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.

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.

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.

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.

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.

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.

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.

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.

The circuit architecture of cortical multisensory processing: Distinct functions jointly operating within a common anatomical network.

Our perceptual systems continuously process sensory inputs from different modalities and organize these streams of information such that our subjective representation of the outside world is a unified experience. By doing so, they also enable further cognitive processing and behavioral action. While cortical multisensory processing has been extensively investigated in terms of psychophysics and mesoscale neural correlates, an in depth understanding of the underlying circuit-level mechanisms is lacking. Previous studies on circuit-level mechanisms of multisensory processing have predominantly focused on cue integration, i.e. the mechanism by which sensory features from different modalities are combined to yield more reliable stimulus estimates than those obtained by using single sensory modalities. In this review, we expand the framework on the circuit-level mechanisms of cortical multisensory processing by highlighting that multisensory processing is a family of functions - rather than a single operation - which involves not only the integration but also the segregation of modalities. In addition, multisensory processing not only depends on stimulus features, but also on cognitive resources, such as attention and memory, as well as behavioral context, to determine the behavioral outcome. We focus on rodent models as a powerful instrument to study the circuit-level bases of multisensory processes, because they enable combining cell-type-specific recording and interventional techniques with complex behavioral paradigms. We conclude that distinct multisensory processes share overlapping anatomical substrates, are implemented by diverse neuronal micro-circuitries that operate in parallel, and are flexibly recruited based on factors such as stimulus features and behavioral constraints.

Functional determinants of enhanced and depressed interareal information flow in nonrapid eye movement sleep between neuronal ensembles in rat cortex and hippocampus.

Compared with wakefulness, neuronal activity during nonrapid eye movement (NREM) sleep is characterized by a decreased ability to integrate information, but also by the reemergence of task-related information patterns. To investigate the mechanisms underlying these seemingly opposing phenomena, we measured directed information flow by computing transfer entropy between neuronal spiking activity in three cortical regions and the hippocampus of rats across brain states. State-dependent information flow was jointly determined by the anatomical distance between neurons and by their functional specialization. We distinguished two regimes, operating at short and long time scales, respectively. From wakefulness to NREM sleep, transfer entropy at short time scales increased for interareal connections between neurons showing behavioral task correlates. Conversely, transfer entropy at long time scales became stronger between nontask modulated neurons and weaker between task-modulated neurons. These results may explain how, during NREM sleep, a global interareal disconnection is compatible with highly specific task-related information transfer.

Sensory Processing Across Conscious and Nonconscious Brain States: From Single Neurons to Distributed Networks for Inferential Representation.

Neuronal activity is markedly different across brain states: it varies from desynchronized activity during wakefulness to the synchronous alternation between active and silent states characteristic of deep sleep. Surprisingly, limited attention has been paid to investigating how brain states affect sensory processing. While it was long assumed that the brain was mostly disconnected from external stimuli during sleep, an increasing number of studies indicates that sensory stimuli continue to be processed across all brain states-albeit differently. In this review article, we first discuss what constitutes a brain state. We argue that-next to global, behavioral states such as wakefulness and sleep-there is a concomitant need to distinguish bouts of oscillatory dynamics with specific global/local activity patterns and lasting for a few hundreds of milliseconds, as these can lead to the same sensory stimulus being either perceived or not. We define these short-lasting bouts as micro-states. We proceed to characterize how sensory-evoked neural responses vary between conscious and nonconscious states. We focus on two complementary aspects: neuronal ensembles and inter-areal communication. First, we review which features of ensemble activity are conducive to perception, and how these features vary across brain states. Properties such as heterogeneity, sparsity and synchronicity in neuronal ensembles will especially be considered as essential correlates of conscious processing. Second, we discuss how inter-areal communication varies across brain states and how this may affect brain operations and sensory processing. Finally, we discuss predictive coding (PC) and the concept of multi-level representations as a key framework for understanding conscious sensory processing. In this framework the brain implements conscious representations as inferences about world states across multiple representational levels. In this representational hierarchy, low-level inference may be carried out nonconsciously, whereas high levels integrate across different sensory modalities and larger spatial scales, correlating with conscious processing. This inferential framework is used to interpret several cellular and population-level findings in the context of brain states, and we briefly compare its implications to two other theories of consciousness. In conclusion, this review article, provides foundations to guide future studies aiming to uncover the mechanisms of sensory processing and perception across brain states.

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.

Advanced life support provider course in Italy: A 5-year nationwide study to identify the determinants of course success.

INTRODUCTION: The advanced life support (ALS) provider course is the gold standard for teaching and assessing competence in advanced resuscitation. Outcomes over a 5-year period of European Resuscitation (ERC)/IRC ALS provider courses in Italy were investigated, and the factors associated with course success are described. METHODS: In 2008, the Italian Resuscitation Council (IRC) created a database in which every ERC/IRC ALS course was recorded. Data from courses organized from 2008 to 2012 were analysed. The data included: candidate's age and degree (medical doctor (MD) or nurse), medical specialty of MD candidates, course outcomes, duration and reference guidelines, number of instructors and course director. Relationships between the course outcomes and the courses and candidates' characteristics were analysed using logistic regression. RESULTS: A total of 13,624 candidates were evaluated from 871 courses. Among the candidates, 55% were MDs and 45% were nurses. Ninety-seven percent of candidates passed the final evaluation, while 3% failed. Candidates who passed were younger (37 [31-44] vs. 43 [37-50] years, p<0.0001) and had a greater pre-course resuscitation knowledge (multiple choice quiz (MCQ) score: 88 [83-93] vs. 80 [73-87], p<0.0001) compared to those who failed. The course pass rate was higher for MDs compared to nurses (98% vs. 95%, p<0.0001) and participants in emergency disciplines were most significantly associated with course success (χ(2) 71, p<0.0001). In the multivariate analysis, an older age (OR 0.926, 95%CI [0.915-0.937]) was independently associated with course failure, while being a MD (OR 3.021, 95%CI [2.212-4.132]), having a higher pre-course MCQ score (OR 1.033, 95%CI [1.026-1.040]) together with a higher candidate/instructor ratio (OR 1.314, 95%CI [1.067-1.618]), and having a longer course duration (OR 1.717, 95%CI [1.090-2.703]), were independently associated with success. CONCLUSIONS: Younger age, professional background, and pre-course resuscitation knowledge are the most important predictors of ALS provider course success, together with higher candidate/instructor ratios and longer course durations.

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.

Synaptic recruitment of gephyrin regulates surface GABAA receptor dynamics for the expression of inhibitory LTP.

Postsynaptic long-term potentiation of inhibition (iLTP) can rely on increased GABAA receptors (GABA(A)Rs) at synapses by promoted exocytosis. However, the molecular mechanisms that enhance the clustering of postsynaptic GABA(A)Rs during iLTP remain obscure. Here we demonstrate that during chemically induced iLTP (chem-iLTP), GABA(A)Rs are immobilized and confined at synapses, as revealed by single-particle tracking of individual GABA(A)Rs in cultured hippocampal neurons. Chem-iLTP expression requires synaptic recruitment of the scaffold protein gephyrin from extrasynaptic areas, which in turn is promoted by CaMKII-dependent phosphorylation of GABA(A)R-ß3-Ser(383). Impairment of gephyrin assembly prevents chem-iLTP and, in parallel, blocks the accumulation and immobilization of GABA(A)Rs at synapses. Importantly, an increase of gephyrin and GABA(A)R similar to those observed during chem-iLTP in cultures were found in the rat visual cortex following an experience-dependent plasticity protocol that potentiates inhibitory transmission in vivo. Thus, phospho-GABA(A)R-ß3-dependent accumulation of gephyrin at synapses and receptor immobilization are crucial for iLTP expression and are likely to modulate network excitability.

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.