INSTRUCTOR NOTE: Before beginning the PPT itself, here are points you (the student) should consider - Thanks, WK What type of research is it? (descriptive, comparative, analytical) What questions does the paper address? Who are Thompson and Shapiro? What are the main conclusions of the paper? What evidence supports those conclusions? (logical connection between data and interpretation is sound/not sound) What is the quality of the evidence? (validity, qualitative vs. quantitative data) Methods, limitations, data shown vs. what authors claim, use of proper controls in the experiment Why are the conclusions important? Significant advance in knowledge? Lead to new insights/research directions?

Complexity of Treatment of Syntactic deficits C. Thompson L Complexity of Treatment of Syntactic deficits C. Thompson L. Shapiro American Journal of Speech-Language Pathology 13, 236-249 (2007) “Tricia O.” 2009

PURPOSE/ QUESTION For pts with agrammatic aphasia…. ..and treatments addressing sentence structural impairments using complex sentences…. Q: Is training simple structures first and then building to more complex, the best method? Outcome: Training complex sentences improves simpler structures ONLY WHEN underlying linguistic properties are shared by both Training simple structures first and building to more complex, does provide full benefit of treatment (little or no generalization occurs)

BACKGROUND: AGRAMMATIC APHASIA Broca’s aphasia Deficits in grammatical structure: Short, simple sentences Structurally impoverished word strings Noun phrase, verb phrase misordered Grammatical morphemes substituted/ omitted Difficulty with complex sentences: passives and object relative clause constructions (comprehension and production)

BACKGROUND - CONT’D: TREATMENT FOR AGRAMMATISM Mapping Therapy Treatment of Underlying Forms (TUF) Verbs: thematic roles Syntactic properties of sentences Primary focus: syntactically simple sentences - comprehension only Primary focus: syntactically complex features (passive sentences) - comprehension + production Claim: Training complex linguistic materials Improved production and comprehension of structures greater generalization to untrained sentences

AUTHORS’ CLAIM Generalization occurs when untrained and trained structures are LINGUISTICALLY RELATED COMPLEXITY ACCOUNT OF TREATMENT EFFICACY (“CATE”): “Training complex structures results in generalization to less complex structures when untreated structures encompass processes relevant to treated ones”

BACKGROUND: SYNTACTIC COMPLEXITY - THEORETICAL CONSIDERATIONS Structural complexity influenced by: # of propositions (aligned with number of verbs in a sentence) # of embedding in a sentence Order in which elements appear in a sentence (canonical vs. noncanonical: Types of syntactic dependencies within a sentence) Argument structure Distance between crucial elements in a sentence

BACKGROUND: SYNTAX All sentences are similarly formed through Phrase structure building operations Argument structure of selected verbs Number of selected verbs influence selected building complexity Merge and Move are operations in sentence formation NOTE: Complexity variables affect human sentence processing

“MERGE” – AN ILLUSTRATION -2 categories merge to yield a higher order category –a series of merge operations builds the syntactic structure MERGE V + N = VP ARGUMENT STRUCTURE -role of verbs in merge participants that “go with” verb + verb (to be grammatical) - ARGUMENT STRUCTURE - THEMATIC ROLE – assigned each verb argument (agent, theme, goal) i.e., thief chased artist (2 argument verb: thief- agent; artist – theme / the direct object argument) “The artist (agent) chased the thief (theme)” assigned to each verb Argument (agent, theme/ direct object argument, goal) THEMATIC ROLE

“MOVE” – AN ILLUSTRATION NP Movement (argument position) Passive Sentences (“the artist was chased by the thief”) Sentence Raising Structures (“The thief seems to have chased the artist”) Wh- Movement (nonargument position) Object-extracted Wh- question (“who did the thief chase?”) Object cleft (“It was the artist who the thief chased”) Object relative (“The man saw the artist who the thief chased”) NO MOVEMENT (“The thief MOVE Noncanonical – order of the words in the sentences have been moved from their basic (underlying) position to other sentence positions Sentences with movement (more complex) > sentences without movement wh- movement – moved material lands in the Specifier position of the complementizer phrase (Spec CP – a nonargument position) – involve displacement of the direct object argument from its underlying position to a different position (I.e., it was the artist who chased the thief) a.1. Object-extracted wh- question: who did the chief chase? a.2. Object cleft: it was the artist who the thief chased a.3 Object relative: The man saw the artist who the thief chased b) NP movement - - land in the specifier position of the tense phrase (spec, TP – argument position) (I.e., The artist was chased by the thief) occurs because , in underlying form, both sentences have an empty subject position B1. Passive – the artist was chased by the thief – the object (NP) is moved to the subject position of same clause B2. Subject raising – the thief seems to have chased the artist – subject NP is raised from a lower clause to a higher clause (resulting in an embedded sentence NOTE: both take only the internal argument and do not assign an external thematic role to the subject position Movement crosses clausal boundaries (lower to higher clause) creating greater distance between moved element and its original site Clausal embedding which further influences sentence complexity

(nonargument position) MOVEMENT HIERARCHY No movement NP Movement (argument position) Passive Sentences Sentence Raising Structures Wh- Movement (nonargument position) Object-extracted Wh- question Object cleft Object relative

RELEVANCE OF MERGE AND MOVE IN SENTENCE PROCESSING SEMANTIC PRIMING EFFECT Faster reaction times if: semantically related Auditory: “Which doctor did the supervisor call to help with emergency?” Visual: Strings of letters (+/- semantically related to moved sentence constituent) If visual string is a word/nonword RESULTS RESPONSE STIMULI SENSITIVITY TO ORIGIN OF MOVED SENTENCE CONSTITUENT Faster reaction times after the verb (vs. before the verb) Results: CROSS MODAL LEXICAL PRIMING TASKS (Ability to process sentences with movement)

RESULTS OF OTHER CMLP TASKS Similar results with anomaly detection and eye-tracking while listening paradigms (Dickey and Thompson, 2004) Following Wh- therapy to movement in aphasic patients with agrammatism – patients were able to reject anomalous sentences with movement (i.e., “the girl wore the shirt her mother fried for her”)

TREE PRUNING HYPOTHESIS (Syntactic Tree Structure and complexity) When the lower nodes are impaired, projecting higher nodes in the tree is impossible Japanese patients (Hagiwara, 1995): CP vs. tense and negation Hebrew-speaking patients (Friedmann & Grodinsky, 1997): agreement vs. tense

OVERVIEW OF TREATMENT STUDIES AND FINDINGS “It was the artist who chased the thief” “The artist was chased by the thief” NP Trained Simpler Wh- Trained wh- Simpler

COMPLEXITY IN TREATMENT OF Wh- MOVEMENT Increased object cleft production (significantly above baseline levels) Wh- production emerged Similar learning curves for object clefts and wh- production Object relative clause + objective clefts + wh- questions -Successful generalization to simpler and complex wh-questions (involving movement within an embedded clause) Minimal generalization to wh-questions with more complex structures and embedded clauses No generalization to object clefts (similar to hypothesis: wh- movement does not improve NP movement) Object relative clause (“the man saw the artist who chased the thief”) Object clefts (“it was the artist who the thief chased”) and /or Wh-questions (“who did the thief chase?”

COMPLEXITY IN TREATMENT OF NP- MOVEMENT Subject raising Structures (SRS) SRS PS AS Passive Structures (PS) Active Structures (AS) No generalization to PS and SRS

DISCUSSION OF TREATMENT FINDINGS More pronounced effect of treatment results when complex structures are addressed (simpler structures emerge without direct treatment) Treatment of complex structures only improves less complex structures when they are linguistically linked to trained structures (no generalization with wh- and NP-movement constructions)

DISCUSSION Generalization vs. TPH: NP-movement < wh-movement structures Generalization vs. CATE: cannot be predicted due to underlying linguistic properties which differ across structures (lack of generalization from wh- and NP movement structures because they are fundamentally unrelated) Generalization due to nonlinguistic accounts of complexity? more complex forms require greater processing resources Yet OC and PS had no generalization even though they were similar in form

CLINICAL RELEVANCE Better generalization when working with comprehension and production of complex than simple items Improvements in: MLU Proportion of grammatical sentences used Proportionate number of verbs vs. nouns Correct information units (CIUs): Improved access to a variety of language structures which affects the amount and efficiency of information expressed

CLINICAL RELEVANCE 2. Number of treatment sessions differ between the use of complex vs simple linguistic material Need to provide treatment that results in greatest improvement given a short amount of time (especially considering US health care system)

CLINICAL RELEVANCE 3. Linguistic material vs. treatment approach itself Protocols that exploit linguistic and psycholinguistic properties of sentences result in greater treatment and generalization (vs. direct production approaches / surface form of target sentences)

MAPPING vs. TUF Wh- movement (object clefts and wh-questions) Complex NP movement structures (subject raising structures) MP Comprehension and production of trained forms No NP-/wh- generalization No generalization from passive to more complex NP structures TUF Generalization to object clefts and wh-questions when object relatives were trained

APPLICATIONS OF THE COMPLEXITY ACCOUNT Complexity Hierarchies of Verbs a. Argument structure 1-argument verbs (run) 2-argument verbs (chase, eat) 3-argument verbs (give: agent+theme+goal) Thus training complex 3-argument verbs can improve complex 1- or 2-argument verbs

APPLICATIONS OF THE COMPLEXITY ACCOUNT b. Syntactic movement operations Unaccusative, intransitive (1-argument) verbs involving NP movement which do not have direct mapping of thematic roles onto sentences (fall) 1-argument verb involving no movement (run) which have direct mapping of thematic role onto sentences Psychological verbs which entail an experience thematic role (admire > amuse) Admire: Experiencer + theme in subject and object positions; subject experiencer Amuse: Experiencer occupies the object position, subject is the theme; object experiencer

APPLICATIONS OF THE COMPLEXITY ACCOUNT 2. Complexity of Functional Category Members Complementizer: “He hopes that you go ahead with the speech” No generalization Tense: “I am going”, “I will go” Agreement: “The dogs are barking,” “she is sick” C – Complementizers T- Tense A - Agreement 2 inflected forms are related to one another but one is not necessarily more complex than the other A T T A

CONCLUSIONS Optimal generalization across sentence structures results when underlying linguistic structures are shared When underlying properties differ across structures, generalization does not occur When structural complexity of sentences is controlled, treatment focused on more complex forms results in cascading generalization to simpler forms

CONCLUSIONS Training complex materials results in widespread changes: exploiting lexical and syntactic properties of involved in complex sentences enhances a wide array of structures Fewer treatment sessions are required for patients who receive treatment on complex forms first