Imperatori Claudio, Allegrini Giorgia, Lo Presti Aurelia, Carbone Giuseppe A, Adenzato Mauro, Farina Benedetto, Ardito Rita B
Experimental and Applied Psychology Laboratory, Department of Human Sciences, European University of Rome, Rome, Italy.
Department of Psychology, University of Turin, Turin, Italy.
J Neural Transm (Vienna). 2025 May;132(5):731-741. doi: 10.1007/s00702-025-02894-3. Epub 2025 Feb 15.
Anhedonia is a core transnosographic symptom in several neuropsychiatric disorders. Recently, the Triple Network (TN) model has been proposed as a useful neurophysiological paradigm for conceptualizing anhedonia, providing new insights to clinicians and researchers. Despite this, the relationship between the functional dynamics of TN and the severity of anhedonia has been relatively understudied in non-clinical samples, especially in the resting state (RS) condition. Therefore, in the current study, we investigated this relationship using electroencephalography (EEG) functional connectivity. Eighty-two participants (36 males; mean age: 24.28 ± 7.35 years) underwent RS EEG recording with eyes-closed and completed the Beck Depression Inventory-derived 4-item anhedonia scale (BDI-Anh4) and the Brief Symptoms Inventory (BSI). EEG data on functional connectivity were analyzed using the exact low-resolution electromagnetic tomography (eLORETA). A significant positive correlation was observed between the BDI-Anh4 total score and salience-default mode network connectivity in the beta frequency band (r = 0.409; p = 0.010). The results of the hierarchical linear regression analysis also showed that this connectivity pattern was positively and independently associated (β = 0.358; p < 0.001) with the BDI-Anh4 total score and explained an additional 11% of the anhedonia variability. The association between anhedonia severity and increased salience-default mode network synchronization detected in the current study may reflect difficulty disengaging from internal/self-related mental contents, which consequently impairs the processing of other stimuli, including rewarding stimuli.
快感缺失是几种神经精神疾病的核心跨诊断症状。最近，三重网络（TN）模型被提出作为一种有用的神经生理学范式来概念化快感缺失，为临床医生和研究人员提供了新的见解。尽管如此，在非临床样本中，尤其是在静息状态（RS）条件下，TN的功能动力学与快感缺失严重程度之间的关系相对较少受到研究。因此，在当前的研究中，我们使用脑电图（EEG）功能连接性来研究这种关系。82名参与者（36名男性；平均年龄：24.28±7.35岁）进行了闭眼RS EEG记录，并完成了贝克抑郁量表衍生的4项快感缺失量表（BDI-Anh4）和简明症状量表（BSI）。使用精确低分辨率电磁断层扫描（eLORETA）分析功能连接性的EEG数据。在β频段，观察到BDI-Anh4总分与突显-默认模式网络连接性之间存在显著正相关（r = 0.409；p = 0.010）。分层线性回归分析结果还表明，这种连接模式与BDI-Anh4总分呈正相关且独立相关（β = 0.358；p < 0.001），并解释了快感缺失变异性的另外11%。在当前研究中检测到的快感缺失严重程度与突显-默认模式网络同步增加之间的关联可能反映了难以从内部/自我相关的心理内容中脱离出来，从而损害了对包括奖励性刺激在内的其他刺激的处理。
