Experimental and theoretical approaches to conscious processing

Recent experimental studies and theoretical models have begun to address the challenge of establishing a causal link between subjective conscious experience and measurable neuronal activity. The present review focuses on the well-delimited issue of how an external or internal piece of information goes beyond nonconscious processing and gains access to conscious processing, a transition characterized by the existence of a reportable subjective experience. Converging neuroimaging and neurophysiological data, acquired during minimal experimental contrasts between conscious and nonconscious processing, point to objective neural measures of conscious access: late amplification of relevant sensory activity, long-distance cortico-cortical synchronization at beta and gamma frequencies, and "ignition" of a large-scale prefronto-parietal network. We compare these findings to current theoretical models of conscious processing, including the Global Neuronal Workspace (GNW) model according to which conscious access occurs when incoming information is made globally available to multiple brain systems through a network of neurons with long-range axons densely distributed in prefrontal, parieto-temporal, and cingulate cortices. The clinical implications of these results for general anesthesia, coma, vegetative state, and schizophrenia are discussed.     

Evolution and Optimality of Similar Neural Mechanisms for Perception and Action during Search

A prevailing theory proposes that the brain''s two visual pathways, the ventral and dorsal, lead to differing visual processing and world representations for conscious perception than those for action. Others have claimed that perception and action share much of their visual processing. But which of these two neural architectures is favored by evolution? Successful visual search is life-critical and here we investigate the evolution and optimality of neural mechanisms mediating perception and eye movement actions for visual search in natural images. We implement an approximation to the ideal Bayesian searcher with two separate processing streams, one controlling the eye movements and the other stream determining the perceptual search decisions. We virtually evolved the neural mechanisms of the searchers'' two separate pathways built from linear combinations of primary visual cortex receptive fields (V1) by making the simulated individuals'' probability of survival depend on the perceptual accuracy finding targets in cluttered backgrounds. We find that for a variety of targets, backgrounds, and dependence of target detectability on retinal eccentricity, the mechanisms of the searchers'' two processing streams converge to similar representations showing that mismatches in the mechanisms for perception and eye movements lead to suboptimal search. Three exceptions which resulted in partial or no convergence were a case of an organism for which the targets are equally detectable across the retina, an organism with sufficient time to foveate all possible target locations, and a strict two-pathway model with no interconnections and differential pre-filtering based on parvocellular and magnocellular lateral geniculate cell properties. Thus, similar neural mechanisms for perception and eye movement actions during search are optimal and should be expected from the effects of natural selection on an organism with limited time to search for food that is not equi-detectable across its retina and interconnected perception and action neural pathways.     

Source Space Estimation of Oscillatory Power and Brain Connectivity in Tinnitus

Tinnitus is the perception of an internally generated sound that is postulated to emerge as a result of structural and functional changes in the brain. However, the precise pathophysiology of tinnitus remains unknown. Llinas’ thalamocortical dysrhythmia model suggests that neural deafferentation due to hearing loss causes a dysregulation of coherent activity between thalamus and auditory cortex. This leads to a pathological coupling of theta and gamma oscillatory activity in the resting state, localised to the auditory cortex where normally alpha oscillations should occur. Numerous studies also suggest that tinnitus perception relies on the interplay between auditory and non-auditory brain areas. According to the Global Brain Model, a network of global fronto—parietal—cingulate areas is important in the generation and maintenance of the conscious perception of tinnitus. Thus, the distress experienced by many individuals with tinnitus is related to the top—down influence of this global network on auditory areas. In this magnetoencephalographic study, we compare resting-state oscillatory activity of tinnitus participants and normal-hearing controls to examine effects on spectral power as well as functional and effective connectivity. The analysis is based on beamformer source projection and an atlas-based region-of-interest approach. We find increased functional connectivity within the auditory cortices in the alpha band. A significant increase is also found for the effective connectivity from a global brain network to the auditory cortices in the alpha and beta bands. We do not find evidence of effects on spectral power. Overall, our results provide only limited support for the thalamocortical dysrhythmia and Global Brain models of tinnitus.     

Individual differences in trait anxiety predict the response of the basolateral amygdala to unconsciously processed fearful faces

Responses to threat-related stimuli are influenced by conscious and unconscious processes, but the neural systems underlying these processes and their relationship to anxiety have not been clearly delineated. Using fMRI, we investigated the neural responses associated with the conscious and unconscious (backwardly masked) perception of fearful faces in healthy volunteers who varied in threat sensitivity (Spielberger trait anxiety scale). Unconscious processing modulated activity only in the basolateral subregion of the amygdala, while conscious processing modulated activity only in the dorsal amygdala (containing the central nucleus). Whereas activation of the dorsal amygdala by conscious stimuli was consistent across subjects and independent of trait anxiety, activity in the basolateral amygdala to unconscious stimuli, and subjects' reaction times, were predicted by individual differences in trait anxiety. These findings provide a biological basis for the unconscious emotional vigilance characteristic of anxiety and a means for investigating the mechanisms and efficacy of treatments for anxiety.     

Rhythmic TMS over parietal cortex links distinct brain frequencies to global versus local visual processing

Neural networks underlying visual perception exhibit oscillations at different frequencies (e.g.,). But how these map onto distinct aspects of visual perception remains elusive. Recent electroencephalography data indicate that theta or beta frequencies at parietal sensors increase in amplitude when conscious perception is dominated by global or local features, respectively, of a reversible visual stimulus. But this provides only correlative, noninterventional evidence. Here we show via transcranial magnetic stimulation (TMS) interventions that short rhythmic bursts of right-parietal TMS at theta or beta frequency can causally benefit processing of global or local levels, respectively, for hierarchical visual stimuli, especially in the context of salient incongruent distractors. This double dissociation between theta and beta TMS reveals distinct causal roles for particular frequencies in processing global versus local visual features.     

Density dependent neurodynamics

The dynamics of a neural network depends on density parameters at (at least) two different levels: the subcellular density of ion channels in single neurons, and the density of cells and synapses at a network level. For the Frankenhaeuser-Huxley (FH) neural model, the density of sodium (Na) and potassium (K) channels determines the behaviour of a single neuron when exposed to an external stimulus. The features of the onset of single neuron oscillations vary qualitatively among different regions in the channel density plane. At a network level, the density of neurons is reflected in the global connectivity. We study the relation between the two density levels in a network of oscillatory FH neurons, by qualitatively distinguishing between three regions, where the mean network activity is (1) spiking, (2) oscillating with enveloped frequencies, and (3) bursting, respectively. We demonstrate that the global activity can be shifted between regions by changing either the density of ion channels at the subcellular level, or the connectivity at the network level, suggesting that different underlying mechanisms can explain similar global phenomena. Finally, we model a possible effect of anaesthesia by blocking specific inhibitory ion channels.     

一种感知视觉运动信息的简化脑模型

视觉运动信息的感知过程,包括从局域运动检测到对模式整体运动的感知过程.我们以蝇视觉系统的图形-背景相对运动分辨的神经回路网络为基本框架,采用初级运动检测器的六角形阵列作为输入层,构造了一种感知视觉运动信息的简化脑模型,模拟了运动信息应该神经计算模型各个层次上的处理.该模型对差分行为实验结果作出了正确预测.本文并对空间生理整合的神经机制作了讨论.     

Vagaries of visual perception in autism

Three classes of perceptual phenomena have repeatedly been associated with autism spectrum disorder (ASD): superior processing of fine detail (local structure), either inferior processing of overall/global structure or an ability to ignore disruptive global/contextual information, and impaired motion perception. This review evaluates the quality of the evidence bearing on these three phenomena. We argue that while superior local processing has been robustly demonstrated, conclusions about global processing cannot be definitively drawn from the experiments to date, which have generally not precluded observers using more local cues. Perception of moving stimuli is impaired in ASD, but explanations in terms of magnocellular/dorsal deficits do not appear to be sufficient. We suggest that abnormalities in the superior temporal sulcus (STS) may provide a neural basis for the range of motion-processing deficits observed in ASD, including biological motion perception. Such an explanation may also provide a link between perceptual abnormalities and specific deficits in social cognition associated with autism.     

Object segmentation and recovery via neural oscillators implementing the similarity and prior knowledge gestalt rules

Object recognition requires the solution of the binding and segmentation problems, i.e., grouping different features to achieve a coherent representation. Synchronization of neural activity in the gamma-band, associated with gestalt perception, has often been proposed as a putative mechanism to solve these problems, not only as to low-level processing, but also in higher cortical functions. In the present work, a network of Wilson-Cowan oscillators is used to segment simultaneous objects, and recover an object from partial or corrupted information, by implementing two gestalt rules: similarity and prior knowledge. The network consists of H different areas, each devoted to representation of a particular feature of the object, according to a topological organization. The similarity law is realized via lateral intra-area connections, arranged as a "Mexican-hat". Prior knowledge is realized via inter-area connections, which link properties belonging to a previously memorized object. A global inhibitor allows segmentation of several objects avoiding interference. Simulation results, performed using three simultaneous input objects, show that the network is able to detect an object even in difficult conditions (i.e., when some features are absent or shifted with respect to the original one). Moreover, the trade-off between sensitivity (capacity to detect true positives) and specificity (capacity to reject false positives) can be controlled acting on the extension of lateral synapses (i.e., on the level of accepted similarity). Finally, the network can also deal with correlated objects, i.e., objects which have some common features. Simulations performed using a different number of objects (2, 3, 4 or 5) suggest that the network is able to segment and recall up to four objects, but the oscillation frequency must increase, the lower the number of objects simultaneously present. The model, although quite simpler compared with neurophysiology, may represent a theoretical framework for the analysis of the relationships between object representation, memory, learning, and gamma-band activity. In particular, it extends previous studies on autoassociative memory since it exploits not only oscillatory dynamics, but also a topological organization of features.     

Subjective visual perception: from local processing to emergent phenomena of brain activity

The combination of electrophysiological recordings with ambiguous visual stimulation made possible the detection of neurons that represent the content of subjective visual perception and perceptual suppression in multiple cortical and subcortical brain regions. These neuronal populations, commonly referred to as the neural correlates of consciousness, are more likely to be found in the temporal and prefrontal cortices as well as the pulvinar, indicating that the content of perceptual awareness is represented with higher fidelity in higher-order association areas of the cortical and thalamic hierarchy, reflecting the outcome of competitive interactions between conflicting sensory information resolved in earlier stages. However, despite the significant insights into conscious perception gained through monitoring the activities of single neurons and small, local populations, the immense functional complexity of the brain arising from correlations in the activity of its constituent parts suggests that local, microscopic activity could only partially reveal the mechanisms involved in perceptual awareness. Rather, the dynamics of functional connectivity patterns on a mesoscopic and macroscopic level could be critical for conscious perception. Understanding these emergent spatio-temporal patterns could be informative not only for the stability of subjective perception but also for spontaneous perceptual transitions suggested to depend either on the dynamics of antagonistic ensembles or on global intrinsic activity fluctuations that may act upon explicit neural representations of sensory stimuli and induce perceptual reorganization. Here, we review the most recent results from local activity recordings and discuss the potential role of effective, correlated interactions during perceptual awareness.     

Recurrent fractal neural networks: a strategy for the exchange of local and global information processing in the brain

The regulation of biological networks relies significantly on convergent feedback signaling loops that render a global output locally accessible. Ideally, the recurrent connectivity within these systems is self-organized by a time-dependent phase-locking mechanism. This study analyzes recurrent fractal neural networks (RFNNs), which utilize a self-similar or fractal branching structure of dendrites and downstream networks for phase-locking of reciprocal feedback loops: output from outer branch nodes of the network tree enters inner branch nodes of the dendritic tree in single neurons. This structural organization enables RFNNs to amplify re-entrant input by over-the-threshold signal summation from feedback loops with equivalent signal traveling times. The columnar organization of pyramidal neurons in the neocortical layers V and III is discussed as the structural substrate for this network architecture. RFNNs self-organize spike trains and render the entire neural network output accessible to the dendritic tree of each neuron within this network. As the result of a contraction mapping operation, the local dendritic input pattern contains a downscaled version of the network output coding structure. RFNNs perform robust, fractal data compression, thus coping with a limited number of feedback loops for signal transport in convergent neural networks. This property is discussed as a significant step toward the solution of a fundamental problem in neuroscience: how is neuronal computation in separate neurons and remote brain areas unified as an instance of experience in consciousness? RFNNs are promising candidates for engaging neural networks into a coherent activity and provide a strategy for the exchange of global and local information processing in the human brain, thereby ensuring the completeness of a transformation from neuronal computation into conscious experience.     

Breakthrough to awareness: a preliminary neural network model of conscious and unconscious perception in word processing

 A neural network model is constructed to mimic the processing involved in semantic and working memory when subliminal effects are involved. These effects involve modifications of reaction time to later inputs, according to whether or not there has been conscious or unconscious processing of the earlier input. The model is constructed of two separate modules: one (a semantic memory module) allowing for processing at a semantic, but unconscious, level, and the other (a working memory module) for conscious experience. The latter module, although a replica of the earlier one, has different lateral connectivity and output function from the former. The model is shown to give a good fit to Marcel’s data on the processing of polysemous words. Further tests are suggested for the model, and a possible cortical implementation suggested. The relevance of the model to recent approaches to consciousness is also explored. Received: 7 February 1995/Accepted in revised form: 14 November 1995     

Investigation of the role of interneurons and their modulation by centrifugal fibers in a neural model of the olfactory bulb

Olfactory bulb processing results from the interaction of relay neurons with two main categories of interneurons which mediate inhibition in two distinct layers: periglomerular cells and granule cells. We present here a neural model of the mammalian olfactory bulb which allows to separately investigate the functional consequences of the two types of interneurons onto the relay neurons responsiveness to odors. The model, although built with simplified representations of neural elements generates various aspects of neural dynamics from the cellular to the populational level. We propose that the combined action of centrifugal control at two different layers of processing is complementary: reduction of the number of active relay neurons responding to a given odorant through increased activity of periglomerular cells, and an increase of response intensity of active mitral cells through decrease of granule cell inhibition.     

Balanced input allows optimal encoding in a stochastic binary neural network model: an analytical study

Recent neurophysiological experiments have demonstrated a remarkable effect of attention on the underlying neural activity that suggests for the first time that information encoding is indeed actively influenced by attention. Single cell recordings show that attention reduces both the neural variability and correlations in the attended condition with respect to the non-attended one. This reduction of variability and redundancy enhances the information associated with the detection and further processing of the attended stimulus. Beyond the attentional paradigm, the local activity in a neural circuit can be modulated in a number of ways, leading to the general question of understanding how the activity of such circuits is sensitive to these relatively small modulations. Here, using an analytically tractable neural network model, we demonstrate how this enhancement of information emerges when excitatory and inhibitory synaptic currents are balanced. In particular, we show that the network encoding sensitivity--as measured by the Fisher information--is maximized at the exact balance. Furthermore, we find a similar result for a more realistic spiking neural network model. As the regime of balanced inputs has been experimentally observed, these results suggest that this regime is functionally important from an information encoding standpoint.     

Attentional load modulates responses of human primary visual cortex to invisible stimuli

Visual neuroscience has long sought to determine the extent to which stimulus-evoked activity in visual cortex depends on attention and awareness. Some influential theories of consciousness maintain that the allocation of attention is restricted to conscious representations [1, 2]. However, in the load theory of attention [3], competition between task-relevant and task-irrelevant stimuli for limited-capacity attention does not depend on conscious perception of the irrelevant stimuli. The critical test is whether the level of attentional load in a relevant task would determine unconscious neural processing of invisible stimuli. Human participants were scanned with high-field fMRI while they performed a foveal task of low or high attentional load. Irrelevant, invisible monocular stimuli were simultaneously presented peripherally and were continuously suppressed by a flashing mask in the other eye [4]. Attentional load in the foveal task strongly modulated retinotopic activity evoked in primary visual cortex (V1) by the invisible stimuli. Contrary to traditional views [1, 2, 5, 6], we found that availability of attentional capacity determines neural representations related to unconscious processing of continuously suppressed stimuli in human primary visual cortex. Spillover of attention to cortical representations of invisible stimuli (under low load) cannot be a sufficient condition for their awareness.     

Robust Single Trial Identification of Conscious Percepts Triggered by Sensory Events of Variable Saliency

The neural correlates of visual awareness are elusive because of its fleeting nature. Here we have addressed this issue by using single trial statistical “brain reading” of neurophysiological event related (ERP) signatures of conscious perception of visual attributes with different levels of saliency. Behavioral reports were taken at every trial in 4 experiments addressing conscious access to color, luminance, and local phase offset cues. We found that single trial neurophysiological signatures of target presence can be observed around 300 ms at central parietal sites. Such signatures are significantly related with conscious perception, and their probability is related to sensory saliency levels. These findings identify a general neural correlate of conscious perception at the single trial level, since conscious perception can be decoded as such independently of stimulus salience and fluctuations of threshold levels. This approach can be generalized to successfully detect target presence in other individuals.     

To Perceive or Not Perceive: The Role of Gamma-band Activity in Signaling Object Percepts

The relation of gamma-band synchrony to holistic perception in which concerns the effects of sensory processing, high level perceptual gestalt formation, motor planning and response is still controversial. To provide a more direct link to emergent perceptual states we have used holistic EEG/ERP paradigms where the moment of perceptual “discovery” of a global pattern was variable. Using a rapid visual presentation of short-lived Mooney objects we found an increase of gamma-band activity locked to perceptual events. Additional experiments using dynamic Mooney stimuli showed that gamma activity increases well before the report of an emergent holistic percept. To confirm these findings in a data driven manner we have further used a support vector machine classification approach to distinguish between perceptual vs. non perceptual states, based on time-frequency features. Sensitivity, specificity and accuracy were all above 95%. Modulations in the 30–75 Hz range were larger for perception states. Interestingly, phase synchrony was larger for perception states for high frequency bands. By focusing on global gestalt mechanisms instead of local processing we conclude that gamma-band activity and synchrony provide a signature of holistic perceptual states of variable onset, which are separable from sensory and motor processing.     

Single units and conscious vision.

Figures that can be seen in more than one way are invaluable tools for the study of the neural basis of visual awareness, because such stimuli permit the dissociation of the neural responses that underlie what we perceive at any given time from those forming the sensory representation of a visual pattern. To study the former type of responses, monkeys were subjected to binocular rivalry, and the response of neurons in a number of different visual areas was studied while the animals reported their alternating percepts by pulling levers. Perception-related modulations of neural activity were found to occur to different extents in different cortical visual areas. The cells that were affected by suppression were almost exclusively binocular, and their proportion was found to increase in the higher processing stages of the visual system. The strongest correlations between neural activity and perception were observed in the visual areas of the temporal lobe. A strikingly large number of neurons in the early visual areas remained active during the perceptual suppression of the stimulus, a finding suggesting that conscious visual perception might be mediated by only a subset of the cells exhibiting stimulus selective responses. These physiological findings, together with a number of recent psychophysical studies, offer a new explanation of the phenomenon of binocular rivalry. Indeed, rivalry has long been considered to be closely linked with binocular fusion and stereopsis, and the sequences of dominance and suppression have been viewed as the result of competition between the two monocular channels. The physiological data presented here are incompatible with this interpretation. Rather than reflecting interocular competition, the rivalry is most probably between the two different central neural representations generated by the dichoptically presented stimuli. The mechanisms of rivalry are probably the same as, or very similar to, those underlying multistable perception in general, and further physiological studies might reveal much about the neural mechanisms of our perceptual organization.     

Identifying the Core Components of Emotional Intelligence: Evidence from Amplitude of Low-Frequency Fluctuations during Resting State

Emotional intelligence (EI) is a multi-faceted construct consisting of our ability to perceive, monitor, regulate and use emotions. Despite much attention being paid to the neural substrates of EI, little is known of the spontaneous brain activity associated with EI during resting state. We used resting-state fMRI to investigate the association between the amplitude of low-frequency fluctuations (ALFFs) and EI in a large sample of young, healthy adults. We found that EI was significantly associated with ALFFs in key nodes of two networks: the social emotional processing network (the fusiform gyrus, right superior orbital frontal gyrus, left inferior frontal gyrus and left inferior parietal lobule) and the cognitive control network (the bilateral pre-SMA, cerebellum and right precuneus). These findings suggest that the neural correlates of EI involve several brain regions in two crucial networks, which reflect the core components of EI: emotion perception and emotional control.     

Nonoptimal component placement, but short processing paths, due to long-distance projections in neural systems

It has been suggested that neural systems across several scales of organization show optimal component placement, in which any spatial rearrangement of the components would lead to an increase of total wiring. Using extensive connectivity datasets for diverse neural networks combined with spatial coordinates for network nodes, we applied an optimization algorithm to the network layouts, in order to search for wire-saving component rearrangements. We found that optimized component rearrangements could substantially reduce total wiring length in all tested neural networks. Specifically, total wiring among 95 primate (Macaque) cortical areas could be decreased by 32%, and wiring of neuronal networks in the nematode Caenorhabditis elegans could be reduced by 48% on the global level, and by 49% for neurons within frontal ganglia. Wiring length reductions were possible due to the existence of long-distance projections in neural networks. We explored the role of these projections by comparing the original networks with minimally rewired networks of the same size, which possessed only the shortest possible connections. In the minimally rewired networks, the number of processing steps along the shortest paths between components was significantly increased compared to the original networks. Additional benchmark comparisons also indicated that neural networks are more similar to network layouts that minimize the length of processing paths, rather than wiring length. These findings suggest that neural systems are not exclusively optimized for minimal global wiring, but for a variety of factors including the minimization of processing steps.