Repetition suppression: a means to index neural representations using BOLD?

Binding of cortical functional modules by synchronous high-frequency oscillations

Whether high-frequency phase-locked oscillations facilitate integration ('binding') of information across widespread cortical areas is controversial. Here we show with intracranial electroencephalography that cortico-cortical co-ripples (~100-ms-long ~90 Hz oscillations) increase during reading and semantic decisions, at the times and co-locations when and where binding should occur. Fusiform wordform areas co-ripple with virtually all language areas, maximally from 200 to 400 ms post-word-onset. Semantically specified target words evoke strong co-rippling between wordform, semantic, executive and response areas from 400 to 800 ms, with increased co-rippling between semantic, executive and response areas prior to correct responses. Co-ripples were phase-locked at zero lag over long distances (>12 cm), especially when many areas were co-rippling. General co-activation, indexed by non-oscillatory high gamma, was mainly confined to early latencies in fusiform and earlier visual areas, preceding co-ripples. These findings suggest that widespread synchronous co-ripples may assist the integration of multiple cortical areas for sustained periods during cognition.

Age-related changes in brain oscillatory patterns during an n-back task in children and adolescents

The development of brain oscillatory responses and their possible role in the working memory (WM) performance of children, adolescents and young adults was investigated. A set of 0- and 1-back tasks with letter stimuli were administered to a final sample of 131 subjects (between 6 and 20 years of age). A decrease in response times (RTs) and an increase of the sensitivity index d-prime (d') were seen with increased age. RTs increased and d' decreased with load, indicating higher difficulty for higher loads. Event-related synchronization (ERS) and event-related desynchronization (ERD) were obtained by the convolution of Morlet wavelets on the recorded EEG. Statistical analyses were performed of the absolute and relative power of brain oscillations defined by topography, frequency and latency. Posterior alpha and beta ERD, and frontocentral theta ERS, were induced by the stimuli presented during the n-back task. While relative theta ERS increased with age, absolute theta ERS, absolute and relative alpha and, absolute beta ERD, decreased with age. Age-related improvement in behavioral performance was mediated by relative theta. Alpha and beta ERD were more pronounced for the most difficult task (1-back) and for the target condition. Globally, there was high consistency of the effects of target type and task load across development. Theta ERS maturation is a crucial step for improving WM performance during development, while alpha and beta ERD maturation seem to be less critical for behavioral performance improvement with age, possibly due to a sufficient level of alpha-beta ERD for good performance in young children.

Repetition Suppression for Familiar Visual Words Through Acceleration of Early Processing

The visual N1 (N170) component with occipito-temporal negativity and fronto-central positivity is sensitive to visual expertise for print. Slightly later, an N200 component with an increase after stimulus repetition was reported to be specific for Chinese, but found at centro-parietal electrodes against a mastoid reference. Given the unusual location, temporal proximity to the N1, and atypical repetition behavior, we aimed at clarifying the relation between the two components. We collected 128-channel EEG data from 18 native Chinese readers during a script decision experiment. Familiar Chinese one- and two-character words were presented among unfamiliar Korean control stimuli with half of the stimuli immediately repeated. Stimulus repetition led to a focal increase in the N1 onset and to a wide-spread decrease in the N1 offset, especially for familiar Chinese and also prominently near the mastoids. A TANOVA analysis corroborated robust repetition effects in the N1 offset across ERP maps with a modulation by script familiarity around 300 ms. Microstate analyses revealed a shorter N1 microstate duration after repetitions, especially for Chinese. The results demonstrate that the previously reported centro-parietal N200 effects after repetitions reflect changes during the N1 offset at occipito-temporal electrodes including the mastoids. Although larger for Chinese, repetition effects could also be found for two-character Korean words, suggesting that they are not specific for Chinese. While the decrease of the N1 offset after repetition is in agreement with a repetition suppression effect, the microstate findings suggest that at least part of the facilitation is due to accelerated processing after repetition.

Binding of cortical functional modules by synchronous high frequency oscillations

Whether high-frequency phase-locked oscillations facilitate integration ('binding') of information across widespread cortical areas is controversial. Here we show with intracranial EEG that cortico-cortical co-ripples (~100ms long ~90Hz oscillations) increase during reading and semantic decisions, at the times and co-locations when and where binding should occur. Fusiform wordform areas co-ripple with virtually all language areas, maximally from 200-400ms post-word-onset. Semantically-specified target words evoke strong co-rippling between wordform, semantic, executive and response areas from 400-800ms, with increased co-rippling between semantic, executive and response areas prior to correct responses. Co-ripples were phase-locked at zero-lag over long distances (>12cm), especially when many areas were co-rippling. General co-activation, indexed by non-oscillatory high gamma, was mainly confined to early latencies in fusiform and earlier visual areas, preceding co-ripples. These findings suggest that widespread synchronous co-ripples may assist the integration of multiple cortical areas for sustained periods during cognition.

Functional Resilience of the Neural Visual Recognition System Post-Pediatric Occipitotemporal Resection

In the typically developing (TD) brain, neural representations for visual stimulus categories (e.g., faces, objects, and words) emerge in bilateral occipitotemporal cortex (OTC), albeit with weighted asymmetry; in parallel, recognition behavior continues to be refined. A fundamental question is whether two hemispheres are necessary or redundant for the emergence of neural representations and recognition behavior typically distributed across both hemispheres. The rare population of patients undergoing unilateral OTC resection in childhood offers a unique opportunity to evaluate whether neural computations for visual stimulus individuation suffice for recognition with only a single developing OTC. Here, using functional magnetic resonance imaging, we mapped category selectivity (CS) and neural representations for individual stimulus exemplars using repetition suppression (RS) in the non-resected hemisphere of pediatric OTC resection patients (n = 9) and control patients with resection outside of OTC (n = 12), as well as in both hemispheres of TD controls (n = 21). There were no univariate group differences in the magnitude of CS or RS or any multivariate differences (per representational similarity analysis) in neural activation to faces, objects, or words across groups. Notwithstanding their comparable neural profiles, accuracy of OTC resection patients on face and object recognition, but not word recognition, was statistically inferior to that of controls. The comparable neural signature of the OTC resection patients' preserved hemisphere and the other two groups highlights the resilience of the system following damage to the contralateral homologue. Critically, however, a single OTC does not suffice for normal behavior, and, thereby, implicates the necessity for two hemispheres.

Expectation Modulates Repetition Suppression at Late But Not Early Stages during Visual Word Recognition: Evidence from Event-related Potentials

Visual word recognition is commonly rapid and efficient, incorporating top-down predictive processing mechanisms. Neuroimaging studies with face stimuli suggest that repetition suppression (RS) reflects predictive processing at the neural level, as this effect is larger when repetitions are more frequent, that is, more expected. It remains unclear, however, at the temporal level whether and how RS and its modulation by expectation occur in visual word recognition. To address this gap, the present study aimed to investigate the presence and time course of these effects during visual word recognition using EEG. Thirty-six native Cantonese speakers were presented with pairs of Chinese written words and performed a nonlinguistic oddball task. The second word of a pair was either a repetition of the first or a different word (alternation). In repetition blocks, 75% of trials were repetitions and 25% were alternations, whereas the reverse was true in alternation blocks. Topographic analysis of variance of EEG at each time point showed robust RS effects in three time windows (141-227 msec, 242-445 msec, and 467-513 msec) reflecting facilitation of visual word recognition. Importantly, the modulation of RS by expectation was observed at the late rather than early intervals (334-387 msec, 465-550 msec, and 559-632 msec) and more than 100 msec after the first RS effects. In the predictive coding view of RS, only late repetition effects are modulated by expectation, whereas early RS effects may be mediated by lower-level predictions. Taken together, our findings provide the first EEG evidence revealing distinct temporal dynamics of RS effects and repetition probability on RS effects in visual processing of Chinese words.

Repetition Suppression Reveals Cue-Specific Spatial Representations for Landmarks and Self-Motion Cues in the Human Retrosplenial Cortex

The efficient use of various spatial cues within a setting is crucial for successful navigation. Two fundamental forms of spatial navigation, landmark-based and self-motion-based, engage distinct cognitive mechanisms. The question of whether these modes invoke shared or separate spatial representations in the brain remains unresolved. While nonhuman animal studies have yielded inconsistent results, human investigation is limited. In our previous work (Chen et al., 2019), we introduced a novel spatial navigation paradigm utilizing ultra-high field fMRI to explore neural coding of positional information. We found that different entorhinal subregions in the right hemisphere encode positional information for landmarks and self-motion cues. The present study tested the generalizability of our previous finding with a modified navigation paradigm. Although we did not replicate our previous finding in the entorhinal cortex, we identified adaptation-based allocentric positional codes for both cue types in the retrosplenial cortex (RSC), which were not confounded by the path to the spatial location. Crucially, the multi-voxel patterns of these spatial codes differed between the cue types, suggesting cue-specific positional coding. The parahippocampal cortex exhibited positional coding for self-motion cues, which was not dissociable from path length. Finally, the brain regions involved in successful navigation differed from our previous study, indicating overall distinct neural mechanisms recruited in our two studies. Taken together, the current findings demonstrate cue-specific allocentric positional coding in the human RSC in the same navigation task for the first time and that spatial representations in the brain are contingent on specific experimental conditions.

Temporally organized representations of reward and risk in the human brain

The value and uncertainty associated with choice alternatives constitute critical features relevant for decisions. However, the manner in which reward and risk representations are temporally organized in the brain remains elusive. Here we leverage the spatiotemporal precision of intracranial electroencephalography, along with a simple card game designed to elicit the unfolding computation of a set of reward and risk variables, to uncover this temporal organization. Reward outcome representations across wide-spread regions follow a sequential order along the anteroposterior axis of the brain. In contrast, expected value can be decoded from multiple regions at the same time, and error signals in both reward and risk domains reflect a mixture of sequential and parallel encoding. We further highlight the role of the anterior insula in generalizing between reward prediction error and risk prediction error codes. Together our results emphasize the importance of neural dynamics for understanding value-based decisions under uncertainty.

Habituation to pain: self-report, electroencephalography, and functional magnetic resonance imaging in healthy individuals. A scoping review and future recommendations

ABSTRACT

Habituation to pain is a fundamental learning process and important adaption. Yet, a comprehensive review of the current state of the field is lacking. Through a systematic search, 63 studies were included. Results address habituation to pain in healthy individuals based on self-report, electroencephalography, or functional magnetic resonance imaging. Our findings indicate a large variety in methods, experimental settings, and contexts, making habituation a ubiquitous phenomenon. Habituation to pain based on self-report studies shows a large influence of expectations, as well as the presence of individual differences. Furthermore, widespread neural effects, with sometimes opposing effects in self-report measures, are noted. Electroencephalography studies showed habituation of the N2-P2 amplitude, whereas functional magnetic resonance imaging studies showed decreasing activity during painful repeated stimulation in several identified brain areas (cingulate cortex and somatosensory cortices). Important considerations for the use of terminology, methodology, statistics, and individual differences are discussed. This review will aid our understanding of habituation to pain in healthy individuals and may lead the way to improving methods and designs for personalized treatment approaches in chronic pain patients.

Parallel cognitive maps for multiple knowledge structures in the hippocampal formation

The hippocampal-entorhinal system uses cognitive maps to represent spatial knowledge and other types of relational information. However, objects can often be characterized by different types of relations simultaneously. How does the hippocampal formation handle the embedding of stimuli in multiple relational structures that differ vastly in their mode and timescale of acquisition? Does the hippocampal formation integrate different stimulus dimensions into one conjunctive map or is each dimension represented in a parallel map? Here, we reanalyzed human functional magnetic resonance imaging data from Garvert et al. (2017) that had previously revealed a map in the hippocampal formation coding for a newly learnt transition structure. Using functional magnetic resonance imaging adaptation analysis, we found that the degree of representational similarity in the bilateral hippocampus also decreased as a function of the semantic distance between presented objects. Importantly, while both map-like structures localized to the hippocampal formation, the semantic map was located in more posterior regions of the hippocampal formation than the transition structure and thus anatomically distinct. This finding supports the idea that the hippocampal-entorhinal system forms parallel cognitive maps that reflect the embedding of objects in diverse relational structures.

Adaptive adjustment after conflict with group opinion: evidence from neural electrophysiology

Individuals inherently seek social consensus when making decisions or judgments. Previous studies have consistently indicated that dissenting group opinions are perceived as social conflict that demands attitude adjustment. However, the neurocognitive processes of attitude adjustment are unclear. In this electrophysiological study, participants were recruited to perform a face attractiveness judgment task. After forming their own judgment of a face, participants were informed of a purported group judgment (either consistent or inconsistent with their judgment), and then, critically, the same face was presented again. The neural responses to the second presented faces were measured. The second presented faces evoked a larger late positive potential after conflict with group opinions than those that did not conflict, suggesting that more motivated attention was allocated to stimulus. Moreover, faces elicited greater midfrontal theta (4-7 Hz) power after conflict with group opinions than after consistency with group opinions, suggesting that cognitive control was initiated to support attitude adjustment. Furthermore, the mixed-effects model revealed that single-trial theta power predicted behavioral change in the Conflict condition, but not in the No-Conflict condition. These findings provide novel insights into the neurocognitive processes underlying attitude adjustment, which is crucial to behavioral change during conformity.

Generative replay underlies compositional inference in the hippocampal-prefrontal circuit

Human reasoning depends on reusing pieces of information by putting them together in new ways. However, very little is known about how compositional computation is implemented in the brain. Here, we ask participants to solve a series of problems that each require constructing a whole from a set of elements. With fMRI, we find that representations of novel constructed objects in the frontal cortex and hippocampus are relational and compositional. With MEG, we find that replay assembles elements into compounds, with each replay sequence constituting a hypothesis about a possible configuration of elements. The content of sequences evolves as participants solve each puzzle, progressing from predictable to uncertain elements and gradually converging on the correct configuration. Together, these results suggest a computational bridge between apparently distinct functions of hippocampal-prefrontal circuitry and a role for generative replay in compositional inference and hypothesis testing.

No Evidence for Cross-Modal fMRI Adaptation in Macaque Parieto-Premotor Mirror Neuron Regions

To probe the presence of mirror neurons in the human brain, cross-modal fMRI adaptation has been suggested as a suitable technique. The rationale behind this suggestion is that this technique allows making more accurate inferences about neural response properties underlying fMRI voxel activations, beyond merely showing shared voxels that are active during both action observation and execution. However, the validity of using cross-modal fMRI adaptation to demonstrate the presence of mirror neurons in parietal and premotor brain regions has been questioned given the inconsistent and weak results obtained in human studies. A better understanding of cross-modal fMRI adaptation effects in the macaque brain is required as the rationale for using this approach is based on several assumptions related to macaque mirror neuron response properties that still need validation. Here, we conducted a cross-modal fMRI adaptation study in macaque monkeys, using the same action execution and action observation tasks that successfully yielded mirror neuron region cross-modal action decoding in a previous monkey MVPA study. We scanned two male rhesus monkeys while they first executed a sequence of either reach-and-grasp or reach-and-touch hand actions and then observed a video of a human actor performing these motor acts. Both whole-brain and region-of-interest analyses failed to demonstrate cross-modal fMRI adaptation effects in parietal and premotor mirror neuron regions. Our results, in line with previous findings in non-human primates, show that cross-modal motor-to-visual fMRI adaptation is not easily detected in monkey brain regions known to house mirror neurons. Thus, our results advocate caution in using cross-modal fMRI adaptation as a method to infer whether mirror neurons can be found in the primate brain.

A functional account of stimulation-based aerobic glycolysis and its role in interpreting BOLD signal intensity increases in neuroimaging experiments

In aerobic glycolysis, oxygen is abundant, and yet cells metabolize glucose without using it, decreasing their ATP per glucose yield by 15-fold. During task-based stimulation, aerobic glycolysis occurs in localized brain regions, presenting a puzzle: why produce ATP inefficiently when, all else being equal, evolution should favor the efficient use of metabolic resources? The answer is that all else is not equal. We propose that a tradeoff exists between efficient ATP production and the efficiency with which ATP is spent to transmit information. Aerobic glycolysis, despite yielding little ATP per glucose, may support neuronal signaling in thin (< 0.5 µm), information-efficient axons. We call this the efficiency tradeoff hypothesis. This tradeoff has potential implications for interpretations of task-related BOLD "activation" observed in fMRI. We hypothesize that BOLD "activation" may index local increases in aerobic glycolysis, which support signaling in thin axons carrying "bottom-up" information, or "prediction error"-i.e., the BIAPEM (BOLD increases approximate prediction error metabolism) hypothesis. Finally, we explore implications of our hypotheses for human brain evolution, social behavior, and mental disorders.

Visual Representations: Insights from Neural Decoding

Patterns of brain activity contain meaningful information about the perceived world. Recent decades have welcomed a new era in neural analyses, with computational techniques from machine learning applied to neural data to decode information represented in the brain. In this article, we review how decoding approaches have advanced our understanding of visual representations and discuss efforts to characterize both the complexity and the behavioral relevance of these representations. We outline the current consensus regarding the spatiotemporal structure of visual representations and review recent findings that suggest that visual representations are at once robust to perturbations, yet sensitive to different mental states. Beyond representations of the physical world, recent decoding work has shone a light on how the brain instantiates internally generated states, for example, during imagery and prediction. Going forward, decoding has remarkable potential to assess the functional relevance of visual representations for human behavior, reveal how representations change across development and during aging, and uncover their presentation in various mental disorders.

Art Value Creation and Destruction

I present a theory of creative and destructive value state referring to abstract art. Value is a probabilistic state held as a mixture of its expectation and information forces that coexist in a give-and-take relationship. Expectations are driven by the disclosure of novel information about the value state of various events of desire. Each bit of accumulated information contributes to the improvement of perception up to a threshold level, beyond which begin conscious states. The desire to disclose a value state triggers a triadic system of evaluation which uses concepts, observables and approaches. While the triadic valuation mechanisms can be used to assess various commodities, the scope of this work is limited to the case of artworks, in particular abstract paintings. I assume that art value is basically mediated by the interplay between these value state mechanisms of creation and destruction. Expectations in artwork develop attraction by challenging its contemplator to evaluate (predict) its meaning. Once the relevant information, corresponding to its creative expectations, is acquired (and conditioned), emotional states of indifference, disinterest and desensitization develop.

Representations in human primary visual cortex drift over time

Primary sensory regions are believed to instantiate stable neural representations, yet a number of recent rodent studies suggest instead that representations drift over time. To test whether sensory representations are stable in human visual cortex, we analyzed a large longitudinal dataset of fMRI responses to images of natural scenes. We fit the fMRI responses using an image-computable encoding model and tested how well the model generalized across sessions. We found systematic changes in model fits that exhibited cumulative drift over many months. Convergent analyses pinpoint changes in neural responsivity as the source of the drift, while population-level representational dissimilarities between visual stimuli were unchanged. These observations suggest that downstream cortical areas may read-out a stable representation, even as representations within V1 exhibit drift.

Interoceptive Awareness of the Breath Preserves Attention and Language Networks amidst Widespread Cortical Deactivation: A Within-Participant Neuroimaging Study

Interoception, the representation of the body's internal state, serves as a foundation for emotion, motivation, and wellbeing. Yet despite its centrality in human experience, the neural mechanisms of interoceptive attention are poorly understood. The Interoceptive/Exteroceptive Attention Task (IEAT) is a novel neuroimaging paradigm that compares behavioral tracking of the respiratory cycle (Active Interoception) to tracking of a visual stimulus (Active Exteroception). Twenty-two healthy participants completed the IEAT during two separate scanning sessions (N = 44) as part of a randomized control trial of mindful awareness in body-oriented therapy (MABT). Compared with Active Exteroception, Active Interoception deactivated somatomotor and prefrontal regions. Greater self-reported interoceptive sensibility (MAIA scale) predicted sparing from deactivation within the anterior cingulate cortex (ACC) and left-lateralized language regions. The right insula, typically described as a primary interoceptive cortex, was only specifically implicated by its deactivation during an exogenously paced respiration condition (Active Matching) relative to self-paced Active Interoception. Psychophysiological interaction (PPI) analysis characterized Active Interoception as promoting greater ACC connectivity with lateral prefrontal and parietal regions commonly referred to as the dorsal attention network (DAN). In contrast to evidence relating accurate detection of liminal interoceptive signals such as the heartbeat to anterior insula activity, interoceptive attention toward salient signals such as the respiratory cycle may involve reduced cortical activity but greater ACC-DAN connectivity, with greater sensibility linked to reduced deactivation within the ACC and language-processing regions.

Task state representations in vmPFC mediate relevant and irrelevant value signals and their behavioral influence

The ventromedial prefrontal-cortex (vmPFC) is known to contain expected value signals that inform our choices. But expected values even for the same stimulus can differ by task. In this study, we asked how the brain flexibly switches between such value representations in a task-dependent manner. Thirty-five participants alternated between tasks in which either stimulus color or motion predicted rewards. We show that multivariate vmPFC signals contain a rich representation that includes the current task state or context (motion/color), the associated expected value, and crucially, the irrelevant value of the alternative context. We also find that irrelevant value representations in vmPFC compete with relevant value signals, interact with task-state representations and relate to behavioral signs of value competition. Our results shed light on vmPFC's role in decision making, bridging between its role in mapping observations onto the task states of a mental map, and computing expected values for multiple states.

Dissociative effects of age on neural differentiation at the category and item level

Increasing age is associated with age-related neural dedifferentiation, a reduction in the selectivity of neural representations which has been proposed to contribute to cognitive decline in older age. Recent findings indicate that when operationalized in terms of selectivity for different perceptual categories, age-related neural dedifferentiation, and the apparent age-invariant association of neural selectivity with cognitive performance, are largely restricted to the cortical regions typically recruited during scene processing. It is currently unknown whether this category-level dissociation extends to metrics of neural selectivity defined at the level of individual stimulus items. Here, we examined neural selectivity at the category and item levels using multivoxel pattern similarity analysis (PSA) of fMRI data. Healthy young and older male and female adults viewed images of objects and scenes. Some items were presented singly, while others were either repeated or followed by a 'similar lure'. Consistent with recent findings, category-level PSA revealed robustly lower differentiation in older than younger adults in scene-selective, but not object-selective, cortical regions. By contrast, at the item level, robust age-related declines in neural differentiation were evident for both stimulus categories. Moreover, we identified an age-invariant association between category-level scene-selectivity in the parahippocampal place area and subsequent memory performance, but no such association was evident for item-level metrics. Lastly, category and item-level neural metrics were uncorrelated. Thus, the present findings suggest that age-related category- and item-level dedifferentiation depend on distinct neural mechanisms.

Temporally organized representations of reward and risk in the human brain

The value and uncertainty associated with choice alternatives constitute critical features along which decisions are made. While the neural substrates supporting reward and risk processing have been investigated, the temporal organization by which these computations are encoded remains elusive. Here we leverage the high spatiotemporal precision of intracranial electroencephalography (iEEG) to uncover how representations of decision-related computations unfold in time. We present evidence of locally distributed representations of reward and risk variables that are temporally organized across multiple regions of interest. Reward outcome representations across wide-spread regions follow a temporally cascading order along the anteroposterior axis of the brain. In contrast, expected value can be decoded from multiple regions at the same time, and error signals in both reward and risk domains reflect a mixture of sequential and parallel encoding. We highlight the role of the anterior insula in generalizing between reward prediction error (RePE) and risk prediction error (RiPE), within which the encoding of RePE in the distributed iEEG signal predicts RiPE. Together our results emphasize the utility of uncovering temporal dynamics in the human brain for understanding how computational processes critical for value-based decisions under uncertainty unfold.

Grasp-specific high-frequency broadband mirror neuron activity during reach-and-grasp movements in humans

Broadly congruent mirror neurons, responding to any grasp movement, and strictly congruent mirror neurons, responding only to specific grasp movements, have been reported in single-cell studies with primates. Delineating grasp properties in humans is essential to understand the human mirror neuron system with implications for behavior and social cognition. We analyzed electrocorticography data from a natural reach-and-grasp movement observation and delayed imitation task with 3 different natural grasp types of everyday objects. We focused on the classification of grasp types from high-frequency broadband mirror activation patterns found in classic mirror system areas, including sensorimotor, supplementary motor, inferior frontal, and parietal cortices. Classification of grasp types was successful during movement observation and execution intervals but not during movement retention. Our grasp type classification from combined and single mirror electrodes provides evidence for grasp-congruent activity in the human mirror neuron system potentially arising from strictly congruent mirror neurons.

Single-neuron mechanisms of neural adaptation in the human temporal lobe

A central function of the human brain is to adapt to new situations based on past experience. Adaptation is reflected behaviorally by shorter reaction times to repeating or similar stimuli, and neurophysiologically by reduced neural activity in bulk-tissue measurements with fMRI or EEG. Several potential single-neuron mechanisms have been hypothesized to cause this reduction of activity at the macroscopic level. We here explore these mechanisms using an adaptation paradigm with visual stimuli bearing abstract semantic similarity. We recorded intracranial EEG (iEEG) simultaneously with spiking activity of single neurons in the medial temporal lobes of 25 neurosurgical patients. Recording from 4917 single neurons, we demonstrate that reduced event-related potentials in the macroscopic iEEG signal are associated with a sharpening of single-neuron tuning curves in the amygdala, but with an overall reduction of single-neuron activity in the hippocampus, entorhinal cortex, and parahippocampal cortex, consistent with fatiguing in these areas.

Hippocampal spatio-predictive cognitive maps adaptively guide reward generalization

The brain forms cognitive maps of relational knowledge-an organizing principle thought to underlie our ability to generalize and make inferences. However, how can a relevant map be selected in situations where a stimulus is embedded in multiple relational structures? Here, we find that both spatial and predictive cognitive maps influence generalization in a choice task, where spatial location determines reward magnitude. Mirroring behavior, the hippocampus not only builds a map of spatial relationships but also encodes the experienced transition structure. As the task progresses, participants' choices become more influenced by spatial relationships, reflected in a strengthening of the spatial map and a weakening of the predictive map. This change is driven by orbitofrontal cortex, which represents the degree to which an outcome is consistent with the spatial rather than the predictive map and updates hippocampal representations accordingly. Taken together, this demonstrates how hippocampal cognitive maps are used and updated flexibly for inference.

Repetition enhances the effects of activated long-term memory

Recent research indicates that visual long-term memory (vLTM) representations directly interface with perception and guide attention. This may be accomplished through a state known as activated LTM, however, little is known about the nature of activated LTM. Is it possible to enhance the attentional effects of these activated representations? And furthermore, is activated LTM discrete (i.e., a representation is either active or not active, but only active representations interact with perception) or continuous (i.e., there are different levels within the active state that all interact with perception)? To answer these questions, in the present study, we measured intrusion effects during a modified Sternberg task. Participants saw two lists of three complex visual objects, were cued that only one list was relevant for the current trial (the other list was, thus, irrelevant), and then their memory for the cued list was probed. Critically, half of the trials contained repeat objects (shown 10 times each), and half of the trials contained non-repeat objects (shown only once each). Results indicated that repetition enhanced activated LTM, as the intrusion effect (i.e., longer reaction times to irrelevant list objects than novel objects) was larger for repeat trials compared with non-repeat trials. These initial findings provide preliminary support that LTM activation is continuous, as the intrusion effect was not the same size for repeat and non-repeat trials. We conclude that researchers should repeat stimuli to increase the size of their effects and enhance how LTM representations interact with perception.

From scanner to court: A neuroscientifically informed "reasonable person" test of trademark infringement

Many legal decisions center on the thoughts or perceptions of some idealized group of individuals, referred to variously as the "average person," "the typical consumer," or the "reasonable person." Substantial concerns exist, however, regarding the subjectivity and vulnerability to biases inherent in conventional means of assessing such responses, particularly the use of self-report evidence. Here, we addressed these concerns by complementing self-report evidence with neural data to inform the mental representations in question. Using an example from intellectual property law, we demonstrate that it is possible to construct a parsimonious neural index of visual similarity that can inform the reasonable person test of trademark infringement. Moreover, when aggregated across multiple participants, this index was able to detect experimenter-induced biases in self-report surveys in a sensitive and replicable fashion. Together, these findings potentially broaden the possibilities for neuroscientific data to inform legal decision-making across a range of settings.

Neural fatigue by passive induction: repeated stimulus exposure results in cognitive fatigue and altered representations in task-relevant networks

Cognitive fatigue is defined by a reduced capacity to perform mental tasks. Despite its pervasiveness, the underlying neural mechanisms remain elusive. Specifically, it is unclear whether prolonged effort affects performance through alterations in over-worked task-relevant neuronal assemblies. Our paradigm based on repeated passive visual stimulation discerns fatigue effects from the influence of motivation, skill and boredom. We induced performance loss and observed parallel alterations in the neural blueprint of the task, by mirroring behavioral performance with multivariate neuroimaging techniques (MVPA) that afford a subject-specific approach. Crucially, functional areas that responded the most to repeated stimulation were also the most affected. Finally, univariate analysis revealed clusters displaying significant disruption within the extrastriate visual cortex. In sum, here we show that repeated stimulation impacts the implicated brain areas' activity and causes tangible behavioral repercussions, providing evidence that cognitive fatigue can result from local, functional, disruptions in the neural signal induced by protracted recruitment.

Entorhinal grid-like codes and time-locked network dynamics track others navigating through space

Navigating through crowded, dynamically changing environments requires the ability to keep track of other individuals. Grid cells in the entorhinal cortex are a central component of self-related navigation but whether they also track others' movement is unclear. Here, we propose that entorhinal grid-like codes make an essential contribution to socio-spatial navigation. Sixty human participants underwent functional magnetic resonance imaging (fMRI) while observing and re-tracing different paths of a demonstrator that navigated a virtual reality environment. Results revealed that grid-like codes in the entorhinal cortex tracked the other individual navigating through space. The activity of grid-like codes was time-locked to increases in co-activation and entorhinal-cortical connectivity that included the striatum, the hippocampus, parahippocampal and right posterior parietal cortices. Surprisingly, the grid-related effects during observation were stronger the worse participants performed when subsequently re-tracing the demonstrator's paths. Our findings suggests that network dynamics time-locked to entorhinal grid-cell-related activity might serve to distribute information about the location of others throughout the brain.

Face processing in the infant brain after pandemic lockdown

The role of visual experience in the development of face processing has long been debated. We present a new angle on this question through a serendipitous study that cannot easily be repeated. Infants viewed short blocks of faces during fMRI in a repetition suppression task. The same identity was presented multiple times in half of the blocks (repeat condition) and different identities were presented once each in the other half (novel condition). In adults, the fusiform face area (FFA) tends to show greater neural activity for novel versus repeat blocks in such designs, suggesting that it can distinguish same versus different face identities. As part of an ongoing study, we collected data before the COVID-19 pandemic and after an initial local lockdown was lifted. The resulting sample of 12 infants (9-24 months) divided equally into pre- and post-lockdown groups with matching ages and data quantity/quality. The groups had strikingly different FFA responses: pre-lockdown infants showed repetition suppression (novel > repeat), whereas post-lockdown infants showed the opposite (repeat > novel), often referred to as repetition enhancement. These findings provide speculative evidence that altered visual experience during the lockdown, or other correlated environmental changes, may have affected face processing in the infant brain.

Neurocomputational mechanisms of confidence in self and others

Computing confidence in one’s own and others’ decisions is critical for social success. While there has been substantial progress in our understanding of confidence estimates about oneself, little is known about how people form confidence estimates about others. Here, we address this question by asking participants undergoing fMRI to place bets on perceptual decisions made by themselves or one of three other players of varying ability. We show that participants compute confidence in another player’s decisions by combining distinct estimates of player ability and decision difficulty – allowing them to predict that a good player may get a difficult decision wrong and that a bad player may get an easy decision right. We find that this computation is associated with an interaction between brain systems implicated in decision-making (LIP) and theory of mind (TPJ and dmPFC). These results reveal an interplay between self- and other-related processes during a social confidence computation.

Representation of motion concepts in occipitotemporal cortex: fMRI activation, decoding and connectivity analyses

Embodied theories of semantic cognition predict that brain regions involved in motion perception are engaged when people comprehend motion concepts expressed in language. Left lateral occipitotemporal cortex (LOTC) is implicated in both motion perception and motion concept processing but prior studies have produced mixed findings on which parts of this region are engaged by motion language. We scanned participants performing semantic judgements about sentences describing motion events and static events. We performed univariate analyses, multivariate pattern analyses (MVPA) and psychophysiological interaction (PPI) analyses to investigate the effect of motion on activity and connectivity in different parts of LOTC. In multivariate analyses that decoded whether a sentence described motion or not, the middle and posterior parts of LOTC showed above-chance level performance, with performance exceeding that of other brain regions. Univariate ROI analyses found the middle part of LOTC was more active for motion events than static ones. Finally, PPI analyses found that when processing motion events, the middle and posterior parts of LOTC (overlapping with motion perception regions), increased their connectivity with cognitive control regions. Taken together, these results indicate that the more posterior parts of LOTC, including motion perception cortex, respond differently to motion vs. static events. These findings are consistent with embodiment accounts of semantic processing, and suggest that understanding verbal descriptions of motion engages areas of the occipitotemporal cortex involved in perceiving motion.

Brain Reactions to Opening and Closing the Eyes: Salivary Cortisol and Functional Connectivity

This study empirically assessed the strength and duration of short-term effects induced by brain reactions to closing/opening the eyes on a few well-known resting-state networks. We also examined the association between these reactions and subjects’ cortisol levels. A total of 55 young adults underwent 8-min resting-state fMRI (rs-fMRI) scans under 4-min eyes-closed and 4-min eyes-open conditions. Saliva samples were collected from 25 of the 55 subjects before and after the fMRI sessions and assayed for cortisol levels. Our empirical results indicate that when the subjects were relaxed with their eyes closed, the effect of opening the eyes on conventional resting-state networks (e.g., default-mode, frontal-parietal, and saliency networks) lasted for roughly 60-s, during which we observed a short-term increase in activity in rs-fMRI time courses. Moreover, brain reactions to opening the eyes had a pronounced effect on time courses in the temporo-parietal lobes and limbic structures, both of which presented a prolonged decrease in activity. After controlling for demographic factors, we observed a significantly positive correlation between pre-scan cortisol levels and connectivity in the limbic structures under both conditions. Under the eyes-closed condition, the temporo-parietal lobes presented significant connectivity to limbic structures and a significantly positive correlation with pre-scan cortisol levels. Future research on rs-fMRI could consider the eyes-closed condition when probing resting-state connectivity and its neuroendocrine correlates, such as cortisol levels. It also appears that abrupt instructions to open the eyes while the subject is resting quietly with eyes closed could be used to probe brain reactivity to aversive stimuli in the ventral hippocampus and other limbic structures.

Entropy Could Quantify Brain Activation Induced by Mechanical Impedance-Restrained Active Arm Motion: A Functional NIRS Study

Brain activation has been used to understand brain-level events associated with cognitive tasks or physical tasks. As a quantitative measure for brain activation, we propose entropy in place of signal amplitude and beta value, which are widely used, but sometimes criticized for their limitations and shortcomings as such measures. To investigate the relevance of our proposition, we provided 22 subjects with physical stimuli through elbow extension-flexion motions by using our exoskeleton robot, measured brain activation in terms of entropy, signal amplitude, and beta value; and compared entropy with the other two. The results show that entropy is superior, in that its change appeared in limited, well established, motor areas, while signal amplitude and beta value changes appeared in a widespread fashion, contradicting the modularity theory. Entropy can predict increase in brain activation with task duration, while the other two cannot. When stimuli shifted from the rest state to the task state, entropy exhibited a similar increase as the other two did. Although entropy showed only a part of the phenomenon induced by task strength, it showed superiority by showing a decrease in brain activation that the other two did not show. Moreover, entropy was capable of identifying the physiologically important location.

Neural Coding of Cognitive Control: The Representational Similarity Analysis Approach

Cognitive control relies on distributed and potentially high-dimensional frontoparietal task representations. Yet, the classical cognitive neuroscience approach in this domain has focused on aggregating and contrasting neural measures - either via univariate or multivariate methods - along highly abstracted, 1D factors (e.g., Stroop congruency). Here, we present representational similarity analysis (RSA) as a complementary approach that can powerfully inform representational components of cognitive control theories. We review several exemplary uses of RSA in this regard. We further show that most classical paradigms, given their factorial structure, can be optimized for RSA with minimal modification. Our aim is to illustrate how RSA can be incorporated into cognitive control investigations to shed new light on old questions.

Feeling left out or just surprised? Neural correlates of social exclusion and overinclusion in adolescence

Social belonging is an important human drive that influences mood and behavior. Neural responses to social exclusion are well-characterized, but the specificity of these responses to processing rejection-related affective distress is unknown. The present study compares neural responses to exclusion and overinclusion, a condition that similarly violates fairness expectations but does not involve rejection, with a focus on implications for models of dorsal anterior cingulate cortex (dACC) and anterior insula (AI) function. In an fMRI adaptation of the Cyberball paradigm with adolescents aged 11.1-17.7 years (N = 69), we employed parametric modulators to examine scaling of neural signal with cumulative exclusion and inclusion events, an approach that overcomes arbitrary definitions of condition onsets/offsets imposed on fluid, continuous gameplay. We identified positive scaling of dACC and posterior insula response with cumulative exclusion events, but these same regions exhibited trending signal decreases with cumulative inclusion events. Furthermore, areas within the dACC and insula also responded to context incongruency (throws to the participant in the exclusion run; throws between computer players in the overinclusion run). These findings caution against interpretations that responses in these regions uniquely reflect the affective distress of exclusion within social interaction paradigms. We further identified that the left ventrolateral PFC, rostromedial PFC, and left intraparietal sulcus responded similarly to cumulative exclusion and inclusion. These findings shed light on which neural regions exhibit patterns of differential sensitivity to exclusion or overinclusion, as well as those that are more broadly engaged by both types of social interaction.

Long term fMRI adaptation depends on adapter response in face-selective cortex

Repetition suppression (RS) reflects a neural attenuation during repeated stimulation. We used fMRI and the subsequent memory paradigm to test the predictive coding hypothesis for RS during visual memory processing by investigating the interaction between RS and differences due to memory in category-selective cortex (FFA, pSTS, PPA, and RSC). Fifty-six participants encoded face and house stimuli twice, followed by an immediate and delayed (48 h) recognition memory assessment. Linear Mixed Model analyses with repetition, subsequent recognition performance, and their interaction as fixed effects revealed that absolute RS during encoding interacts with probability of future remembrance in face-selective cortex. This effect was not observed for relative RS, i.e. when controlled for adapter-response. The findings also reveal an association between adapter response and RS, both for short and long term (48h) intervals, after controlling for the mathematical dependence between both measures. These combined findings are challenging for predictive coding models of visual memory and are more compatible with adapter-related and familiarity accounts.

Temporally delayed linear modelling (TDLM) measures replay in both animals and humans

There are rich structures in off-task neural activity which are hypothesized to reflect fundamental computations across a broad spectrum of cognitive functions. Here, we develop an analysis toolkit - temporal delayed linear modelling (TDLM) - for analysing such activity. TDLM is a domain-general method for finding neural sequences that respect a pre-specified transition graph. It combines nonlinear classification and linear temporal modelling to test for statistical regularities in sequences of task-related reactivations. TDLM is developed on the non-invasive neuroimaging data and is designed to take care of confounds and maximize sequence detection ability. Notably, as a linear framework, TDLM can be easily extended, without loss of generality, to capture rodent replay in electrophysiology, including in continuous spaces, as well as addressing second-order inference questions, for example, its temporal and spatial varying pattern. We hope TDLM will advance a deeper understanding of neural computation and promote a richer convergence between animal and human neuroscience.

Repetition Suppression in Visual and Auditory Modalities Affects the Sound-Induced Flash Illusion

Sound-induced flash illusion (SiFI) refers to the illusion that the number of visual flashes is equal to the number of auditory sounds when the visual flashes are accompanied by an unequal number of auditory sounds presented within 100 ms. The effect of repetition suppression (RS), an adaptive effect caused by stimulus repetition, upon the SiFI has not been investigated. Based on the classic SiFI paradigm, the present study investigated whether RS would affect the SiFI differently by adding preceding stimuli in visual and auditory modalities prior to the appearance of audiovisual stimuli. The results showed the auditory RS effect on the SiFI varied with the number of preceding auditory stimuli. The hit rate was higher with two preceding auditory stimuli than one preceding auditory stimulus in fission illusion, but it did not affect the size of the fusion illusion. However, the visual RS had no effect on the size of the fission and fusion illusions. The present study suggested that RS could affect the SiFI, indicating that the RS effect in different modalities would differentially affect the magnitude of the SiFI. In the process of multisensory integration, the visual and auditory modalities had asymmetrical RS effects.

Neural evidence for recognition of naturalistic videos in monkey hippocampus

The role of the hippocampus in recognition memory has long been a source of debate. Tasks used to study recognition that typically require an explicit probe, where the participant must make a response to prove they remember, yield mixed results on hippocampal involvement. Here, we tasked monkeys to freely view naturalistic videos, and only tested their memory via looking times for two separate novel versus repeat video conditions on each trial. Notably, a large proportion (>30%) of hippocampal neurons differentiated these videos via changes in firing rates time-locked to the duration of their presentation on screen, and not during the delay period between them as would be expected for working memory. Many of these single neurons (>15%) contributed to both retrieval conditions, and differentiated novel from repeat videos across trials with trial-unique content, suggesting they detect familiarity. The majority of neurons contributing to the classifier showed an enhancement in firing rate on repeat compared with novel videos, a pattern which has not previously been shown in hippocampus. These results suggest the hippocampus contributes to recognition memory via familiarity during free-viewing.

Adapting non-invasive human recordings along multiple task-axes shows unfolding of spontaneous and over-trained choice

Choices rely on a transformation of sensory inputs into motor responses. Using invasive single neuron recordings, the evolution of a choice process has been tracked by projecting population neural responses into state spaces. Here, we develop an approach that allows us to recover similar trajectories on a millisecond timescale in non-invasive human recordings. We selectively suppress activity related to three task-axes, relevant and irrelevant sensory inputs and response direction, in magnetoencephalography data acquired during context-dependent choices. Recordings from premotor cortex show a progression from processing sensory input to processing the response. In contrast to previous macaque recordings, information related to choice-irrelevant features is represented more weakly than choice-relevant sensory information. To test whether this mechanistic difference between species is caused by extensive over-training common in non-human primate studies, we trained humans on >20,000 trials of the task. Choice-irrelevant features were still weaker than relevant features in premotor cortex after over-training.

Warmth is more influential than competence: an fMRI repetition suppression study

Previous neuroimaging studies have revealed neural representation of traits in the medial prefrontal cortex (mPFC), but related studies mainly investigated the neural representation of warmth or competence trait respectively. To identify the potential differences of trait codes of warmth and competence in the mPFC, we applied functional magnetic resonance imaging (fMRI) repetition suppression which is a rapid reduction of neuronal responses upon repeated presentation of the same implied trait. Participants read two successive trait-implying behavioral descriptions. In each trial, the critical target sentence implied either a warmth-related or competence-related trait was preceded by a prime sentence that implied trait from the other dimension of the 'Big Two' with a same or opposite valence, or no trait. The results revealed robust repetition suppression from prime to target in the mPFC only when the prime was a warmth-related trait, regardless of valence. Critically, the suppression effect was much stronger after being primed with a similar and opposite warmth trait compared with a trait-irrelevant prime. This suppression pattern was found nowhere else in the brain. The result seems to indicate that humans do not completely interpret and represent warmth and competence traits as independent dimensions and the warmth trait is more influential than Competence trait. The finding extends the understanding of the 'Big Two' theory of impression formation from the aspect of neural activity.

Stimulus valence, episodic memory, and the priming of brain activation profiles in borderline personality disorder

BACKGROUND

Borderline personality disorder (BPD) is characterized by instability in affective regulation that can result in a loss of cognitive control. Triggers may be neuronal responses to emotionally valenced context and/or stimuli. 'Neuronal priming' indexes the familiarity of stimuli, and may capture the obligatory effects of affective valence on the brain's processing system, and how such valence mediates responses to the repeated presentation of stimuli. We investigated the effects of affective valence of stimuli on neuronal priming (i.e. changes in activation to repeated presentation of stimuli), and if these effects distinguished BPD patients from controls.

METHODS

Forty BPD subjects and 25 control subjects (age range: 18-44) participated in an episodic memory task during fMRI. Stimuli were presented in alternating epochs of encoding (six images of positive, negative, and neutral valence) and recognition (six images for 'old' v. 'new' recognition). Analyses focused on inter-group differences in the change in activation to repeated stimuli (presented during Encoding and Recognition).

RESULTS

Relative to controls, BPD showed greater priming (generally greater decrease from encoding to recognition) for negatively valenced stimuli. Conversely, BPD showed less priming for positively valenced stimuli (generally greater increase from encoding to recognition).

CONCLUSION

Plausibly, the relative familiarity of negative valence to patients with BPD exerts an influence on obligatory responses to repeated stimuli leading to repetition priming of neuronal profiles. The specific effects of valence on memory and/or attention, and consequently on priming can inform the understanding of mechanisms of altered salience for affective stimuli in BPD.

Morpho-semantic analysis of ambiguous morphemes in Chinese compound word recognition: An fMRI study

The present fMRI study examined the neural basis of processing context-supported or -unsupported interpretations of ambiguous morphemes during Chinese compound word reading in a masked priming lexical decision task. Targets were Chinese bimorphemic words that contained ambiguous morphemes. Prime words contained the same ambiguous morphemes with either the same meanings (context-supported interpretation) or different ones (context-unsupported interpretation). Lexical-level semantic sharing and unrelated control conditions were also included. Compared to the unrelated control condition, the context-supported morphemic meaning was associated with increased activity in the left SFG and bilateral MTG, and this priming effect could be dissociated from that of the lexical-level semantic-related condition. In broader brain regions, including the left SFG, bilateral MTG, left STG, right IOG, and left precuneus, the context-unsupported meaning condition showed decreased activity compared with the unrelated control condition. These findings indicate that both the context-supported and -unsupported meanings evoke significant priming effects, however, they differ from each other with different brain basis, providing new insight into the neural substrates of ambiguous morpheme processing.

The dimensionality of neural representations for control

Cognitive control allows us to think and behave flexibly based on our context and goals. At the heart of theories of cognitive control is a control representation that enables the same input to produce different outputs contingent on contextual factors. In this review, we focus on an important property of the control representation's neural code: its representational dimensionality. Dimensionality of a neural representation balances a basic separability/generalizability trade-off in neural computation. We will discuss the implications of this trade-off for cognitive control. We will then briefly review current neuroscience findings regarding the dimensionality of control representations in the brain, particularly the prefrontal cortex. We conclude by highlighting open questions and crucial directions for future research.

Memory specificity is linked to repetition effects in event-related potentials across the lifespan

The specificity with which past experiences can be remembered varies across the lifespan, possibly due to differences in how precisely information is encoded. Memory formation can be investigated through repetition effects, the common finding that neural activity is altered when stimuli are repeated. However, whether differences in this indirect measure of memory formation relate to lifespan differences in memory specificity has not yet been established. In the present study, we examined repetition effects in event-related potentials and their relation to recognition. During incidental encoding, children (aged 7-9 years), young adults (18-30 years), and older adults (65-76 years) viewed repeated object images from different categories. During subsequent recognition, we distinguished memory for the specific items versus the general categories. We identified repetition suppression in all age groups, and repetition enhancement for adults. Furthermore, individual item recognition performance comprising lure discrimination was positively associated with the magnitude of the neural repetition effects, which did not differ between groups, indicating common neural mechanisms of memory formation. Our findings demonstrate that neural repetition effects reflect the formation of highly specific memory representations and highlight their significance as a neural indicator of individual differences in episodic memory encoding across the lifespan.

To be specific: The role of orbitofrontal cortex in signaling reward identity

The orbitofrontal cortex (OFC) plays a prominent role in signaling reward expectations. Two important features of rewards are their value (how good they are) and their specific identity (what they are). Whereas research on OFC has traditionally focused on reward value, recent findings point toward a pivotal role of reward identity in understanding OFC signaling and its contribution to behavior. Here, we review work in rodents, nonhuman primates, and humans on how the OFC represents expectations about the identity of rewards, and how these signals contribute to outcome-guided behavior. Moreover, we summarize recent findings suggesting that specific reward expectations in OFC are learned and updated by means of identity errors in the dopaminergic midbrain. We conclude by discussing how OFC encoding of specific rewards complements recent proposals that this region represents a cognitive map of relevant task states, which forms the basis for model-based behavior. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Quantum semantics of text perception

The paper presents quantum model of subjective text perception based on binary cognitive distinctions corresponding to words of natural language. The result of perception is quantum cognitive state represented by vector in the qubit Hilbert space. Complex-valued structure of the quantum state space extends the standard vector-based approach to semantics, allowing to account for subjective dimension of human perception in which the result is constrained, but not fully predetermined by input information. In the case of two distinctions, the perception model generates a two-qubit state, entanglement of which quantifies semantic connection between the corresponding words. This two-distinction perception case is realized in the algorithm for detection and measurement of semantic connectivity between pairs of words. The algorithm is experimentally tested with positive results. The developed approach to cognitive modeling unifies neurophysiological, linguistic, and psychological descriptions in a mathematical and conceptual structure of quantum theory, extending horizons of machine intelligence.