TY - JOUR
T1 - Structural and functional motor-network disruptions predict selective action-concept deficits
T2 - Evidence from frontal lobe epilepsy
AU - Moguilner, Sebastian
AU - Birba, Agustina
AU - Fino, Daniel
AU - Isoardi, Roberto
AU - Huetagoyena, Celeste
AU - Otoya, Raúl
AU - Tirapu, Viviana
AU - Cremaschi, Fabián
AU - Sedeño, Lucas
AU - Ibáñez, Agustín
AU - García, Adolfo M.
N1 - Funding Information:
This work was supported by CONICET ; FONCYT-PICT [grant numbers 2017–1818, 2017–1820 ]; ANID , FONDECYT Regular [grant numbers 1210176 and 1210195 ]; FONDAP [grant number 15150012]; Programa Interdisciplinario de Investigación Experimental en Comunicación y Cognición (PIIECC) , Facultad de Humanidades, USACH; Alzheimer's Association GBHI ALZ UK-20-639295; Takeda CW2680521; and the Multi-Partner Consortium to Expand Dementia Research in Latin America (ReDLat), funded by the National Institutes of Aging of the National Institutes of Health under award number R01AG057234 , an Alzheimer's Association grant (SG-20-725707-ReDLat), the Rainwater Foundation , and the Global Brain Health Institute. The content is solely the responsibility of the authors and does not represent the official views of the National Institutes of Health, Alzheimer's Association, Rainwater Charitable Foundation, or Global Brain Health Institute.
Funding Information:
This work was supported by CONICET; FONCYT-PICT [grant numbers 2017?1818, 2017?1820]; ANID, FONDECYT Regular [grant numbers 1210176 and 1210195]; FONDAP [grant number 15150012]; Programa Interdisciplinario de Investigaci?n Experimental en Comunicaci?n y Cognici?n (PIIECC), Facultad de Humanidades, USACH; Alzheimer's Association GBHI ALZ UK-20-639295; Takeda CW2680521; and the Multi-Partner Consortium to Expand Dementia Research in Latin America (ReDLat), funded by the National Institutes of Aging of the National Institutes of Health under award number R01AG057234, an Alzheimer's Association grant (SG-20-725707-ReDLat), the Rainwater Foundation, and the Global Brain Health Institute. The content is solely the responsibility of the authors and does not represent the official views of the National Institutes of Health, Alzheimer's Association, Rainwater Charitable Foundation, or Global Brain Health Institute.
Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2021/11
Y1 - 2021/11
N2 - Built on neurodegenerative lesions models, the disrupted motor grounding hypothesis (DMGH) posits that motor-system alterations selectively impair action comprehension. However, major doubts remain concerning the dissociability, neural signatures, and etiological generalizability of such deficits. Few studies have compared action-concept outcomes between disorders affecting and sparing motor circuitry, and none has examined their multimodal network predictors via data-driven approaches. Here, we first assessed action- and object-concept processing in patients with frontal lobe epilepsy (FLE), patients with posterior cortex epilepsy (PCE), and healthy controls. Then, we examined structural and functional network signatures via diffusion tensor imaging and resting-state connectivity measures. Finally, we used these measures to predict behavioral performance with an XGBoost machine learning regression algorithm. Relative to controls, FLE (but not PCE) patients exhibited selective action-concept deficits together with structural and functional abnormalities along motor networks. The XGBoost model reached a significantly large effect size only for action-concept outcomes in FLE, mainly predicted by structural (cortico-spinal tract, anterior thalamic radiation, uncinate fasciculus) and functional (M1-parietal/supramarginal connectivity) motor networks. These results extend the DMGH, suggesting that action-concept deficits are dissociable markers of frontal/motor (relative to posterior) disruptions, directly related to the structural and functional integrity of motor networks, and traceable beyond canonical movement disorders.
AB - Built on neurodegenerative lesions models, the disrupted motor grounding hypothesis (DMGH) posits that motor-system alterations selectively impair action comprehension. However, major doubts remain concerning the dissociability, neural signatures, and etiological generalizability of such deficits. Few studies have compared action-concept outcomes between disorders affecting and sparing motor circuitry, and none has examined their multimodal network predictors via data-driven approaches. Here, we first assessed action- and object-concept processing in patients with frontal lobe epilepsy (FLE), patients with posterior cortex epilepsy (PCE), and healthy controls. Then, we examined structural and functional network signatures via diffusion tensor imaging and resting-state connectivity measures. Finally, we used these measures to predict behavioral performance with an XGBoost machine learning regression algorithm. Relative to controls, FLE (but not PCE) patients exhibited selective action-concept deficits together with structural and functional abnormalities along motor networks. The XGBoost model reached a significantly large effect size only for action-concept outcomes in FLE, mainly predicted by structural (cortico-spinal tract, anterior thalamic radiation, uncinate fasciculus) and functional (M1-parietal/supramarginal connectivity) motor networks. These results extend the DMGH, suggesting that action-concept deficits are dissociable markers of frontal/motor (relative to posterior) disruptions, directly related to the structural and functional integrity of motor networks, and traceable beyond canonical movement disorders.
KW - Action semantics
KW - Diffusion tensor imaging
KW - Frontal lobe epilepsy
KW - Functional connectivity
KW - Machine learning
UR - http://www.scopus.com/inward/record.url?scp=85116853723&partnerID=8YFLogxK
U2 - 10.1016/j.cortex.2021.08.003
DO - 10.1016/j.cortex.2021.08.003
M3 - Article
C2 - 34637999
AN - SCOPUS:85116853723
SN - 0010-9452
VL - 144
SP - 43
EP - 55
JO - Cortex
JF - Cortex
ER -