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Lena Palaniyappan

Robarts Research Institute, University of Western Ontario, London, ON, Canada.

4 papers in the library · 53 citations · publishing 2023-2026

Papers

Syntactic complexity of spoken language in the diagnosis of schizophrenia: A probabilistic Bayes network model.

Schizophrenia research September 1, 2023 Angelica M Silva, Roberto Limongi, Michael Mackinley et al. 49 citations

Syntactic complexity, specifically the number of nominal subjects per clause in spoken language, declines in the six months following a first episode of psychosis among individuals who later receive a schizophrenia diagnosis. In a cohort of 26 first-episode psychosis patients and 12 healthy controls, automated analysis of speech samples from the Thought and Language Index interview showed that a 50% decrease in mean nominal subjects per clause after six months was explained by the presence of first-episode psychosis with 95.4% probability. Among those with psychosis, a 30% decrease predicted a schizophrenia diagnosis with 95% probability. This longitudinal decline distinguishes schizophrenia from other psychotic disorders.

Quantitative natural language processing markers of psychoactive drug effects: A pre-registered systematic review

Journal of Psychopharmacology February 16, 2025 Sachin Ahuja, Farida Zaher, Lena Palaniyappan 4 citations

A systematic review of studies using natural language processing to analyze speech and text after psychoactive drug use found that all studied substances—stimulants, MDMA, cannabis, ketamine, and psychedelics—alter language production. Emerging patterns include increased verbosity with stimulants, reduced lexicon with LSD, increased semantic proximity to emotional words with MDMA, increased positive sentiment with psilocybin, and altered speech acoustics with cannabis. Only one study provided externally validated support for identifying MDMA intoxication using NLP and machine learning. Meta-analysis was not possible due to heterogeneity and few studies. The authors call for standardized speech tasks and a shared language corpus to improve replicability.

Grounding psychosis research: why observable signs should anchor biological investigations.

Frontiers in psychiatry January 1, 2026 Lena Palaniyappan

Biological psychiatry struggles to find valid targets for mechanistic research because both diagnostic categories and individual symptoms are abstract symbols defined circularly within a closed interpretive system, creating a symbol grounding problem that blocks discovery of biomarkers. The author argues that progress requires separating ungrounded symptoms like delusions and hallucinations, which are co-constructed through personal and clinical interpretation, from grounded signs—directly observable features anchored in shared sensorimotor reality. A Minimal Grounding Set (MGS) can be recovered from common psychosis criteria, exemplified by disorganization and impoverishment. This MGS offers a privileged pathway for neuroscientific inquiry, with predictions that biological correlates will be most replicable for MGS, that MGS will serve as modular anchors in symptom networks, and that precision psychiatry programs depend on separating MGS from ungrounded symptoms.

Language and Psychosis: Tightening the Association.

Schizophrenia bulletin March 22, 2023 Eric J Tan, Iris E C Sommer, Lena Palaniyappan

This special issue examines the role of language in psychosis, exploring the connections between formal thought disorder and conceptual disorganization, along with speech and language markers and their neural underpinnings. It also discusses the use of computational methods to analyze language in psychosis and the potential of speech and language data for digital phenotyping in psychiatry.