From neuronal to psychological noise – Long-range temporal correlations in EEG intrinsic activity reduce noise in internally-guided decision making

The more random people's preference judgments are, the more they explore in gambling tasks

BACKGROUND

The decision-making process has been investigated separately in the context of externally guided decision-making (EDM, e.g., a gambling task) and internally guided decision-making (IDM, e.g., a preference judgment). In EDM situations, a predictable correct answer exists, and the value of the chosen item increases when positive feedback is received. On the contrary, in IDM situations, there is no objectively correct answer, and participants must decide based on their own internal criteria, such as preference or belief. In IDM, a choice-induced preference change occurs when the value of the chosen item increases and that of the rejected item decreases. However, since these two types of decision-making have been investigated separately, their relationship remains unclear.

METHODS

The present study examined the consistency in an individual's tendency of decision-making reflected in the model parameters (i.e., learning rate and inverse temperature) between EDM and IDM. In this study, participants performed EDM and IDM tasks with different items.

RESULTS

The findings indicated that an individual's tendency with respect to how much value is reflected in decision-making (i.e., inverse temperature) between EDM and IDM is consistent. By contrast, no such consistency was observed for the degree of value change after a decision (i.e., the learning rate).

CONCLUSIONS

This study demonstrates the close relationship between these two types of decision-making and offers a more comprehensive understanding of the human decision-making process.

Application of HFO and scaling analysis of neuronal oscillations in the presurgical evaluation of focal epilepsy

PURPOSE

To explore the utility of high frequency oscillations (HFO) and long-range temporal correlations (LRTCs) in preoperative assessment of epilepsy.

METHODS

MEG ripples were detected in 59 drug-resistant epilepsy patients, comprising 5 with parietal lobe epilepsy (PLE), 21 with frontal lobe epilepsy (FLE), 14 with lateral temporal lobe epilepsy (LTLE), and 19 with mesial temporal lobe epilepsy (MTLE) to identify the epileptogenic zone (EZ). The results were compared with clinical MEG reports and resection area. Subsequently, LRTCs were quantified at the source-level by detrended fluctuation analysis (DFA) and life/waiting -time at 5 bands for 90 cerebral cortex regions. The brain regions with larger DFA exponents and standardized life-waiting biomarkers were compared with the resection results.

RESULTS

Compared to MEG sensor-level data, ripple sources were more frequently localized within the resection area. Moreover, source-level analysis revealed a higher proportion of DFA exponents and life-waiting biomarkers with relatively higher rankings, primarily distributed within the resection area (p<0.01). Moreover, these two LRCT indices across five distinct frequency bands correlated with EZ.

CONCLUSION

HFO and source-level LRTCs are correlated with EZ. Integrating HFO and LRTCs may be an effective approach for presurgical evaluation of epilepsy.

Aperiodic and Hurst EEG exponents across early human brain development: A systematic review

In electroencephalographic (EEG) data, power-frequency slope exponents (1/f_β) can provide non-invasive markers of in vivo neural activity excitation-inhibition (E:I) balance. E:I balance may be altered in neurodevelopmental conditions; hence, understanding how 1/fβ evolves across infancy/childhood has implications for developing early assessments/interventions. This systematic review (PROSPERO-ID: CRD42023363294) explored the early maturation (0-26 yrs) of resting-state EEG 1/f measures (aperiodic [AE], power law [PLE] and Hurst [HE] exponents), including studies containing ≥1 1/f measures and ≥10 typically developing participants. Five databases (including Embase and Scopus) were searched during March 2023. Forty-two studies were identified (Nparticipants=3478). Risk of bias was assessed using the Quality Assessment with Diverse Studies tool. Narrative synthesis of HE data suggests non-stationary EEG activity occurs throughout development. Age-related trends were complex, with rapid decreases in AEs during infancy and heterogenous changes thereafter. Regionally, AE maxima shifted developmentally, potentially reflecting spatial trends in maturing brain connectivity. This work highlights the importance of further characterising the development of 1/f measures to better understand how E:I balance shapes brain and cognitive development.

Internally Formed Preferences for Options only Influence Initial Decisions in Gambling Tasks, while the Gambling Outcomes do not Alter these Preferences

All humans must engage in decision-making. Decision-making processes can be broadly classified into internally guided decision-making (IDM), which is determined by individuals' internal value criteria, such as preference, or externally guided decision-making (EDM), which is determined by environmental external value criteria, such as monetary rewards. However, real-life decisions are never made simply using one kind of decision-making, and the relationship between IDM and EDM remains unclear. This study had individuals perform gambling tasks requiring the EDM using stimuli that formed preferences through the preference judgment task as the IDM. Computational model analysis revealed that strong preferences in the IDM affected initial choice behavior in the EDM. Moreover, through the analysis of the subjective preference evaluation after the gambling tasks, we found that even when stimuli that were preferred in the IDM were perceived as less valuable in the EDM, the preference for IDM was maintained after EDM. These results indicate that although internal criteria, such as preferences, influence EDM, the results show that internal and external criteria differ.

Tracing conflict-induced cognitive-control adjustments over time using aperiodic EEG activity

Cognitive-control theories assume that the experience of response conflict can trigger control adjustments. However, while some approaches focus on adjustments that impact the selection of the present response (in trial N), other approaches focus on adjustments in the next upcoming trial  (N + 1). We aimed to trace control adjustments over time by quantifying cortical noise by means of the fitting oscillations and one over f algorithm, a measure of aperiodic activity. As predicted, conflict trials increased the aperiodic exponent in a large sample of 171 healthy adults, thus indicating noise reduction. While this adjustment was visible in trial N already, it did not affect response selection before the next trial. This suggests that control adjustments do not affect ongoing response-selection processes but prepare the system for tighter control in the next trial. We interpret the findings in terms of a conflict-induced switch from metacontrol flexibility to metacontrol persistence, accompanied or even implemented by a reduction of cortical noise.

Intrinsic neural timescales mediate the cognitive bias of self - temporal integration as key mechanism

Our perceptions and decisions are not always objectively correct as they are featured by a bias related to our self. What are the behavioral, neural, and computational mechanisms of such cognitive bias? Addressing this yet unresolved question, we here investigate whether the cognitive bias is related to temporal integration and segregation as mediated by the brain's Intrinsic neural timescales (INT). Using Signal Detection Theory (SDT), we operationalize the cognitive bias by the Criterion C as distinguished from the sensitivity index d'. This was probed in a self-task based on morphed self- and other faces. Behavioral data demonstrate clear cognitive bias, i.e., Criterion C. That was related to the EEG-based INT as measured by the autocorrelation window (ACW) in especially the transmodal regions dorsolateral prefrontal cortex (dlPFC) and default-mode network (DMN) as distinct from unimodal visual cortex. Finally, simulation of the same paradigm in a large-scale network model shows high degrees of temporal integration of temporally distinct inputs in CMS/DMN and dlPFC while temporal segregation predominates in visual cortex. Together, we demonstrate a key role of INT-based temporal integration in CMS/DMN and dlPFC including its relation to the brain's uni-transmodal topographical organization in mediating the cognitive bias of our self.

Intermittent brain network reconfigurations and the resistance to social media influence

Since its development, social media has grown as a source of information and has a significant impact on opinion formation. Individuals interact with others and content via social media platforms in a variety of ways, but it remains unclear how decision-making and associated neural processes are impacted by the online sharing of informational content, from factual to fabricated. Here, we use EEG to estimate dynamic reconfigurations of brain networks and probe the neural changes underlying opinion change (or formation) within individuals interacting with a simulated social media platform. Our findings indicate that the individuals who changed their opinions are characterized by less frequent network reconfigurations while those who did not change their opinions tend to have more flexible brain networks with frequent reconfigurations. The nature of these frequent network configurations suggests a fundamentally different thought process between intervals in which individuals are easily influenced by social media and those in which they are not. We also show that these reconfigurations are distinct to the brain dynamics during an in-person discussion with strangers on the same content. Together, these findings suggest that brain network reconfigurations may not only be diagnostic to the informational context but also the underlying opinion formation.

Augmenting Human Selves Through Artificial Agents – Lessons From the Brain

Much of current artificial intelligence (AI) and the drive toward artificial general intelligence (AGI) focuses on developing machines for functional tasks that humans accomplish. These may be narrowly specified tasks as in AI, or more general tasks as in AGI – but typically these tasks do not target higher-level human cognitive abilities, such as consciousness or morality; these are left to the realm of so-called “strong AI” or “artificial consciousness.” In this paper, we focus on how a machine can augment humans rather than do what they do, and we extend this beyond AGI-style tasks to augmenting peculiarly personal human capacities, such as wellbeing and morality. We base this proposal on associating such capacities with the “self,” which we define as the “environment-agent nexus”; namely, a fine-tuned interaction of brain with environment in all its relevant variables. We consider richly adaptive architectures that have the potential to implement this interaction by taking lessons from the brain. In particular, we suggest conjoining the free energy principle (FEP) with the dynamic temporo-spatial (TSD) view of neuro-mental processes. Our proposed integration of FEP and TSD – in the implementation of artificial agents – offers a novel, expressive, and explainable way for artificial agents to adapt to different environmental contexts. The targeted applications are broad: from adaptive intelligence augmenting agents (IA’s) that assist psychiatric self-regulation to environmental disaster prediction and personal assistants. This reflects the central role of the mind and moral decision-making in most of what we do as humans.

Differential modulation of behavior by infraslow activities of different brain regions

The oscillation phase of electroencephalograms (EEGs) is associated with behavioral performance. Several studies have demonstrated this association for relatively fast oscillations (>1 Hz); a similar finding has also been reported for slower oscillations, showing that behavioral performance is correlated with the phase of infraslow activity (ISA, 0.01-0.1 Hz) of electroencephalography (EEG). However, the previous study only investigated ISA in a local brain region using a relatively simple task (somatosensory discrimination task), leaving it difficult to determine how the EEG ISA for various brain regions is associated with behavioral performance. In addition, it is not known whether the EEG ISA phase modulates more complex behavioral task performance. In the present study, we analyzed the ISA of whole-brain EEG of participants performing various behaviors while playing video games. We found that behavior was associated with the specific oscillation phase of EEG ISA when that behavior was independent of other behaviors. In addition, we found that the EEG ISA oscillation phases modulating the different behaviors varied across brain regions. Our results suggest that the EEG ISA for different brain regions modulates behavioral performance in different ways and such modulation of EEG ISA can be generalized to diverse behaviors. This study may deepen the understanding of how EEG ISA modulates behavior and increases the applicability of EEG ISA.

Multivariate patterns and long-range temporal correlations of alpha oscillations are associated with flexible manipulation of visual working memory representations

The ability to flexibly manipulate memory representations is embedded in visual working memory (VWM) and can be tested using paradigms with retrospective cues. Although valid retrospective cues often facilitate memory recall, invalid ones may or may not result in performance costs. We investigated individual differences in utilising retrospective cues and evaluated how these individual differences are associated with brain oscillatory activity at rest. At the behavioural level, we operationalised flexibility as the ability to make effective use of retrospective cues or disregard them if required. At the neural level, we tested whether individual differences in such flexibility were associated with properties of resting-state alpha oscillatory activity (8-12 Hz). To capture distinct aspects of these brain oscillations, we evaluated their power spectral density and temporal dynamics using long-range temporal correlations (LRTCs). In addition, we performed multivariate patterns analysis (MVPA) to classify individuals' level of behavioural flexibility based on these neural measures. We observed that alpha power alone (magnitude) at rest was not associated with flexibility. However, we found that the participants' ability to manipulate VWM representations was correlated with alpha LRTC and could be decoded using MVPA on patterns of alpha power. Our findings suggest that alpha LRTC and multivariate patterns of alpha power at rest may underlie some of the individual differences in using retrospective cues in working memory tasks.

What COVID-19 tells us about the self: The deep intersubjective and cultural layers of our brain

The COVID-19 crisis is affecting our sense of self and touches upon our existential fears. This extends to the self-other relationship, as there is both being infected and infecting the other. What does this pandemic crisis tell us about our self and relatedness, its cultural differences, and how these are rooted in the brain's relation to the world? First, we discuss the psychological and neuronal features of self and self-other relation and how they are rooted in a deeper layer of the brain's neural activity complementing its cognitive surface layer. Second, we demonstrate cultural differences of Eastern and Western concepts of the self (i.e., independency and interdependency) and how these reflect the manifestation of the brain's neuro-social and neuro-ecological alignment. Finally, we highlight the intersubjective and cultural nature of the self and its surface in the COVID-19 crisis. Discussing various lines of empirical data showing the brain's intimate alignment to both social and ecological environmental contexts, our results support the assumption of the brain's deep layer features by laying bare a continuum of different degrees of neuro-social and neuro-ecological alignment. This entails a two-stage model of self with neuro-social-ecological and psychological levels that extends the previously suggested basis model of self-specificity. We conclude that the current pandemic shows the importance of the deeper intersubjective and cultural layers of both the self and brain; their neglect can be life-threatening for the self and others and, paradoxically, might reduce, rather than enlarge, the self's sense of freedom and independence.

Association between long-range temporal correlations in intrinsic EEG activity and subjective sense of identity

The long-range temporal correlation (LRTC) in resting-state intrinsic brain activity is known to be associated with temporal behavioral patterns, including decision making based on internal criteria such as self-knowledge. However, the association between the neuronal LRTC and the subjective sense of identity remains to be explored; in other words, whether our subjective sense of consistent self across time relates to the temporal consistency of neural activity. The present study examined the relationship between the LRTC of resting-state scalp electroencephalography (EEG) and a subjective sense of identity measured by the Erikson Psychosocial Stage Inventory (EPSI). Consistent with our prediction based on previous studies of neuronal-behavioral relationships, the frontocentral alpha LRTC correlated negatively with identity confusion. Moreover, from the descriptive analyses, centroparietal beta LRTC showed negative correlations with identity confusion, and frontal theta LRTC showed positive relationships with identity synthesis. These results suggest that more temporal consistency (reversely, less random noise) in intrinsic brain activity is associated with less confused and better-synthesized identity. Our data provide further evidence that the LRTC of intrinsic brain activity might serve as a noise suppression mechanism at the psychological level.

Computational modeling of choice-induced preference change: A Reinforcement-Learning-based approach

The value learning process has been investigated using decision-making tasks with a correct answer specified by the external environment (externally guided decision-making, EDM). In EDM, people are required to adjust their choices based on feedback, and the learning process is generally explained by the reinforcement learning (RL) model. In addition to EDM, value is learned through internally guided decision-making (IDM), in which no correct answer defined by external circumstances is available, such as preference judgment. In IDM, it has been believed that the value of the chosen item is increased and that of the rejected item is decreased (choice-induced preference change; CIPC). An RL-based model called the choice-based learning (CBL) model had been proposed to describe CIPC, in which the values of chosen and/or rejected items are updated as if own choice were the correct answer. However, the validity of the CBL model has not been confirmed by fitting the model to IDM behavioral data. The present study aims to examine the CBL model in IDM. We conducted simulations, a preference judgment task for novel contour shapes, and applied computational model analyses to the behavioral data. The results showed that the CBL model with both the chosen and rejected value’s updated were a good fit for the IDM behavioral data compared to the other candidate models. Although previous studies using subjective preference ratings had repeatedly reported changes only in one of the values of either the chosen or rejected items, we demonstrated for the first time both items’ value changes were based solely on IDM choice behavioral data with computational model analyses.

Temporal integration as "common currency" of brain and self-scale-free activity in resting-state EEG correlates with temporal delay effects on self-relatedness

The self is a multifaceted phenomenon that integrates information and experience across multiple time scales. How temporal integration on the psychological level of the self is related to temporal integration on the neuronal level remains unclear. To investigate temporal integration on the psychological level, we modified a well-established self-matching paradigm by inserting temporal delays. On the neuronal level, we indexed temporal integration in resting-state EEG by two related measures of scale-free dynamics, the power law exponent and autocorrelation window. We hypothesized that the previously established self-prioritization effect, measured as decreased response times or increased accuracy for self-related stimuli, would change with the insertion of different temporal delays between the paired stimuli, and that these changes would be related to temporal integration on the neuronal level. We found a significant self-prioritization effect on accuracy in all conditions with delays, indicating stronger temporal integration of self-related stimuli. Further, we observed a relationship between temporal integration on psychological and neuronal levels: higher degrees of neuronal integration, that is, higher power-law exponent and longer autocorrelation window, during resting-state EEG were related to a stronger increase in the self-prioritization effect across longer temporal delays. We conclude that temporal integration on the neuronal level serves as a template for temporal integration of the self on the psychological level. Temporal integration can thus be conceived as the "common currency" of neuronal and psychological levels of self.

Resting-state theta/beta ratio is associated with distraction but not with reappraisal

Although previous research indicated that resting-state theta/beta ratio (TBR) is related to unspecified emotion regulation (ER), the ER strategies associated with TBR remain unclear. We examined whether representative ER strategies-distraction and reappraisal-are related to resting-state TBR. Data from sixty-one healthy Japanese university students were recorded in an eyes-closed resting-state with an electroencephalogram (EEG). Their self-reported tendencies of distraction and reappraisal were assessed. Rank-correlation analyses revealed that lower frontal and parietal TBR were associated with high distraction tendency. However, frontal and parietal TBR were not correlated with reappraisal. Given that TBR is linked to attention control, distraction may be associated with TBR. Consequently, TBR can be used to identify persons with ER difficulties, based on the results of this study.

Stronger resting-state neural oscillations associated with wiser advising from the 2nd- but not the 3rd-person perspective

This is the first electroencephalogram study exploring the personal perspective effect on wise advising. Participants advised hypothetical protagonists in life dilemmas from both the 2nd- and 3rd-person perspective. Their advice for each dilemma was rated by two independent raters on wisdom criteria, i.e., metacognitive humility, metacognitive flexibility, and perspective taking. The results revealed that participants felt a significantly shorter psychological distance from protagonists when advising from the 2nd- (vs. the 3rd-) person perspective, p < 0.001. However, there was no significant effect of perspective condition on the wisdom score. Nevertheless, stronger resting-state absolute EEG powers in the frontal lobe were associated with wiser advising from the 2nd-, but not the 3rd-person perspective. Moreover, Z tests revealed that the correlations between the resting-state absolute EEG powers and wisdom scores were significantly stronger during advising from the 2nd- than the 3rd-person perspective. These results suggest that advising from the 2nd-person perspective was more self-related, and mental activities during rest contributed to advising from the 2nd- but not the 3rd-person perspective.

Spatiotemporal neuroscience - what is it and why we need it

The excellent commentaries to our target paper hint upon three main issues, (i) spatiotemporal neuroscience; (ii) neuro-mental relationship; and (iii) mind, brain, and world relationship. (i) We therefore discuss briefly the history of Spatiotemporal Neuroscience. Distinguishing it from Cognitive Neuroscience and related branches (like Affective, Social, etc. Neuroscience), Spatiotemporal Neuroscience can be characterized by focus on brain activity (rather than brain function), spatiotemporal relationship (rather than input-cognition-output relationship), and structure (rather than stimuli/contents). (ii) Taken in this sense, Spatiotemporal Neuroscience allows one to conceive the neuro-mental relationship in dynamic spatiotemporal terms that complement and extend (rather than contradict) their cognitive characterization. (iii) Finally, more philosophical issues like the need to dissolve the mind-body problem (and replace it by the world-brain relation) and the question for different levels of time including their nestedness are discussed.

The Self and its World: A Neuro-Ecological and Temporo-Spatial Account of Existential Fear

The current international crisis situation caused by the COVID-19 pandemic is having a strong psychological impact on our subjectivities. We are constantly threatened by the danger of i) being infected, ii) infecting other people, and (iii) by the loss of social relation. Departing from these premises, we here aim to investigate the psychological and neurodynamics of this complex phenomenon. First, we discuss about recent psychological and neuronal findings on fear and its disorders, related to an unbalanced intero-exteroceptive processing and emotional regulation. Secondly we move to the psychological and neuronal dynamics of self and others characterized by a temporo-spatial alignment with the world. Due to the neural overlap of emotion and self and the deep-reaching neuro-ecological layers of self, emotional feelings like fear and anxiety cannot be detached and dissociated from the world; they signify the world–brain relation, and, more specifically, our self-other relation. The deepest neuro-ecological and neuro-social layers of self are threatened by the loss of subjectivity, which is manifest in our loss of body and thus the fear of dying, and the loss of intersubjectivity that surfaces in our fear of infecting others, which reflect the intimate anchorage of the self with the world. In our opinion the pandemic of COVID-19 deeply affect our sense of self and its spatio-temporal neuronal dynamics providing the prerequisites for the manifestation of fear and existential anxiety, thus disrupting the brain-world relation with significant repercussions on our psyche and on our daily lives.