Microcircuits in visual cortex

Abstract

The microcircuity of the neocortex is bewildering in its anatomical detail, but seen through the filters of physiology, some simple circuits have been suggested. Intensive investigations of the cortical representation of orientation, however, show how difficult it is to achieve any consensus on what the circuits are, how they develop, and how they work. New developments in modeling allied with powerful experimental tools are changing this. Experimental work combining optical imaging with anatomy and physiology has revealed a rich local cortical circuitry. Whereas older models of cortical circuits have concentrated on simple ‘feedforward’ circuits, newer theoretical work has explored more the role of the recurrent cortical circuits, which are more realistic representations of the actual circuits and are computationally richer.

Introduction

Francis Crick once advised: ‘if you do not make headway studying a complex system, study its structure and knowledge of its function will follow automatically’ (cited in [1]). Explorers of neocortical microcircuits have traditionally chosen the reverse strategy: they study function and use it to infer structure. How successful have they been? Very — if textbooks and computational models of cortical microcircuits are any indication. Despite the recent flowering of anatomical studies associated with physiological recordings in slices of cortex maintained in vitro, these new studies have had remarkably little influence on modern ideas of microcircuits in visual cortex. This is quite unlike the central significance that anatomy has had for concepts of hierarchical processing and for notions of feedforward and feedback processing between cortical areas.

It could be argued that the relative lack of impact of anatomical discoveries in cortical slices is because the work in slices has been directed to questions of neuronal biophysics and synaptic physiology and not to the structural basis of the functional microcircuits. Also, most cortical slice studies use rodent somatomotor cortex and not the visual cortex of the cat or monkey, which have been the major models for investigations of cortical circuits. A more fundamental reason may be that most of the progress in our understanding of cortical microcircuits has come about through the approach deployed with effortless brilliance by Hubel and Wiesel [2]. They first constructed a hierarchical model (Fig. 1a) of the microcircuit in visual cortex on the basis of the receptive fields and of the lamina in which neurons were recorded [2]. The power of their approach was that it mattered not whether one or one hundred cell types were involved, whether the synapses depressed or potentiated, or what glutamate receptor subtypes and ion channels were present: the baffling complexity of microanatomy and microphysiology was simply irrelevant. Thus, despite its ripe age, their model continues to be remarkably agile and it remains the textbooks’ favorite. It has had the good fortune to be insoluble by past and current techniques and thus it continues to tantalize successive generations of experimentalists. Most modelers of cortical microcircuits have followed suit and taken the first stage of the hierarchy — the generation of orientation-selective ‘simple cells’ from a row of relay cells in the lateral geniculate nucleus (LGN) of the thalamus — as their test case.

With this history as ambience, it is no surprise to discover that recent publications on cortical microcircuits maintain this bias of approach and interest. According to the dictum, ‘anatomy tells you what could be, physiology tells you what is’ (JA Movshon, personal communication), in vivo physiology and modeling continue to be the main tools used to solve the structure of cortical microcircuits. Where real structural studies are made in vivo, it is usually at the level of populations of labeled neurons observed through the light microscope. Thus, although the anatomical basis of the visual field map (retinotopy) and the segregated inputs of left and right eyes (ocular dominance) appear to be fully explained by the distribution of the eye-specific thalamic inputs to layer 4 [3], to date, no anatomical circuits have been demonstrated for the cortical properties of orientation tuning, binocular disparity, direction selectivity and contrast adaptation, amongst others. Yet, this apparent lack of progress is deceptive, for many of the elements required for a new synthesis are already here. The new experimental and theoretical evidence reviewed here indicates that feedforward inputs to cortical layers from the thalamus are not the sole determinant of the specificity of neurons, even in the orientation domain. Rather, local recurrent cortical circuits (Fig. 1b) play an important role in the organization of such specificity at the level of single neurons and at the level of cortical maps (Fig. 2).