Department of Psychology, Royal Holloway, University of London, Egham, UK.
Neuroimage. 2011 May 15;56(2):525-30. doi: 10.1016/j.neuroimage.2010.05.079. Epub 2010 Jun 4.
Multi-voxel pattern analysis (MVPA) is proving very powerful in the analysis of fMRI timeseries data, yielding surprising sensitivity, in many different contexts, to the response characteristics of neurons in a given brain region. However, MVPA yields a metric (classification performance) that does not readily lend itself to quantitative comparisons across experimental conditions, brain regions or people. This is because performance is influenced by a number of factors other than the sensitivity of neurons to the experimental manipulation. One such factor that varies widely but has been largely ignored in MVPA studies is the amplitude of the response being decoded. In a noisy system, it is expected that measured classification performance will decline with declining response amplitude, even if the underlying neuronal specificity is constant. We document the relationship between response amplitude and classification performance in the context of orientation decoding in the visual cortex. Flickering sine gratings were presented at each of two orthogonal orientations in a block design (multivariate experiment) or an event-related design (univariate experiment). Response amplitude was manipulated by varying stimulus contrast. Orientation classification performance in retinotopically defined occipital area V1 increased approximately linearly with the logarithm of stimulus contrast. As expected, univariate response amplitude also increased with contrast. Similar results were obtained in V2, V3 and V3A. Plotting classification performance against response amplitude gave a function with a compressive non-linearity that was well fit by a power function. Knowledge of this function potentially allows adjustment of classification performance to take account of the effect of response size, making comparisons across brain areas, categories or people more meaningful.
多体素模式分析（MVPA）在 fMRI 时间序列数据分析中证明非常强大，在许多不同的情况下，对给定脑区神经元的反应特征具有惊人的敏感性。然而，MVPA 产生的度量（分类性能）不容易在实验条件、脑区或人群之间进行定量比较。这是因为性能受到许多因素的影响，而不仅仅是神经元对实验操作的敏感性。其中一个因素变化很大，但在 MVPA 研究中基本上被忽略了，那就是正在解码的反应的幅度。在噪声系统中，即使潜在的神经元特异性保持不变，也预计测量的分类性能将随着反应幅度的降低而降低。我们在视觉皮层的方向解码背景下记录了反应幅度和分类性能之间的关系。在块设计（多元实验）或事件相关设计（单变量实验）中，以两种正交方向呈现闪烁正弦光栅。通过改变刺激对比度来操纵反应幅度。在视网膜定义的枕叶 V1 中，方向分类性能随刺激对比度的对数大致呈线性增加。如预期的那样，单变量反应幅度也随对比度增加。在 V2、V3 和 V3A 中也得到了类似的结果。将分类性能与反应幅度作图得到一个具有压缩非线性的函数，该函数很好地符合幂函数。对该函数的了解可以对分类性能进行调整，以考虑到反应大小的影响，从而使脑区、类别或人群之间的比较更有意义。
