sensitivity to spatiotemporal sequences of synaptic activation in cortical pyramidal cell dendrites has been a challenge due to the difficulty in delivering the spatiotemporal input patterns with the necessary submillisecond and submicron precision.
To test the sensitivity of single dendrites to the order of activation of a defined set of synapses, we controlled spatiotemporal input patterns using multisite, two-photon glutamate uncaging at identified dendritic spines in layer 2/3 pyramidal neurons of somatosensory and visual cortex.
We have shown that single cortical pyramidal cell dendrites can encode the temporal sequence of synaptic input. The underlying mechanism relies on the interplay between nonlinear activation of synaptic NMDA receptors and the impedance gradient along dendritic branches, two fundamental biophysical features common to most neurons in the brain. The active, regenerative nature of this mechanism contrasts with the classic, passive directional selectivity proposed by Rall, which requires electrotonically very long dendrites. Instead, the NMDA-dependent mechanism produced strong sensitivity to the direction of synaptic input, even in short pyramidal cell dendrites, making it more general and sensitive to synaptic input, robust against timing jitter, and further enhanced and tunable by depolarization [such as in network UP states]. Different input sequences also lead to differential dendritic Ca++ signals, raising the possibility that they will engage plasticity mechanisms to different extents. The large dynamic range conferred by NMDA receptor activation allowed for high discriminability of multiple temporal sequences, both when inputs were on the same dendrite or when they were dispersed over the dendritic tree. This further extends the range of computational and plasticity mechanisms that have recently been described in dendrites. In particular, this sensitivity to temporal input sequences may be relevant for detecting features of sensory stimuli and for encoding the speed and directionality of waves of activity propagating in the cortex. It is also especially relevant for circuits with layered input such as the hippocampus, where this mechanism could be used by dentate gyrus granule cells to directly detect the sequence of entorhinal cortex activation. These computations are conventionally thought to be implemented at the level of neural populations, and thus, our results represent a demonstration of the power of dendrites for solving computational problems in the brain.
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