Cortical mechanisms of spatial hearing

Humans and other animals use spatial hearing to rapidly localize events in the environment. However, neural encoding of sound location is a complex process involving the computation and integration of multiple spatial cues that are not represented directly in the sensory organ (the cochlea). Our understanding of these mechanisms has increased enormously in the past few years. Current research is focused on the contribution of animal models for understanding human spatial audition, the effects of behavioural demands on neural sound location encoding, the emergence of a cue-independent location representation in the auditory cortex, and the relationship between single-source and concurrent location encoding in complex auditory scenes. Furthermore, computational modelling seeks to unravel how neural representations of sound source locations are derived from the complex binaural waveforms of real-life sounds. In this article, we review and integrate the latest insights from neurophysiological, neuroimaging and computational modelling studies of mammalian spatial hearing. We propose that the cortical representation of sound location emerges from recurrent processing taking place in a dynamic, adaptive network of early (primary) and higher-order (posterior-dorsal and dorsolateral prefrontal) auditory regions. This cortical network accommodates changing behavioural requirements and is especially relevant for processing the location of real-life, complex sounds and complex auditory scenes

Discovering and Validating Cancer Genetic Dependencies: Approaches and Pitfalls

Cancer 'genetic dependencies' - genes whose products are essential for cancer cell fitness - are promising targets for therapeutic development. However, recent evidence has cast doubt on the validity of several putative dependencies that are currently being targeted in cancer clinical trials, underscoring the challenges inherent in correctly identifying cancer-essential genes. Here we review several common techniques and platforms for discovering and characterizing cancer dependencies. We discuss the strengths and drawbacks of different gene-perturbation approaches, and we highlight the use of poorly validated genetic and pharmacological agents as a common cause of target misidentification. A careful consideration of the limitations of current technologies and cancer models will improve our ability to correctly uncover cancer genetic dependencies and will facilitate the development of improved therapeutic agents