Context. The identification of smaller and smaller signals from objects observed with a non-perfect instrument in a noisy environment poses a challenge for a statistically clean data analysis. Aims. We compute the probability that frequencies determined in various data sets are related or not, which cannot be answered with a simple comparison of amplitudes. Our method provides a statistical estimator for whether a given signal with different strengths in a set of observations is of instrumental origin or is intrinsic. Methods. Based on the spectral significance as an unbiased statistical quantity in frequency analysis, Discrete Fourier Transforms (DFTs) of target and background light curves are compared. The individual False-Alarm Probabilities are used to deduce a conditional probability of a peak in a target spectrum being real in spite of a corresponding peak in the spectrum of sky background or of comparison stars. Alternatively, we can compute joint probabilities of frequencies to occur in the DFT spectra of several data sets simultaneously but with different amplitude, leading to composed spectral significances. These are useful to investigate a star observed in different filters or during several observing runs. The composed spectral significance is a measure of the probability that none of the coinciding peaks in the DFT spectra under consideration are due to noise.Results. Cinderella is a mathematical approach to a general statistical problem. Its potential reaches beyond photometry from ground or space to all cases where a quantitative statistical comparison of periodicities in different data sets is desired. Examples of the composed and the conditional Cinderella mode for different observation setups are presented.

Functional imaging studies of neurologically intact adults have demonstrated that the right posterior cerebellum is activated during verb generation, semantic processing, sentence processing, and verbal fluency. Studies of patients with cerebellar damage converge to show that the cerebellum supports sentence processing and verbal fluency. However, to date there are no patient studies that investigated the specific importance of the right posterior cerebellum in language processing, because: (i) case studies presented patients with lesions affecting the anterior cerebellum (with or without damage to the posterior cerebellum), and (ii) group studies combined patients with lesions to different cerebellar regions, without specifically reporting the effects of right posterior cerebellar damage. Here we investigated whether damage to the right posterior cerebellum is critical for sentence processing and verbal fluency in four patients with focal stroke damage to different parts of the right posterior cerebellum (all involving Crus II, and lobules VII and VIII). We examined detailed lesion location by going beyond common anatomical definitions of cerebellar anatomy (i.e., according to lobules or vascular territory), and employed a recently proposed functional parcellation of the cerebellum. All four patients experienced language difficulties that persisted for at least a month after stroke but three performed in the normal range within a year. In contrast, one patient with more damage to lobule IX than the other patients had profound long-lasting impairments in the comprehension and repetition of sentences, and the production of spoken sentences during picture description. Spoken and written word comprehension and visual recognition memory were also impaired, however, verbal fluency was within the normal range, together with object naming, visual perception and verbal short-term memory. This is the first study to show that focal damage to the right posterior cerebellum leads to language difficulties after stroke; and that processing impairments persisted in the case with most damage to lobule IX. We discuss these results in relation to current theories of cerebellar contribution to language processing. Overall, our study highlights the need for longitudinal studies of language function in patients with focal damage to different cerebellar regions, with functional imaging to understand the mechanisms that support recovery.

Tobacco smoking is associated with deleterious health outcomes. Most smokers want to quit smoking, yet relapse rates are high. Understanding neural differences associated with tobacco use may help generate novel treatment options. Several animal studies have recently highlighted the central role of the thalamus in substance use disorders, but this research focus has been understudied in human smokers. Here, we investigated associations between structural and functional magnetic resonance imaging measures of the thalamus and its subnuclei to distinct smoking characteristics. We acquired anatomical scans of 32 smokers as well as functional resting-state scans before and after a cue-reactivity task. Thalamic functional connectivity was associated with craving and dependence severity, whereas the volume of the thalamus was associated with dependence severity only. Craving, which fluctuates rapidly, was best characterized by differences in brain function, whereas the rather persistent syndrome of dependence severity was associated with both brain structural differences and function. Our study supports the notion that functional versus structural measures tend to be associated with behavioral measures that evolve at faster versus slower temporal scales, respectively. It confirms the importance of the thalamus to understand mechanisms of addiction and highlights it as a potential target for brain-based interventions to support smoking cessation, such as brain stimulation and neurofeedback.