Changes in task-based effective connectivity in language networks following rehabilitation in post-stroke patients with aphasia

Swathi Kiran, Erin L Meier, Kushal J Kapse, Peter A Glynn, Swathi Kiran, Erin L Meier, Kushal J Kapse, Peter A Glynn

Abstract

In this study, we examined regions in the left and right hemisphere language network that were altered in terms of the underlying neural activation and effective connectivity subsequent to language rehabilitation. Eight persons with chronic post-stroke aphasia and eight normal controls participated in the current study. Patients received a 10 week semantic feature-based rehabilitation program to improve their skills. Therapy was provided on atypical examples of one trained category while two control categories were monitored; the categories were counterbalanced across patients. In each fMRI session, two experimental tasks were conducted: (a) picture naming and (b) semantic feature verification of trained and untrained categories. Analysis of treatment effect sizes revealed that all patients showed greater improvements on the trained category relative to untrained categories. Results from this study show remarkable patterns of consistency despite the inherent variability in lesion size and activation patterns across patients. Across patients, activation that emerged as a function of rehabilitation on the trained category included bilateral IFG, bilateral SFG, LMFG, and LPCG for picture naming; and bilateral IFG, bilateral MFG, LSFG, and bilateral MTG for semantic feature verification. Analysis of effective connectivity using Dynamic Causal Modeling (DCM) indicated that LIFG was the consistently significantly modulated region after rehabilitation across participants. These results indicate that language networks in patients with aphasia resemble normal language control networks and that this similarity is accentuated by rehabilitation.

Keywords: aphasia; dynamic causal modeling; effective connectivity; fMRI activations; language recovery; naming; rehabilitation; stroke.

Figures

Figure 1
Figure 1
Lesion overlap of all the eight patients.
Figure 2
Figure 2
Picture naming (top) and Semantic feature task (bottom).
Figure 3
Figure 3
(A) Overlap activation maps of the eight healthy controls for picture naming task. (B) Overlap activation maps of the eight healthy controls for the semantic feature verification task. The voxels are at threshold based on T > 3.10, p = 0.001. See Tables 4, 5 for individual thresholded activation.
Figure 4
Figure 4
(A) Connectivity patterns for controls for the picture naming task. (B) Connectivity patterns for controls for the semantic feature verification task. For both tasks, average modulation for eight controls are shown. Oval shapes are the VOI's selected for model space, ranging from lowest (red) to highest (blue) modulation strengths. Intrinsic connections are shown in black arrows.
Figure 5
Figure 5
Series of images showing individual patients' activation maps for the picture naming task illustrating the [post-rehabilitation (picture-scrambled)]–[pre-rehabilitation (picture-scrambled)] contrast for the trained category atp= 0.001 uncorrected. Voxels above a threshold of T > 3.10 are shown.
Figure 6
Figure 6
Series of images showing individual patients' activation maps for the semantic feature verification task illustrating the [post-rehabilitation (picture-scrambled)]–[pre-rehabilitation (picture-scrambled)] contrast for the trained category atp= 0.001 uncorrected. Voxels above a threshold of T > 3.10 are shown.
Figure 7
Figure 7
Series of images show individual patients' connectivity networks as a function of rehabilitation for the trained category on the picture naming task. Regions with significant modulations are shown in blue ovals while regions with non-significant modulations are shown in white ovals. Intrinsic connections are shown in black arrows while connections with significant modulations are shown in red arrows.
Figure 8
Figure 8
Series of images showing individual patients' connectivity networks as a function of rehabilitation for the trained category on the semantic feature verification task. Regions with significant modulations are shown in blue ovals while regions with non-significant modulations are shown in white ovals. Intrinsic connections are shown in black arrows while connections with significant modulations are shown in red arrows.

References

    1. Abutalebi J., Rosa P. A., Tettamanti M., Green D. W., Cappa S. F. (2009). Bilingual aphasia and language control: a follow-up fMRI and intrinsic connectivity study. Brain Lang. 109, 141–156. 10.1016/j.bandl.2009.03.003
    1. Beeson P. M., Robey R. R. (2006). Evaluating single-subject treatment research: lessons learned from the aphasia literature. Neuropsychol. Rev. 16, 161–169. 10.1007/s11065-006-9013-7
    1. Binder J. R., Desai R. H. (2011). The neurobiology of semantic memory. Trends Cogn. Sci. 15, 527–536. 10.1016/j.tics.2011.10.001
    1. Binder J. R., Desai R. H., Graves W. W., Conant L. L. (2009). Where is the semantic system? A critical review and meta-analysis of 120 functional neuroimaging studies. Cereb. Cortex 19, 2767–2796. 10.1093/cercor/bhp055
    1. Birn R. M., Cox R. W., Bandettini P. A. (2004). Experimental designs and processing strategies for fMRI studies involving overt verbal responses. Neuroimage 23, 1046–1058. 10.1016/j.neuroimage.2004.07.039
    1. Brett M., Leff A. P., Rorden C., Ashburner J. (2001). Spatial normalization of brain images with focal lesions using cost function masking. Neuroimage 14, 486–500. 10.1006/nimg.2001.0845
    1. Busk P. L., Serlin R. (1992). Meta analysis for single case research, in Single Case Research Design and Analysis: New Directions for Psychology and Education, eds Kratochwill T. R., Levin J. R. (Hillsdale, NJ: Lawrence Earlbaum Associates Inc; ), 187–212.
    1. Campo P., Poch C., Toledano R., Igoa J. M., Belinchon M., Garcia-Morales I., et al. . (2013). Anterobasal temporal lobe lesions alter recurrent functional connectivity within the ventral pathway during naming. J. Neurosci. 33, 12679–12688. 10.1523/JNEUROSCI.0645-13.2013
    1. Cappa S. F. (2012). Imaging semantics and syntax. Neuroimage 61, 427–431. 10.1016/j.neuroimage.2011.10.006
    1. Coltheart M. (1981). The MRC psycholinguistic database. Q. J. Exp. Psychol. 33A, 497–505. 10.1080/14640748108400805
    1. Crinion J. T., Leff A. P. (2007). Recovery and treatment of aphasia after stroke: functional imaging studies. Curr. Opin. Neurol. 20, 667–673. 10.1097/WCO.0b013e3282f1c6fa
    1. Crosson B., McGregor K., Gopinath K. S., Conway T. W., Benjamin M., Chang Y. L., et al. . (2007). Functional MRI of language in aphasia: a review of the literature and the methodological challenges. Neuropsychol. Rev. 17, 157–177. 10.1007/s11065-007-9024-z
    1. Crosson B., Moore A. B., McGregor K. M., Chang Y. L., Benjamin M., Gopinath K., et al. . (2009). Regional changes in word-production laterality after a naming treatment designed to produce a rightward shift in frontal activity. Brain Lang. 111, 73–85. 10.1016/j.bandl.2009.08.001
    1. Davis C. H., Harrington G., Baynes K. (2006). Intensive semantic intervention in fluent aphasia: a pilot study with fMRI. Aphasiology 20, 59–83. 10.1080/02687030500331841
    1. Fedorenko E., Duncan J., Kanwisher N. (2013). Broad domain generality in focal regions of frontal and parietal cortex. Proc. Natl. Acad. Sci. U.S.A. 110, 16616–16621. 10.1073/pnas.1315235110
    1. Fridriksson J. (2010). Preservation and modulation of specific left hemisphere regions is vital for treated recovery from anomia in stroke. J. Neurosci. 30, 11558–11564. 10.1523/JNEUROSCI.2227-10.2010
    1. Fridriksson J., Bonilha L., Baker J. M., Moser D., Rorden C. (2010). Activity in preserved left hemisphere regions predicts anomia severity in aphasia. Cereb. Cortex 20, 1013–1019. 10.1093/cercor/bhp160
    1. Fridriksson J., Morrow-Odom L., Moser D., Fridriksson A., Baylis G. (2006). Neural recruitment associated with anomia treatment in aphasia. Neuroimage 32, 1403–1412. 10.1016/j.neuroimage.2006.04.194
    1. Fridriksson J., Moser D., Bonilha L., Morrow-Odom K. L., Shaw H., Fridriksson A., et al. . (2007). Neural correlates of phonological and semantic-based anomia treatment in aphasia. Neuropsychologia 45, 1812–1822. 10.1016/j.neuropsychologia.2006.12.017
    1. Fridriksson J., Richardson J. D., Fillmore P., Cai B. (2012). Left hemisphere plasticity and aphasia recovery. Neuroimage 60, 854–863. 10.1016/j.neuroimage.2011.12.057
    1. Goodglass H., Kaplan E., Weintraub S. (1983). Boston Naming Test. Philadelphia, PA: Lea & Febiger.
    1. Grefkes C., Eickhoff S. B., Nowak D. A., Dafotakis M., Fink G. R. (2008). Dynamic intra- and interhemispheric interactions during unilateral and bilateral hand movements assessed with fMRI and DCM. Neuroimage 41, 1382–1394. 10.1016/j.neuroimage.2008.03.048
    1. Harnish S. M., Neils-Strunjas J., Lamy M., Eliassen J. C., Harnish S. M., Neils-Strunjas J., et al. . (2008). Use of fMRI in the study of chronic aphasia recovery after therapy: a case study. Top. Stroke Rehabil. 15, 468–483. 10.1310/tsr1505-468
    1. Heath S., McMahon K. L., Nickels L., Angwin A., MacDonald A. D., van Hees S., et al. . (2012). Neural mechanisms underlying the facilitation of naming in aphasia using a semantic task: an fMRI study. BMC Neurosci. 13:98. 10.1186/1471-2202-13-98
    1. Helm-Estabrooks N. (2001). Cognitive Linguistic Quick Test. London: Harcourt Assessment.
    1. Howard D., Patterson K. (1992). Pyramids and Palm Trees. London: Harcourt Assessment.
    1. Indefrey P., Levelt W. J. (2004). The spatial and temporal signatures of word production components. Cognition 92, 101–144. 10.1016/j.cognition.2002.06.001
    1. Jefferies E. (2013). The neural basis of semantic cognition: converging evidence from neuropsychology, neuroimaging and TMS. Cortex 49, 611–625. 10.1016/j.cortex.2012.10.008
    1. Kahan J., Foltynie T. (2013). Understanding DCM: ten simple rules for the clinician. Neuroimage 83, 542–549. 10.1016/j.neuroimage.2013.07.008
    1. Kaplan E., Goodglass H., Weintraub S. (2001). Boston Naming Test, 2nd Edn. Philadelphia, PA: Lippincott Williams & Wilkins.
    1. Kertesz A. (2007). The Western Aphasia Battery-Revised. San Antonio, TX: Psych Corp.
    1. Kiran S. (2007). Complexity in the treatment of naming deficits. Am. J. Speech Lang. Pathol. 16, 18–29. 10.1044/1058-0360(2007/004)
    1. Kiran S. (2008). Typicality of inanimate category exemplars in aphasia treatment: further evidence for semantic complexity. J. Speech Lang. Hear. Res. 51, 1550–1568. 10.1044/1092-4388(2008/07-0038)
    1. Kiran S., Ansaldo A., Bastiaanse R., Cherney L. R., Howard D., Faroqi-Shah Y., et al. . (2013). Neuroimaging in aphasia treatment research: Standards for establishing the effects of treatment. Neuroimage 76, 428–435.
    1. Kiran S., Bassetto G. (2008). Evaluating the effectivness of semantic based treatment for naming deficits in aphasia: what works? Semin. Speech Lang. 29, 71–82. 10.1055/s-2008-1061626
    1. Kiran S., Johnson L. (2008). Semantic complexity in treatment of naming deficits in aphasia: evidence from well-defined categories. Am. J. Speech Lang. Pathol. 17, 389–400. 10.1044/1058-0360(2008/06-0085)
    1. Kiran S., Sandberg C., Abbott K. (2009). Treatment for lexical retrieval using abstract and concrete words in persons with aphasia: effect of complexity. Aphasiology 23, 835–853. 10.1080/02687030802588866
    1. Kiran S., Sandberg C., Sebastian R. (2011). Treatment of category generation and retrieval in aphasia: effect of typicality of category items. J. Speech Lang. Hear. Res. 54, 1101–1117. 10.1044/1092-4388(2010/10-0117)
    1. Kiran S., Thompson C. K. (2003). The role of semantic complexity in treatment of naming deficits: training semantic categories in fluent aphasia by controlling exemplar typicality. J. Speech Lang. Hear. Res. 46, 608; 773–787. 10.1044/1092-4388(2003/061)
    1. Marcotte K., Adrover-Roig D., Damien B., de Preaumont M., Genereux S., Hubert M., et al. . (2012). Therapy-induced neuroplasticity in chronic aphasia. Neuropsychologia 50, 1776–1786. 10.1016/j.neuropsychologia.2012.04.001
    1. Marcotte K., Ansaldo A. I. (2010). The neural correlates of semantic feature analysis in chronic aphasia: discordant patterns according to the etiology. Semin. Speech Lang. 31, 52–63. 10.1055/s-0029-1244953
    1. Mazaika P., Hoeft F., Glover G. H., Reiss A. L. (2009). Methods and software for fMRI analysis for clinical subjects, in Human Brain Mapping, (San Francisco, CA: ).
    1. Meinzer M., Beeson P. M., Cappa S., Crinion J., Kiran S., Saur D., et al. . (2013). Neuroimaging in aphasia treatment research: consensus and practical guidelines for data analysis. Neuroimage 73, 215–224. 10.1016/j.neuroimage.2012.02.058
    1. Meinzer M., Flaisch T., Breitenstein C., Wienbruch C., Elbert T., Rockstroh B. (2008). Functional re-recruitment of dysfunctional brain areas predicts language recovery in chronic aphasia. Neuroimage 39, 2038–2046. 10.1016/j.neuroimage.2007.10.008
    1. Meltzer J. A., Postman-Caucheteux W. A., McArdle J. J., Braun A. R. (2009). Strategies for longitudinal neuroimaging studies of overt language production. Neuroimage 47, 745–755. 10.1016/j.neuroimage.2009.04.089
    1. Menke R., Meinzer M., Kugel H., Deppe M., Baumgartner A., Schiffbauer H., et al. . (2009). Imaging short- and long-term training success in chronic aphasia. BMC Neurosci. 10:118. 10.1186/1471-2202-10-118
    1. Peck K. K., Moore A. B., Crosson B. A., Gaiefsky M., Gopinath K. S., White K., et al. . (2004). Functional magnetic resonance imaging before and after aphasia therapy: shifts in hemodynamic time to peak during an overt language task. Stroke 35, 554–559. 10.1161/01.STR.0000110983.50753.9D
    1. Postman-Caucheteux W. A., Birn R. M., Pursley R. H., Butman J. A., Solomon J. M., Picchioni D., et al. . (2009). Single-trial fMRI shows contralesional activity linked to overt naming errors in chronic aphasic patients. J. Cogn. Neurosci. 22, 1299–1318. 10.1162/jocn.2009.21261
    1. Price C. J., Crinion J. (2005). The latest on functional imaging studies of aphasic stroke. Curr. Opin. Neurol. 18, 429–434. 10.1097/01.wco.0000168081.76859.c1
    1. Raboyeau G., De Boissezon X., Marie N., Balduyck S., Puel M., Bezy C., et al. . (2008). Right hemisphere activation in recovery from aphasia: lesion effect or function recruitment? Neurology 70, 290–298. 10.1212/01.wnl.0000287115.85956.87
    1. Rehme A. K., Eickhoff S. B., Wang L. E., Fink G. R., Grefkes C. (2011). Dynamic causal modeling of cortical activity from the acute to the chronic stage after stroke. Neuroimage 55, 1147–1158. 10.1016/j.neuroimage.2011.01.014
    1. Rochon E., Leonard C., Burianova H., Laird L., Soros P., Graham S., et al. . (2010). Neural changes after phonological treatment for anomia: an fMRI study. Brain Lang. 114, 164–179. 10.1016/j.bandl.2010.05.005
    1. Sandberg C., Kiran S. (2014). Analysis of abstract and concrete word processing in persons with aphasia and age-matched neurologically healthy adults using fMRI. Neurocase 20, 361–388.
    1. Sarasso S., Santhanam P., Maatta S., Poryazova R., Ferrarelli F., Tononi G., et al. . (2010). Non-fluent aphasia and neural reorganization after speech therapy: insights from human sleep electrophysiology and functional magnetic resonance imaging. Arch. Ital. Biol. 148, 271–278.
    1. Sebastian R., Kiran S. (2011). Task modulated activation patterns in chronic stroke patients with aphasia. Aphasiology 25, 927–951. 10.1080/02687038.2011.557436
    1. Sebastian R., Kiran S., Sandberg C. (2012). Semantic processing in Spanish–English bilinguals with aphasia. J. Neurolinguistics 25, 240–262. 10.1016/j.jneuroling.2012.01.003
    1. Seghier M. L., Lazeyras F., Pegna A. J., Annoni J. M., Zimine I., Mayer E., et al. . (2004). Variability of fMRI activation during a phonological and semantic language task in healthy subjects. Hum. Brain Mapp. 23, 140–155. 10.1002/hbm.20053
    1. Seghier M. L., Price C. J. (2011). Explaining left lateralization for words in the ventral occipitotemporal cortex. J. Neurosci. 31, 14745–14753. 10.1523/JNEUROSCI.2238-11.2011
    1. Seghier M. L., Zeidman P., Neufeld N. H., Leff A. P., Price C. J. (2010). Identifying abnormal connectivity in patients using dynamic causal modeling of FMRI responses. Front. Syst. Neurosci. 4:142. 10.3389/fnsys.2010.00142
    1. Soldan A., Habeck C., Gazes Y., Stern Y. (2010). Neural mechanisms of repetition priming of familiar and globally unfamiliar visual objects. Brain Res. 1343, 122–134. 10.1016/j.brainres.2010.04.071
    1. Sonty S. P., Mesulam M. M., Weintraub S., Johnson N. A., Parrish T. B., Gitelman D. R. (2007). Altered effective connectivity within the language network in primary progressive aphasia. J. Neurosci. 27, 1334–1345. 10.1523/JNEUROSCI.4127-06.2007
    1. Stephan K. E., Penny W. D., Moran R. J., den Ouden H. E., Daunizeau J., Friston K. J. (2010). Ten simple rules for dynamic causal modeling. Neuroimage 49, 3099–3109. 10.1016/j.neuroimage.2009.11.015
    1. Teki S., Barnes G. R., Penny W. D., Iverson P., Woodhead Z. V., Griffiths T. D., et al. . (2013). The right hemisphere supports but does not replace left hemisphere auditory function in patients with persisting aphasia. Brain 136, 1901–1912. 10.1093/brain/awt087
    1. Thompson C. K. (2007). Complexity in language learning and treatment. Am. J. Speech Lang. Pathol. 16, 3–5. 10.1044/1058-0360(2007/002)
    1. Thompson C. K., den Ouden D. B. (2008). Neuroimaging and recovery of language in aphasia. Curr. Neurol. Neurosci. Rep. 8, 475–483. 10.1007/s11910-008-0076-0
    1. Turkeltaub P. E., Messing S., Norise C., Hamilton R. H. (2011). Are networks for residual language function and recovery consistent across aphasic patients? Neurology 76, 1726–1734. 10.1212/WNL.0b013e31821a44c1
    1. Tyler L. K., Chiu S., Zhuang J., Randall B., Devereux B. J., Wright P., et al. . (2013). Objects and categories: feature statistics and object processing in the ventral stream. J. Cogn. Neurosci. 25, 1723–1735. 10.1162/jocn_a_00419
    1. Vanderwouden T. (1990). Celex - building a multifunctional, polytheoretical lexical database, in Budalex '88 Proceedings (Budapest: ), 363–373.
    1. van Hees S., McMahon K., Angwin A., de Zubicaray G., Copland D. A. (2014). Neural activity associated with semantic versus phonological anomia treatments in aphasia. Brain Lang. 129, 47–57. 10.1016/j.bandl.2013.12.004
    1. van Oers C. A., Vink M., van Zandvoort M. J., van der Worp H. B., de Haan E. H., Kappelle L. J., et al. . (2010). Contribution of the left and right inferior frontal gyrus in recovery from aphasia. A functional MRI study in stroke patients with preserved hemodynamic responsiveness. Neuroimage 49, 885–893. 10.1016/j.neuroimage.2009.08.057
    1. Vigneau M., Beaucousin V., Herve P. Y., Duffau H., Crivello F., Houde O., et al. . (2006). Meta-analyzing left hemisphere language areas: phonology, semantics, and sentence processing. Neuroimage 30, 1414–1432. 10.1016/j.neuroimage.2005.11.002
    1. Vigneau M., Beaucousin V., Herve P. Y., Jobard G., Petit L., Crivello F., et al. . (2011). What is right-hemisphere contribution to phonological, lexico-semantic, and sentence processing? Insights from a meta-analysis. Neuroimage 54, 577–593. 10.1016/j.neuroimage.2010.07.036
    1. Visser M., Jefferies E., Embleton K. V., Lambon Ralph M. A. (2012). Both the middle temporal gyrus and the ventral anterior temporal area are crucial for multimodal semantic processing: distortion-corrected fMRI evidence for a double gradient of information convergence in the temporal lobes. J. Cogn. Neurosci. 24, 1766–1778. 10.1162/jocn_a_00244
    1. Vitali P., Abutalebi J., Tettamanti M., Danna M., Ansaldo A. I., Perani D., et al. . (2007). Training-induced brain remapping in chronic aphasia: a pilot study. Neurorehabil. Neural Repair 21, 152–160. 10.1177/1545968306294735
    1. Vitali P., Tettamanti M., Abutalebi J., Ansaldo A. I., Perani D., Cappa S. F., et al. . (2010). Generalization of the effects of phonological training for anomia using structural equation modelling: a multiple single-case study. Neurocase 16, 93–105. 10.1080/13554790903329117
    1. Voets N. L., Adcock J. E., Flitney D. E., Behrens T. E., Hart Y., Stacey R., et al. . (2006). Distinct right frontal lobe activation in language processing following left hemisphere injury. Brain 129, 754–766. 10.1093/brain/awh679
    1. Wierenga C. E., Benjamin M., Gopinath K., Perlstein W. M., Leonard C. M., Rothi L. J., et al. . (2008). Age-related changes in word retrieval: role of bilateral frontal and subcortical networks. Neurobiol. Aging 29, 436–451. 10.1016/j.neurobiolaging.2006.10.024
    1. Winhuisen L., Thiel A., Schumacher B., Kessler J., Rudolf J., Haupt W. F., et al. . (2007). The right inferior frontal gyrus and poststroke aphasia: a follow-up investigation. Stroke 38, 1286–1292. 10.1161/01.STR.0000259632.04324.6c
    1. Zannino G. D., Buccione I., Perri R., Macaluso E., Lo Gerfo E., Caltagirone C., et al. . (2010). Visual and semantic processing of living things and artifacts: an FMRI study. J. Cogn. Neurosci. 22, 554–570. 10.1162/jocn.2009.21197
    1. Zhu D., Chang J., Freeman S., Tan Z., Xiao J., Gao Y., et al. . (2014). Changes of functional connectivity in the left frontoparietal network following aphasic stroke. Front. Behav. Neurosci. 8:167. 10.3389/fnbeh.2014.00167

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