A differential role for human hippocampus in novelty and contextual processing: Implications for P300

Attention control training and transfer effects on cognitive tasks

Attention control is the common element underlying different executive functions. The backward Masking Majority Function Task (MFT-M) requires intensive attention control, and represents a diverse situation where attentional resources need to be allocated dynamically and flexibly to reduce uncertainty. Aiming to train attention control using MFT-M and examine the training transfer effects in various executive functions, we recruited healthy young adults (n = 84) and then equally randomized them into two groups trained with either MFT-M or a sham program for seven consecutive days. Cognitive evaluations were conducted before and after the training, and the electroencephalograph (EEG) signals were recorded for the revised Attention Network Test (ANT-R), N-back, and Task-switching (TS) tasks. Compared to the control group, the training group performed better on the congruent condition of Flanker and the double-congruency condition of Flanker and Location in the ANT-R task, and on the learning trials in the verbal memory test. The training group also showed a larger P2 amplitude decrease and P3 amplitude increase in the 2-back task and a larger P3 amplitude increase in the TS task's repeat condition than the control group, indicating improved neural efficiency in two tasks' attentional processes. Introversion moderated the transfer effects of training, as indicated by the significant group*introversion interactions on the post-training 1-back efficiency and TS switching cost. Our results suggested that attention control training with the MFT-M showed a broad transfer scope, and the transfer effect was influenced by the form of training task. Introversion facilitated the transfer to working memory and hindered the transfer to flexibility.

Cognitive simulation along with neural adaptation explain effects of suggestions: a novel theoretical framework

Hypnosis is an effective intervention with proven efficacy that is employed in clinical settings and for investigating various cognitive processes. Despite their practical success, no consensus exists regarding the mechanisms underlying well-established hypnotic phenomena. Here, we suggest a new framework called the Simulation-Adaptation Theory of Hypnosis (SATH). SATH expands the predictive coding framework by focusing on (a) redundancy elimination in generative models using intrinsically generated prediction errors, (b) adaptation due to amplified or prolonged neural activity, and (c) using internally generated predictions as a venue for learning new associations. The core of our treatise is that simulating proprioceptive, interoceptive, and exteroceptive signals, along with the top-down attenuation of the precision of sensory prediction errors due to neural adaptation, can explain objective and subjective hypnotic phenomena. Based on these postulations, we offer mechanistic explanations for critical categories of direct verbal suggestions, including (1) direct-ideomotor, (2) challenge-ideomotor, (3) perceptual, and (4) cognitive suggestions. Notably, we argue that besides explaining objective responses, SATH accounts for the subjective effects of suggestions, i.e., the change in the sense of agency and reality. Finally, we discuss individual differences in hypnotizability and how SATH accommodates them. We believe that SATH is exhaustive and parsimonious in its scope, can explain a wide range of hypnotic phenomena without contradiction, and provides a host of testable predictions for future research.

Neural correlates of intelligence: ERP Components of temporary storage predict fluid intelligence over and above those of executive functions

Previous research has revealed that individuals with different levels of intelligence exhibit distinct patterns of event-related potentials (ERPs) related to executive functions and temporary storage. However, there is a lack of studies investigating the relative contributions of these ERPs in predicting individual differences in fluid intelligence. This study aims to examine the extent to which ERPs associated with executive functions and temporary storage can predict individual differences in fluid intelligence. Special attention is given to determining whether electrophysiological activities of temporary storage can predict fluid intelligence after accounting for executive functions, and vice versa. Both executive attention and temporary storage were measured by two experimental tasks, while electroencephalographic data were collected simultaneously. Fluid intelligence was assessed by two established tests. To address previous inconsistencies due to small sample sizes, a relatively large sample of young adults (N = 136) was recruited. The results revealed that participants with lower fluid intelligence displayed larger P3 amplitudes in the executive functions and temporary storage tasks compared to those with higher fluid intelligence. Additionally, the amplitudes of frontal and parietal P3s elicited by both executive functions and temporary storage significantly predicted fluid intelligence. Interestingly, the frontal and parietal P3s associated with temporary storage predicted fluid intelligence beyond the contributions of executive functions, supporting the storage account of individual differences in fluid intelligence. This study provides an original and fresh understanding of how executive functions and temporary storage contribute to fluid intelligence, offering new insights into the neurocognitive mechanisms underlying intelligence.

Sound category habituation requires task-relevant attention

Introduction

Processing the wealth of sensory information from the surrounding environment is a vital human function with the potential to develop learning, advance social interactions, and promote safety and well-being.

Methods

To elucidate underlying processes governing these activities we measured neurophysiological responses to patterned stimulus sequences during a sound categorization task to evaluate attention effects on implicit learning, sound categorization, and speech perception. Using a unique experimental design, we uncoupled conceptual categorical effects from stimulus-specific effects by presenting categorical stimulus tokens that did not physically repeat.

Results

We found effects of implicit learning, categorical habituation, and a speech perception bias when the sounds were attended, and the listeners performed a categorization task (task-relevant). In contrast, there was no evidence of a speech perception bias, implicit learning of the structured sound sequence, or repetition suppression to repeated within-category sounds (no categorical habituation) when participants passively listened to the sounds and watched a silent closed-captioned video (task-irrelevant). No indication of category perception was demonstrated in the scalp-recorded brain components when participants were watching a movie and had no task with the sounds.

Discussion

These results demonstrate that attention is required to maintain category identification and expectations induced by a structured sequence when the conceptual information must be extracted from stimuli that are acoustically distinct. Taken together, these striking attention effects support the theoretical view that top-down control is required to initiate expectations for higher level cognitive processing.

The P300, the LPP, context updating, and memory: What is the functional significance of the emotion-related late positive potential?

The emotion-related late positive potential (LPP) of the event-related potential (ERP) has been the topic of many studies over the previous two decades, but the function of this component (the cognitive process that it reflects) is very much an open question. In this paper, I build on frameworks that suggest a close relationship between the LPP and the P300 component of the ERP to argue that the classic context updating account of the P300 may provide insights into the function of the LPP. I then review broader connections between the LPP and memory, and I connect the LPP to research and theory in the area of emotional memory. I argue that while a relationship between the LPP and attention has been widely noted in the literature, connections to memory have been overlooked and that a memory-related process should be considered as one candidate for the function of the LPP.

Neurophysiological markers of successful learning in healthy aging

The capacity to learn and memorize is a key determinant for the quality of life but is known to decline to varying degrees with age. However, neural correlates of memory formation and the critical features that determine the extent to which aging affects learning are still not well understood. By employing a visual sequence learning task, we were able to track the behavioral and neurophysiological markers of gradual learning over several repetitions, which is not possible in traditional approaches that utilize a remember vs. forgotten comparison. On a neurophysiological level, we focused on two learning-related centro-parietal event-related potential (ERP) components: the expectancy-driven P300 and memory-related broader positivity (BP). Our results revealed that although both age groups showed significant learning progress, young individuals learned faster and remembered more stimuli than older participants. Successful learning was directly linked to a decrease of P300 and BP amplitudes. However, young participants showed larger P300 amplitudes with a sharper decrease during the learning, even after correcting for an observed age-related longer P300 latency and increased P300 peak variability. Additionally, the P300 amplitude predicted learning success in both age groups and showed good test-retest reliability. On the other hand, the memory formation processes, reflected by the BP amplitude, revealed a similar level of engagement in both age groups. However, this engagement did not translate into the same learning progress in the older participants. We suggest that the slower and more variable timing of the stimulus identification process reflected in the P300 means that despite the older participants engaging the memory formation process, there is less time for it to translate the categorical stimulus location information into a solidified memory trace. The results highlight the important role of the P300 and BP as a neurophysiological marker of learning and may enable the development of preventive measures for cognitive decline.

Reliability and stability of oddball P300 amplitude in older adults: The role of stimulus sequence effects

The P300 may be an individual difference marker of neuro-cognitive function, which due to age-related cognitive decline may be particularly useful in older adults. Recently, we reported effects of the local stimulus sequence in an oddball task (i.e., the number of non-targets that preceded a target) on P300 amplitude in young and older adults. The same older adults completed a second session of the task 4-8 months after the first session. Here, we examined the effect of the stimulus sequence on the between- and within-session reliability and stability of P300 amplitude and RT, and their intertrial variability, in this sample of older adults. The sequence effects - an inverted U-shape effect of the number of standards preceding a target on parietal P300, and a linear effect on frontal P300 - were stable within and across sessions on the group level. Within individuals, P300 amplitude at frontal and parietal electrodes was generally very reliable and stable, mostly independently of sequence effects, encouraging its use as an individual difference marker of neuro-cognitive function in older adults. However, measures of the strength of the sequence effects themselves showed unacceptable reliability, speaking against their use as individual difference markers, at least in older adults.

A neurophysiological perspective on the integration between incidental learning and cognitive control

Adaptive behaviour requires interaction between neurocognitive systems. Yet, the possibility of concurrent cognitive control and incidental sequence learning remains contentious. We designed an experimental procedure of cognitive conflict monitoring that follows a pre-defined sequence unknown to participants, in which either statistical or rule-based regularities were manipulated. We show that participants learnt the statistical differences in the sequence when stimulus conflict was high. Neurophysiological (EEG) analyses confirmed but also specified the behavioural results: the nature of conflict, the type of sequence learning, and the stage of information processing jointly determine whether cognitive conflict and sequence learning support or compete with each other. Especially statistical learning has the potential to modulate conflict monitoring. Cognitive conflict and incidental sequence learning can engage in cooperative fashion when behavioural adaptation is challenging. Three replication and follow-up experiments provide insights into the generalizability of these results and suggest that the interaction of learning and cognitive control is dependent on the multifactorial aspects of adapting to a dynamic environment. The study indicates that connecting the fields of cognitive control and incidental learning is advantageous to achieve a synergistic view of adaptive behaviour.

A key role of the hippocampal P3 in the attentional blink

The attentional blink (AB) refers to an impaired identification of target stimuli (T2), which are presented shortly after a prior target (T1) within a rapid serial visual presentation (RSVP) stream. It has been suggested that the AB is related to a failed transfer of T2 into working memory and that hippocampus (HC) and entorhinal cortex (EC) are regions crucial for this transfer. Since the event-related P3 component has been linked to inhibitory processes, we hypothesized that the hippocampal P3 elicited by T1 may impact on T2 processing within HC and EC. To test this hypothesis, we reanalyzed microwire data from 21 patients, who performed an RSVP task, during intracranial recordings for epilepsy surgery assessment (Reber et al., 2017). We identified T1-related hippocampal P3 components in the local field potentials (LFPs) and determined the temporal onset of T2 processing in HC/EC based on single-unit response onset activity. In accordance with our hypothesis, T1-related single-trial P3 amplitudes at the onset of T2 processing were clearly larger for unseen compared to seen T2-stimuli. Moreover, increased T1-related single-trial P3 peak latencies were found for T2[unseen] versus T2[seen] trials in case of lags 1 to 3, which was in line with our predictions. In conclusion, our findings support inhibition models of the AB and indicate that the hippocampal P3 elicited by T1 plays a central role in the AB.

The P3 indexes the distance between perceived and target image

Visual recognition requires inferring the similarity between a perceived object and a mental target. However, a measure of similarity is difficult to determine when it comes to complex stimuli such as faces. Indeed, people may notice someone "looks like" a familiar face, but find it hard to describe on the basis of what features such a comparison is based. Previous work shows that the number of similar visual elements between a face pictogram and a memorized target correlates with the P300 amplitude in the visual evoked potential. Here, we redefine similarity as the distance inferred from a latent space learned using a state-of-the-art generative adversarial neural network (GAN). A rapid serial visual presentation experiment was conducted with oddball images generated at varying distances from the target to determine how P300 amplitude related to GAN-derived distances. The results showed that distance-to-target was monotonically related to the P300, showing perceptual identification was associated with smooth, drifting image similarity. Furthermore, regression modeling indicated that while the P3a and P3b sub-components had distinct responses in location, time, and amplitude, they were similarly related to target distance. The work demonstrates that the P300 indexes the distance between perceived and target image in smooth, natural, and complex visual stimuli and shows that GANs present a novel modeling methodology for studying the relationships between stimuli, perception, and recognition.

Global Functional Connectivity at Rest Is Associated with Attention: An Arterial Spin Labeling Study

Neural markers of attention, including those frequently linked to the event-related potential P3 (P300) or P3b component, vary widely within and across participants. Understanding the neural mechanisms of attention that contribute to the P3 is crucial for better understanding attention-related brain disorders. All ten participants were scanned twice with a resting-state PCASL perfusion MRI and an ERP with a visual oddball task to measure brain resting-state functional connectivity (rsFC) and P3 parameters (P3 amplitudes and P3 latencies). Global rsFC (average rsFC across the entire brain) was associated with both P3 amplitudes (r = 0.57, p = 0.011) and P3 onset latencies (r = -0.56, p = 0.012). The observed P3 parameters were correlated with predicted P3 amplitude from the global rsFC (amplitude: r = +0.48, p = 0.037; latency: r = +0.40, p = 0.088) but not correlated with the rsFC over the most significant individual edge. P3 onset latency was primarily related to long-range connections between the prefrontal and parietal/limbic regions, while P3 amplitudes were related to connections between prefrontal and parietal/occipital, between sensorimotor and subcortical, and between limbic/subcortical and parietal/occipital regions. These results demonstrated the power of resting-state PCASL and P3 correlation with brain global functional connectivity.

Modulation of Spectral Representation and Connectivity Patterns in Response to Visual Narrative in the Human Brain

The regional brain networks and the underlying neurophysiological mechanisms subserving the cognition of visual narrative in humans have largely been studied with non-invasive brain recording. In this study, we specifically investigated how regional and cross-regional cortical activities support visual narrative interpretation using intracranial stereotactic electroencephalograms recordings from thirteen human subjects (6 females, and 7 males). Widely distributed recording sites across the brain were sampled while subjects were explicitly instructed to observe images from fables presented in “sequential” order, and a set of images drawn from multiple fables presented in “scrambled” order. Broadband activity mainly within the frontal and temporal lobes were found to encode if a presented image is part of a visual narrative (sequential) or random image set (scrambled). Moreover, the temporal lobe exhibits strong activation in response to visual narratives while the frontal lobe is more engaged when contextually novel stimuli are presented. We also investigated the dynamics of interregional interactions between visual narratives and contextually novel series of images. Interestingly, the interregional connectivity is also altered between sequential and scrambled sequences. Together, these results suggest that both changes in regional neuronal activity and cross-regional interactions subserve visual narrative and contextual novelty processing.

Generalized Simultaneous Localization and Mapping (G-SLAM) as unification framework for natural and artificial intelligences: towards reverse engineering the hippocampal/entorhinal system and principles of high-level cognition

Simultaneous localization and mapping (SLAM) represents a fundamental problem for autonomous embodied systems, for which the hippocampal/entorhinal system (H/E-S) has been optimized over the course of evolution. We have developed a biologically-inspired SLAM architecture based on latent variable generative modeling within the Free Energy Principle and Active Inference (FEP-AI) framework, which affords flexible navigation and planning in mobile robots. We have primarily focused on attempting to reverse engineer H/E-S "design" properties, but here we consider ways in which SLAM principles from robotics may help us better understand nervous systems and emergent minds. After reviewing LatentSLAM and notable features of this control architecture, we consider how the H/E-S may realize these functional properties not only for physical navigation, but also with respect to high-level cognition understood as generalized simultaneous localization and mapping (G-SLAM). We focus on loop-closure, graph-relaxation, and node duplication as particularly impactful architectural features, suggesting these computational phenomena may contribute to understanding cognitive insight (as proto-causal-inference), accommodation (as integration into existing schemas), and assimilation (as category formation). All these operations can similarly be describable in terms of structure/category learning on multiple levels of abstraction. However, here we adopt an ecological rationality perspective, framing H/E-S functions as orchestrating SLAM processes within both concrete and abstract hypothesis spaces. In this navigation/search process, adaptive cognitive equilibration between assimilation and accommodation involves balancing tradeoffs between exploration and exploitation; this dynamic equilibrium may be near optimally realized in FEP-AI, wherein control systems governed by expected free energy objective functions naturally balance model simplicity and accuracy. With respect to structure learning, such a balance would involve constructing models and categories that are neither too inclusive nor exclusive. We propose these (generalized) SLAM phenomena may represent some of the most impactful sources of variation in cognition both within and between individuals, suggesting that modulators of H/E-S functioning may potentially illuminate their adaptive significances as fundamental cybernetic control parameters. Finally, we discuss how understanding H/E-S contributions to G-SLAM may provide a unifying framework for high-level cognition and its potential realization in artificial intelligences.

Visual Selective Attention P300 Source in Frontal-Parietal Lobe: ERP and fMRI Study

Visual selective attention can be achieved into bottom-up and top-down attention. Different selective attention tasks involve different attention control ways. The pop-out task requires more bottom-up attention, whereas the search task involves more top-down attention. P300, which is the positive potential generated by the brain in the latency of 300 ~ 600 ms after stimulus, reflects the processing of attention. There is no consensus on the P300 source. The aim of present study is to study the source of P300 elicited by different visual selective attention. We collected thirteen participants' P300 elicited by pop-out and search tasks with event-related potentials (ERP). We collected twenty-six participants' activation brain regions in pop-out and search tasks with functional magnetic resonance imaging (fMRI). And we analyzed the sources of P300 using the ERP and fMRI integration with high temporal resolution and high spatial resolution. ERP results indicated that the pop-out task induced larger P300 than the search task. P300 induced by the two tasks distributed at frontal and parietal lobes, with P300 induced by the pop-out task mainly at the parietal lobe and that induced by the search task mainly at the frontal lobe. Further ERP and fMRI integration analysis showed that neural difference sources of P300 were the right precentral gyrus, left superior frontal gyrus (medial orbital), left middle temporal gyrus, left rolandic operculum, right postcentral gyrus, and left angular gyrus. Our study suggests that the frontal and parietal lobes contribute to the P300 component of visual selective attention.

Can the elderly take the action? - The influence of unitization induced by action relationships on the associative memory deficit

Healthy aging is associated with intact familiarity, whereas recollection, usually supporting associative memory, is attenuated. Accordingly, associative memory shows a stronger age-related decline than item memory. One approach to alleviate age-related associative memory deficits is to increase the contribution of familiarity to associative memory by creating encoding conditions that allow to integrate separate stimuli to an entity (unitization). The current study investigated whether bottom-up unitization can reduce age-related differences in associative memory. Younger (YA) and older adults (OA) studied associations between semantically unrelated objects, spatially arranged in a way that an action between these two objects is possible (unitized, e.g., emptying a bottle into a sneaker) or not (non-unitized). At test, participants distinguished intact from recombined and new object pairs. As expected, we found larger age differences for associative memory than for item memory. Additionally, the presence of action relationships supports memory performance in both age groups. In the event-related potentials (ERP) of the test phase, we observed an age-related attenuation of recollection and preserved familiarity independent of the action relationship condition. Considering comparisons including the recombined pairs, the ERP correlate of associative familiarity (i.e., intact vs. recombined) was present in OA for action-related pairs, whereas for YA, there was no evidence for enhanced familiarity for action-related pairs. In the late time window, ERP evidence for recollection for intact action-related object pairs was obtained independent of age group. In conclusion, both age groups benefited from unitization by action relationships but by different mechanisms. While YA show no associative familiarity for action-related object pairs but a general reliance on recollection for associations in action-related and -unrelated pairs, OA seem to rely more on familiarity for the specific arrangement of action-related pairs.

A State-of-the-Art Review of EEG-Based Imagined Speech Decoding

Currently, the most used method to measure brain activity under a non-invasive procedure is the electroencephalogram (EEG). This is because of its high temporal resolution, ease of use, and safety. These signals can be used under a Brain Computer Interface (BCI) framework, which can be implemented to provide a new communication channel to people that are unable to speak due to motor disabilities or other neurological diseases. Nevertheless, EEG-based BCI systems have presented challenges to be implemented in real life situations for imagined speech recognition due to the difficulty to interpret EEG signals because of their low signal-to-noise ratio (SNR). As consequence, in order to help the researcher make a wise decision when approaching this problem, we offer a review article that sums the main findings of the most relevant studies on this subject since 2009. This review focuses mainly on the pre-processing, feature extraction, and classification techniques used by several authors, as well as the target vocabulary. Furthermore, we propose ideas that may be useful for future work in order to achieve a practical application of EEG-based BCI systems toward imagined speech decoding.

Automatic Sensory Predictions: A Review of Predictive Mechanisms in the Brain and Their Link to Conscious Processing

The human brain has the astonishing capacity of integrating streams of sensory information from the environment and forming predictions about future events in an automatic way. Despite being initially developed for visual processing, the bulk of predictive coding research has subsequently focused on auditory processing, with the famous mismatch negativity signal as possibly the most studied signature of a surprise or prediction error (PE) signal. Auditory PEs are present during various consciousness states. Intriguingly, their presence and characteristics have been linked with residual levels of consciousness and return of awareness. In this review we first give an overview of the neural substrates of predictive processes in the auditory modality and their relation to consciousness. Then, we focus on different states of consciousness - wakefulness, sleep, anesthesia, coma, meditation, and hypnosis - and on what mysteries predictive processing has been able to disclose about brain functioning in such states. We review studies investigating how the neural signatures of auditory predictions are modulated by states of reduced or lacking consciousness. As a future outlook, we propose the combination of electrophysiological and computational techniques that will allow investigation of which facets of sensory predictive processes are maintained when consciousness fades away.

How predictability affects habituation to novelty

One becomes accustomed to repeated exposures, even for a novel event. In the present study, we investigated how predictability affects habituation to novelty by applying a mathematical model of arousal that we previously developed, and through the use of psychophysiological experiments to test the model's prediction. We formalized habituation to novelty as a decrement in Kullback-Leibler divergence from Bayesian prior to posterior (i.e., information gain) representing arousal evoked from a novel event through Bayesian update. The model predicted an interaction effect between initial uncertainty and initial prediction error (i.e., predictability) on habituation to novelty: the greater the initial uncertainty, the faster the decrease in information gain (i.e., the sooner habituation occurs). This prediction was supported by experimental results using subjective reports of surprise and event-related potential (P300) evoked by visual-auditory incongruity. Our findings suggest that in highly uncertain situations, repeated exposure to stimuli can enhance habituation to novel stimuli.

Expectation-driven novelty effects in episodic memory

Novel and unexpected stimuli are often prioritised in memory, given their inherent salience. Nevertheless, not all forms of novelty show such an enhancement effect. Here, we discuss the role expectation plays in modulating the way novelty affects memory processes, circuits, and subsequent performance. We first review independent effects of expectation on memory, and then consider how different types of novelty are characterised by expectation. We argue that different types of novelty defined by expectation implicate differential neurotransmission in memory formation brain regions and may also result in the creation of different types of memory. Contextual novelty, which is unexpected by definition, is often associated with better recollection, supported by dopaminergic-hippocampal interactions. On the other hand, expected stimulus novelty is supported by engagement of medial temporal cortices, as well as the hippocampus, through cholinergic modulation. Furthermore, when expected stimulus novelty results in enhanced memory, it is predominantly driven by familiarity. The literature reviewed here highlights the complexity of novelty-sensitive memory systems, the distinction between types of novelty, and how they are differentially affected by expectancy.

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.

Encoding-linked pupil response is modulated by expected and unexpected novelty: Implications for memory formation and neurotransmission

Whether a novel stimulus is expected or unexpected may have implications for the kind of ensuing encoding and the type of subsequent memory. Pupil response was used in the present study to explore the way expected and unexpected stimuli are encoded and whether encoding-linked pupil response is modulated by expectation. Participants first established a contingency relationship between a series of symbols and the type of stimulus (man-made or natural) that followed each one. At encoding, some of the target stimuli violated the previously established relationship (i.e., unexpected), while the majority conformed to this relationship (i.e., expected). Expectation at encoding had opposite effects on familiarity and recollection, the two types of memory that support recognition, and modulated differently the way pupil response predicted subsequent memory. Encoding of unexpected novel stimuli was associated with increased pupil dilation as a predictor of subsequent memory type and strength. In contrast, encoding of expected novel stimuli was associated with decreased pupil response (constriction), which was predictive of subsequent memory type and strength. The findings support the close link between pupil response and memory formation, but critically indicate that this is modulated by the type of novelty as defined by expectation. These novel findings have important implications for the encoding mechanisms involved when different types of novelty are detected and is proposed to indicate the operation of different neurotransmitters during memory formation.

Out of the blue: understanding abrupt and wayward transitions in thought using probability and predictive processing

Thoughts that appear to come to us ‘out of the blue’ or ‘out of nowhere’ are a familiar aspect of mental experience. Such thoughts tend to elicit feelings of surprise and spontaneity. Although we are beginning to understand the neural processes that underlie the arising of such thoughts, little is known about what accounts for their peculiar phenomenology. Here, we focus on one central aspect of this phenomenology—the experience of surprise at their occurrence, as it relates to internal probabilistic predictions regarding mental states. We introduce a distinction between two phenomenologically different types of transitions in thought content: (i) abrupt transitions, which occur at surprising times but lead to unsurprising thought content, and (ii) wayward transitions, which occur at surprising times and also lead to surprising thought content. We examine these two types of transitions using a novel approach that combines probabilistic and predictive processing concepts and principles. We employ two different probability metrics—transition and occurrence probability—to characterize and differentiate between abrupt and wayward transitions. We close by discussing some potentially beneficial ways in which these two kinds of transitions in thought content may contribute to mental function, and how they may be implemented at the neural level.

This article is part of the theme issue ‘Offline perception: voluntary and spontaneous perceptual experiences without matching external stimulation’.

Neuronal activation in the human centromedian-parafascicular complex predicts cortical responses to behaviorally significant auditory events

Studies with non-human primates have suggested an excitatory influence of the thalamus on the cerebral cortex, with the centromedian-parafascicular complex (CM-Pf) being particularly involved in processes of sensory event-driven attention and arousal. To define the involvement of the human CM-Pf in bottom-up and top-down auditory attention, we simultaneously recorded cortical EEG activity and intracranial local field potentials (LFPs) via electrodes implanted for deep brain stimulation for the treatment of neuropathic pain. The patients (N ​= ​6) performed an auditory three-class oddball paradigm with frequent standard stimuli and two types of infrequent deviant stimuli (target and distractor). We found a parietal P3b to targets and a central P3a to distractors at the scalp level. Subcortical recordings in the CM-Pf revealed enhanced activation to targets compared to standards. Interarea-correlation analyses showed that activation in the CM-Pf predicted the generation of longer latency P3b scalp potentials specifically in the target condition. Our results provide first direct human evidence for a functional temporal relationship between target-related activation in the CM-Pf and an enhanced cortical target response. These results corroborate the hypothetical model of a cortico-basal ganglia loop system that switches from top-down to bottom-up mode in response to salient, task-relevant external events that are not predictable.