Simon J. Makin is an auditory perception researcher turned science journalist. Originally from Liverpool, he has a Ph.D. in computational auditory modeling from the University of Sheffield. His writing has appeared in Nature, Scientific American and New Scientist, among other places.
Simon Makin
Science writer
From this contributor
Optimized two-photon microscopy enables voltage imaging at multiple depths
The tool could reveal how information flows within and between cortical layers during neural processing.
Optimized two-photon microscopy enables voltage imaging at multiple depths
Designer synapses edit brain circuits in living animals
The approach could help elucidate relationships between circuit structure and function, as well as the role of natural electrical synapses.
Designer synapses edit brain circuits in living animals
From 0 to 60 in 10 years
After a decade of fast-paced discovery, researchers are racing toward bigger datasets, more genes and a deeper understanding of the biology of autism.
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Finally, a new route for the magnetic-sense field
Researchers have dueled for years over how the magnetic sense works. New data from monarch butterflies could finally help settle the debate.
Finally, a new route for the magnetic-sense field
Researchers have dueled for years over how the magnetic sense works. New data from monarch butterflies could finally help settle the debate.
Sensory over-responsivity tied to autism, anxiety but not other conditions
Negative reactions to sensations track with certain neurodevelopmental traits in more than 15,000 children—pointing to shared neurobiological roots.
Sensory over-responsivity tied to autism, anxiety but not other conditions
Negative reactions to sensations track with certain neurodevelopmental traits in more than 15,000 children—pointing to shared neurobiological roots.
Neuromechanical models deepen our understanding of animal motor control
Thanks to recent progress in physics-based simulators and robotics, it has never been easier for neuroscientists to use neuromechanical modeling to test hypotheses about animal movement.
Neuromechanical models deepen our understanding of animal motor control
Thanks to recent progress in physics-based simulators and robotics, it has never been easier for neuroscientists to use neuromechanical modeling to test hypotheses about animal movement.