We present here the most comprehensive analysis to date of neuroaesthetic processing by reporting the results of voxel-based meta-analyses of 93 neuroimaging studies of positive-valence aesthetic appraisal across four sensory modalities. The results demonstrate that the most concordant area of activation across all four modalities is the right anterior insula, an area typically associated with visceral perception, especially of negative valence (disgust, pain, etc.). We argue that aesthetic processing is, at its core, the appraisal of the valence of perceived objects. This appraisal is in no way limited to artworks but is instead applicable to all types of perceived objects. Therefore, one way to naturalize aesthetics is to argue that such a system evolved first for the appraisal of objects of survival advantage, such as food sources, and was later co-opted in humans for the experience of artworks for the satisfaction of social needs.Copyright © 2011 Elsevier Inc. All rights reserved.

Decisions to act while pursuing goals in the presence of danger must be made quickly but safely. Premature decisions risk injury or death, whereas postponing decisions risk goal loss. Here we show how mice resolve these competing demands. Using microstructural behavioral analyses, we identified the spatiotemporal dynamics of approach-avoidance decisions under motivational conflict in male mice. Then we used cognitive modeling to show that these dynamics reflect the speeded decision-making mechanisms used by humans and nonhuman primates, with mice trading off decision speed for safety of choice when danger loomed. Using calcium imaging in paraventricular thalamus and optogenetic inhibition of the prelimbic cortex to paraventricular thalamus pathway, we show that this speed-safety trade off occurs because increases in paraventricular thalamus activity increase decision caution, thereby increasing approach-avoid decision times in the presence of danger. Our findings demonstrate that a discrete brain circuit involving the paraventricular thalamus and its prefrontal input adjusts decision caution during motivational conflict, trading off decision speed for decision safety when danger is close. We identify the corticothalamic pathway as central to cognitive control during decision-making under conflict. Foraging animals balance the need to seek food and energy against the conflicting needs to avoid injury and predation. This competition is fundamental to survival but rarely has a stable, correct solution. Here we show that approach-avoid decisions under motivational conflict involve strategic adjustments in decision caution controlled via a top-down corticothalamic pathway from the prelimbic cortex to the paraventricular thalamus. We identify a novel corticothalamic mechanism for cognitive control that is applicable across a range of motivated behaviors and mark paraventricular thalamus and its prefrontal cortical input as targets to remediate the deficits in decision caution characteristic of unsafe and impulsive choices.Copyright © 2022 Choi, Husić et al.

Research on overeating and self-regulation has associated eating pleasure with short-term visceral impulses triggered by hunger, external cues, or internal emotional urges. Drawing on research on the social and cultural dimensions of eating, we contrast this approach with what we call "Epicurean" eating pleasure, which is the enduring pleasure derived from the aesthetic appreciation of the sensory and symbolic value of the food. To contrast both approaches, we develop and test a scale measuring Epicurean eating pleasure tendencies and show that they are distinct from the tendency to experience visceral pleasure (measured using the external eating and emotional eating scales). We find that Epicurean eating pleasure is more prevalent among women than men but is independent of age, income and education. Unlike visceral eating pleasure tendencies, Epicurean eating tendencies are associated with a preference for smaller food portions and higher wellbeing, and not associated with higher BMI. Overall, we argue that the moralizing approach equating the pleasure of eating with 'low-level' visceral urges should give way to a more holistic approach which recognizes the positive role of Epicurean eating pleasure in healthy eating and wellbeing.Copyright © 2015 Elsevier Ltd. All rights reserved.

We have developed a toolbox and graphic user interface, EEGLAB, running under the crossplatform MATLAB environment (The Mathworks, Inc.) for processing collections of single-trial and/or averaged EEG data of any number of channels. Available functions include EEG data, channel and event information importing, data visualization (scrolling, scalp map and dipole model plotting, plus multi-trial ERP-image plots), preprocessing (including artifact rejection, filtering, epoch selection, and averaging), independent component analysis (ICA) and time/frequency decompositions including channel and component cross-coherence supported by bootstrap statistical methods based on data resampling. EEGLAB functions are organized into three layers. Top-layer functions allow users to interact with the data through the graphic interface without needing to use MATLAB syntax. Menu options allow users to tune the behavior of EEGLAB to available memory. Middle-layer functions allow users to customize data processing using command history and interactive 'pop' functions. Experienced MATLAB users can use EEGLAB data structures and stand-alone signal processing functions to write custom and/or batch analysis scripts. Extensive function help and tutorial information are included. A 'plug-in' facility allows easy incorporation of new EEG modules into the main menu. EEGLAB is freely available (http://www.sccn.ucsd.edu/eeglab/) under the GNU public license for noncommercial use and open source development, together with sample data, user tutorial and extensive documentation.

Attributing meaning to diverse visual input is a core feature of human cognition. Violating environmental expectations (e.g., a toothbrush in the fridge) induces a late event-related negativity of the event-related potential/ERP. This N400 ERP has not only been linked to the semantic processing of language, but also to objects and scenes. Inconsistent object-scene relationships are additionally associated with an earlier negative deflection of the EEG signal between 250 and 350 ms. This N300 is hypothesized to reflect pre-semantic perceptual processes. To investigate whether these two components are truly separable or if the early object-scene integration activity (250-350 ms) shares certain levels of processing with the late neural correlates of meaning processing (350-500 ms), we used time-resolved multivariate pattern analysis (MVPA) where a classifier trained at one time point in a trial (e.g., during the N300 time window) is tested at every other time point (i.e., including the N400 time window). Forty participants were presented with semantic inconsistencies, in which an object was inconsistent with a scene's meaning. Replicating previous findings, our manipulation produced significant N300 and N400 deflections. MVPA revealed above chance decoding performance for classifiers trained during time points of the N300 component and tested during later time points of the N400, and vice versa. This provides no evidence for the activation of two separable neurocognitive processes following the violation of context-dependent predictions in visual scene perception. Our data supports the early appearance of high-level, context-sensitive processes in visual cognition.Copyright © 2018 Elsevier Ltd. All rights reserved.

Optimal decision-making often requires exercising self-control. A growing fMRI literature has implicated the dorsolateral prefrontal cortex (dlPFC) in successful self-control, but due to the limitations inherent in BOLD measures of brain activity, the neurocomputational role of this region has not been resolved. Here we exploit the high temporal resolution and whole-brain coverage of event-related potentials (ERPs) to test the hypothesis that dlPFC affects dietary self-control through two different mechanisms: attentional filtering and value modulation. Whereas attentional filtering of sensory input should occur early in the decision process, value modulation should occur later on, after the computation of stimulus values begins. Hungry human subjects were asked to make food choices while we measured neural activity using ERP in a natural condition, in which they responded freely and did not exhibit a tendency to regulate their diet, and in a self-control condition, in which they were given a financial incentive to lose weight. We then measured various neural markers associated with the attentional filtering and value modulation mechanisms across the decision period to test for changes in neural activity during the exercise of self-control. Consistent with the hypothesis, we found evidence for top-down attentional filtering early on in the decision period (150-200 ms poststimulus onset) as well as evidence for value modulation later in the process (450-650 ms poststimulus onset). We also found evidence that dlPFC plays a role in the deployment of both mechanisms.

Objects that are semantically related to the visual scene context are typically better recognized than unrelated objects. While context effects on object recognition are well studied, the question which particular visual information of an object's surroundings modulates its semantic processing is still unresolved. Typically, one would expect contextual influences to arise from high-level, semantic components of a scene but what if even low-level features could modulate object processing? Here, we generated seemingly meaningless textures of real-world scenes, which preserved similar summary statistics but discarded spatial layout information. In Experiment 1, participants categorized such textures better than colour controls that lacked higher-order scene statistics while original scenes resulted in the highest performance. In Experiment 2, participants recognized briefly presented consistent objects on scenes significantly better than inconsistent objects, whereas on textures, consistent objects were recognized only slightly more accurately. In Experiment 3, we recorded event-related potentials and observed a pronounced mid-central negativity in the N300/N400 time windows for inconsistent relative to consistent objects on scenes. Critically, inconsistent objects on textures also triggered N300/N400 effects with a comparable time course, though less pronounced. Our results suggest that a scene's low-level features contribute to the effective processing of objects in complex real-world environments.

While scene context is known to facilitate object recognition, little is known about which contextual "ingredients" are at the heart of this phenomenon. Here, we address the question of whether the materials that frequently occur in scenes (e.g., tiles in a bathroom) associated with specific objects (e.g., a perfume) are relevant for the processing of that object. To this end, we presented photographs of consistent and inconsistent objects (e.g., perfume vs. pinecone) superimposed on scenes (e.g., a bathroom) and close-ups of materials (e.g., tiles). In Experiment 1, consistent objects on scenes were named more accurately than inconsistent ones, while there was only a marginal consistency effect for objects on materials. Also, we did not find any consistency effect for scrambled materials that served as color control condition. In Experiment 2, we recorded event-related potentials and found N300/N400 responses-markers of semantic violations-for objects on inconsistent relative to consistent scenes. Critically, objects on materials triggered N300/N400 responses of similar magnitudes. Our findings show that contextual materials indeed affect object processing-even in the absence of spatial scene structure and object content-suggesting that material is one of the contextual "ingredients" driving scene context effects.© 2021. The Author(s).

An experiment conducted in a naturalistic dining context is reported, in which the impact of different styles of plating on diners' experience of the food was assessed. A hundred and sixty three diners were separated into two groups during a luncheon event held in a large dining room. Each group of diners was served the same menu, with a variation in the visual presentation of the ingredients on the plate. The results revealed that the diners were willing to pay significantly more for the appetizer (a salad), when arranged in an artistically-inspired manner (M = £5.94 vs. £4.10). The main course was liked more, and considered more artistic, when the various elements were presented in the centre of the plate, rather than placed off to one side. The participants also reported being willing to pay significantly more for the centred than for the offset plating (M = £15.35 vs. £11.65). These results are consistent with the claim that people "eat first with their eyes", and that a diner's experience of the very same ingredients can be significantly enhanced (or diminished) simply by changing the visual layout of the food elements of the dish. Results such as these suggest that theories regarding the perception of food can potentially be confirmed (or disconfirmed) outside of the confines of the laboratory (i.e., in naturalistic dining settings).Copyright © 2015 Elsevier Ltd. All rights reserved.

In theoretical accounts of perceptual decision-making, a decision variable integrates noisy sensory evidence and determines action through a boundary-crossing criterion. Signals bearing these very properties have been characterized in single neurons in monkeys, but have yet to be directly identified in humans. Using a gradual target detection task, we isolated a freely evolving decision variable signal in human subjects that exhibited every aspect of the dynamics observed in its single-neuron counterparts. This signal could be continuously tracked in parallel with fully dissociable sensory encoding and motor preparation signals, and could be systematically perturbed mid-flight during decision formation. Furthermore, we found that the signal was completely domain general: it exhibited the same decision-predictive dynamics regardless of sensory modality and stimulus features and tracked cumulative evidence even in the absence of overt action. These findings provide a uniquely clear view on the neural determinants of simple perceptual decisions in humans.

Decades ago, discussion of an impending global pandemic of obesity was thought of as heresy. But in the 1970s, diets began to shift towards increased reliance upon processed foods, increased away-from-home food intake, and increased use of edible oils and sugar-sweetened beverages. Reductions in physical activity and increases in sedentary behavior began to be seen as well. The negative effects of these changes began to be recognized in the early 1990s, primarily in low- and middle-income populations, but they did not become clearly acknowledged until diabetes, hypertension, and obesity began to dominate the globe. Now, rapid increases in the rates of obesity and overweight are widely documented, from urban and rural areas in the poorest countries of sub-Saharan Africa and South Asia to populations in countries with higher income levels. Concurrent rapid shifts in diet and activity are well documented as well. An array of large-scale programmatic and policy measures are being explored in a few countries; however, few countries are engaged in serious efforts to prevent the serious dietary challenges being faced.© 2012 International Life Sciences Institute.

The diffusion decision model allows detailed explanations of behavior in two-choice discrimination tasks. In this article, the model is reviewed to show how it translates behavioral data-accuracy, mean response times, and response time distributions-into components of cognitive processing. Three experiments are used to illustrate experimental manipulations of three components: stimulus difficulty affects the quality of information on which a decision is based; instructions emphasizing either speed or accuracy affect the criterial amounts of information that a subject requires before initiating a response; and the relative proportions of the two stimuli affect biases in drift rate and starting point. The experiments also illustrate the strong constraints that ensure the model is empirically testable and potentially falsifiable. The broad range of applications of the model is also reviewed, including research in the domains of aging and neurophysiology.

Most studies exploring multisensory integration have used clearly perceivable stimuli. According to the principle of inverse effectiveness, the added neural and behavioral benefit of integrating clear stimuli is reduced in comparison to stimuli with degraded and less salient unisensory information. Traditionally, speed and accuracy measures have been analyzed separately with few studies merging these to gain an understanding of speed-accuracy trade-offs in multisensory integration. In two separate experiments, we assessed multisensory integration of naturalistic audio-visual objects consisting of individually-tailored perithreshold dynamic visual and auditory stimuli, presented within a multiple-choice task, using a Bayesian Hierarchical Drift Diffusion Model that combines response time and accuracy. For both experiments, unisensory stimuli were degraded to reach a 75% identification accuracy level for all individuals and stimuli to promote multisensory binding. In Experiment 1, we subsequently presented uni- and their respective bimodal stimuli followed by a 5-alternative-forced-choice task. In Experiment 2, we controlled for low-level integration and attentional differences. Both experiments demonstrated significant superadditive multisensory integration of bimodal perithreshold dynamic information. We present evidence that the use of degraded sensory stimuli may provide a link between previous findings of inverse effectiveness on a single neuron level and overt behavior. We further suggest that a combined measure of accuracy and reaction time may be a more valid and holistic approach of studying multisensory integration and propose the application of drift diffusion models for studying behavioral correlates as well as brain-behavior relationships of multisensory integration.Copyright © 2015 Elsevier Ltd. All rights reserved.

When decisions are made under speed pressure, "urgency" signals elevate neural activity toward action-triggering thresholds independent of the sensory evidence, thus incurring a cost to choice accuracy. While urgency signals have been observed in brain circuits involved in preparing actions, their influence at other levels of the sensorimotor pathway remains unknown. We used a novel contrast-comparison paradigm to simultaneously trace the dynamics of sensory evidence encoding, evidence accumulation, motor preparation, and muscle activation in humans. Results indicate speed pressure impacts multiple sensorimotor levels but in crucially distinct ways. Evidence-independent urgency was applied to cortical action-preparation signals and downstream muscle activation, but not directly to upstream levels. Instead, differential sensory evidence encoding was enhanced in a way that partially countered the negative impact of motor-level urgency on accuracy, and these opposing sensory-boost and motor-urgency effects had knock-on effects on the buildup and pre-response amplitude of a motor-independent representation of cumulative evidence.

Objects in the real world typically appear within a broader context, having relationships with the environment. Do these relations between objects and the contexts in which they appear affect object identification? Previous findings of an N300 component evoked by scene-incongruent objects were taken as evidence for such an effect, since N300 is held to reflect object identification processes. Yet this conjuncture was never directly tested, and ignores differences between the fronto-central incongruency-evoked N300 and the typically bi-polar fronto-occipital identification-related N300. Here, the possible influence of context on object identification was examined by manipulating both object-scene congruency and object identifiability. N300 effects were found both for incongruity and for identifiability, in line with previous studies. Critically, a comparison of divergence times of waveforms evoked by congruent/incongruent objects and waveforms evoked by unidentifiable objects showed that incongruent objects started to diverge from unidentifiable ones later than congruent objects did. This provides first direct evidence for the effect of scene context on object identification; arguably, rapidly extracted gist activates scene-congruent schemas which facilitate the identification of congruent objects in comparison to incongruent ones.Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Two-choice response times are a common type of data, and much research has been devoted to the development of process models for such data. However, the practical application of these models is notoriously complicated, and flexible methods are largely nonexistent. We combine a popular model for choice response times-the Wiener diffusion process-with techniques from psychometrics in order to construct a hierarchical diffusion model. Chief among these techniques is the application of random effects, with which we allow for unexplained variability among participants, items, or other experimental units. These techniques lead to a modeling framework that is highly flexible and easy to work with. Among the many novel models this statistical framework provides are a multilevel diffusion model, regression diffusion models, and a large family of explanatory diffusion models. We provide examples and the necessary computer code.(c) 2011 APA, all rights reserved

Implicit memory and explicit memory are fundamentally different manifestations of memory storage in the brain. Yet, conceptual fluency driven by previous experience could theoretically be responsible for both conceptual implicit memory and aspects of explicit memory. For example, contemplating the meaning of a word might serve to speed subsequent processing of that word and also make it seem familiar. We examined electrophysiological correlates of conceptual priming with 180 celebrity faces to determine whether or not they resemble electrophysiological correlates of explicit memory. Celebrity faces are ideal for this purpose because they carry with them preexisting conceptual information (i.e., biographical facts) that can selectively be brought to mind such that conceptual processing can be manipulated systematically. In our experiment, exposure to biographical information associated with only one-half of the celebrities yielded conceptual priming for those faces, whereas all faces were perceptually primed. Conceptual priming was indexed by positive brain potentials over frontal regions from approximately 250 to 500 ms. Explicit memory retrieval was associated with later brain potentials over posterior regions that were strikingly similar to potentials previously associated with pure familiarity for faces (when a face seems familiar in the absence of retrieval of any specific information about previous occurrence). Furthermore, the magnitude of conceptual priming was correlated across subjects with the amplitude of frontal but not posterior potentials, whereas the opposite was true for explicit memory. Distinct brain processes were thus associated with conceptual priming and conscious recognition of faces, thus providing a sharper focus on the border between implicit and explicit memory.

The diffusion model is a commonly used tool to infer latent psychological processes underlying decision-making, and to link them to neural mechanisms based on response times. Although efficient open source software has been made available to quantitatively fit the model to data, current estimation methods require an abundance of response time measurements to recover meaningful parameters, and only provide point estimates of each parameter. In contrast, hierarchical Bayesian parameter estimation methods are useful for enhancing statistical power, allowing for simultaneous estimation of individual subject parameters and the group distribution that they are drawn from, while also providing measures of uncertainty in these parameters in the posterior distribution. Here, we present a novel Python-based toolbox called HDDM (hierarchical drift diffusion model), which allows fast and flexible estimation of the the drift-diffusion model and the related linear ballistic accumulator model. HDDM requires fewer data per subject/condition than non-hierarchical methods, allows for full Bayesian data analysis, and can handle outliers in the data. Finally, HDDM supports the estimation of how trial-by-trial measurements (e.g., fMRI) influence decision-making parameters. This paper will first describe the theoretical background of the drift diffusion model and Bayesian inference. We then illustrate usage of the toolbox on a real-world data set from our lab. Finally, parameter recovery studies show that HDDM beats alternative fitting methods like the χ(2)-quantile method as well as maximum likelihood estimation. The software and documentation can be downloaded at: http://ski.clps.brown.edu/hddm_docs/