Breakdown of effective connectivity during slow wave sleep: investigating the mechanism underlying a cortical gate using large-scale modeling

Unresponsiveness ≠ unconsciousness

Consciousness is subjective experience. During both sleep and anesthesia, consciousness is common, evidenced by dreaming. A defining feature of dreaming is that, while conscious, we do not experience our environment; we are disconnected. Besides inducing behavioral unresponsiveness, a key goal of anesthesia is to prevent the experience of surgery (connected consciousness), by inducing either unconsciousness or disconnection of consciousness from the environment. Review of the isolated forearm technique demonstrates that consciousness, connectedness, and responsiveness uncouple during anesthesia; in clinical conditions, a median 37% of patients demonstrate connected consciousness. We describe potential neurobiological constructs that can explain this phenomenon: during light anesthesia the subcortical mechanisms subserving spontaneous behavioral responsiveness are disabled but information integration within the corticothalamic network continues to produce consciousness, and unperturbed norepinephrinergic signaling maintains connectedness. These concepts emphasize the need for developing anesthetic regimens and depth of anesthesia monitors that specifically target mechanisms of consciousness, connectedness, and responsiveness.

Melatonin has membrane receptor-independent hypnotic action on neurons: an hypothesis

Melatonin, which is known to have sleep-promoting properties, has no morpho-physiological barriers and readily enters neurons and their subcellular compartments from both the blood and cerebrospinal fluid. It has multiple receptor-dependent and receptor-independent functions. Sleep is a neuronal function, and it can no longer be postulated that one or more anatomical structures fully control sleep. Neurons require sleep for metabolically driven restorative purposes, and as a result, the process of sleep is modulated by peripheral and central mechanisms. This is an important finding because it suggests that melatonin should have intracellular sleep-inducing properties. Based on recent evidence, it is proposed that melatonin induces sleep at the neuronal level independently of its membrane receptors. Thus, the hypnotic action of melatonin and the mechanisms involving the circadian rhythms are separate neurological functions. This is contrary to the presently accepted view.

Perceptual learning in Vision Research

Reports published in Vision Research during the late years of the 20th century described surprising effects of long-term sensitivity improvement with some basic visual tasks as a result of training. These improvements, found in adult human observers, were highly specific to simple visual features, such as location in the visual field, spatial-frequency, local and global orientation, and in some cases even the eye of origin. The results were interpreted as arising from the plasticity of sensory brain regions that display those features of specificity within their constituting neuronal subpopulations. A new view of the visual cortex has emerged, according to which a degree of plasticity is retained at adult age, allowing flexibility in acquiring new visual skills when the need arises. Although this "sensory plasticity" interpretation is often questioned, it is commonly believed that learning has access to detailed low-level visual representations residing within the visual cortex. More recent studies during the last decade revealed the conditions needed for learning and the conditions under which learning can be generalized across stimuli and tasks. The results are consistent with an account of perceptual learning according to which visual processing is remodeled by the brain, utilizing sensory information acquired during task performance. The stability of the visual system is viewed as an adaptation to a stable environment and instances of perceptual learning as a reaction of the brain to abrupt changes in the environment. Training on a restricted stimulus set may lead to perceptual overfitting and over-specificity. The systemic methodology developed for perceptual learning, and the accumulated knowledge, allows us to explore issues related to learning and memory in general, such as learning rules, reinforcement, memory consolidation, and neural rehabilitation. A persistent open question is the neuro-anatomical substrate underlying these learning effects.

Sleep and synaptic renormalization: a computational study

Recent evidence indicates that net synaptic strength in cortical and other networks increases during wakefulness and returns to a baseline level during sleep. These homeostatic changes in synaptic strength are accompanied by corresponding changes in sleep slow wave activity (SWA) and in neuronal firing rates and synchrony. Other evidence indicates that sleep is associated with an initial reactivation of learned firing patterns that decreases over time. Finally, sleep can enhance performance of learned tasks, aid memory consolidation, and desaturate the ability to learn. Using a large-scale model of the corticothalamic system equipped with a spike-timing dependent learning rule, in agreement with experimental results, we demonstrate a net increase in synaptic strength in the waking mode associated with an increase in neuronal firing rates and synchrony. In the sleep mode, net synaptic strength decreases accompanied by a decline in SWA. We show that the interplay of activity and plasticity changes implements a control loop yielding an exponential, self-limiting renormalization of synaptic strength. Moreover, when the model "learns" a sequence of activation during waking, the learned sequence is preferentially reactivated during sleep, and reactivation declines over time. Finally, sleep-dependent synaptic renormalization leads to increased signal-to-noise ratios, increased resistance to interference, and desaturation of learning capabilities. Although the specific mechanisms implemented in the model cannot capture the variety and complexity of biological substrates, and will need modifications in line with future evidence, the present simulations provide a unified, parsimonious account for diverse experimental findings coming from molecular, electrophysiological, and behavioral approaches.

Neurophysiological and computational principles of cortical rhythms in cognition

Synchronous rhythms represent a core mechanism for sculpting temporal coordination of neural activity in the brain-wide network. This review focuses on oscillations in the cerebral cortex that occur during cognition, in alert behaving conditions. Over the last two decades, experimental and modeling work has made great strides in elucidating the detailed cellular and circuit basis of these rhythms, particularly gamma and theta rhythms. The underlying physiological mechanisms are diverse (ranging from resonance and pacemaker properties of single cells to multiple scenarios for population synchronization and wave propagation), but also exhibit unifying principles. A major conceptual advance was the realization that synaptic inhibition plays a fundamental role in rhythmogenesis, either in an interneuronal network or in a reciprocal excitatory-inhibitory loop. Computational functions of synchronous oscillations in cognition are still a matter of debate among systems neuroscientists, in part because the notion of regular oscillation seems to contradict the common observation that spiking discharges of individual neurons in the cortex are highly stochastic and far from being clocklike. However, recent findings have led to a framework that goes beyond the conventional theory of coupled oscillators and reconciles the apparent dichotomy between irregular single neuron activity and field potential oscillations. From this perspective, a plethora of studies will be reviewed on the involvement of long-distance neuronal coherence in cognitive functions such as multisensory integration, working memory, and selective attention. Finally, implications of abnormal neural synchronization are discussed as they relate to mental disorders like schizophrenia and autism.

Cortical reactivity and effective connectivity during REM sleep in humans

We recorded the electroencephalographic (EEG) responses evoked by transcranial magnetic stimulation (TMS) during the first rapid eye movement (REM) sleep episode of the night and we compared them with the responses obtained during previous wakefulness and NREM sleep. Confirming previous findings, upon falling into NREM sleep, cortical activations became more local and stereotypical, indicating a significant impairment of the intracortical dialogue. During REM sleep, a state in which subjects regain consciousness but are almost paralyzed, TMS triggered more widespread and differentiated patterns of cortical activation, that were similar to the ones observed in wakefulness. Similarly, TMS/hd-EEG may be used to probe the internal dialogue of the thalamocortical system in brain injured patients that are unable to move and communicate.

Stimulation of the frontal eye field reveals persistent effective connectivity after controlled behavior

Our ability to choose nonhabitual controlled behavior instead of habitual automatic behavior is based on a flexible control mechanism subserved by neural activity representing the behavior-guiding rule. However, it has been shown that the behavior slows down more when switching from controlled to automatic behavior than vice versa. Here we show that persistent effective connectivity of the neural network after execution of controlled behavior is responsible for the behavioral slowing on a subsequent trial. We asked normal human subjects to perform a prosaccade or antisaccade task based on a cue and examined the effective connectivity of the neural network based on the pattern of neural impulse transmission induced by stimulation of the frontal eye field (FEF). Effective connectivity during the task preparation period was dependent on the task that subjects had performed on the previous trial, regardless of the upcoming task. The strength of this persistent effective connectivity was associated with saccade slowing especially on trials after controlled antisaccade. In contrast, the pattern of regional activation changed depending on the upcoming task regardless of the previous task and the decrease in activation was associated with errors in upcoming antisaccade task. These results suggest that the effective connectivity examined by FEF stimulation reflects a residual functional state of the network involved in performance of controlled antisaccade and its persistence may account for the behavioral slowing on the subsequent trial.

Breakdown in cortical effective connectivity during midazolam-induced loss of consciousness

By employing transcranial magnetic stimulation (TMS) in combination with high-density electroencephalography (EEG), we recently reported that cortical effective connectivity is disrupted during early non-rapid eye movement (NREM) sleep. This is a time when subjects, if awakened, may report little or no conscious content. We hypothesized that a similar breakdown of cortical effective connectivity may underlie loss of consciousness (LOC) induced by pharmacologic agents. Here, we tested this hypothesis by comparing EEG responses to TMS during wakefulness and LOC induced by the benzodiazepine midazolam. Unlike spontaneous sleep states, a subject's level of vigilance can be monitored repeatedly during pharmacological LOC. We found that, unlike during wakefulness, wherein TMS triggered responses in multiple cortical areas lasting for >300 ms, during midazolam-induced LOC, TMS-evoked activity was local and of shorter duration. Furthermore, a measure of the propagation of evoked cortical currents (significant current scattering, SCS) could reliably discriminate between consciousness and LOC. These results resemble those observed in early NREM sleep and suggest that a breakdown of cortical effective connectivity may be a common feature of conditions characterized by LOC. Moreover, these results suggest that it might be possible to use TMS-EEG to assess consciousness during anesthesia and in pathological conditions, such as coma, vegetative state, and minimally conscious state.

Dreaming and the brain: from phenomenology to neurophysiology

Dreams are a remarkable experiment in psychology and neuroscience, conducted every night in every sleeping person. They show that the human brain, disconnected from the environment, can generate an entire world of conscious experiences by itself. Content analysis and developmental studies have promoted understanding of dream phenomenology. In parallel, brain lesion studies, functional imaging and neurophysiology have advanced current knowledge of the neural basis of dreaming. It is now possible to start integrating these two strands of research to address fundamental questions that dreams pose for cognitive neuroscience: how conscious experiences in sleep relate to underlying brain activity; why the dreamer is largely disconnected from the environment; and whether dreaming is more closely related to mental imagery or to perception.