ABSTRACT
Electrical activity is essential for neuronal communication. Over the years, in vivo multielectrode recordings have revealed that the electrical activities of individual neurons are not independent of each other. Instead, neurons tend to re in a coordinated way within a given neural network. When measured as the electroencephalogram (EEG) or local eld potential (LFP) signals, this neural coordination results in complex oscillatory activity patterns, which reect synchronous synaptic potentials
Introduction ............................................................................................................ 145 Forebrain Dynamics In Different Wake-Sleep States ........................................... 146
Limitations of Existing State Identication Algorithms ............................ 148 State-Space Framework Reveals Global Brain States ........................................... 149
Data Collection ........................................................................................... 149 2-D State Space........................................................................................... 150 Global Brain States ..................................................................................... 153
Global Brain States: The Neural Correlates of Wake-Sleep States ....................... 154 State-Coding Algorithm ............................................................................. 154 Comparison against Behavioral State Coding ............................................ 155 Validation against EMG Activity in Mice .................................................. 155
Gradients and Functional Subdivisions Within Global Brain States ..................... 157 Forebrain Dynamics During State Transitions ...................................................... 159 General Discussion ................................................................................................ 161
Advantages and Limitations of the State-Space Framework...................... 161 The Driving Forces: Neuromodulatory Systems ........................................ 163 State-Dependent Information Processing and Memory Formation ........... 164
Conclusions ............................................................................................................ 165 References .............................................................................................................. 165
in a local network (Lopes da Silva 1991). Thus, unveiling the physiological mechanisms generating such complex oscillatory neural activity patterns is key to achieving a better understanding of how the brain operates in behaving animals.
