Auditory oddball responses in the human subthalamic nucleus and substantia nigra pars reticulata

The auditory oddball is a mainstay in research on attention, novelty, and sensory prediction. How this task engages subcortical structures like the subthalamic nucleus and substantia nigra pars reticulata is unclear. We administered an auditory OB task while recording single unit activity (35 units) and local field potentials (57 recordings) from the subthalamic nucleus and substantia nigra pars reticulata of 30 patients with Parkinson's disease undergoing deep brain stimulation surgery. We found tone modulated and oddball modulated units in both regions. Population activity differentiated oddball from standard trials from 200 ms to 1000 ms after the tone in both regions. In the substantia nigra, beta band activity in the local field potential was decreased following oddball tones. The oddball related activity we observe may underlie attention, sensory prediction, or surprise-induced motor suppression.

Surprise!-Clarifying the link between insight and prediction error

The AHA experience, a moment of deep understanding during insightful problem-solving involving feelings of certainty, pleasure, and surprise, has captivated psychologists for more than a century. Recently, a new theoretical framework has proposed a link between the AHA experience and prediction error (PE), a popular concept in decision-making and reinforcement learning. This framework suggests that participants maintain a meta-cognitive prediction about the time it takes to solve a problem and the AHA experience arises when the problem is solved earlier than expected, resulting in a meta-cognitive PE. In our preregistered online study, we delved deeper into this idea, investigating whether prediction errors also pertain to participants' predictions regarding the solvability of the problem itself, and which dimension of the AHA experience aligns with the meta-cognitive PE. Utilizing verbal insight problems, we found a positive association between the AHA experience and the meta-cognitive PE, specifically in regards to problem solvability. Specifically, the element of surprise, a critical AHA dimension, emerged as a key indicator of the meta-cognitive PE, while other dimensions-such as pleasure, certainty, and suddenness-showed no signs for similar relationships, with suddenness exhibiting a negative correlation with meta-cognitive PE. This new finding provides further evidence that aspects of the AHA experience, surprise in particular, correspond to a meta-cognitive PE. The finding also underscores the multifaceted nature of this phenomenon, linking insights with learning theories and enhancing our understanding of this intriguing phenomenon.

Alerting effects require the absence of surprise

Ongoing actions are interrupted for a brief period of time whenever salient and expectancy-discrepant stimuli (surprise stimuli) interfere with the present task set. By contrast, salient stimuli (alerting cues) preceding targets can facilitate behaviour by reducing time to initiate actions. Both phenomena seem to be at odds with each other as actions are either impaired or facilitated. Therefore, in the present study, we asked how surprise and alerting effects interact. In two experiments, participants performed choice reaction tasks without any prior knowledge of the impending alerting cue. After a baseline period of trials without an alerting cue, the alerting cue was presented for the first time. It was found that the initial presentation of the alerting cue significantly slowed down reaction times. However, after just a single trial this impairment went away. This reveals that the beneficial effects of alerting for action presuppose that alerting cues are expected and represented in the top-down task set. As such, the present findings challenge the standard view of phasic alerting as a bottom-up and entirely stimulus-driven phenomenon.

Modeling road user response timing in naturalistic traffic conflicts: A surprise-based framework

There is currently no established method for evaluating human response timing across a range of naturalistic traffic conflict types. Traditional notions derived from controlled experiments, such as perception-response time, fail to account for the situation-dependency of human responses and offer no clear way to define the stimulus in many common traffic conflict scenarios. As a result, they are not well suited for application in naturalistic settings. We present a novel framework for measuring and modeling response times in naturalistic traffic conflicts applicable to automated driving systems as well as other traffic safety domains. The framework suggests that response timing must be understood relative to the subject's current (prior) belief and is always embedded in, and dependent on, the dynamically evolving situation. The response process is modeled as a belief update process driven by perceived violations to this prior belief, that is, by surprising stimuli. The framework resolves two key limitations with traditional notions of response time when applied in naturalistic scenarios: (1) The strong situation dependence of response timing and (2) how to unambiguously define the stimulus. Resolving these issues is a challenge that must be addressed by any response timing model intended to be applied in naturalistic traffic conflicts. We show how the framework can be implemented by means of a relatively simple heuristic model fit to naturalistic human response data from real crashes and near crashes from the SHRP2 dataset and discuss how it is, in principle, generalizable to any traffic conflict scenario. We also discuss how the response timing framework can be implemented computationally based on evidence accumulation enhanced by machine learning-based generative models and the information-theoretic concept of surprise.

Belief-consistent information is most shared despite being the least surprising

In the classical information theoretic framework, information "value" is proportional to how novel/surprising the information is. Recent work building on such notions claimed that false news spreads faster than truth online because false news is more novel and therefore surprising. However, another determinant of surprise, semantic meaning (e.g., information's consistency or inconsistency with prior beliefs), should also influence value and sharing. Examining sharing behavior on Twitter, we observed separate relations of novelty and belief consistency with sharing. Though surprise could not be assessed in those studies, belief consistency should relate to less surprise, suggesting the relevance of semantic meaning beyond novelty. In two controlled experiments, belief-consistent (vs. belief-inconsistent) information was shared more despite consistent information being the least surprising. Manipulated novelty did not predict sharing or surprise. Thus, classical information theoretic predictions regarding perceived value and sharing would benefit from considering semantic meaning in contexts where people hold pre-existing beliefs.

Stimulus expectations do not modulate visual event-related potentials in probabilistic cueing designs

Humans and other animals can learn and exploit repeating patterns that occur within their environments. These learned patterns can be used to form expectations about future sensory events. Several influential predictive coding models have been proposed to explain how learned expectations influence the activity of stimulus-selective neurons in the visual system. These models specify reductions in neural response measures when expectations are fulfilled (termed expectation suppression) and increases following surprising sensory events. However, there is currently scant evidence for expectation suppression in the visual system when confounding factors are taken into account. Effects of surprise have been observed in blood oxygen level dependent (BOLD) signals, but not when using electrophysiological measures. To provide a strong test for expectation suppression and surprise effects we performed a predictive cueing experiment while recording electroencephalographic (EEG) data. Participants (n=48) learned cue-face associations during a training session and were then exposed to these cue-face pairs in a subsequent experiment. Using univariate analyses of face-evoked event-related potentials (ERPs) we did not observe any differences across expected (90% probability), neutral (50%) and surprising (10%) face conditions. Across these comparisons, Bayes factors consistently favoured the null hypothesis throughout the time-course of the stimulus-evoked response. When using multivariate pattern analysis we did not observe above-chance classification of expected and surprising face-evoked ERPs. By contrast, we found robust within- and across-trial stimulus repetition effects. Our findings do not support predictive coding-based accounts that specify reduced prediction error signalling when perceptual expectations are fulfilled. They instead highlight the utility of other types of predictive processing models that describe expectation-related phenomena in the visual system without recourse to prediction error signalling.

Bayesian Surprise Predicts Human Event Segmentation in Story Listening

Event segmentation theory posits that people segment continuous experience into discrete events and that event boundaries occur when there are large transient increases in prediction error. Here, we set out to test this theory in the context of story listening, by using a deep learning language model (GPT-2) to compute the predicted probability distribution of the next word, at each point in the story. For three stories, we used the probability distributions generated by GPT-2 to compute the time series of prediction error. We also asked participants to listen to these stories while marking event boundaries. We used regression models to relate the GPT-2 measures to the human segmentation data. We found that event boundaries are associated with transient increases in Bayesian surprise but not with a simpler measure of prediction error (surprisal) that tracks, for each word in the story, how strongly that word was predicted at the previous time point. These results support the hypothesis that prediction error serves as a control mechanism governing event segmentation and point to important differences between operational definitions of prediction error.

WTF?! Covid-19, indignation, and the internet

The Covid-19 pandemic has fuelled indignation. People have been indignant about the breaking of lockdown rules, about the mistakes and deficiencies of government pandemic policies, about enforced mask-wearing, about vaccination programmes (or lack thereof), about lack of care with regards vulnerable individuals, and more. Indeed, indignation seems to have been particularly prevalent on social media platforms such as Twitter and Facebook, where indignant remarks are often accompanied by variations on the hashtag #WTF?! In this paper, I explore indignation's distinctive character as a form of moral anger, in particular suggesting that what is characteristic of indignation is not only that it discloses moral injustices but betrays our disbelief at the very occurrence of the offence. Having outlined the character of indignation, I consider how the structure of indignation impacts how we do, respond to, and receive indignation. I explore indignation in action, so to speak, in the context of Covid-19, with a particular emphasis on how indignation occurs 'on the internet'.

Ignore the glitch but mind the switch: Positive effects of methylphenidate on cognition in attention deficit hyperactivity disorder are related to prediction gain

Neuropsychological symptoms such as inattention and distractibility constitute a core characteristic of attention deficit hyperactivity disorder (ADHD). Here, we tested the hypothesis that attentional dysfunctions result from a deficit in neural gain modulation, which translates into difficulty in predictively weighting relevant sensory input while ignoring distraction. We compared thirty-seven hitherto untreated adults diagnosed with ADHD and thirty-eight healthy participants with a serial switch-drift task that requires internal models of predictable digit sequences to be either updated or stabilized. Switches between sequences that had to be indicated by key presses and digit omissions within a sequence (drifts) that should be ignored varied by stimulus-bound surprise quantified as Shannon information. To investigate whether catecholaminergic modulation by increasing extracellular norepinephrine and dopamine levels leads to an amelioration in prediction gain, participants were tested twice, with patients receiving a single dose of methylphenidate, a norepinephrine/dopamine reuptake inhibitor, in the second session. Patients and controls differed in both updating and stabilizing, depending on the respective event surprise. Specifically, patients showed difficulty in detecting expectable switches, while having greater difficulty to ignore surprising distractions. Thus, underconfident prior beliefs in ADHD may fail to appropriately weight expected relevant input, whereas the gain of neural responses to unexpected irrelevant distractors is increased. Methylphenidate improved both flexibility and stability of prediction and had a positive effect on selective responding over time. Our results suggest that ADHD is associated with an impairment in the use of prior expectations to optimally weight sensory inputs, which is improved by increasing catecholaminergic neurotransmission.

Explicitly predicting outcomes enhances learning of expectancy-violating information

Predictive coding models suggest that the brain constantly makes predictions about what will happen next based on past experiences. Learning is triggered by surprising events, i.e., a prediction error. Does it benefit learning when these predictions are made deliberately, so that an individual explicitly commits to an outcome before experiencing it? Across two experiments, we tested whether generating an explicit prediction before seeing numerical facts boosts learning of expectancy-violating information relative to doing so post hoc. Across both experiments, predicting boosted memory for highly unexpected outcomes, leading to a U-shaped relation between expectedness and memory. In the post hoc condition, memory performance decreased with increased unexpectedness. Pupillary data of Experiment 2 further indicated that the pupillary surprise response to highly expectancy-violating outcomes predicted successful learning of these outcomes. Together, these findings suggest that generating an explicit prediction increases learners' stakes in the outcome, which particularly benefits learning of those outcomes that are different than expected.

Saccadic eye movement metrics reflect surprise and mental model updating

Two experiments investigated what eye movements can reveal about how we process surprising information and how we update mental models in dynamic and unstructured environments. Participants made saccades to visual targets presented one at a time, radially, around an invisible perimeter. Target locations were normally distributed and shifted at an unannounced point during the task. Trials following the shift were considered surprising and unexpected. These unexpected and surprising events prompted the need to update. Slower saccadic latencies were observed for surprising/unexpected events, perhaps indicative of the need to reorient attention to the unexpected target location. Longer dwell times were observed for events that signaled a change in the distribution. These data show that eye movement metrics provide a reliable indicator of mental model updating when contingencies change even in the absence of explicit change signals.

A neurocomputational model of creative processes

Creativity is associated with finding novel, surprising, and useful solutions. We argue that creative cognitive processes, divergent thinking, abstraction, and improvisation are constructed on different novelty-based processes. The prefrontal cortex plays a role in creative ideation by providing a control mechanism. Moreover, thinking about novel solutions activates the distant or loosely connected neurons of a semantic network that involves the hippocampus. Novelty can also be interpreted as different combinations of earlier learned processes, such as the motor sequencing mechanism of the basal ganglia. In addition, the cerebellum is responsible for the precise control of movements, which is particularly important in improvisation. Our neurocomputational perspective is based on three creative processes centered on novelty seeking, subserved by the prefrontal cortex, hippocampus, cerebellum, basal ganglia, and dopamine. The algorithmic implementation of our model would enable us to describe commonalities and differences between these creative processes based on the proposed neural circuitry. Given that most previous studies have mainly provided theoretical and conceptual models of creativity, this article presents the first brain-inspired neural network model of creative cognition.

Brain signals of a Surprise-Actor-Critic model: Evidence for multiple learning modules in human decision making

Learning how to reach a reward over long series of actions is a remarkable capability of humans, and potentially guided by multiple parallel learning modules. Current brain imaging of learning modules is limited by (i) simple experimental paradigms, (ii) entanglement of brain signals of different learning modules, and (iii) a limited number of computational models considered as candidates for explaining behavior. Here, we address these three limitations and (i) introduce a complex sequential decision making task with surprising events that allows us to (ii) dissociate correlates of reward prediction errors from those of surprise in functional magnetic resonance imaging (fMRI); and (iii) we test behavior against a large repertoire of model-free, model-based, and hybrid reinforcement learning algorithms, including a novel surprise-modulated actor-critic algorithm. Surprise, derived from an approximate Bayesian approach for learning the world-model, is extracted in our algorithm from a state prediction error. Surprise is then used to modulate the learning rate of a model-free actor, which itself learns via the reward prediction error from model-free value estimation by the critic. We find that action choices are well explained by pure model-free policy gradient, but reaction times and neural data are not. We identify signatures of both model-free and surprise-based learning signals in blood oxygen level dependent (BOLD) responses, supporting the existence of multiple parallel learning modules in the brain. Our results extend previous fMRI findings to a multi-step setting and emphasize the role of policy gradient and surprise signalling in human learning.

Violations of expectation trigger infants to search for explanations

Infants look longer and explore more following violations-of-expectation, but the reasons for these surprise-induced behaviors are unclear. One possibility is that expectancy violations heighten arousal generally, thereby increasing infants' post-surprise activity. Another possibility is that infants' exploration reflects the search for an explanation for the surprising event. We tested these alternatives in three experiments. First in Experiment 1 we confirmed that seeing an object violate expectations (by passing through a solid wall) increased infants' exploration of the surprising object, relative to when no expectancy violation was seen. Then in Experiment 2 we measured infants' exploration after they had seen the same violation event, but then an explanation for the event was provided (the wall was revealed to have a large hole in it). We found that providing this explanation abolished infants' surprise-induced exploration. In Experiment 3 we replicated this effect. Furthermore, we found that the longer infants looked at the explanation, the greater their reversal in exploratory preference (i.e., the more they ignored the surprising object). These findings demonstrate that preverbal infants both seek and recognize explanations for surprising events.

Towards a unified neural mechanism for reactive adaptive behaviour

Surviving in natural environments requires animals to sense sudden events and swiftly adapt behaviour accordingly. The study of such Reactive Adaptive Behaviour (RAB) has been central to a number of research streams, all orbiting around movement science but progressing in parallel, with little cross-field fertilization. We first provide a concise review of these research streams, independently describing four types of RAB: (1) cortico-muscular resonance, (2) stimulus locked response, (3) online motor correction and (4) action stopping. We then highlight remarkable similarities across these four RABs, suggesting that they might be subserved by the same neural mechanism, and propose directions for future research on this topic.

On the physiology of interruption after unexpectedness

We tested whether surprise elicits similar physiological changes as those associated with orienting and freezing after threat, as surprise also involves a state of interruption and attention for effective action. Moreover, because surprise is primarily driven by the unexpectedness of an event, initial physiological responses were predicted to be similar for positive, neutral, and negative surprises. Results of repetition-change studies (4 + 1 in Supplemental Materials) showed that surprise lowers heart rate (Experiments 1-4) and increases blood pressure (Experiment 4). No effects on body movement (Experiment 2) or finger temperature (Experiment 4) were found. When unexpected stimuli were presented more often (making them less surprising) heart rate returned to baseline, while blood pressure remained high (Experiment 4). These effects were not influenced by stimulus valence. However, second-to-second analyses within the first (surprising) block showed a tendency for a stronger increase in systolic blood pressure after negative vs. positive surprise.

Multiple prosodic meanings are conveyed through separate pitch ranges: Evidence from perception of focus and surprise in Mandarin Chinese

F0 variation is a crucial feature in speech prosody, which can convey linguistic information such as focus and paralinguistic meanings such as surprise. How can multiple layers of information be represented with F0 in speech: are they divided into discrete layers of pitch or overlapped without clear divisions? We investigated this question by assessing pitch perception of focus and surprise in Mandarin Chinese. Seventeen native Mandarin listeners rated the strength of focus and surprise conveyed by the same set of synthetically manipulated sentences. An fMRI experiment was conducted to assess neural correlates of the listeners' perceptual response to the stimuli. The results showed that behaviourally, the perceptual threshold for focus was 3 semitones and that for surprise was 5 semitones above the baseline. Moreover, the pitch range of 5-12 semitones above the baseline signalled both focus and surprise, suggesting a considerable overlap between the two types of prosodic information within this range. The neuroimaging data positively correlated with the variations in behavioural data. Also, a ceiling effect was found as no significant behavioural differences or neural activities were shown after reaching a certain pitch level for the perception of focus and surprise respectively. Together, the results suggest that different layers of prosodic information are represented in F0 through different pitch ranges: paralinguistic information is represented at a pitch range beyond that used by linguistic information. Meanwhile, the representation of paralinguistic information is achieved without obscuring linguistic prosody, thus allowing F0 to represent the two layers of information in parallel.

A predictive account of how novelty influences declarative memory

A rich body of studies in the human and non-human literature has examined the question how novelty influences memory. For a variety of different stimuli, ranging from simple objects and words to vastly complex scenarios, the literature reports that novelty improves memory in some cases, but impairs memory in other cases. In recent attempts to reconcile these conflicting findings, novelty has been divided into different subtypes, such as relative versus absolute novelty, or stimulus versus contextual novelty. Nevertheless, a single overarching theory of novelty and memory has been difficult to attain, probably due to the complexities in the interactions among stimuli, environmental factors (e.g., spatial and temporal context) and level of prior knowledge (but see Duszkiewicz et al., 2019; Kafkas & Montaldi, 2018b; Schomaker & Meeter, 2015). Here we describe how a predictive coding framework might be able to shed new light on different types of novelty and how they affect declarative memory in humans. More precisely, we consider how prior expectations modulate the influence of novelty on encoding episodes into memory, e.g., in terms of surprise, and how novelty/surprise affect memory for surrounding information. By reviewing a range of behavioural findings and their possible underlying neurobiological mechanisms, we highlight where a predictive coding framework succeeds and where it appears to struggle.

Electroencephalographic correlates of temporal Bayesian belief updating and surprise

The brain predicts the timing of forthcoming events to optimize responses to them. Temporal predictions have been formalized in terms of the hazard function, which integrates prior beliefs on the likely timing of stimulus occurrence with information conveyed by the passage of time. However, how the human brain updates prior temporal beliefs is still elusive. Here we investigated electroencephalographic (EEG) signatures associated with Bayes-optimal updating of temporal beliefs. Given that updating usually occurs in response to surprising events, we sought to disentangle EEG correlates of updating from those associated with surprise. Twenty-six participants performed a temporal foreperiod task, which comprised a subset of surprising events not eliciting updating. EEG data were analyzed through a regression-based massive approach in the electrode and source space. Distinct late positive, centro-parietally distributed, event-related potentials (ERPs) were associated with surprise and belief updating in the electrode space. While surprise modulated the commonly observed P3b, updating was associated with a later and more sustained P3b-like waveform deflection. Results from source analyses revealed that neural encoding of surprise comprises neural activity in the cingulo-opercular network (CON) and parietal regions. These data provide evidence that temporal predictions are computed in a Bayesian manner, and that this is reflected in P3 modulations, akin to other cognitive domains. Overall, our study revealed that analyzing P3 modulations provides an important window into the Bayesian brain. Data and scripts are shared on OSF: https://osf.io/ckqa5/.

Activation of the cognitive control network associated with information uncertainty

The cognitive control network (CCN) that comprises regions of the frontoparietal network, the cingulo-opercular network, and other sub-cortical regions as core structures is commonly activated by events with an increase in information uncertainty. However, it is not clear whether this CCN activation is associated with both information entropy that represents the information conveyed by the context formed by a sequence of events and the surprise that quantifies the information conveyed by a specific type of event in the context. We manipulated entropy and surprise in this functional magnetic resonance imaging study by varying the probability of occurrence of two types of events in both the visual and auditory modalities and measured brain response as a function of entropy and surprise. We found that activation in regions of the CCN increased as a function of entropy and surprise in both the visual and auditory tasks. The frontoparietal network and additional structures in the CCN mediated the relationship between these information measures and behavioral response. These results suggest that the CCN is a high-level modality-general neural entity for the control of the processing of information conveyed by both context and event.

Big Surprises: Jackpot Reinforcers in Research and Practice

Unusually large, infrequent reinforcers, described as jackpots, are the subject of considerable discussion among applied animal behaviorists. Such reinforcers offer considerable promise in applied behavior analysis as a means of both potentiating training of new responses and response classes and enhancing previously learned ones. The concept of jackpot reinforcement, however, is rife with not only a lack of definitional and procedural clarity but also a paucity of research, either basic or applied, on such reinforcement. Considerations in undertaking such research include defining the parameters of jackpot reinforcers, identifying suitable dependent variables, and creating experimental designs appropriate for their assessment. The few experimental analyses of jackpot reinforcer effects on either response acquisition or maintenance have produced little evidence of systematic effects, despite the use of several different methods and behavioral measures. Negative results could reflect either the absence of systematic effects of these jackpot reinforcers or unsuitable methods of analysis. Only further research will take the topic of jackpot reinforcers beyond opinion and testimonial and into the realm of the science of behavior.

Visual mismatch responses index surprise signalling but not expectation suppression

The ability to distinguish between commonplace and unusual sensory events is critical for efficient learning and adaptive behaviour. This has been investigated using oddball designs in which sequences of often-appearing (i.e., expected) stimuli are interspersed with rare (i.e., surprising) deviants. Resulting differences in electrophysiological responses following surprising compared to expected stimuli are known as visual mismatch responses (VMRs). VMRs are thought to index co-occurring contributions of stimulus repetition effects, expectation suppression (that occurs when one's expectations are fulfilled), and expectation violation (i.e., surprise) responses; however, these different effects have been conflated in existing oddball designs. To better isolate and quantify effects of expectation suppression and surprise, we adapted an oddball design based on Fast Periodic Visual Stimulation (FPVS) that controls for stimulus repetition effects. We recorded electroencephalography (EEG) while participants (N = 48) viewed stimulation sequences in which a single face identity was periodically presented at 6 Hz. Critically, one of two different face identities (termed oddballs) appeared as every 7th image throughout the sequence. The presentation probabilities of each oddball image within a sequence varied between 10 and 90%, such that participants could form expectations about which oddball face identity was more likely to appear within each sequence. We also included 'expectation neutral' 50% probability sequences, whereby consistently biased expectations would not be formed for either oddball face identity. We found that VMRs indexed surprise responses, and effects of expectation suppression were absent. That is, ERPs were more negative-going at occipitoparietal electrodes for surprising compared to neutral oddballs, but did not differ between expected and neutral oddballs. Surprising oddball-evoked ERPs were also highly similar across the 10-40% appearance probability conditions. Our findings indicate that VMRs which are not accounted for by repetition effects are best described as an all-or-none surprise response, rather than a minimisation of prediction error responses associated with expectation suppression.

Non-selective inhibition of the motor system following unexpected and expected infrequent events

Motor inhibition is a key control mechanism that allows humans to rapidly adapt their actions in response to environmental events. One of the hallmark signatures of rapidly exerted, reactive motor inhibition is the non-selective suppression of cortico-spinal excitability (CSE): unexpected sensory stimuli lead to a suppression of CSE across the entire motor system, even in muscles that are inactive. Theories suggest that this reflects a fast, automatic, and broad engagement of inhibitory control, which facilitates behavioral adaptations to unexpected changes in the sensory environment. However, it is an open question whether such non-selective CSE suppression is truly due to the unexpected nature of the sensory event, or whether it is sufficient for an event to be merely infrequent (but not unexpected). Here, we report data from two experiments in which human subjects experienced both unexpected and expected infrequent events during a two-alternative forced-choice reaction time task while CSE was measured from a task-unrelated muscle. We found that expected infrequent events can indeed produce non-selective CSE suppression-but only when they occur during movement initiation. In contrast, unexpected infrequent events produce non-selective CSE suppression relative to frequent, expected events even in the absence of movement initiation. Moreover, CSE suppression due to unexpected events occurs at shorter latencies compared to expected infrequent events. These findings demonstrate that unexpectedness and stimulus infrequency have qualitatively different suppressive effects on the motor system. They also have key implications for studies that seek to disentangle neural and psychological processes related to motor inhibition and stimulus detection.

Risk prediction error signaling: A two-component response?

Organisms use rewards to navigate and adapt to (uncertain) environments. Error-based learning about rewards is supported by the dopaminergic system, which is thought to signal reward prediction errors to make adjustments to past predictions. More recently, the phasic dopamine response was suggested to have two components: the first rapid component is thought to signal the detection of a potentially rewarding stimulus; the second, slightly later component characterizes the stimulus by its reward prediction error. Error-based learning signals have also been found for risk. However, whether the neural generators of these signals employ a two-component coding scheme like the dopaminergic system is unknown. Here, using human high density EEG, we ask whether risk learning, or more generally speaking surprise-based learning under uncertainty, is similarly comprised of two temporally dissociable components. Using a simple card game, we show that the risk prediction error is reflected in the amplitude of the P3b component. This P3b modulation is preceded by an earlier component, that is modulated by the stimulus salience. Source analyses are compatible with the idea that both the early salience signal and the later risk prediction error signal are generated in insular, frontal, and temporal cortex. The identified sources are parts of the risk processing network that receives input from noradrenergic cells in the locus coeruleus. Finally, the P3b amplitude modulation is mirrored by an analogous modulation of pupil size, which is consistent with the idea that both the P3b and pupil size indirectly reflect locus coeruleus activity.

Beyond the Anomaly: Where Piaget and Bruner Meet

The aim of this work is to focus on a basic concept in Brunerian narrative theory, that of violation of canonicity, showing how it relates to other basic concepts of cognitive theories such as anomaly, expectation and relationship between constancy and variability. To reach this aim, we will firstly discuss the Piagetian theory, in particular regarding the way in which the child deals with new and interesting events moved from the need to face and produce "spectacles interessantes" by means of experiencing the violation of canonicity. We will also briefly consider some results of neurosciences studies pointing out that the constancy-variability issue is at the base of human development. Secondly, we will show the convergence between Piagetian theory and Brunerian theory of narration, producing some examples of how violation of canonicity can occur in children and adults.

Decomposing neural responses to melodic surprise in musicians and non-musicians: Evidence for a hierarchy of predictions in the auditory system

Neural responses to auditory surprise are typically studied with highly unexpected, disruptive sounds. Consequently, little is known about auditory prediction in everyday contexts that are characterized by fine-grained, non-disruptive fluctuations of auditory surprise. To address this issue, we used IDyOM, a computational model of auditory expectation, to obtain continuous surprise estimates for a set of newly composed melodies. Our main goal was to assess whether the neural correlates of non-disruptive surprising sounds in a musical context are affected by musical expertise. Using magnetoencephalography (MEG), auditory responses were recorded from musicians and non-musicians while they listened to the melodies. Consistent with a previous study, the amplitude of the N1m component increased with higher levels of computationally estimated surprise. This effect, however, was not different between the two groups. Further analyses offered an explanation for this finding: Pitch interval size itself, rather than probabilistic prediction, was responsible for the modulation of the N1m, thus pointing to low-level sensory adaptation as the underlying mechanism. In turn, the formation of auditory regularities and proper probabilistic prediction were reflected in later components: The mismatch negativity (MMNm) and the P3am, respectively. Overall, our findings reveal a hierarchy of expectations in the auditory system and highlight the need to properly account for sensory adaptation in research addressing statistical learning.

Novelty competes with saliency for attention

A highly debated question in attention research is to what extent attention is biased by bottom-up factors such as saliency versus top-down factors as governed by the task. Visual search experiments in which participants are briefly familiarized with the task and then see a novel stimulus unannounced and for the first time support yet another factor, showing that novel and surprising features attract attention. In the present study, we tested whether gaze behavior as an indicator for attentional prioritization can be predicted accurately within displays containing both salient and novel stimuli by means of a priority map that assumes novelty as an additional source of activation. To that aim, we conducted a visual search experiment where a color singleton was presented for the first time in the surprise trial and manipulated the color-novelty of the remaining non-singletons between participants. In one group, the singleton was the only novel stimulus ("one-new"), whereas in another group, the non-singleton stimuli were likewise novel ("all-new"). The surprise trial was always target absent and designed such that top-down prioritization of any color was unlikely. The results show that the singleton in the all-new group captured the gaze less strongly, with more early fixations being directed to the novel non-singletons. Overall, the fixation pattern can accurately be explained by noisy priority maps where saliency and novelty compete for gaze control.

The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities

Evolution provides a creative fount of complex and subtle adaptations that often surprise the scientists who discover them. However, the creativity of evolution is not limited to the natural world: Artificial organisms evolving in computational environments have also elicited surprise and wonder from the researchers studying them. The process of evolution is an algorithmic process that transcends the substrate in which it occurs. Indeed, many researchers in the field of digital evolution can provide examples of how their evolving algorithms and organisms have creatively subverted their expectations or intentions, exposed unrecognized bugs in their code, produced unexpectedly adaptations, or engaged in behaviors and outcomes, uncannily convergent with ones found in nature. Such stories routinely reveal surprise and creativity by evolution in these digital worlds, but they rarely fit into the standard scientific narrative. Instead they are often treated as mere obstacles to be overcome, rather than results that warrant study in their own right. Bugs are fixed, experiments are refocused, and one-off surprises are collapsed into a single data point. The stories themselves are traded among researchers through oral tradition, but that mode of information transmission is inefficient and prone to error and outright loss. Moreover, the fact that these stories tend to be shared only among practitioners means that many natural scientists do not realize how interesting and lifelike digital organisms are and how natural their evolution can be. To our knowledge, no collection of such anecdotes has been published before. This article is the crowd-sourced product of researchers in the fields of artificial life and evolutionary computation who have provided first-hand accounts of such cases. It thus serves as a written, fact-checked collection of scientifically important and even entertaining stories. In doing so we also present here substantial evidence that the existence and importance of evolutionary surprises extends beyond the natural world, and may indeed be a universal property of all complex evolving systems.

In-flight spatial disorientation induces roll reversal errors when using the attitude indicator

We hypothesized that an incorrect expectation due to spatial disorientation may induce roll reversal errors. To test this, an in-flight experiment was performed, in which forty non-pilots rolled wings level after receiving motion cues. A No-leans condition (subthreshold motion to a bank angle) was included, as well as a Leans-opposite condition (leans cues, opposite to the bank angle) and a Leans-level condition (leans cues, but level flight). The presence of leans cues led to an increase of the roll reversal error (RRE) rate by a factor of 2.6. There was no significant difference between the Leans-opposite and Leans-level condition. This suggests that the expectation strongly affects the occurrence of an RRE, and that people tend to base their responses on motion cues instead of on information on the AI. We conclude that expectation and spatial disorientation have a large effect on piloting errors and may cause hazardous aircraft upsets.

Medical Surprise Anticipation and Recognition Capability: A New Concept for Better Health Care

Predicting and preparing for the unforeseen is challenging. Medicine and health care are continuously changing based on science, technology, and regulation. This very process of change creates pathways for surprise and leaves us vulnerable to its impact. The armed forces have established strategies to identify and address surprising events, a framework that can be adapted to benefit the medical community. We introduce Medical Surprise Anticipation and Recognition Capability (SARC), adapted from an established military strategy. SARC is the process of addressing surprising events before they emerge. We explore the framework for mitigating surprise as developed by the Committee on Capability Surprise on U.S. Naval Forces. We recommend further exploration of this concept in health care as a potential asset in our quest towards high reliability.

Bayesian modeling of temporal expectations in the human brain

The brain predicts the timing of forthcoming events to optimize processes in response to them. Temporal predictions are driven by both our prior expectations on the likely timing of stimulus occurrence and the information conveyed by the passage of time. Specifically, such predictions can be described in terms of the hazard function, that is, the conditional probability that an event will occur, given it has not yet occurred. Events violating expectations cause surprise and often induce updating of prior expectations. While it is well-known that the brain is able to track the temporal hazard of event occurrence, the question of how prior temporal expectations are updated is still unsettled. Here we combined a Bayesian computational approach with brain imaging to map updating of temporal expectations in the human brain. Moreover, since updating is usually highly correlated with surprise, participants performed a task that allowed partially differentiating between the two processes. Results showed that updating and surprise differently modulated activity in areas belonging to two critical networks for cognitive control, the fronto-parietal (FPN) and the cingulo-opercular network (CON). Overall, these data provide a first computational characterization of the neural correlates associated with updating and surprise related to temporal expectation.

Depressive symptoms bias the prediction-error enhancement of memory towards negative events in reinforcement learning

RATIONALE

Depression is a disorder characterized by sustained negative affect and blunted positive affect, suggesting potential abnormalities in reward learning and its interaction with episodic memory.

OBJECTIVES

This study investigated how reward prediction errors experienced during learning modulate memory for rewarding events in individuals with depressive and non-depressive symptoms.

METHODS

Across three experiments, participants learned the average values of two scene categories in two learning contexts. Each learning context had either high or low outcome variance, allowing us to test the effects of small and large prediction errors on learning and memory. Participants were later tested for their memory of trial-unique scenes that appeared alongside outcomes. We compared learning and memory performance of individuals with self-reported depressive symptoms (N = 101) to those without (N = 184).

RESULTS

Although there were no overall differences in reward learning between the depressive and non-depressive group, depression severity within the depressive group predicted greater error in estimating the values of the scene categories. Similarly, there were no overall differences in memory performance. However, in depressive participants, negative prediction errors enhanced episodic memory more so than did positive prediction errors, and vice versa for non-depressive participants who showed a larger effect of positive prediction errors on memory. These results reflected differences in memory both within group and across groups.

CONCLUSIONS

Individuals with self-reported depressive symptoms showed relatively intact reinforcement learning, but demonstrated a bias for encoding events that accompanied surprising negative outcomes versus surprising positive ones. We discuss a potential neural mechanism supporting these effects, which may underlie or contribute to the excessive negative affect observed in depression.

Shades of surprise: Assessing surprise as a function of degree of deviance and expectation constraints

Merging recent surprise theories renders the prediction that surprise is a function of how strong an event deviates from what was expected and of how easily this event can be integrated into the constraints of an activated expectation. The present research investigates the impact of both these factors on the behavioral, affective, experiential, and cognitive surprise responses. In two experiments (total N = 1257), participants were instructed that ten stimuli of a certain type would appear on the screen. Crucially, we manipulated the degree of deviance of the last stimulus by showing a stimulus that deviated to either no, a medium, or a high degree from the previous nine stimuli. Orthogonally to this deviation, we induced an expectation with either high, moderate, or low constraints prior to the experimental task. We measured behavioral response delay and explicit ratings of liking, surprise, and expectancy. Our findings point out an overall only low association between the behavioral, affective, experiential, and cognitive surprise responses and reveal rather dichotomous response patterns that differentiate between deviance and non-deviance of an event. Challenging previous accounts, the present evidence further implies that surprise is not about the ease of integrating an event with the constraints of an explicit a-priori expectation but rather reflects the automatic outcome of implicit discrepancy detection, resulting from a continuous cognitive fine-tuning of expectations.

Surprising depth cue captures attention in visual search

A substantial amount of evidence indicates that surprising events capture attention. The present study was primarily intended to investigate whether expectancy discrepant depth information also is able to capture attention immediately and-more specifically-whether cues that are relatively closer or farther differentially modulate behavior. For this purpose, participants had to identify one of two target letters in a search display. Stimulus positions were initially cued by uninformative placeholders. After half of the trials, the cue at the target position was suddenly and unexpectedly (critical trial) displayed closer to or farther from the observer. In line with previous research, both depth cues captured attention on their very first appearance. Performance in the critical trial was superior to the error rates in the trials without depth cue and was even above the performance in subsequent trials that included depth cue. This effect was only observed when the cue preceded the target by 400 ms. Using a shorter cue-stimulus interval of 100 ms, only a delayed improvement was observed, which denotes a typical feature of surprise capture. Moreover, response times were faster in trials comprising a depth cue, and this was already true for the critical trial. Apart from that, no other marked differences between near and far depth cues were observed. Therefore, the present results emphasize that surprising depth information indeed captures attention. However, in contrast to other perceptual tasks, search performance was not considerably influenced by relative position in depth.

Jerome Seymour Bruner: an Anticipator Scientist for an Anticipation Theory

In this paper the Author intends to present the work of Jerome Bruner from the particular angle of the concept of anticipation. After having duly traced the biographical and scientific profile of the scientist, the Author shows how anticipation is a red thread that joints early youthful works up to those written in the last period of his life. The concept of anticipation then introduces that of expectation of a norm and that violation of the norm and how the person should consider them appropriately to produce new knowledge. Therefore Jerome Bruner was an anticipatory in his theories but also the anticipation was the pivotal concept in these theories, as they propose an idea of ​​ person capable of surprise in front of the incongruities of reality.

Infants differentially update their internal models of a dynamic environment

Unexpected events provide us with opportunities for learning about what to expect from the world around us. Using a saccadic-planning paradigm, we investigated whether and how infants and adults represent the statistics of a changing environment (i.e. build an internal model of the environment). Participants observed differently colored bees that appeared at an unexpected location every few trials. The color cues indicated whether the subsequent bees would appear at this new location (i.e. update trials) or at the same location as previously (i.e. no-update trials). Infants learned the predictive value of the color cues and updated their internal models when necessary. Unlike infants, adults had a tendency to update their models each time they observed a change in the structure. We argue that infants are open to learning from current evidence due to being less influenced by their prior knowledge. This is an advantageous learning strategy to form accurate representations in dynamic environments, which is fundamental for successful adaptation.

Editors' Introduction and Review: An Appraisal of Surprise: Tracing the Threads That Stitch It Together

Though the scientific study of surprise dates back to Darwin (), there was an upsurge in interest beginning in the 1960s and 70s, and this has continued to the present. Recent developments have shed much light on the cognitive mechanisms and consequences of surprise, but research has often been siloed within sub-areas of Cognitive Science. A central challenge for research on surprise is, therefore, to connect various research programs around their overlapping foci. This issue has its roots in a symposium on surprise, entitled "Triangulating Surprise: Expectations, Uncertainty, and Making Sense," at the 36th Annual Conference of the Cognitive Science Society (Quebec City, July 2014). Building on the interdisciplinary conversations that started at the symposium, this issue aims to draw attention to some promising empirical and modeling results and their theoretical implications. The present paper sets the stage for the issue by presenting a historical summary, discussing contrasting definitions of surprise, and then by tracing major threads that run through both this issue and the larger literature on surprise. Our aim is to develop broader, shared understandings of the main insights, theories, and findings regarding surprise, with a view to supporting future integration and progress.

Learning From Surprise: Harnessing a Metacognitive Surprise Signal to Build and Adapt Belief Networks

One's level of surprise can be thought of as a metacognitive signal indicating how well one can explain new information. We discuss literature on how this signal can be used adaptively to build, and, when necessary, reorganize belief networks. We present challenges in the use of a surprise signal, such as hindsight bias and the tendency to equate difficulty with implausibility, and point to evidence suggesting that one can overcome these challenges through consideration of alternative outcomes-especially before receiving feedback on actual outcomes-and by calibrating task difficulty with one's knowledge level. As such, we propose that a major function of education-broadly construed as the work of teachers, journalists, parents, etc.-is to assist learners in using their metacognitive surprise signals to facilitate the building and adaptation of belief networks.

Enhanced deviant responses in patterned relative to random sound sequences

The brain draws on knowledge of statistical structure in the environment to facilitate detection of new events. Understanding the nature of this representation is a key challenge in sensory neuroscience. Specifically, it is unknown whether real-time perception of rapidly-unfolding sensory signals is driven by a coarse or detailed representation of the proximal stimulus history. We recorded electroencephalography brain responses to frequency outliers in regularly-patterned (REG) versus random (RAND) tone-pip sequences which were generated anew on each trial. REG and RAND sequences were matched in frequency content and span, only differing in the specific order of the tone-pips. Stimuli were very rapid, limiting conscious reasoning in favour of automatic processing of regularity. Listeners were naïve and performed an incidental visual task. Outliers within REG evoked a larger response than matched outliers in RAND. These effects arose rapidly (within 80 msec) and were underpinned by distinct sources from those classically associated with frequency-based deviance detection. These findings are consistent with the notion that the brain continually maintains a detailed representation of ongoing sensory input and that this representation shapes the processing of incoming information. Predominantly auditory-cortical sources code for frequency deviance whilst frontal sources are associated with tracking more complex sequence structure.

The Role of Surprise in Learning: Different Surprising Outcomes Affect Memorability Differentially

Surprise has been explored as a cognitive-emotional phenomenon that impacts many aspects of mental life from creativity to learning to decision-making. In this paper, we specifically address the role of surprise in learning and memory. Although surprise has been cast as a basic emotion since Darwin's () The Expression of the Emotions in Man and Animals, recently more emphasis has been placed on its cognitive aspects. One such view casts surprise as a process of "sense making" or "explanation finding": metacognitive explanation-based theory proposes that people's perception of surprise is a metacognitive assessment of the cognitive work done to explain a surprising outcome. Or, to put it more simply, surprise increases with the explanatory work required to resolve it. This theory predicts that some surprises should be more surprising than others because they are harder to explain. In the current paper, this theory is extended to consider the role of surprise in learning as evidenced by memorability. This theory is tested to determine how scenarios with differentially surprising outcomes impact the memorability of those outcomes. The results show that surprising outcomes (less-known outcomes) that are more difficult to explain are recalled more accurately than less-surprising outcomes that require little (known outcomes) or no explanation (normal).

Violations of Core Knowledge Shape Early Learning

Research on cognitive development has revealed that even the youngest minds detect and respond to events that adults find surprising. These surprise responses suggest that infants have a basic set of "core" expectations about the world that are shared with adults and other species. However, little work has asked what purpose these surprise responses serve. Here we discuss recent evidence that violations of core knowledge offer special opportunities for learning. Infants and young children make predictions about the world on the basis of their core knowledge of objects, quantities, and social entities. We argue that when these predictions fail to match the observed data, infants and children experience an enhanced drive to seek and retain new information. This impact of surprise on learning is not equipotent. Instead, it is directed to entities that are relevant to the surprise itself; this drive propels children-even infants-to form and test new hypotheses about surprising aspects of the world. We briefly consider similarities and differences between these recent findings with infants and children, on the one hand, and findings on prediction errors in humans and non-human animals, on the other. These comparisons raise open questions that require continued inquiry, but suggest that considering phenomena across species, ages, kinds of surprise, and types of learning will ultimately help to clarify how surprise shapes thought.

Surprise: unfolding of facial expressions

Responses to surprising events are dynamic. We argue that initial responses are primarily driven by the unexpectedness of the surprising event and reflect an interrupted and surprised state in which the outcome does not make sense yet. Later responses, after sense-making, are more likely to incorporate the valence of the outcome itself. To identify initial and later responses to surprising stimuli, we conducted two repetition-change studies and coded the general valence of facial expressions using computerised facial coding and specific facial action using the Facial Action Coding System (FACS). Results partly supported our unfolding logic. The computerised coding showed that initial expressions to positive surprises were less positive than later expressions. Moreover, expressions to positive and negative surprises were initially similar, but after some time differentiated depending on the valence of the event. Importantly, these patterns were particularly pronounced in a subset of facially expressive participants, who also showed facial action in the FACS coding. The FACS data showed that the initial phase was characterised by limited facial action, whereas the later increase in positivity seems to be explained by smiling. Conceptual as well as methodological implications are discussed.

Visual mismatch response and fMRI signal adaptation correlate in the occipital-temporal cortex

Several electrophysiological studies found response differences to a given stimulus when it is repeated frequently as compared to when it occurs rarely in oddball sequences. Initially defined in acoustic perception, such difference also exists in the visual modality and is referred to as visual mismatch negativity (vMMN). However, the repetition of a stimulus also leads to the reduction of the blood oxygen-level dependent (BOLD) signal (fMRI adaptation, fMRIa) when compared to alternating stimuli in fMRI experiments. So far no study compared the vMMN to fMRIa within the same paradigm and participants. Here we tested the possible connection between fMRIa and vMMN in a visual oddball paradigm in two separate sessions, acquiring electrophysiological and neuroimaging data for real and false characters from the same participants. We found significant visual mismatch response (vMM) as well as fMRIa for both character types. Importantly, the magnitude of the vMM over the CP1 electrode cluster showed a significant correlation with the fMRIa within the letter form area, for real characters. This finding suggests that similar neural mechanisms are responsible for the two phenomena.

Disrupted modular organization of primary sensory brain areas in schizophrenia

Abnormal brain resting-state functional connectivity has been consistently observed in patients affected by schizophrenia (SCZ) using functional MRI and other neuroimaging techniques. Graph theoretical methods provide a framework to investigate these defective functional interactions and their effects on the organization of brain connectivity networks. A few studies have shown altered distribution of connectivity within and between functional modules in SCZ patients, an indication of imbalanced functional segregation ad integration. However, no major alterations of modular organization have been reported in patients, and unambiguous identification of the neural substrates affected remains elusive. Recently, it has been demonstrated that current modularity analysis methods suffer from a fundamental and severe resolution limit, as they fail to detect features that are smaller than a scale determined by the size of the entire connectivity network. This resolution limit is likely to have hampered the ability to resolve differences between patients and controls in previous studies. Here, we apply Surprise, a novel resolution limit-free approach, to study the modular organization of resting state functional connectivity networks in a large cohort of SCZ patients and in matched healthy controls. Leveraging these important methodological advances we find new evidence of substantial fragmentation and reorganization involving primary sensory, auditory and visual areas in SCZ patients. Conversely, frontal and prefrontal areas, typically associated with higher cognitive functions, appear to be largely unaffected, with changes selectively involving language and speech processing areas. Our findings support the hypothesis that cognitive dysfunction in SCZ may involve deficits occurring already at early stages of sensory processing.

The Cognitive-Evolutionary Model of Surprise: A Review of the Evidence

Research on surprise relevant to the cognitive-evolutionary model of surprise proposed by Meyer, Reisenzein, and Schützwohl (1997) is reviewed. The majority of the assumptions of the model are found empirically supported. Surprise is evoked by unexpected (schema-discrepant) events and its intensity is determined by the degree if schema-discrepancy, whereas the novelty and the valence of the eliciting events probably do not have an independent effect. Unexpected events cause an automatic interruption of ongoing mental processes that is followed by an attentional shift and attentional binding to the events, which is often followed by causal and other event analysis processes and by schema revision. The facial expression of surprise postulated by evolutionary emotion psychologists has been found to occur rarely in surprise, for as yet unknown reasons. A physiological orienting response marked by skin conductance increase, heart rate deceleration, and pupil dilation has been observed to occur regularly in the standard version of the repetition-change paradigm of surprise induction, but the specificity of these reactions as indicators of surprise is controversial. There is indirect evidence for the assumption that the feeling of surprise consists of the direct awareness of the schema-discrepancy signal, but this feeling, or at least the self-report of surprise, is also influenced by experienced interference. In contrast, facial feedback probably does contribute substantially to the feeling of surprise and the evidence for the hypothesis that surprise is affected by the difficulty of explaining an unexpected event is, in our view, inconclusive. Regardless of how the surprise feeling is constituted, there is evidence that it has both motivational and informational effects. Finally, the prediction failure implied by unexpected events sometimes causes a negative feeling, but there is no convincing evidence that this is always the case, and we argue that even if it were so, this would not be a sufficient reason for regarding this feeling as a component, rather than as an effect of surprise.

Temporal Vulnerability and the Post-Disaster 'Window of Opportunity to Woo:' a Case Study of an African-American Floodplain Neighborhood after Hurricane Floyd in North Carolina

After major flooding associated with Hurricane Floyd (1999) in North Carolina, mitigation managers seized upon the "window of opportunity" to woo residents to accept residential buyout offers despite sizable community resistance. I present a theoretical explanation of how post-crisis periods turn into "opportunities" based on a temporal referential theory that complements alternative explanations based on temporal coincidence, panarchy, and shock-doctrine theories. Results from fieldwork conducted from 2002 to 2004 illustrate how several temporal influences compromised collective calibration of "normalcy" in local cultural models, leading to an especially heightened vulnerability to collective surprise. Four factors particularly influenced this temporal vulnerability: 1) epistemological uncertainty of floodplain dynamics due to colonization; 2) cultural practices that maintained a casual amnesia; 3) meaning attributed to stochastic timing of floods; and 4) competitive impact of referential flood baseline attractors.

Characterization of the Nencki Affective Picture System by discrete emotional categories (NAPS BE)

The Nencki Affective Picture System (NAPS; Marchewka, Żurawski, Jednoróg, & Grabowska, Behavior Research Methods, 2014) is a standardized set of 1,356 realistic, high-quality photographs divided into five categories (people, faces, animals, objects, and landscapes). NAPS has been primarily standardized along the affective dimensions of valence, arousal, and approach–avoidance, yet the characteristics of discrete emotions expressed by the images have not been investigated thus far. The aim of the present study was to collect normative ratings according to categorical models of emotions. A subset of 510 images from the original NAPS set was selected in order to proportionally cover the whole dimensional affective space. Among these, using three available classification methods, we identified images eliciting distinguishable discrete emotions. We introduce the basic-emotion normative ratings for the Nencki Affective Picture System (NAPS BE), which will allow researchers to control and manipulate stimulus properties specifically for their experimental questions of interest. The NAPS BE system is freely accessible to the scientific community for noncommercial use as supplementary materials to this article.

Spectral-temporal EEG dynamics of speech discrimination processing in infants during sleep

Background

Oddball paradigms are frequently used to study auditory discrimination by comparing event-related potential (ERP) responses from a standard, high probability sound and to a deviant, low probability sound. Previous research has established that such paradigms, such as the mismatch response or mismatch negativity, are useful for examining auditory processes in young children and infants across various sleep and attention states. The extent to which oddball ERP responses may reflect subtle discrimination effects, such as speech discrimination, is largely unknown, especially in infants that have not yet acquired speech and language.

Results

Mismatch responses for three contrasts (non-speech, vowel, and consonant) were computed as a spectral-temporal probability function in 24 infants, and analyzed at the group level by a modified multidimensional scaling. Immediately following an onset gamma response (30–50 Hz), the emergence of a beta oscillation (12–30 Hz) was temporally coupled with a lower frequency theta oscillation (2–8 Hz). The spectral-temporal probability of this coupling effect relative to a subsequent theta modulation corresponds with discrimination difficulty for non-speech, vowel, and consonant contrast features.

Discussion

The theta modulation effect suggests that unexpected sounds are encoded as a probabilistic measure of surprise. These results support the notion that auditory discrimination is driven by the development of brain networks for predictive processing, and can be measured in infants during sleep. The results presented here have implications for the interpretation of discrimination as a probabilistic process, and may provide a basis for the development of single-subject and single-trial classification in a clinically useful context.

Conclusion

An infant’s brain is processing information about the environment and performing computations, even during sleep. These computations reflect subtle differences in acoustic feature processing that are necessary for language-learning. Results from this study suggest that brain responses to deviant sounds in an oddball paradigm follow a cascade of oscillatory modulations. This cascade begins with a gamma response that later emerges as a beta synchronization, which is temporally coupled with a theta modulation, and followed by a second, subsequent theta modulation. The difference in frequency and timing of the theta modulations appears to reflect a measure of surprise. These insights into the neurophysiological mechanisms of auditory discrimination provide a basis for exploring the clinically utility of the MMR_TF and other auditory oddball responses.

Roles of centromedian parafascicular nuclei of thalamus and cholinergic interneurons in the dorsal striatum in associative learning of environmental events

The thalamus provides a massive input to the striatum, but despite accumulating evidence, the functions of this system remain unclear. It is known, however, that the centromedian (CM) and parafascicular (Pf) nuclei of the thalamus can strongly influence particular striatal neuron subtypes, notably including the cholinergic interneurons of the striatum (CINs), key regulators of striatal function. Here, we highlight the thalamostriatal system through the CM-Pf to striatal CINs. We consider how, by virtue of the direct synaptic connections of the CM and PF, their neural activity contributes to the activity of CINs and striatal projection neurons (SPNs). CM-Pf neurons are strongly activated at sudden changes in behavioral context, such as switches in action-outcome contingency or sequence of behavioral requirements, suggesting that their activity may represent change of context operationalized as associability. Striatal CINs, on the other hand, acquire and loose responses to external events associated with particular contexts. In light of this physiological evidence, we propose a hypothesis of the CM-Pf-CINs system, suggesting that it augments associative learning by generating an associability signal and promotes reinforcement learning guided by reward prediction error signals from dopamine-containing neurons. We discuss neuronal circuit and synaptic organizations based on in vivo/in vitro studies that we suppose to underlie our hypothesis. Possible implications of CM-Pf-CINs dysfunction (or degeneration) in brain diseases are also discussed by focusing on Parkinson's disease.

Activity patterns of serotonin neurons underlying cognitive flexibility

Serotonin is implicated in mood and affective disorders. However, growing evidence suggests that a core endogenous role is to promote flexible adaptation to changes in the causal structure of the environment, through behavioral inhibition and enhanced plasticity. We used long-term photometric recordings in mice to study a population of dorsal raphe serotonin neurons, whose activity we could link to normal reversal learning using pharmacogenetics. We found that these neurons are activated by both positive and negative prediction errors, and thus report signals similar to those proposed to promote learning in conditions of uncertainty. Furthermore, by comparing the cue responses of serotonin and dopamine neurons, we found differences in learning rates that could explain the importance of serotonin in inhibiting perseverative responding. Our findings show how the activity patterns of serotonin neurons support a role in cognitive flexibility, and suggest a revised model of dopamine-serotonin opponency with potential clinical implications.