United we sense, divided we fail: context-driven perception of ambiguous visual stimuli

Ambiguous visual stimuli provide the brain with sensory information that contains conflicting evidence for multiple mutually exclusive interpretations. Two distinct aspects of the phenomenological experience associated with viewing ambiguous visual stimuli are the apparent stability of perception whenever one perceptual interpretation is dominant, and the instability of perception that causes perceptual dominance to alternate between perceptual interpretations upon extended viewing. This review summarizes several ways in which contextual information can help the brain resolve visual ambiguities and construct temporarily stable perceptual experiences. Temporal context through prior stimulation or internal brain states brought about by feedback from higher cortical processing levels may alter the response characteristics of specific neurons involved in rivalry resolution. Furthermore, spatial or crossmodal context may strengthen the neuronal representation of one of the possible perceptual interpretations and consequently bias the rivalry process towards it. We suggest that contextual influences on perceptual choices with ambiguous visual stimuli can be highly informative about the neuronal mechanisms of context-driven inference in the general processes of perceptual decision-making.     

Dynamic predictions: oscillations and synchrony in top-down processing

Classical theories of sensory processing view the brain as a passive, stimulus-driven device. By contrast, more recent approaches emphasize the constructive nature of perception, viewing it as an active and highly selective process. Indeed, there is ample evidence that the processing of stimuli is controlled by top-down influences that strongly shape the intrinsic dynamics of thalamocortical networks and constantly create predictions about forthcoming sensory events. We discuss recent experiments indicating that such predictions might be embodied in the temporal structure of both stimulus-evoked and ongoing activity, and that synchronous oscillations are particularly important in this process. Coherence among subthreshold membrane potential fluctuations could be exploited to express selective functional relationships during states of expectancy or attention, and these dynamic patterns could allow the grouping and selection of distributed neuronal responses for further processing.     

Asynchrony adaptation reveals neural population code for audio-visual timing

The relative timing of auditory and visual stimuli is a critical cue for determining whether sensory signals relate to a common source and for making inferences about causality. However, the way in which the brain represents temporal relationships remains poorly understood. Recent studies indicate that our perception of multisensory timing is flexible--adaptation to a regular inter-modal delay alters the point at which subsequent stimuli are judged to be simultaneous. Here, we measure the effect of audio-visual asynchrony adaptation on the perception of a wide range of sub-second temporal relationships. We find distinctive patterns of induced biases that are inconsistent with the previous explanations based on changes in perceptual latency. Instead, our results can be well accounted for by a neural population coding model in which: (i) relative audio-visual timing is represented by the distributed activity across a relatively small number of neurons tuned to different delays; (ii) the algorithm for reading out this population code is efficient, but subject to biases owing to under-sampling; and (iii) the effect of adaptation is to modify neuronal response gain. These results suggest that multisensory timing information is represented by a dedicated population code and that shifts in perceived simultaneity following asynchrony adaptation arise from analogous neural processes to well-known perceptual after-effects.     

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.     

Predictive Coding or Evidence Accumulation? False Inference and Neuronal Fluctuations

Perceptual decisions can be made when sensory input affords an inference about what generated that input. Here, we report findings from two independent perceptual experiments conducted during functional magnetic resonance imaging (fMRI) with a sparse event-related design. The first experiment, in the visual modality, involved forced-choice discrimination of coherence in random dot kinematograms that contained either subliminal or periliminal motion coherence. The second experiment, in the auditory domain, involved free response detection of (non-semantic) near-threshold acoustic stimuli. We analysed fluctuations in ongoing neural activity, as indexed by fMRI, and found that neuronal activity in sensory areas (extrastriate visual and early auditory cortex) biases perceptual decisions towards correct inference and not towards a specific percept. Hits (detection of near-threshold stimuli) were preceded by significantly higher activity than both misses of identical stimuli or false alarms, in which percepts arise in the absence of appropriate sensory input. In accord with predictive coding models and the free-energy principle, this observation suggests that cortical activity in sensory brain areas reflects the precision of prediction errors and not just the sensory evidence or prediction errors per se.     

Seeing more than meets the eye: processing of illusory contours in animals

This review article illustrates that mammals, birds and insects are able to perceive illusory contours. Illusory contours lack a physical counterpart, but monkeys, cats, owls and bees perceive them as if they were real borders. In all of these species, a neural correlate for such perceptual completion phenomena has been described. The robustness of neuronal responses and the abundance of cells argue that such neurons might indeed represent a neural correlate for illusory contour perception. The internal state of an animal subject (i.e., alert and behaving) seems to be an important factor when correlating neural activity with perceptual phenomena. The fact that the neural network necessary for illusory contour perception has been found in relatively early visual brain areas in all tested animals suggests that bottom-up processing is largely sufficient to explain such perceptual abilities. However, recent findings in monkeys indicate that feedback loops within the visual system may provide additional modulation. The detection of illusory contours by independently evolved visual systems argues that processing of edges in the absence of contrast gradients reflects fundamental visual constraints and not just an artifact of visual processing.     

Analysis of Slow (Theta) Oscillations as a Potential Temporal Reference Frame for Information Coding in Sensory Cortices

While sensory neurons carry behaviorally relevant information in responses that often extend over hundreds of milliseconds, the key units of neural information likely consist of much shorter and temporally precise spike patterns. The mechanisms and temporal reference frames by which sensory networks partition responses into these shorter units of information remain unknown. One hypothesis holds that slow oscillations provide a network-intrinsic reference to temporally partitioned spike trains without exploiting the millisecond-precise alignment of spikes to sensory stimuli. We tested this hypothesis on neural responses recorded in visual and auditory cortices of macaque monkeys in response to natural stimuli. Comparing different schemes for response partitioning revealed that theta band oscillations provide a temporal reference that permits extracting significantly more information than can be obtained from spike counts, and sometimes almost as much information as obtained by partitioning spike trains using precisely stimulus-locked time bins. We further tested the robustness of these partitioning schemes to temporal uncertainty in the decoding process and to noise in the sensory input. This revealed that partitioning using an oscillatory reference provides greater robustness than partitioning using precisely stimulus-locked time bins. Overall, these results provide a computational proof of concept for the hypothesis that slow rhythmic network activity may serve as internal reference frame for information coding in sensory cortices and they foster the notion that slow oscillations serve as key elements for the computations underlying perception.     

Dynamics on the manifold: Identifying computational dynamical activity from neural population recordings

The question of how the collective activity of neural populations gives rise to complex behaviour is fundamental to neuroscience. At the core of this question lie considerations about how neural circuits can perform computations that enable sensory perception, decision making, and motor control. It is thought that such computations are implemented through the dynamical evolution of distributed activity in recurrent circuits. Thus, identifying dynamical structure in neural population activity is a key challenge towards a better understanding of neural computation. At the same time, interpreting this structure in light of the computation of interest is essential for linking the time-varying activity patterns of the neural population to ongoing computational processes. Here, we review methods that aim to quantify structure in neural population recordings through a dynamical system defined in a low-dimensional latent variable space. We discuss advantages and limitations of different modelling approaches and address future challenges for the field.     

运动对时距知觉的影响及其神经机制

在运动过程中,时距知觉的能力非常重要,能帮助个体对时长进行判断及对事件的发生做出预测和准备.近年来,越来越多的研究发现运动本身会直接影响个体的时距知觉.本文分别从运动参数、运动阶段、视觉运动刺激和运动有关的个体因素四个方面梳理了运动对时距知觉产生影响的行为学证据.目前已经有大量研究从不同角度证明,大脑运动系统组成了支持主观时间知觉的神经网络,并且编码和参与了人类的时距知觉.运动作用于时距知觉的理论机制可以基于内部时钟模型的理论框架并进而从感觉运动信息的交互、运动对唤醒状态的改变及具身认知理论三个角度予以解释.未来研究需要关注运动对不同单位级别时距知觉的影响,测评运动状态下时距知觉的研究范式及技术手段等多个方面进行思考和推进,从而更好地揭示运动如何调节时距知觉过程及其作用机制.还应该结合竞技运动项目特点,为减少运动中时距知觉误差和提高运动员时距知觉能力提供帮助与指导.     

Temporal dynamics of auditory and visual bistability reveal common principles of perceptual organization

When dealing with natural scenes, sensory systems have to process an often messy and ambiguous flow of information. A stable perceptual organization nevertheless has to be achieved in order to guide behavior. The neural mechanisms involved can be highlighted by intrinsically ambiguous situations. In such cases, bistable perception occurs: distinct interpretations of the unchanging stimulus alternate spontaneously in the mind of the observer. Bistable stimuli have been used extensively for more than two centuries to study visual perception. Here we demonstrate that bistable perception also occurs in the auditory modality. We compared the temporal dynamics of percept alternations observed during auditory streaming with those observed for visual plaids and the susceptibilities of both modalities to volitional control. Strong similarities indicate that auditory and visual alternations share common principles of perceptual bistability. The absence of correlation across modalities for subject-specific biases, however, suggests that these common principles are implemented at least partly independently across sensory modalities. We propose that visual and auditory perceptual organization could rely on distributed but functionally similar neural competition mechanisms aimed at resolving sensory ambiguities.     

Concepts in vertebrate neuroethology

Neuroethology is concerned with the analysis of the neural substrates and mechanisms that underlie behaviour. In 1951, Tinbergen implied the following goals of Ethophysiology, today known as Neuroethology: (1) recognition and localization of behaviourally meaningful stimuli, e.g. key stimuli; (2) sensorimotor interfacing and feedback interactions; (3) modulations according to internal states and acquired information; (4) motor pattern generation; and (5) ontogenetic and phylogenetic aspects. Using the toad's (Bufo bufo) visually-guided prey-catching behaviour as an example, experimental strategies and concepts of vertebrate Neuroethology can be demonstrated: (i) visual space is mapped in the brain in a multiple manner; (ii) specification of neurons results from inhibitory and/or excitatory interactions among and within space-mapped neuronal networks; (iii) specialized neurons, e.g. those with stimulus recognition and localization properties, show information processing that takes place in functional units of cell assemblies (so-called ‘neuronal machines’ or ‘brain chips’); (iv) activation of motor pattern generators for different behavioural actions may require coincidence of inputs from different combinations of specialized neurons that serve as command elements and together form a command system; (v) a command system can be regarded as a sensorimotor interface fulfilling tasks with respect to (a) visual pattern recognition and localization, (b) command functions, by initiating the activation of the motor pattern generation system, (c) motor pattern generation through participation in the temporal sequence of the positive feedback from the motor system, and (d) integration of modulatory inputs according to internal states; (vi) the motor pattern generation circuitry consists of a neuronal network capable of producing a consistent distribution of excitation and inhibition and whose output has privileged access to the required motoneuronal pools; (vii) the basic principles of prey selection and motor pattern generation of prey capture emerge in the post-metamorphic juvenile toad with the transition to land and without previous prey experience. During early ontogeny the acuity of sensory discrimination and the performance of motor patterns are subject to maturation paralleled by neural differentiations in the bbrain. performance of motor patterns are subject to maturation paralleled by neural differentiations in the brain. those are programmed and, in amphibians, presumably less dependent on the interaction with the environment than in mammals. This of course does not exclude the possibility of modulating, modifying, specifying and/or extending the visual pattern recognition system of toads due to internal states and individual experience.     

Neural Coding with Graded Membrane Potential Changes and Spikes

The neural encoding of sensory stimuli is usually investigated for spike responses, although many neurons are known to convey information by graded membrane potential changes. We compare by model simulations how well different dynamical stimuli can be discriminated on the basis of spiking or graded responses. Although a continuously varying membrane potential contains more information than binary spike trains, we find situations where different stimuli can be better discriminated on the basis of spike responses than on the basis of graded responses. Spikes can be superior to graded membrane potential fluctuations if spikes sharpen the temporal structure of neuronal responses by amplifying fast transients of the membrane potential. Such fast membrane potential changes can be induced deterministically by the stimulus or can be due to membrane potential noise that is influenced in its statistical properties by the stimulus. The graded response mode is superior for discrimination between stimuli on a fine time scale.     

Alpha-Band Rhythms in Visual Task Performance: Phase-Locking by Rhythmic Sensory Stimulation

Oscillations are an important aspect of neuronal activity. Interestingly, oscillatory patterns are also observed in behaviour, such as in visual performance measures after the presentation of a brief sensory event in the visual or another modality. These oscillations in visual performance cycle at the typical frequencies of brain rhythms, suggesting that perception may be closely linked to brain oscillations. We here investigated this link for a prominent rhythm of the visual system (the alpha-rhythm, 8–12 Hz) by applying rhythmic visual stimulation at alpha-frequency (10.6 Hz), known to lead to a resonance response in visual areas, and testing its effects on subsequent visual target discrimination. Our data show that rhythmic visual stimulation at 10.6 Hz: 1) has specific behavioral consequences, relative to stimulation at control frequencies (3.9 Hz, 7.1 Hz, 14.2 Hz), and 2) leads to alpha-band oscillations in visual performance measures, that 3) correlate in precise frequency across individuals with resting alpha-rhythms recorded over parieto-occipital areas. The most parsimonious explanation for these three findings is entrainment (phase-locking) of ongoing perceptually relevant alpha-band brain oscillations by rhythmic sensory events. These findings are in line with occipital alpha-oscillations underlying periodicity in visual performance, and suggest that rhythmic stimulation at frequencies of intrinsic brain-rhythms can be used to reveal influences of these rhythms on task performance to study their functional roles.     

A Generalized Framework for Quantifying the Dynamics of EEG Event-Related Desynchronization

Brains were built by evolution to react swiftly to environmental challenges. Thus, sensory stimuli must be processed ad hoc, i.e., independent—to a large extent—from the momentary brain state incidentally prevailing during stimulus occurrence. Accordingly, computational neuroscience strives to model the robust processing of stimuli in the presence of dynamical cortical states. A pivotal feature of ongoing brain activity is the regional predominance of EEG eigenrhythms, such as the occipital alpha or the pericentral mu rhythm, both peaking spectrally at 10 Hz. Here, we establish a novel generalized concept to measure event-related desynchronization (ERD), which allows one to model neural oscillatory dynamics also in the presence of dynamical cortical states. Specifically, we demonstrate that a somatosensory stimulus causes a stereotypic sequence of first an ERD and then an ensuing amplitude overshoot (event-related synchronization), which at a dynamical cortical state becomes evident only if the natural relaxation dynamics of unperturbed EEG rhythms is utilized as reference dynamics. Moreover, this computational approach also encompasses the more general notion of a “conditional ERD,” through which candidate explanatory variables can be scrutinized with regard to their possible impact on a particular oscillatory dynamics under study. Thus, the generalized ERD represents a powerful novel analysis tool for extending our understanding of inter-trial variability of evoked responses and therefore the robust processing of environmental stimuli.     

Unconsciously Perceived Fear in Peripheral Vision Alerts the Limbic System: A MEG Study

Background

In ecological situations, threatening stimuli often come out from the peripheral vision. Such aggressive messages must trigger rapid attention to the periphery to allow a fast and adapted motor reaction. Several clues converge to hypothesize that peripheral danger presentation can trigger off a fast arousal network potentially independent of the consciousness spot.

Methodology/Principal Findings

In the present MEG study, spatio-temporal dynamics of the neural processing of danger related stimuli were explored as a function of the stimuli position in the visual field. Fearful and neutral faces were briefly presented in the central or peripheral visual field, and were followed by target faces stimuli. An event-related beamformer source analysis model was applied in three time windows following the first face presentations: 80 to 130 ms, 140 to 190 ms, and 210 to 260 ms. The frontal lobe and the right internal temporal lobe part, including the amygdala, reacted as soon as 80 ms of latency to fear occurring in the peripheral vision. For central presentation, fearful faces evoked the classical neuronal activity along the occipito-temporal visual pathway between 140 and 190 ms.

Conclusions

Thus, the high spatio-temporal resolution of MEG allowed disclosing a fast response of a network involving medial temporal and frontal structures in the processing of fear related stimuli occurring unconsciously in the peripheral visual field. Whereas centrally presented stimuli are precisely processed by the ventral occipito-temporal cortex, the related-to-danger stimuli appearing in the peripheral visual field are more efficient to produce a fast automatic alert response possibly conveyed by subcortical structures.     

Critical slowing down and noise-induced intermittency in bistable perception: bifurcation analysis

Stochastic dynamics and critical slowing down were studied experimentally and numerically near the onset of dynamical bistability in visual perception under the influence of noise. Exploring the Necker cube as the essential example of an ambiguous figure, and using its wire contrast as a control parameter, we measured dynamical hysteresis in two coexisting percepts as a function of both the velocity of the parameter change and the background luminance. The bifurcation analysis allowed us to estimate the level of cognitive noise inherent to brain neural cells activity, which induced intermittent switches between different perception states. The results of numerical simulations with a simple energy model are in good qualitative agreement with psychological experiments.     

Fronto-Central Theta Oscillations Are Related to Oscillations in Saccadic Response Times (SRT): An EEG and Behavioral Data Analysis

The phase reset hypothesis states that the phase of an ongoing neural oscillation, reflecting periodic fluctuations in neural activity between states of high and low excitability, can be shifted by the occurrence of a sensory stimulus so that the phase value become highly constant across trials (Schroeder et al., 2008). From EEG/MEG studies it has been hypothesized that coupled oscillatory activity in primary sensory cortices regulates multi sensory processing (Senkowski et al. 2008). We follow up on a study in which evidence of phase reset was found using a purely behavioral paradigm by including also EEG measures. In this paradigm, presentation of an auditory accessory stimulus was followed by a visual target with a stimulus-onset asynchrony (SOA) across a range from 0 to 404 ms in steps of 4 ms. This fine-grained stimulus presentation allowed us to do a spectral analysis on the mean SRT as a function of the SOA, which revealed distinct peak spectral components within a frequency range of 6 to 11 Hz with a modus of 7 Hz. The EEG analysis showed that the auditory stimulus caused a phase reset in 7-Hz brain oscillations in a widespread set of channels. Moreover, there was a significant difference in the average phase at which the visual target stimulus appeared between slow and fast SRT trials. This effect was evident in three different analyses, and occurred primarily in frontal and central electrodes.     

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.     

Timescales of multineuronal activity patterns reflect temporal structure of visual stimuli

The investigation of distributed coding across multiple neurons in the cortex remains to this date a challenge. Our current understanding of collective encoding of information and the relevant timescales is still limited. Most results are restricted to disparate timescales, focused on either very fast, e.g., spike-synchrony, or slow timescales, e.g., firing rate. Here, we investigated systematically multineuronal activity patterns evolving on different timescales, spanning the whole range from spike-synchrony to mean firing rate. Using multi-electrode recordings from cat visual cortex, we show that cortical responses can be described as trajectories in a high-dimensional pattern space. Patterns evolve on a continuum of coexisting timescales that strongly relate to the temporal properties of stimuli. Timescales consistent with the time constants of neuronal membranes and fast synaptic transmission (5-20 ms) play a particularly salient role in encoding a large amount of stimulus-related information. Thus, to faithfully encode the properties of visual stimuli the brain engages multiple neurons into activity patterns evolving on multiple timescales.     

End-to-end neural system identification with neural information flow

Neural information flow (NIF) provides a novel approach for system identification in neuroscience. It models the neural computations in multiple brain regions and can be trained end-to-end via stochastic gradient descent from noninvasive data. NIF models represent neural information processing via a network of coupled tensors, each encoding the representation of the sensory input contained in a brain region. The elements of these tensors can be interpreted as cortical columns whose activity encodes the presence of a specific feature in a spatiotemporal location. Each tensor is coupled to the measured data specific to a brain region via low-rank observation models that can be decomposed into the spatial, temporal and feature receptive fields of a localized neuronal population. Both these observation models and the convolutional weights defining the information processing within regions are learned end-to-end by predicting the neural signal during sensory stimulation. We trained a NIF model on the activity of early visual areas using a large-scale fMRI dataset recorded in a single participant. We show that we can recover plausible visual representations and population receptive fields that are consistent with empirical findings.