Molecular brain imaging using positron emission tomography (PET) has evolved into a vigorous academic field and is progressively gaining importance in the clinical arena. Significant progress has been made in the design of high-resolution three-dimensional (3-D) PET units dedicated to brain research and the development of quantitative imaging protocols incorporating accurate image correction techniques and sophisticated image reconstruction algorithms. However, emerging clinical and research applications of molecular brain imaging demand even greater levels of accuracy and precision and therefore impose more constraints with respect to the quantitative capability of PET. It has long been recognized that photon attenuation in tissues is the most important physical factor degrading PET image quality and quantitative accuracy. Quantitative PET image reconstruction requires an accurate attenuation map of the object under study for the purpose of attenuation compensation. Several methods have been devised to correct for photon attenuation in neurological PET studies. Significant attention has been devoted to optimizing computational performance and to balancing conflicting requirements. Approximate methods suitable for clinical routine applications and more complicated approaches for research applications, where there is greater emphasis on accurate quantitative measurements, have been proposed. The number of scientific contributions related to this subject has been increasing steadily, which motivated the writing of this review as a snapshot of the dynamically changing field of attenuation correction in cerebral 3D PET. This paper presents the physical and methodological basis of photon attenuation and summarizes state of the art developments in algorithms used to derive the attenuation map aiming at accurate attenuation compensation of brain PET data. Future prospects, research trends and challenges are identified and directions for future research are discussed.