Cell Assemblies as Building Blocks of Larger Cognitive Structures J. Eric Ivancich Department of Electrical Engineering and Computer Science, The University of Mic higan, Ann Arbor, MI 48109, ivancich@eecs.umich.edu Christian R. Huyck The University of Sheffield and Department of Computing Sciences, Middlesex Univ ersity, London, N11 2NQ, chris@umich.edu Stephen Kaplan Departments of Psychology and of Electrical Engineering and Computer Science, Th e University of Michigan, Ann Arbor, MI 48109-1109, skap@umich.edu Abstract Pulvermüller's work in pushing Hebb's theory into the realm of language is excit ing. However, we feel that what he characterizes as a single cell assembly is ac tually a set of cooperating cell assemblies that form parts of larger cognitive structures. The se larger structures more easily account for a variety of phenomena, including t he psycholinguistic. Commentary Pulvermüller is to be congratulated for his accomplishment in pushing Hebb's cel l assembly theory into the realm of language and for showing that meaningful and provable predictions can be made with respect to measurable neural activity. Wi thout undermini ng his accomplishments, however, we do feel that adjustments in both the termino logy and the conceptualization of his work reveals a more powerful and flexible cognitive system. In 1949, Hebb, in his landmark book The Organization of Behavior, develo ped the concept of the cell assembly. In his original conception, a cell assembly consisted of a number of neurons that responded to a set of similar sti muli and that c ould sustain activity for about 500 milliseconds (Hebb 1949). Cell assemblies, while powerful themselves, are also ideal building blocks for larger cognitive structures (Kaplan et al. 1990; Holland 1998). The recombinatio n of subsets of building blocks into larger structures yields a vast number of p otential combin ations. Just as a modified Hebbian synaptic learning rule can be used to form cell asse mblies, the very same learning rule can be used to create an associative link be tween two assemblies through a set of mediating connections. Thus, when one asse mbly becomes ac tive, another will likely become active due to this link. When a number of cell assemblies become linked in this way, longer sequences ar e encoded. When many distinct sequences pass through a given set of assemblies i n such a way that each assembly can be re-used in multiple sequences, a more com plex structure evolves. This structure is similar to the cognitive map that Tolman propo sed (Tolman 1948). This cell assembly interpretation of Tolman's cognitive map c oncept has been proposed as a general purpose knowledge structure, useful not on ly for storing information used in navigating an environment (Kaplan and Kaplan 1982; Levenick 1991; Chown et al. 1995) but also for encoding algorithmic and story structures of many kinds. It appears to be equally suitable for the generation and parsing of language. Hebb focused on cognitive structures with direct sensory and motor content. Sin ce a neuron is more likely to be connected to those nearby, a notion of neural d istance exists. Some neurons are close to the sensory and motor apparatuses, whi le others are f urther away. Neurons that are close to the sensory interface are well-placed to become members of cell assemblies with concrete, sensory content. These assembli es then become the inputs for neurons further away from the sensory interface, w here assemblies with diminished sensory content will form. From the simple notion of distance emerges both the concept of depth and a hier archical structure. In such a hierarchy depth equates to abstractness, moving fr om basic-level categories (e.g., tree) (Rosch et al. 1976) to those so ab stract they have little or no sensory content (e.g., justice). Both the cognitive map and the hierarchy are directly applicable to Pulvermülle r's work in language. The pattern of neural activity generated by a noun, a verb , or a grammatical function word that Pulvermüller uses in his argument is not a result of what we view as a single cell assembly. Rather we would characterize the pattern as the result of the activation of a set of strongly associated assemblies. The phonemic representation of a word in perisylvan cortex likely involves a se quence of cell assemblies where each represents a phoneme. The same phonemes in a different order would, after all, generate a different word (e.g., "cat" and " tack"). As the sequence of phonemes is recognized, activity may then collect in another assembl y sitting at the next level of a hierarchy and representing the whole word. Note that this hierarchical relationship is based on the grouping of a sequence. A c ategorical hier archy is also available so that "cat" may be an animate noun, or more traditiona lly, an animal. The phoneme-based word cell assembly has strong associations to potentially man y semantic correlates. By keeping the phonemic and semantic assemblies separate, yet highly associated, the system can readily deal with homonyms by using conte xtual cues to r esolve the competing interpretations. A set of separate cell assemblies can account for a number of other phenomena a s well. Many concepts simply do not have simple verbal correlates. People can le arn and represent nonsense words. Since one can have a word without a concept, o r a concept wit hout a word, the assemblies are separate. If we might be a bit more speculative, we conceptualize a set of world maps< /i> composed of cell assemblies rich in semantic content, and a set of word m aps composed of phoneme-based cell assemblies. These two maps are highly ass ociated and tra versal between them is often easy and consciously seamless. By keeping the maps separate, the system has a more powerful and flexible struc ture. There are links within each map as well as links between the maps. Among o ther things, the word maps encode the likelihood of connections between phonemes . If two phonem es never connect in the language, a word in which they do connect will seem unna tural (which can explain the "phonological rules of the language" that Pulvermül ler [section 4.2, 7th paragraph] mentions). In word maps, words can be combined to form multi-w ord units whose semantic content is unrelated to the base words, as in "The Big Apple", "kick the bucket", and other idiomatic expressions. It is difficult to e xplain how this could be the case if the maps were not separate. Finally, hierarchical and map structures go a long way towards explaining how a system as complex as language can be learned in the first place. Preverbal chil dren obviously have sophisticated representations of the world around them, and children underg o an explosive growth in vocabulary. A high school graduate knows 60,000 words ( Pinker 1994) and likely knows most of them by age five. It is difficult to accou nt for this unless children are, at least in part, building larger structures fr om already-lear ned building blocks, both semantic and phonemic. Pulvermüller's findings are indeed encouraging. We believe it would be worthwhi le to explore the application of his methods towards these more complex cognitiv e structures, opening up fascinating possibilities for the explanation of many c omplex psycholo gical and psycholinguistic phenomena. 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(1948) Cognitive maps in rats and men. Psychological Review, 55:1 89-203. 6 BBS Comment Ivancich, Huyck, Kaplan