Higher order visual areas enhance stimulus responsiveness in mouse primary visual cortex.

Over the past few years, the various areas that surround the primary visual cortex (V1) in the mouse have been associated with many functions, ranging from higher order visual processing to decision-making. Recently, some studies have shown that higher order visual areas influence the activity of the primary visual cortex, refining its processing capabilities. Here, we studied how in vivo optogenetic inactivation of two higher order visual areas with different functional properties affects responses evoked by moving bars in the primary visual cortex. In contrast with the prevailing view, our results demonstrate that distinct higher order visual areas similarly modulate early visual processing. In particular, these areas enhance stimulus responsiveness in the primary visual cortex, by more strongly amplifying weaker compared with stronger sensory-evoked responses (for instance specifically amplifying responses to stimuli not moving along the direction preferred by individual neurons) and by facilitating responses to stimuli entering the receptive field of single neurons. Such enhancement, however, comes at the expense of orientation and direction selectivity, which increased when the selected higher order visual areas were inactivated. Thus, feedback from higher order visual areas selectively amplifies weak sensory-evoked V1 responses, which may enable more robust processing of visual stimuli.

Heart rate detection by Fitbit ChargeHR™ : A validation study versus portable polysomnography.

Consumer "Smartbands" can collect physiological parameters, such as heart rate (HR), continuously across the sleep-wake cycle. Nevertheless, the quality of HR data detected by such devices and their place in the research and clinical field is debatable, as they are rarely rigorously validated. The objective of the present study was to investigate the reliability of pulse photoplethysmographic detection by the Fitbit ChargeHR™ (FBCHR, Fitbit Inc.) in a natural setting of continuous recording across vigilance states. To fulfil this aim, concurrent portable polysomnographic (pPSG) and the Fitbit's photoplethysmographic data were collected from a group of 25 healthy young adults, for ≥12 hr. The pPSG-derived HR was automatically computed and visually verified for each 1-min epoch, while the FBCHR HR measurements were downloaded from the application programming interface provided by the manufacturer. The FBCHR was generally accurate in estimating the HR, with a mean (SD) difference of -0.66 (0.04) beats/min (bpm) versus the pPSG-derived HR reference, and an overall Pearson's correlation coefficient (r) of 0.93 (average per participant r = 0.85 ± 0.11), regardless of vigilance state. The correlation coefficients were larger during all sleep phases (rapid eye movement, r = 0.9662; N1, r = 0.9918; N2, r = 0.9793; N3, r = 0.9849) than in wakefulness (r = 0.8432). Moreover, the correlation coefficient was lower for HRs of >100 bpm (r = 0.374) than for HRs of <100 bpm (r = 0.84). Consistently, Bland-Altman analysis supports the overall higher accuracy in the detection of HR during sleep. The relatively high accuracy of FBCHR pulse rate detection during sleep makes this device suitable for sleep-related research applications in healthy participants, under free-living conditions.

Consciousness Regained: Disentangling Mechanisms, Brain Systems, and Behavioral Responses.

How consciousness (experience) arises from and relates to material brain processes (the "mind-body problem") has been pondered by thinkers for centuries, and is regarded as among the deepest unsolved problems in science, with wide-ranging theoretical, clinical, and ethical implications. Until the last few decades, this was largely seen as a philosophical topic, but not widely accepted in mainstream neuroscience. Since the 1980s, however, novel methods and theoretical advances have yielded remarkable results, opening up the field for scientific and clinical progress. Since a seminal paper by Crick and Koch (1998) claimed that a science of consciousness should first search for its neural correlates (NCC), a variety of correlates have been suggested, including both content-specific NCCs, determining particular phenomenal components within an experience, and the full NCC, the neural substrates supporting entire conscious experiences. In this review, we present recent progress on theoretical, experimental, and clinical issues. Specifically, we (1) review methodological advances that are important for dissociating conscious experience from related enabling and executive functions, (2) suggest how critically reconsidering the role of the frontal cortex may further delineate NCCs, (3) advocate the need for general, objective, brain-based measures of the capacity for consciousness that are independent of sensory processing and executive functions, and (4) show how animal studies can reveal population and network phenomena of relevance for understanding mechanisms of consciousness.

Visual Stimulus Detection Correlates with the Consistency of Temporal Sequences within Stereotyped Events of V1 Neuronal Population Activity.

UNLABELLED: Sensory information about the world is translated into rate codes, such that modulations in mean spiking activity of neurons relate to differences in stimulus features. More recently, it has been proposed that also temporal properties of activity, such as assembly formation and sequential population activation, are important for understanding the relation between neuronal activity and behavioral output. These phenomena appear to be robust properties of neural circuits, but their relevance for perceptual judgments, such as the behavioral detection of stimuli, remains to be tested. Studying neuronal activity with two-photon calcium imaging in primary visual cortex of mice performing a go/no-go visual detection task, we found that assemblies (i.e., configurations of neuronal group activity) reliably recur, as defined using Ward-method clustering. However, population activation events with a recurring configuration of core neurons did not appear to serve a particular function in the coding of orientation or the detection of stimuli. Instead, we found that, regardless of whether the population event showed a recurring or nonrecurring configuration of neurons, the sequence of cluster activation was correlated with the detection of stimuli. Moreover, each neuron showed a preferred temporal position of activation within population events, which was robust despite varying neuronal participation. Furthermore, the timing of neuronal activity within such a sequence was more consistent when a stimulus was detected (hits) than when it remained unreported (misses). Our data indicate that neural processing of information related to visual detection behavior depends on the temporal positioning of individual and group-wise cell activity. SIGNIFICANCE STATEMENT: Temporally coactive neurons have been hypothesized to form functional assemblies that might subserve different functions in the brain, but many of these proposed functions have not yet been experimentally tested. We used two-photon calcium imaging in V1 of mice performing a stimulus detection task to study the relation of assembly activity to the behavioral detection of visual stimuli. We found that the presence of recurring assemblies per se was not correlated with behavior, and these assemblies did not appear to serve a function in the coding of stimulus orientation. Instead, we found that activity in V1 is characterized by population events of varying membership, within which the consistency of the temporal sequence of neuronal activation is correlated with stimulus detection.

Spike-Based Functional Connectivity in Cerebral Cortex and Hippocampus: Loss of Global Connectivity Is Coupled to Preservation of Local Connectivity During Non-REM Sleep.

UNLABELLED: Behavioral states are commonly considered global phenomena with homogeneous neural determinants. However, recent studies indicate that behavioral states modulate spiking activity with neuron-level specificity as a function of brain area, neuronal subtype, and preceding history. Although functional connectivity also strongly depends on behavioral state at a mesoscopic level and is globally weaker in non-REM (NREM) sleep and anesthesia than wakefulness, it is unknown how neuronal communication is modulated at the cellular level. We hypothesize that, as for neuronal activity, the influence of behavioral states on neuronal coupling strongly depends on type, location, and preceding history of involved neurons. Here, we applied nonlinear, information-theoretical measures of functional connectivity to ensemble recordings with single-cell resolution to quantify neuronal communication in the neocortex and hippocampus of rats during wakefulness and sleep. Although functional connectivity (measured in terms of coordination between firing rate fluctuations) was globally stronger in wakefulness than in NREM sleep (with distinct traits for cortical and hippocampal areas), the drop observed during NREM sleep was mainly determined by a loss of inter-areal connectivity between excitatory neurons. Conversely, local (intra-area) connectivity and long-range (inter-areal) coupling between interneurons were preserved during NREM sleep. Furthermore, neuronal networks that were either modulated or not by a behavioral task remained segregated during quiet wakefulness and NREM sleep. These results show that the drop in functional connectivity during wake-sleep transitions globally holds true at the cellular level, but confine this change mainly to long-range coupling between excitatory neurons. SIGNIFICANCE STATEMENT: Studies performed at a mesoscopic level of analysis have shown that communication between cortical areas is disrupted in non-REM sleep and anesthesia. However, the neuronal determinants of this phenomenon are not known. Here, we applied nonlinear, information-theoretical measures of functional coupling to multi-area tetrode recordings from freely moving rats to investigate whether and how brain state modulates coordination between individual neurons. We found that the previously observed drop in functional connectivity during non-REM (NREM) sleep can be explained by a decrease in coupling between excitatory neurons located in distinct brain areas. Conversely, intra-area communication and coupling between interneurons are preserved. Our results provide significant new insights into the neuron-level mechanisms responsible for the loss of consciousness occurring in NREM sleep.

Local sleep in awake rats.

In an awake state, neurons in the cerebral cortex fire irregularly and electroencephalogram (EEG) recordings display low-amplitude, high-frequency fluctuations. During sleep, neurons oscillate between 'on' periods, when they fire as in an awake brain, and 'off' periods, when they stop firing altogether and the EEG displays high-amplitude slow waves. However, what happens to neuronal firing after a long period of being awake is not known. Here we show that in freely behaving rats after a long period in an awake state, cortical neurons can go briefly 'offline' as in sleep, accompanied by slow waves in the local EEG. Neurons often go offline in one cortical area but not in another, and during these periods of 'local sleep', the incidence of which increases with the duration of the awake state, rats are active and display an 'awake' EEG. However, they are progressively impaired in a sugar pellet reaching task. Thus, although both the EEG and behaviour indicate wakefulness, local populations of neurons in the cortex may be falling asleep, with negative consequences for performance.

Slow cortical rhythms: from single-neuron electrophysiology to whole-brain imaging in vivo.

The slow cortical oscillation is the major brain rhythm occurring during sleep, and has been the object of thorough investigation for over thirty years. Despite all these efforts, the function and the neuronal mechanisms behind slow cortical rhythms remain only partially understood. In this review we will provide an overview of the techniques available for the in vivo study of slow cortical oscillations in animal models. Our goal is to provide an up to date resource for the selection of the best experimental strategies to study specific aspects of slow oscillations. We will cover both traditional, population-level electrophysiological approaches (electroencephalography - EEG, local field potentials) as well as more recent techniques, such as two photon calcium imaging and optogenetics. Overall, we believe that new breakthroughs in our understanding of slow cortical rhythms will require the integration of different techniques, to bridge the gap between different spatio-temporal scales and go from a correlative to a causal level of analysis.

A switch from inter-ocular to inter-hemispheric suppression following monocular deprivation in the rat visual cortex.

Binocularity is a key property of primary visual cortex (V1) neurons that is widely used to study synaptic integration in the brain and plastic mechanisms following an altered visual experience. However, it is not clear how the inputs from the two eyes converge onto binocular neurons, and how their interaction is modified by an unbalanced visual drive. Here, using visual evoked potentials recorded in the juvenile rat V1, we report evidence for a suppressive mechanism by which contralateral eye activity inhibits responses from the ipsilateral eye. Accordingly, we found a lack of additivity of the responses evoked independently by the two eyes in the V1, and acute silencing of the contralateral eye resulted in the enhancement of ipsilateral eye responses in cortical neurons. We reverted the relative cortical strength of the two eyes by suturing the contralateral eye shut [monocular deprivation (MD)]. After 7 days of MD, there was a loss of interocular suppression mediated by the contralateral, deprived eye, and weak inputs from the closed eye were functionally inhibited by interhemispheric callosal pathways. We conclude that interocular suppressive mechanisms play a crucial role in shaping normal binocularity in visual cortical neurons, and a switch from interocular to interhemispheric suppression represents a key step in the ocular dominance changes induced by MD. These data have important implications for a deeper understanding of the key mechanisms that underlie activity-dependent rearrangements of cortical circuits following alteration of sensory experience.

Triple dissociation of visual, auditory and motor processing in mouse primary visual cortex.

Primary sensory cortices respond to crossmodal stimuli-for example, auditory responses are found in primary visual cortex (V1). However, it remains unclear whether these responses reflect sensory inputs or behavioral modulation through sound-evoked body movement. We address this controversy by showing that sound-evoked activity in V1 of awake mice can be dissociated into auditory and behavioral components with distinct spatiotemporal profiles. The auditory component began at approximately 27 ms, was found in superficial and deep layers and originated from auditory cortex. Sound-evoked orofacial movements correlated with V1 neural activity starting at approximately 80-100 ms and explained auditory frequency tuning. Visual, auditory and motor activity were expressed by different laminar profiles and largely segregated subsets of neuronal populations. During simultaneous audiovisual stimulation, visual representations remained dissociable from auditory-related and motor-related activity. This three-fold dissociability of auditory, motor and visual processing is central to understanding how distinct inputs to visual cortex interact to support vision.

The neural and computational architecture of feedback dynamics in mouse cortex during stimulus report.

Conscious reportability of visual input is associated with a bimodal neural response in primary visual cortex (V1): an early-latency response coupled to stimulus features and a late-latency response coupled to stimulus report or detection. This late wave of activity, central to major theories of consciousness, is thought to be driven by prefrontal cortex (PFC), responsible for "igniting" it. Here we analyzed two electrophysiological studies in mice performing different stimulus detection tasks, and characterize neural activity profiles in three key cortical regions: V1, posterior parietal cortex (PPC) and PFC. We then developed a minimal network model, constrained by known connectivity between these regions, reproducing the spatio-temporal propagation of visual- and report-related activity. Remarkably, while PFC was indeed necessary to generate report-related activity in V1, this occurred only through the mediation of PPC. PPC, and not PFC, had the final veto in enabling the report-related late wave of V1 activity.Significance statement A long-standing objective in the study of consciousness is to characterize the neural signatures of perceived compared to non-perceived sensory stimuli. In particular, the role of different cortical areas in the generation of consciousness is actively debate. Here we combined electrophysiological and modeling studies to investigate the mechanistic role of individual connections between brain regions in the generation of the activity patterns observed during conscious report. We found that, while frontal areas initiate report-related activity, parietal cortex acts as a gate to determine whether such activity will propagate back to visual cortex. This division of labor between prefrontal and parietal cortices is unexplained by current theoretical models of consciousness and therefore should strongly impact mechanistic neural models of conscious report.

Cortical source of blink-related delta oscillations and their correlation with levels of consciousness.

Recently, blink-related delta oscillations (delta BROs) have been observed in healthy subjects during spontaneous blinking at rest. Delta BROs have been linked with continuous gathering of information from the surrounding environment, which is classically attributed to the precuneus. Furthermore, fMRI studies have shown that precuneal activity is reduced or missing when consciousness is low or absent. We therefore hypothesized that the source of delta BROs in healthy subjects could be located in the precuneus and that delta BROs could be absent or reduced in patients with disorders of consciousness (DOC). To test these hypotheses, electroencephalographic (EEG) activity at rest was recorded in 12 healthy controls and nine patients with DOC (four vegetative states, and five minimally conscious states). Three-second-lasting EEG epochs centred on each blink instance were analyzed in both time- (BROs) and frequency domains (event-related spectral perturbation or ERSP and intertrial coherence or ITC). Cortical sources of the maximum blink-related delta power, corresponding to the positive peak of the delta BROs, were estimated by standardized Low Resolution Electromagnetic Tomography. In control subjects, as expected, the source of delta BROs was located in the precuneus, whereas in DOC patients, delta BROs were not recognizable and no precuneal localization was possible. Furthermore, we observed a direct relationship between spectral indexes and levels of cognitive functioning in all subjects participating in the study. This reinforces the hypothesis that delta BROs reflect neural processes linked with awareness of the self and of the environment.

Prolonged wakefulness alters neuronal responsiveness to local electrical stimulation of the neocortex in awake rats..

Prolonged wakefulness or a lack of sleep lead to cognitive deficits, but little is known about the underlying cellular mechanisms. We recently found that sleep deprivation affects spontaneous neuronal activity in the neocortex of sleeping and awake rats. While it is well known that synaptic responses are modulated by ongoing cortical activity, it remains unclear whether prolonged waking affects responsiveness of cortical neurons to incoming stimuli. By applying local electrical microstimulation to the frontal area of the neocortex, we found that after a 4 h period of waking the initial neuronal response in the contralateral frontal cortex was stronger and more synchronous, and was followed by a more profound inhibition of neuronal spiking as compared with the control condition. These changes in evoked activity suggest increased neuronal excitability and indicate that, after staying awake, cortical neurons become transiently bistable. We propose that some of the detrimental effects of sleep deprivation may be a result of altered neuronal responsiveness to incoming intrinsic and extrinsic inputs.

Sleep homeostasis in the rat is preserved during chronic sleep restriction.

Sleep is homeostatically regulated in all animal species that have been carefully studied so far. The best characterized marker of sleep homeostasis is slow wave activity (SWA), the EEG power between 0.5 and 4 Hz during nonrapid eye movement (NREM) sleep. SWA reflects the accumulation of sleep pressure as a function of duration and/or intensity of prior wake: it increases after spontaneous wake and short-term (3-24 h) sleep deprivation and decreases during sleep. However, recent evidence suggests that during chronic sleep restriction (SR) sleep may be regulated by both allostatic and homeostatic mechanisms. Here, we performed continuous, almost completely artifact-free EEG recordings from frontal, parietal, and occipital cortex in freely moving rats (n = 11) during and after 5 d of SR. During SR, rats were allowed to sleep during the first 4 h of the light period (4S(+)) but not during the following 20 h (20S(-)). During the daily 20S(-) most sleep was prevented, whereas the number of short (<20 s) sleep attempts increased. Low-frequency EEG power (1-6 Hz) in both sleep and wake also increased during 20S(-), most notably in the occipital cortex. In all animals NREM SWA increased above baseline levels during the 4S(+) periods and in post-SR recovery. The SWA increase was more pronounced in frontal cortex, and its magnitude was determined by the efficiency of SR. Analysis of cumulative slow wave energy demonstrated that the loss of SWA during SR was compensated by the end of the second recovery day. Thus, the homeostatic regulation of sleep is preserved under conditions of chronic SR.

How 'visual' is the visual cortex? The interactions between the visual cortex and other sensory, motivational and motor systems as enabling factors for visual perception.

The definition of the visual cortex is primarily based on the evidence that lesions of this area impair visual perception. However, this does not exclude that the visual cortex may process more information than of retinal origin alone, or that other brain structures contribute to vision. Indeed, research across the past decades has shown that non-visual information, such as neural activity related to reward expectation and value, locomotion, working memory and other sensory modalities, can modulate primary visual cortical responses to retinal inputs. Nevertheless, the function of this non-visual information is poorly understood. Here we review recent evidence, coming primarily from studies in rodents, arguing that non-visual and motor effects in visual cortex play a role in visual processing itself, for instance disentangling direct auditory effects on visual cortex from effects of sound-evoked orofacial movement. These findings are placed in a broader framework casting vision in terms of predictive processing under control of frontal, reward- and motor-related systems. In contrast to the prevalent notion that vision is exclusively constructed by the visual cortical system, we propose that visual percepts are generated by a larger network-the extended visual system-spanning other sensory cortices, supramodal areas and frontal systems. This article is part of the theme issue 'Decision and control processes in multisensory perception'.

A novel task to investigate vibrotactile detection in mice.

Throughout the last decades, understanding the neural mechanisms of sensory processing has been a key objective for neuroscientists. Many studies focused on uncovering the microcircuit-level architecture of somatosensation using the rodent whisker system as a model. Although these studies have significantly advanced our understanding of tactile processing, the question remains to what extent the whisker system can provide results translatable to the human somatosensory system. To address this, we developed a restrained vibrotactile detection task involving the limb system in mice. A vibrotactile stimulus was delivered to the hindlimb of head-fixed mice, who were trained to perform a Go/No-go detection task. Mice were able to learn this task with satisfactory performance and with reasonably short training times. In addition, the task we developed is versatile, as it can be combined with diverse neuroscience methods. Thus, this study introduces a novel task to study the neuron-level mechanisms of tactile processing in a system other than the more commonly studied whisker system.

Multisensory task demands temporally extend the causal requirement for visual cortex in perception.

Primary sensory areas constitute crucial nodes during perceptual decision making. However, it remains unclear to what extent they mainly constitute a feedforward processing step, or rather are continuously involved in a recurrent network together with higher-order areas. We found that the temporal window in which primary visual cortex is required for the detection of identical visual stimuli was extended when task demands were increased via an additional sensory modality that had to be monitored. Late-onset optogenetic inactivation preserved bottom-up, early-onset responses which faithfully encoded stimulus features, and was effective in impairing detection only if it preceded a late, report-related phase of the cortical response. Increasing task demands were marked by longer reaction times and the effect of late optogenetic inactivation scaled with reaction time. Thus, independently of visual stimulus complexity, multisensory task demands determine the temporal requirement for ongoing sensory-related activity in V1, which overlaps with report-related activity.

Obstructive Sleep Apnoea Syndrome Screening Through Wrist-Worn Smartbands: A Machine-Learning Approach.

Purpose: A large portion of the adult population is thought to suffer from obstructive sleep apnoea syndrome (OSAS), a sleep-related breathing disorder associated with increased morbidity and mortality. International guidelines include the polysomnography and the cardiorespiratory monitoring (CRM) as diagnostic tools for OSAS, but they are unfit for a large-scale screening, given their invasiveness, high cost and lengthy process of scoring. Current screening methods are based on self-reported questionnaires that suffer from lack of objectivity. On the contrary, commercial smartbands are wearable devices capable of collecting accelerometric and photoplethysmographic data in a user-friendly and objective way. We questioned whether machine-learning (ML) classifiers trained on data collected through these wearable devices would help predict OSAS severity. Patients and Methods: Each of the patients (n = 78, mean age ± SD: 57.2 ± 12.9 years; 30 females) underwent CRM and concurrently wore a commercial wrist smartband. CRM's traces were scored, and OSAS severity was reported as apnoea hypopnoea index (AHI). We trained three pairs of classifiers to make the following prediction: AHI <5 vs AHI ≥5, AHI <15 vs AHI ≥15, and AHI <30 vs AHI ≥30. Results: According to the Matthews correlation coefficient (MCC), the proposed algorithms reached an overall good correlation with the ground truth (CRM) for AHI <5 vs AHI ≥5 (MCC: 0.4) and AHI <30 vs AHI ≥30 (MCC: 0.3) classifications. AHI <5 vs AHI ≥5 and AHI <30 vs AHI ≥30 classifiers' sensitivity, specificity, positive predictive values (PPV), negative predictive values (NPV) and diagnostic odds ratio (DOR) are comparable with the STOP-Bang questionnaire, an established OSAS screening tool. Conclusion: Machine learning algorithms showed an overall good performance. Unlike questionnaires, these are based on objectively collected data. Furthermore, these commercial devices are widely distributed in the general population. The aforementioned advantages of machine-learning algorithms applied to smartbands' data over questionnaires lead to the conclusion that they could serve a population-scale screening for OSAS.

The continued need for animals to advance brain research.

Policymakers aim to move toward animal-free alternatives for scientific research and have introduced very strict regulations for animal research. We argue that, for neuroscience research, until viable and translational alternatives become available and the value of these alternatives has been proven, the use of animals should not be compromised.

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.

The Role of Top-Down Modulation in Shaping Sensory Processing Across Brain States: Implications for Consciousness.

Top-down, feedback projections account for a large portion of all connections between neurons in the thalamocortical system, yet their precise role remains the subject of much discussion. A large number of studies has focused on investigating how sensory information is transformed across hierarchically-distributed processing stages in a feedforward fashion, and computational models have shown that purely feedforward artificial neural networks can even outperform humans in pattern classification tasks. What is then the functional role of feedback connections? Several key roles have been identified, ranging from attentional modulation to, crucially, conscious perception. Specifically, most of the major theories on consciousness postulate that feedback connections would play an essential role in enabling sensory information to be consciously perceived. Consequently, it follows that their efficacy in modulating target regions should drastically decrease in nonconscious brain states [non-rapid eye movement (REM) sleep, anesthesia] compared to conscious ones (wakefulness), and also in instances when a given sensory stimulus is not perceived compared to when it is. Until recently, however, this prediction could only be tested with correlative experiments, due to the lack of techniques to selectively manipulate and measure the activity of feedback pathways. In this article, we will review the most recent literature on the functions of feedback connections across brain states and based on the presence or absence of perception. We will focus on experiments studying mismatch negativity, a phenomenon which has been hypothesized to rely on top-down modulation but which persists during nonconscious states. While feedback modulation is generally dampened in nonconscious states and enhanced when perception occurs, there are clear deviations from this rule. As we will discuss, this may pose a challenge to most theories of consciousness, and possibly require a change in how the level of consciousness in supposedly nonconscious states is assessed.