Julian M. L. Budd

Model-based analysis of excitatory lateral connections in the visual cortex

Excitatory lateral connections within the primary visual cortex are thought to link neurons with similar receptive field properties. Here we studied whether this rule can predict the distribution of excitatory connections in relation to cortical location and orientation preference in the cat visual cortex. To this end, we obtained orientation maps of areas 17 or 18 using optical imaging and injected anatomical tracers into these regions. The distribution of labeled axonal boutons originating from large populations of excitatory neurons was then analyzed and compared with that of individual pyramidal or spiny stellate cells. We demonstrate that the connection patterns of populations of nearby neurons can be reasonably predicted by Gaussian and von Mises distributions as a function of cortical location and orientation, respectively. The connections were best described by superposition of two components: a spatially extended, orientation‐specific and a local, orientation‐invariant component. We then fitted the same model to the connections of single cells. The composite pattern of nine excitatory neurons (obtained from seven different animals) was consistent with the assumptions of the model. However, model fits to single cell axonal connections were often poorer and their estimated spatial and orientation tuning functions were highly variable. We conclude that the intrinsic excitatory network is biased to similar cortical locations and orientations but it is composed of neurons showing significant deviations from the population connectivity rule. J. Comp. Neurol. 499:861–881, 2006.

One axon-multiple functions: Specificity of lateral inhibitory connections by large basket cells

The functional specificity of the projections of single large basket cells of the cat primary visual cortex was studied using novel analytical approaches. The distribution of the labelled axons and that of the target cells were three-dimensionally reconstructed and compared quantitatively to orientation, direction and ocular dominance maps obtained with the intrinsic signal optical imaging technique. Quantitative analysis was carried out (i) for the entire basket cell, (ii) separately, for local and distal projections of the axon and (iii) by dissecting the same axon into two projection fields at the first bifurcation. It was found that although the functional distributions (orientation, direction and ocular dominance) for the entire cell were multi-modal and broadly tuned, individual main branches of the same cell displayed highly specific topography. In the further analysis, 2-dimensional probability density estimates of the target cell distributions revealed clear clustering which may be important for local subfield antagonism. These findings provide support to the idea that the same basket cell mediates several specific receptive field operations depending on the location of the target somata in the functional maps.

Communication and wiring in the cortical connectome

In cerebral cortex, the huge mass of axonal wiring that carries information between near and distant neurons is thought to provide the neural substrate for cognitive and perceptual function. The goal of mapping the connectivity of cortical axons at different spatial scales, the cortical connectome, is to trace the paths of information flow in cerebral cortex. To appreciate the relationship between the connectome and cortical function, we need to discover the nature and purpose of the wiring principles underlying cortical connectivity. A popular explanation has been that axonal length is strictly minimized both within and between cortical regions. In contrast, we have hypothesized the existence of a multi-scale principle of cortical wiring where to optimize communication there is a trade-off between spatial (construction) and temporal (routing) costs. Here, using recent evidence concerning cortical spatial networks we critically evaluate this hypothesis at neuron, local circuit, and pathway scales. We report three main conclusions. First, the axonal and dendritic arbor morphology of single neocortical neurons may be governed by a similar wiring principle, one that balances the conservation of cellular material and conduction delay. Second, the same principle may be observed for fiber tracts connecting cortical regions. Third, the absence of sufficient local circuit data currently prohibits any meaningful assessment of the hypothesis at this scale of cortical organization. To avoid neglecting neuron and microcircuit levels of cortical organization, the connectome framework should incorporate more morphological description. In addition, structural analyses of temporal cost for cortical circuits should take account of both axonal conduction and neuronal integration delays, which appear mostly of the same order of magnitude. We conclude the hypothesized trade-off between spatial and temporal costs may potentially offer a powerful explanation for cortical wiring patterns.

Neocortical Axon Arbors Trade-off Material and Conduction Delay Conservation

The brain contains a complex network of axons rapidly communicating information between billions of synaptically connected neurons. The morphology of individual axons, therefore, defines the course of information flow within the brain. More than a century ago, Ramón y Cajal proposed that conservation laws to save material (wire) length and limit conduction delay regulate the design of individual axon arbors in cerebral cortex. Yet the spatial and temporal communication costs of single neocortical axons remain undefined. Here, using reconstructions of in vivo labelled excitatory spiny cell and inhibitory basket cell intracortical axons combined with a variety of graph optimization algorithms, we empirically investigated Cajals conservation laws in cerebral cortex for whole three-dimensional (3D) axon arbors, to our knowledge the first study of its kind. We found intracortical axons were significantly longer than optimal. The temporal cost of cortical axons was also suboptimal though far superior to wire-minimized arbors. We discovered that cortical axon branching appears to promote a low temporal dispersion of axonal latencies and a tight relationship between cortical distance and axonal latency. In addition, inhibitory basket cell axonal latencies may occur within a much narrower temporal window than excitatory spiny cell axons, which may help boost signal detection. Thus, to optimize neuronal network communication we find that a modest excess of axonal wire is traded-off to enhance arbor temporal economy and precision. Our results offer insight into the principles of brain organization and communication in and development of grey matter, where temporal precision is a crucial prerequisite for coincidence detection, synchronization and rapid network oscillations.

A self-organizing model of “color blob” formation

This paper explores the possibility that the formation of color blobs in primate striate cortex can be partly explained through the process of activity-based self-organization. We present a simulation of a highly simplified model of visual processing along the parvocellular pathway, that combines precortical color processing, excitatory and inhibitory cortical interactions, and Hebbian learning. The model self-organizes in response to natural color images and develops islands of unoriented, color-selective cells within a sea of contrast-sensitive, orientation-selective cells. By way of understanding this topography, a principal component analysis of the color inputs presented to the network reveals that the optimal linear coding of these inputs keeps color information and contrast information separate.

Inhibitory basket cell synaptic input to layer IV simple cells in cat striate visual cortex (area 17): A quantitative analysis of connectivity

In the absence of a direct and specific marker for basket cells, the aim of this paper was to use available data to estimate the density of basket cell synaptic input to smooth and spiny neurons within layer IV of cat striate visual cortex (area 17). A linear quantitative analysis of layer IV basket cell connectivity data suggests that on average basket cells (1) comprise 25-35% of all GABAergic neurons in layer IV (3552-4736 cells mm(-3)), (2) account for 30-41% of all putative inhibitory dendritic synapses of layer IV spiny stellate cells (145-195 synapses cell(-1)) and a similar proportion of layer IV basket cells (25-37%, 71-107 synapses cell(-1)), and (3) provide each layer IV spiny cell with 13-45 axons and each layer IV basket cell with 6-29 axons. These estimates suggest that basket cells may be less common and provide a smaller proportion of the dendritic synaptic input to layer IV spiny and smooth neurons than previously thought. In addition, the analysis indicates that a layer IV spiny stellate cell may receive on average as many synapses and axons from layer IV basket cells as from lateral geniculate relay cells. Based on this potential numerical similarity, a geniculate-basket synaptic pairing in a spine-shaft microcircuit is hypothesized. This microcircuit could implement a type of local (dendritic) push-pull interaction underlying subfield antagonism.

How much feedback from visual cortex to lateral geniculate nucleus in cat: A perspective

Corticothalamic feedback is believed to play an important role in selectively regulating the flow of sensory information from thalamus to cortex. But despite its importance, the size and nature of corticothalamic pathway connectivity is not fully understood. In light of recent empirical data, the aim of this paper was to quantify the contribution of area 17 axon connectivity to the synaptic organization of A-laminae in dorsal lateral geniculate nucleus (dLGN) in cat, the best studied corticothalamic pathway. Numerical constraints indicate that most corticogeniculate synapses are not formed with inhibitory interneurons. However, the main finding is that there was an order of magnitude difference between estimates of the mean number of cortical synapses per A-laminae neuron based on individual corticogeniculate axon data (12,000-16,000 cortical synapses per cell) than that previously derived from partial reconstructions of the synaptic input to two physiologically identified relay cells (1200-1500 cortical synapses per cell). In an attempt to reconcile these different estimates, parameter variation and comparative analyses suggest that previous work may have overestimated the density of corticogeniculate efferent neurons and underestimated the total number of synapses per geniculate neuron. But as this analysis did not include area 18 corticogeniculate axons innervating A-laminae, the discrepancy between different estimates may be greater and require further explanation. Thus, the analysis presented here suggests geniculate neurons receive on average a greater number of cortical synapses per cell but from far fewer corticogeniculate axons than previously thought.

Theta oscillations by synaptic excitation in a neocortical circuit model

Neocortical theta-band oscillatory activity is associated with cognitive tasks involving learning and memory. This oscillatory activity is proposed to originate from the synchronization of interconnected layer V intrinsic bursting (IB) neurons by recurrent excitation. To test this hypothesis, a sparsely connected spiking circuit model based on empirical data was simulated using Hodgkin-Huxley-type bursting neurons and use-dependent depressing synaptic connections. In response to a heterogeneous tonic current stimulus, the model generated coherent and robust oscillatory activity throughout the theta-band (4-12 Hz). These oscillations were not, however, self-sustaining without a driving current, and not dependent on N-methyl-D-aspartate receptor synaptic currents. At realistic connection strengths, synaptic depression was necessary to avoid instability and expanded the basin of attraction for theta oscillations by controlling the gain of recurrent excitation. These results support the hypothesis that IB neuron networks can generate robust and coherent theta-band oscillations in neocortex.

How do you wire a brain

Cerebral cortex is generally thought to provide the neural basis for higher cognitive and perceptual functions (see Gazzaniga et al., 2008). In cerebral cortex, billions of individual neurons, the functional units of cortex, are interconnected via a massive yet highly organized network of axonal and dendritic wiring. This wiring enables both near and distant neurons to coordinate their responses to external stimulation. Specific patterns of cortical activity generated within this network have been found to correlate with cognitive and perceptual functions (see Wang, 2010). If cortical wiring is damaged, through disease or trauma, characteristic behavioral disorders result (e.g., Seeley et al., 2009). Understanding the organizing principles of cortical wiring, therefore, represents a central goal toward explaining human cognition and perception in health and disease. Despite more than a century of endeavor, however, the organizing principles and function of cortical connectivity are not well understood. This Research Topic presents recent progress and challenges to existing ideas about the principles concerning how cerebral cortex is wired. The publication of this collection of articles comes at a time of great excitement in the field of cortical neuroscience resulting from recent technical advances such as the more rapid tracing of cortical wiring and the ability to more precisely manipulate cortical activity experimentally. The large amount of data these new methods will yield must be tempered by the knowledge that mapping all synaptic connections or connectome of an individual brain represents a distant goal (see DeFelipe, 2010). In any case, the main aim of obtaining any map of cortical connectivity is to extract its underlying principles of organization—the subject of this Research Topic. Although there are many interwoven themes in this collection of articles, we draw attention to five questions which we think will have a major bearing on the direction of future research and discuss how articles here bear on these questions.

Editorial: Quantitative Analysis of Neuroanatomy.

The true revolution in the age of digital neuroanatomy is the ability to extensively quantify anatomical structures and thus investigate structure-function relationships in great detail. Large-scale projects were recently launched with the aim of providing infrastructure for brain simulations. These projects will increase the need for a precise understanding of brain structure, e.g., through statistical analysis and models. From articles in this Research Topic, we identify three main themes that clearly illustrate how new quantitative approaches are helping advance our understanding of neural structure and function. First, new approaches to reconstruct neurons and circuits from empirical data are aiding neuroanatomical mapping. Second, methods are introduced to improve understanding of the underlying principles of organization. Third, by combining existing knowledge from lower levels of organization, models can be used to make testable predictions about a higher-level organization where knowledge is absent or poor. This latter approach is useful for examining statistical properties of specific network connectivity when current experimental methods have not yet been able to fully reconstruct whole circuits of more than a few hundred neurons.