Scientific Understanding of Consciousness
Consciousness as an Emergent Property of Thalamocortical Activity

Network Local Synaptic Connections



Nature, 473, 87–91  (05 May 2011)

Functional specificity of local synaptic connections in neocortical networks

Ho Ko,  Sonja B. Hofer, Bruno Pichler, Katherine A. Buchanan, P. Jesper Sjöström & Thomas D. Mrsic-Flogel

Department of Neuroscience, Physiology and Pharmacology, University College London, 21 University Street, London WC1E 6DE, UK


Neuronal connectivity is fundamental to information processing in the brain. Therefore, understanding the mechanisms of sensory processing requires uncovering how connection patterns between neurons relate to their function. On a coarse scale, long-range projections can preferentially link cortical regions with similar responses to sensory stimuli. But on the local scale, where dendrites and axons overlap substantially, the functional specificity of connections remains unknown.

Here we determine synaptic connectivity between nearby layer 2/3 pyramidal neurons in vitro, the response properties of which were first characterized in mouse visual cortex in vivo. We found that connection probability was related to the similarity of visually driven neuronal activity. Neurons with the same preference for oriented stimuli connected at twice the rate of neurons with orthogonal orientation preferences. Neurons responding similarly to naturalistic stimuli formed connections at much higher rates than those with uncorrelated responses. Bidirectional synaptic connections were found more frequently between neuronal pairs with strongly correlated visual responses. Our results reveal the degree of functional specificity of local synaptic connections in the visual cortex, and point to the existence of fine-scale subnetworks dedicated to processing related sensory information.

Paired intracellular recordings in cortical slices indicate that synaptic connectivity between neighbouring neurons is heterogeneous and depends on factors such as cell type, electrophysiological properties and long-range targets. In fact, even within relatively homogenous groups of neurons, connectivity is not uniformly distributed. Although this non-random connectivity raises the possibility that functionally similar neurons form synaptically coupled subnetworks, the relationship between a neuron’s synaptic partners and their functional properties in local cortical circuits has not been determined.

To elucidate this relationship, we developed an approach to relate connectivity to function in identified neurons of the layer 2/3 (L2/3) network in mouse visual cortex (V1), where neurons with diverse preferences for sensory stimuli are locally intermixed.

We carried out simultaneous whole-cell patch-clamp recordings from up to four neighbouring L2/3 pyramidal neurons (mean distance ± standard deviation (s.d.) = 25 ± 9 µm). Synaptic connectivity between cells was assessed by evoking action potentials in each neuron in turn while simultaneously recording membrane potential in the other neurons. Monosynaptic connections appeared as spike-locked postsynaptic potentials with millisecond latency (mean latency ± s.e.m. = 1.69 ± 0.11 ms; for sample traces). This approach allowed us to determine connectivity rates and patterns (unidirectional, bidirectional), and to relate these to cell functionality in the intact brain.

Correlated variability in neuronal firing independent of a sensory stimulus is assumed to reflect neuronal connectivity in the network. Correlated fluctuations in neuronal firing may either be driven by common input or by recurrent synaptic connections, or both. For a subset of visually responsive neuronal pairs (12/56) that were imaged simultaneously in vivo (that is, on the same optical planes), we computed noise correlations, which provide an indication of correlated response variability. Noise correlations were low (mean ± s.d. = 0.02 ± 0.04). Despite the small sample size, connection probability was found to increase significantly with increase in noise correlation (P = 0.011, Cochran–Armitage test), indicating that recurrent connectivity may contribute to correlated fluctuations of neuronal firing.

We next compared how visual response similarity relates to connectivity motifs in the local network. Previous work indicates that bidirectional connections are overrepresented in a network of sparsely connected pyramidal neurons. We found that the connectivity bias between neurons responding similarly to drifting gratings or to natural movies was further accentuated when investigating the distribution of unidirectionally or bidirectionally connected pairs.

In this study, we have characterized the functional specificity of local connections in mouse V1. Our results demonstrate that connectivity between neighbouring neurons (<50 µm apart) is not random, but specifically structured; visually driven neurons were more likely to connect to each other, and this probability increased with the degree of their response similarity. This relationship between connectivity and function was stronger when comparing responses to natural sensory input than for relatively artificial grating stimuli.

We have shown in mouse V1 that—although a given neuron receives input from nearby neurons preferring a wide range of stimulus orientations—more than twice as many connections are made between similarly tuned neurons as between disparately tuned cells. In keeping, subthreshold tuning in L2/3 pyramidal neurons in mouse V1 is broad but nonetheless biased towards the preferred orientation. This is similar to the tuning of neurons in pinwheel centres of orientation maps in visual cortex of other species. In carnivores and primates, long-range horizontal projections in L2/3 (>500 µm) are biased towards cortical columns with similar orientation preference. Our results indicate that similar principles of connectivity apply at the level of local neocortical networks in the mouse—a species without columnar architecture—indicating that functionally biased connectivity may be a general feature of organization in the visual cortex. In the visual cortex this selective connection scheme may serve as a mechanism for the amplification of thalamic input and sharpening of tuning or for local contour integration.

Analysis of connectivity rate with respect to similarity of responses to natural movies revealed a marked degree of specificity of local connections. Connection probability increased sharply with increase in both signal and noise correlation to natural movies. Neurons with higher signal correlations to natural movies probably share similar receptive field structures, and may therefore be driven by common feed-forward input. Our results are therefore consistent with the finding that L2/3 pyramidal neurons form highly interconnected subnetworks sharing common input from layer 4 in slices of rat visual cortex.

Developmentally, this organization of lateral connections based on receptive field similarity may arise through activity-dependent synaptic plasticity, whereby neurons driven by common input develop stable bidirectional connections. Indeed, our data show that the majority of bidirectionally connected neurons had stronger signal correlations to natural movies and shared similar orientation preference. As individual neurons show variability in their responses to the same visual stimulus, recurrent excitation between similarly tuned neurons may reduce response variance, while introducing redundancy into the population code for robustness against errors.

Our results do not preclude the possibility that other factors—including inhibitory connections or synaptic strength—also contribute to functional specificity in the circuit. Because inhibition, in particular, may be important in determining the receptive field properties of neurons in V1, it will be important to examine the extent to which inhibitory connections are functionally specific.

Using a novel and relatively straightforward approach for in vitro mapping of synaptic connectivity among neurons that had been identified functionally in vivo, we found that neighbouring neurons with similar feature selectivity preferentially but not exclusively connected to each other in L2/3 of mouse V1. Together with other powerful approaches, our method can be used to uncover functional biases of connectivity between different cell types and cortical layers, and in other brain areas. This information will be critical for understanding the functional wiring of circuits mediating perception and behaviour.

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