During the period from 1960 to 1986 research emphasized cortical architecture and topographic maps as the computational substrate for vision, with orderly receptive fields, orientation maps, and retinotopic organization guiding processing across cat and primate cortex. Population-level dynamics stressed excitation–inhibition balance and rhythmic activity, linking cellular interactions to macroscopic cortical patterns through dynamical theories and neural-field intuitions. Quantitative approaches and signal-processing methods underpinned brain research, spanning spontaneous single-neuron activity, EEG spectral analysis, and studies of brain-state relations, while emergent computation and cross-regional connectivity highlighted scalable architecture and distributed networks. Attentional modulation and state-dependent processing demonstrated how behavioral context alters neural excitability and perceptual readiness, exemplified by fixation-related modulation and context-sensitive responses. Historical Significance: The era produced formal neural-field and population-dynamics frameworks for cortex–thalamus interactions and large-scale brain dynamics, enabling integrated models of cortical activity and perception. It also established energy-minimizing, distributed computation schemes that realized associative memory and optimization in networks of simple units. Collectively, these breakthroughs formed foundational paradigms in computational neuroscience, bridging micro-level neural mechanisms with macro-level brain function and guiding the development of later large-scale simulations and theory.