In the primary visual cortex (V1), “simple” and “complex” cells are arranged to function as filters that detect line orientation and position. Using micro-electrode recordings, Hubel and Wiesel characterized these receptive-field properties and proposed that visual information is processed hierarchically and in parallel. When they covered one eye of young kittens for several weeks, input from that eye was eliminated from V1, defining a critical period of development. Their findings influenced therapies for developmental disorders such as amblyopia and inspired the design of artificial vision systems.

Using glass micropipettes, Hubel and Wiesel recorded single-neuron activity in feline and primate V1, combining receptive-field mapping with a scanning light-spot stimulator. Spike histograms revealed that simple cells possess spatially separated ON/OFF subfields, whereas complex cells lack spatial segregation yet exhibit robust direction selectivity. They proposed the orthogonally arranged ocular-dominance and orientation columns (“ice-cube model”), forming the basis for hierarchical computational models (Hubel-Wiesel model) and ultimately inspiring convolutional neural networks.

Employing vertical penetrations based on a striopengular action approach, the duo electrophysiologically identified columnar organization. Spike-triggered averaging and drifting sinusoidal dot analysis quantified frequency tuning, leading to a linear/non-linear modular processing hypothesis. In monocular deprivation models they observed BDNF fluctuations and NMDA-dependent LTD, revealing synaptic competition mechanisms. These insights defined clinical intervention windows for visual developmental disorders and provided receptive-field design principles for artificial neural networks.