Sentence comprehension in aphasia: A noisy channel approach
Probabilistic accounts of language understanding assume that comprehension involves determining the probability of an intended message (m) given an input utterance (u) (P(m|u); e.g. Gibson et al, 2013a; Levy et al, 2009). One challenge is that communication occurs within a noisy channel; i.e. the co...
Ausführliche Beschreibung
Autor*in: |
Michael Walsh Dickey [verfasserIn] |
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Englisch |
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2014 |
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In: Frontiers in Psychology - Frontiers Media S.A., 2010, 5(2014) |
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volume:5 ; year:2014 |
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DOI / URN: |
10.3389/conf.fpsyg.2014.64.00068 |
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DOAJ043420826 |
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520 | |a Probabilistic accounts of language understanding assume that comprehension involves determining the probability of an intended message (m) given an input utterance (u) (P(m|u); e.g. Gibson et al, 2013a; Levy et al, 2009). One challenge is that communication occurs within a noisy channel; i.e. the comprehender’s representation of u may have been distorted, e.g., by a typo or by impairment associated with aphasia. Bayes’ rule provides a model of how comprehenders can combine the prior probability of m (P(m)) with the probability that m would have been distorted to u (P(mu)) to calculate the probability of m given u (P(m|u) P(m)P(mu)). This formalism can capture the observation that people with aphasia (PWA) rely more on semantics than syntax during comprehension (e.g., Caramazza & Zurif, 1976): given the high probability that their representation of the input is unreliable, they weigh message likelihood more heavily. Gibson et al. (2013a) showed that unimpaired adults are sensitive to P(m) and P(mu): they more often chose interpretations that increased message plausibility or involved distortions requiring fewer changes, and/or deletions instead of insertions (see Figure 1a for examples). Gibson et al. (2013b) found PWA were also sensitive to both P(m) and P(mu) in an act-out task, but relied more heavily than unimpaired controls on P(m). This shows group-level optimization towards the less noisy (semantic) channel in PWA. The current experiment (8 PWA; 7 age-matched controls) investigated noisy channel optimization at the level of individual PWA. It also included active/passive items with a weaker plausibility manipulation to test whether P(m) is higher for implausible than impossible strings. The task was forced-choice sentence-picture matching (Figure 1b). Experimental sentences crossed active versus passive (A-P) structures with plausibility (Set 1) or impossibility (Set 2), and prepositional-object versus double-object structures (PO-DO: Set 3) with plausibility. Target pictures depicted the observed utterance u; foils depicted a message that could have been distorted to u (Figure 1a-b). Replicating Gibson et al (2013b), both controls and PWA more often chose foils when the possible distortions involved fewer changes (DO-PO compared to A-P: F[1,13]=4.82, p<.05). This is despite passives’ low frequency and common impairment in aphasia (Schwartz, et al., 1980). Furthermore, although both groups more often chose foils when the possible distortion was more plausible, this preference was larger for PWA (plausibility x group interaction : F[1,13]=12.09, p<.01). The strength of the semantic manipulation did not matter: plausibility and possibility manipulations did not differ. Interestingly, there was little evidence that an individual’s reliance on the form of the input vs. the likelihood of a message was predicted by their syntactic vs. semantic abilities. Standardized sentence-comprehension scores (Comprehensive Aphasia Test: Swinburn, et al., 2004) did not predict preference for simpler distortions, nor did conceptual-semantic processing measures (e.g., Kissing and Dancing: Bak & Hodges, 2003; Pyramids and Palm Trees: Howard & Patterson, 1992) predict the size of plausibility effects. Additionally, individual participants showed non-optimization: one PWA with relatively spared syntax (good performance on reversible passives) but impaired semantics (poor conceptual-semantic processing scores) relied almost exclusively on semantics. | ||
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10.3389/conf.fpsyg.2014.64.00068 doi (DE-627)DOAJ043420826 (DE-599)DOAJ71ae7d737b5a486aa841b1e08df12a20 DE-627 ger DE-627 rakwb eng BF1-990 Michael Walsh Dickey verfasserin aut Sentence comprehension in aphasia: A noisy channel approach 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Probabilistic accounts of language understanding assume that comprehension involves determining the probability of an intended message (m) given an input utterance (u) (P(m|u); e.g. Gibson et al, 2013a; Levy et al, 2009). One challenge is that communication occurs within a noisy channel; i.e. the comprehender’s representation of u may have been distorted, e.g., by a typo or by impairment associated with aphasia. Bayes’ rule provides a model of how comprehenders can combine the prior probability of m (P(m)) with the probability that m would have been distorted to u (P(mu)) to calculate the probability of m given u (P(m|u) P(m)P(mu)). This formalism can capture the observation that people with aphasia (PWA) rely more on semantics than syntax during comprehension (e.g., Caramazza & Zurif, 1976): given the high probability that their representation of the input is unreliable, they weigh message likelihood more heavily. Gibson et al. (2013a) showed that unimpaired adults are sensitive to P(m) and P(mu): they more often chose interpretations that increased message plausibility or involved distortions requiring fewer changes, and/or deletions instead of insertions (see Figure 1a for examples). Gibson et al. (2013b) found PWA were also sensitive to both P(m) and P(mu) in an act-out task, but relied more heavily than unimpaired controls on P(m). This shows group-level optimization towards the less noisy (semantic) channel in PWA. The current experiment (8 PWA; 7 age-matched controls) investigated noisy channel optimization at the level of individual PWA. It also included active/passive items with a weaker plausibility manipulation to test whether P(m) is higher for implausible than impossible strings. The task was forced-choice sentence-picture matching (Figure 1b). Experimental sentences crossed active versus passive (A-P) structures with plausibility (Set 1) or impossibility (Set 2), and prepositional-object versus double-object structures (PO-DO: Set 3) with plausibility. Target pictures depicted the observed utterance u; foils depicted a message that could have been distorted to u (Figure 1a-b). Replicating Gibson et al (2013b), both controls and PWA more often chose foils when the possible distortions involved fewer changes (DO-PO compared to A-P: F[1,13]=4.82, p<.05). This is despite passives’ low frequency and common impairment in aphasia (Schwartz, et al., 1980). Furthermore, although both groups more often chose foils when the possible distortion was more plausible, this preference was larger for PWA (plausibility x group interaction : F[1,13]=12.09, p<.01). The strength of the semantic manipulation did not matter: plausibility and possibility manipulations did not differ. Interestingly, there was little evidence that an individual’s reliance on the form of the input vs. the likelihood of a message was predicted by their syntactic vs. semantic abilities. Standardized sentence-comprehension scores (Comprehensive Aphasia Test: Swinburn, et al., 2004) did not predict preference for simpler distortions, nor did conceptual-semantic processing measures (e.g., Kissing and Dancing: Bak & Hodges, 2003; Pyramids and Palm Trees: Howard & Patterson, 1992) predict the size of plausibility effects. Additionally, individual participants showed non-optimization: one PWA with relatively spared syntax (good performance on reversible passives) but impaired semantics (poor conceptual-semantic processing scores) relied almost exclusively on semantics. syntax semantics sentence comprehension Bayesian inference sentence comprehension in aphasia Psychology Michael Walsh Dickey verfasserin aut In Frontiers in Psychology Frontiers Media S.A., 2010 5(2014) (DE-627)631495711 (DE-600)2563826-9 16641078 nnns volume:5 year:2014 https://doi.org/10.3389/conf.fpsyg.2014.64.00068 kostenfrei https://doaj.org/article/71ae7d737b5a486aa841b1e08df12a20 kostenfrei http://journal.frontiersin.org/Journal/10.3389/conf.fpsyg.2014.64.00068/full kostenfrei https://doaj.org/toc/1664-1078 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2086 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 5 2014 |
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10.3389/conf.fpsyg.2014.64.00068 doi (DE-627)DOAJ043420826 (DE-599)DOAJ71ae7d737b5a486aa841b1e08df12a20 DE-627 ger DE-627 rakwb eng BF1-990 Michael Walsh Dickey verfasserin aut Sentence comprehension in aphasia: A noisy channel approach 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Probabilistic accounts of language understanding assume that comprehension involves determining the probability of an intended message (m) given an input utterance (u) (P(m|u); e.g. Gibson et al, 2013a; Levy et al, 2009). One challenge is that communication occurs within a noisy channel; i.e. the comprehender’s representation of u may have been distorted, e.g., by a typo or by impairment associated with aphasia. Bayes’ rule provides a model of how comprehenders can combine the prior probability of m (P(m)) with the probability that m would have been distorted to u (P(mu)) to calculate the probability of m given u (P(m|u) P(m)P(mu)). This formalism can capture the observation that people with aphasia (PWA) rely more on semantics than syntax during comprehension (e.g., Caramazza & Zurif, 1976): given the high probability that their representation of the input is unreliable, they weigh message likelihood more heavily. Gibson et al. (2013a) showed that unimpaired adults are sensitive to P(m) and P(mu): they more often chose interpretations that increased message plausibility or involved distortions requiring fewer changes, and/or deletions instead of insertions (see Figure 1a for examples). Gibson et al. (2013b) found PWA were also sensitive to both P(m) and P(mu) in an act-out task, but relied more heavily than unimpaired controls on P(m). This shows group-level optimization towards the less noisy (semantic) channel in PWA. The current experiment (8 PWA; 7 age-matched controls) investigated noisy channel optimization at the level of individual PWA. It also included active/passive items with a weaker plausibility manipulation to test whether P(m) is higher for implausible than impossible strings. The task was forced-choice sentence-picture matching (Figure 1b). Experimental sentences crossed active versus passive (A-P) structures with plausibility (Set 1) or impossibility (Set 2), and prepositional-object versus double-object structures (PO-DO: Set 3) with plausibility. Target pictures depicted the observed utterance u; foils depicted a message that could have been distorted to u (Figure 1a-b). Replicating Gibson et al (2013b), both controls and PWA more often chose foils when the possible distortions involved fewer changes (DO-PO compared to A-P: F[1,13]=4.82, p<.05). This is despite passives’ low frequency and common impairment in aphasia (Schwartz, et al., 1980). Furthermore, although both groups more often chose foils when the possible distortion was more plausible, this preference was larger for PWA (plausibility x group interaction : F[1,13]=12.09, p<.01). The strength of the semantic manipulation did not matter: plausibility and possibility manipulations did not differ. Interestingly, there was little evidence that an individual’s reliance on the form of the input vs. the likelihood of a message was predicted by their syntactic vs. semantic abilities. Standardized sentence-comprehension scores (Comprehensive Aphasia Test: Swinburn, et al., 2004) did not predict preference for simpler distortions, nor did conceptual-semantic processing measures (e.g., Kissing and Dancing: Bak & Hodges, 2003; Pyramids and Palm Trees: Howard & Patterson, 1992) predict the size of plausibility effects. Additionally, individual participants showed non-optimization: one PWA with relatively spared syntax (good performance on reversible passives) but impaired semantics (poor conceptual-semantic processing scores) relied almost exclusively on semantics. syntax semantics sentence comprehension Bayesian inference sentence comprehension in aphasia Psychology Michael Walsh Dickey verfasserin aut In Frontiers in Psychology Frontiers Media S.A., 2010 5(2014) (DE-627)631495711 (DE-600)2563826-9 16641078 nnns volume:5 year:2014 https://doi.org/10.3389/conf.fpsyg.2014.64.00068 kostenfrei https://doaj.org/article/71ae7d737b5a486aa841b1e08df12a20 kostenfrei http://journal.frontiersin.org/Journal/10.3389/conf.fpsyg.2014.64.00068/full kostenfrei https://doaj.org/toc/1664-1078 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2086 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 5 2014 |
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10.3389/conf.fpsyg.2014.64.00068 doi (DE-627)DOAJ043420826 (DE-599)DOAJ71ae7d737b5a486aa841b1e08df12a20 DE-627 ger DE-627 rakwb eng BF1-990 Michael Walsh Dickey verfasserin aut Sentence comprehension in aphasia: A noisy channel approach 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Probabilistic accounts of language understanding assume that comprehension involves determining the probability of an intended message (m) given an input utterance (u) (P(m|u); e.g. Gibson et al, 2013a; Levy et al, 2009). One challenge is that communication occurs within a noisy channel; i.e. the comprehender’s representation of u may have been distorted, e.g., by a typo or by impairment associated with aphasia. Bayes’ rule provides a model of how comprehenders can combine the prior probability of m (P(m)) with the probability that m would have been distorted to u (P(mu)) to calculate the probability of m given u (P(m|u) P(m)P(mu)). This formalism can capture the observation that people with aphasia (PWA) rely more on semantics than syntax during comprehension (e.g., Caramazza & Zurif, 1976): given the high probability that their representation of the input is unreliable, they weigh message likelihood more heavily. Gibson et al. (2013a) showed that unimpaired adults are sensitive to P(m) and P(mu): they more often chose interpretations that increased message plausibility or involved distortions requiring fewer changes, and/or deletions instead of insertions (see Figure 1a for examples). Gibson et al. (2013b) found PWA were also sensitive to both P(m) and P(mu) in an act-out task, but relied more heavily than unimpaired controls on P(m). This shows group-level optimization towards the less noisy (semantic) channel in PWA. The current experiment (8 PWA; 7 age-matched controls) investigated noisy channel optimization at the level of individual PWA. It also included active/passive items with a weaker plausibility manipulation to test whether P(m) is higher for implausible than impossible strings. The task was forced-choice sentence-picture matching (Figure 1b). Experimental sentences crossed active versus passive (A-P) structures with plausibility (Set 1) or impossibility (Set 2), and prepositional-object versus double-object structures (PO-DO: Set 3) with plausibility. Target pictures depicted the observed utterance u; foils depicted a message that could have been distorted to u (Figure 1a-b). Replicating Gibson et al (2013b), both controls and PWA more often chose foils when the possible distortions involved fewer changes (DO-PO compared to A-P: F[1,13]=4.82, p<.05). This is despite passives’ low frequency and common impairment in aphasia (Schwartz, et al., 1980). Furthermore, although both groups more often chose foils when the possible distortion was more plausible, this preference was larger for PWA (plausibility x group interaction : F[1,13]=12.09, p<.01). The strength of the semantic manipulation did not matter: plausibility and possibility manipulations did not differ. Interestingly, there was little evidence that an individual’s reliance on the form of the input vs. the likelihood of a message was predicted by their syntactic vs. semantic abilities. Standardized sentence-comprehension scores (Comprehensive Aphasia Test: Swinburn, et al., 2004) did not predict preference for simpler distortions, nor did conceptual-semantic processing measures (e.g., Kissing and Dancing: Bak & Hodges, 2003; Pyramids and Palm Trees: Howard & Patterson, 1992) predict the size of plausibility effects. Additionally, individual participants showed non-optimization: one PWA with relatively spared syntax (good performance on reversible passives) but impaired semantics (poor conceptual-semantic processing scores) relied almost exclusively on semantics. syntax semantics sentence comprehension Bayesian inference sentence comprehension in aphasia Psychology Michael Walsh Dickey verfasserin aut In Frontiers in Psychology Frontiers Media S.A., 2010 5(2014) (DE-627)631495711 (DE-600)2563826-9 16641078 nnns volume:5 year:2014 https://doi.org/10.3389/conf.fpsyg.2014.64.00068 kostenfrei https://doaj.org/article/71ae7d737b5a486aa841b1e08df12a20 kostenfrei http://journal.frontiersin.org/Journal/10.3389/conf.fpsyg.2014.64.00068/full kostenfrei https://doaj.org/toc/1664-1078 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2086 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 5 2014 |
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10.3389/conf.fpsyg.2014.64.00068 doi (DE-627)DOAJ043420826 (DE-599)DOAJ71ae7d737b5a486aa841b1e08df12a20 DE-627 ger DE-627 rakwb eng BF1-990 Michael Walsh Dickey verfasserin aut Sentence comprehension in aphasia: A noisy channel approach 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Probabilistic accounts of language understanding assume that comprehension involves determining the probability of an intended message (m) given an input utterance (u) (P(m|u); e.g. Gibson et al, 2013a; Levy et al, 2009). One challenge is that communication occurs within a noisy channel; i.e. the comprehender’s representation of u may have been distorted, e.g., by a typo or by impairment associated with aphasia. Bayes’ rule provides a model of how comprehenders can combine the prior probability of m (P(m)) with the probability that m would have been distorted to u (P(mu)) to calculate the probability of m given u (P(m|u) P(m)P(mu)). This formalism can capture the observation that people with aphasia (PWA) rely more on semantics than syntax during comprehension (e.g., Caramazza & Zurif, 1976): given the high probability that their representation of the input is unreliable, they weigh message likelihood more heavily. Gibson et al. (2013a) showed that unimpaired adults are sensitive to P(m) and P(mu): they more often chose interpretations that increased message plausibility or involved distortions requiring fewer changes, and/or deletions instead of insertions (see Figure 1a for examples). Gibson et al. (2013b) found PWA were also sensitive to both P(m) and P(mu) in an act-out task, but relied more heavily than unimpaired controls on P(m). This shows group-level optimization towards the less noisy (semantic) channel in PWA. The current experiment (8 PWA; 7 age-matched controls) investigated noisy channel optimization at the level of individual PWA. It also included active/passive items with a weaker plausibility manipulation to test whether P(m) is higher for implausible than impossible strings. The task was forced-choice sentence-picture matching (Figure 1b). Experimental sentences crossed active versus passive (A-P) structures with plausibility (Set 1) or impossibility (Set 2), and prepositional-object versus double-object structures (PO-DO: Set 3) with plausibility. Target pictures depicted the observed utterance u; foils depicted a message that could have been distorted to u (Figure 1a-b). Replicating Gibson et al (2013b), both controls and PWA more often chose foils when the possible distortions involved fewer changes (DO-PO compared to A-P: F[1,13]=4.82, p<.05). This is despite passives’ low frequency and common impairment in aphasia (Schwartz, et al., 1980). Furthermore, although both groups more often chose foils when the possible distortion was more plausible, this preference was larger for PWA (plausibility x group interaction : F[1,13]=12.09, p<.01). The strength of the semantic manipulation did not matter: plausibility and possibility manipulations did not differ. Interestingly, there was little evidence that an individual’s reliance on the form of the input vs. the likelihood of a message was predicted by their syntactic vs. semantic abilities. Standardized sentence-comprehension scores (Comprehensive Aphasia Test: Swinburn, et al., 2004) did not predict preference for simpler distortions, nor did conceptual-semantic processing measures (e.g., Kissing and Dancing: Bak & Hodges, 2003; Pyramids and Palm Trees: Howard & Patterson, 1992) predict the size of plausibility effects. Additionally, individual participants showed non-optimization: one PWA with relatively spared syntax (good performance on reversible passives) but impaired semantics (poor conceptual-semantic processing scores) relied almost exclusively on semantics. syntax semantics sentence comprehension Bayesian inference sentence comprehension in aphasia Psychology Michael Walsh Dickey verfasserin aut In Frontiers in Psychology Frontiers Media S.A., 2010 5(2014) (DE-627)631495711 (DE-600)2563826-9 16641078 nnns volume:5 year:2014 https://doi.org/10.3389/conf.fpsyg.2014.64.00068 kostenfrei https://doaj.org/article/71ae7d737b5a486aa841b1e08df12a20 kostenfrei http://journal.frontiersin.org/Journal/10.3389/conf.fpsyg.2014.64.00068/full kostenfrei https://doaj.org/toc/1664-1078 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2086 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 5 2014 |
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This formalism can capture the observation that people with aphasia (PWA) rely more on semantics than syntax during comprehension (e.g., Caramazza & Zurif, 1976): given the high probability that their representation of the input is unreliable, they weigh message likelihood more heavily. Gibson et al. (2013a) showed that unimpaired adults are sensitive to P(m) and P(mu): they more often chose interpretations that increased message plausibility or involved distortions requiring fewer changes, and/or deletions instead of insertions (see Figure 1a for examples). Gibson et al. (2013b) found PWA were also sensitive to both P(m) and P(mu) in an act-out task, but relied more heavily than unimpaired controls on P(m). This shows group-level optimization towards the less noisy (semantic) channel in PWA. The current experiment (8 PWA; 7 age-matched controls) investigated noisy channel optimization at the level of individual PWA. It also included active/passive items with a weaker plausibility manipulation to test whether P(m) is higher for implausible than impossible strings. The task was forced-choice sentence-picture matching (Figure 1b). Experimental sentences crossed active versus passive (A-P) structures with plausibility (Set 1) or impossibility (Set 2), and prepositional-object versus double-object structures (PO-DO: Set 3) with plausibility. Target pictures depicted the observed utterance u; foils depicted a message that could have been distorted to u (Figure 1a-b). Replicating Gibson et al (2013b), both controls and PWA more often chose foils when the possible distortions involved fewer changes (DO-PO compared to A-P: F[1,13]=4.82, p<.05). This is despite passives’ low frequency and common impairment in aphasia (Schwartz, et al., 1980). Furthermore, although both groups more often chose foils when the possible distortion was more plausible, this preference was larger for PWA (plausibility x group interaction : F[1,13]=12.09, p<.01). The strength of the semantic manipulation did not matter: plausibility and possibility manipulations did not differ. Interestingly, there was little evidence that an individual’s reliance on the form of the input vs. the likelihood of a message was predicted by their syntactic vs. semantic abilities. Standardized sentence-comprehension scores (Comprehensive Aphasia Test: Swinburn, et al., 2004) did not predict preference for simpler distortions, nor did conceptual-semantic processing measures (e.g., Kissing and Dancing: Bak & Hodges, 2003; Pyramids and Palm Trees: Howard & Patterson, 1992) predict the size of plausibility effects. 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Michael Walsh Dickey |
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Sentence comprehension in aphasia: A noisy channel approach |
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Sentence comprehension in aphasia: A noisy channel approach |
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sentence comprehension in aphasia: a noisy channel approach |
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Sentence comprehension in aphasia: A noisy channel approach |
abstract |
Probabilistic accounts of language understanding assume that comprehension involves determining the probability of an intended message (m) given an input utterance (u) (P(m|u); e.g. Gibson et al, 2013a; Levy et al, 2009). One challenge is that communication occurs within a noisy channel; i.e. the comprehender’s representation of u may have been distorted, e.g., by a typo or by impairment associated with aphasia. Bayes’ rule provides a model of how comprehenders can combine the prior probability of m (P(m)) with the probability that m would have been distorted to u (P(mu)) to calculate the probability of m given u (P(m|u) P(m)P(mu)). This formalism can capture the observation that people with aphasia (PWA) rely more on semantics than syntax during comprehension (e.g., Caramazza & Zurif, 1976): given the high probability that their representation of the input is unreliable, they weigh message likelihood more heavily. Gibson et al. (2013a) showed that unimpaired adults are sensitive to P(m) and P(mu): they more often chose interpretations that increased message plausibility or involved distortions requiring fewer changes, and/or deletions instead of insertions (see Figure 1a for examples). Gibson et al. (2013b) found PWA were also sensitive to both P(m) and P(mu) in an act-out task, but relied more heavily than unimpaired controls on P(m). This shows group-level optimization towards the less noisy (semantic) channel in PWA. The current experiment (8 PWA; 7 age-matched controls) investigated noisy channel optimization at the level of individual PWA. It also included active/passive items with a weaker plausibility manipulation to test whether P(m) is higher for implausible than impossible strings. The task was forced-choice sentence-picture matching (Figure 1b). Experimental sentences crossed active versus passive (A-P) structures with plausibility (Set 1) or impossibility (Set 2), and prepositional-object versus double-object structures (PO-DO: Set 3) with plausibility. Target pictures depicted the observed utterance u; foils depicted a message that could have been distorted to u (Figure 1a-b). Replicating Gibson et al (2013b), both controls and PWA more often chose foils when the possible distortions involved fewer changes (DO-PO compared to A-P: F[1,13]=4.82, p<.05). This is despite passives’ low frequency and common impairment in aphasia (Schwartz, et al., 1980). Furthermore, although both groups more often chose foils when the possible distortion was more plausible, this preference was larger for PWA (plausibility x group interaction : F[1,13]=12.09, p<.01). The strength of the semantic manipulation did not matter: plausibility and possibility manipulations did not differ. Interestingly, there was little evidence that an individual’s reliance on the form of the input vs. the likelihood of a message was predicted by their syntactic vs. semantic abilities. Standardized sentence-comprehension scores (Comprehensive Aphasia Test: Swinburn, et al., 2004) did not predict preference for simpler distortions, nor did conceptual-semantic processing measures (e.g., Kissing and Dancing: Bak & Hodges, 2003; Pyramids and Palm Trees: Howard & Patterson, 1992) predict the size of plausibility effects. Additionally, individual participants showed non-optimization: one PWA with relatively spared syntax (good performance on reversible passives) but impaired semantics (poor conceptual-semantic processing scores) relied almost exclusively on semantics. |
abstractGer |
Probabilistic accounts of language understanding assume that comprehension involves determining the probability of an intended message (m) given an input utterance (u) (P(m|u); e.g. Gibson et al, 2013a; Levy et al, 2009). One challenge is that communication occurs within a noisy channel; i.e. the comprehender’s representation of u may have been distorted, e.g., by a typo or by impairment associated with aphasia. Bayes’ rule provides a model of how comprehenders can combine the prior probability of m (P(m)) with the probability that m would have been distorted to u (P(mu)) to calculate the probability of m given u (P(m|u) P(m)P(mu)). This formalism can capture the observation that people with aphasia (PWA) rely more on semantics than syntax during comprehension (e.g., Caramazza & Zurif, 1976): given the high probability that their representation of the input is unreliable, they weigh message likelihood more heavily. Gibson et al. (2013a) showed that unimpaired adults are sensitive to P(m) and P(mu): they more often chose interpretations that increased message plausibility or involved distortions requiring fewer changes, and/or deletions instead of insertions (see Figure 1a for examples). Gibson et al. (2013b) found PWA were also sensitive to both P(m) and P(mu) in an act-out task, but relied more heavily than unimpaired controls on P(m). This shows group-level optimization towards the less noisy (semantic) channel in PWA. The current experiment (8 PWA; 7 age-matched controls) investigated noisy channel optimization at the level of individual PWA. It also included active/passive items with a weaker plausibility manipulation to test whether P(m) is higher for implausible than impossible strings. The task was forced-choice sentence-picture matching (Figure 1b). Experimental sentences crossed active versus passive (A-P) structures with plausibility (Set 1) or impossibility (Set 2), and prepositional-object versus double-object structures (PO-DO: Set 3) with plausibility. Target pictures depicted the observed utterance u; foils depicted a message that could have been distorted to u (Figure 1a-b). Replicating Gibson et al (2013b), both controls and PWA more often chose foils when the possible distortions involved fewer changes (DO-PO compared to A-P: F[1,13]=4.82, p<.05). This is despite passives’ low frequency and common impairment in aphasia (Schwartz, et al., 1980). Furthermore, although both groups more often chose foils when the possible distortion was more plausible, this preference was larger for PWA (plausibility x group interaction : F[1,13]=12.09, p<.01). The strength of the semantic manipulation did not matter: plausibility and possibility manipulations did not differ. Interestingly, there was little evidence that an individual’s reliance on the form of the input vs. the likelihood of a message was predicted by their syntactic vs. semantic abilities. Standardized sentence-comprehension scores (Comprehensive Aphasia Test: Swinburn, et al., 2004) did not predict preference for simpler distortions, nor did conceptual-semantic processing measures (e.g., Kissing and Dancing: Bak & Hodges, 2003; Pyramids and Palm Trees: Howard & Patterson, 1992) predict the size of plausibility effects. Additionally, individual participants showed non-optimization: one PWA with relatively spared syntax (good performance on reversible passives) but impaired semantics (poor conceptual-semantic processing scores) relied almost exclusively on semantics. |
abstract_unstemmed |
Probabilistic accounts of language understanding assume that comprehension involves determining the probability of an intended message (m) given an input utterance (u) (P(m|u); e.g. Gibson et al, 2013a; Levy et al, 2009). One challenge is that communication occurs within a noisy channel; i.e. the comprehender’s representation of u may have been distorted, e.g., by a typo or by impairment associated with aphasia. Bayes’ rule provides a model of how comprehenders can combine the prior probability of m (P(m)) with the probability that m would have been distorted to u (P(mu)) to calculate the probability of m given u (P(m|u) P(m)P(mu)). This formalism can capture the observation that people with aphasia (PWA) rely more on semantics than syntax during comprehension (e.g., Caramazza & Zurif, 1976): given the high probability that their representation of the input is unreliable, they weigh message likelihood more heavily. Gibson et al. (2013a) showed that unimpaired adults are sensitive to P(m) and P(mu): they more often chose interpretations that increased message plausibility or involved distortions requiring fewer changes, and/or deletions instead of insertions (see Figure 1a for examples). Gibson et al. (2013b) found PWA were also sensitive to both P(m) and P(mu) in an act-out task, but relied more heavily than unimpaired controls on P(m). This shows group-level optimization towards the less noisy (semantic) channel in PWA. The current experiment (8 PWA; 7 age-matched controls) investigated noisy channel optimization at the level of individual PWA. It also included active/passive items with a weaker plausibility manipulation to test whether P(m) is higher for implausible than impossible strings. The task was forced-choice sentence-picture matching (Figure 1b). Experimental sentences crossed active versus passive (A-P) structures with plausibility (Set 1) or impossibility (Set 2), and prepositional-object versus double-object structures (PO-DO: Set 3) with plausibility. Target pictures depicted the observed utterance u; foils depicted a message that could have been distorted to u (Figure 1a-b). Replicating Gibson et al (2013b), both controls and PWA more often chose foils when the possible distortions involved fewer changes (DO-PO compared to A-P: F[1,13]=4.82, p<.05). This is despite passives’ low frequency and common impairment in aphasia (Schwartz, et al., 1980). Furthermore, although both groups more often chose foils when the possible distortion was more plausible, this preference was larger for PWA (plausibility x group interaction : F[1,13]=12.09, p<.01). The strength of the semantic manipulation did not matter: plausibility and possibility manipulations did not differ. Interestingly, there was little evidence that an individual’s reliance on the form of the input vs. the likelihood of a message was predicted by their syntactic vs. semantic abilities. Standardized sentence-comprehension scores (Comprehensive Aphasia Test: Swinburn, et al., 2004) did not predict preference for simpler distortions, nor did conceptual-semantic processing measures (e.g., Kissing and Dancing: Bak & Hodges, 2003; Pyramids and Palm Trees: Howard & Patterson, 1992) predict the size of plausibility effects. Additionally, individual participants showed non-optimization: one PWA with relatively spared syntax (good performance on reversible passives) but impaired semantics (poor conceptual-semantic processing scores) relied almost exclusively on semantics. |
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title_short |
Sentence comprehension in aphasia: A noisy channel approach |
url |
https://doi.org/10.3389/conf.fpsyg.2014.64.00068 https://doaj.org/article/71ae7d737b5a486aa841b1e08df12a20 http://journal.frontiersin.org/Journal/10.3389/conf.fpsyg.2014.64.00068/full https://doaj.org/toc/1664-1078 |
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|
score |
7.40149 |