Sawrie S M, Martin R C, Gilliam F G, Faught R E, Maton B, Hugg J W, Bush N, Sinclair K, Kuzniecky R I
Epilepsy Center, Department of Neurology, University of Alabama at Birmingham 35294, USA.
Brain. 2000 Apr;123 ( Pt 4):770-80. doi: 10.1093/brain/123.4.770.
Prior research on the relationship between visual confrontation naming and hippocampal function has been inconclusive. The present study examined this relationship using quantitative (1)H magnetic resonance spectroscopy ((1)H-MRS) to operationalize the function of the left and right hippocampi. The 60-item Boston Naming Test (BNT) was used to measure naming. Our sample included 46 patients with medically intractable, focal mesial temporal lobe epilepsy who had been screened for all pathology other than mesial temporal sclerosis. Statistics included Pearson correlations and neural network analysis (multilayer perceptron and radial basis function). Baseline BNT performance correlated significantly with left (1)H-MRS hippocampal ratios. Thirty-six per cent of the variance in baseline BNT performance was explained by a neural network model using left and right (1)H-MRS ratios(creatine/N-acetylaspartate) as input. This was elevated to 49% when input from the right hippocampus was lesioned mathematically. In a second model, left (1)H-MRS hippocampal ratios were modelled using measures of semantic and episodic memory as input (including the BNT). Explained variance in left (1)H-MRS hippocampal ratios fell from 60.8 to 3.6% when input from BNT and another semantic memory measure was degraded mathematically. These results provide evidence that the speech-dominant hippocampus is a significant component of the overall neuroanatomical network of visual confrontation naming. Clinical and theoretical implications are explored.
先前关于视觉对抗命名与海马体功能之间关系的研究尚无定论。本研究使用定量氢磁共振波谱(¹H-MRS)来衡量左右海马体的功能,从而检验这种关系。采用60项的波士顿命名测试(BNT)来测量命名能力。我们的样本包括46例患有药物难治性局灶性内侧颞叶癫痫的患者,这些患者已针对除内侧颞叶硬化症以外的所有病变进行了筛查。统计分析包括Pearson相关性分析和神经网络分析(多层感知器和径向基函数)。BNT基线表现与左侧¹H-MRS海马体比率显著相关。使用左右¹H-MRS比率(肌酸/N-乙酰天门冬氨酸)作为输入的神经网络模型解释了BNT基线表现中36%的方差。当右侧海马体的输入在数学上被损伤时,这一比例提高到了49%。在第二个模型中,使用语义记忆和情景记忆的测量指标(包括BNT)作为输入,对左侧¹H-MRS海马体比率进行建模。当BNT和另一项语义记忆测量指标的输入在数学上被削弱时,左侧¹H-MRS海马体比率的解释方差从60.8%降至3.6%。这些结果证明,语言优势侧海马体是视觉对抗命名整体神经解剖网络的重要组成部分。本文还探讨了其临床和理论意义。