Sophie Heywood, Samantha Bunzli, Miriam Dillon, Nadia Bicchi, Susan Black, Philippa Hemus, Eva Bogatek, Jenny Setchell
Trauma-informed physiotherapy and the principles of safety, trustworthiness, choice, collaboration, and empowerment: a qualitative study
Physiotherapy theory and practice
neuroscience focused detailed implementation computation studying neural codes dynamics circuits machine learning however artificial neural networks tend eschew precisely designed codes dynamics circuits favor brute force optimization cost function often using simple relatively uniform initial architectures two recent developments emerged within machine learning create opportunity connect seemingly divergent perspectives first structured architectures used including dedicated systems attention recursion various forms short longterm memory storage second cost functions training procedures become complex varied across layers time think brain terms ideas hypothesize 1 brain optimizes cost functions 2 cost functions diverse differ across brain locations development 3 optimization operates within prestructured architecture matched computational problems posed behavior support hypotheses argue range implementations credit assignment multiple layers neurons compatible current knowledge neural circuitry brains specialized systems interpreted enabling efficient optimization specific problem classes heterogeneously optimized system enabled series interacting cost functions serves make learning dataefficient precisely targeted needs organism suggest directions neuroscience could seek refine test hypotheses