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A recent study by Wu, Podvalny, and colleagues investigated how ongoing spontaneous brain activity interacts with sensory input and shapes conscious perception. It reports diverse effects of prestimulus activity in several key networks, revealing new roles of the prefrontal cortex and the default mode network in perception and consciousness., Competing Interests: Declaration of interests The author declares no competing interests., (Copyright © 2024 The Author. Published by Elsevier Ltd.. All rights reserved.)

Inspired by the well-known Papez circuit theory and neuroscience knowledge of reinforcement learning, a double dueling deep Q network (DQN) is built incorporating the electroencephalogram (EEG) signals of the frontal lobe as prior information, which is named frontal lobe double dueling DQN (FLD3QN). The framework of FLD3QN is constructed in accord with the brain emotion mechanism which takes the frontal lobe and the thalamus as the core, in which the part of the Papez circuit is simulated by the bifrontal lobe residual convolution neural network (BiFRCNN). Moreover, a step penalty factor is designed to constrain the number of mistakes of the agent. The ablation studies results on the public EEG emotion dataset DEAP verified the important roles of the frontal lobe and the Papez circuit in modeling the procedure of learning rewards during the perception of emotions, with a great increase in the average accuracies by 25.24% and 23.31% in valence and arousal dimensions.

The embodied approach argues that interaction with the environment plays a crucial role in brain development and that the presence of sensory effects generated by movements is fundamental. The movement of the fetus is initially random. Then, the repeated execution of the movement creates a link between it and its sensory effects, allowing the selection of movements that produce expected sensations. During fetal life, the brain develops from a transitory fetal circuit to the permanent cortical circuit, which completes development after birth. Accordingly, this process must concern the interaction of the fetus with the intrauterine environment and of the newborn with the new aerial environment, which provides a new sensory stimulation, light. The goal of the present review is to provide suggestions for neuroscientific research capable of shedding light on brain development process by describing from a functional point of view the relationship between the motor and sensory abilities of fetuses and newborns and the increasing complexity of their interaction with objects in the womb and outside of it., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Previous functional magnetic resonance imaging (fMRI) studies have shown that brain responses to nociceptive pain, non-nociceptive somatosensory, visual, and auditory stimuli are extremely similar. Actually, perception of external sensory stimulation requires complex interactions among distributed cortical and subcortical brain regions. However, the interactions among these regions elicited by nociceptive pain remain unclear, which limits our understanding of mechanisms of pain from a brain network perspective. Task fMRI data were collected with a random sequence of intermixed stimuli of four sensory modalities in 80 healthy subjects. Whole-brain psychophysiological interaction analysis was performed to identify task-modulated functional connectivity (FC) patterns for each modality. Task-modulated FC strength and graph-theoretical-based network properties were compared among the four modalities. Lastly, we performed across-sensory-modality prediction analysis based on the whole-brain task-modulated FC patterns to confirm the specific relationship between brain patterns and sensory modalities. For each sensory modality, task-modulated FC patterns were distributed over widespread brain regions beyond those typically activated or deactivated during the stimulation. As compared with the other three sensory modalities, nociceptive stimulation exhibited significantly different patterns (more widespread and stronger FC within the cingulo-opercular network, between cingulo-opercular and sensorimotor networks, between cingulo-opercular and emotional networks, and between default mode and emotional networks) and global property (smaller modularity). Further, a cross-sensory-modality prediction analysis found that task-modulated FC patterns could predict sensory modality at the subject level successfully. Collectively, these results demonstrated that the whole-brain task-modulated FC is preferentially modulated by pain, thus providing new insights into the neural mechanisms of pain processing., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Innovative payment methods have been getting worldwide attention. Exploring the mechanisms behind consumers' purchase behaviors modulated by different payment methods was critical but challenging. In this paper, we proposed a 2 (payment methods: cash payment vs mobile payment) × 2 (price levels of products: high vs low) Event-Related Potentials (ERPs) experiment to study the difference of cash payment and mobile payment on consumers' purchase intention of products in different price level from a neuroscience perspective. Greater P200 amplitude was found in mobile payment condition, which meant that mobile payment captured more early attention resources than cash. Larger N270 amplitude was found in cash payment condition as the participants had to spend more cognitive resources and struggled more when using cash. Moreover, lower N270 amplitude was found in high-price product condition, which indicated that when there were limited cognitive resources, the affective process played a dominating role. Specifically, buying the high-price products with mobile payment, the consumers would experience the pleasure of consumption more rather than the pain of paying. The study offers insights on the cognitive process of consumers when they pay with different methods., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Age-related changes in the brain are associated with a decline in functional flexibility. Intrinsic functional flexibility is evident in the brain's dynamic ability to switch between alternative spatiotemporal states during resting state. However, the relationship between brain connectivity states, associated psychological functions during resting state, and the changes in normal aging remain poorly understood. In this study, we analyzed resting-state functional magnetic resonance imaging (rsfMRI) data from the Human Connectome Project (HCP; N = 812) and the UK Biobank (UKB; N = 6,716). Using signed community clustering to identify distinct states of dynamic functional connectivity, and text-mining of a large existing literature for functional annotation of each state, our findings from the HCP dataset indicated that the resting brain spontaneously transitions between three functionally specialized states: sensory, somatomotor, and internal mentation networks. The occurrence, transition-rate, and persistence-time parameters for each state were correlated with behavioural scores using canonical correlation analysis. We estimated the same brain states and parameters in the UKB dataset, subdivided into three distinct age ranges: 50-55, 56-67, and 68-78 years. We found that the internal mentation network was more frequently expressed in people aged 71 and older, whereas people younger than 55 more frequently expressed sensory and somatomotor networks. Furthermore, analysis of the functional entropy - a measure of uncertainty of functional connectivity - also supported this finding across the three age ranges. Our study demonstrates that dynamic functional connectivity analysis can expose the time-varying patterns of transition between functionally specialized brain states, which are strongly tied to increasing age., Competing Interests: Declaration of Competing Interest Nothing to declare., (Copyright © 2021. Published by Elsevier Inc.)

Accurate perception of the orientations of the body axis and gravity is essential for actions. The ability to perceive these orientations during head and body tilt varies across individuals, and its underlying neural basis is unknown. To address this, we investigated the association between inter-individual differences in local gray matter (GM) volume and inter-individual differences in the ability to estimate the directions of body longitudinal axis or gravity during whole-body tilt using voxel-based morphometry (VBM) analysis in 50 healthy adults (20-46 years, 25 men and 25 women). Although no anatomical regions were identified relating to performance requiring estimates of gravitational direction, we found a significant correlation between the GM volume in the right middle occipital gyrus and the ability to estimate the body axis orientation. This finding provides the first evidence on neuroanatomical substrates of the perception of body axis orientation during body tilt., (© 2021. The Author(s).)

Arginine vasopressin (AVP), a neuropeptide with widespread receptors in brain regions important for socioemotional processing, is critical in regulating various mammalian social behavior and emotion. Although a growing body of task-based brain imaging studies have revealed the effects of AVP on brain activity associated with emotion processing, social cognition and behaviors, the potential modulations of AVP on resting-state brain activity remain largely unknown. Here, the current study addressed this issue by adopting a machine learning approach to distinguish administration of AVP and placebo, employing the amplitude of low-frequency fluctuation (ALFF) as a measure of resting-state brain activity. The brain regions contributing to the classification were then subjected to functional connectivity and decoding analyses, allowing for a data-driven quantitative inference on psychophysiological functions. Our results indicated that ALFF across multiple neural systems were sufficient to distinguish between AVP and placebo at individual level, with the contributing regions distributed across the social cognition network, sensorimotor regions and emotional processing network. These findings suggest that the role of AVP in socioemotional functioning recruits multiple brain networks distributed across the whole brain rather than specific localized neural pathways. Beyond these findings, the current data-driven approach also opens a novel avenue to delineate neural underpinnings of various neuropeptides or hormones., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Political partisans see the world through an ideologically biased lens. What drives political polarization? Although it has been posited that polarization arises because of an inability to tolerate uncertainty and a need to hold predictable beliefs about the world, evidence for this hypothesis remains elusive. We examined the relationship between uncertainty tolerance and political polarization using a combination of brain-to-brain synchrony and intersubject representational similarity analysis, which measured committed liberals' and conservatives' ( n = 44) subjective interpretation of naturalistic political video material. Shared ideology between participants increased neural synchrony throughout the brain during a polarizing political debate filled with provocative language but not during a neutrally worded news clip on polarized topics or a nonpolitical documentary. During the political debate, neural synchrony in mentalizing and valuation networks was modulated by one's aversion to uncertainty: Uncertainty-intolerant individuals experienced greater brain-to-brain synchrony with politically like-minded peers and lower synchrony with political opponents-an effect observed for liberals and conservatives alike. Moreover, the greater the neural synchrony between committed partisans, the more likely that two individuals formed similar, polarized attitudes about the debate. These results suggest that uncertainty attitudes gate the shared neural processing of political narratives, thereby fueling polarized attitude formation about hot-button issues., Competing Interests: The authors declare no competing interest.

The neural bases of anger are still a matter of debate. In particular we do not know whether anger perception and anger experience rely on similar or different neural mechanisms. To study this topic, we performed activation-likelihood-estimation meta-analyses of human neuroimaging studies on 61 previous studies on anger perception and experience. Anger perception analysis resulted in significant activation in the amygdala, the right superior temporal gyrus, the right fusiform gyrus and the right IFG, thus revealing the role of perceptual temporal areas for perceiving angry stimuli. Anger experience analysis resulted in the bilateral activations of the insula and the ventrolateral prefrontal cortex, thus revealing a role for these areas in the subjective experience of anger and, possibly, in a subsequent evaluation of the situation. Conjunction analyses revealed a common area localized in the right inferior frontal gyrus, probably involved in the conceptualization of anger for both perception and experience. Altogether these results provide new insights on the functional architecture underlying the neural processing of anger that involves separate and joint mechanisms. According to our tentative model, angry stimuli are processed by temporal areas, such as the superior temporal gyrus, the fusiform gyrus and the amygdala; on the other hand, the subjective experience of anger mainly relies on the anterior insula; finally, this pattern of activations converges in the right IFG. This region seems to play a key role in the elaboration of a general meaning of this emotion, when anger is perceived or experienced., Competing Interests: Declaration of Competing Interest None., (Copyright © 2021. Published by Elsevier Inc.)

The brain exhibits a complex temporal structure which translates into a hierarchy of distinct neural timescales. An open question is how these intrinsic timescales are related to sensory or motor information processing and whether these dynamics have common patterns in different behavioral states. We address these questions by investigating the brain's intrinsic timescales in healthy controls, motor (amyotrophic lateral sclerosis, locked-in syndrome), sensory (anesthesia, unresponsive wakefulness syndrome), and progressive reduction of sensory processing (from awake states over N1, N2, N3). We employed a combination of measures from EEG resting-state data: auto-correlation window (ACW), power spectral density (PSD), and power-law exponent (PLE). Prolonged neural timescales accompanied by a shift towards slower frequencies were observed in the conditions with sensory deficits, but not in conditions with motor deficits. Our results establish that the spontaneous activity's intrinsic neural timescale is related to the neural capacity that specifically supports sensory rather than motor information processing in the healthy brain., Competing Interests: Declaration of Competing Interest None., (Copyright © 2020. Published by Elsevier Inc.)

Within the broad field of human perception lies the category of stimulus-independent perceptions, which draws together experiences such as hallucinations, mental imagery and dreams. Traditional divisions between medical and psychological sciences have contributed to these experiences being investigated separately. This review aims to examine their similarities and differences at the levels of phenomenology and underlying brain function and thus reassemble them within a common framework. Using Edmund Parish's historical work as a guiding tool and the latest research findings in the cognitive, clinical and computational sciences, we consider how different perspectives may be reconciled and help generate novel hypotheses for future research. This article is part of the theme issue 'Offline perception: voluntary and spontaneous perceptual experiences without matching external stimulation'.

Decades of research on collective decision making has claimed that aggregated judgment of multiple individuals is more accurate than expert individual judgement. A longstanding problem in this regard has been to determine how decisions of individuals can be combined to form intelligent group decisions. Our study consisted of a random target detection task in natural scenes, where human subjects (18 subjects, 7 female) detected the presence or absence of a random target as indicated by the cue word displayed prior to stimulus display. Concurrently the neural activities (EEG signals) were recorded. A separate behavioural experiment was performed by different subjects (20 subjects, 11 female) on the same set of images to categorize the tasks according to their difficulty levels. We demonstrate that the weighted average of individual decision confidence/neural decision variables produces significantly better performance than the frequently used majority pooling algorithm. Further, the classification error rates from individual judgement were found to increase with increasing task difficulty. This error could be significantly reduced upon combining the individual decisions using group aggregation rules. Using statistical tests, we show that combining all available participants is unnecessary to achieve minimum classification error rate. We also try to explore if group aggregation benefits depend on the correlation between the individual judgements of the group and our results seem to suggest that reduced inter-subject correlation can improve collective decision making for a fixed difficulty level.

We examined effects of a 20-min nap following 3 h of sleep deprivation on brain wave activity, auditory reaction time, the running-based anaerobic sprint test, leg muscle strength and the rating of perceived exertion in male college soccer players. Eleven players underwent three sleep conditions; normal sleep, sleep deprivation and 20-min nap after sleep deprivation. The sleep deprivation demonstrated an increase in the mean power of delta waves over the frontal area and a decrease in the mean power of alpha waves over the parietal area compared to the normal sleep. The nap and the sleep deprivation showed an increase in auditory reaction time compared with those in the normal sleep. The sleep deprivation demonstrated a decrease in the running-based anaerobic sprint test compared to the normal sleep, whereas the nap has partially reversed only minimal power and average power of the running-based anaerobic sprint test. The nap showed a recovery effect on leg muscle strength, but not on the rating of perceived exertion compared with the sleep deprivation. Thus, a 20-min nap after sleep deprivation did not completely return brain activity back to active state and did not entirely reverse the negative impact of sleep deprivation on soccer performance in soccer players., Competing Interests: The authors declare that they have no Conflict of Interest, (Thieme. All rights reserved.)

The Predictive Processing Theory (PP) and its foundational Free Energy Principle (FEP) provide a unifying theoretical groundwork that subsumes theories of perception, cognition, and action. Recently Colin Klein (2018) contends that PP-FEP cannot explain adaptive action with the same force that they deal with perceptions. In his answer to the objection, Clark (2020) points out that FEP explains action, desire and motivation on the basis of minimisation of energy. I argue that this answer begs the question of the unifying framework of FEP. I assume that FEP-PP alone cannot provide an ultimately compelling explanation of action. However, I argue that when paired with a high level theory of psychology, such as Theriault et al.'s (2020) theory of social conformation in terms of the sense of should, the coupled theories provide an inclusive, symmetrical explanation of action. The symmetry of explanations is not a gap but a feature, on this specific occasion., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Adaptive brain function requires that sensory impressions of the social and natural milieu are dynamically incorporated into intrinsic brain activity. While dynamic switches between brain states have been well characterised in resting state acquisitions, the remodelling of these state transitions by engagement in naturalistic stimuli remains poorly understood. Here, we show that the temporal dynamics of brain states, as measured in fMRI, are reshaped from predominantly bistable transitions between two relatively indistinct states at rest, toward a sequence of well-defined functional states during movie viewing whose transitions are temporally aligned to specific features of the movie. The expression of these brain states covaries with different physiological states and reflects subjectively rated engagement in the movie. In sum, a data-driven decoding of brain states reveals the distinct reshaping of functional network expression and reliable state transitions that accompany the switch from resting state to perceptual immersion in an ecologically valid sensory experience.

Predictive coding emerged as an explanation for how the brain can efficiently encode sensory stimuli. The hierarchical organization of neural circuits for perception thus passes prediction errors between computational layers. Extensions of this theory have provided a unifying understanding of Bayesian inference within neural circuits and psychiatric disorders. In particular, disorders of perception and belief have been explained as a Bayesian process of weighing prior beliefs (predictions) against new sensory data (prediction errors). The present issue of the Journal of Abnormal Psychology provides further evidence for how psychotic disorders develop and persist and how addiction- and trauma-related disorders may also be conceptualized. Trauma-related disorders in particular have begun to be identified as disorders of excessive accumulated prediction errors (uncertainty) over life. Here we summarize and reconcile recent advances in reinforcement learning momentum models with predictive processing and attempt to point out potential pitfalls for the application of hierarchical prediction models to stress. Future directions for understanding stress through this lens may need to involve updates to a purely hierarchical view or reframing long times cale molecular predictions as higher-order predictions. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

About 25 years ago, the discovery of receptive field (RF) remapping in the parietal cortex of nonhuman primates revealed that visual RFs, widely assumed to have a fixed retinotopic organization, can change position before every saccade. Measuring such changes can be deceptively difficult. As a result, studies that followed have generated a fascinating but somewhat confusing picture of the phenomenon. In this review, we describe how observations of RF remapping depend on the spatial and temporal sampling of visual RFs and saccade directions. Further, we summarize some of the theories of how remapping might occur in neural circuitry. Finally, based on neurophysiological and psychophysical observations, we discuss the ways in which remapping information might facilitate computations in downstream brain areas.

ABSTRACT The role that language plays in shaping non-linguistic cognitive and perceptual systems has been the subject of much theoretical and experimental attention over the past half-century. Understanding how language interacts with non-linguistic systems can provide insight into broader constraints on cognitive and brain organization. The papers that form this volume investigate various ways in which linguistic structure can interact with and influence how speakers think about and perceive the world, and the related issue of the constraints that in turn shape linguistic representations. These theoretical and empirical contributions support deeper understanding of the interactions between language, thought, and perception, and motivate new approaches for developing directional predictions at both the neural and cognitive levels.

Human subjects of both sexes were asked to make a perceptual decision between multiple directions of visual motion. In addition to reporting a primary choice, they also had to report a second guess, indicating which of the remaining options they would rather bet on, assuming that they got their primary choice wrong. The second guess was clearly informed by the amounts of sensory evidence that were provided for the different options. A single computational integration-to-threshold model, based on the assumption that the second guess is determined by the rank ordering of accumulated evidence at or shortly after the time of the decision, was able to explain the distribution of primary choices, associated response times, and the distribution of second guesses. This suggests that the decision-maker has access to how well supported unchosen options are by the sensory evidence. SIGNIFICANCE STATEMENT Perceptual decisions require conversion of sensory evidence into a discrete choice. Computational models based on the accumulation of evidence to a decision threshold can explain the distribution of choices and associated decision times. Subjects are also able to report the level of confidence in their decision. Here we show that, when making decisions between more than two alternatives, the decision-maker can even report a second guess that is clearly informed by the sensory evidence. These second guesses show a distribution that is consistent with subjects having access to how much sensory evidence was accumulated for the unchosen options. The decision-maker therefore has knowledge about the outcome of the decision process that goes beyond just the choice and an associated confidence., (Copyright © 2020 the authors.)

Studies have shown that adolescents are more likely than adults to take risks in the presence of peers than when alone, and that young adolescents' risk perception is more influenced by other teenagers than by adults. The current fMRI study investigated the effect of social influence on risk perception in female adolescents (aged 12-14) and adults (aged 23-29). Participants rated the riskiness of everyday situations and were then informed about the (alleged) risk ratings of a social influence group (teenagers or adults), before rating each situation again. The results showed that adolescents adjusted their ratings to conform with others more than adults did, and both age groups were influenced more by adults than by teenagers. When there was a conflict between the participants' own risk ratings and the ratings of the social influence group, activation was increased in the posterior medial frontal cortex, dorsal cingulate cortex and inferior frontal gyrus in both age groups. In addition, there was greater activation during no-conflict situations in the right middle frontal gyrus and bilateral parietal cortex in adults compared with adolescents. These results suggest that there are behavioral and neural differences between adolescents and adults in conflict and no-conflict social situations.

Previous unimodal PET and fMRI studies in humans revealed a reproducible vestibular brain activation pattern, but with variations in its weighting and expansiveness. Hybrid studies minimizing methodological variations at baseline conditions are rare and still lacking for task-based designs. Thus, we applied for the first time hybrid 3T PET-MRI scanning (Siemens mMR) in healthy volunteers using galvanic vestibular stimulation (GVS) in healthy volunteers in order to directly compare H215O-PET and BOLD MRI responses. List mode PET acquisition started with the injection of 750 MBq H215O simultaneously to MRI EPI sequences. Group-level statistical parametric maps were generated for GVS vs. rest contrasts of PET, MR-onset (event-related), and MR-block. All contrasts showed a similar bilateral vestibular activation pattern with remarkable proximity of activation foci. Both BOLD contrasts gave more bilateral wide-spread activation clusters than PET; no area showed contradictory signal responses. PET still confirmed the right-hemispheric lateralization of the vestibular system, whereas BOLD-onset revealed only a tendency. The reciprocal inhibitory visual-vestibular interaction concept was confirmed by PET signal decreases in primary and secondary visual cortices, and BOLD-block decreases in secondary visual areas. In conclusion, MRI activation maps contained a mixture of CBF measured using H215O-PET and additional non-CBF effects, and the activation-deactivation pattern of the BOLD-block appears to be more similar to the H215O-PET than the BOLD-onset., Competing Interests: The authors have declared that no competing interests exist.

Humans are highly attuned to perceptual cues about their values. A growing body of evidence suggests that people selectively attend to moral stimuli. However, it is unknown whether morality is prioritized early in perception or much later in cognitive processing. We use a combination of behavioral methods and electroencephalography to investigate how early in perception moral words are prioritized relative to non-moral words. The behavioral data replicate previous research indicating that people are more likely to correctly identify moral than non-moral words in a modified lexical decision task. The electroencephalography data reveal that words are distinguished from non-words as early as 200 ms after onset over frontal brain areas and moral words are distinguished from non-moral words 100 ms later over left-posterior cortex. Further analyses reveal that differences in brain activity to moral vs non-moral words cannot be explained by differences in arousal associated with the words. These results suggest that moral content might be prioritized in conscious awareness after an initial perceptual encoding but before subsequent memory processing or action preparation. This work offers a more precise theoretical framework for understanding how morality impacts vision and behavior., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

The idea that predictions shape how we perceive and comprehend the world has become increasingly influential in the field of systems neuroscience. It also forms an important framework for understanding neuropsychiatric disorders, which are proposed to be the result of disturbances in the mechanisms through which prior information influences perception and belief, leading to the production of suboptimal models of the world. There is a widespread tendency to conceptualize the influence of predictions exclusively in terms of 'top-down' processes, whereby predictions generated in higher-level areas exert their influence on lower-level areas within an information processing hierarchy. However, this excludes from consideration the predictive information embedded in the 'bottom-up' stream of information processing. We describe evidence for the importance of this distinction and argue that it is critical for the development of the predictive processing framework and, ultimately, for an understanding of the perturbations that drive the emergence of neuropsychiatric symptoms and experiences.

White matter (WM) plasticity during adulthood is a recently described phenomenon by which experience can shape brain structure. It has been observed in humans using diffusion tensor imaging (DTI) and myelination has been suggested as a possible mechanism. Here, we set out to identify molecular and cellular changes associated with WM plasticity measured by DTI. We combined DTI, immunohistochemistry and mRNA expression analysis and examined the effects of somatosensory experience in adult rats. First, we observed experience-induced DTI differences in WM and in grey matter structure. C-Fos mRNA expression, a marker of cortical activity, in the barrel cortex correlated with the MRI WM metrics, indicating that molecular correlates of cortical activity relate to macroscale measures of WM structure. Analysis of myelin-related genes revealed higher myelin basic protein (MBP) mRNA expression. Higher MBP protein expression was also found via immunohistochemistry in WM. Finally, unbiased RNA sequencing analysis identified 134 differentially expressed genes encoding proteins involved in functions related to cell proliferation and differentiation, regulation of myelination and neuronal activity modulation. In conclusion, macroscale measures of WM plasticity are supported by both molecular and cellular evidence and confirm that myelination is one of the underlying mechanisms., Competing Interests: Declaration of Competing Interest We report no conflict of interest., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Mouse fMRI has become increasingly popular in the small animal imaging field. However, compared to the more commonly used rat fMRI, it is challenging for mouse fMRI to obtain robust and specific functional imaging results. In the meantime, in other neuroscience modalities such as optical imaging, functional recording in the awake mice is common and becoming standard. Therefore, in the current study we developed comprehensive setups and analysis pipeline for multi-sensory fMRI paradigms in the awake mice. Customized setups of somatosensory (whisker), auditory and olfactory stimulation were developed for use in the cryogenic coil in the awake mouse fMRI setting. After carefully evaluating head motion and motion artefacts, the nuisance regression approach was optimized for reducing the confounding effect of motion. The high temporal resolution data (TR = 0.35 s) revealed fast temporal dynamics (time-to-peak ~2 s) of evoked BOLD responses in most brain regions. Using the derived awake mouse specific hemodynamic response functions, high spatial resolution data revealed robust, specific and consistent cortical and subcortical activations in response to somatosensory, auditory and olfactory stimulations, respectively. Overall, we present comprehensive methods for acquiring and analyzing sensory evoked awake mouse fMRI data. The establishment of multi-sensory paradigms in awake mouse fMRI provides valuable tools for examining spatiotemporal characteristics and neural mechanisms of BOLD signals in the future., (Copyright © 2019 Elsevier Inc. All rights reserved.)

During the past two decades, the number of animal models of psychiatric disorders has grown exponentially. Of these, genetic animal models that are modeled after rare but highly penetrant mutations hold great promise for deciphering critical molecular, synaptic, and neurocircuitry deficits of major psychiatric disorders, such as schizophrenia. Animal models should aim to focus on core aspects rather than capture the entire human disease. In this context, animal models with strong etiological validity, where behavioral and neurophysiological phenotypes and the features of the disease being modeled are in unambiguous homology, are being used to dissect both elementary and complex cognitive and perceptual processing deficits present in psychiatric disorders at the level of neurocircuitry, shedding new light on critical disease mechanisms. Recent progress in neuroscience along with large-scale initiatives that propose a consistent approach in characterizing these deficits across different laboratories will further enhance the efficacy of these studies that will ultimately lead to identifying new biological targets for drug development.

Research on whether perception or other processes depend on the phase of neural oscillations is rapidly gaining popularity. However, it is unknown which methods are optimally suited to evaluate the hypothesized phase effect. Using a simulation approach, we here test the ability of different methods to detect such an effect on dichotomous (e.g., "hit" vs "miss") and continuous (e.g., scalp potentials) response variables. We manipulated parameters that characterise the phase effect or define the experimental approach to test for this effect. For each parameter combination and response variable, we identified an optimal method. We found that methods regressing single-trial responses on circular (sine and cosine) predictors perform best for all of the simulated parameters, regardless of the nature of the response variable (dichotomous or continuous). In sum, our study lays a foundation for optimized experimental designs and analyses in future studies investigating the role of phase for neural and behavioural responses. We provide MATLAB code for the statistical methods tested., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

The strategy of integrating motor signals with sensory information during voluntary behavior is a general feature of sensory processing. It is required to distinguish externally applied (exafferent) from self-generated (reafferent) sensory inputs. This distinction, in turn, underlies our ability to achieve both perceptual stability and accurate motor control during everyday activities. In this review, we consider the results of recent experiments that have provided circuit-level insight into how motor-related inputs to sensory areas selectively cancel self-generated sensory inputs during active behaviors. These studies have revealed both common strategies and important differences across systems. Sensory reafference is suppressed at the earliest stages of central processing in the somatosensory, vestibular, and auditory systems, with the cerebellum and cerebellum-like structures playing key roles. Furthermore, motor-related inputs can also suppress reafferent responses at higher levels of processing such as the cortex-a strategy preferentially used in visual processing. These recent findings have important implications for understanding how the brain achieves the flexibility required to continuously calibrate relationships between motor signals and the resultant sensory feedback, a computation necessary for our subjective awareness that we control both our actions and their sensory consequences., (Copyright © 2019 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Hohwy (2013) proposed an account of conscious access that integrates the global neuronal workspace (GNW) into the framework of predictive processing, a view that I term the predictive global neuronal workspace (PGNW). Whilst promising, the PGNW is theoretically underdeveloped and empirically underexplored. The aim of this article is to outline the empirical predictions that distinguish the PGNW from other workspace models. I do so by (i) placing the PGNW in close contact with experimental work and cashing out a set of predictions that distinguish it from the standard formulation of the GNW, (ii) exploring the evidence for the first of these predictions in the context of bistable perception and the conscious processing of auditory regularities, and (iii), contrasting the PGNW with Chanes and Barrett (2016) limbic workspace. Combined, these arguments show that the PGNW is both testable and supported by current evidence., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Objective: Brain computer interfacing (BCI) is a promising method to control assistive systems for patients with severe disabilities. Recently, we have presented a novel BCI approach that combines an electrotactile menu and a brain switch, which allows the user to trigger many commands robustly and efficiently. However, the commands are timed to periodic tactile cues and this may challenge online control. In the present study, therefore, we implemented and evaluated a novel approach for online closed-loop control using the proposed BCI., Approach: Eleven healthy subjects used the novel method to move a cursor in a 2D space. To assure robust control with properly timed commands, the BCI was integrated within a state machine allowing the subject to start the cursor movement in the selected direction and asynchronously stop the cursor. The brain switch was controlled using motor execution (ME) or imagery (MI) and the menu implemented four (straight movements) or eight commands (straight and diagonal movements)., Main Results: The results showed a high completion rate of a target hitting task (~97% and ~92% for ME and MI, respectively), with a small number of collisions, when four-channel control was used. There was no significant difference in outcome measures between MI and ME, and performance was similar for four and eight commands., Significance: These results demonstrate that the novel state-based scheme driven by a robust BCI can be successfully utilized for online control. Therefore, it can be an attractive solution for providing the user an online-control interface with many commands, which is difficult to achieve using classic BCI solutions.

The emotional expression of fear can be processed through a number of modalities, and of varying forms, however, much of the functional imaging literature has centered on investigating fear as expressed through faces. Findings point to an active involvement of the amygdala, and remain fairly consistent in other studies of unimodal fear perception; however, few studies have looked at within-subject cross-modal responses to fear. Thus, we approached this inquiry by testing 30 healthy young adults with fast, high-resolution fMRI, recording the neural responses of fear perception, as expressed through faces, bodies, prosody, and vocalizations. The study was analyzed using a multivariate approach (multi-voxel pattern analysis) and yielded a significant distinction in the responses associated with the perception of fearful vs. neutral emotions. Calculated weights highlighted areas in the amygdala and surrounding subcortical structures as contributing the greatest to the discrimination; however, a whole-brain analysis was necessary to obtain above-chance classification accuracy, suggesting that processing fear across modalities likely involves a broad, distributed network. Thus, our findings support a multivariate approach to studying a highly complex construct such as emotion, as it accounts for multiple voxels simultaneously and can accommodate the high subject-level variability that oftentimes comes with studying emotion perception., (© 2018 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

Intrinsic brain activity is organized in spatial-temporal patterns, called resting-state networks (RSNs), exhibiting specific structural-functional architecture. These networks presumably reflect complex neurophysiological processes and have a central role in distinct perceptual and cognitive functions. In this work, we propose an innovative approach for characterizing RSNs according to their underlying neural oscillations. We investigated specific electrophysiological properties, including spectral features, fractal dimension, and entropy, associated with eight core RSNs derived from high-density electroencephalography (EEG) source-reconstructed signals. Specifically, we found higher synchronization of the gamma-band activity and higher fractal dimension values in perceptual (PNs) compared with higher cognitive (HCNs) networks. The inspection of this underlying rapid activity becomes of utmost importance for assessing possible alterations related to specific brain disorders. The disruption of the coordinated activity of RSNs may result in altered behavioral and perceptual states. Thus, this approach could potentially be used for the early detection and treatment of neurological disorders., (© 2018 Wiley Periodicals, Inc.)

The foundation for modern understanding of how we make perceptual decisions about what we see or where to look comes from considering the optimal way to perform these behaviors. While statistical computation is useful for deriving the optimal solution to a perceptual problem, optimality requires perfect knowledge of priors and often complex computation. Accumulating evidence, however, suggests that optimal perceptual goals can be achieved or approximated more simply by human observers using heuristic approaches. Perceptual neuroscientists captivated by optimal explanations of sensory behaviors will fail in their search for the neural circuits and cortical processes that implement an optimal computation whenever that behavior is actually achieved through heuristics. This article provides a cross-disciplinary review of decision-making with the aim of building perceptual theory that uses optimality to set the computational goals for perceptual behavior but, through consideration of ecological, computational, and energetic constraints, incorporates how these optimal goals can be achieved through heuristic approximation.

Fatigue is a health problem prevalent in modern societies. Fatigue sensation plays an important role as a biological alarm urging rest to maintain homeostasis, and clarifying the neural mechanisms related to fatigue sensations by which we decide to engage in rest is therefore essential. This study enrolled healthy male volunteers and showed that the decrease in alpha-band power as assessed by magnetoencephalography of the left Brodmann's area (BA) 6 before perception of fatigue when a button-press based on the level of fatigue was required was smaller than that before perception of the intention to move when a voluntary button-press was required. In addition, the decrease of alpha-band power in the left BA 6 before the perception of fatigue was not altered compared with that in the right BA 6 when a button-press based on the level of fatigue was required. These results suggest that the button-press based on the perception of fatigue is not prepared before the perception of fatigue. These findings will advance the understanding of the neural mechanisms related to subjective feelings such as fatigue sensation.

Destructured sensory fields, involving homogenous stimulation with little or no time-varying structure, provide a fertile ground for testing hypotheses about predictive coding in the human brain. Extended exposure to sensory patterns that deviate substantially from the statistics of natural environments can elicit a bewildering range of perceptual phenomena, up to and including vivid oneiric imagery. We illustrate how this large variety of perceptual effects can be understood as the experiential counterpart of auto-generated neuronal dynamics, unconstrained by parameters that tune the waking sensorium. We synthesize the literature on autonomous neuronal activity across multiple spatiotemporal scales with generative models of brain function and evidence from artificial neural architectures. Perception, we argue, emerges from a process of non-random sampling from an intrinsic distribution of hypotheses rather than a direct transfer of information from the world. The imagery that occurs in altered sensory environments is explained as the outcome of an iterative search through internal world models in which the structural typology of percepts reflects the brain's intrinsic functional architectures., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Classical eyeblink conditioning (EBC) is one of the simplest forms of associative learning that depends critically on the cerebellum. Using delay EBC (dEBC), a standard paradigm in which the unconditioned stimulus (US) is delayed and co-terminates with the conditioned stimulus (CS), converging lines of evidence has been accumulated and shows that the essential neural circuit mediating EBC resides in the cerebellum and brainstem. In addition to this essential circuit, multiple cerebral cortical and subcortical structures are required to modulate dEBC with suboptimal training parameters, and trace EBC (tEBC) in which a trace-interval separates the CS and US. However, it remains largely unclear why and how so many brain regions are involved for modulation of EBC. Previous research has suggested that the forebrain regions, such as medial prefrontal cortex (mPFC) and hippocampus, may be required to process weak CSs, or to realize temporal overlap between the CS and US signal inputs when the two stimuli were separated in time (i.e. during tEBC). Here, we proposed a multi-level network model for EBC modulation which focuses on sensory processing of CS. The model explains how different neural pathways projecting to pontine nucleus (PN) are involved to amplify or extend CS through heterosynaptic facilitation mechanism or "substitution effect" under different circumstances to achieve EBC. As such, our model can serve as a general framework to explain the modulating mechanism of EBC in a variety of conditions and to help understand the interaction among cerebellum, brainstem, cortical and subcortical regions in EBC modulation., (Copyright © 2018 Elsevier B.V. All rights reserved.)

The goal of sensory neuroscience is to understand how the brain creates its myriad of representations of the world, and uses these representations to produce perception and behavior. Circuits of neurons in spatially segregated regions of brain tissue have distinct functional specializations, and these regions are connected to form a functional processing hierarchy. Advances in technology for recording neuronal activity from multiple sites in multiple cortical areas mean that we are now able to collect data that reflects how information is transformed within and between connected members of this hierarchy. This advance is an important step in understanding the brain because, after the sensory organs have transduced a physical signal, every processing stage takes the activity of other neurons as its input, not measurements of the physical world. However, as we explore the potential of studying how populations of neurons in multiple areas respond in concert, we must also expand both the analytical tools that we use to make sense of these data and the scope of the theories that we attempt to define. In this article, we present an overview of some of the most promising analytical approaches for making inferences from population recordings in multiple brain areas, such as dimensionality reduction and measuring changes in correlated variability, and examine how they may be used to address longstanding questions in sensory neuroscience.

Bayesian theories of perception have traditionally cast the brain as an idealised scientist, refining predictions about the outside world based on evidence sampled by the senses. However, recent predictive coding models include predictions that are resistant to change, and these stubborn predictions can be usefully incorporated into cognitive models., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Background: Dementia with Lewy bodies (DLB) is characterized by progressive cognitive decline, fluctuating cognition, visual hallucinations, rapid eye movement sleep behavior disorder, and parkinsonism. DLB is the second most common type of degenerative dementia of all dementia cases. However, DLB, particularly in the early stage, is underdiagnosed and sometimes misdiagnosed with other types of dementia. Thus, it is of great interest investigating neurophysiological markers of DLB., Method: We introduced exact low-resolution brain electromagnetic tomography (eLORETA)-independent component analysis (ICA) to assess activities of 5 electroencephalography (EEG) resting-state networks (RSNs) in 41 drug-free DLB patients., Results: Compared to 80 healthy controls, DLB patients had significantly decreased activities in occipital visual and sensorimotor networks, where DLB patients and healthy controls showed no age dependences in all EEG-RSN activities. Also, we found correlations between all EEG-RSN activities and DLB symptoms. Specifically, decreased occipital α activity showed correlations with worse brain functions related to attention/concentration, visuospatial discrimination, and global cognition. Enhanced visual perception network activity correlated with milder levels of depression and anxiety. Enhanced self-referential network activity correlated with milder levels of depression. Enhanced memory perception network activity correlated with better semantic memory, visuospatial discrimination function, and global cognitive function as well as with severer visual hallucination. In addition, decreased sensorimotor network activity correlated with a better semantic memory., Conclusion: These results indicate that eLORETA-ICA can detect EEG-RSN activity alterations in DLB related to symptoms. Therefore, eLORETA-ICA with EEG data can be a useful noninvasive tool for sensitive detection of EEG-RSN activity changes characteristic of DLB and for understanding the neurophysiological mechanisms underlying this disease., (© 2019 S. Karger AG, Basel.)

Absorption, the ability to highly focus attention, as well as openness to self-altering experiences, is an important psychological construct, closely related to deep-meditation states and other altered states of consciousness. Yet, little is known about the electrophysiological profile of states of absorption, possibly due to the difficulty to induce this state in the lab. While most studies have used a visual Ganzfeld (homogeneous perceptual field), here we use a novel technique of full immersion-the OVO Whole-Body Perceptual Deprivation (OVO-WBPD) chamber, which is an altered sensory environment in the form of a human-sized egg. Consequently, the aims of the current study were to investigate whether the OVO-WBPD chamber induces state absorption, using first-person reports, as well as to examine electrophysiological change following immersion in this altered sensory environment. Fourteen participants volunteered to participate in the study. Trait absorption was measured using the Tellegen Absorption Scale (TAS). State absorption was assessed by analyzing the content of the subjective reports, using sub-categories of the absorption construct (e.g., synesthesia). EEG was measured before and during a 20-min OVO-WBPD experience. Using exact low-resolution brain electromagnetic tomography (eLORETA), we analyzed change in oscillatory EEG activity and localized the generators of the scalp EEG power spectra following the OVO-WBPD. Our results show that OVO-WBPD immersion leads to a state of absorption in all participants. We also report significant increased oscillatory activity in the delta and beta bands, in the left inferior frontal cortex, with a peak in the sub-lobar of the left insula. In addition, a positive correlation was found between change in delta activity and trait absorption. The results are discussed in light of other meditative practices and altered states of consciousness., (© 2019 Elsevier B.V. All rights reserved.)

Understanding the neural mechanisms underlying conscious perception has become a central endeavor in cognitive neuroscience. In theories of conscious perception, a stimulus gaining conscious access is usually considered as a discrete neuronal event to be characterized in time or space, sometimes referred to as a conscious "episode." Surprisingly, the alternative hypothesis according to which conscious perception is a dynamic process has rarely been considered. Here, we discuss this hypothesis and its implications. We show how it can reconcile inconsistent empirical findings on the timing of the neural correlates of consciousness and make testable predictions. According to this hypothesis, a stimulus is consciously perceived for as long as it is recoded to fit an ongoing stream composed of all other perceived stimuli. We suggest that this "updating" process is governed by at least three factors (1) context, (2) stimulus saliency, and (3) observers' goals. Finally, this framework forces us to reconsider the typical distinction between conscious and unconscious information processing.

Predominant conceptual frameworks often describe peripersonal space (PPS) as a single, distance-based, in-or-out zone within which stimuli elicit enhanced neural and behavioural responses. Here we argue that this intuitive framework is contradicted by neurophysiological and behavioural data. First, PPS-related measures are not binary, but graded with proximity. Second, they are strongly influenced by factors other than proximity, such as walking, tool use, stimulus valence, and social cues. Third, many different PPS-related responses exist, and each can be used to describe a different space. Here, we reconceptualise PPS as a set of graded fields describing behavioural relevance of actions aiming to create or avoid contact between objects and the body. This reconceptualisation incorporates PPS into mainstream theories of action selection and behaviour., (Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Increasing command generation rate of an event-related potential-based brain-robot system is challenging, because of limited information transfer rate of a brain-computer interface system. To improve the rate, we propose a dual stimuli approach that is flashing a robot image and is scanning another robot image simultaneously. Two kinds of event-related potentials, N200 and P300 potentials, evoked in this dual stimuli condition are decoded by a convolutional neural network. Compared with the traditional approaches, this proposed approach significantly improves the online information transfer rate from 23.0 or 17.8 to 39.1 bits/min at an accuracy of 91.7%. These results suggest that combining multiple types of stimuli to evoke distinguishable ERPs might be a promising direction to improve the command generation rate in the brain-computer interface.

At any given moment, we receive input through our different sensory systems, and this information needs to be processed and integrated. Multisensory processing requires the coordinated activity of distinct cortical areas. Key mechanisms implicated in these processes include local neural oscillations and functional connectivity between distant cortical areas. Evidence is now emerging that neural oscillations in distinct frequency bands reflect different mechanisms of multisensory processing. Moreover, studies suggest that aberrant neural oscillations contribute to multisensory processing deficits in clinical populations, such as schizophrenia. In this article, we review recent literature on the neural mechanisms underlying multisensory processing, focusing on neural oscillations. We derive a framework that summarizes findings on (1) stimulus-driven multisensory processing, (2) the influence of top-down information on multisensory processing, and (3) the role of predictions for the formation of multisensory perception. We propose that different frequency band oscillations subserve complementary mechanisms of multisensory processing. These processes can act in parallel and are essential for multisensory processing.

The human brain is known by its ability to modify and update existing memories, mediated by underlying neuronal plasticity. This ability is facilitated by two main phenomena, interference and generalization. Interference occurs when a new memory harms, or is being harmed by, a different memory that was acquired in temporal proximity to it. Generalization on the other hand, refers to the case in which a learned memory is expanded beyond its specific properties. While each of these two phenomena may be well known separately, we review recent evidence primarily in perceptual and motor skill memory, spanning synaptic, neural systems-level, and behavioral research, suggesting that although the outcomes are different, the underlying neural and behavioral processes responsible for their inducements share numerous commonalities. The reviewed literature may imply a common mechanism underlying these two phenomena, and suggests a unified framework of memory and learning in the human brain., (Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.)

The dysregulation of food intake in chronic obesity has been explained by different theories. To assess their explanatory power, we meta-analyzed 22 brain-activation imaging studies. We found that obese individuals exhibit hyper-responsivity of the brain regions involved in taste and reward for food-related stimuli. Consistent with a Reward Surfeit Hypothesis, obese individuals exhibit a ventral striatum hyper-responsivity in response to pure tastes, particularly when fasting. Furthermore, we found that obese subjects display more frequent ventral striatal activation for visual food cues when satiated: this continued processing within the reward system, together with the aforementioned evidence, is compatible with the Incentive Sensitization Theory. On the other hand, we did not find univocal evidence in favor of a Reward Deficit Hypothesis nor for a systematic deficit of inhibitory cognitive control. We conclude that the available brain activation data on the dysregulated food intake and food-related behavior in chronic obesity can be best framed within an Incentive Sensitization Theory. Implications of these findings for a brain-based therapy of obesity are briefly discussed., (Copyright © 2018 Elsevier Ltd. All rights reserved.)