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Periods of rhythmic slow-wave activity during physiological slow-wave sleep or induced by anesthesia are characterized by a waxing and waning of spontaneous neuronal firing coordinated between cortex and thalamus. This activity is generated in the cortex but influences neuronal excitability and stimulus–response properties of neuronal networks throughout the brain (Steriade et al., 1993; Stroh et al., 2013; McGinley et al., 2015b). The corresponding low-frequency component of field potential recordings reflects alternating active states, in which cells are depolarized and synaptic activity is high, and silent states with hyperpolarized membrane potentials and low synaptic activity (Steriade et al., 2001; Timofeev et al., 2001). In contrast, waking is generally associated with continuous depolarization of cortical neurons, resulting in persistent activity (Destexhe et al., 2007; Sheroziya and Timofeev, 2015) and suppression of silent states (Steriade et al., 2001; McGinley et al., 2015b). In their recent study, Sheroziya and Timofeev (2015) demonstrated that moderate cortical cooling (to 29–31°C) of lightly ketamine/xylazin (ket/xyl) anesthetized or non-anesthetized mice reversibly diminished silent states and induced a persistent active state of the cortex. Mild heating (to 39–40°C), in contrast, increased rhythmicity of slow waves. Under deep ket/xyl anesthesia, cortical cooling disrupted slow waves and promoted bursts of activity correlated with thalamic firing. Local cooling of somatosensory cortex was shown to be sufficient to induce a shift from slow-wave to wide-spread persistent cortical activity, extending to the thalamus as well as the contralateral hemisphere. These results suggest that cortical temperature change can be used as a bidirectional and reversible tool for investigating global brain state fluctuations, and provide evidence that the thalamocortical network rapidly reacts upon local depolarization of a small neuronal population with wide-spread shifts of brain state. ...
Operating in a reverberating regime enables rapid tuning of network states to task requirements
(2018)
Neural circuits are able to perform computations under very diverse conditions and requirements. The required computations impose clear constraints on their fine-tuning: a rapid and maximally informative response to stimuli in general requires decorrelated baseline neural activity. Such network dynamics is known as asynchronous-irregular. In contrast, spatio-temporal integration of information requires maintenance and transfer of stimulus information over extended time periods. This can be realized at criticality, a phase transition where correlations, sensitivity and integration time diverge. Being able to flexibly switch, or even combine the above properties in a task-dependent manner would present a clear functional advantage. We propose that cortex operates in a "reverberating regime" because it is particularly favorable for ready adaptation of computational properties to context and task. This reverberating regime enables cortical networks to interpolate between the asynchronous-irregular and the critical state by small changes in effective synaptic strength or excitation-inhibition ratio. These changes directly adapt computational properties, including sensitivity, amplification, integration time and correlation length within the local network. We review recent converging evidence that cortex in vivo operates in the reverberating regime, and that various cortical areas have adapted their integration times to processing requirements. In addition, we propose that neuromodulation enables a fine-tuning of the network, so that local circuits can either decorrelate or integrate, and quench or maintain their input depending on task. We argue that this task-dependent tuning, which we call "dynamic adaptive computation," presents a central organization principle of cortical networks and discuss first experimental evidence.