Chapter 1 describes how specifically organized, hierarchical structures of a neural network can create neural representations of perceived reality. The authors describe how, as a result of categorization and generalization, memory traces created in subsequent layers can represent the perceived world in all its complexity. Starting from the representation of direct sensual impressions in the lowest layers, closely connected to the sensors of individual senses, to the representation of increasingly complex objects, the feelings and knowledge about the observed world are built. They postulate that to achieve this goal imaginary natural and artificial brains must contain such semihierarchical structures capable of creating new connections and information transmission paths. By associating large areas of brain fields in multiple layers, it is possible to create representations of complex reality. The dominant mechanism of self-learning is correlation learning, during which simultaneous, synchronous arousal of different senses creates mutually correlated features of the observed object. Perceived objects excite neuronal stimulation patterns that allow the system to identify the object in the future. The re-stimulation of the memory structures from the top layers to the sensory fields, causes the recall and creation of sensations similar to those felt during the original experiences. By comparing new sensual impressions with those stored in memory, the perceived objects are recognized. Frequent, simultaneous co-occurrence of stimulations of mental representations results in associations of memory cells and synapses, and thus associations of mental facts. Order and sequences of their occurrence is the basis of episodic memory. Imagined neural network memory cells, like natural brain neurons, do not limit their role to just remembering the information that they receive. They actively process this information and change the structure of their connections. We put forward the thesis that the described memory cells, artificial neurons, can create brains with features such as natural brains. It is this semihierarchical structure of neurons, which arise from categorization, generalization and association processes that can create neural representations of perceived reality. Learning through life experiences allows us to give them the characteristics of psychological sensations and thus they also become mental correlates of perceptions. The knowledge that these structures represent is as hierarchical they are. This hierarchy starts from the representation of the simplest direct sensual features, to complex models of the environment and abstract concepts that can be defined by symbolic language. The presented model describes the creation of knowledge in the mind, pattern recognition, remembering and imagining objects and events, planning, and making decisions. The systems thus created yield minds with cognitive, intentional, and propositional awareness. Unfortunately, they are devoid of phenomenal awareness, which we write about in the following chapters.
When complex is easy on the mind: Internal repetition of visual information in complex objects is a source of perceptual fluency.
