Visual object recognition is facilitated by temporal community structure.

Humans and others primates are highly attuned to temporal consistencies and regularities in their sensory environment and learn to predict such statistical structure. Moreover, in several instances, the presence of temporal structure has been found to facilitate procedural learning and to improve task performance. Here we extend these findings to visual object recognition and to presentation sequences in which mutually predictive objects form distinct clusters or "communities." Our results show that temporal community structure accelerates recognition learning and affects the order in which objects are learned ("onset of familiarity").

Unstructured network topology begets order-based representation by privileged neurons.

How spiking activity reverberates through neuronal networks, how evoked and spontaneous activity interacts and blends, and how the combined activities represent external stimulation are pivotal questions in neuroscience. We simulated minimal models of unstructured spiking networks in silico, asking whether and how gentle external stimulation might be subsequently reflected in spontaneous activity fluctuations. Consistent with earlier findings in silico and in vitro, we observe a privileged subpopulation of 'pioneer neurons' that, by their firing order, reliably encode previous external stimulation. We also confirm that pioneer neurons are 'sensitive' in that they are recruited by small fluctuations of population activity. We show that order-based representations rely on a 'chain' of pioneer neurons with different degrees of sensitivity and thus constitute an emergent property of collective dynamics. The forming of such representations is greatly favoured by a broadly heterogeneous connection topology-a broad 'middle class' in degree of connectedness. In conclusion, we offer a minimal model for the representational role of pioneer neurons, as observed experimentally in vitro. In addition, we show that broadly heterogeneous connectivity enhances the representational capacity of unstructured networks.

Perceptual reversals in binocular rivalry: Improved detection from OKN.

When binocular rivalry is induced by opponent motion displays, perceptual reversals are often associated with changed oculomotor behavior (Frässle, Sommer, Jansen, Naber, & Einhäuser, 2014; Fujiwara et al., 2017). Specifically, the direction of smooth pursuit phases in optokinetic nystagmus typically corresponds to the direction of motion that dominates perceptual appearance at any given time. Here we report an improved analysis that continuously estimates perceived motion in terms of "cumulative smooth pursuit." In essence, smooth pursuit segments are identified, interpolated where necessary, and joined probabilistically into a continuous record of cumulative smooth pursuit (i.e., probability of eye position disregarding blinks, saccades, signal losses, and artefacts). The analysis is fully automated and robust in healthy, developmental, and patient populations. To validate reliability, we compare volitional reports of perceptual reversals in rivalry displays, and of physical reversals in nonrivalrous control displays. Cumulative smooth pursuit detects physical reversals and estimates eye velocity more accurately than existing methods do (Frässle et al., 2014). It also appears to distinguish dominant and transitional perceptual states, detecting changes with a precision of ±100 ms. We conclude that cumulative smooth pursuit significantly improves the monitoring of binocular rivalry by means of recording optokinetic nystagmus.

Perceptual coupling induces co-rotation and speeds up alternations in adjacent bi-stable structure-from-motion objects.

When two bi-stable structure-from-motion (SFM) spheres are presented simultaneously, they tend to rotate in the same direction. This effect reflects a common state bias that is present for various multistable displays. However, it was also reported that when two spheres are positioned so that they touch each other, they tend to counterrotate instead. The latter effect is interpreted as a frictional interaction, indicating the influence of the embedded physics on our visual perception. Here, we examined the interplay between these two biases in two experiments using a wide range of conditions. Those included two SFM shapes, two types of disambiguation cues, the presence or absence of the disambiguation cues, different layout options, and two samples of observers from two different universities (in sum 26 participants). Contrary to the prior report, we observed a robust common state bias for all conditions, including those that were optimized for frictional and "gear meshing" interactions. We found that stronger coupling of perceptual states is accompanied by more frequent synchronous perceptual reversals of the two objects. However, we found that the simultaneity of the individual switches does not predict the duration of the following dominance phase. Finally, we report that stronger perceptual coupling speeds up perceptual alternations.

Collective Activity of Many Bistable Assemblies Reproduces Characteristic Dynamics of Multistable Perception.

UNLABELLED: The timing of perceptual decisions depends on both deterministic and stochastic factors, as the gradual accumulation of sensory evidence (deterministic) is contaminated by sensory and/or internal noise (stochastic). When human observers view multistable visual displays, successive episodes of stochastic accumulation culminate in repeated reversals of visual appearance. Treating reversal timing as a "first-passage time" problem, we ask how the observed timing densities constrain the underlying stochastic accumulation. Importantly, mean reversal times (i.e., deterministic factors) differ enormously between displays/observers/stimulation levels, whereas the variance and skewness of reversal times (i.e., stochastic factors) keep characteristic proportions of the mean. What sort of stochastic process could reproduce this highly consistent "scaling property?" Here we show that the collective activity of a finite population of bistable units (i.e., a generalized Ehrenfest process) quantitatively reproduces all aspects of the scaling property of multistable phenomena, in contrast to other processes under consideration (Poisson, Wiener, or Ornstein-Uhlenbeck process). The postulated units express the spontaneous dynamics of attractor assemblies transitioning between distinct activity states. Plausible candidates are cortical columns, or clusters of columns, as they are preferentially connected and spontaneously explore a restricted repertoire of activity states. Our findings suggests that perceptual representations are granular, probabilistic, and operate far from equilibrium, thereby offering a suitable substrate for statistical inference. SIGNIFICANCE STATEMENT: Spontaneous reversals of high-level perception, so-called multistable perception, conform to highly consistent and characteristic statistics, constraining plausible neural representations. We show that the observed perceptual dynamics would be reproduced quantitatively by a finite population of distinct neural assemblies, each with locally bistable activity, operating far from the collective equilibrium (generalized Ehrenfest process). Such a representation would be consistent with the intrinsic stochastic dynamics of neocortical activity, which is dominated by preferentially connected assemblies, such as cortical columns or clusters of columns. We predict that local neuron assemblies will express bistable dynamics, with spontaneous active-inactive transitions, whenever they contribute to high-level perception.

Stochastic accumulation by cortical columns may explain the scalar property of multistable perception.

The timing of certain mental events is thought to reflect random walks performed by underlying neural dynamics. One class of such events--stochastic reversals of multistable perceptions--exhibits a unique scalar property: even though timing densities vary widely, higher moments stay in particular proportions to the mean. We show that stochastic accumulation of activity in a finite number of idealized cortical columns--realizing a generalized Ehrenfest urn model--may explain these observations. Modeling stochastic reversals as the first-passage time of a threshold number of active columns, we obtain higher moments of the first-passage time density. We derive analytical expressions for noninteracting columns and generalize the results to interacting columns in simulations. The scalar property of multistable perception is reproduced by a dynamic regime with a fixed, low threshold, in which the activation of a few additional columns suffices for a reversal.

Navigating Pubertal Goldilocks: The Optimal Pace for Hierarchical Brain Organization.

Adolescence is a timed process with an onset, tempo, and duration. Nevertheless, the temporal dimension, especially the pace of maturation, remains an insufficiently studied aspect of developmental progression. The primary objective is to estimate the precise influence of pubertal maturational tempo on the configuration of associative brain regions. To this end, the connection between maturational stages and the level of hierarchical organization of large-scale brain networks in 12-13-year-old females is analyzed. Skeletal maturity is used as a proxy for pubertal progress. The degree of maturity is defined by the difference between bone age and chronological age. To assess the level of hierarchical organization in the brain, the temporal dynamic of closed eye resting state high-density electroencephalography (EEG) in the alpha frequency range is analyzed. Different levels of hierarchical order are captured by the measured asymmetry in the directionality of information flow between different regions. The calculated EEG-based entropy production of participant groups is then compared with accelerated, average, and decelerated maturity. Results indicate that an average maturational trajectory optimally aligns with cerebral hierarchical order, and both accelerated and decelerated timelines result in diminished cortical organization. This suggests that a "Goldilocks rule" of brain development is favoring a particular maturational tempo.

Pediatric computed tomography doses in Germany from 2016 to 2018 based on large-scale data collection.

PURPOSE: Accumulating evidence from epidemiological studies that pediatric computed tomography (CT) examinations can be associated with a small but non-zero excess risk for developing leukemia or brain tumor highlights the need to optimize doses of pediatric CT procedures. Mandatory dose reference levels (DRL) can support reduction of collective dose from CT imaging. Regular surveys of applied dose-related parameters are instrumental to decide when technological advances and optimized protocol design allow lower doses without sacrificing image quality. Our aim was to collect dosimetric data to support adapting current DRL to changing clinical practice. METHOD: Dosimetric data and technical scan parameters from common pediatric CT examinations were retrospectively collected directly from Picture Archiving and Communication Systems (PACS), Dose Management Systems (DMS), and Radiological Information Systems (RIS). RESULTS: We collected data from 17 institutions on 7746 CT series from the years 2016 to 2018 from examinations of the head, thorax, abdomen, cervical spine, temporal bone, paranasal sinuses and knee in patients below 18 years of age. Most of the age-stratified parameter distributions were lower than distributions from previously-analyzed data from before 2010. Most of the third quartiles were lower than German DRL at the time of the survey. CONCLUSIONS: Directly interfacing PACS, DMS, and RIS installations allows large-scale data collection but relies on high data-quality at the documentation stage. Data should be validated by expert knowledge or guided questionnaires. Observed clinical practice in pediatric CT imaging suggests lowering some DRL in Germany is reasonable.

Believable change: bistable reversals are governed by physical plausibility.

Planar motion flows can induce the illusory appearance of a volume rotating in depth ("depth from motion"; G. Sperling, & B. A. Dosher 1994). This appearance changes spontaneously from time to time, reversing simultaneously its depth and its direction of rotation. We investigated asymmetric illusory volumes, which reverse more frequently at some angles of view than at others. In three experiments, we studied spontaneous joint reversals of depth and motion, as well as induced reversals of either motion or depth alone. We find that depth reversals occur exclusively when the illusory volume is depth symmetric (so that the shape of the volume remains unchanged). In contrast, motion reversals occur at all view angles, but their frequency varies with the motion speed. The probability of joint reversals is well approximated by the product of the individual reversal probabilities, suggestive of two independent random processes. We hypothesize that reversals of illusory volumes are conditioned by prior experience of physical transformations in the visual world.

Alternative female and male developmental trajectories in the dynamic balance of human visual perception.

The numerous multistable phenomena in vision, hearing and touch attest that the inner workings of perception are prone to instability. We investigated a visual example-binocular rivalry-with an accurate no-report paradigm, and uncovered developmental and maturational lifespan trajectories that were specific for age and sex. To interpret these trajectories, we hypothesized that conflicting objectives of visual perception-such as stability of appearance, sensitivity to visual detail, and exploration of fundamental alternatives-change in relative importance over the lifespan. Computational modelling of our empirical results allowed us to estimate this putative development of stability, sensitivity, and exploration over the lifespan. Our results confirmed prior findings of developmental psychology and appear to quantify important aspects of neurocognitive phenotype. Additionally, we report atypical function of binocular rivalry in autism spectrum disorder and borderline personality disorder. Our computational approach offers new ways of quantifying neurocognitive phenotypes both in development and in dysfunction.

Spike-Dependent Dynamic Partitioning of the Locus Coeruleus Network through Noradrenergic Volume Release in a Simulation of the Nucleus Core.

The Locus coeruleus (LC) modulates various neuronal circuits throughout the brain. Its unique architectural organization encompasses a net of axonal innervation that spans the entire brain, while its somatic core is highly compact. Recent research revealed an unexpected cellular input specificity within the nucleus that can give rise to various network states that either broadcast norepinephrine signals throughout the brain or pointedly modulate specific brain areas. Such adaptive input-output functions likely surpass our existing network models that build upon a given synaptic wiring configuration between neurons. As the distances between noradrenergic neurons in the core of the LC are unusually small, neighboring neurons could theoretically impact each other via volume transmission of NE. We therefore set out to investigate if such interaction could be mediated through noradrenergic alpha2-receptors in a spiking neuron model of the LC. We validated our model of LC neurons through comparison with experimental patch-clamp data and identified key variables that impact alpha2-mediated inhibition of neighboring LC neurons. Our simulation confirmed a reliable autoinhibition of LC neurons after episodes of high neuronal activity that continue even after neuronal activity subsided. Additionally, dendro-somatic synapses inhibited spontaneous spiking in the somatic compartment of connected neurons in our model. We determined the exact position of hundreds of LC neurons in the mouse brain stem via a tissue clearing approach and, based on this, further determined that 25 percent of noradrenergic neurons have a neighboring LC neuron within less than a 25-micrometer radius. By modeling NE diffusion, we estimated that more than 15 percent of the alpha2-adrenergic receptors fraction can bind NE within such a diffusion radius. Our spiking neuron model of LC neurons predicts that repeated or long-lasting episodes of high neuronal activity induce partitioning of the gross LC network and reduce the spike rate in neighboring neurons at distances smaller than 25 µm. As these volume-mediating neighboring effects are challenging to test with the current methodology, our findings can guide future experimental approaches to test this phenomenon and its physiological consequences.

Vision: attention makes the cup flow over.

Scalp potentials are surprisingly informative about visual attention: a recent study that used them to record neural responses to up to four superimposed visual patterns simultaneously has now revealed the flow of attentional signals back to visual cortex.

Cumulative history quantifies the role of neural adaptation in multistable perception.

Neural adaptation plays an important role in multistable perception, but its effects are difficult to discern in sequences of perceptual reversals. Investigating the multistable appearance of kinetic depth and binocular rivalry displays, we introduce cumulative history as a novel statistical measure of adaptive state. We show that cumulative history-an integral of past perceptual states, weighted toward the most recent states-significantly and consistently correlates with future dominance durations: the larger the cumulative history measure, the shorter are future dominance times, revealing a robust effect of neural adaptation. The characteristic time scale of cumulative history, which may be computed by Monte Carlo methods, correlates with average dominance durations, as expected for a measure of neural adaptation. When the cumulative histories of two competing percepts are balanced, perceptual reversals take longer and their outcome becomes random, demonstrating that perceptual reversals are fluctuation-driven in the absence of adaptational bias. Our findings quantify the role of neural adaptation in multistable perception, which accounts for approximately 10% of the variability of reversal timing.

Binocular rivalry reveals an out-of-equilibrium neural dynamics suited for decision-making.

In ambiguous or conflicting sensory situations, perception is often 'multistable' in that it perpetually changes at irregular intervals, shifting abruptly between distinct alternatives. The interval statistics of these alternations exhibits quasi-universal characteristics, suggesting a general mechanism. Using binocular rivalry, we show that many aspects of this perceptual dynamics are reproduced by a hierarchical model operating out of equilibrium. The constitutive elements of this model idealize the metastability of cortical networks. Independent elements accumulate visual evidence at one level, while groups of coupled elements compete for dominance at another level. As soon as one group dominates perception, feedback inhibition suppresses supporting evidence. Previously unreported features in the serial dependencies of perceptual alternations compellingly corroborate this mechanism. Moreover, the proposed out-of-equilibrium dynamics satisfies normative constraints of continuous decision-making. Thus, multistable perception may reflect decision-making in a volatile world: integrating evidence over space and time, choosing categorically between hypotheses, while concurrently evaluating alternatives.

Cortical response to task-relevant stimuli presented outside the primary focus of attention.

Visual attention selectively enhances the neural response to a task-relevant item. But what happens when an item outside the primary focus of attention is also relevant to the task at hand? In a dual-task fMRI experiment, we studied the responses in retinotopically organized visual cortex in such a situation. Observers performed an attention-demanding task in the fovea while another, unmasked stimulus appeared in the visual periphery. With respect to this latter stimulus, observers attempted to perform either a less or a more attentionally demanding task. Both tasks increased the BOLD response to the peripheral stimulus. Behaviorally, however, only the less demanding task was performed well, whereas the demanding task was carried out near chance. What could explain the discrepancy between BOLD response and behavioral performance? A control experiment revealed that the report of the less demanding feature was severely disturbed by a mask. Moreover, the visual attributes queried by the demanding task had a significantly shorter iconic memory persistence. We conclude that, in the dual-task situation, the focus of attention initially remains with the foveal task, but subsequently shifts to the former location of the peripheral stimulus. Such a belated shift to a peripheral iconic memory (futile in one case, informative in the other) would reconcile the similar BOLD response with the disparate behavioral performance. In summary, our results show that an enhanced BOLD response is consistently associated with attentional modulation, but not with behavioral performance.

Attractors and noise: twin drivers of decisions and multistability.

Perceptual decisions are made not only during goal-directed behavior such as choice tasks, but also occur spontaneously while multistable stimuli are being viewed. In both contexts, the formation of a perceptual decision is best captured by noisy attractor dynamics. Noise-driven attractor transitions can accommodate a wide range of timescales and a hierarchical arrangement with "nested attractors" harbors even more dynamical possibilities. The attractor framework seems particularly promising for understanding higher-level mental states that combine heterogeneous information from a distributed set of brain areas.

Vision: attending the invisible.

In everyday vision, attention and awareness are hand in glove and almost impossible to tell apart. Recent work has exploited more contrived situations that allow these psychologically defined processes to be dissociated, providing insights into their respective neurophysiological correlates.

Temporal context and conditional associative learning.

BACKGROUND: We investigated how temporal context affects the learning of arbitrary visuo-motor associations. Human observers viewed highly distinguishable, fractal objects and learned to choose for each object the one motor response (of four) that was rewarded. Some objects were consistently preceded by specific other objects, while other objects lacked this task-irrelevant but predictive context. RESULTS: The results of five experiments showed that predictive context consistently and significantly accelerated associative learning. A simple model of reinforcement learning, in which three successive objects informed response selection, reproduced our behavioral results. CONCLUSIONS: Our results imply that not just the representation of a current event, but also the representations of past events, are reinforced during conditional associative learning. In addition, these findings are broadly consistent with the prediction of attractor network models of associative learning and their prophecy of a persistent representation of past objects.

Bistable perception modeled as competing stochastic integrations at two levels.

We propose a novel explanation for bistable perception, namely, the collective dynamics of multiple neural populations that are individually meta-stable. Distributed representations of sensory input and of perceptual state build gradually through noise-driven transitions in these populations, until the competition between alternative representations is resolved by a threshold mechanism. The perpetual repetition of this collective race to threshold renders perception bistable. This collective dynamics - which is largely uncoupled from the time-scales that govern individual populations or neurons - explains many hitherto puzzling observations about bistable perception: the wide range of mean alternation rates exhibited by bistable phenomena, the consistent variability of successive dominance periods, and the stabilizing effect of past perceptual states. It also predicts a number of previously unsuspected relationships between observable quantities characterizing bistable perception. We conclude that bistable perception reflects the collective nature of neural decision making rather than properties of individual populations or neurons.

A short-term memory of multi-stable perception.

It is well known that pauses in the presentation of an ambiguous display may stabilize its perceptual appearance. Here we show that this stabilization depends on an extended history spanning several dominance periods, not merely on the most recent period. Specifically, appearance after a pause often reflects less recent (but longer) dominance periods rather than more recent (but shorter) periods. Our results imply the existence of a short-tem memory for perceptual appearance that builds up over seconds, decays over minutes, and is robust to perceptual reversals. Although this memory is most evident in paused displays, it influences perceptual reversals also when display presentation continues: while the memory of one appearance prevails over that of the other, successive dominance durations are positively correlated. This highly unusual successive dependence suggests that multi-stable perception is not the memory-less 'renewal process' as which it has long been regarded. Instead, a short-term memory of appearance must be added to the multiple processes that jointly produce reversals of perceptual appearance.