A Parametric Framework to Generate Visual Illusions Using Python.

Visual illusions are fascinating phenomena that have been used and studied by artists and scientists for centuries, leading to important discoveries about the neurocognitive underpinnings of perception, consciousness, and neuropsychiatric disorders such as schizophrenia or autism. Surprisingly, despite their historical and theoretical importance as psychological stimuli, there is no dedicated software, nor consistent approach, to generate illusions in a systematic fashion. Instead, scientists have to craft them by hand in an idiosyncratic fashion, or use pre-made images not tailored for the specific needs of their studies. This, in turn, hinders the reproducibility of illusion-based research, narrowing possibilities for scientific breakthroughs and their applications. With the aim of addressing this gap, Pyllusion is a Python-based open-source software (freely available at https://github.com/RealityBending/Pyllusion), that offers a framework to manipulate and generate illusions in a systematic way, compatible with different output formats such as image files (.png, .jpg, .tiff, etc.) or experimental software (such as PsychoPy).

Ethical issues in the clinical application of fMRI: factors affecting the validity and interpretation of activations.

The ability of functional magnetic resonance imaging (fMRI) to localize activations in a single patient, along with the safety and widespread availability of this methodology, has lead to an increasing use of fMRI for clinical purposes such as pre-surgical planning. As methodology continues to improve and more experience with fMRI in the clinical setting is acquired, clinical functional neuroimaging will likely have an increasing influence over patient care. Therefore, ethical use of fMRI, as with other medical techniques, requires understanding the factors impacting the interpretation of the methodology. Issues affecting the validity and interpretation of clinical functional neuroimaging, including effects of altered hemodynamic response function, head motion, and structural changes in the brain, are reviewed. The distinction between correlated and necessary activation in a clinical context is discussed. Different types of statistical errors in fMRI analysis are described, along with their consequences to the patient. Finally, for the future of clinical fMRI development, the need for normative patient data, as well as standardized tasks, scan protocols, and data analyses, is discussed.