Linda Geddes is a Bristol-based freelance journalist writing about biology, medicine and technology. Born in Cambridge, she graduated from the University of Liverpool with a first-class degree in cell biology. She spent nine years as an editor and reporter for New Scientist magazine and has received numerous awards for her journalism, including winning the Association of British Science Writers’ award for best investigative journalism and being shortlisted for the Paul Foot Award. Her first book, Bumpology: The myth-busting pregnancy book for curious parents-to-be, was published in 2013.
Linda Geddes
From this contributor
How genetics is revealing rare childhood conditions
A pioneering project is showing how, 17 years since the first draft of the human genome, our genes are giving up their secrets and bringing hope to parents around the world.
How genetics is revealing rare childhood conditions
Explore more from The Transmitter
The illusion of AI consciousness: Lessons from human unconscious processing
Complex, goal-directed and even emotionally responsive behavior can unfold without awareness, providing a useful lens for interpreting artificial systems.
The illusion of AI consciousness: Lessons from human unconscious processing
Complex, goal-directed and even emotionally responsive behavior can unfold without awareness, providing a useful lens for interpreting artificial systems.
‘Push-pull’ recipe for neural wiring used in multiple brain regions
A versatile pair of proteins steers neurons toward their targets and helps establish the brain’s sensory maps, new studies suggest.
‘Push-pull’ recipe for neural wiring used in multiple brain regions
A versatile pair of proteins steers neurons toward their targets and helps establish the brain’s sensory maps, new studies suggest.
Reward-learning algorithm hardwired into dopamine circuit
The finding bolsters the canonical model of reward prediction error, which has come under scrutiny in recent years.
Reward-learning algorithm hardwired into dopamine circuit
The finding bolsters the canonical model of reward prediction error, which has come under scrutiny in recent years.