Up and Down States of Cortical Neurons in Focal Limbic Seizures.

Recent work suggests an important role for cortical-subcortical networks in seizure-related loss of consciousness. Temporal lobe seizures disrupt subcortical arousal systems, which may lead to depressed cortical function and loss of consciousness. Extracellular recordings show ictal neocortical slow waves at about 1 Hz, but it is not known whether these simply represent seizure propagation or alternatively deep sleep-like activity, which should include cortical neuronal Up and Down states. In this study, using in vivo whole-cell recordings in a rat model of focal limbic seizures, we directly examine the electrophysiological properties of cortical neurons during seizures and deep anesthesia. We found that during seizures, the membrane potential of frontal cortical secondary motor cortex layer 5 neurons fluctuates between Up and Down states, with decreased input resistance and increased firing rate in Up states when compared to Down states. Importantly, Up and Down states in seizures are not significantly different from those in deep anesthesia, in terms of membrane potential, oscillation frequency, firing rate, and input resistance. By demonstrating these fundamental similarities in cortical electrophysiology between deep anesthesia and seizures, our results support the idea that a state of decreased cortical arousal may contribute to mechanisms of loss of consciousness during seizures.

Default mode and visual network activity in an attention task: Direct measurement with intracranial EEG.

Dynamic attention states are necessary to navigate the ever changing task demands of daily life. Previous investigations commonly utilize a block paradigm to study sustained and transient changes in attention networks. fMRI investigations have shown that sustained attention in visual block design attention tasks corresponds to decreased signal in the default mode and visual processing networks. While task negative networks are anticipated to decrease during active task engagement, it is unexpected that visual networks would also be suppressed during a visual task where event-related fMRI studies have found transient increases to visual stimuli. To resolve these competing results, the current investigations utilized intracranial EEG to directly interrogate visual and default mode network dynamics during a visual continuous performance task. We used the electrophysiological data to model expected fMRI signals and to maximize interpretation of current results with previous investigations. Results show broadband gamma power decreases in the default mode network, corresponding to previous EEG and fMRI findings. Meanwhile, visual processing regions including the primary visual cortex and fusiform gyrus demonstrate both sustained decreases during task engagement and stimuli-driven transient increases in gamma power. Modeled fMRI based on gamma power reproduces signal decreases reported in the fMRI literature, and emphasizes the insensitivity of fMRI to transient, regularly spaced signal changes embedded within sustained network dynamics. The signal processing functions of the dynamic visual and default mode network changes explored in this study are unknown but may be elucidated through further investigation.