Ensemble Encoding Research Articles

A refined approach to early movie box office prediction leveraging ensemble learning and feature encoding

Predicting the revenue of a movie prior to its release presents a significant challenge. The ability to predict pre-release revenue enables movie production companies to devise effective marketing strategies and mitigate the risks associated with potential box office failures. The primary hurdles in this endeavor stem from managing the myriad factors influencing box office outcomes and accurately forecasting a movie's revenue before it becomes available to the public. To overcome these challenges, we introduce a sophisticated Early Movie Box Office Prediction Model that incorporates Ensemble Learning and Feature Encoding techniques. This model amalgamates multiple foundational models, utilizing regression and decision trees to forecast box office revenues. Our composite model demonstrates superior performance over its constituent models, achieving an impressive accuracy rate of 91.4%.

The Neural Dynamics of Face Ensemble and Central Face Processing.

Extensive work has investigated the neural processing of single faces, including the role of shape and surface properties. However, much less is known about the neural basis of face ensemble perception (e.g., simultaneously viewing several faces in a crowd). Importantly, the contribution of shape and surface properties have not been elucidated in face ensemble processing. Furthermore, how single central faces are processed within the context of an ensemble remains unclear. Here, we probe the neural dynamics of ensemble representation using pattern analyses as applied to electrophysiology data in healthy adults (seven males, nine females). Our investigation relies on a unique set of stimuli, depicting different facial identities, which vary parametrically and independently along their shape and surface properties. These stimuli were organized into ensemble displays consisting of six surround faces arranged in a circle around one central face. Overall, our results indicate that both shape and surface properties play a significant role in face ensemble encoding, with the latter demonstrating a more pronounced contribution. Importantly, we find that the neural processing of the center face precedes that of the surround faces in an ensemble. Further, the temporal profile of center face decoding is similar to that of single faces, while those of single faces and face ensembles diverge extensively from each other. Thus, our work capitalizes on a new center-surround paradigm to elucidate the neural dynamics of ensemble processing and the information that underpins it. Critically, our results serve to bridge the study of single and ensemble face perception.

The influence of scene context on individual and ensemble encoding of object positions

The influence of scene context on individual and ensemble encoding of object positions

Personalized visual encoding model construction with small data

Quantifying population heterogeneity in brain stimuli-response mapping may allow insight into variability in bottom-up neural systems that can in turn be related to individual’s behavior or pathological state. Encoding models that predict brain responses to stimuli are one way to capture this relationship. However, they generally need a large amount of fMRI data to achieve optimal accuracy. Here, we propose an ensemble approach to create encoding models for novel individuals with relatively little data by modeling each subject’s predicted response vector as a linear combination of the other subjects’ predicted response vectors. We show that these ensemble encoding models trained with hundreds of image-response pairs, achieve accuracy not different from models trained on 20,000 image-response pairs. Importantly, the ensemble encoding models preserve patterns of inter-individual differences in the image-response relationship. We also show the proposed approach is robust against domain shift by validating on data with a different scanner and experimental setup. Additionally, we show that the ensemble encoding models are able to discover the inter-individual differences in various face areas’ responses to images of animal vs human faces using a recently developed NeuroGen framework. Our approach shows the potential to use existing densely-sampled data, i.e. large amounts of data collected from a single individual, to efficiently create accurate, personalized encoding models and, subsequently, personalized optimal synthetic images for new individuals scanned under different experimental conditions.

How Strong is Automaticity of Ensemble Encoding? Empirical Evidence from Ensemble Orientation and Facial Emotion

How Strong is Automaticity of Ensemble Encoding? Empirical Evidence from Ensemble Orientation and Facial Emotion

Encoding of small-scale air motion dynamics in the cricket, Acheta domesticus.

The cercal sensory system of cricket mediates the detection, localization, and identification of air current signals generated by predators, mates, and competitors. This mechanosensory system has been used extensively for experimental and theoretical studies of sensory coding at the cellular and system levels. It is currently thought that sensory interneurons (INs) in the terminal abdominal ganglion extract information about the direction, velocity, and acceleration of the air currents in the animal's immediate environment and project a coarse-coded representation of those parameters to higher centers. All feature detection is thought to be carried out in higher ganglia by more complex, specialized circuits. We present results that force a substantial revision of current hypotheses. Using multiple extracellular recordings and a special sensory stimulation device, we demonstrate that four well-studied interneurons in this system respond with high sensitivity and selectivity to complex dynamic multidirectional features of air currents that have a spatial scale smaller than the physical dimensions of the cerci. The INs showed much greater sensitivity for these features than for unidirectional bulk-flow stimuli used in previous studies. Thus, in addition to participating in the ensemble encoding of bulk airflow stimulus characteristics, these interneurons are capable of operating as feature detectors for naturalistic stimuli. In this sense, these interneurons are encoding and transmitting information about different aspects of their stimulus environment; they are multiplexing information. Major aspects of the stimulus-response specificity of these interneurons can be understood from the dendritic anatomy and connectivity with the sensory afferent map.NEW & NOTEWORTHY A set of sensory interneurons that have been studied for over 30 years by several different research groups were discovered to have previously unknown encoding characteristics. As well as encoding the direction of bulk airflow with a coarse-coding scheme as shown in previous studies, these interneurons are also responsive to very small-scale, directionally complex air current waveforms. This feature sensitivity can be understood in terms of the cells' complex dendritic branching patterns.

Comparison of prefrontal cortex sucrose seeking ensembles engaged in multiple seeking sessions: Context is key.

Encoding of memories, including those associated with prior drug or reward, is thought to take place within distinct populations of neurons, termed ensembles. Neuronal ensembles for drug- and reward-seeking have been identified in regions of the medial prefrontal cortex, but much of our understanding of these ensembles is based on experiments that take place in a single reward-associated environment and measure ensemble encoding over short durations of time. In contrast, reward seeking behavior is evident across different reward-associated environments and persists over time. Using TetTag mice and Fos immunohistochemistry, we examined the relationship between persistent sucrose-seeking and ensemble encoding in mice that undergo seeking sessions in the same or different sucrose self-administration contexts 2weeks apart. We found that prelimbic (PrL) and anterior cingulate cortex ensembles tagged in the first seeking session were highly sensitive to the context in which a second seeking session took place: reactivation of these ensembles was reduced in the same context but elevated in a distinct sucrose self-administration context. Correlational analyses revealed that ensemble reactivation in the PrL was proportional to the persistence of sucrose seeking behavior across sessions in differing ways in female mice. In the same context, reactivation was proportional to the persistence of non-reinforced operant responses, whereas in a distinct context, reactivation was proportional to the persistence of non-reinforced head entries into the sucrose receptacle. This study underlines the importance of the medial prefrontal cortex importance in maintaining a reward-seeking ensemble over time and identifies context-dependent changes in behavioral correlates of ensemble reactivation.

Global and local interference effects in ensemble encoding are best explained by interactions between summary representations of the mean and the range

Through ensemble encoding, the visual system compresses redundant statistical properties from multiple items into a single summary metric (e.g., average size). Numerous studies have shown that global summary information is extracted quickly, does not require access to single-item representations, and often interferes with reports of single items from the set. Yet a thorough understanding of ensemble processing would benefit from a more extensive investigation at the local level. Thus, the purpose of this study was to provide a more critical inspection of global-local processing in ensemble perception. Taking inspiration from Navon (Cognitive Psychology, 9(3), 353-383, 1977), we employed a novel paradigm that independently manipulates the degree of interference at the global (mean) or local (single item) level of the ensemble. Initial results were consistent with reciprocal interference between global and local ensemble processing. However, further testing revealed that local interference effects were better explained by interference from another summary statistic, the range of the set. Furthermore, participants were unable to disambiguate single items from the ensemble display from other items that were within the ensemble range but, critically, were not actually present in the ensemble. Thus, it appears that local item values are likely inferred based on their relationship to higher-order summary statistics such as the range and the mean. These results conflict with claims that local information is captured alongside global information in summary representations. In such studies, successful identification of set members was not compared with misidentification of items within the range, but which were nevertheless not presented within the set.

Synergy between research on ensemble perception, data visualization, and statistics education: A tutorial review.

In the age of big data, we are constantly inventing new data visualizations to consolidate massive amounts of numerical information into smaller and more digestible visual formats. These data visualizations use various visual features to convey quantitative information, such as spatial position in scatter plots, color saturation in heat maps, and area in dot maps. These data visualizations are typically composed of ensembles, or groups of related objects, that together convey information about a data set. Ensemble perception, or one's ability to perceive summary statistics from an ensemble, such as the mean, has been used as a foundation for understanding and explaining the effectiveness of certain data visualizations. However, research in data visualization has revealed some perceptual biases and conceptual difficulties people face when trying to utilize the information in these graphs. In this tutorial review, we will provide a broad overview of research conducted in ensemble perception, discuss how principles of ensemble encoding have been applied to the research in data visualization, and showcase the barriers graphs can pose to learning statistical concepts, using histograms as a specific example. The goal of this tutorial review is to highlight possible connections between three areas of research-ensemble perception, data visualization, and statistics education-and to encourage research in the practical applications of ensemble perception in solving real-world problems in statistics education.

Internally Noisy Cortical Processing Underlies Failures to Perceive Sounds in External Noise

SUMMARYCorrelational evidence in humans suggests that specific difficulties hearing in noisy, social settings may reflect premature auditory nerve degeneration. Here, we partially eliminated cochlear afferent neurons in mice and found direct behavioral evidence for selective detection deficits in background noise. To identify central determinants for this perceptual disorder, we tracked daily changes in ensembles of auditory cortex parvalbumin-expressing inhibitory neurons and surrounding pyramidal neurons with chronic two-photon calcium imaging. Primary auditory neuropathy (PAN) tipped the cortical excitatory-inhibitory balance towards net hyperactivity, elevated correlated activity, and disrupted adaptation to background noise. In control conditions, layer 2/3 ensemble encoding of the target sound could accurately classify hit or miss trials in background noise. After PAN, miss trials in background noise were instead predicted from random surges of synchronized activity occurring prior to target onset. These data reveal sources of internal cortical noise underlying failures to perceive sounds in external noise.

Encoding perceptual ensembles during visual search in peripheral vision.

Observers can learn complex statistical properties of visual ensembles, such as their probability distributions. Even though ensemble encoding is considered critical for peripheral vision, whether observers learn such distributions in the periphery has not been studied. Here, we used a visual search task to investigate how the shape of distractor distributions influences search performance and ensemble encoding in peripheral and central vision. Observers looked for an oddly oriented bar among distractors taken from either uniform or Gaussian orientation distributions with the same mean and range. The search arrays were either presented in the foveal or peripheral visual fields. The repetition and role reversal effects on search times revealed observers’ internal model of distractor distributions. Our results showed that the shape of the distractor distribution influenced search times only in foveal, but not in peripheral search. However, role reversal effects revealed that the shape of the distractor distribution could be encoded peripherally depending on the interitem spacing in the search array. Our results suggest that, although peripheral vision might rely heavily on summary statistical representations of feature distributions, it can also encode information about the distributions themselves.

Ensemble coding of facial identity is not refined by experience: Evidence from other-race and inverted faces.

The ability to recognize identity despite within-person variability in appearance is likely a face-specific skill and shaped by experience. Ensemble coding - the automatic extraction of the average of a stimulus array - has been proposed as a mechanism underlying face learning (allowing one to recognize novel instances of a newly learned face). We investigated whether ensemble encoding, like face learning and recognition, is refined by experience by testing participants with upright own-race faces and two categories of faces with which they lacked experience: other-race faces (Experiment 1) and inverted faces (Experiment 2). Participants viewed four images of an unfamiliar identity and then were asked whether a test image of that same identity had been in the study array. Each test image was a matching exemplar (from the array), matching average (the average of the images in the array), non-matching exemplar (a novel image of the same identity), or non-matching average (an average of four different images of the same identity). Adults showed comparable ensemble coding for all three categories (i.e., reported that matching averages had been present more than non-matching averages), providing evidence that this early stage of face learning is not shaped by face-specific experience.

Ensemble encoding of action speed by striatal fast-spiking interneurons.

Striatal fast-spiking interneurons (FSIs) potently inhibit the output neurons of the striatum and, as such, powerfully modulate action learning. Through electrical synaptic coupling, FSIs are theorized to temporally coordinate their activity. This has important implications for their ability to temporally summate inhibition on downstream striatal projection neurons. While some in vivo single-unit electrophysiological recordings of putative FSIs support coordinated firing, others do not. Moreover, it is unclear as to what aspect of action FSIs encode. To address this, we used in vivo calcium imaging of genetically identified FSIs in freely moving mice and applied machine learning analyses to decipher the relationship between FSI activity and movement. We report that FSIs exhibit ensemble activity that encodes the speed of action sub-components, including ambulation and head movements. These results suggest FSI population dynamics fit within a Hebbian model for ensemble inhibition of striatal output guiding action.

Spike-timing-dependent ensemble encoding by non-classically responsive cortical neurons.

Neurons recorded in behaving animals often do not discernibly respond to sensory input and are not overtly task-modulated. These non-classically responsive neurons are difficult to interpret and are typically neglected from analysis, confounding attempts to connect neural activity to perception and behavior. Here, we describe a trial-by-trial, spike-timing-based algorithm to reveal the coding capacities of these neurons in auditory and frontal cortex of behaving rats. Classically responsive and non-classically responsive cells contained significant information about sensory stimuli and behavioral decisions. Stimulus category was more accurately represented in frontal cortex than auditory cortex, via ensembles of non-classically responsive cells coordinating the behavioral meaning of spike timings on correct but not error trials. This unbiased approach allows the contribution of all recorded neurons - particularly those without obvious task-related, trial-averaged firing rate modulation - to be assessed for behavioral relevance on single trials.

Prior experience informs ensemble encoding.

People quickly form summary representations that capture the statistical structure in a set of simultaneously-presented objects. We present evidence that such ensemble encoding is informed not only by the presented set of objects, but also by a meta-ensemble, or prototype, that captures the structure of previously viewed stimuli. Participants viewed four objects (shaded squares in Experiment 1; emotional expressions in Experiment 2) and estimated their average by adjusting a response object. Estimates were biased toward the central value of previous stimuli, consistent with Bayesian models of how people combine hierarchical sources of information. The results suggest that an inductively learned prototype may serve as a source of prior information to adjust ensemble estimates. To the extent that real environments present statistical structure in a given moment as well as consistently over time, ensemble encoding in real-world situations ought to take advantage of both kinds of regularity.

Relating the perception of visual ensemble statistics to individual levels of autistic traits.

Integrating information across the visual field into an ensemble (e.g., seeing the forest from the trees) is an effective strategy to efficiently process the visual world, and one that is often impaired in autism spectrum disorder. Individual differences in sensory processing predict ensemble encoding, providing a potential mechanism for differing perceptual strategies across individuals, and possibly across diagnostic groups exhibiting atypical sensory processing. Here, we explore whether ensemble encoding is associated with traits associated with autism spectrum disorder (ASD). Participants (N=68) were presented with an ensemble display consisting of circles of varying sizes and colors, and were asked to remember the size of the red and blue circles, while ignoring the green circles. Participants were then cued to a target location after a brief delay, and instructed to report the remembered size of the circle they had previously viewed in that location, as ensemble information commonly biases memory for individual objects toward the probed mean of a set of similar objects. The Autism-spectrum Quotient (AQ) was completed to measure each individual's level of autistic traits. We found that an individual's level of ensemble perception, measured as their bias toward the probed mean, was negatively associated with a higher level of ASD traits. These results suggest that individuals with higher levels of ASD traits are less likely to integrate perceptual information. These findings may shed light on different perceptual processing within the autism spectrum, and provide insight into the relationship between individual differences and ensemble encoding.

Embedded ensemble encoding hypothesis: The role of the “Prepared” cell

We here reconsider current theories of neural ensembles in the context of recent discoveries about neuronal dendritic physiology. The key physiological observation is that the dendritic plateau potential produces sustained depolarization of the cell body (amplitude 10-20 mV, duration 200-500 ms). Our central hypothesis is that synaptically-evoked dendritic plateau potentials lead to a prepared state of a neuron that favors spike generation. The plateau both depolarizes the cell toward spike threshold, and provides faster response to inputs through a shortened membrane time constant. As a result, the speed of synaptic-to-action potential (AP) transfer is faster during the plateau phase. Our hypothesis relates the changes from "resting" to "depolarized" neuronal state to changes in ensemble dynamics and in network information flow. The plateau provides the Prepared state (sustained depolarization of the cell body) with a time window of 200-500 ms. During this time, a neuron can tune into ongoing network activity and synchronize spiking with other neurons to provide a coordinated Active state (robust firing of somatic APs), which would permit "binding" of signals through coordination of neural activity across a population. The transient Active ensemble of neurons is embedded in the longer-lasting Prepared ensemble of neurons. We hypothesize that "embedded ensemble encoding" may be an important organizing principle in networks of neurons.

Biased by the Group: Memory for an Emotional Expression Biases Towards the Ensemble

An emotional expression can be misremembered as more similar to previously seen expressions than it actually was – demonstrating inductive category effects for emotional expressions. Given that memory is influenced over time, we sought to determine whether memory for a single expression would be similarly influenced by other expressions viewed simultaneously. In other words, we test whether the ability to encode statistical features of an ensemble (i.e., ensemble encoding) is leveraged when attempting to recall a single expression from the ensemble. In three preregistered experiments, participants saw an ensemble of 4 expressions, one neutral and the three either happy or sad. After a delay, participants were asked to reproduce the neutral face by adjusting a response face’s expression. In Experiment 1, the ensemble comprised images of the same actor; in Experiments 2 and 3, images were comprised of individuals varying race and gender. In each experiment we demonstrated that even after only a single exposure, memory for the neutral expression in the happy group was biased happier relative to the same expression in the sad group. Data and syntax can be found at https://osf.io/gcbez/.

Correlates of decisional dynamics in the dorsal anterior cingulate cortex.

We hypothesized that during binary economic choice, decision makers use the first option they attend as a default to which they compare the second. To test this idea, we recorded activity of neurons in the dorsal anterior cingulate cortex (dACC) of macaques choosing between gambles presented asynchronously. We find that ensemble encoding of the value of the first offer includes both choice-dependent and choice-independent aspects, as if reflecting a partial decision. That is, its responses are neither entirely pre- nor post-decisional. In contrast, coding of the value of the second offer is entirely decision dependent (i.e., post-decisional). This result holds even when offer-value encodings are compared within the same time period. Additionally, we see no evidence for 2 pools of neurons linked to the 2 offers; instead, all comparison appears to occur within a single functionally homogenous pool of task-selective neurons. These observations suggest that economic choices reflect a context-dependent evaluation of attended options. Moreover, they raise the possibility that value representations reflect, to some extent, a tentative commitment to a choice.

P.2.g.001 - Cell cycle regulation of the hippocampal progenitor cells in an animal model of depression and after fluoxetine treatment

Studies have reported divergent behavioral effects of depression on spontaneous vs. stimulus-evoked pain. However, the underlying neurobiological mechanisms are still unclear. The present study used a depression model of unpredictable chronic mild stress (UCMS) and pain models for spontaneous pain (i.e., the formalin test) and acute evoked pain (i.e., noxious thermal stimulation) in rats. The activity of neurons within thalamo-cortical circuits in the lateral and medial pain pathways was recorded by a multiple-channel recording technique, and behaviors were observed simultaneously. The results confirmed our previous findings that rats exposed to UCMS tended to exhibit decreased pain sensitivity to experimental stimuli but increased behavioral responses to ongoing pain. Based on the analysis of single-unit responses, the results demonstrated that the processing of spontaneous vs. evoked pain in a depressive-like state was altered in the opposite direction (activation vs. inhibition). The ensemble encoding analysis revealed that exposure to UCMS gave rise to enhanced inter-regional functional connectivity in spontaneous pain processing, but did not influence that of evoked pain. In addition, different brain activation patterns underlying the processing of spontaneous vs. evoked pain were observed. These findings revealed that the distinct response patterns of neurons within the pain-related brain circuits, especially in the affective pain pathway, mediate the divergent effects of depression on spontaneous vs. evoked pain. This is also the first report on the electrophysiology of depression models that provides direct evidence that the effect of depression on spontaneous and evoked pain may involve different brain mechanisms.