Peled Avi
Bruce and Ruth Rappaport Faculty of Medicine, Technion, Haifa, Israel.
Med Hypotheses. 2006;67(4):941-6. doi: 10.1016/j.mehy.2006.03.029. Epub 2006 May 15.
The current psychiatric diagnostic system, the diagnostic statistic manual, has recently come under increasing criticism. The major reason for the shortcomings of the current psychiatric diagnosis is the lack of a scientific brain-related etiological knowledge about mental disorders. The advancement toward such knowledge is further hampered by the lack of a theoretical framework or "language" that translates clinical findings of mental disorders to brain disturbances and insufficiencies. Here such a theoretical construct is proposed based on insights from neuroscience and neural-computation models. Correlates between clinical manifestations and presumed neuronal network disturbances are proposed in the form of a practical diagnostic system titled "Brain Profiling". Three dimensions make-up brain profiling, "neural complexity disorders", "neuronal resilience insufficiency", and "context-sensitive processing decline". The first dimension relates to disturbances occurring to fast neuronal activations in the millisecond range, it incorporates connectivity and hierarchical imbalances appertaining typically to psychotic and schizophrenic clinical manifestations. The second dimension relates to disturbances that alter slower changes namely long-term synaptic modulations, and incorporates disturbances to optimization and constraint satisfactions within relevant neuronal circuitry. Finally, the level of internal representations related to personality disorders is presented by a "context-sensitive process decline" as the third dimension. For practical use of brain profiling diagnosis a consensual list of psychiatric clinical manifestations provides a "diagnostic input vector", clinical findings are coded 1 for "detection" and 0 for "non-detection", 0.5 is coded for "questionable". The entries are clustered according to their presumed neuronal dynamic relationships and coefficients determine their relevance to the specific related brain disturbance. Relevant equations calculate and normalize the different values attributed to relevant brain disturbances culminating in a three-digit estimation representing the three diagnostic dimensions. brain profiling has the promise for a future brain-related diagnosis. It offers testable predictions about the etiology of mental disorders because being brain-related it lends readily to brain imaging investigations. Being presented also as a one-point representation in a three-dimensional space, multiple follow-up diagnoses trace a trajectory representing an easy-to-see clinical history of the patient. Additional, more immediate, advantages involve reduced stigma because it relaters the disorder to the brain not the person, in addition the three-digit diagnostic code is clinically informative unlike the DSM codes that have no clinical relevance. To conclude, brain profiling diagnosis of mental disorders could be a bold new step toward a "clinical-neuroscience" substituting "psychiatry".
当前的精神科诊断系统,即《诊断统计手册》,最近受到了越来越多的批评。当前精神科诊断存在缺陷的主要原因是缺乏关于精神障碍的与大脑相关的科学病因学知识。而向此类知识的推进又因缺乏一个将精神障碍的临床发现转化为大脑功能紊乱和不足的理论框架或“语言”而进一步受阻。在此,基于神经科学和神经计算模型的见解,提出了这样一种理论构想。以一个名为“脑图谱分析”的实用诊断系统的形式,提出了临床表现与假定的神经网络紊乱之间的关联。脑图谱分析由三个维度组成,即“神经复杂性障碍”、“神经元恢复力不足”和“情境敏感加工衰退”。第一个维度涉及在毫秒范围内快速神经元激活时发生的紊乱,它包含通常与精神病性和精神分裂症临床表现相关的连接性和层级失衡。第二个维度涉及改变较慢变化(即长期突触调制)的紊乱,并包含相关神经元回路内优化和约束满足方面的紊乱。最后,与人格障碍相关的内部表征水平由作为第三个维度的“情境敏感加工衰退”来呈现。为了实际应用脑图谱分析诊断,一份达成共识的精神科临床表现清单提供了一个“诊断输入向量”,临床发现对于“检测到”编码为1,对于“未检测到”编码为0,对于“可疑”编码为0.5。这些条目根据其假定的神经元动态关系进行聚类,系数确定它们与特定相关脑功能紊乱的相关性。相关方程计算并归一化归因于相关脑功能紊乱的不同值,最终得出一个代表三个诊断维度的三位数估计值。脑图谱分析有望实现未来与大脑相关的诊断。它提供了关于精神障碍病因的可检验预测,因为与大脑相关,它很容易用于脑成像研究。它还以三维空间中的单点表示形式呈现,多次随访诊断描绘出一条轨迹,代表患者易于理解的临床病史。另外,更直接的优势包括减少污名化,因为它将疾病与大脑而非个人联系起来,此外,与没有临床相关性的《精神疾病诊断与统计手册》代码不同,三位数诊断代码具有临床信息价值。总之,精神障碍的脑图谱分析诊断可能是迈向取代“精神病学”的“临床神经科学”的大胆新举措。