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Cometa A, Battaglini C, Artoni F, Greco M, Frank R, Repetto C, Bottoni F, Cappa SF, Micera S, Ricciardi E, Moro A. Brain and grammar: revealing electrophysiological basic structures with competing statistical models. Cereb Cortex 2024; 34:bhae317. [PMID: 39098819 DOI: 10.1093/cercor/bhae317] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Revised: 07/08/2024] [Accepted: 07/24/2024] [Indexed: 08/06/2024] Open
Abstract
Acoustic, lexical, and syntactic information are simultaneously processed in the brain requiring complex strategies to distinguish their electrophysiological activity. Capitalizing on previous works that factor out acoustic information, we could concentrate on the lexical and syntactic contribution to language processing by testing competing statistical models. We exploited electroencephalographic recordings and compared different surprisal models selectively involving lexical information, part of speech, or syntactic structures in various combinations. Electroencephalographic responses were recorded in 32 participants during listening to affirmative active declarative sentences. We compared the activation corresponding to basic syntactic structures, such as noun phrases vs. verb phrases. Lexical and syntactic processing activates different frequency bands, partially different time windows, and different networks. Moreover, surprisal models based on part of speech inventory only do not explain well the electrophysiological data, while those including syntactic information do. By disentangling acoustic, lexical, and syntactic information, we demonstrated differential brain sensitivity to syntactic information. These results confirm and extend previous measures obtained with intracranial recordings, supporting our hypothesis that syntactic structures are crucial in neural language processing. This study provides a detailed understanding of how the brain processes syntactic information, highlighting the importance of syntactic surprisal in shaping neural responses during language comprehension.
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Affiliation(s)
- Andrea Cometa
- MoMiLab, IMT School for Advanced Studies Lucca, Piazza S.Francesco, 19, Lucca 55100, Italy
- The BioRobotics Institute and Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Viale Rinaldo Piaggio 34, Pontedera 56025, Italy
- Cognitive Neuroscience (ICoN) Center, University School for Advanced Studies IUSS, Piazza Vittoria 15, Pavia 27100, Italy
| | - Chiara Battaglini
- Neurolinguistics and Experimental Pragmatics (NEP) Lab, University School for Advanced Studies IUSS Pavia, Piazza della Vittoria 15, Pavia 27100, Italy
| | - Fiorenzo Artoni
- Department of Clinical Neurosciences, Faculty of Medicine, University of Geneva, 1, rue Michel-Servet, Genéve 1211, Switzerland
| | - Matteo Greco
- Cognitive Neuroscience (ICoN) Center, University School for Advanced Studies IUSS, Piazza Vittoria 15, Pavia 27100, Italy
| | - Robert Frank
- Department of Linguistics, Yale University, 370 Temple St, New Haven, CT 06511, United States
| | - Claudia Repetto
- Department of Psychology, Università Cattolica del Sacro Cuore, Largo A. Gemelli 1, Milan 20123, Italy
| | - Franco Bottoni
- Istituto Clinico Humanitas, IRCCS, Via Alessandro Manzoni 56, Rozzano 20089, Italy
| | - Stefano F Cappa
- Cognitive Neuroscience (ICoN) Center, University School for Advanced Studies IUSS, Piazza Vittoria 15, Pavia 27100, Italy
- Dementia Research Center, IRCCS Mondino Foundation National Institute of Neurology, Via Mondino 2, Pavia 27100, Italy
| | - Silvestro Micera
- The BioRobotics Institute and Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Viale Rinaldo Piaggio 34, Pontedera 56025, Italy
- Bertarelli Foundation Chair in Translational NeuroEngineering, Center for Neuroprosthetics and School of Engineering, Ecole Polytechnique Federale de Lausanne, Campus Biotech, Chemin des Mines 9, Geneva, GE CH 1202, Switzerland
| | - Emiliano Ricciardi
- MoMiLab, IMT School for Advanced Studies Lucca, Piazza S.Francesco, 19, Lucca 55100, Italy
| | - Andrea Moro
- Cognitive Neuroscience (ICoN) Center, University School for Advanced Studies IUSS, Piazza Vittoria 15, Pavia 27100, Italy
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Silfwerbrand L, Koike Y, Nyström P, Gingnell M. Directed causal effect with PCMCI in hyperscanning EEG time series. Front Neurosci 2024; 18:1305918. [PMID: 38686325 PMCID: PMC11057377 DOI: 10.3389/fnins.2024.1305918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Accepted: 04/03/2024] [Indexed: 05/02/2024] Open
Abstract
Social activities are likely to cause effects or reactivity in the brains of the people involved in collaborative social situations. This study assesses a new method, Tigramite, for time domain analysis of directed causality between the prefrontal cortex (PFC) of persons in such situations. An experimental situation using hyperscanning EEG was applied while individuals led and followed each other in finger-tapping rhythms. This structured task has a long duration and a high likelihood of inter-brain causal reactions in the prefrontal cortices. Tigramite is a graph-based causal discovery method to identify directed causal relationships in observational time series. Tigramite was used to analyze directed causal connections within and between the PFC. Significantly directed causality within and between brains could be detected during the social interactions. This is the first empirical evidence the Tigramite can reveal inter- and intra-brain-directed causal effects in hyperscanning EEG time series. The findings are promising for further studies of causality in neural networks during social activities using Tigramite on EEG in the time domain.
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Affiliation(s)
- Lykke Silfwerbrand
- Department of Medical Sciences, Psychiatry, Akademiska Sjukhuset, Uppsala, Sweden
- Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, Japan
| | - Yasuharu Koike
- Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, Japan
| | - Pär Nyström
- Department of Psychology, Developmental Psychology, Uppsala University, Uppsala, Sweden
| | - Malin Gingnell
- Department of Medical Sciences, Psychiatry, Akademiska Sjukhuset, Uppsala, Sweden
- Department of Psychology, Division of Emotion Psychology, Uppsala University, Uppsala, Sweden
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Artoni F, Cometa A, Dalise S, Azzollini V, Micera S, Chisari C. Cortico-muscular connectivity is modulated by passive and active Lokomat-assisted Gait. Sci Rep 2023; 13:21618. [PMID: 38062035 PMCID: PMC10703891 DOI: 10.1038/s41598-023-48072-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 11/22/2023] [Indexed: 12/18/2023] Open
Abstract
The effects of robotic-assisted gait (RAG) training, besides conventional therapy, on neuroplasticity mechanisms and cortical integration in locomotion are still uncertain. To advance our knowledge on the matter, we determined the involvement of motor cortical areas in the control of muscle activity in healthy subjects, during RAG with Lokomat, both with maximal guidance force (100 GF-passive RAG) and without guidance force (0 GF-active RAG) as customary in rehabilitation treatments. We applied a novel cortico-muscular connectivity estimation procedure, based on Partial Directed Coherence, to jointly study source localized EEG and EMG activity during rest (standing) and active/passive RAG. We found greater cortico-cortical connectivity, with higher path length and tendency toward segregation during rest than in both RAG conditions, for all frequency bands except for delta. We also found higher cortico-muscular connectivity in distal muscles during swing (0 GF), and stance (100 GF), highlighting the importance of direct supraspinal control to maintain balance, even when gait is supported by a robotic exoskeleton. Source-localized connectivity shows that this control is driven mainly by the parietal and frontal lobes. The involvement of many cortical areas also in passive RAG (100 GF) justifies the use of the 100 GF RAG training for neurorehabilitation, with the aim of enhancing cortical-muscle connections and driving neural plasticity in neurological patients.
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Affiliation(s)
- Fiorenzo Artoni
- Department of Clinical Neurosciences, University of Genève, Faculty of Medicine, 1211, Geneva, Switzerland.
- Ago Neurotechnologies Sàrl, 1201, Geneva, Switzerland.
| | - Andrea Cometa
- The BioRobotics Institute and Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Viale Rinaldo Piaggio 34, 56025, Pontedera, Italy
- University School for Advanced Studies IUSS Pavia, 27100, Pavia, Italy
| | - Stefania Dalise
- Unit of Neurorehabilitation, Pisa University Hospital, Pisa, Italy
| | - Valentina Azzollini
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - Silvestro Micera
- The BioRobotics Institute and Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Viale Rinaldo Piaggio 34, 56025, Pontedera, Italy
- Translational Neural Engineering Laboratory (TNE), École Polytechnique Fédérale de Lausanne, Campus Biotech, Geneva, Switzerland
| | - Carmelo Chisari
- Unit of Neurorehabilitation, Pisa University Hospital, Pisa, Italy
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
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