8.1 Reading Models
The Logogen Model
Proposed by Morton (1969, 1970), the Logogen model assumes units called logogens which are used to understand words that are heard and read. Logogens are specialized recognition units that are used for word recognition. Logogen is from the Greek λόγος (logos, word) and γένος (genos, origin). So, every word we know has its own logogen which contains phonemic and graphemic information about that word. As we encounter a word, the logogen for that word accumulates activation until a given threshold is reached upon which the word is recognized. An important issue to remember is that the logogen itself doesn’t contain the word. Rather, it contains information that can be used to retrieve the word. Accessing words is direct and parallel for all words.
Each logogen has a resting activation level. As it receives more evidence that corresponds to its word, this activation level increases up to a threshold. For example, if the input contains the grapheme <p>, then all logogens containing that visual input get an increase in activation. Once enough graphemes are there to fully activate the logogen it fires and word recognition occurs. The model is particularly good as including contextual information in recognizing words. One of the problems with this model was that it equated visual and auditory input for a word as using the same logogen process. A prediction of this model would be that a spoken prime should facilitate a written word just as much as a visual prime. However, experimental evidence contradicted this prediction (Winnick & Daniel, 1970). Following his own observation that confirms these findings, Morton divided the model into different sets of logogens (see Figure 8.1).
While the logogen model is quite successful in explaining word recognition in terms of semantics, there are some limitations to this model. There have been challenges to the existence of the logogen as a unit of recognition. Given that different pathways process information on the way to word recognition, is it really necessary to have such centralized units? The model’s limited scope for word recognition that ignores innate syntactic rules and grammatical construction is also a limitation.
Interactive Activation Model
McClelland and Rumelhart (1981) and Rumelhart and McClelland (1982) developed the Interactive activation and competition (IAC) model. The model accounted for word context effects. This means that letters are easier to recognize if they are in words rather than as isolated letters (also known as the word superiority effect). As seen in Figure 8.3, the model consists of three levels: visual feature units, indivudla letter units, and word units. Each unit is connected to units in the level immediately before and after it with connections that are excitatory (if appropriate) or inhibitory (if inappropriate).
Let’s look at the example in Figure 8.3 for the word leap. First, the individual features are recognized. For example, the ver