Repetition suppression – An integrative view

Suppression, Maintenance, and Surprise: Neuronal Correlates of Predictive Processing Specialization for Musical Rhythm

Auditory repetition suppression and omission activation are opposite neural phenomena and manifestations of principles of predictive processing. Repetition suppression describes the temporal decrease in neural activity when a stimulus is constant or repeated in an expected temporal fashion; omission activity is the transient increase in neural activity when a stimulus is temporarily and unexpectedly absent. The temporal, repetitive nature of musical rhythms is ideal for investigating these phenomena. During an fMRI session, 10 healthy participants underwent scanning while listening to musical rhythms with two levels of metric complexity, and with beat omissions with different positional complexity. Participants first listened to 16-s-long presentations of continuous rhythms, before listening to a longer continuous presentation with beat omissions quasi-randomly introduced. We found deactivation in bilateral superior temporal gyri during the repeated presentation of the normal, unaltered rhythmic stimulus, with more suppression of activity in the left hemisphere. Omission activation of bilateral middle temporal gyri was right lateralized. Persistent activity was found in areas including the supplementary motor area, caudate nucleus, anterior insula, frontal areas, and middle and posterior cingulate cortex, not overlapping with either listening, suppression, or omission activation. This suggests that the areas are perhaps specialized for working memory maintenance. We found no effect of metric complexity for either the normal presentation or omissions, but we found evidence for a small effect of omission position—at an uncorrected threshold—where omissions in the more metrical salient position, i.e., the first position in the bar, showed higher activation in anterior cingulate/medial superior frontal gyrus, compared to omissions in the less salient position, in line with the role of the anterior cingulate cortex for saliency detection. The results are consistent with findings in our previous studies on Parkinson’s disease, but are put into a bigger theoretical frameset.

External (Versus Internal) Facial Features Contribute Most to Repetition Priming in Facial Recognition: ERP Evidence

Previous event-related potential (ERP) research demonstrated four successive ERP components in the repetition priming of human face recognition: P100, N170, N250r, and N400. While these components correspond, respectively, to the four stages proposed by the interactive activation and competition (IAC) model, there has been no emphasis in past research on how internal and external facial features affect repetition priming and the sensitivity of these ERP components to item interval. This study was designed to address these issues. We used faces of celebrities as targets, including completely familiar faces, familiar internal feature faces, and familiar external feature faces. We displayed a target face either immediately following its prime (immediate repetition) or after a delay with interference from a presentation of two other faces (delayed repetition). ERP differences at P100 and N170 were nearly statistically non-significant; familiar faces and familiar external feature faces were associated with reliable ERP signals of N250r and N400 in the immediate repetition condition. For delayed repetition, however, N250r and N400 signals were only preserved for the familiar external feature faces. The differences of these ERP components suggest that, compared with internal facial features, external features of a previously presented face contribute more to brain-based facial repetition priming, particularly during the last two stages of the IAC model.

Expectations about word stress modulate neural activity in speech-sensitive cortical areas

A recent dual-stream model of language processing proposed that the postero-dorsal stream performs predictive sequential processing of linguistic information via hierarchically organized internal models. However, it remains unexplored whether the prosodic segmentation of linguistic information involves predictive processes. Here, we addressed this question by investigating the processing of word stress, a major component of speech segmentation, using probabilistic repetition suppression (RS) modulation as a marker of predictive processing. In an event-related acoustic fMRI RS paradigm, we presented pairs of pseudowords having the same (Rep) or different (Alt) stress patterns, in blocks with varying Rep and Alt trial probabilities. We found that the BOLD signal was significantly lower for Rep than for Alt trials, indicating RS in the posterior and middle superior temporal gyrus (STG) bilaterally, and in the anterior STG in the left hemisphere. Importantly, the magnitude of RS was modulated by repetition probability in the posterior and middle STG. These results reveal the predictive processing of word stress in the STG areas and raise the possibility that words stress processing is related to the dorsal "where" auditory stream.

Auditory-vocal control system is object for predictive processing within seconds time range

Predictive processing across hierarchically organized time scales is one of the fundamental principles of neural computations in the cerebral cortex. We hypothesize that relatively complex aggregation of auditory and vocal brain systems that use auditory feedback for reflexive control of vocalizations can be an object for predictive processing. We used repetitive patterns of perturbations in auditory feedback during vocalizations to elicit implicit expectations that were violated by surprising direction of perturbations in one of the experimental conditions. Our results provide empirical support for the idea that formation of expectancy for integrated auditory-vocal brain systems, within the time range of seconds, resulted in two sequential neuronal processes. The first process reflects monitoring and error detection in prediction about perturbations in auditory feedback during vocalizations within the time range of seconds. The second neuronal process can be attributed to the optimization of brain predictions for sensory contingencies during vocalizations at separable and distinct timescales.

Evaluating the neurophysiological evidence for predictive processing as a model of perception

For many years, the dominant theoretical framework guiding research into the neural origins of perceptual experience has been provided by hierarchical feedforward models, in which sensory inputs are passed through a series of increasingly complex feature detectors. However, the long-standing orthodoxy of these accounts has recently been challenged by a radically different set of theories that contend that perception arises from a purely inferential process supported by two distinct classes of neurons: those that transmit predictions about sensory states and those that signal sensory information that deviates from those predictions. Although these predictive processing (PP) models have become increasingly influential in cognitive neuroscience, they are also criticized for lacking the empirical support to justify their status. This limited evidence base partly reflects the considerable methodological challenges that are presented when trying to test the unique predictions of these models. However, a confluence of technological and theoretical advances has prompted a recent surge in human and nonhuman neurophysiological research seeking to fill this empirical gap. Here, we will review this new research and evaluate the degree to which its findings support the key claims of PP.

Neural adaptation and cognitive inflexibility in repeated problem-solving behaviors

Repeated stimulus processing is often associated with a reduction in neural activity, known as neural adaptation. Therefore, people are more sensitive to novelty detection but likely lose flexibility in subsequent novelty processing after detection. To demonstrate the dynamic changes in neural adaption in repeated problem-solving behaviors and test its negative influence on subsequent nonrepetitive problem-solving behaviors, we adopted a Chinese character decomposition task in this fMRI study. Participants were asked to repeatedly perform 3-5 practice problems that could be solved by the same loose chunk decomposition (LCD) solution followed by a test problem that could be solved by a tight chunk decomposition (TCD) solution in the enhanced-set condition. The practice problem gradually elicited lower percent signal changes within the cuneus, superior parietal lobule (SPL), inferior frontal gyrus (IFG) and medial prefrontal cortex (mPFC) in serial positions -1, -2 and -3 of a set, implying that neural adaptation occurred in repeated practice. Both the test problem and the practice problem that following it recruited greater activation of the SPL and IFG in the enhanced-set condition than in the base-set condition when the practice problem and test problem alternately appeared, implying that the task switching cost from a more dominant task to a less dominant task and vice versa was increased after neural adaptation occurred. In other words, repeatedly solving a set of similar problems with the same solution likely leads to neural adaptation and cognitive inflexibility, which in turn have an undifferentiated impact on task switching. This finding expands existing knowledge about the neurocognitive mechanism underlying the formation of the mental set and sheds light on the influence of neural adaptation on subsequent processing.

Rehearsal initiates systems memory consolidation, sleep makes it last

After encoding, memories undergo a transitional process termed systems memory consolidation. It allows fast acquisition of new information by the hippocampus, as well as stable storage in neocortical long-term networks, where memory is protected from interference. Whereas this process is generally thought to occur slowly over time and sleep, we recently found a rapid memory systems transition from hippocampus to posterior parietal cortex (PPC) that occurs over repeated rehearsal within one study session. Here, we use fMRI to demonstrate that this transition is stabilized over sleep, whereas wakefulness leads to a reset to naïve responses, such as observed during early encoding. The role of sleep therefore seems to go beyond providing additional rehearsal through memory trace reactivation, as previously thought. We conclude that repeated study induces systems consolidation, while sleep ensures that these transformations become stable and long lasting. Thus, sleep and repeated rehearsal jointly contribute to long-term memory consolidation.

People got lost in solving a set of similar problems

A mental set generally refers to the human brain's tendency to persist with a familiar solution and stubbornly ignore alternatives. However, if a familiar solution is unable to solve a problem similar to a previous problem, does it continue to hinder alternative solutions, and if so, how and why? To answer these questions, a Chinese character decomposition task was adopted in this study. Participants were asked to perform a practice problem that could be solved by a familiar loose chunk decomposition (LCD) solution followed by a test problem that was similar to the practice problem but could only be solved by an unfamiliar tight chunk decomposition (TCD) solution or were asked to repeatedly perform 3-5 practice problems followed by a test problem; the former is the base-set condition, and the latter is the enhanced-set condition. The results showed that the test problem recruited more activation of the inferior frontal gyrus (IFG), middle occipital cortex (MOG), superior parietal lobule (SPL) and dorsal anterior cingulate cortex (dACC) than the practice problem in the latter operation and verification stage, but almost equal activation of the dACC occurred in the early exploration stage. This likely implied that people did not think that the familiar but currently invalid LCD solution could not be used to solve the test problem; thus, it continuously competed for attention with the unfamiliar TCD solution, which required more executive control to suppress. Moreover, compared with the base-set condition, the test problem in the enhanced-set condition recruited greater activations of the IFG, SPL and dACC in the latter verification stage but less activations of regions in the left IFG and MOG in the early exploration stage. These results revealed that people less actively explored and had to work harder to operate the unfamiliar TCD solution, particularly to resolve competition from the familiar but currently invalid LCD solution. In conclusion, people lost the ability to identify errors in the familiar but currently invalid solution, which in turn decreased the exploration efforts and increased the processing demands associated with alternative solutions in the form of attentional bias and competition. This finding broadly explains the dilemma of creative problem solving.

Neural correlates of novelty and appropriateness processing in externally induced constraint relaxation

Novelty and appropriateness are considered the two fundamental features of creative thinking, including insight problem solving, which can be performed through chunk decomposition and constraint relaxation. Based on a previous study that separated the neural bases of novelty and appropriateness in chunk decomposition, in this study, we used event-related functional magnetic resonance imaging (fMRI) to further dissociate these mechanisms in constraint relaxation. Participants were guided to mentally represent the method of problem solving according to the externally provided solutions that were elaborately prepared in advance and systematically varied in their novelty and appropriateness for the given problem situation. The results showed that novelty processing was completed by the temporoparietal junction (TPJ) and regions in the executive system (dorsolateral prefrontal cortex [DLPFC]), whereas appropriateness processing was completed by the TPJ and regions in the episodic memory (hippocampus), emotion (amygdala), and reward systems (orbitofrontal cortex [OFC]). These results likely indicate that appropriateness processing can result in a more memorable and richer experience than novelty processing in constraint relaxation. The shared and distinct neural mechanisms of the features of novelty and appropriateness in constraint relaxation are discussed, enriching the representation of the change theory of insight.

Rapid and independent memory formation in the parietal cortex

Previous evidence indicates that the brain stores memory in two complementary systems, allowing both rapid plasticity and stable representations at different sites. For memory to be established in a long-lasting neocortical store, many learning repetitions are considered necessary after initial encoding into hippocampal circuits. To elucidate the dynamics of hippocampal and neocortical contributions to the early phases of memory formation, we closely followed changes in human functional brain activity while volunteers navigated through two different, initially unknown virtual environments. In one condition, they were able to encode new information continuously about the spatial layout of the maze. In the control condition, no information could be learned because the layout changed constantly. Our results show that the posterior parietal cortex (PPC) encodes memories for spatial locations rapidly, beginning already with the first visit to a location and steadily increasing activity with each additional encounter. Hippocampal activity and connectivity between the PPC and hippocampus, on the other hand, are strongest during initial encoding, and both decline with additional encounters. Importantly, stronger PPC activity related to higher memory-based performance. Compared with the nonlearnable control condition, PPC activity in the learned environment remained elevated after a 24-h interval, indicating a stable change. Our findings reflect the rapid creation of a memory representation in the PPC, which belongs to a recently proposed parietal memory network. The emerging parietal representation is specific for individual episodes of experience, predicts behavior, and remains stable over offline periods, and must therefore hold a mnemonic function.