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Even in the absence of specific sensory input or a behavioral task, the brain produces structured patterns of activity. This organized activity is modulated by changes in arousal. Here, we use wide-field voltage imaging to establish how arousal relates to cortical network voltage and hemodynamic activity in spontaneously behaving head-fixed male and female mice expressing the voltage-sensitive fluorescent FRET sensor Butterfly 1.2. We find that global voltage and hemodynamic signals are both positively correlated with changes in arousal with amaximum correlation of 0.5 and 0.25, respectively, at a time lag of 0 s. We next show that arousal influences distinct cortical regions for both voltage and hemodynamic signals. These include a broad positive correlation across most sensorymotor cortices extending posteriorly to the primary visual cortex observed in both signals. In contrast, activity in the prefrontal cortex is positively correlated to changes in arousal for the voltage signal while it is a slight net negative correlation observed in the hemodynamic signal. Additionally, we show that coherence between voltage and hemodynamic signals relative to arousal is strongest for slow frequencies below 0.15 Hz and is near zero for frequencies >1 Hz. We finally show that coupling patterns are dependent on the behavioral state of the animal with correlations being driven by periods of increased orofacial movement. Our results indicate that while hemodynamic signals show strong relations to behavior and arousal, these relations are distinct from those observed by voltage activity. [ABSTRACT FROM AUTHOR]

Author(s): Daniel A. Butts (corresponding author) [1, 2]; Chong Weng [3]; Jianzhong Jin [3]; Chun-I Yeh [3, 4]; Nicholas A. Lesica [1]; Jose-Manuel Alonso [3]; Garrett B. Stanley [1] The [...]

The electrolarynx (EL) voice prosthesis is widely used, but suffers from the inconvenience of requiring manual control. Therefore, a hands-free EL triggered by neck muscle electromyographic (EMG) activity was developed (EMG-EL). Signal processing circuitry in a belt-mounted control unit transforms EMG activity into control signals for initiation and termination of voicing. These control signals are then fed to an EL held against the neck by an inconspicuous brace. Performance of the EMG-EL was evaluated by comparison to normal voice, manual EL voice, and tracheo-esophageal (TE) voice in a series of reaction time experiments in seven normal subjects and one laryngectomy patient. The normal subjects produced voice initiation with the EMG-EL that was as fast as both normal voice and the manual EL. The laryngectomy subject produced voice initiation that was slower than with the manual EL, but faster than with TE voice. Voice termination with the EMG-EL was slower than normal voice for the normal subjects, but not significantly different than with the manual EL. The laryngectomy subject produced voice termination with the EMG-EL that was slower than with TE or manual EL. The EMG-EL threshold was set at 10% of the range of vocal-related EMG activity above baseline. Simulations of EMG-EL behavior showed that the 10% threshold was not significantly different from the optimum threshold produced through the process of error minimization. The EMG-EL voice reaction time appears to be adequate for use in a day-to-day conversation. Index Terms--Electromyography, prosthesis, voice.

As the tools to simultaneously record electrophysiological signals from large numbers of neurons within and across brain regions become increasingly available, this opens up for the first time the possibility of establishing the details of causal relationships between monosynaptically connected neurons and the patterns of neural activation that underlie perception and behavior. Although recorded activity across synaptically connected neurons has served as the cornerstone for much of what we know about synaptic transmission and plasticity, this has largely been relegated to ex vivo preparations that enable precise targeting under relatively well-controlled conditions. Analogous studies in vivo, where image-guided targeting is often not yet possible, rely on indirect, data-driven measures, and as a result such studies have been sparse and the dependence upon important experimental parameters has not been well studied. Here, using in vivo extracellular single-unit recordings in the topographically aligned rodent thalamocortical pathway, we sought to establish a general experimental and computational framework for inferring synaptic connectivity. Specifically, attacking this problem within a statistical signal detection framework utilizing experimentally recorded data in the ventral-posterior medial (VPm) region of the thalamus and the homologous region in layer 4 of primary somatosensory cortex (S1) revealed a trade-off between network activity levels needed for the data-driven inference and synchronization of nearby neurons within the population that results in masking of synaptic relationships. Here, we provide a framework for establishing connectivity in multisite, multielectrode recordings based on statistical inference, setting the stage for large-scale assessment of synaptic connectivity within and across brain structures. NEW & NOTEWORTHY Despite the fact that all brain function relies on the long-range transfer of information across different regions, the tools enabling us to measure connectivity across brain structures are lacking. Here, we provide a statistical framework for identifying and assessing potential monosynaptic connectivity across neuronal circuits from population spiking activity that generalizes to large-scale recording technologies that will help us to better understand the signaling within networks that underlies perception and behavior. [ABSTRACT FROM AUTHOR]