Speech Graphs Provide a Quantitative Measure of Thought Disorder in Psychosis
Open accessAbstract
BACKGROUND: Psychosis has various causes, including mania and schizophrenia. Since the differential diagnosis of psychosis is exclusively based on subjective assessments of oral interviews with patients, an objective quantification of the speech disturbances that characterize mania and schizophrenia is in order. In principle, such quantification could be achieved by the analysis of speech graphs. A graph represents a network with nodes connected by edges; in speech graphs, nodes correspond to words and edges correspond to semantic and grammatical relationships. METHODOLOGY/PRINCIPAL FINDINGS: To quantify speech differences related to psychosis, interviews with schizophrenics, manics and normal subjects were recorded and represented as graphs. Manics scored significantly higher than schizophrenics in ten graph measures. Psychopathological symptoms such as logorrhea, poor speech, and flight of thoughts were grasped by the analysis even when verbosity differences were discounted. Binary classifiers based on speech graph measures sorted schizophrenics from manics with up to 93.8% of sensitivity and 93.7% of specificity. In contrast, sorting based on the scores of two standard psychiatric scales (BPRS and PANSS) reached only 62.5% of sensitivity and specificity. CONCLUSIONS/SIGNIFICANCE: The results demonstrate that alterations of the thought process manifested in the speech of psychotic patients can be objectively measured using graph-theoretical tools, developed to capture specific features of the normal and dysfunctional flow of thought, such as divergence and recurrence. The quantitative analysis of speech graphs is not redundant with standard psychometric scales but rather complementary, as it yields a very accurate sorting of schizophrenics and manics. Overall, the results point to automated psychiatric diagnosis based not on what is said, but on how it is said.
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Iter et al. were unable to convincingly separate clinical and control participants using the tangentiality model of Elvevåg et al. and the incoherence model of Bedi et al.
“They noted that when using the tangentiality model of semantic coherence (i.e. regression of the coherence over time with the sliding window) of Elvevåg et al. [25] and the incoherence model of semantic coherence of Bedi et al. [16], they were unable to convincingly separate their clinical and control participants based on language analysis.”
From A Review of Automated Speech and Language Features for Assessment of Cognitive and Thought Disorders (2020) · cites this paper as [16]
In Bedi et al.'s study, the most predictive language features were the minimum coherence between consecutive phrases and the frequency of determiners normalized by sentence length.
“The language features with the best predictive power in the classifier were the minimum coherence between consecutive phrases for each participant (maximum discontinuity) and the frequency of use of determiners (normalized by sentence length).”
From A Review of Automated Speech and Language Features for Assessment of Cognitive and Thought Disorders (2020) · cites this paper as [16]
Bedi et al.'s initial study had only 34 participants total, including 5 CHR+ participants, and was intended as a proof-of-principle exploration.
“This initial study only had 34 participants total (only 5 CHR+ participants) and was intended as a proof-of-principle exploration.”
From A Review of Automated Speech and Language Features for Assessment of Cognitive and Thought Disorders (2020) · cites this paper as [16]
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Cites
A Coefficient of Agreement for Nominal Scales
Cohen, J. (1960) · Educational and Psychological Measurement · doi:10.1177/001316446002000104 · Cited by 42,398 · see citing works
(2003) · Journal of Machine Learning Research · doi:10.5555/944919.944937 · Cited by 32,337 · see citing works
An introduction to ROC analysis
Fawcett, T. (2006) · Pattern Recognition Letters · doi:10.1016/j.patrec.2005.10.010 · Cited by 21,879 · see citing works
The Positive and Negative Syndrome Scale (PANSS) for schizophrenia.
Kay, S. R., Fiszbein, A., & Opler, L. A. (1987) · Schizophrenia Bulletin · doi:10.1093/schbul/13.2.261 · Cited by 21,378 · see citing works
Seel, N. M. (2012) · Springer eBooks · doi:10.1007/978-1-4419-1428-6_5195 · Cited by 19,525 · see citing works
The WEKA data mining software: an update
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., & Witten, I. H. (2009) · ACM SIGKDD Explorations Newsletter · doi:10.1145/1656274.1656278 · Cited by 17,750 · see citing works
Blei, D. M., Ng, A. Y., & Jordan, M. I. (2002) · The MIT Press eBooks · doi:10.7551/mitpress/1120.003.0082 · Cited by 12,649 · see citing works
Complex brain networks: graph theoretical analysis of structural and functional systems
Bullmore, E., & Sporns, O. (2009) · Nature Reviews Neuroscience · doi:10.1038/nrn2575 · Cited by 11,820 · see citing works
I.—COMPUTING MACHINERY AND INTELLIGENCE
TURING, A. M. (1950) · Mind · doi:10.1093/mind/lix.236.433 · Cited by 10,290 · see citing works
(2006) · Springer eBooks · Cited by 8,123 · see citing works
Russell, E. L., Chiang, L. H., & Braatz, R. D. (2000) · Advances in industrial control · doi:10.1007/978-1-4471-0409-4_3 · Cited by 7,938 · see citing works
Computing Machinery and Intelligence (1950)
Turing, A. M. (2004) · doi:10.1093/oso/9780198250791.003.0017 · Cited by 6,120 · see citing works
Supervised Machine Learning: A Review of Classification Techniques
Kotsiantis, S. B. (2007) · Informatica · Cited by 4,192 · see citing works
Bollobás, B. (1998) · Graduate texts in mathematics · doi:10.1007/978-1-4612-0619-4 · Cited by 3,863 · see citing works
Comprehensive Textbook of Psychiatry
Freedman, A. M., & Kaplan, H. I. (1967) · The American Journal of the Medical Sciences · doi:10.1097/00000441-196712000-00052 · Cited by 3,825 · see citing works
Estimating Continuous Distributions in Bayesian ClassifiersPreprint
John, G. H., & Pat Langley, B. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1302.4964 · Cited by 2,914 · see citing works
Duda, R. O., Hart, P. E. 1., & Stork, D. G. C. 2. /. J. (2001) · Cited by 2,469 · see citing works
Insel, T. R. (2010) · Nature · doi:10.1038/nature09552 · Cited by 1,783 · see citing works
The Structured Clinical Interview for DSM-III-R (SCID)
Williams, J. B. W. (1992) · Archives of General Psychiatry · doi:10.1001/archpsyc.1992.01820080038006 · Cited by 1,627 · see citing works
Kaplan & Sadock's Comprehensive Textbook of Psychiatry
Sadock, B. J., & Sadock, V. A. (2000) · Cited by 1,523 · see citing works
The small world of human language
Ferrer‐i‐Cancho, R., & Solé, R. V. (2001) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2001.1800 · Cited by 1,050 · see citing works
Book Review: Pattern Recognition and Machine Learning
Nasrabadi, N. M. (2007) · Journal of Electronic Imaging · doi:10.1117/1.2819119 · Cited by 636 · see citing works
Revisiting the Foundations of Network Analysis
Butts, C. T. (2009) · Science · doi:10.1126/science.1171022 · Cited by 544 · see citing works
Bech, P., Kastrup, M., & Rafaelsen, O. J. (1986) · PubMed · Cited by 466 · see citing works
High interrater reliability for the Structured Clinical Interview for DSM-III-R Axis I (SCID-I)
Skre, I., Onstad, S., Torgersen, S., & Kringlen, E. (1991) · Acta Psychiatrica Scandinavica · doi:10.1111/j.1600-0447.1991.tb03123.x · Cited by 353 · see citing works
Global organization of the Wordnet lexicon
Sigman, M., & Cecchi, G. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.022341799 · Cited by 281 · see citing works
Self-citationMoretti, F. (2011) · New Left Review · doi:10.64590/vko · Cited by 180 · see citing works
Graph theoretic modeling of large-scale semantic networks
Bales, M. E., & Johnson, S. B. (2005) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2005.10.007 · Cited by 91 · see citing works
Thesaurus as a complex network
Holanda, A. D. J., Pisa, I. T., Kinouchi, O., Martinêz, A. S., & Ruiz, E. E. S. (2004) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2004.06.025 · Cited by 63 · see citing works
Self-citationIn retrospect: The five lives of the psychiatry manual
GRINKER, R. R. (2010) · Nature · doi:10.1038/468168a · Cited by 63 · see citing works
Ordered cyclic motifs contribute to dynamic stability in biological and engineered networks
Ma’ayan, A., Cecchi, G., Wagner, J., Rao, A. R., Iyengar, R., & Stolovitzky, G. A. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0805344105 · Cited by 51 · see citing works
Self-citationUsing Computational Patients to Evaluate Illness Mechanisms in Schizophrenia
Hoffman, R. E., Grasemann, U., Gueorguieva, R. V., Quinlan, D. M., Lane, D., & Miikkulainen, R. (2011) · Biological Psychiatry · doi:10.1016/j.biopsych.2010.12.036 · Cited by 42 · see citing works
A Comparison of Induction Algorithms for Selective and non-Selective Bayesian Classifiers
Singh, M., & Provan, G. M. (1995) · Elsevier eBooks · doi:10.1016/b978-1-55860-377-6.50068-2 · Cited by 32 · see citing works
Scale-invariant transition probabilities in free word association trajectories
Costa, M. E. (2009) · Frontiers in Integrative Neuroscience · doi:10.3389/neuro.07.019.2009 · Cited by 16 · see citing works
Flagged first, then by citations
1 of the 35 references couldn’t be matched to a known paper.
Research works printed but not linked: 1
- [2]First MH Spitzer RL Gibbon M Williams J 1990 Structured Clinical Interview for DSM-IV Axis I Disorders – Research Version, Patient Edition (SCID-I/P) New York Biometrics Research, New York State Psychiatric Institute
Cited by
Sorted by citations
Automated analysis of free speech predicts psychosis onset in high-risk youths
Bedi, G., Carrillo, F., Cecchi, G. A., Slezak, D. F., Sigman, M., Mota, N. B., Ribeiro, S., Javitt, D. C., Copelli, M., & Corcoran, C. M. (2015) · npj Schizophrenia · doi:10.1038/npjschz.2015.30 · Cited by 673 · see citing works
Self-citationPrediction of psychosis across protocols and risk cohorts using automated language analysis
Corcoran, C. M., Carrillo, F., Slezak, D. F., Bedi, G., Klim, C. C., Javitt, D. C., Bearden, C. E., & Cecchi, G. (2018) · World Psychiatry · doi:10.1002/wps.20491 · Cited by 381 · see citing works
Self-citationWang, X., & Krystal, J. H. (2014) · Neuron · doi:10.1016/j.neuron.2014.10.018 · Cited by 309 · see citing works
Rezaii, N., Walker, E. F., & Wolff, P. (2019) · Schizophrenia · doi:10.1038/s41537-019-0077-9 · Cited by 203 · see citing works
Language as a biomarker for psychosis: a natural language processing approach
Corcoran, C. M., Mittal, V. A., Bearden, C. E., E. Gur, R., Hitczenko, K., Bilgrami, Z., Savic, A., Cecchi, G. A., & Wolff, P. (2020) · Schizophrenia Research · doi:10.1016/j.schres.2020.04.032 · Cited by 186 · see citing works
Self-citationMota, N. B., Copelli, M., & Ribeiro, S. (2017) · npj Schizophrenia · doi:10.1038/s41537-017-0019-3 · Cited by 157 · see citing works
Self-citationEvaluation of Speech-Based Digital Biomarkers: Review and Recommendations
Robin, J., Harrison, J., Kaufman, L. D., Rudzicz, F., Simpson, W. S., & Yancheva, M. (2020) · Digital Biomarkers · doi:10.1159/000510820 · Cited by 171 · see citing works
Graph analysis of dream reports is especially informative about psychosis
Mota, N. B., Furtado, R., Maia, P., Copelli, M., & Ribeiro, S. T. G. (2014) · Scientific Reports · doi:10.1038/srep03691 · Cited by 157 · see citing works
Self-citationCorcoran, C. M., & Cecchi, G. (2020) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2020.06.004 · Cited by 148 · see citing works
Self-citationGarcía, A. M., Carrillo, F., Orozco-Arroyave, J. R., Trujillo, N., Vargas Bonilla, J. F., Fittipaldi, S., Adolfi, F., Nöth, E., Sigman, M., Fernández Slezak, D., et al. (2016) · Brain and Language · doi:10.1016/j.bandl.2016.07.008 · Cited by 144 · see citing works
Self-citationKenett, Y. N., Beaty, R. E., Silvia, P. J., Anaki, D., & Faust, M. (2016) · Psychology of Aesthetics Creativity and the Arts · doi:10.1037/aca0000056 · Cited by 145 · see citing works
Tang, S. X., Kriz, R., Cho, S., Park, S. J., Harowitz, J., Gur, R. E., Bhati, M. T., Wolf, D. H., Sedoc, J., & Liberman, M. (2021) · Schizophrenia · doi:10.1038/s41537-021-00154-3 · Cited by 133 · see citing works
Balagopalan, A., Eyre, B., Rudzicz, F., & Novikova, J. (2020) · Interspeech (USB) · doi:10.21437/interspeech.2020-2557 · Cited by 144 · see citing works
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Kenett, Y. N., Wechsler-Kashi, D., Kenett, D. Y., Schwartz, R. G., Ben‐Jacob, E., & Faust, M. (2013) · Frontiers in Psychology · doi:10.3389/fpsyg.2013.00543 · Cited by 131 · see citing works
Predicting future mental illness from social media: A big-data approach
Thorstad, R., & Wolff, P. (2019) · Behavior Research Methods · doi:10.3758/s13428-019-01235-z · Cited by 119 · see citing works
Anomalies in language as a biomarker for schizophrenia
de Boer, J. N., Brederoo, S., Voppel, A., & Sommer, I. E. (2020) · Current Opinion in Psychiatry · doi:10.1097/yco.0000000000000595 · Cited by 117 · see citing works
Bertola, L., Mota, N. B., Copelli, M., Rivero, T., Diniz, B. S., Romano-Silva, M. A., Ribeiro, S., & Malloy-Diniz, L. F. (2014) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2014.00185 · Cited by 107 · see citing works
Self-citationBirnbaum, M. L., Ernala, S. K., Rizvi, A. F., Arenare, E., Meter, A. V., Choudhury, M. D., & Kane, J. M. (2019) · Schizophrenia · doi:10.1038/s41537-019-0085-9 · Cited by 109 · see citing works
Comparing Pre-trained and Feature-Based Models for Prediction of Alzheimer's Disease Based on Speech
Balagopalan, A., Eyre, B., Robin, J., Rudzicz, F., & Novikova, J. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.635945 · Cited by 97 · see citing works
A Review of Automated Speech and Language Features for Assessment of Cognitive and Thought Disorders
Voleti, R., Liss, J. M., & Berisha, V. (2020) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2019.2952087 · Cited by 96 · see citing works
Automated computerized analysis of speech in psychiatric disorders
Cohen, A. S., & Elvevåg, B. (2014) · Current Opinion in Psychiatry · doi:10.1097/yco.0000000000000056 · Cited by 93 · see citing works
Smartphones and the Neuroscience of Mental Health
Gillan, C. M., & Rutledge, R. B. (2021) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-101220-014053 · Cited by 84 · see citing works
A Window into the Intoxicated Mind? Speech as an Index of Psychoactive Drug Effects
Bedi, G., Cecchi, G., Slezak, D. F., Carrillo, F., Sigman, M., & de Wit, H. (2014) · Neuropsychopharmacology · doi:10.1038/npp.2014.80 · Cited by 88 · see citing works
Self-citationNatural Language Processing markers in first episode psychosis and people at clinical high-risk
Morgan, S. E., Diederen, K. M. J., Vértes, P. E., Ip, S., Wang, B., Thompson, B., Demjaha, A., Micheli, A. D., Oliver, D., Liakata, M., et al. (2021) · Translational Psychiatry · doi:10.1038/s41398-021-01722-y · Cited by 86 · see citing works
Hitczenko, K., Mittal, V. A., & Goldrick, M. (2020) · Schizophrenia Bulletin · doi:10.1093/schbul/sbaa141 · Cited by 81 · see citing works
Quantified language connectedness in schizophrenia-spectrum disorders
Voppel, A., de Boer, J. N., Brederoo, S., Schnack, H. G., & Sommer, I. E. (2021) · Psychiatry Research · doi:10.1016/j.psychres.2021.114130 · Cited by 81 · see citing works
Faust, M., & Kenett, Y. N. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00511 · Cited by 80 · see citing works
Bari, A., Mikell, C. B., Abosch, A., Ben‐Haim, S., Buchanan, R. J., Burton, A. W., Carcieri, S., Cosgrove, G. R., D’Haese, P.-F., Daskalakis, Z. J., et al. (2018) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp-2017-317082 · Cited by 70 · see citing works
Mota, N. B., Weissheimer, J., Ribeiro, M., de Paiva, M. M. M., Avilla-Souza, J., Simabucuru, G., Chaves, M. F., Cecchi, L., de Oliveira, J. B. C., Cecchi, G., et al. (2020) · PLoS ONE · doi:10.1371/journal.pone.0242903 · Cited by 74 · see citing works
Self-citationSpeech structure links the neural and socio-behavioural correlates of psychotic disorders
Palaniyappan, L. K., Mota, N. B., Oowise, S., Balain, V., Copelli, M., Ribeiro, S. T. G., & Liddle, P. F. (2018) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2018.07.007 · Cited by 69 · see citing works
Self-citationLower speech connectedness linked to incidence of psychosis in people at clinical high risk
Spencer, T. J., Thompson, B., Oliver, D., Diederen, K. M. J., Demjaha, A., Weinstein, S., Morgan, S. E., Day, F., Valmaggia, L., Rutigliano, G., et al. (2020) · Schizophrenia Research · doi:10.1016/j.schres.2020.09.002 · Cited by 66 · see citing works
Self-citationLarge-scale Network Representations of Semantics in the Mental Lexicon
Deyne, S. D., Kenett, Y. N., Anaki, D., & Faust, M. (2016) · Psychology Press eBooks · doi:10.4324/9781315413570-18 · Cited by 56 · see citing works
Alonso-Sánchez, M. F., Ford, S. D., Mackinley, M., Silva, A., Limongi, R., & Palaniyappan, L. K. (2022) · Schizophrenia · doi:10.1038/s41537-022-00246-8 · Cited by 55 · see citing works
Olhar e ler: verbo-visualidade em perspectiva dialógica
Brait, B. (2013) · Bakhtiniana Revista de Estudos do Discurso · doi:10.1590/s2176-45732013000200004 · Cited by 55 · see citing works
Linguistic findings in persons with schizophrenia—a review of the current literature
Ehlen, F., Montag, C., Leopold, K., & Heinz, A. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1287706 · Cited by 58 · see citing works
Bilgrami, Z. R., Sarac, C., Srivastava, A., Herrera, S. N., Azis, M., Haas, S. S., Shaik, R., Parvaz, M. A., Mittal, V. A., Cecchi, G., et al. (2022) · Schizophrenia Research · doi:10.1016/j.schres.2022.01.019 · Cited by 47 · see citing works
Self-citationSemantic coherence markers: The contribution of perplexity metrics
Colla, D., Delsanto, M., Agosto, M., Vitiello, B., & Radicioni, D. P. (2022) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2022.102393 · Cited by 48 · see citing works
Graph analysis of semantic word association among children, adults, and the elderly
Zortéa, M., Menegola, B., Villavicencio, A., & de Salles, J. F. (2014) · Psicologia Reflexão e Crítica · doi:10.1590/s0102-79722014000100011 · Cited by 48 · see citing works
Silva, A., Limongi, R., Mackinley, M., Ford, S. D., Alonso-Sánchez, M. F., & Palaniyappan, L. K. (2022) · Schizophrenia Research · doi:10.1016/j.schres.2022.06.011 · Cited by 48 · see citing works
Birnbaum, M., Norel, R., Meter, A. V., Ali, A. F., Arenare, E., Eyigoz, E., Agurto, C., Germano, N., Kane, J., & Cecchi, G. (2020) · npj Schizophrenia · doi:10.1038/s41537-020-00125-0 · Cited by 44 · see citing works
Self-citationThe epilepsies: Complex challenges needing complex solutions
Tejada, J., Costa, K. M., Bertti, P., & Garcia‐Cairasco, N. (2012) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2012.09.029 · Cited by 46 · see citing works
Mota, N. B., Weissheimer, J., Madruga, B., Adamy, N., Bunge, S. A., Copelli, M., & Ribeiro, S. T. G. (2016) · Mind Brain and Education · doi:10.1111/mbe.12122 · Cited by 46 · see citing works
Self-citationKenett, Y. N., Gold, R., & Faust, M. (2015) · Language and Speech · doi:10.1177/0023830915589397 · Cited by 46 · see citing works
Eyigoz, E., Courson, M., Sedeño, L., Rogg, K., Orozco-Arroyave, J. R., Nöth, E., Skodda, S., Trujillo, N., Rodríguez, M., Rusz, J., et al. (2020) · Cortex · doi:10.1016/j.cortex.2020.08.020 · Cited by 44 · see citing works
Self-citationStructural differences between REM and non-REM dream reports assessed by graph analysis
Martin, J. M., Wainstein, D., Mota, N. B., Mota-Rolim, S. A., Araújo, J. F., Solms, M., & Ribeiro, S. T. G. (2020) · PLoS ONE · doi:10.1371/journal.pone.0228903 · Cited by 45 · see citing works
Self-citationAutomatic language analysis identifies and predicts schizophrenia in first-episode of psychosis
Figueroa-Barra, A. I., Aguila, D. D., Cerda, M., Gaspar, P. A., Terissi, L. D., Durán, M., & Valderrama, C. (2022) · Schizophrenia · doi:10.1038/s41537-022-00259-3 · Cited by 43 · see citing works
Pauselli, L., Halpern, B., Cleary, S. D., Ku, B. S., Covington, M. A., & Compton, M. T. (2018) · Psychiatry Research · doi:10.1016/j.psychres.2018.02.037 · Cited by 44 · see citing works
Word use in first-person accounts of schizophrenia
Fineberg, S. K., Deutsch‐Link, S., Ichinose, M. C., McGuinness, T., Bessette, A. J., Chung, C. K., & Corlett, P. R. (2014) · The British Journal of Psychiatry · doi:10.1192/bjp.bp.113.140046 · Cited by 42 · see citing works
Natural language processing in psychiatry: the promises and perils of a transformative approach
Rezaii, N., Wolff, P., & Price, B. H. (2022) · The British Journal of Psychiatry · doi:10.1192/bjp.2021.188 · Cited by 41 · see citing works
The maturation of speech structure in psychosis is resistant to formal education
Mota, N. B., Sigman, M., Cecchi, G., Copelli, M., & Ribeiro, S. T. G. (2018) · Schizophrenia · doi:10.1038/s41537-018-0067-3 · Cited by 42 · see citing works
Self-citationUsing machine learning of computerized vocal expression to measure blunted vocal affect and alogia
Cohen, A. S., Cox, C. R., Le, T. P., Cowan, T., Masucci, M. D., Strauss, G. P., & Kirkpatrick, B. W. (2020) · Schizophrenia · doi:10.1038/s41537-020-00115-2 · Cited by 39 · see citing works
Huang, Y.-J., Lin, Y.-T., Liu, C.-C., Lee, L.-E., Hung, S.-H., Lo, J.-K., & Fu, L.-C. (2022) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2022.3163777 · Cited by 44 · see citing works
Psychosis and the Control of Lucid Dreaming
Mota, N. B., Resende, A., Mota-Rolim, S. A., Copelli, M., & Ribeiro, S. T. G. (2016) · Frontiers in Psychology · doi:10.3389/fpsyg.2016.00294 · Cited by 39 · see citing works
Self-citationGutierrez, E., Cecchi, G., Corcoran, C. M., & Corlett, P. R. (2017) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/d17-1316 · Cited by 39 · see citing works
Self-citationSilva, A., Limongi, R., Mackinley, M., & Palaniyappan, L. K. (2021) · Schizophrenia Bulletin Open · doi:10.1093/schizbullopen/sgab010 · Cited by 41 · see citing works
Dalal, T. C., Liang, L., Silva, A. M., Mackinley, M., Voppel, A., & Palaniyappan, L. K. (2024) · Acta Psychiatrica Scandinavica · doi:10.1111/acps.13685 · Cited by 38 · see citing works
Elvevåg, B., Cohen, A. S., Wolters, M. K., Whalley, H. C., Gountouna, V., Kuznetsova, K. A., Watson, A. R., & Nicodemus, K. K. (2016) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32438 · Cited by 37 · see citing works
The entropic tongue: Disorganization of natural language under LSD
Sanz, C., Pallavicini, C., Carrillo, F., Zamberlán, F., Sigman, M., Mota, N. B., Copelli, M., Ribeiro, S. T. G., Nutt, D., Carhart-Harris, R. L., et al. (2020) · Consciousness and Cognition · doi:10.1016/j.concog.2020.103070 · Cited by 34 · see citing works
Self-citationSchneider, K. L., Leinweber, K., Jamalabadi, H., Teutenberg, L., Brosch, K., Pfarr, J., Thomas‐Odenthal, F., Usemann, P. L., Wroblewski, A., Straube, B., et al. (2023) · Schizophrenia · doi:10.1038/s41537-023-00359-8 · Cited by 34 · see citing works
Ratana, R., Sharifzadeh, H., Krishnan, J., & Pang, S. (2019) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2019.00659 · Cited by 34 · see citing works
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Diuk, C., Slezak, D. F., Raskovsky, I., Sigman, M., & Cecchi, G. (2012) · Frontiers in Integrative Neuroscience · doi:10.3389/fnint.2012.00080 · Cited by 33 · see citing works
Self-citationBambini, V., Frau, F., Bischetti, L., Cuoco, F., Bechi, M., Buonocore, M., Agostoni, G., Ferri, I., Sapienza, J., Martini, F., et al. (2022) · Schizophrenia · doi:10.1038/s41537-022-00306-z · Cited by 33 · see citing works
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Hitczenko, K., Cowan, H. R., Goldrick, M., & Mittal, V. A. (2021) · Schizophrenia Bulletin · doi:10.1093/schbul/sbab131 · Cited by 31 · see citing works
Birnbaum, M. L., Abrami, A., Heisig, S., Ali, A. F., Arenare, E., Agurto, C., Lu, N. Y., Kane, J. M., & Cecchi, G. (2022) · JMIR Mental Health · doi:10.2196/24699 · Cited by 31 · see citing works
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Elvevåg, B., Foltz, P. W., Rosenstein, M., Ferrer‐i‐Cancho, R., Deyne, S. D., Mizraji, E., & Cohen, A. S. (2017) · Schizophrenia Bulletin · doi:10.1093/schbul/sbx040 · Cited by 31 · see citing works
Morphological characteristics of spoken language in schizophrenia patients - an exploratory study.
Ziv, I., Baram, H., Bar, K., Zilberstein, V., Itzikobitz, S., Harel, E. V., & Dershowitz, N. (2021) · Scandinavian Journal of Psychology · doi:10.1111/sjop.12790 · Cited by 28 · see citing works
García, A. M., Johann, F., Echegoyen, R. E., Calcaterra, C., Riera, P., Belloli, L. M. L., & Carrillo, F. (2023) · Behavior Research Methods · doi:10.3758/s13428-023-02240-z · Cited by 29 · see citing works
Tang, S. X., Cong, Y., Nikzad, A. H., Mehta, A., Cho, S., Hänsel, K., Berretta, S. A., Dhar, A. A., Kane, J. M., & Malhotra, A. K. (2022) · Schizophrenia Research · doi:10.1016/j.schres.2022.06.012 · Cited by 29 · see citing works
DEPAC: a Corpus for Depression and Anxiety Detection from Speech
Tasnim, M., Ehghaghi, M., Diep, B., & Novikova, J. (2022) · Workshop on Computational Linguistics and Clinical Psychology (CLPsych) · doi:10.18653/v1/2022.clpsych-1.1 · Cited by 32 · see citing works
Syntactic Network Analysis in Schizophrenia-Spectrum Disorders
Ciampelli, S., de Boer, J. N., Voppel, A., Hernández, H. C., Brederoo, S., van Dellen, E., Mota, N. B., & Sommer, I. E. (2023) · Schizophrenia Bulletin · doi:10.1093/schbul/sbac194 · Cited by 28 · see citing works
Self-citationElce, V., Handjaras, G., & Bernardi, G. (2021) · Clocks & Sleep · doi:10.3390/clockssleep3030035 · Cited by 27 · see citing works
Applications of Speech Analysis in Psychiatry
Dikaios, K., Rempel, S., Dumpala, S. H., Oore, S., Kiefte, M., & Uher, R. (2023) · Harvard Review of Psychiatry · doi:10.1097/hrp.0000000000000356 · Cited by 28 · see citing works
Matton, K., McInnis, M. G., & Provost, E. M. (2019) · Interspeech (USB) · doi:10.21437/interspeech.2019-2698 · Cited by 27 · see citing works
Nikzad, A. H., Cong, Y., Berretta, S. A., Hänsel, K., Cho, S., Pradhan, S., Behbehani, L. M., DeSouza, D. D., Liberman, M., & Tang, S. X. (2022) · Schizophrenia · doi:10.1038/s41537-022-00263-7 · Cited by 26 · see citing works
Lundin, N. B., Hochheiser, J., Minor, K. S., Hetrick, W. P., & Lysaker, P. H. (2019) · Schizophrenia Research · doi:10.1016/j.schres.2019.11.032 · Cited by 25 · see citing works
Haas, S. S., Doucet, G. E., Garg, S., Herrera, S. N., Sarac, C., Bilgrami, Z. R., Shaik, R., & Corcoran, C. M. (2020) · European Psychiatry · doi:10.1192/j.eurpsy.2020.73 · Cited by 25 · see citing works
Semantic Speech Networks Linked to Formal Thought Disorder in Early Psychosis
Nettekoven, C., Diederen, K. M. J., Giles, O. T., Duncan, H., Stenson, I., Olah, J., Gibbs-Dean, T., Collier, N., Vértes, P. E., Spencer, T. J., et al. (2023) · Schizophrenia Bulletin · doi:10.1093/schbul/sbac056 · Cited by 25 · see citing works
Lavigne, K. M., Deng, J., Raucher‐Chéné, D., Hotte‐Meunier, A., Voyer, C., Sarraf, L., Lepage, M., & Sauvé, G. (2023) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2023.110894 · Cited by 27 · see citing works
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Alves, C. L., Toutain, T. G. L. D. O., Porto, J. A. M., Aguiar, P. D. C., de Sena, E. P., Rodrigues, F. A., Pineda, A. M., & Thielemann, C. (2023) · Journal of Neural Engineering · doi:10.1088/1741-2552/acf734 · Cited by 23 · see citing works
Arslan, B., Kizilay, E., Verim, B., Demirlek, C., Demir, M., Cesim, E., Eyuboglu, M. S., Ozbek, S. U., Süt, E., Yalınçetin, B., et al. (2024) · Journal of Affective Disorders · doi:10.1016/j.jad.2024.07.102 · Cited by 24 · see citing works
Quillivic, R., Gayraud, F., Auxéméry, Y., Vanni, L., Peschanski, D., Eustache, F., Dayan, J., & Mesmoudi, S. (2024) · Scientific Reports · doi:10.1038/s41598-024-61557-7 · Cited by 24 · see citing works
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Language Analytics for Assessment of Mental Health Status and Functional Competency
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Arslan, B., Kizilay, E., Verim, B., Demirlek, C., Dokuyan, Y., Turan, Y. E., Kucukakdag, A., Demir, M., Cesim, E., & Bora, E. (2024) · Schizophrenia Research · doi:10.1016/j.schres.2024.03.014 · Cited by 22 · see citing works
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Network analysis of narrative discourse and attention-deficit hyperactivity symptoms in adults
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Self-citationXu, W., Wang, W., Portanova, J., Chander, A., Campbell, A. T., Pakhomov, S., Ben‐Zeev, D., & Cohen, T. (2022) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2022.103998 · Cited by 21 · see citing works
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Gumus, M., DeSouza, D. D., Xu, M., Fidalgo, C., Simpson, W. S., & Robin, J. (2023) · Digital Health · doi:10.1177/20552076231180523 · Cited by 21 · see citing works
An investigation of Hebbian phase sequences as assembly graphs
Filho, D. A., Lopes‐dos‐Santos, V., de Vasconcelos, N. A. P., Miranda, J. G. V., Tort, A. B. L., & Ribeiro, S. T. G. (2014) · Frontiers in Neural Circuits · doi:10.3389/fncir.2014.00034 · Cited by 21 · see citing works
Self-citationComputing the structure of language for neuropsychiatric evaluation
Cecchi, G., Gurev, V., Heisig, S., Norel, R., Rish, I., & Schrecke, S. R. (2017) · IBM Journal of Research and Development · doi:10.1147/jrd.2017.2648478 · Cited by 19 · see citing works
Self-citationArgôlo, F. C., Magnavita, G. M., Mota, N. B., Ziebold, C., Mabunda, D., Pan, P. M., Zugman, A., Gadelha, A., Corcoran, C. M., & Bressan, R. A. (2020) · Brazilian Journal of Psychiatry · doi:10.1590/1516-4446-2019-0722 · Cited by 19 · see citing works
Self-citationAutomated analysis of speech as a marker of sub-clinical psychotic experiences
Olah, J., Spencer, T. J., Cummins, N., & Diederen, K. M. J. (2024) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2023.1265880 · Cited by 18 · see citing works
Mota, N. B., Fujii, R. C., Leite, L., Torres, A. R., Weissheimer, J., Bunge, S. A., Copelli, M., & Ribeiro, S. T. G. (2019) · Mind Brain and Education · doi:10.1111/mbe.12208 · Cited by 18 · see citing works
Self-citationAcoustic and prosodic information for home monitoring of bipolar disorder
Farrús, M., Codina, J., & Escudero, J. (2021) · Health Informatics Journal · doi:10.1177/1460458220972755 · Cited by 18 · see citing works
Decision Models and Technology Can Help Psychiatry Develop Biomarkers
Barron, D. S., Baker, J. T., Budde, K. S., Bzdok, D., Eickhoff, S. B., Friston, K. J., Fox, P. T., Geha, P., Heisig, S., Holmes, A. J., et al. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.706655 · Cited by 19 · see citing works
- Authors
- Mota, N. B., Vasconcelos, N. A. P., Lemos, N., Pieretti, A. C., Kinouchi, O., Cecchi, G. A., Copelli, M., & Ribeiro, S.
- Affiliations
- Universidade Federal do Rio Grande do Norte (BR)
- Universidade de São Paulo (BR)
- IBM Research - Thomas J. Watson Research Center (US)
- Universidade Federal de Pernambuco (BR)
- Corresponding author
- Ribeiro, Sidarta
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2012-04-09
- Volume
- 7
- Issue
- 4
- Pages
- e34928
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC3322168
- OpenAlex
- W2091298722
- Cited by
- 265
- References
- 35
- Citations by year
- 2026: 22 · 2025: 18 · 2024: 24 · 2023: 43 · 2022: 34 · 2021: 21 · 2020: 30 · 2019: 15 · 2018: 13 · 2017: 10 · 2016: 12 · 2015: 4 · 2014: 11 · 2013: 6 · 2012: 2
- FWCI
- 5.17
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Americanae (AECID Library) (publishedVersion, other-oa)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (publishedVersion, other-oa)
- Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Funders
- Governo Brasil
- Conselho Nacional de Desenvolvimento Científico e Tecnológico (481506/2007-1)
- Financiadora de Estudos e Projetos (01.06.1092.00)
- Universidade Federal do Rio Grande do Norte
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Social Sciences › Psychology › Social Psychology › Mental Health via Writing
- Keywords
- thought disorder, psychosis, schizophrenia, mania, differential diagnosis, graph theory, speech analysis, flight of ideas, automated psychiatric diagnosis, psychiatric symptoms
- MeSH terms
- Adult, Female, Humans, Male, Middle Aged, Psychiatric Status Rating Scales, Psychotic Disorders, Schizophrenia, Speech, Thinking, Young Adult
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