Olfactory hallucinations without subsequent myoclonic activity have not been well characterized or understood. Herein we describe, in a retrospective study, two major forms of olfactory hallucinations labeled phantosmias: one, unirhinal, the other, birhinal. To describe these disorders we performed several procedures to elucidate similarities and differences between these processes. From 1272, patients evaluated for taste and smell dysfunction at The Taste and Smell Clinic, Washington, DC with clinical history, neurological and otolaryngological examinations, evaluations of taste and smell function, EEG and neuroradiological studies 40 exhibited cyclic unirhinal phantosmia (CUP) usually without hyposmia whereas 88 exhibited non-cyclic birhinal phantosmia with associated symptomology (BPAS) with hyposmia. Patients with CUP developed phantosmia spontaneously or after laughing, coughing or shouting initially with spontaneous inhibition and subsequently with Valsalva maneuvers, sleep or nasal water inhalation; they had frequent EEG changes usually ipsilateral sharp waves. Patients with BPAS developed phantosmia secondary to several clinical events usually after hyposmia onset with few EEG changes; their phantosmia could not be initiated or inhibited by any physiological maneuver. CUP is uncommonly encountered and represents a newly defined clinical syndrome. BPAS is commonly encountered, has been observed previously but has not been clearly defined. Mechanisms responsible for phantosmia in each group were related to decreased gamma-aminobutyric acid (GABA) activity in specific brain regions. Treatment which activated brain GABA inhibited phantosmia in both groups.
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http://dx.doi.org/10.3390/brainsci3041483 | DOI Listing |
J ECT
January 2025
Department of Psychiatry, Central Institute of Psychiatry, Kanke, Ranchi, Jharkhand, India.
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RISE-Health, Nursing School of Porto, 4200-450 Porto, Portugal.
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January 2025
Department of Applied Bioengineering, Graduate School of Convergence Science and Technology, Seoul National University, Seoul 08826, Republic of Korea.
Recent advancements in deep learning have significantly improved medical image segmentation. However, the generalization performance and potential risks of data-driven models remain insufficiently validated. Specifically, unrealistic segmentation predictions deviating from actual anatomical structures, known as a Seg-Hallucination, often occur in deep learning-based models.
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June 2025
School of Social Sciences, University of Tasmania, Tasmania 7005, Australia.
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Early Psychosis: Interventions and Clinical-Detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
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