Presentation Transcript

1. Broca’s Area and the Language Instinct

   By Peter Dang and Kyle Dennison
2. Introduction Ability to acquire language is a unique and essential human trait Chomsky’s Universal Grammar The human brain contains a limited set of rules for organizing language Assumption that all languages have a common structural basis
3. Purpose of the Study Purpose: To investigate the system underlying the acquisition of new linguistic competence based on Chomsky’s UG Alternative View: The human mind is a general learning tool without specialized structures
4. Methods Two fMRI experiments Both consisted of native German speakers Difference was whether participants learned Japanese or Italian Subjects were to learn 3 grammatical rules in foreign language and 3 artificial rules of an ‘unreal’ language
5. Methods (Cont…) Prior to the experiment, participants were given a list of words to memorize Avoid confounding syntactic rule acquisition with word learning Recall ability was tested over words
6. fMRI Trials Subjects learned real and unreal grammatical rules during pauses of 3 minutes between sessions in the form of slides Subjects read 6 sentences in real and unreal languages and judged their syntactic correctness Correct – Left middle finger Incorrect – Left index finger
7. Grammatical Rule Examples Null-subject parameter German: “I eat the pear” Italian: “Eat the pear” Subordinate construction German: “Pia says that Paolo the pear eats” Italian: “Pia says that Paolo eats the pear”
8. Unreal Grammatical Rules Negative Construction “Paolo eats the no pear” Interrogative Construction “Pear the eats Paolo”
9. Relevant Brain Regions
10. Behavioral Results Eight subjects from each experiment were analyzed: In judging the syntactical correctness of sentences the subjects achieved the same percent correct by the end of the experiment. Real Italian: 97 ± 4.1 % Unreal Italian: 91.6 ± 10% Real Japanese: 97 ± 3.2% Unreal Japanese: 94 ± 4.68%
11. Behavioral Results Continued The increase in performance between the acquisition of real vs. unreal rules was not significantly different. T7 =0.1, P = 0.57 in the first fMRI experiment T7 = 0.5, P = 0.32 in the second fMRI experiment
12. Figure 1a Figure 1 Behavioral measurements. (a) Performance (mean % correct) in judging the syntactical correctness of the sentences presented in each of the five fMRI sessions per learning task (data averaged across subjects). Performance showed an improvement across sessions during the learning tasks. Performance increase was not significantly difference between the acquisition of real versus unreal Italian (left) or Japanese (right) grammatical rules.
13. Behavioral Results: Reaction Time Over the course of the sessions subjects responded faster (reduced RT) and improved in accuracy. There were four of these experiments: Real vs. Unreal Italian and Real vs. Unreal Japanese. In every reaction time experiment the faster responses were significant: T7 = 0.79, P < 0.0001
14. Reaction Time Results Continued Subjects were able to make faster grammatical judgments in the real learning tasks than in the unreal learning tasks (Both Italian and Japanese). Real vs. Unreal Italian: T7 = 0.79, P < 0.0001 Real vs. Unreal Japanese: T7 = 1.9, P < 0.03 These results are significant.
15. Figure 1b Figure 1 Behavioral measurements. (b) Mean reaction times (RT) for the correct syntactical judgment of the presented sentences in each of five fMRI sessions per task. Subjects showed a significant RT reduction (P < 0.0001) across sessions in all grammatical rules learning tasks. Reaction times were faster during the grammatical learning tasks (either Italian or Japanese) than during the artificial learning tasks (P < 0.03).
16. Functional Imaging Results There were two conditions: Looking at a black screen (the baseline task) Judging grammatical correctness of sentences (classification task) With the condition of judging grammatical correctness fMRI data showed activation in: Anterior Cingulate Occipital Cortex Cerebellum Inferior and middle temporal gyrus Prefrontal parietal P < 0.05 and corrected for multiple comparisons
17. fMRI Results Continued fMRI measured blood-oxygen level dependent (BOLD) signal A random effects model was used to identify the activation pattern specific to the interaction between the change in BOLD signal and type of rule learning (real or unreal) reflected by accuracy of performance. No specific pattern of brain activation was found for unreal grammatical acquisition (Italian or Japanese). There was an interaction between real and unreal grammatical acquisition in Broca’s Area (pars triangularis of the left inferior frontal gyrus). In this area the increase in BOLD signal was correlated with the increase in accuracy during the acquisition of natural rules for Japanese and Italian.
18. Figure 2 Figure 2 Result of the interaction between performance and type of rule learning (real versus unreal Italian). Left, the activation specific to real language acquisition resulting from the random effects analysis is displayed on selected slices of the MRI template available in SPM99. The threshold was set at P < 0.05 (corrected for multiple comparisons). Right, plots of changes in BOLD (blood oxygen-level dependent) signal in the left inferior frontal gyrus (Talairach coordinates x, y, z: –45, 21, 6) for the five sessions containing ‘real grammatical rule’ trials and the five sessions with ‘unreal grammatical rule’ trials are shown as a function of accuracy within sessions. The distances between individual subjects’ peak voxel and the peak voxel derived from the group analysis using a random model were 28, 23, 3, 24, 13, 11, 23 and 15 mm, respectively, for subjects 1–8.
19. Figure 2 Images
20. Figure 4 Figure 4 Results of the interaction between performance and type of rule learning (real Italian versus unreal Italian in yellow; real versus unreal Japanese in red) resulting from the random effects analysis are shown on selected slices of the T1 template, thresholded at P < 0.001 (uncorrected) for visualization. Right, plots of individual changes in BOLD signal in the left inferior frontal gyrus during the acquisition of grammatical rules of either real or unreal Japanese are shown as a function of accuracy within sessions The distances between individual subjects’ peak voxel and the peak voxel derived from the group analysis using a random model were 12, 21, 25, 9, 9, 9, 6 and 11 mm, respectively, for subjects 1–8.
21. Figure 4 Images
22. fMRI Results: Broca’s Area The correlation coefficient between parameter estimates in Broca’s Area and the accuracy of performance showed: A significant positive correlation between BOLD signal and accuracy in the real grammatical task. Italian experiment: r = + 0.66, P < 0.001 Japanese Experiment: r = + 0.47, P < 0.001 A significant negative correlation between parameter estimates (BOLD signal) and learning unreal rules. Italian experiment: r = - 0.50, P < 0.001 Japanese experiment: r = - 0.32, P = 0.021
23. fMRI Results Not in Broca’s Area There was a significant increase in BOLD signal in 2 parts of the right inferior frontal gyrus related to better performance (accuracy). This positive correlation between BOLD signal and accuracy occurred for both the real (Italian and Japanese) and unreal (Italian and Japanese) tasks. Real Italian r = .37, P = .008; Real Japanese r = .21, P = .009 Unreal Italian r = .33, P = .01; Unreal Japanese r = .040, P = .004 There was also activation in the left lingual gyrus The Japanese study showed further activation in the: Left cingulate, Right Insula, Right supramarginal gyrus, and Left cerebellum
24. Figure 3
25. Figure 5
26. Discussion: Right Inferior Frontal Gyrus Adults acquire language by learning explicitly about grammar. The inferior frontal gyrus is part of a neuronal system that deals with episodic memory retrieval. It’s generally accepted that the job of the right inferior frontal gyrus in learning “real” and “unreal” rules is to monitor information independently of its character. It retrieves either hierarchical or linear information from episodic memory when making a response. Explicit retrieval of information does not seem to be enough to acquire proficiency in a new language.
27. Discussion: Broca’s Area This study presents neurophysiological evidence that learning UG based and Non-UG based languages involves different brain systems. Broca’s Area plays a significant part in learning “real” language rules. Because languages from different families were used general statements can be made about acquiring language. The study points to a universal syntactic specialization among “real” languages because activation of Broca’s area occurred regardless of language of the subjects. This study combined with previous research leads the authors to think that this region is specialized for acquiring and processing hierarchical structures (common character of every known grammar) Additional support is provided by the negative correlation between BOLD signal and learning “unreal” grammatical rules.
28. Other Evidence Suggesting Broca’s Importance Members of the KE family are prone to dysphasia (difficulty understanding/speaking language, either written or spoken). There are structural and functional abnormalities in the left prefrontal cortex, which includes Broca’s area. Problems with the FOXP2 gene are the likely cause of KE family’s disorders This is consistent with the observation that language impairments can run in families and are more concordant in identical than fraternal twins. This shows that genetic material can influence language ability.
29. Evolution and Broca’s Area The target of selection in humans appears to be the FOXP2 gene. Results seem to support a common origin for human speech and possibly some communication in non-human primates. Chimpanzees and gorillas learn words, but they don’t have the same syntax abilities as humans nor are their sign motions as well defined. Monkey’s show left hemisphere asymmetry similar to humans, but the left inferior frontal lobe has less cellular density and is less differentiated This study in particular demonstrates that the left inferior frontal gyrus is centrally involved in acquiring new languages based on UG. The authors speculate that the complexities of Broca’s area may be what makes us different from the other primates.