An artificial neural network for automated behavioral state classification in rats.

Accurate behavioral state classification is critical for many research applications. Researchers typically rely upon manual identification of behavioral state through visual inspection of electrophysiological signals, but this approach is time intensive and subject to low inter-rater reliability. To overcome these limitations, a diverse set of algorithmic approaches have been put forth to automate the classification process.

Interindividual differences in memory system local field potential activity predict behavioral strategy on a dual-solution T-maze.

Individuals can use diverse behavioral strategies to navigate their environment including hippocampal-dependent place strategies reliant upon cognitive maps and striatal-dependent response strategies reliant upon egocentric body turns. The existence of multiple memory systems appears to facilitate successful navigation across a wide range of environmental and physiological conditions. The mechanisms by which these systems interact to ultimately generate a unitary behavioral response, however, remain unclear.

Infraslow coordination of slow wave activity through altered neuronal synchrony.

Slow wave activity (SWA; the EEG power between 0.5 and 4 Hz during non-rapid eye movement sleep [NREM]) is the best electrophysiological marker of sleep need; SWA dissipates across the night and increases following sleep deprivation. In addition to these well-documented homeostatic SWA trends, SWA exhibits extensive variability across shorter timescales (seconds to minutes) and between local cortical regions.

Cortical zeta-inhibitory peptide injection reduces local sleep need.

Local sleep need within cortical circuits exhibits extensive interregional variability and appears to increase following learning during preceding waking. Although the biological mechanisms responsible for generating sleep need are unclear, this local variability could arise as a consequence of wake-dependent synaptic plasticity. To test whether cortical synaptic strength is a proximate driver of sleep homeostasis, we developed a novel experimental approach to alter local sleep need.

Spontaneous Infraslow Fluctuations Modulate Hippocampal EPSP-PS Coupling.

Extensive trial-to-trial variability is a hallmark of most behavioral, cognitive, and physiological processes. Spontaneous brain activity (SBA), a ubiquitous phenomenon that coordinates levels and patterns of neuronal activity throughout the brain, may contribute to this variability by dynamically altering neuronal excitability. In freely-behaving male rats, we observed extensive variability of the hippocampal evoked response across 28-min recording periods despite maintaining constant stimulation parameters of the medial perforant path.

Sleep/wake dependent changes in cortical glucose concentrations.

Most of the energy in the brain comes from glucose and supports glutamatergic activity. The firing rate of cortical glutamatergic neurons, as well as cortical extracellular glutamate levels, increase with time spent awake and decline throughout non rapid eye movement sleep, raising the question whether glucose levels reflect behavioral state and sleep/wake history. Here chronic (2-3 days) electroencephalographic recordings in the rat cerebral cortex were coupled with fixed-potential amperometry to monitor the extracellular concentration of glucose ([gluc]) on a second-by-second basis across the spontaneous sleep-wake cycle and in response to 3 h of sleep deprivation.

Extracellular levels of lactate, but not oxygen, reflect sleep homeostasis in the rat cerebral cortex.

Study Objective: It is well established that brain metabolism is higher during wake and rapid eye movement (REM) sleep than in nonrapid eye movement (NREM) sleep. Most of the brain's energy is used to maintain neuronal firing and glutamatergic transmission. Recent evidence shows that cortical firing rates, extracellular glutamate levels, and markers of excitatory synaptic strength increase with time spent awake and decline throughout NREM sleep.

Long-term homeostasis of extracellular glutamate in the rat cerebral cortex across sleep and waking states.

Neuronal firing patterns, neuromodulators, and cerebral metabolism change across sleep-waking states, and the synaptic release of glutamate is critically involved in these processes. Extrasynaptic glutamate can also affect neural function and may be neurotoxic, but whether and how extracellular glutamate is regulated across sleep-waking states is unclear. To assess the effect of behavioral state on extracellular glutamate at high temporal resolution, we recorded glutamate concentration in prefrontal and motor cortex using fixed-potential amperometry in freely behaving rats.