First, Chapman et al. (1991) silenced
the cortex so that action potentials from individual thalamic axons could be recorded. They found that in the ferret, LGN axons that projected to a single column had receptive fields that lined up in a row (Chapman et al., 1991; see Jin et al., 2011). Ferster et al. (1996) examined the same question from the standpoint of a single neuron rather than a single column. They found that in the cat, the orientation selectivity of a cortical neuron did not change when the cortex was silenced: thus, the orientation selectivity click here of the thalamic input alone matched that of the neuron in the unperturbed circuit. To examine the functional logic of individual connections between a pair of neurons, however, it was necessary to study their receptive fields and connections a pair at a time, as Hubel and Wiesel suggested. In the 1960s, this was possible within the LGN (Hubel and Wiesel, 1961) but later it became possible for the thalamocortical projection with the technique of cross-correlation (see below; Tanaka, 1983; Reid and Alonso, 1995). The second model (for complex cells, Figure 1D) addressed the much more difficult problem of how intracortical circuitry might transform sensory information, although some progress with this model has been made with conventional electrophysiology (Alonso and Martinez, 1998). In Hubel and Wiesel’s
complex cell model (Figure 1D), a difficult problem, of receiving inputs BAY 73-4506 from simple cells with one preferred orientation, Edoxaban was solved by the orientation column. It was transformed from a
problem that might require fine-scale functional specificity to one that was solved by topography. To quote the key passage again, “At first sight it would seem necessary to imagine a highly intricate tangle of interconnexions in order to link cells with common axis orientations … [but] gathered together in discrete columns are the very cells we require to be interconnected in our scheme” (Hubel and Wiesel, 1962). Without orientation columns, in the mouse, it is necessary to imagine this “highly intricate tangle of interconnexions,” a phrase that can serve as perhaps the best definition of functional specificity (Hubel and Wiesel, 1962). Hubel and Wiesel’s simple-cell model (Figure 1A) relies on functional specificity. To first approximation, in the cat visual cortex, the axons of on-center and off-center LGN cells are intermingled in layer 4 (but see Jin et al., 2011). Therefore, the precise arrangement of receptive fields of on- or off-center LGN inputs to a single simple cell cannot be explained simply by a random sampling of local thalamocortical axons (unless the number of LGN afferents to a simple cell are assumed to be unrealistically low; Ringach, 2004). Hubel and Wiesel’s complex cell model ( Figure 1D), however, relies primarily on topographic specificity.