Pub Date : 2024-09-25DOI: 10.1016/j.pscychresns.2024.111907
Ruipeng Li, Yueqi Huang, Yanbin Wang, Chen Song, Xiaobo Lai
Mood disorders, particularly bipolar disorder (BD) and major depressive disorder (MDD), manifest changes in brain structure that can be detected using structural magnetic resonance imaging (MRI). Although structural MRI is a promising diagnostic tool, prevailing diagnostic criteria for BD and MDD are predominantly subjective, sometimes leading to misdiagnosis. This challenge is compounded by a limited understanding of the underlying causes of these disorders. In response, we present SE-ResNet, a Residual Network (ResNet)-based framework designed to discriminate between BD, MDD, and healthy controls (HC) using structural MRI data. Our approach extends the traditional Squeeze-and-Excitation (SE) layer by incorporating a dedicated branch for spatial attention map generation, equipped with soft-pooling, a 7 × 7 convolution, and a sigmoid function, intended to detect complex spatial patterns. The fusion of channel and spatial attention maps through element-wise addition aims to enhance the model's ability to discriminate features. Unlike conventional methods that use max-pooling for downsampling, our methodology employs soft-pooling, which aims to preserve a richer representation of input features and reduce data loss. When evaluated on a proprietary dataset comprising 303 subjects, the SE-ResNet achieved an accuracy of 85.8 %, a recall of 85.7 %, a precision of 85.9 %, and an F1 score of 85.8 %. These performance metrics suggest that the SE-ResNet framework has potential as a tool for detecting psychiatric disorders using structural MRI data.
{"title":"MRI-based deep learning for differentiating between bipolar and major depressive disorders.","authors":"Ruipeng Li, Yueqi Huang, Yanbin Wang, Chen Song, Xiaobo Lai","doi":"10.1016/j.pscychresns.2024.111907","DOIUrl":"https://doi.org/10.1016/j.pscychresns.2024.111907","url":null,"abstract":"<p><p>Mood disorders, particularly bipolar disorder (BD) and major depressive disorder (MDD), manifest changes in brain structure that can be detected using structural magnetic resonance imaging (MRI). Although structural MRI is a promising diagnostic tool, prevailing diagnostic criteria for BD and MDD are predominantly subjective, sometimes leading to misdiagnosis. This challenge is compounded by a limited understanding of the underlying causes of these disorders. In response, we present SE-ResNet, a Residual Network (ResNet)-based framework designed to discriminate between BD, MDD, and healthy controls (HC) using structural MRI data. Our approach extends the traditional Squeeze-and-Excitation (SE) layer by incorporating a dedicated branch for spatial attention map generation, equipped with soft-pooling, a 7 × 7 convolution, and a sigmoid function, intended to detect complex spatial patterns. The fusion of channel and spatial attention maps through element-wise addition aims to enhance the model's ability to discriminate features. Unlike conventional methods that use max-pooling for downsampling, our methodology employs soft-pooling, which aims to preserve a richer representation of input features and reduce data loss. When evaluated on a proprietary dataset comprising 303 subjects, the SE-ResNet achieved an accuracy of 85.8 %, a recall of 85.7 %, a precision of 85.9 %, and an F1 score of 85.8 %. These performance metrics suggest that the SE-ResNet framework has potential as a tool for detecting psychiatric disorders using structural MRI data.</p>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142366350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-24DOI: 10.1016/j.pscychresns.2024.111905
Pia Thönnessen, L Cornelius Bollheimer, Michael Luehrs, Ute Habel, Bettina Sorger, Charlotte Huppertz
Major depressive disorder in old age can cause changes in the cerebral cortex that might lead to postural imbalance and thus increase fall risk. We aim to examine cortical activation during standing balance in depressed older patients compared to healthy controls and to determine how an additional cognitive task affects this activation. Eleven older patients (age ≥65 years) diagnosed with major depressive disorder and sixteen age-matched healthy controls participated in the study. Functional near-infrared spectroscopy (fNIRS) was used to assess cortical activation of the prefrontal (PFC) and motor (MC) cortex during standing balance with eyes closed under single and dual task (counting backwards). The present study generally revealed tendencies in the MC - and partly the PFC too - for more activation whilst balancing compared to baseline. Also, in the MC, patients tended to show more cortical activation compared to controls and dual task tended to elicit more activation. The results suggest that depressed older patients, to compensate for their illness, may require increased cortical activation to perform motor and cognitive tasks than healthy controls. The absence of PFC activation in the main analyses may be related to the small participant number and possibly to too simple task conditions.
老年重度抑郁症会导致大脑皮层发生变化,从而可能导致姿势失衡,进而增加跌倒风险。与健康对照组相比,我们旨在研究老年抑郁症患者在站立平衡时大脑皮层的激活情况,并确定额外的认知任务会如何影响这种激活。11 名被诊断为重度抑郁症的老年患者(年龄≥65 岁)和 16 名年龄匹配的健康对照组参加了研究。研究人员使用功能性近红外光谱(fNIRS)评估了闭眼站立平衡时在单一任务和双重任务(倒数)下前额叶(PFC)和运动(MC)皮层的激活情况。本研究普遍发现,与基线相比,MC(部分也包括前额叶)在平衡时的激活程度更高。此外,与对照组相比,在 MC 部分,患者倾向于表现出更多的皮质激活,而双重任务则倾向于引起更多的激活。这些结果表明,与健康对照组相比,老年抑郁症患者可能需要更多的大脑皮层激活来完成运动和认知任务,以补偿他们的疾病。在主要分析中没有发现前脑皮层激活可能与参与人数较少有关,也可能与任务条件过于简单有关。
{"title":"(Interfering) Cortical mechanisms of standing balance and cognition in old-age depression: A functional near-infrared spectroscopy (fNIRS) study.","authors":"Pia Thönnessen, L Cornelius Bollheimer, Michael Luehrs, Ute Habel, Bettina Sorger, Charlotte Huppertz","doi":"10.1016/j.pscychresns.2024.111905","DOIUrl":"https://doi.org/10.1016/j.pscychresns.2024.111905","url":null,"abstract":"<p><p>Major depressive disorder in old age can cause changes in the cerebral cortex that might lead to postural imbalance and thus increase fall risk. We aim to examine cortical activation during standing balance in depressed older patients compared to healthy controls and to determine how an additional cognitive task affects this activation. Eleven older patients (age ≥65 years) diagnosed with major depressive disorder and sixteen age-matched healthy controls participated in the study. Functional near-infrared spectroscopy (fNIRS) was used to assess cortical activation of the prefrontal (PFC) and motor (MC) cortex during standing balance with eyes closed under single and dual task (counting backwards). The present study generally revealed tendencies in the MC - and partly the PFC too - for more activation whilst balancing compared to baseline. Also, in the MC, patients tended to show more cortical activation compared to controls and dual task tended to elicit more activation. The results suggest that depressed older patients, to compensate for their illness, may require increased cortical activation to perform motor and cognitive tasks than healthy controls. The absence of PFC activation in the main analyses may be related to the small participant number and possibly to too simple task conditions.</p>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142378213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Objective: Although proven neuronal changes are correlated with anorexia nervosa (AN), where these changes occur and how they change during the course of this disease are often unclear; this is especially true regarding emotion processing, e.g., of anxiety, despite a growing body of literature on its importance for the pathophysiology and clinical course of patients with AN.
Methods: Twenty-two female adolescent patients with AN were scanned during acute starvation and after short-term weight recovery and were compared to 27 healthy controls. A well-established face-matching paradigm involving individuals with different emotions was used during fMRI.
Results: Patients with AN selectively showed significantly increasing neural activation in the somatomotor cortex when viewing fearful faces following short-term weight recovery. No differences were found compared to healthy controls or for neutral, angry or surprised faces. Neural activation in response to fearful faces during acute starvation was associated with lower BMI-SDS and greater illness burden.
Conclusion: Higher somatomotor activity could represent anxiety-induced preparations for motor reactions (e.g., fight or flight) that are more pronounced in more affected patients. These results align with recent models of AN that increasingly incorporate anxiety into the pathophysiological and prognostic model of AN and help elucidate its underlying neurological mechanisms.
目的:尽管神经元变化已被证实与神经性厌食症(AN)有关,但这些变化发生在何处以及在病程中如何变化往往并不清楚;情绪处理(如焦虑)方面的情况尤其如此,尽管越来越多的文献指出了情绪处理对神经性厌食症患者的病理生理学和临床病程的重要性:在急性饥饿期和短期体重恢复后对 22 名女性青少年 AN 患者进行了扫描,并与 27 名健康对照者进行了比较。在进行fMRI扫描时,采用了一种成熟的人脸匹配范式,涉及不同情绪的个体:结果:短期体重恢复后,当观察恐惧面孔时,选择性自闭症患者躯体运动皮层的神经激活明显增加。与健康对照组相比,或与中性、愤怒或惊讶面孔相比,均未发现差异。在急性饥饿期间,神经激活对恐惧面孔的反应与较低的 BMI-SDS 和较重的疾病负担有关:较高的躯体运动活动可能代表焦虑引起的运动反应准备(如战斗或逃跑),这在受影响较大的患者中更为明显。这些结果与最近的AN模型一致,这些模型越来越多地将焦虑纳入AN的病理生理学和预后模型中,并有助于阐明其潜在的神经机制。
{"title":"Longitudinal changes in neural responses to fearful faces in adolescents with anorexia nervosa - A fMRI study.","authors":"Lukas Stanetzky, Arne Hartz, Kimberly Buettgen, Brigitte Dahmen, Beate Herpertz-Dahlmann, Kerstin Konrad, Jochen Seitz","doi":"10.1016/j.pscychresns.2024.111904","DOIUrl":"https://doi.org/10.1016/j.pscychresns.2024.111904","url":null,"abstract":"<p><strong>Objective: </strong>Although proven neuronal changes are correlated with anorexia nervosa (AN), where these changes occur and how they change during the course of this disease are often unclear; this is especially true regarding emotion processing, e.g., of anxiety, despite a growing body of literature on its importance for the pathophysiology and clinical course of patients with AN.</p><p><strong>Methods: </strong>Twenty-two female adolescent patients with AN were scanned during acute starvation and after short-term weight recovery and were compared to 27 healthy controls. A well-established face-matching paradigm involving individuals with different emotions was used during fMRI.</p><p><strong>Results: </strong>Patients with AN selectively showed significantly increasing neural activation in the somatomotor cortex when viewing fearful faces following short-term weight recovery. No differences were found compared to healthy controls or for neutral, angry or surprised faces. Neural activation in response to fearful faces during acute starvation was associated with lower BMI-SDS and greater illness burden.</p><p><strong>Conclusion: </strong>Higher somatomotor activity could represent anxiety-induced preparations for motor reactions (e.g., fight or flight) that are more pronounced in more affected patients. These results align with recent models of AN that increasingly incorporate anxiety into the pathophysiological and prognostic model of AN and help elucidate its underlying neurological mechanisms.</p>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142378214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-23DOI: 10.1016/j.pscychresns.2024.111906
The hypothalamus is an important component of the hypothalamic-pituitary-adrenal axis and an important brain region of the limbic system. Twenty-four first depressive episode(FDE) patients and 25 healthy controls were recruited for this study. The hypothalamus was used as a seed to observe the characteristics of resting state and dynamic functional connectivity (FC) changes in FDE patients, and further observed the correlation between the different brain regions and clinical symptoms. The results found that compared with the HC group, the FDE group showed sFC was increased of the left hypothalamus with right superior parietal gyrus and right middle temporal gyrus, and dFC was increased of the left hypothalamus with left inferior occipital gyrus. And sFC was increased of the right hypothalamus with right orbital part of inferior frontal gyrus, right supplementary motor area, and right middle temporal gyrus, and the dFC was also increased of right hypothalamus with right superior parietal gyrus and left middle temporal gyrus. In addition,there was a negative correlation between dFC values of the right hypothalamus with the right superior parietal gyrus and clinical symptoms in the FDE group. This study provides new insights into understanding the altered neuropathological mechanisms of the hypothalamic circuit in FDE.
{"title":"Altered resting-state and dynamic functional connectivity of hypothalamic in first-episode depression: A functional magnetic resonance imaging study","authors":"","doi":"10.1016/j.pscychresns.2024.111906","DOIUrl":"10.1016/j.pscychresns.2024.111906","url":null,"abstract":"<div><div>The hypothalamus is an important component of the hypothalamic-pituitary-adrenal axis and an important brain region of the limbic system. Twenty-four first depressive episode(FDE) patients and 25 healthy controls were recruited for this study. The hypothalamus was used as a seed to observe the characteristics of resting state and dynamic functional connectivity (FC) changes in FDE patients, and further observed the correlation between the different brain regions and clinical symptoms. The results found that compared with the HC group, the FDE group showed sFC was increased of the left hypothalamus with right superior parietal gyrus and right middle temporal gyrus, and dFC was increased of the left hypothalamus with left inferior occipital gyrus. And sFC was increased of the right hypothalamus with right orbital part of inferior frontal gyrus, right supplementary motor area, and right middle temporal gyrus, and the dFC was also increased of right hypothalamus with right superior parietal gyrus and left middle temporal gyrus. In addition,there was a negative correlation between dFC values of the right hypothalamus with the right superior parietal gyrus and clinical symptoms in the FDE group. This study provides new insights into understanding the altered neuropathological mechanisms of the hypothalamic circuit in FDE.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142352679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-16DOI: 10.1016/j.pscychresns.2024.111901
Rationale and objectives
To explore the characteristics of brain structure in Chinese children with autism spectrum disorder (ASD) using artificial intelligence automatic brain segmentation technique, and to diagnose children with ASD using machine learning (ML) methods in combination with structural magnetic resonance imaging (sMRI) features.
Methods
A total of 60 ASD children and 48 age- and sex-matched typically developing (TD) children were prospectively enrolled from January 2023 to April 2024. All subjects were scanned using 3D-T1 sequences. Automated brain segmentation techniques were utilized to obtain the standardized volume of each brain structure (the ratio of the absolute volume of brain structure to the whole brain volume). The standardized volumes of each brain structure in the two groups were statistically compared, and the volume data of brain areas with significant differences were combined with ML methods to diagnose and predict ASD patients.
Results
Compared with the TD group, the volumes of the right lateral orbitofrontal cortex, right medial orbitofrontal cortex, right pars opercularis, right pars triangularis, left hippocampus, bilateral parahippocampal gyrus, left fusiform gyrus, right superior temporal gyrus, bilateral insula, bilateral inferior parietal cortex, right precuneus cortex, bilateral putamen, left pallidum, and right thalamus were significantly increased in the ASD group (P< 0.05). Among six ML algorithms, support vector machine (SVM) and adaboost (AB) had better performance in differentiating subjects with ASD from those TD children, with their average area under curve (AUC) reaching 0.91 and 0.92, respectively.
Conclusion
Automatic brain segmentation technology based on artificial intelligence can rapidly and directly measure and display the volume of brain structures in children with autism spectrum disorder and typically developing children. Children with ASD show abnormalities in multiple brain structures, and when paired with sMRI features, ML algorithms perform well in the diagnosis of ASD.
{"title":"Quantitative assessment of brain structural abnormalities in children with autism spectrum disorder based on artificial intelligence automatic brain segmentation technology and machine learning methods","authors":"","doi":"10.1016/j.pscychresns.2024.111901","DOIUrl":"10.1016/j.pscychresns.2024.111901","url":null,"abstract":"<div><h3>Rationale and objectives</h3><div>To explore the characteristics of brain structure in Chinese children with autism spectrum disorder (ASD) using artificial intelligence automatic brain segmentation technique, and to diagnose children with ASD using machine learning (ML) methods in combination with structural magnetic resonance imaging (sMRI) features.</div></div><div><h3>Methods</h3><div>A total of 60 ASD children and 48 age- and sex-matched typically developing (TD) children were prospectively enrolled from January 2023 to April 2024. All subjects were scanned using 3D-T1 sequences. Automated brain segmentation techniques were utilized to obtain the standardized volume of each brain structure (the ratio of the absolute volume of brain structure to the whole brain volume). The standardized volumes of each brain structure in the two groups were statistically compared, and the volume data of brain areas with significant differences were combined with ML methods to diagnose and predict ASD patients.</div></div><div><h3>Results</h3><div>Compared with the TD group, the volumes of the right lateral orbitofrontal cortex, right medial orbitofrontal cortex, right pars opercularis, right pars triangularis, left hippocampus, bilateral parahippocampal gyrus, left fusiform gyrus, right superior temporal gyrus, bilateral insula, bilateral inferior parietal cortex, right precuneus cortex, bilateral putamen, left pallidum, and right thalamus were significantly increased in the ASD group (<em>P</em>< 0.05). Among six ML algorithms, support vector machine (SVM) and adaboost (AB) had better performance in differentiating subjects with ASD from those TD children, with their average area under curve (AUC) reaching 0.91 and 0.92, respectively.</div></div><div><h3>Conclusion</h3><div>Automatic brain segmentation technology based on artificial intelligence can rapidly and directly measure and display the volume of brain structures in children with autism spectrum disorder and typically developing children. Children with ASD show abnormalities in multiple brain structures, and when paired with sMRI features, ML algorithms perform well in the diagnosis of ASD.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142293988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-12DOI: 10.1016/j.pscychresns.2024.111902
Approximately 7–10% of people experiencing bereavement following a death develop prolonged grief disorder, a psychiatric disorder included in the DSM-5-TR. Prolonged grief disorder encompasses core symptoms of intense yearning/longing for and preoccupation with thoughts or memories of the deceased person experienced to a clinically significant degree for at least the last month, other key associated symptoms (e.g., avoidance, emotional pain), and the death must have occurred at least one year prior to diagnosis. Extant research has shown a relationship between activation in the reward pathway (e.g., nucleus accumbens) and grief severity. To date, functional MRI studies have primarily utilized the Emotional Counting Stroop task (ecStroop) and the Grief Elicitation task to explore these relationships. However, these prior studies are not without limitations, including small sample sizes and absence of a unified task protocol, hindering meaningful comparisons between studies. This protocol paper describes the ecStroop task and the Grief Elicitation task, which will be vital for facilitating multisite studies and enabling comparisons across studies. This will aid to advance the field by identifying neurophysiological measures that may, in the future, serve as potential biomarkers of prolonged grief disorder.
{"title":"Personalized fMRI tasks for grief severity in bereaved individuals: Emotional counting Stroop and grief elicitation protocols","authors":"","doi":"10.1016/j.pscychresns.2024.111902","DOIUrl":"10.1016/j.pscychresns.2024.111902","url":null,"abstract":"<div><p>Approximately 7–10% of people experiencing bereavement following a death develop prolonged grief disorder, a psychiatric disorder included in the DSM-5-TR. Prolonged grief disorder encompasses core symptoms of intense yearning/longing for and preoccupation with thoughts or memories of the deceased person experienced to a clinically significant degree for at least the last month, other key associated symptoms (e.g., avoidance, emotional pain), and the death must have occurred at least one year prior to diagnosis. Extant research has shown a relationship between activation in the reward pathway (e.g., nucleus accumbens) and grief severity. To date, functional MRI studies have primarily utilized the Emotional Counting Stroop task (ecStroop) and the Grief Elicitation task to explore these relationships. However, these prior studies are not without limitations, including small sample sizes and absence of a unified task protocol, hindering meaningful comparisons between studies. This protocol paper describes the ecStroop task and the Grief Elicitation task, which will be vital for facilitating multisite studies and enabling comparisons across studies. This will aid to advance the field by identifying neurophysiological measures that may, in the future, serve as potential biomarkers of prolonged grief disorder.</p></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142232418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-07DOI: 10.1016/j.pscychresns.2024.111889
Substance use is a chronic and recurrent public healthcare concern increasing in the world, causing negative outcomes. Two or more substance use is common among people who have substance use disorders and who receive treatment. For this reason, the present study aimed to measure Retinal Nerve Fiber Layer (RNFL), Mean Macular Thickness (MMT), Central Macular Thickness (CMT) in patients who have Multiple substance use disorder (MSUD) using Optical Coherence Tomography (OCT), considering that it will contribute to the literature. Among the inpatients who were rehabilitated in Elazig Mental Hospital Alcohol and Substance Addiction Treatment Center, 75 people who were diagnosed with MSUD according to DSM-5 and met the criteria, and 51 control groups were included in the study. RNFL, MMT and CMT measurements of both eyes of all participants were made by using the OCT. Total RNFL measurement were significantly thicker than the control group (p < 0.001). MMT and CMT of the eyes of the patient were thinner than the control group (p = 0.009, p < 0.001). The findings provide important contributions to the literature data and in light of these findings, it can be recommended to consider visual findings and possible neurodegeneration when evaluating patients in the addiction group and planning their treatment.
{"title":"Assessment of RNFL and macular changes in the eye related to multiple substance use using OCT","authors":"","doi":"10.1016/j.pscychresns.2024.111889","DOIUrl":"10.1016/j.pscychresns.2024.111889","url":null,"abstract":"<div><p>Substance use is a chronic and recurrent public healthcare concern increasing in the world, causing negative outcomes. Two or more substance use is common among people who have substance use disorders and who receive treatment. For this reason, the present study aimed to measure Retinal Nerve Fiber Layer (RNFL), Mean Macular Thickness (MMT), Central Macular Thickness (CMT) in patients who have Multiple substance use disorder (MSUD) using Optical Coherence Tomography (OCT), considering that it will contribute to the literature. Among the inpatients who were rehabilitated in Elazig Mental Hospital Alcohol and Substance Addiction Treatment Center, 75 people who were diagnosed with MSUD according to DSM-5 and met the criteria, and 51 control groups were included in the study. RNFL, MMT and CMT measurements of both eyes of all participants were made by using the OCT. Total RNFL measurement were significantly thicker than the control group (<em>p</em> < 0.001). MMT and CMT of the eyes of the patient were thinner than the control group (<em>p</em> = 0.009, <em>p</em> < 0.001). The findings provide important contributions to the literature data and in light of these findings, it can be recommended to consider visual findings and possible neurodegeneration when evaluating patients in the addiction group and planning their treatment.</p></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142232417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-05DOI: 10.1016/j.pscychresns.2024.111891
Background
Emotional dysregulation is a serious and impairing mental health problem. We examined functional activity and connectivity of neural networks involved in emotional dysregulation at baseline and following a pilot neurostimulation-enhanced cognitive restructuring intervention in a transdiagnostic clinical adult sample.
Methods
Neuroimaging data were analyzed from adults who scored 89 or higher on the Difficulties with Emotion Regulation (DERS) scale and had at least one DSM-5 diagnosis. These participants were part of a pilot randomized, double-blind, placebo-controlled trial combining a single therapeutic session of cognitive restructuring with active or sham transcranial magnetic stimulation over the dorsolateral prefrontal cortex. During the study, participants engaged in an emotional regulation task using personalized autobiographical stressors while undergoing functional magnetic resonance imaging (fMRI) before and after the pilot intervention. The fMRI task required participants to either experience the emotions associated with the memories or apply cognitive restructuring strategies to reduce their distress.
Results
Whole-brain fMRI results during regulation at baseline revealed increased activation in the dorsal frontoparietal network but decreased activation in the supplementary motor area, cingulate cortex, insula, and ventrolateral prefrontal cortex (vlPFC). Emotion dysregulation was associated with greater vmPFC and amygdala activation and functional connectivity between these regions. The strength of functional connectivity between the dlPFC and other frontal regions was also a marker of emotional dysregulation. Preliminary findings from a subset of participants who completed the follow-up fMRI scan showed that active neurostimulation improved behavioral indices of emotion regulation more than sham stimulation. A whole-brain generalized psychophysiological interaction analysis indicated that active neurostimulation selectively increased occipital cortex connectivity with both the insula and the dlPFC. Region-of-interest functional connectivity analyses showed that active neurostimulation selectively increased dlPFC connectivity with the insula and orbitofrontal cortex (OFC).
Conclusion
Insufficient neural specificity during the emotion regulation process and over-involvement of frontal regions may be a marker of emotional dysregulation across disorders. OFC, vlPFC, insula activity, and connectivity are associated with improved emotion regulation in transdiagnostic adults. In this pilot study, active neurostimulation led to neural changes in the emotion regulation network after a single session; however, the intervention findings are preliminary, given the small sample size. These functional network properties can inform future neuroscience-driven interventions and larger-scale studies.
{"title":"Characterization of neural networks involved in transdiagnostic emotion dysregulation from a pilot randomized controlled trial of a neurostimulation-enhanced behavioral intervention","authors":"","doi":"10.1016/j.pscychresns.2024.111891","DOIUrl":"10.1016/j.pscychresns.2024.111891","url":null,"abstract":"<div><h3>Background</h3><p>Emotional dysregulation is a serious and impairing mental health problem. We examined functional activity and connectivity of neural networks involved in emotional dysregulation at baseline and following a pilot neurostimulation-enhanced cognitive restructuring intervention in a transdiagnostic clinical adult sample.</p></div><div><h3>Methods</h3><p>Neuroimaging data were analyzed from adults who scored 89 or higher on the Difficulties with Emotion Regulation (DERS) scale and had at least one DSM-5 diagnosis. These participants were part of a pilot randomized, double-blind, placebo-controlled trial combining a single therapeutic session of cognitive restructuring with active or sham transcranial magnetic stimulation over the dorsolateral prefrontal cortex. During the study, participants engaged in an emotional regulation task using personalized autobiographical stressors while undergoing functional magnetic resonance imaging (fMRI) before and after the pilot intervention. The fMRI task required participants to either experience the emotions associated with the memories or apply cognitive restructuring strategies to reduce their distress.</p></div><div><h3>Results</h3><p>Whole-brain fMRI results during regulation at baseline revealed increased activation in the dorsal frontoparietal network but decreased activation in the supplementary motor area, cingulate cortex, insula, and ventrolateral prefrontal cortex (vlPFC). Emotion dysregulation was associated with greater vmPFC and amygdala activation and functional connectivity between these regions. The strength of functional connectivity between the dlPFC and other frontal regions was also a marker of emotional dysregulation. Preliminary findings from a subset of participants who completed the follow-up fMRI scan showed that active neurostimulation improved behavioral indices of emotion regulation more than sham stimulation. A whole-brain generalized psychophysiological interaction analysis indicated that active neurostimulation selectively increased occipital cortex connectivity with both the insula and the dlPFC. Region-of-interest functional connectivity analyses showed that active neurostimulation selectively increased dlPFC connectivity with the insula and orbitofrontal cortex (OFC).</p></div><div><h3>Conclusion</h3><p>Insufficient neural specificity during the emotion regulation process and over-involvement of frontal regions may be a marker of emotional dysregulation across disorders. OFC, vlPFC, insula activity, and connectivity are associated with improved emotion regulation in transdiagnostic adults. In this pilot study, active neurostimulation led to neural changes in the emotion regulation network after a single session; however, the intervention findings are preliminary, given the small sample size. These functional network properties can inform future neuroscience-driven interventions and larger-scale studies.</p></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142232416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-02DOI: 10.1016/j.pscychresns.2024.111882
Background
Individuals with borderline personality traits are known to have disturbed representations of self and others. Specifically, an unstable self-identity and difficulties distinguishing between self and others can impair their mentalizing abilities in interpersonal situations. However, it is unclear whether these traits are linked to differences in neural representation of self and others.
Methods
In this study involving 156 young adults, changes in neural function during self-other processing were measured using a Functional Near-Infrared Spectroscopy (fNIRS) task and a self-report survey. During the fNIRS task, participants were asked about their own traits, others' traits, how they believed others perceived them, and the basic meaning of words. The study aimed to determine whether the degree of neural differentiation between the task conditions was related to borderline personality traits.
Result
The study found that traits indicative of identity instability could be predicted by similarities in task-dependent connectivity. Specifically, the neural patterns when individuals estimated how others perceived them were more similar to the patterns when they judged their own traits.
Conclusions
These findings suggest that borderline personality traits related to identity issues may reflect difficulties in distinguishing between neural patterns when processing self and other information.
{"title":"Borderline personality trait is associated with neural differentiation of self-other processing: A functional near-infrared spectroscopy study","authors":"","doi":"10.1016/j.pscychresns.2024.111882","DOIUrl":"10.1016/j.pscychresns.2024.111882","url":null,"abstract":"<div><h3>Background</h3><p>Individuals with borderline personality traits are known to have disturbed representations of self and others. Specifically, an unstable self-identity and difficulties distinguishing between self and others can impair their mentalizing abilities in interpersonal situations. However, it is unclear whether these traits are linked to differences in neural representation of self and others.</p></div><div><h3>Methods</h3><p>In this study involving 156 young adults, changes in neural function during self-other processing were measured using a Functional Near-Infrared Spectroscopy (fNIRS) task and a self-report survey. During the fNIRS task, participants were asked about their own traits, others' traits, how they believed others perceived them, and the basic meaning of words. The study aimed to determine whether the degree of neural differentiation between the task conditions was related to borderline personality traits.</p></div><div><h3>Result</h3><p>The study found that traits indicative of identity instability could be predicted by similarities in task-dependent connectivity. Specifically, the neural patterns when individuals estimated how others perceived them were more similar to the patterns when they judged their own traits.</p></div><div><h3>Conclusions</h3><p>These findings suggest that borderline personality traits related to identity issues may reflect difficulties in distinguishing between neural patterns when processing self and other information.</p></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142146097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-30DOI: 10.1016/j.pscychresns.2024.111881
Background
Schizophrenia patients frequently present with structural and functional abnormalities of the ventral striatum (VS).
Methods
we examined basal activation state and functional connectivity (FC) in four subregions of the bilateral ventral striatum: left inferior ventral striatum (VSi_L), left superior ventral striatum(VSs_L), right inferior ventral striatum(VSi_R), and right superior ventral striatum(VSs_R). Resting-state functional magnetic resonance images were obtained from 62 schizophrenia patients (SCH), 57 bipolar disorder (BD) patients, and 26 healthy controls (HCs).
Results
The schizophrenia group exhibited greater fALFF in bilateral VS subregions compared to BD and HC groups as well as greater FC between the bilateral VSi and multiple brain regions, including the thalamus, putamen, posterior cingulate gyrus (PCC), frontal cortex and caudate. Moreover, the fALFF values of the bilateral ventral striatum were positively correlated with the severity of positive symptoms. We also found the functional connectivity between the bilateral inferior ventral striatum and some brain regions aforementioned were positively correlated with the severity of negative symptoms.
Conclusion
These findings confirm a crucial contribution of ventral striatum dysfunction, especially of the bilateral VSi in schizophrenia. Functionally dissociated regions of the ventral striatum are differentially disturbed in schizophrenia.
背景精神分裂症患者经常出现腹侧纹状体(VS)结构和功能异常。方法我们研究了双侧腹侧纹状体四个亚区的基础激活状态和功能连接(FC):左下腹侧纹状体(VSi_L)、左上腹侧纹状体(VSs_L)、右下腹侧纹状体(VSi_R)和右上腹侧纹状体(VSs_R)。62 名精神分裂症患者(SCH)、57 名双相情感障碍患者(BD)和 26 名健康对照组(HC)获得了静息态功能磁共振图像。结果与 BD 组和 HC 组相比,精神分裂症组的双侧 VS 亚区的 fALFF 更大,双侧 VSi 与多个脑区(包括丘脑、丘脑、扣带后回、额叶皮层和尾状核)之间的 FC 更大。此外,双侧腹侧纹状体的 fALFF 值与阳性症状的严重程度呈正相关。我们还发现,双侧腹侧纹状体下部与上述一些脑区之间的功能连接与阴性症状的严重程度呈正相关。腹侧纹状体的功能分离区在精神分裂症中受到不同程度的干扰。
{"title":"Hyperactivity and altered functional connectivity of the ventral striatum in schizophrenia compared with bipolar disorder: A resting state fMRI study","authors":"","doi":"10.1016/j.pscychresns.2024.111881","DOIUrl":"10.1016/j.pscychresns.2024.111881","url":null,"abstract":"<div><h3>Background</h3><p>Schizophrenia patients frequently present with structural and functional abnormalities of the ventral striatum (VS).</p></div><div><h3>Methods</h3><p>we examined basal activation state and functional connectivity (FC) in four subregions of the bilateral ventral striatum: left inferior ventral striatum (VSi_L), left superior ventral striatum(VSs_L), right inferior ventral striatum(VSi_R), and right superior ventral striatum(VSs_R). Resting-state functional magnetic resonance images were obtained from 62 schizophrenia patients (SCH), 57 bipolar disorder (BD) patients, and 26 healthy controls (HCs).</p></div><div><h3>Results</h3><p>The schizophrenia group exhibited greater fALFF in bilateral VS subregions compared to BD and HC groups as well as greater FC between the bilateral VSi and multiple brain regions, including the thalamus, putamen, posterior cingulate gyrus (PCC), frontal cortex and caudate. Moreover, the fALFF values of the bilateral ventral striatum were positively correlated with the severity of positive symptoms. We also found the functional connectivity between the bilateral inferior ventral striatum and some brain regions aforementioned were positively correlated with the severity of negative symptoms.</p></div><div><h3>Conclusion</h3><p>These findings confirm a crucial contribution of ventral striatum dysfunction, especially of the bilateral VSi in schizophrenia. Functionally dissociated regions of the ventral striatum are differentially disturbed in schizophrenia.</p></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":null,"pages":null},"PeriodicalIF":2.1,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142230319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}