Prediction Error Responses Research Articles

Interpretation of individual differences in computational neuroscience using a latent input approach.

Computational neuroscience offers a valuable opportunity to understand the neural mechanisms underlying behavior. However, interpreting individual differences in these mechanisms, such as developmental differences, is less straightforward. We illustrate this challenge through studies that examine individual differences in reinforcement learning. In these studies, a computational model generates an individual-specific prediction error regressor to model activity in a brain region of interest. Individual differences in the resulting regression weight are typically interpreted as individual differences in neural coding. We first demonstrate that the absence of individual differences in neural coding is not problematic, as such differences are already captured in the individual specific regressor. We then review that the presence of individual differences is typically interpreted as individual differences in the use of brain resources. However, through simulations, we illustrate that these differences could also stem from other factors such as the standardization of the prediction error, individual differences in brain networks outside the region of interest, individual differences in the duration of the prediction error response, individual differences in outcome valuation, and in overlooked individual differences in computational model parameters or the type of computational model. To clarify these interpretations, we provide several recommendations. In this manner we aim to advance the understanding and interpretation of individual differences in computational neuroscience.

Learned response dynamics reflect stimulus timing and encode temporal expectation violations in superficial layers of mouse V1.

The ability to recognize ordered event sequences is a fundamental component of sensory cognition and underlies the capacity to generate temporally specific expectations of future events based on previous experience. Various lines of evidence suggest that the primary visual cortex participates in some form of predictive processing, but many details remain ambiguous. Here we use two-photon calcium imaging in layer 2/3 of the mouse primary visual cortex (V1) to study changes to neural activity under a multi-day sequence learning paradigm with respect to prediction error responses, stimulus encoding, and time. We find increased neural activity at the time an expected, but omitted, stimulus would have occurred but no significant prediction error responses following an unexpected stimulus substitution. Sequence representations became sparser and less correlated with training, although these changes had no effect on decoding accuracy of stimulus identity or timing. Additionally, we find that experience modifies the temporal structure of stimulus responses to produce a bias towards predictive stimulus-locked activity. Finally, we find significant temporal structure during intersequence rest periods that was largely unchanged by training.

Auditory prediction errors in sound frequency and duration generated different cortical activation patterns in the human brain: an ECoG study.

Sound frequency and duration are essential auditory components. The brain perceives deviations from the preceding sound context as prediction errors, allowing efficient reactions to the environment. Additionally, prediction error response to duration change is reduced in the initial stages of psychotic disorders. To compare the spatiotemporal profiles of responses to prediction errors, we conducted a human electrocorticography study with special attention to high gamma power in 13 participants who completed both frequency and duration oddball tasks. Remarkable activation in the bilateral superior temporal gyri in both the frequency and duration oddball tasks were observed, suggesting their association with prediction errors. However, the response to deviant stimuli in duration oddball task exhibited a second peak, which resulted in a bimodal response. Furthermore, deviant stimuli in frequency oddball task elicited a significant response in the inferior frontal gyrus that was not observed in duration oddball task. These spatiotemporal differences within the Parasylvian cortical network could account for our efficient reactions to changes in sound properties. The findings of this study may contribute to unveiling auditory processing and elucidating the pathophysiology of psychiatric disorders.

Acetylcholine modulates the precision of prediction error in the auditory cortex.

A fundamental property of sensory systems is their ability to detect novel stimuli in the ambient environment. The auditory brain contains neurons that decrease their response to repetitive sounds but increase their firing rate to novel or deviant stimuli; the difference between both responses is known as stimulus-specific adaptation or neuronal mismatch (nMM). Here, we tested the effect of microiontophoretic applications of ACh on the neuronal responses in the auditory cortex (AC) of anesthetized rats during an auditory oddball paradigm, including cascade controls. Results indicate that ACh modulates the nMM, affecting prediction error responses but not repetition suppression, and this effect is manifested predominantly in infragranular cortical layers. The differential effect of ACh on responses to standards, relative to deviants (in terms of averages and variances), was consistent with the representational sharpening that accompanies an increase in the precision of prediction errors. These findings suggest that ACh plays an important role in modulating prediction error signaling in the AC and gating the access of these signals to higher cognitive levels.

Acetylcholine modulates the precision of prediction error in the auditory cortex

A fundamental property of sensory systems is their ability to detect novel stimuli in the ambient environment. The auditory brain contains neurons that decrease their response to repetitive sounds but increase their firing rate to novel or deviant stimuli; the difference between both responses is known as stimulus-specific adaptation or neuronal mismatch (nMM). Here, we tested the effect of microiontophoretic applications of ACh on the neuronal responses in the auditory cortex (AC) of anesthetized rats during an auditory oddball paradigm, including cascade controls. Results indicate that ACh modulates the nMM, affecting prediction error responses but not repetition suppression, and this effect is manifested predominantly in infragranular cortical layers. The differential effect of ACh on responses to standards, relative to deviants (in terms of averages and variances), was consistent with the representational sharpening that accompanies an increase in the precision of prediction errors. These findings suggest that ACh plays an important role in modulating prediction error signaling in the AC and gating the access of these signals to higher cognitive levels.

Auditory prediction and prediction error responses evoked through a novel cascade roving paradigm: a human ECoG study.

Auditory sensory processing is assumed to occur in a hierarchical structure including the primary auditory cortex (A1), superior temporal gyrus, and frontal areas. These areas are postulated to generate predictions for incoming stimuli, creating an internal model of the surrounding environment. Previous studies on mismatch negativity have indicated the involvement of the superior temporal gyrus in this processing, whereas reports have been mixed regarding the contribution of the frontal cortex. We designed a novel auditory paradigm, the "cascade roving" paradigm, which incorporated complex structures (cascade sequences) into a roving paradigm. We analyzed electrocorticography data from six patients with refractory epilepsy who passively listened to this novel auditory paradigm and detected responses to deviants mainly in the superior temporal gyrus and inferior frontal gyrus. Notably, the inferior frontal gyrus exhibited broader distribution and sustained duration of deviant-elicited responses, seemingly differing in spatio-temporal characteristics from the prediction error responses observed in the superior temporal gyrus, compared with conventional oddball paradigms performed on the same participants. Moreover, we observed that the deviant responses were enhanced through stimulus repetition in the high-gamma range mainly in the superior temporal gyrus. These features of the novel paradigm may aid in our understanding of auditory predictive coding.

Making sense of music: Insights from neurophysiology and connectivity analyses in naturalistic listening conditions

According to the latest frameworks, auditory perception and memory involve the constant prediction of future sound events by the brain, based on the continuous extraction of feature regularities from the environment. The neural hierarchical mechanisms for predictive processes in perception and memory for sounds are typically studied in relation to simple acoustic features in isolated sounds or sound patterns inserted in highly certain contexts. Such studies have identified reliable prediction formation and error signals, e.g., the N100 or the mismatch negativity (MMN) evoked responses. In real life, though, individuals often face situations in which uncertainty prevails and where making sense of sounds becomes a hard challenge. In music, not only deviations from predictions are masterly set up by composers to induce emotions but sometimes the sheer uncertainty of sound scenes is exploited for aesthetic purposes, especially in compositional styles such as Western atonal classical music. In very recent magnetoencephalography (MEG) and electroencephalography (EEG) studies, experimental and technical advances in stimulation paradigms and analysis approaches have permitted the identification of prediction-error responses from highly uncertain, atonal contexts and the extraction of prediction-related responses from real, continuous music. Moreover, functional connectivity analyses revealed the emergence of cortico-hippocampal interactions during the formation of auditory memories for more predictable vs. less predictable patterns. These findings contribute to understanding the general brain mechanisms that enable us to predict even highly uncertain sound environments and to possibly make sense of and appreciate even atonal music.

Molecularly targetable cell types in mouse visual cortex have distinguishable prediction error responses

Predictive processing postulates the existence of prediction error neurons in cortex. Neurons with both negative and positive prediction error response properties have been identified in layer 2/3 of visual cortex, but whether they correspond to transcriptionally defined subpopulations is unclear. Here we used the activity-dependent, photoconvertible marker CaMPARI2 to tag neurons in layer 2/3 of mouse visual cortex during stimuli and behaviors designed to evoke prediction errors. We performed single-cell RNA-sequencing on these populations and found that previously annotated Adamts2 and Rrad layer 2/3 transcriptional cell types were enriched when photolabeling during stimuli that drive negative or positive prediction error responses, respectively. Finally, we validated these results functionally by designing artificial promoters for use in AAV vectors to express genetically encoded calcium indicators. Thus, transcriptionally distinct cell types in layer 2/3 that can be targeted using AAV vectors exhibit distinguishable negative and positive prediction error responses.

Same but different: The latency of a shared expectation signal interacts with stimulus attributes

Predictive coding theories assert that perceptual inference is a hierarchical process of belief updating, wherein the onset of unexpected sensory data causes so-called prediction error responses that calibrate erroneous inferences. Given the functionally specialised organisation of visual cortex, it is assumed that prediction error propagation interacts with the specific visual attribute violating an expectation. We sought to test this within the temporal domain by applying time-resolved decoding methods to electroencephalography (EEG) data evoked by contextual trajectory violations of either brightness, size, or orientation within a bound stimulus. We found that following ∼170 ms post stimulus onset, responses to both size violations and orientation violations were decodable from physically identical control trials in which no attributes were violated. These two violation types were then directly compared, with attribute-specific signalling being decoded from 265 ms. Temporal generalisation suggested that this dissociation was driven by latency shifts in shared expectation signalling between the two conditions. Using a novel temporal bias method, we then found that this shared signalling occurred earlier for size violations than orientation violations. To our knowledge, we are among the first to decode expectation violations in humans using EEG and have demonstrated a temporal dissociation in attribute-specific expectancy violations.

Neural Response to Expecting a Caloric Sweet Taste Stimulus Predicts Body Mass Index Longitudinally Among Young Adult Women With Anorexia Nervosa

BackgroundAnorexia nervosa (AN) is an often-chronic illness, and we lack biomarkers to predict long-term outcome. Recent neuroimaging studies using caloric taste stimuli suggest that paradigms that have tested conditioned neural responses to expectation or salient stimulus receipt may underpin behaviors. However, whether activation of those neural circuits can predict long-term outcome has not been studied. MethodsWe followed women treated for AN (n = 35, mean age [SD] = 23 [7] years) and tested whether functional imaging brain response during a taste conditioning paradigm could predict posttreatment body mass index (BMI). We anticipated greater neural activity relative to caloric stimulus expectation and that dopamine-related receipt conditions would predict lower posttreatment BMI, indicating fear-associated arousal. ResultsFollow-up occurred at mean (SD) = 1648 (1216) days after imaging. Stimulus expectation in orbitofrontal and striatal regions and BMI and BMI change at follow-up were negatively correlated, and these correlations remained significant for the right superior orbitofrontal cortex and BMI change after multiple comparison correction (r = −0.484, p = .003). This relationship remained significant after including time between brain scanning and follow-up in the model. Reward prediction error response did not predict long-term BMI. ConclusionsThe orbitofrontal cortex is involved in learning and conditioning, and these data implicate this region in learned caloric stimulus expectation and long-term prediction of weight outcomes in AN. Thus, conditioned elevated brain response to the anticipation of receiving a caloric stimulus may drive food avoidance, suggesting that breaking such associations is central for long-term recovery from AN.

Brain reward response in adolescents and young adults with anorexia nervosa is moderated by changes in body weight and sweetness perception.

Anorexia nervosa (AN) is a severe psychiatric illness with complex etiology. Recently, we found elevated striatal brain response to sweet taste stimuli in adolescents and young adults with AN. Here, we tested the hypothesis that nutritional rehabilitation normalizes prediction error activation, a measure for dopamine-related reward circuit response, to salient caloric taste stimuli in AN. A total of 28 individuals with AN (age=16 ± 2 years; body mass index [BMI]=16 ± 1) who previously underwent brain imaging while performing a taste prediction error task using sucrose as salient caloric stimulus, participated in a second brain imaging scan (BMI=18 ± 1) after intensive specialized eating disorder treatment (41 ± 15 days). A total of 31 healthy controls (age=16 ± 3 years; BMI=21 ± 2) were also studied on two occasions. At baseline, individuals with AN demonstrated an elevated salience response in bilateral caudate head and nucleus accumbens, and right ventral striatum. At the second scan, elevated response was only found in the right nucleus accumbens. A moderator analysis indicated that greater increase in BMI and greater decrease in sweetness perception predicted lesser prediction error response at the second scan in AN. Consistent with the previously reported monetary stimulus-response, elevated taste prediction error response in AN was largely absent after weight restoration. This study indicates that changes in BMI and sweet taste perception are independent moderators of change of brain salience response in adolescents and young adults with AN. The study points toward dynamic changes in the brain reward circuitry in AN and highlights the importance of nutrition and weight restoration in that process. AN is a severe psychiatric illness. Biological factors that integrate neurobiology and behavior could become important targets to improve treatment outcome. This study highlights the importance of weight normalization and taste perception the normalization of brain function, and food type or taste-specific interventions could help in the recovery process. Furthermore, the study suggests that food-related and nonfood-related reward processing adapts to illness state in AN.

Rapid adaptation of predictive models during language comprehension: Aperiodic EEG slope, individual alpha frequency and idea density modulate individual differences in real-time model updating.

Predictive coding provides a compelling, unified theory of neural information processing, including for language. However, there is insufficient understanding of how predictive models adapt to changing contextual and environmental demands and the extent to which such adaptive processes differ between individuals. Here, we used electroencephalography (EEG) to track prediction error responses during a naturalistic language processing paradigm. In Experiment 1, 45 native speakers of English listened to a series of short passages. Via a speaker manipulation, we introduced changing intra-experimental adjective order probabilities for two-adjective noun phrases embedded within the passages and investigated whether prediction error responses adapt to reflect these intra-experimental predictive contingencies. To this end, we calculated a novel measure of speaker-based, intra-experimental surprisal (“speaker-based surprisal”) as defined on a trial-by-trial basis and by clustering together adjectives with a similar meaning. N400 amplitude at the position of the critical second adjective was used as an outcome measure of prediction error. Results showed that N400 responses attuned to speaker-based surprisal over the course of the experiment, thus indicating that listeners rapidly adapt their predictive models to reflect local environmental contingencies (here: the probability of one type of adjective following another when uttered by a particular speaker). Strikingly, this occurs in spite of the wealth of prior linguistic experience that participants bring to the laboratory. Model adaptation effects were strongest for participants with a steep aperiodic (1/f) slope in resting EEG and low individual alpha frequency (IAF), with idea density (ID) showing a more complex pattern. These results were replicated in a separate sample of 40 participants in Experiment 2, which employed a highly similar design to Experiment 1. Overall, our results suggest that individuals with a steep aperiodic slope adapt their predictive models most strongly to context-specific probabilistic information. Steep aperiodic slope is thought to reflect low neural noise, which in turn may be associated with higher neural gain control and better cognitive control. Individuals with a steep aperiodic slope may thus be able to more effectively and dynamically reconfigure their prediction-related neural networks to meet current task demands. We conclude that predictive mechanisms in language are highly malleable and dynamic, reflecting both the affordances of the present environment as well as intrinsic information processing capabilities of the individual.

Increased context adjustment is associated with auditory sensitivities but not with autistic traits.

Bayesian models of autism suggest that alterations in context‐sensitive prediction error weighting may underpin sensory perceptual alterations, such as hypersensitivities. We used an auditory oddball paradigm with pure tones arising from high or low uncertainty contexts to determine whether autistic individuals display differences in context adjustment relative to neurotypicals. We did not find group differences in early prediction error responses indexed by mismatch negativity. A dimensional approach revealed a positive correlation between context‐dependent prediction errors and subjective reports of auditory sensitivities, but not with autistic traits. These findings suggest that autism studies may benefit from accounting for sensory sensitivities in group comparisons.Lay SummaryWe aimed to understand if autistic and non‐autistic groups showed differences in their electrical brain activity measured by electroencephalography (EEG) when listening to surprising tones infrequently embedded in a statistical pattern. We found no differences between the autistic and the non‐autistic group in their EEG response to the surprising sound even if the pattern switched, indicating their ability to learn a pattern. We did find that, as subjective sensory sensitivities (but not autistic traits) increased, there were increasingly large differences between the EEG responses to surprising tones that were embedded in the different statistical patterns of tones. These findings show that perceptual alterations may be a function of sensory sensitivities, but not necessarily autistic traits. We suggest that future EEG studies in autism may benefit from accounting for sensory sensitivities.

Scene Context Impairs Perception of Semantically Congruent Objects

Visual scene context is well-known to facilitate the recognition of scene-congruent objects. Interestingly, however, according to predictive-processing accounts of brain function, scene congruency may lead to reduced (rather than enhanced) processing of congruent objects, compared with incongruent ones, because congruent objects elicit reduced prediction-error responses. We tested this counterintuitive hypothesis in two online behavioral experiments with human participants (N = 300). We found clear evidence for impaired perception of congruent objects, both in a change-detection task measuring response times and in a bias-free object-discrimination task measuring accuracy. Congruency costs were related to independent subjective congruency ratings. Finally, we show that the reported effects cannot be explained by low-level stimulus confounds, response biases, or top-down strategy. These results provide convincing evidence for perceptual congruency costs during scene viewing, in line with predictive-processing theory.

Broadband Dynamics Rather than Frequency-Specific Rhythms Underlie Prediction Error in the Primate Auditory Cortex.

Detection of statistical irregularities, measured as a prediction error response, is fundamental to the perceptual monitoring of the environment. We studied whether prediction error response is associated with neural oscillations or asynchronous broadband activity. Electrocorticography was conducted in three male monkeys, who passively listened to the auditory roving oddball stimuli. Local field potentials (LFPs) recorded over the auditory cortex underwent spectral principal component analysis, which decoupled broadband and rhythmic components of the LFP signal. We found that the broadband component captured the prediction error response, whereas none of the rhythmic components were associated with statistical irregularities of sounds. The broadband component displayed more stochastic, asymmetrical multifractal properties than the rhythmic components, which revealed more self-similar dynamics. We thus conclude that the prediction error response is captured by neuronal populations generating asynchronous broadband activity, defined by irregular dynamic states, which, unlike oscillatory rhythms, appear to enable the neural representation of auditory prediction error response.SIGNIFICANCE STATEMENT This study aimed to examine the contribution of oscillatory and asynchronous components of auditory local field potentials in the generation of prediction error responses to sensory irregularities, as this has not been directly addressed in the previous studies. Here, we show that mismatch negativity-an auditory prediction error response-is driven by the asynchronous broadband component of potentials recorded in the auditory cortex. This finding highlights the importance of nonoscillatory neural processes in the predictive monitoring of the environment. At a more general level, the study demonstrates that stochastic neural processes, which are often disregarded as neural noise, do have a functional role in the processing of sensory information.

Attention and prediction modulations in expected and unexpected visuospatial trajectories.

Humans are constantly exposed to a rich tapestry of visual information in a potentially changing environment. To cope with the computational burden this engenders, our perceptual system must use prior context to simultaneously prioritise stimuli of importance and suppress irrelevant surroundings. This study investigated the influence of prediction and attention in visual perception by investigating event-related potentials (ERPs) often associated with these processes, N170 and N2pc for prediction and attention, respectively. A contextual trajectory paradigm was used which violated visual predictions and neglected to predetermine areas of spatial interest, to account for the potentially unpredictable nature of a real-life visual scene. Participants (N = 36) viewed a visual display of cued and non-cued shapes rotating in a five-step predictable trajectory, with the fifth and final position of either the cued or non-cued shape occurring in a predictable or unpredictable spatial location. To investigate the predictive coding theory of attention we used factors of attention and prediction, whereby attention was manipulated as either cued or non-cued conditions, and prediction manipulated in either predictable or unpredictable conditions. Results showed both enhanced N170 and N2pc amplitudes to unpredictable compared to predictable stimuli. Stimulus cueing status also increased N170 amplitude, but this did not interact with stimulus predictability. The N2pc amplitude was not affected by stimulus cueing status. In accordance with previous research these results suggest the N170 is in part a visual prediction error response with respect to higher-level visual processes, and furthermore the N2pc may index attention reorientation. The results demonstrate prior context influences the sensitivity of the N170 and N2pc electrophysiological responses. These findings add further support to the role of N170 as a prediction error signal and suggest that the N2pc may reflect attentional reorientation in response to unpredicted stimulus locations.

Intention-based and sensory-based predictions

We inhabit a continuously changing world, where the ability to anticipate future states of the environment is critical for adaptation. Anticipation can be achieved by learning about the causal or temporal relationship between sensory events, as well as by learning to act on the environment to produce an intended effect. Together, sensory-based and intention-based predictions provide the flexibility needed to successfully adapt. Yet it is currently unknown whether the two sources of information are processed independently to form separate predictions, or are combined into a common prediction. To investigate this, we ran an experiment in which the final tone of two possible four-tone sequences could be predicted from the preceding tones in the sequence and/or from the participants’ intention to trigger that final tone. This tone could be congruent with both sensory-based and intention-based predictions, incongruent with both, or congruent with one while incongruent with the other. Trials where predictions were incongruent with each other yielded similar prediction error responses irrespectively of the violated prediction, indicating that both predictions were formulated and coexisted simultaneously. The violation of intention-based predictions yielded late additional error responses, suggesting that those violations underwent further differential processing which the violations of sensory-based predictions did not receive.

Standard Tone Stability as a Manipulation of Precision in the Oddball Paradigm: Modulation of Prediction Error Responses to Fixed-Probability Deviants

Electrophysiological sensory deviance detection signals, such as the mismatch negativity (MMN), have been interpreted from the predictive coding framework as manifestations of prediction error (PE). From a frequentist perspective of the classic oddball paradigm, deviant stimuli are unexpected because of their low probability. However, the amount of PE elicited by a stimulus can be dissociated from its probability of occurrence: when the observer cannot make confident predictions, any event holds little surprise value, no matter how improbable. Here we tested the hypothesis that the magnitude of the neural response elicited to an improbable sound (D) would scale with the precision of the prediction derived from the repetition of another sound (S), by manipulating repetition stability. We recorded the Electroencephalogram (EEG) from 20 participants while passively listening to 4 types of isochronous pure tone sequences differing in the probability of the S tone (880 Hz) while holding constant the probability of the D tone [1,046 Hz; p(D) = 1/11]: Oddball [p(S) = 10/11]; High confidence (7/11); Low confidence (4/11); and Random (1/11). Tones of 9 different frequencies were equiprobably presented as fillers [p(S) + p(D) + p(F) = 1]. Using a mass-univariate non-parametric, cluster-based correlation analysis controlling for multiple comparisons, we found that the amplitude of the deviant-elicited ERP became more negative with increasing S probability, in a time-electrode window consistent with the MMN (ca. 120–200 ms; frontal), suggesting that the strength of a PE elicited to an improbable event indeed increases with the precision of the predictive model.

Prediction under uncertainty: Dissociating sensory from cognitive expectations in highly uncertain musical contexts

Predictive models in the brain rely on the continuous extraction of regularities from the environment. These models are thought to be updated by novel information, as reflected in prediction error responses such as the mismatch negativity (MMN). However, although in real life individuals often face situations in which uncertainty prevails, it remains unclear whether and how predictive models emerge in high-uncertainty contexts. Recent research suggests that uncertainty affects the magnitude of MMN responses in the context of music listening. However, musical predictions are typically studied with MMN stimulation paradigms based on Western tonal music, which are characterized by relatively high predictability. Hence, we developed an MMN paradigm to investigate how the high uncertainty of atonal music modulates predictive processes as indexed by the MMN and behavior. Using MEG in a group of 20 subjects without musical training, we demonstrate that the magnetic MMN in response to pitch, intensity, timbre, and location deviants is evoked in both tonal and atonal melodies, with no significant differences between conditions. In contrast, in a separate behavioral experiment involving 39 non-musicians, participants detected pitch deviants more accurately and rated confidence higher in the tonal than in the atonal musical context. These results indicate that contextual tonal uncertainty modulates processing stages in which conscious awareness is involved, although deviants robustly elicit low-level pre-attentive responses such as the MMN. The achievement of robust MMN responses, despite high tonal uncertainty, is relevant for future studies comparing groups of listeners’ MMN responses to increasingly ecological music stimuli.

The Prediction Error Responses of Unexpected Emotion and Neutral Body Postures: a vMMN Study

The Prediction Error Responses of Unexpected Emotion and Neutral Body Postures: a vMMN Study