Real-time fMRI neurofeedback modulates induced hallucinations and underlying brain mechanisms.
Herberto DhanisNicolas GninenkoElenor MorgenrothJevita PotheegadooGiulio RogniniNathan FaivreOlaf BlankeD Van De VillePublished in: Communications biology (2024)
Hallucinations can occur in the healthy population, are clinically relevant and frequent symptoms in many neuropsychiatric conditions, and have been shown to mark disease progression in patients with neurodegenerative disorders where antipsychotic treatment remains challenging. Here, we combine MR-robotics capable of inducing a clinically-relevant hallucination, with real-time fMRI neurofeedback (fMRI-NF) to train healthy individuals to up-regulate a fronto-parietal brain network associated with the robotically-induced hallucination. Over three days, participants learned to modulate occurrences of and transition probabilities to this network, leading to heightened sensitivity to induced hallucinations after training. Moreover, participants who became sensitive and succeeded in fMRI-NF training, showed sustained and specific neural changes after training, characterized by increased hallucination network occurrences during induction and decreased hallucination network occurrences during a matched control condition. These data demonstrate that fMRI-NF modulates specific hallucination network dynamics and highlights the potential of fMRI-NF as a novel antipsychotic treatment in neurodegenerative disorders and schizophrenia.
Keyphrases
- resting state
- functional connectivity
- signaling pathway
- lps induced
- high glucose
- diabetic rats
- oxidative stress
- pi k akt
- nuclear factor
- drug induced
- magnetic resonance
- inflammatory response
- virtual reality
- electronic health record
- network analysis
- machine learning
- depressive symptoms
- working memory
- multiple sclerosis
- cell proliferation
- white matter
- big data
- combination therapy
- smoking cessation
- artificial intelligence
- risk assessment
- high speed