Effect of cognitive load on time spent offline during wakefulness

Humans continuously alternate between online attention to the current environment and offline attention to internally generated thought and imagery. This may be a fundamental feature of the waking brain, but remains poorly understood. Here, we took a data-driven approach to defining online and offline states of wakefulness, using machine learning methods applied to measures of sensory responsiveness, subjective report, electroencephalogram (EEG), and pupil diameter. We tested the effect of cognitive load on the structure and prevalence of online and offline states, hypothesizing that time spent offline would increase as cognitive load of an ongoing task decreased. We also expected that alternation between online and offline states would persist even in the absence of a cognitive task. As in prior studies, we arrived at a three-state model comprised of one online state and two offline states. As predicted, when cognitive load was high, more time was spent online. Also as predicted, the same three states were present even when participants were not performing a task. These observations confirm our method is successful at isolating seconds-long periods of offline time. Varying cognitive load may be a useful way to manipulate time spent in at least one of these offline states in future experimental studies.

Alpha EEG Activity and Pupil Diameter Coupling during Inactive Wakefulness in Humans

Variations in human behavior correspond to the adaptation of the nervous system to different internal and environmental demands. Attention, a cognitive process for weighing environmental demands, changes over time. Pupillary activity, which is affected by fluctuating levels of cognitive processing, appears to identify neural dynamics that relate to different states of attention. In mice, for example, pupil dynamics directly correlate with brain state fluctuations. Although, in humans, alpha-band activity is associated with inhibitory processes in cortical networks during visual processing, and its amplitude is modulated by attention, conclusive evidence linking this narrowband activity to pupil changes in time remains sparse. We hypothesize that, as alpha activity and pupil diameter indicate attentional variations over time, these two measures should be comodulated. In this work, we recorded the electroencephalographic (EEG) and pupillary activity of 16 human subjects who had their eyes fixed on a gray screen for 1 min. Our study revealed that the alpha-band amplitude and the high-frequency component of the pupil diameter covariate spontaneously. Specifically, the maximum alpha-band amplitude was observed to occur ∼300 ms before the peak of the pupil diameter. In contrast, the minimum alpha-band amplitude was noted to occur ∼350 ms before the trough of the pupil diameter. The consistent temporal coincidence of these two measurements strongly suggests that the subject’s state of attention, as indicated by the EEG alpha amplitude, is changing moment to moment and can be monitored by measuring EEG together with the diameter pupil.

Cortical State Fluctuations during Sensory Decision Making

In many behavioral tasks, cortex enters a desynchronized state where low-frequency fluctuations in population activity are suppressed. The precise behavioral correlates of desynchronization and its global organization are unclear. One hypothesis holds that desynchronization enhances stimulus coding in the relevant sensory cortex. Another hypothesis holds that desynchronization reflects global arousal, such as task engagement. Here, we trained mice on tasks where task engagement could be distinguished from sensory accuracy. Using widefield calcium imaging, we found that performance-related desynchronization was global and correlated better with engagement than with accuracy. Consistent with this link between desynchronization and engagement, rewards had a long-lasting desynchronizing effect. To determine whether engagement-related state changes depended on the relevant sensory modality, we trained mice on visual and auditory tasks and found that in both cases desynchronization was global, including regions such as somatomotor cortex. We conclude that variations in low-frequency fluctuations are predominately global and related to task engagement.

Brain-State-Dependent Modulation of Neuronal Firing and Membrane Potential Dynamics in the Somatosensory Thalamus during Natural Sleep

The thalamus plays a central role in sleep rhythms in the mammalian brain and, yet, surprisingly little is known about its function and interaction with local cortical oscillations during NREM sleep (NREM). We investigated the neuronal correlates of cortical barrel activity in the two corresponding thalamic nuclei, the ventral posterior medial (VPM), and the posterior medial (Pom) nuclei during natural NREM in mice. Our data reveal (1) distinct modulations of VPM and Pom activity throughout NREM episodes, (2) a thalamic nucleus-specific phase-locking to cortical slow and spindle waves, (3) cell-specific subthreshold spindle oscillations in VPM neurons that only partially overlap with cortical spindles, and (4) that spindle features evolve throughout NREM episodes and vary according to the post-NREM state. Taken together, our results suggest that, during natural sleep, the barrel cortex exerts a leading role in the generation and transfer of slow rhythms to the somatosensory thalamus and reciprocally for spindle oscillations.

Cortical state transitions and stimulus response evolve along stiff and sloppy parameter dimensions, respectively

Previous research showed that spontaneous neuronal activity presents sloppiness: the collective behavior is strongly determined by a small number of parameter combinations, defined as ‘stiff’ dimensions, while it is insensitive to many others (‘sloppy’ dimensions). Here, we analyzed neural population activity from the auditory cortex of anesthetized rats while the brain spontaneously transited through different synchronized and desynchronized states and intermittently received sensory inputs. We showed that cortical state transitions were determined by changes in stiff parameters associated with the activity of a core of neurons with low responses to stimuli and high centrality within the observed network. In contrast, stimulus-evoked responses evolved along sloppy dimensions associated with the activity of neurons with low centrality and displaying large ongoing and stimulus-evoked fluctuations without affecting the integrity of the network. Our results shed light on the interplay among stability, flexibility, and responsiveness of neuronal collective dynamics during intrinsic and induced activity.

Milliseconds of Sensory Input Abruptly Modulate the Dynamics of Cortical States for Seconds

Spontaneous internal activity plays a major role in higher brain functions. The question of how it modulates sensory evoked activity and behavior has been explored in anesthetized rodents, cats, monkeys and in behaving human subjects. However, the complementary question of how a brief sensory input modulates the internally generated activity in vivo remains unresolved, and high-resolution mapping of these bidirectional interactions was never performed. Integrating complementary methodologies, at population and single cells levels, we explored this question. Voltage-sensitive dye imaging of population activity in anesthetized rats' somatosensory cortex revealed that spontaneous up-states were largely diminished for ~2 s, even after a single weak whisker deflection. This effect was maximal at the stimulated barrel but spread across several cortical areas. A higher velocity whisker deflection evoked activity at ~15Hz. Two-photon calcium imaging activity and cell-attached recordings confirmed the VSD results and revealed that for several seconds most single cells decreased their firing, but a small number increased firing. Comparing single deflection with long train stimulation, we found a dominant effect of the first population spike. We suggest that, at the onset of a sensory input, some internal messages are silenced to prevent overloading of the processing of relevant incoming sensory information.

Visually Evoked Spiking Evolves While Spontaneous Ongoing Dynamics Persist

Neurons in the primary visual cortex spontaneously spike even when there are no visual stimuli. It is unknown whether the spiking evoked by visual stimuli is just a modification of the spontaneous ongoing cortical spiking dynamics or whether the spontaneous spiking state disappears and is replaced by evoked spiking. This study of laminar recordings of spontaneous spiking and visually evoked spiking of neurons in the ferret primary visual cortex shows that the spiking dynamics does not change: the spontaneous spiking as well as evoked spiking is controlled by a stable and persisting fixed point attractor. Its existence guarantees that evoked spiking return to the spontaneous state. However, the spontaneous ongoing spiking state and the visual evoked spiking states are qualitatively different and are separated by a threshold (separatrix). The functional advantage of this organization is that it avoids the need for a system reorganization following visual stimulation, and impedes the transition of spontaneous spiking to evoked spiking and the propagation of spontaneous spiking from layer 4 to layers 2-3.