How Long Depends on How Fast—Perceived Flicker Dilates Subjective Duration

How do humans perceive the passage of time and the duration of events without a dedicated sensory system for timing? Previous studies have demonstrated that when a stimulus changes over time, its duration is subjectively dilated, indicating that duration judgments are based on the number of changes within an interval. In this study, we tested predictions derived from three different accounts describing the relation between a changing stimulus and its subjective duration as either based on (1) the objective rate of changes of the stimulus, (2) the perceived saliency of the changes, or (3) the neural energy expended in processing the stimulus. We used visual stimuli flickering at different frequencies (4–166 Hz) to study how the number of changes affects subjective duration. To this end, we assessed the subjective duration of these stimuli and measured participants'' behavioral flicker fusion threshold (the highest frequency perceived as flicker), as well as their threshold for a frequency-specific neural response to the flicker using EEG. We found that only consciously perceived flicker dilated perceived duration, such that a 2 s long stimulus flickering at 4 Hz was perceived as lasting as long as a 2.7 s steady stimulus. This effect was most pronounced at the slowest flicker frequencies, at which participants reported the most consistent flicker perception. Flicker frequencies higher than the flicker fusion threshold did not affect perceived duration at all, even if they evoked a significant frequency-specific neural response. In sum, our findings indicate that time perception in the peri-second range is driven by the subjective saliency of the stimulus'' temporal features rather than the objective rate of stimulus changes or the neural response to the changes.     

How robust are neural network models of stimulus generalization?

Artificial feed-forward neural networks are commonly used as a tool for modelling stimulus selection and animal signalling. A key finding of stimulus selection research has been generalization: if a given behaviour has been established to one stimulus, perceptually similar novel stimuli are likely to induce a similar response. Stimulus generalization, in feed-forward neural networks, automatically arises as a property of the network. This network property raises understandable concern regarding the sensitivity of the network to variation in its internal parameter values used in relation to its structure and to its training process. Researchers must have confidence that the predictions of their model follow from the underlying biology that they deliberately incorporated in the model, and not from often arbitrary choices about model implementation. We study how network training and parameter perturbations influence the qualitative and quantitative behaviour of a simple but general network. Specifically, for models of stimulus control we study the effect that parameter variation has on the shape of the generalization curves produced by the network. We show that certain network and training conditions produce undesirable artifacts that need to be avoided (or at least understood) when modelling stimulus selection.     

Searching for Optimal Sensory Signals: Iterative Stimulus Reconstruction in Closed-Loop Experiments

Shaped by evolutionary processes, sensory systems often represent behaviorally relevant stimuli with higher fidelity than other stimuli. The stimulus dependence of neural reliability could therefore provide an important clue in a search for relevant sensory signals. We explore this relation and introduce a novel iterative algorithm that allows one to find stimuli that are reliably represented by the sensory system under study. To assess the quality of a neural representation, we use stimulus reconstruction methods. The algorithm starts with the presentation of an initial stimulus (e.g. white noise). The evoked spike train is recorded and used to reconstruct the stimulus online. Within a closed-loop setup, this reconstruction is then played back to the sensory system. Iterating this procedure, the newly generated stimuli can be better and better reconstructed. We demonstrate the feasibility of this method by applying it to auditory receptor neurons in locusts. Our data show that the optimal stimuli often exhibit pronounced sub-threshold periods that are interrupted by short, yet intense pulses. Similar results are obtained for simple model neurons and suggest that these stimuli are encoded with high reliability by a large class of neurons.     

Neural representation of the acoustic biotope

Cats were stimulated with tones and with natural sounds selected from the normal acoustic environment of the animal. Neural activity evoked by the natural sounds and tones was recorded in the cochlear nucleus and in the medial geniculate body. The set of biological sounds proved to be effective in influencing neural activity of single cells at both levels in the auditory system. At the level of the cochlear nucleus the response of a neuron evoked by a natural sound stimulus could be understood reasonably well on the basis of the structure of the spectrograms of the natural sounds and the unit's responses to tones. At the level of the medial geniculate body analysis with tones did not provide sufficient information to explain the responses to natural sounds. At this level the use of an ensemble of natural sound stimuli allows the investigation of neural properties, which are not seen by analysis with simple artificial stimuli. Guidelines for the construction of an ensemble of complex natural sound stimuli, based on the ecology and ethology of the animal under investigation are discussed. This stimulus ensemble is defined as the Acoustic Biotope.     

Topography of alpha and theta oscillatory responses upon auditory and visual stimuli in humans

Brain resonance phenomena and induced rhythms in the brain recently gained importance in electroencephalographic, magnetoencephalographic and cellular studies (Ba\c sar and Bullock 1992). It was hypothesized that evoked potentials are superpositions of induced rhythms caused by resonance phenomena in neural populations (Ba\c sar et al. 1992). According to Ba\c sar (1972), such resonance phenomena are reflected in the main peaks of the amplitude frequency characteristics computed from EEG responses. The present study is based on a frequency domain approach for the evaluation of topography- and modality-dependent properties of oscillatory brain responses. EEG and evoked potentials were recorded from vertex, parietal and occipital scalp locations in 24 volunteers. Two combined methods were applied: (1) amplitude frequency characteristics were computed from the transient evoked responses, and (2) frequency components of the transient responses were obtained by adaptive digital filtering. Our main goal was to investigate theta (4--7 Hz) and alpha (8--15 Hz) response components. (1) Amplitude frequency characteristics. Auditory stimuli elicited theta-alpha compound responses in the 4--11 Hz frequency band (e.g. typical peaking frequency around 7 Hz for vertex recordings). Visual stimuli elicited alpha responses (e.g. typical peaking frequency for vertex recordings around 9--12 Hz). Frequency maxima for visual stimuli thus had main peaks at higher frequency values than frequency maxima for auditory stimuli. (2) Digital filtering confirmed these results: for vertex recordings, theta vs. alpha response amplitudes were 9 vs 6 for auditory stimuli and 5 vs 5 for visual stimuli, thus confirming a shift towards higher frequencies, i.e. a more prominent contribution of the alpha range, in the case of visual stimulation. We hypothesize that these properties might reflect site- and modality-specific features of stimulus encoding in the brain in which resonance properties of neuron populations are involved. Furthermore we emphasize the utility of the systems theory approach for a better understanding of brain function by means of EPs. Received: 25 February 1994 / Accepted in revised form: 5 August 1994     

A shift in sensory processing that enables the developing human brain to discriminate touch from pain

When and how infants begin to discriminate noxious from innocuous stimuli is a fundamental question in neuroscience [1]. However, little is known about the development of the necessary cortical somatosensory functional prerequisites in the intact human brain. Recent studies of developing brain networks have emphasized the importance of transient spontaneous and evoked neuronal bursting activity in the formation of functional circuits [2, 3]. These neuronal bursts are present during development and precede the onset of sensory functions [4, 5]. Their disappearance and the emergence of more adult-like activity are therefore thought to signal the maturation of functional brain circuitry [2, 4]. Here we show the changing patterns of neuronal activity that underlie the onset of nociception and touch discrimination in the preterm infant. We have conducted noninvasive electroencephalogram (EEG) recording of the brain neuronal activity in response to time-locked touches and clinically essential noxious lances of the heel in infants aged 28-45?weeks gestation. We show a transition in brain response following tactile and noxious stimulation from nonspecific, evenly dispersed neuronal bursts to modality-specific, localized, evoked potentials. The results suggest that specific neural circuits necessary for discrimination between touch and nociception emerge from 35-37?weeks gestation in the human brain.     

Multi-Variate EEG Analysis as a Novel Tool to Examine Brain Responses to Naturalistic Music Stimuli

Note onsets in music are acoustic landmarks providing auditory cues that underlie the perception of more complex phenomena such as beat, rhythm, and meter. For naturalistic ongoing sounds a detailed view on the neural representation of onset structure is hard to obtain, since, typically, stimulus-related EEG signatures are derived by averaging a high number of identical stimulus presentations. Here, we propose a novel multivariate regression-based method extracting onset-related brain responses from the ongoing EEG. We analyse EEG recordings of nine subjects who passively listened to stimuli from various sound categories encompassing simple tone sequences, full-length romantic piano pieces and natural (non-music) soundscapes. The regression approach reduces the 61-channel EEG to one time course optimally reflecting note onsets. The neural signatures derived by this procedure indeed resemble canonical onset-related ERPs, such as the N1-P2 complex. This EEG projection was then utilized to determine the Cortico-Acoustic Correlation (CACor), a measure of synchronization between EEG signal and stimulus. We demonstrate that a significant CACor (i) can be detected in an individual listener''s EEG of a single presentation of a full-length complex naturalistic music stimulus, and (ii) it co-varies with the stimuli’s average magnitudes of sharpness, spectral centroid, and rhythmic complexity. In particular, the subset of stimuli eliciting a strong CACor also produces strongly coordinated tension ratings obtained from an independent listener group in a separate behavioral experiment. Thus musical features that lead to a marked physiological reflection of tone onsets also contribute to perceived tension in music.     

Acoustic Oddball during NREM Sleep: A Combined EEG/fMRI Study

Background

A condition vital for the consolidation and maintenance of sleep is generally reduced responsiveness to external stimuli. Despite this, the sleeper maintains a level of stimulus processing that allows to respond to potentially dangerous environmental signals. The mechanisms that subserve these contradictory functions are only incompletely understood.

Methodology/Principal Findings

Using combined EEG/fMRI we investigated the neural substrate of sleep protection by applying an acoustic oddball paradigm during light NREM sleep. Further, we studied the role of evoked K-complexes (KCs), an electroencephalographic hallmark of NREM sleep with a still unknown role for sleep protection. Our main results were: (1) Other than in wakefulness, rare tones did not induce a blood oxygenation level dependent (BOLD) signal increase in the auditory pathway but a strong negative BOLD response in motor areas and the amygdala. (2) Stratification of rare tones by the presence of evoked KCs detected activation of the auditory cortex, hippocampus, superior and middle frontal gyri and posterior cingulate only for rare tones followed by a KC. (3) The typical high frontocentral EEG deflections of KCs were not paralleled by a BOLD equivalent.

Conclusions/Significance

We observed that rare tones lead to transient disengagement of motor and amygdala responses during light NREM sleep. We interpret this as a sleep protective mechanism to delimit motor responses and to reduce the sensitivity of the amygdala towards further incoming stimuli. Evoked KCs are suggested to originate from a brain state with relatively increased stimulus processing, revealing an activity pattern resembling novelty processing as previously reported during wakefulness. The KC itself is not reflected by increased metabolic demand in BOLD based imaging, arguing that evoked KCs result from increased neural synchronicity without altered metabolic demand.     

Changes in EEG power, acoustic evoked potentials and heart rate after mildly arousing non-acoustic priming stimuli in carp (Cyprinus carpio).

1. Changes in EEG power spectrum of carp to a priming non-acoustic stimulus followed by acoustic clicks were compared to those due to acoustic clicks delivered alone. Recordings were made from the telencephalon, midbrain and medulla. Acoustic evoked potentials (AEPs) to the clicks were also recorded. 2. EEG power changes to non-acoustic stimuli occurred over the whole 1-40 Hz frequency range and were regionally specific and consistent. 3. The changes in the EEG midfrequency 12-24 Hz power spectrum to non-acoustic stimuli were significantly correlated with changes in the AEP to subsequent clicks. An elevated medullary AEP amplitude and reduced duration were correlated with increased medullary EEG power and increased midbrain AEP duration. 4. Telencephalic EEG power changes were inversely related to changes in medullary and midbrain AEP amplitude.     

Effect of alexithymia on the event-related theta-synchronization of human EEG during reception of emotional visual stimuli

The 62-channel EEG was recorded while control non-alexithymic (n = 21) and alexithymic (n = 20) participants viewed sequentially presented neutral, pleasant and unpleasant pictures and subjectively rated them after each presentation. The event-related synchronization (ERS) to these stimuli was assessed in the theta-1 (4-6 Hr) and theta-2 (6-8 Hz) frequency bands. The obtained findings indicate that alexithymia influences perception of only emotional stimuli. In the upper theta over anterior cortical regions alexithymia vs control individuals in response to both pleasant and unpleasant stimuli manifested decreased left hemisphere ERS in the early test period of 0-200 ms along with enhanced ERS in response to negative vs positive and neutral stimuli in the right hemisphere at 200-600 ms after stimulus onset. The findings provide the first EEG evidence that alexithymia construct, associated with a cognitive deficit in initial evaluation of emotion, is indexed by disrupted early frontal synchronization in the upper theta band that can be best interpreted to reflect disregulation during appraisal of emotional stimuli.     

Stability of rapidly adapting afferent entrainment vs responsivity

Spike discharge activity was recorded from low-threshold, rapidly adapting, skin mechanoreceptive afferents (RA afferents) dissected from the median (forelimb) or tibial (hindlimb) nerves in anesthetized monkeys and cats. The spike activity was evoked by delivery of controlled sinusoidal vertical skin displacement ("flutter") stimuli to the receptive field (RF). The stimuli (15-30 Hz; 30-400 microm peak-to-peak amplitude; duration 0.8-15 s) were superimposed on a static skin indentation (0.5-1.0 mm) which was either maintained continuously throughout the run or applied trial-by-trial. The neural activity and the analog signal of the position of the stimulator probe were digitized at 10 kHz resolution and stored for off-line analysis. The main goal was to determine whether changes in the RA afferent response to skin flutter stimulation may be responsible for the enhanced capacity to discriminate stimulus frequency that accompanies a relatively brief (approximately 1 min) pre-exposure to such stimulation in humans. To this end, the spike train data were evaluated using methods that enabled independent measurement of entrainment and responsivity. Responsivity (response intensity) was measured as the average number of spikes/stimulus cycle, while entrainment (the degree to which evoked spike train activity is phase-locked to the stimulus) was quantitatively assessed using statistical techniques developed for the analysis of "circular" (directional) data, supplemented by methods based on the calculation of power spectra from point process data. The methods are demonstrated to enable quantification of RA afferent entrainment over a range of stimulus durations and amplitudes substantially greater than reported in previous studies. While RA afferent responsivity was found to decline to a minor extent (10-20%) both across and within stimulus trials, entrainment remained consistently high and stable, and exhibited no temporal trends or dependence on any other measured factor. The average phase angle of the entrained RA afferent response also remained stable both within and across trials, showing only a tendency to increase slightly during the initial 100-500 ms after stimulus onset. The results imply that the improved capacity to discriminate stimulus frequency that develops in response to an exposure to cutaneous flutter stimulation is not attributable to a change in RA afferent entrainment per se.     

Stability of rapidly adapting afferent entrainment vs responsivity

Spike discharge activity was recorded from low-threshold, rapidly adapting, skin mechanoreceptive afferents (RA afferents) dissected from the median (forelimb) or tibial (hindlimb) nerves in anesthetized monkeys and cats. The spike activity was evoked by delivery of controlled sinusoidal vertical skin displacement ("flutter") stimuli to the receptive field (RF). The stimuli (15-30 Hz; 30-400 mum peak-to-peak amplitude; duration 0.8-15 s) were superimposed on a static skin indentation (0.5-1.0 mm) which was either maintained continuously throughout the run or applied trial-by-trial. The neural activity and the analog signal of the position of the stimulator probe were digitized at 10 kHz resolution and stored for off-line analysis. The main goal was to determine whether changes in the RA afferent response to skin flutter stimulation may be responsible for the enhanced capacity to discriminate stimulus frequency that accompanies a relatively brief (approximately equal to 1 min) pre-exposure to such stimulation in humans. To this end, the spike train data were evaluated using methods that enabled independent measurement of entrainment and responsivity. Responsivity (response intensity) was measured as the average number of spikes/stimulus cycle, while entrainment (the degree to which evoked spike train activity is phase-locked to the stimulus) was quantitatively assessed using statistical techniques developed for the analysis of "circular" (directional) data, supplemented by methods based on the calculation of power spectra from point process data. The methods are demonstrated to enable quantification of RA afferent entrainment over a range of stimulus durations and amplitudes substantially greater than reported in previous studies. While RA afferent responsivity was found to decline to a minor extent (10-20%) both across and within stimulus trials, entrainment remained consistently high and stable, and exhibited no temporal trends or dependence on any other measured factor. The average phase angle of the entrained RA afferent response also remained stable both within and across trials, showing only a tendency to increase slightly during the initial 100-500 ms after stimulus onset. The results imply that the improved capacity to discriminate stimulus frequency that develops in response to an exposure to cutaneous flutter stimulation is not attributable to a change in RA afferent entrainment per se.     

Power and phase properties of oscillatory neural responses in the presence of background activity

Natural sensory inputs, such as speech and music, are often rhythmic. Recent studies have consistently demonstrated that these rhythmic stimuli cause the phase of oscillatory, i.e. rhythmic, neural activity, recorded as local field potential (LFP), electroencephalography (EEG) or magnetoencephalography (MEG), to synchronize with the stimulus. This phase synchronization, when not accompanied by any increase of response power, has been hypothesized to be the result of phase resetting of ongoing, spontaneous, neural oscillations measurable by LFP, EEG, or MEG. In this article, however, we argue that this same phenomenon can be easily explained without any phase resetting, and where the stimulus-synchronized activity is generated independently of background neural oscillations. It is demonstrated with a simple (but general) stochastic model that, purely due to statistical properties, phase synchronization, as measured by ‘inter-trial phase coherence’, is much more sensitive to stimulus-synchronized neural activity than is power. These results question the usefulness of analyzing the power and phase of stimulus-synchronized activity as separate and complementary measures; particularly in the case of attempting to demonstrate whether stimulus-synchronized neural activity is generated by phase resetting of ongoing neural oscillations.     

Brain’s alpha activity is highly reduced in euthymic bipolar disorder patients

Brain’s alpha activity and alpha responses belong to major electrical signals that are related to sensory/cognitive signal processing. The present study aims to analyze the spontaneous alpha activity and visual evoked alpha response in drug free euthymic bipolar patients. Eighteen DSM-IV euthymic bipolar patients (bipolar I n = 15, bipolar II n = 3) and 18 healthy controls were enrolled in the study. Patients needed to be euthymic at least for 4 weeks and psychotrop free for at least 2 weeks. Spontaneous EEG (4 min eyes closed, 4 min eyes open) and evoked alpha response upon application of simple visual stimuli were analyzed. EEG was recorded at 30 positions. The digital FFT-based power spectrum analysis was performed for spontaneous eyes closed and eyes open conditions and the response power spectrum was also analyzed for simple visual stimuli. In the analysis of spontaneous EEG, the ANOVA on alpha responses revealed significant results for groups (F(1,34) = 8.703; P < 0.007). Post-hoc comparisons showed that spontaneous EEG alpha power of healthy subjects was significantly higher than the spontaneous EEG alpha power of euthymic patients. Furthermore, visual evoked alpha power of healthy subjects was significantly higher than visual evoked alpha power of euthymic patients (F(1,34) = 4.981; P < 0.04). Decreased alpha activity in spontaneous EEG is an important pathological EEG finding in euthymic bipolar patients. Together with an evident decrease in evoked alpha responses, the findings may lead to a new pathway in search of biological correlates of cognitive impairment in bipolar disorder.     

Event-related potentials elicited by social commerce and electronic-commerce reviews

There is an increasing interest regarding the use of electroencephalography (EEG) in social commerce and electronic commerce (e-commerce) research. There are several reviews in the field of social commerce or e-commerce; these have great potential value and mining them is fundamental and significant. To our knowledge, EEG is rarely applied to study these. In this study, we examined the neural correlates of social commerce reviews (SCRs) and e-commerce reviews (ECRs) by using them as stimuli to evoke event-related potentials. All SCRs were from friends through a social media platform, whereas ECRs were from strangers through an e-commerce platform. The experimental design was similar to that of a priming paradigm, and included 40 pairs of stimuli consisting of product information (prime stimulus) and reviews (target stimulus). The results showed that the P300 component was successfully evoked by SCR and ECR stimuli. Moreover, the P300 components elicited by SCRs had higher amplitudes than those elicited by ECRs. These findings indicate that participants paid more attention to SCRs than to ECRs. In addition, the associations between neural responses and reviews in social commerce have the potential to assist companies in studying consumer behaviors, thus permitting them to enhance their social commerce strategies.     

How does the toad's visual system discriminate different worm-like stimuli?

Behavioral experiments show that toads exhibit stimulus- and locus-specific habituation. Different worm-like stimuli that toads can discriminate at a certain visual location form a dishabituation hierarchy. What is the neural mechanism which underlies these behaviors? This paper proposes that the toad discriminates visual objects based on temporal responses, and that discrimination is reflected in different average neuronal firing rates at some higher visual center, hypothetically anterior thalamus. This theory is developed through a large-scale neural simulation which includes retina, tectum and anterior thalamus. The neural model based on this theory predicts that retinal R2 cells play a primary role in the discrimination via tectal small pear cells (SP) and R3 cells refine the feature analysis by inhibition. The simulation demonstrates that the retinal response to the trailing edge of a stimulus is as crucial for pattern discrimination as the response to the leading edge. The new dishabituation hierarchies predicted by this model by reversing contrast and shrinking stimulus size need to be tested experimentally.     

Timing Rhythms: Perceived Duration Increases with a Predictable Temporal Structure of Short Interval Fillers

Variations in the temporal structure of an interval can lead to remarkable differences in perceived duration. For example, it has previously been shown that isochronous intervals, that is, intervals filled with temporally regular stimuli, are perceived to last longer than intervals left empty or filled with randomly timed stimuli. Characterizing the extent of such distortions is crucial to understanding how duration perception works. One account to explain effects of temporal structure is a non-linear accumulator-counter mechanism reset at the beginning of every subinterval. An alternative explanation based on entrainment to regular stimulation posits that the neural response to each filler stimulus in an isochronous sequence is amplified and a higher neural response may lead to an overestimation of duration. If entrainment is the key that generates response amplification and the distortions in perceived duration, then any form of predictability in the temporal structure of interval fillers should lead to the perception of an interval that lasts longer than a randomly filled one. The present experiments confirm that intervals filled with fully predictable rhythmically grouped stimuli lead to longer perceived duration than anisochronous intervals. No general over- or underestimation is registered for rhythmically grouped compared to isochronous intervals. However, we find that the number of stimuli in each group composing the rhythm also influences perceived duration. Implications of these findings for a non-linear clock model as well as a neural response magnitude account of perceived duration are discussed.     

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.     

Effects of stimulus transformations on estimates of sensory neuron selectivity

Stimulus selectivity of sensory systems is often characterized by analyzing response-conditioned stimulus ensembles. However, in many cases these response-triggered stimulus sets have structure that is more complex than assumed. If not taken into account, when present it will bias the estimates of many simple statistics, and distort the estimated stimulus selectivity of a neural sensory system. We present an approach that mitigates these problems by modeling some of the response-conditioned stimulus structure as being generated by a set of transformations acting on a simple stimulus distribution. This approach corrects the estimates of key statistics and counters biases introduced by the transformations. In cases involving temporal spike jitter or spatial jitter of images, the main observed effects of transformations are blurring of the conditional mean and introduction of artefacts in the spectral decomposition of the conditional covariance matrix. We illustrate this approach by analyzing and correcting a set of model stimuli perturbed by temporal and spatial jitter. We apply the approach to neurophysiological data from the cricket cercal sensory system to correct the effects of temporal jitter. Action Editor: Matthew Wiener