Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland.
Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
Commun Biol. 2024 Sep 11;7(1):1120. doi: 10.1038/s42003-024-06842-x.
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.
幻觉可发生于健康人群，是许多神经精神疾病中具有临床相关性和常见症状的表现，并且在神经退行性疾病患者中，幻觉已被证明可标志疾病进展，而抗精神病药物治疗在这些患者中仍然具有挑战性。在这里，我们将能够诱发临床相关幻觉的磁共振机器人与实时 fMRI 神经反馈（fMRI-NF）相结合，以训练健康个体上调与机器人诱发幻觉相关的额顶叶脑网络。在三天的时间里，参与者学会了调节该网络的出现和向其转变的概率，从而在训练后提高了对诱发幻觉的敏感性。此外，在 fMRI-NF 训练中变得敏感并取得成功的参与者，在训练后表现出持续且特定的神经变化，其特征在于诱导期间幻觉网络的出现增加，以及匹配的对照条件下幻觉网络的出现减少。这些数据表明 fMRI-NF 可调节特定的幻觉网络动力学，并凸显了 fMRI-NF 作为神经退行性疾病和精神分裂症的新型抗精神病治疗方法的潜力。
