itative > > relations between number and size of elements, as a necessary contribution > > to general theories of cortical function (such as Hebb's Cell Assemblies or > > Moshe Abeles' Synfire Chains). > > All told, if you want to know "the most promising part of our work", I > > think it is a rather relaxed

on quantitative relations between number and size of elements, as a necessary contribution to general theories of cortical function (such as Hebb's Cell Assemblies or Moshe Abeles' Synfire Chains). All told, if you want to know "the most promising part of our work', I think it is a rather relaxed way of theory

on quantitative relations between number and size of elements, as a necessary contribution to general theories of cortical function (such as Hebb's Cell Assemblies or Moshe Abeles' Synfire Chains). All told, if you want to know "the most promising part of our work", I think it is a rather relaxed way of theory

itative > > relations between number and size of elements, as a necessary contribution > > to general theories of cortical function (such as Hebb's Cell Assemblies or > > Moshe Abeles' Synfire Chains). > > > > All told, if you want to know "the most promising part of our work", I > > think it is a rather rel

on quantitative relations between number and size of elements, as a necessary contribution to general theories of cortical function (such as Hebb's Cell Assemblies or Moshe Abeles' Synfire Chains). All told, if you want to know "the most promising part of our work", I think it is a rather relaxed way of theory

on quantitative relations between number and size of elements, as a necessary contribution to general theories of cortical function (such as Hebb's Cell Assemblies or Moshe Abeles' Synfire Chains). All told, if you want to know "the most promising part of our work", I think it is a rather relaxed way of theory

titative > relations between number and size of elements, as a necessary contribution > > to general theories of cortical function (such as Hebb's Cell Assemblies or > > Moshe Abeles' Synfire Chains). > > > > All told, if you want to know "the most promising part of our work", I > > think it is a rather rel

on quantitative relations between number and size of elements, as = necessary contribution to general theories of cortical function (such as He=b's Cell Assemblies or Moshe Abeles' Synfire Chains). All told, if you want to know "th= most promising part of our work", I think it is a rather relaxed way of theory

on quantitative relations between number and size of elements, as = necessary contribution to general theories of cortical function (such as He=b's Cell Assemblies or Moshe Abeles' Synfire Chains). All told, if you want to know "th= most promising part of our work", I think it is a rather relaxed way of theory

via Attractor Neural Networks 256 EFTA00623773 xviii Contents 13.4.1 The Hopfield neural net model 256 13.4.2 Knowledge Representation via Cell Assemblies 257 13.5 Neural Foundations of Learning 258 13.5.1 Hebbian Learning 258 13.5.2 Virtual Synapses and Hebbian Learning Between Assemblies

56 HOUSE_OVERSIGHT_012913 xviii Contents 13.4.1 The Hopfield neural net model ..............0..0 022 e eee 256 13.4.2 Knowledge Representation via Cell Assemblies .................2.05- 257 13.5 Neural Foundations of Learning ..........0 0.000 ee eee 258 13.5.1 Hebbian Learning............ 0.0.00 eee ete eee 25