From functional architecture to functional connectomics

Abstract

"Receptive Fields, Binocular Interaction and Functional Architecture in the Cat's Visual Cortex" by Hubel and Wiesel (1962) reported several important discoveries: orientation columns, the distinct structures of simple and complex receptive fields, and binocular integration. But perhaps the paper's greatest influence came from the concept of functional architecture (the complex relationship between in vivo physiology and the spatial arrangement of neurons) and several models of functionally specific connectivity. They thus identified two distinct concepts, topographic specificity and functional specificity, which together with cell-type specificity constitute the major determinants of nonrandom cortical connectivity. Orientation columns are iconic examples of topographic specificity, whereby axons within a column connect with cells of a single orientation preference. Hubel and Wiesel also saw the need for functional specificity at a finer scale in their model of thalamic inputs to simple cells, verified in the 1990s. The difficult but potentially more important question of functional specificity between cortical neurons is only now becoming tractable with new experimental techniques.

Figure 1. Hubel and Wiesel’s receptive-field models and some strategies for testing them

(A) Hubel and Wiesel‘s simple-cell model. The simple cell receives convergent input from multiple LGN cells (Connectivity) whose receptive fields (Function) are of the same sign (in this example, on-center) and are aligned in visual space. As a result, the simple cell has a receptive field with an elongated on subregion (indicated by the interrupted lines in the receptive-field diagram) flanked by two off subregions. From Hubel and Wiesel (1962). (B,C) Experimental proof for the model from Reid and Alonso (1995). (B) Summary diagram showing the relationship between the receptive fields (Function) of monosynaptically connected pairs of neurons. Receptive field of each simple cell was transformed into a typical receptive field, shown with a central on subregion (red) flanked by two off subregions (blue). The circles indicate the relative size, sign and locations of the receptive fields of monosynaptically connected LGN cells. (C) Example of a ‘monosynaptic” cross-correlation between an LGN cell and a simple cell (Connectivity). Note the sharp peak at +4 msec, indicating in increase in the probability that the cortical cell fired 4 msec after LGN firing. (D) Hubel and Wiesel‘s complex cell model. (E, F) A theoretical example of how the model might be examined. (E) Simple receptive fields can be mapped with two-photon calcium imaging. Receptive field diagrams (red = on subregion, blue = off subregion) corresponding to different cells (gray outlines) in mouse visual cortex (Bonin et al., 2011). (F) Example of functional connectomics, from a different study of excitatory inputs onto inhibitory neurons (Bock et al., 2011). The axons of a group of neurons with different orientation tunings (coded by different colors) were reconstructed. Axons of vertically and horizontally tuned neurons (red and green) descend and make synapses (small yellow balls) onto dendrites of an inhibitory interneuron (cyan). Insets: electron micrographs showing the synapses onto the inhibitory neuron from cell 4 (b) and cell 10 (c) with corresponding colors overlaid.

Figure 2. Models of function and connectivity in rodent visual cortex

(A) Map of orientation selectivity from mouse visual cortex, with examples of spatial receptive fields from another experiment. Note that vertically oriented cells are interspersed with horizontally oriented cells. (B) Model of like-to-like recurrent connectivity within layer 2/3, as was found with calcium imaging and correlated slice physiology (Ko et al., 2011), but has not been confirmed anatomically. (C) Model of like-to-like feedforward connections from layer 4 to layer 2/3, which has not yet been demonstrated.