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Network Modeling for Functional Magnetic Resonance Imaging (fMRI) Signals during Ultra-Fast Speech Comprehension in Late-Blind Listeners.

Dietrich S, Hertrich I, Ackermann H - PLoS ONE (2015)

Bottom Line: Regarding the output V1 was significantly connected to pre-SMA in blind individuals, and the strength of V1-SMA connectivity correlated with the performance of ultra-fast speech comprehension.By contrast, in sighted controls, not understanding ultra-fast speech, pre-SMA did neither receive input from A1 nor V1.Taken together, right V1 might facilitate the "parsing" of the ultra-fast speech stream in blind subjects by receiving subcortical auditory input via the Pv (= secondary visual pathway) and transmitting this information toward contralateral pre-SMA.

View Article: PubMed Central - PubMed

Affiliation: Department of General Neurology, Hertie Institute for Clinical Brain Research, Center for Neurology, University of Tübingen, Hoppe-Seyler-Str. 3, D-72076 Tübingen, Germany.

ABSTRACT
In many functional magnetic resonance imaging (fMRI) studies blind humans were found to show cross-modal reorganization engaging the visual system in non-visual tasks. For example, blind people can manage to understand (synthetic) spoken language at very high speaking rates up to ca. 20 syllables/s (syl/s). FMRI data showed that hemodynamic activation within right-hemispheric primary visual cortex (V1), bilateral pulvinar (Pv), and left-hemispheric supplementary motor area (pre-SMA) covaried with their capability of ultra-fast speech (16 syllables/s) comprehension. It has been suggested that right V1 plays an important role with respect to the perception of ultra-fast speech features, particularly the detection of syllable onsets. Furthermore, left pre-SMA seems to be an interface between these syllabic representations and the frontal speech processing and working memory network. So far, little is known about the networks linking V1 to Pv, auditory cortex (A1), and (mesio-) frontal areas. Dynamic causal modeling (DCM) was applied to investigate (i) the input structure from A1 and Pv toward right V1 and (ii) output from right V1 and A1 to left pre-SMA. As concerns the input Pv was significantly connected to V1, in addition to A1, in blind participants, but not in sighted controls. Regarding the output V1 was significantly connected to pre-SMA in blind individuals, and the strength of V1-SMA connectivity correlated with the performance of ultra-fast speech comprehension. By contrast, in sighted controls, not understanding ultra-fast speech, pre-SMA did neither receive input from A1 nor V1. Taken together, right V1 might facilitate the "parsing" of the ultra-fast speech stream in blind subjects by receiving subcortical auditory input via the Pv (= secondary visual pathway) and transmitting this information toward contralateral pre-SMA.

No MeSH data available.


Related in: MedlinePlus

Bayesian model averaging (BMA).Individual DCM mean parameters of (a) driving input and (b) connection strength, tested for significance (parameter ≠ 0, one sample t test) separately for each subgroup (blind and sighted). Consistently for both subgroups and all speech conditions (bw8, bw16, fw8, fw16), driving input on A1 and Pv was highly significant. Significant values are represented by asterisks: p < 0.05 (*), p < 0.01 (**), p < 0.001 (***). Lower panels show Bonferroni Holm corrected data of blind (c) and sighted (d) individuals applied to the anatomically/functionally based network hypotheses (gray). Driving input is exemplified with the forward ultra-fast speech condition (fw16).
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pone.0132196.g005: Bayesian model averaging (BMA).Individual DCM mean parameters of (a) driving input and (b) connection strength, tested for significance (parameter ≠ 0, one sample t test) separately for each subgroup (blind and sighted). Consistently for both subgroups and all speech conditions (bw8, bw16, fw8, fw16), driving input on A1 and Pv was highly significant. Significant values are represented by asterisks: p < 0.05 (*), p < 0.01 (**), p < 0.001 (***). Lower panels show Bonferroni Holm corrected data of blind (c) and sighted (d) individuals applied to the anatomically/functionally based network hypotheses (gray). Driving input is exemplified with the forward ultra-fast speech condition (fw16).

Mentions: Consistently for both subgroups and all speech conditions (bw8, bw16, fw8, fw16), driving input on A1 and Pv was highly significant (A1: p < 0.001, Pv: p < 0.01; corr.) (Fig 5A, Table 3). Regarding the blind subgroup, connections from Pv to V1 (positive values, p < 0.01), from V1 to pre-SMA (positive values, p < 0.01), as well as from Pv to A1 (positive values, p < 0.01) and A1 to Pv (negative values, p < 0.001) were significant under Bonferroni Holm correction (Fig 5B and 5C, Table 3A). Coupling between A1 and pre-SMA as well as from pre-SMA/A1 to V1 were found to be significant, but not under Bonferroni Holm correction (Fig 5B and 5C, Table 3). Regarding the sighted subgroup, all connections between Pv, A1, V1, and pre-SMA were found to be non-significant under Bonferroni Holm correction (Fig 5B and 5D, Table 3).


Network Modeling for Functional Magnetic Resonance Imaging (fMRI) Signals during Ultra-Fast Speech Comprehension in Late-Blind Listeners.

Dietrich S, Hertrich I, Ackermann H - PLoS ONE (2015)

Bayesian model averaging (BMA).Individual DCM mean parameters of (a) driving input and (b) connection strength, tested for significance (parameter ≠ 0, one sample t test) separately for each subgroup (blind and sighted). Consistently for both subgroups and all speech conditions (bw8, bw16, fw8, fw16), driving input on A1 and Pv was highly significant. Significant values are represented by asterisks: p < 0.05 (*), p < 0.01 (**), p < 0.001 (***). Lower panels show Bonferroni Holm corrected data of blind (c) and sighted (d) individuals applied to the anatomically/functionally based network hypotheses (gray). Driving input is exemplified with the forward ultra-fast speech condition (fw16).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4492787&req=5

pone.0132196.g005: Bayesian model averaging (BMA).Individual DCM mean parameters of (a) driving input and (b) connection strength, tested for significance (parameter ≠ 0, one sample t test) separately for each subgroup (blind and sighted). Consistently for both subgroups and all speech conditions (bw8, bw16, fw8, fw16), driving input on A1 and Pv was highly significant. Significant values are represented by asterisks: p < 0.05 (*), p < 0.01 (**), p < 0.001 (***). Lower panels show Bonferroni Holm corrected data of blind (c) and sighted (d) individuals applied to the anatomically/functionally based network hypotheses (gray). Driving input is exemplified with the forward ultra-fast speech condition (fw16).
Mentions: Consistently for both subgroups and all speech conditions (bw8, bw16, fw8, fw16), driving input on A1 and Pv was highly significant (A1: p < 0.001, Pv: p < 0.01; corr.) (Fig 5A, Table 3). Regarding the blind subgroup, connections from Pv to V1 (positive values, p < 0.01), from V1 to pre-SMA (positive values, p < 0.01), as well as from Pv to A1 (positive values, p < 0.01) and A1 to Pv (negative values, p < 0.001) were significant under Bonferroni Holm correction (Fig 5B and 5C, Table 3A). Coupling between A1 and pre-SMA as well as from pre-SMA/A1 to V1 were found to be significant, but not under Bonferroni Holm correction (Fig 5B and 5C, Table 3). Regarding the sighted subgroup, all connections between Pv, A1, V1, and pre-SMA were found to be non-significant under Bonferroni Holm correction (Fig 5B and 5D, Table 3).

Bottom Line: Regarding the output V1 was significantly connected to pre-SMA in blind individuals, and the strength of V1-SMA connectivity correlated with the performance of ultra-fast speech comprehension.By contrast, in sighted controls, not understanding ultra-fast speech, pre-SMA did neither receive input from A1 nor V1.Taken together, right V1 might facilitate the "parsing" of the ultra-fast speech stream in blind subjects by receiving subcortical auditory input via the Pv (= secondary visual pathway) and transmitting this information toward contralateral pre-SMA.

View Article: PubMed Central - PubMed

Affiliation: Department of General Neurology, Hertie Institute for Clinical Brain Research, Center for Neurology, University of Tübingen, Hoppe-Seyler-Str. 3, D-72076 Tübingen, Germany.

ABSTRACT
In many functional magnetic resonance imaging (fMRI) studies blind humans were found to show cross-modal reorganization engaging the visual system in non-visual tasks. For example, blind people can manage to understand (synthetic) spoken language at very high speaking rates up to ca. 20 syllables/s (syl/s). FMRI data showed that hemodynamic activation within right-hemispheric primary visual cortex (V1), bilateral pulvinar (Pv), and left-hemispheric supplementary motor area (pre-SMA) covaried with their capability of ultra-fast speech (16 syllables/s) comprehension. It has been suggested that right V1 plays an important role with respect to the perception of ultra-fast speech features, particularly the detection of syllable onsets. Furthermore, left pre-SMA seems to be an interface between these syllabic representations and the frontal speech processing and working memory network. So far, little is known about the networks linking V1 to Pv, auditory cortex (A1), and (mesio-) frontal areas. Dynamic causal modeling (DCM) was applied to investigate (i) the input structure from A1 and Pv toward right V1 and (ii) output from right V1 and A1 to left pre-SMA. As concerns the input Pv was significantly connected to V1, in addition to A1, in blind participants, but not in sighted controls. Regarding the output V1 was significantly connected to pre-SMA in blind individuals, and the strength of V1-SMA connectivity correlated with the performance of ultra-fast speech comprehension. By contrast, in sighted controls, not understanding ultra-fast speech, pre-SMA did neither receive input from A1 nor V1. Taken together, right V1 might facilitate the "parsing" of the ultra-fast speech stream in blind subjects by receiving subcortical auditory input via the Pv (= secondary visual pathway) and transmitting this information toward contralateral pre-SMA.

No MeSH data available.


Related in: MedlinePlus