1. EE141 1 Language Janusz A. Starzyk http://grey.colorado.edu/CompCogNeuro/index.php/CECN_CU_Boulder_OReilly http://grey.colorado.edu/CompCogNeuro/index.php/Main_Page Based on book Cognition, Brain and Consciousness ed. Bernard J. Baars courses taught by Prof. Randall O'Reilly, University of Colorado, and http://wikipedia.org/ Cognitive Architectures

2. EE141 2 Modeling speech Models account for: distributed lexicon, orthography, phonology, semantics. The same learning mechanisms in the brain, but different inputs/outputs. Levels of processing: phonemes/syllables, letters, words, ideas, phrases, sentences, situations, stories. Distributed representations, great possibilities of combining many representations Semantic representations of word co-occurrence. Semantic representations on the level of sentence shapes. Phonological neighborhood density of words = the number of words that sound similar to a given word, so creating similar activations in the brain. Semantic neighborhood density of words = the number of words with a similar meaning (widened activation subnetwork).

3. EE141 3  Learning based on processing temporal sequences  Word sequences must produce meaning representations  Language is the result of unpacking distributed meaning representations in the brain and communicating them to other people through communication channels, with the expectation that their corresponding representations will be created in the brain of the receiver Learning to read dyslexia Sign recognition, mapping orthography onto phonology (not trivial for English) and intonations (important in Chinese) Regularities and exceptions creating too-regular past tenses. Modeling speech

4. EE141 4 Biological foundations Controlling the vocal apparatus is responsible for the correct pronunciation of syllables. Mainly responsible for this control is Broca's area in the frontal cortex; for speech analysis, Wernicke's area in the superior temporal lobe. Broca's: surface representation, Wernicke's: deep representation.

5. EE141 5 Questions We will try, with the help of computer simulations, to find and verify with the help of models, the answers to several questions:  What processes are involved in the reading process and why do they sometimes let us down (dyslexia)?  How do we read known words: cat, yacht, and how do we read invented words, eg. nust, deciding on some pronunciation?  Why do children say "I goed” instead of "I went”?  Where does the meaning of words come from?  How to go from words to sentences?

6. EE141 6 Distributed lexicon and dyslexia Phonological level of dyslexia: nonexistent words don't activate deeper areas (Wernicke's). Deep level: phonological and semantic errors (cat – cot, cat - dog), mistakes in sign recognition. Surface dyslexia: new words don't create a problem, but there is a lack of access to the semantic level + difficulties in reading exception words + mistakes in recognition. A model of reading and dyslexia has two paths from orthography to phonology: direct (by mapping) and indirect, via semantics. Uncommon and difficult words are pronounced through the indirect pathway.

7. EE141 7 Reading Reading models: mapping orthography onto phonology. Two issues:  can one system learn to pronounce regular words and simultaneously deal with exception words?  simulating pronunciation of nonexistent words requires the discovery of subtle regularities of pronuncation. Mint, hint, flint => "i" is the same, but in pint it's different... Regularities are often modified, depending on the context, they have groupings (neighborhoods), and exceptions are on the extremes of these modifications. Regularities and exceptions form a continuum.

8. EE141 8 Reading: distributed lexical model Representations are not localized in one region. Interactions lead to an interesting division of labor.

9. EE141 9 Word meaning Idea semantics is the result of activations distributed across many areas. Simplest model: Strong Hebbian correlations between words, like correlations between elements of images or phonemes creating syllables. LSA- Latent Semantic Analysis, type of PCA, which can be realized by Hebbian learning.

10. EE141 10 Words in the brain Psycholinguistic experiments about speech show that in the brain we have discrete phonological representations, and not acoustic ones. Acoustic signal => phonemes => words => semantic concepts. Semantic activations follow 90 ms after phonological activations (N200 ERPs). F. Pulvermuller (2003) The Neuroscience of Language. On Brain Circuits of Words and Serial Order. Cambridge University Press. Action networks – observations, findings of ERP and fMRI tests.

11. EE141 11 Words: simple model Goals:  making the simplest model of creative thinking;  creating interesting new names, conveying product features;  understanding new words, which aren't in the dictionary. A model inspired by overlapping brain processes which happen during invention of new words. Given is a set of key words, which activate the auditory cortex. Phonemes are resonances, orderly activation of phonemes activates known words and new combinations equally; context + inhibition in the winner- takes-all process leaves one word.  Creativity = imagination (fluctuations) + filtering (competition)  Imagination: many temporary resonances arise in parallel, activating representations of words and non-words, depending on the connection strength of oscillators.  Filtering: associations, emotions, phonological/semantic density.

12. EE141 12 Associations - revision Why does priming neutral for simple associations and nonsensical words worsen results for creative people? Weak creativity = weak associations (connections) between oscillators; adding noise (nonsensical words) strengthens already overlapping oscillations, enabling mutual activations; for a strongly connected neural network and simple associations, it leads to confusion, when it activates many states. For difficult associations, adding noise in weakly creative people won't help because of a lack of connections, priming words cause only chaos. For orthographically similar priming words with close associations, this activates the representation of the second word, always increasing the chance of resonance and shortening latency.

13. EE141 13 Quiz Project sem.proj.gz, description 10.6.2 An already trained network responds to questions...

14. EE141 14 Questions/answers concerning language  What processes are involved in the reading process and why do they sometimes betray us (dyslexia)? Distributed lexical representations, interactions between sign recognition, level of spelling (orthography), phonology and semantics.  How do we read known words: cat, yacht, and how do we read invented words, eg. nust? Thanks to contextually activated representations, giving a continuum between regular forms and exceptions.  Why do children say "I goed” instead of "I went”? Because of the dynamic equilibrium between mapping regular forms and exceptions.  Where does the meaning of words come from? Statistics of co- occurrence, interactions with representations of sensory data.  How to go from words to sentences? This is enabled by the "Sentence Gestalt" (a theory in psychology).