The literate mind and brain. Brenda Rapp Department of Cognitive Science Johns Hopkins University

Transcription

1 The literate mind and brain Brenda Rapp Department of Cognitive Science Johns Hopkins University 1

2 Written language Spoken language: A human capacity with deep genetic roots that allows us to describe and explain the world Written language: A relatively recent human inventions Allows us to preserve ideas independently of the speaker, across time and space Vital for the accumulation of knowledge and science Abraham Lincoln: Writing, the art of communicating thoughts to the mind through the eye, is the great invention of the world...enabling us to converse with the dead, the absent, and the unborn, at all distances of time and space. Speeches And Letters Of Abraham Lincoln,

3 Written language in the age of e-communication? Language-use survey (on-line, Mechanical Turk) 3 age groups: 18-25, 26-35, language types: Spoken language/non-electronic Listening or talking in person Spoken language/electronic phone, TV, radio, movie, online video, podcast, audio book, Skyp)e Written language/non-electronic Reading or writing on paper : book, magazine, letter, notes, docs Written language/electronic Reading or typing in electronic media (text messaging, , websites, online chatting, word processing, blogging, apps, computer programs, e-readers) 3

4 40% 30% 20% 10% 0% (N=152) (N=125) 36+ (N=124) Written Electronic Spoken Electronic Spoken Non-Electronic Written Non-Electronic

5 Written language in the age of e-communication? Conclusions: Written language is increasingly vital in everyday life Among young, tech-savvy individuals time spent reading and writing in electronic media can be greater than time spent with: Face-to-face spoken language Spoken language in electronic media (telephone, TV, radio, etc.)

6 Overview 1. Written language in the expert adult system: Neural evidence 2. Learning written language: Cognitive evidence 3. Learning and relearning written language: Neural approaches 7

7 Overview 1. Written language in the expert adult system: Neural evidence 2. Learning written language: Cognitive evidence 3. Learning and relearning written language: Neural approaches 8

8 Written language Spoken language, object recognition, navigation, etc. are evolutionarily old skills that have genetic basis Written language is an evolutionarily recent human invention (3000 AD) Unlike evolutionarily old skills, written language is explicitly taught and learned How does the human brain incorporate skills like reading and writing that are not specifically dictated by the genetic blueprint? 9

9 Written language in the literate adult How is the study of the neural bases of written language in the adult relevant to understanding written language learning in children? The expert adult brain represents the end-state/goal for the child learner; understanding the end-state can shape teaching 10

10 Neuroimaging studies: During spelling (and reading) the brain recruits areas traditionally associated with various basic cognitive functions, revealing the multiple components of written language processing. spoken language attention/spatial visual object processing Meta-analysis of neuroimaging studies of spelling Purcell, Turkeltaub, Eden & Rapp, 2011 Question: In the adult system, are the written language processes dependent or independent of these older, more basic skills?

11 Predictions: Neuroimaging If, in the adult system, written language is parasitic on evolutionarily older processes such as spoken language and visual object recognition, then: Written language should activate precisely the same areas as these more basic processes. 12

12 Rapp & Lipka, 2011 houses Reading faces Spelling Although learning to read and spell certainly build on visual networks, fmri reveals that specialized orthographic areas develop.

13 Predictions: Cognitive Neuropsychology If, in the adult system, written language is parasitic on evolutionarily older processes such as spoken language and visual object recognition, then: Damage to the spoken language system should necessarily be accompanied by written language deficits Damage to the written language system should co-occur with difficulties in visual object recognition Damage to orthographic working memory should co-occur with visuo-spatial working memory deficits 14

14 DPT 36 year-old, right-handed male Law degree, corporate tax attorney Resection for oligodendroglioma in left fusiform DSN 67 year-old, right-handed female College degree, retired editor Resection for meningioma in left fusiform Purcell, Shea & Rapp 2014) 15

15 DPT DSN Spelling: Words X X Reading: Words X X Reading: Word comprehension (synonym judgment) Spoken: Word comprehension (synonym judgment) X normal X normal Visual object/face processing normal normal 16

16 Orthographic Working Memory Deficit Lesions (n=9) Centered on the left intra-parietal sulcus Traditionally associated with working memory/attention Left Is orthographic working memory idependent from visuo-spatial working memory?

17 Evaluated Visual-Spatial WM: Corsi Blocks Test span = 5 is within normal limits Results: span = 4.8 (range 4-5); within normal limits The absence of a spatial WM deficit is consistent with domain-specific orthographic WM processing in left IPS region 18

18 Is written language parasitic on evolutionarily older processes such as spoken language and object recognition? Written language certainly depends on spoken language, visual object processes and the working memory system during development However, in the competent, literate adult there is considerable independence of orthographic processing Neuronal recycling or neuronal repurposing occurs where areas designed for other cognitive functions are used for specialized orthographic processing/representation 19

19 Overview 1. Written language in the expert adult system: Neural evidence 2. Learning written language: Cognitive evidence 3. Learning and relearning written language: Neural approaches 20

20 Letter perception and learning (Wiley, Wilson and Rapp; under review) 1. Does expertise affect letter perception? Compare naïve and expert observers 2. Are different alphabets perceived differently? Compare visual feature rankings for Roman and Arabic letters 21

21 Two groups of participants: Experts: proficient readers of Arabic (n = 24) Naïve: no prior exposure to Arabic (n = 24) Participants judged if two shapes were physically identical Examined RTs and accuracy 22

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23 Linear mixed effects modeling (LMEM) 1. Group: expert/naïve 2. Knowledge-based factors: phonological similarity, letter identity, motoric similarity, alphabetic order 3. Visual features : For each pair of letters, their similarity was calculated for each of 15 different visual features 24

24 Does expertise affect perception? Knowledge-based factors Visual feature rankings Significant effects of shared identity and motor stroke similarity for the expert viewers only 25

25 Are alphabets perceived differently? Within and across alphabet visual feature rankings 26

26 Learning affects letter perception The findings reveal a visual system that, with learning, dynamically adjusts its weighting of visual features 1. Task-irrelevant knowledge affects perceptual judgments Knowledge-based factors influence perception (motoric strokes, letter identity, etc.) 2. Expertise affects visual feature processing Naïve and expert observers weigh visual features differently and with experience, complex visual features are recognized more efficiently 3. Different alphabets are perceived differently Even expert observers learn to view different alphabets differently 27

27 Cognitively Optimized/individualized of learning of first and multiple written languages/scripts Develop techniques for individualized evaluation of individual perceptual profiles that serves as basis for targeted teaching and interventions that will efficiently move learners from being naïve to expert viewers 28

28 Overview 1. Written language in the expert adult system: Neural evidence 2. Learning written language: Cognitive evidence 3. Learning and relearning written language: Neural approaches 29

29 Measuring neural changes in real-time orthographic learning (Schubert, Purcell & Rapp, in prep) While in the scanner, participants are taught new spellings; items are presented for 7 learning trials while brain responses are measured Results: Orthographic learning involves different types of changes in different brain regions: in cortical areas involved in long-term memory storage (fusiform g.) vs. areas involved in early learning stages (hippocampus) Fusiform gyrus Hippocampus

30 Measuring orthographic learning: Changes in resting state networks Resting-state fmri records brain response while participants are at rest in a relaxed, awake state Advantages: for populations that have difficulty performing tasks in the scanner (children and individuals with disabilities) Can evaluate learning-related changes 31

31 Network-specific regions of interest (ROIs) Reading Network (RdN) Default-Mode Network (DMN) From Turkeltaub et al. (2002) From Laird et al. (2009) Network Coherence: Correlation of RS-fMRI time series for ROIS within and across networks How does network coherence change with (re)learning? 32

32 Network Coherence: Correlation of RS-fMRI time series for within and across network ROIs Neuro-typical group * * } Reading network ROIs RdN DMN DMN network ROIs

33 Within vs. across network coherence values differences for: - Neurotypical individuals - Adults with acquired dysgraphia (pre-treatment)

34 Treatment-related normalization of within vs. across network coherence for adults with acquired dysgraphia: pre vs. post treatment

35 Conclusions We are well-positioned to bridge to the teaching and remediation of reading and spelling in first and multilanguage learners Strong theoretical foundations Neuroimaging methods Analytical techniques Singapore is remarkably well-positioned with its multilingual population and education system 36

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