How Many Subjects Constitute a Study?
ABSTRACT In fMRI there are two classes of inference: one aims to make a comment about the "typical" characteristics of a population, and the other about "average" characteristics. The first pertains to studies of normal subjects that try to identify some qualitative aspect of normal functional anatomy. The second class necessarily applies to clinical neuroscience studies that want to make an inference about quantitative differences of a regionally specific nature. The first class of inferences is adequately serviced by conjunction analyses and fixed-effects models with relatively small numbers of subjects. The second requires random-effect analyses and larger cohorts.
SourceAvailable from: Shachar Maidenbaum
Article: A number-form area in the blind[Show abstract] [Hide abstract]
ABSTRACT: Distinct preference for visual number symbols was recently discovered in the human right inferior temporal gyrus (rITG). It remains unclear how this preference emerges, what is the contribution of shape biases to its formation and whether visual processing underlies it. Here we use congenital blindness as a model for brain development without visual experience. During fMRI, we present blind subjects with shapes encoded using a novel visual-to-music sensory-substitution device (The EyeMusic). Greater activation is observed in the rITG when subjects process symbols as numbers compared with control tasks on the same symbols. Using resting-state fMRI in the blind and sighted, we further show that the areas with preference for numerals and letters exhibit distinct patterns of functional connectivity with quantity and language-processing areas, respectively. Our findings suggest that specificity in the ventral 'visual' stream can emerge independently of sensory modality and visual experience, under the influence of distinct connectivity patterns.Nature Communications 01/2015; 6:6026. DOI:10.1038/ncomms7026 · 10.74 Impact Factor
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ABSTRACT: Voxel-based Morphometry (VBM) is a widely used automated technique for the analysis of neuroanatomical images. Despite its popularity within the neuroimaging community, there are outstanding concerns about its potential susceptibility to false positive findings. Here we review the main methodological factors that are known to influence the results of VBM studies comparing two groups of subjects. We then use two large, open-access data sets to empirically estimate false positive rates and how these depend on sample size, degree of smoothing and modulation. Our review and investigation provide three main results: (i) when groups of equal size are compared false positive rate is not higher than expected, i.e. about 5%; (ii) the sample size, degree of smoothing and modulation do not appear to influence false positive rate; (iii) when they exist, false positive findings are randomly distributed across the brain. These results provide reassurance that VBM studies comparing groups are not vulnerable to the higher than expected false positive rates that are evident in single case VBM. Copyright © 2015. Published by Elsevier Ltd.Neuroscience & Biobehavioral Reviews 02/2015; 11. DOI:10.1016/j.neubiorev.2015.02.008 · 10.28 Impact Factor
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ABSTRACT: This study aimed to identify the neural basis of probabilistic reasoning, a type of inductive inference that aids decision making under conditions of uncertainty. Eight normal subjects performed two separate two-alternative-choice tasks (the balls in a bottle and personality survey tasks) while undergoing functional magnetic resonance imaging (fMRI). The experimental conditions within each task were chosen so that they differed only in their requirement to make a decision under conditions of uncertainty (probabilistic reasoning and frequency determination required) or under conditions of certainty (frequency determination required). The same visual stimuli and motor responses were used in the experimental conditions. We provide evidence that the neo-cerebellum, in conjunction with the premotor cortex, inferior parietal lobule and medial occipital cortex, mediates the probabilistic inferences that guide decision making under uncertainty. We hypothesise that the neo-cerebellum constructs internal working models of uncertain events in the external world, and that such probabilistic models subserve the predictive capacity central to induction.Cognitive Brain Research 06/2004; 20(1):46-53. DOI:10.1016/S0926-6410(04)00034-5 · 3.77 Impact Factor