Predictive Processing Research Articles

A Systematic Review of Information Systems Association with Smart Technology from 3G to 5G

The rapid evolution of telecommunications technology from 3G to 5G has profoundly impacted the landscape of smart technology and information systems. This systematic review examines the association between these technologies, focusing on the transformative effects of advancements in telecommunications. We explore the integration of information systems with smart devices, highlighting how each generation of telecommunications technology has enhanced connectivity and enabled more sophisticated applications across various sectors. Key areas of focus include healthcare, transportation, and industrial automation. In healthcare, advancements have facilitated remote patient monitoring, telemedicine, and wearable health devices. In transportation, the evolution from GPS-based navigation to real-time traffic management and autonomous vehicles is discussed. In industrial automation, the role of smart sensors and IoT devices in predictive maintenance and process optimization is analyzed. This review synthesizes existing literature, providing a comprehensive understanding of how the progression from 3G to 5G has driven innovation and efficiency in these fields. Methodologically, we adhered to PRISMA guidelines, conducting a thorough search of academic databases to identify relevant studies. Our findings underscore the significant impact of each telecommunications generation on the development and implementation of smart technology and information systems. The transition to 5G, in particular, represents a transformative leap, offering unprecedented data speeds, ultra-low latency, and massive connectivity. This review concludes by discussing future perspectives and the potential for further advancements in telecommunications to enhance the integration of information systems with smart technology. By providing a detailed overview, this study contributes to the understanding of the dynamic relationship between telecommunications advancements and smart technology development.

Predictive Processing and Chronic Pain

Predictive Processing and Chronic Pain

Chronic pain – A maladaptive compensation to unbalanced hierarchical predictive processing

The ability to perceive pain presents an interesting evolutionary advantage to adapt to an ever-changing environment. However, in the case of chronic pain (CP), pain perception hinders the capacity of the system to adapt to changing sensory environments. Similar to other chronic perceptual disorders, CP is also proposed to be a maladaptive compensation to aberrant sensory predictive processing. The local-global oddball paradigm relies on learning hierarchical rules and processing environmental irregularities at a local and global level. Prediction errors (PE) between actual and predicted input typically trigger an update of the forward model to limit the probability of encountering future PEs. It has been hypothesised that CP hinders forward model updating, reflected in increased local deviance and decreased global deviance. In the present study, we used the local-global paradigm to examine how CP influences hierarchical learning relative to healthy controls. As hypothesised, we observed that deviance in the stimulus characteristics evoked heightened local deviance and decreased global deviance of the stimulus-driven PE. This is also accompanied by respective changes in theta phase locking that is correlated with the subjective pain perception. Changes in the global deviant in the stimulus-driven-PE could also be explained by dampened attention-related responses. Changing the context of the auditory stimulus did not however show a difference in the context-driven PE. These findings suggest that CP is accompanied by maladaptive forward model updating where the constant presence of pain perception disrupts local deviance in non-nociceptive domains. Furthermore, we hypothesise that the auditory-processing based biomarker identified here could be a marker of domain-general dysfunction that could be confirmed by future research.

Sensorimotor prediction is used to direct gaze toward task-relevant locations in a goal-directed throwing task.

Previous research has shown that action effects of self-generated movements are internally predicted before outcome feedback becomes available. To test whether these sensorimotor predictions are used to facilitate visual information uptake for feedback processing, we measured eye movements during the execution of a goal-directed throwing task. Participants could fully observe the effects of their throwing actions (ball trajectory and either hitting or missing a target) in most of the trials. In a portion of the trials, the ball trajectory was not visible, and participants only received static information about the outcome. We observed a large proportion of predictive saccades, shifting gaze toward the goal region before the ball arrived and outcome feedback became available. Fixation locations after predictive saccades systematically covaried with future ball positions in trials with continuous ball flight information, but notably also in trials with static outcome feedback and only efferent and proprioceptive information about the movement that could be used for predictions. Fixation durations at the chosen positions after feedback onset were modulated by action outcome (longer durations for misses than for hits) and outcome uncertainty (longer durations for narrow vs. clear outcomes). Combining both effects, durations were longest for narrow errors and shortest for clear hits, indicating that the chosen locations offer informational value for feedback processing. Thus, humans are able to use sensorimotor predictions to direct their gaze toward task-relevant feedback locations. Outcome-dependent saccade latency differences (miss vs. hit) indicate that also predictive valuation processes are involved in planning predictive saccades.NEW & NOTEWORTHY We elucidate the potential benefits of sensorimotor predictions, focusing on how the system actually uses this information to optimize feedback processing in goal-directed actions. Sensorimotor information is used to predict spatial parameters of movement outcomes, guiding predictive saccades toward future action effects. Saccade latencies and fixation durations are modulated by outcome quality, indicating that predictive valuation processes are considered and that the locations chosen are of high informational value for feedback processing.

Segmenting and Predicting Musical Phrase Structure Exploits Neural Gain Modulation and Phase Precession.

Music, like spoken language, is often characterized by hierarchically organized structure. Previous experiments have shown neural tracking of notes and beats, but little work touches on the more abstract question: how does the brain establish high-level musical structures in real time? We presented Bach chorales to participants (20 females and 9 males) undergoing electroencephalogram (EEG) recording to investigate how the brain tracks musical phrases. We removed the main temporal cues to phrasal structures, so that listeners could only rely on harmonic information to parse a continuous musical stream. Phrasal structures were disrupted by locally or globally reversing the harmonic progression, so that our observations on the original music could be controlled and compared. We first replicated the findings on neural tracking of musical notes and beats, substantiating the positive correlation between musical training and neural tracking. Critically, we discovered a neural signature in the frequency range ∼0.1 Hz (modulations of EEG power) that reliably tracks musical phrasal structure. Next, we developed an approach to quantify the phrasal phase precession of the EEG power, revealing that phrase tracking is indeed an operation of active segmentation involving predictive processes. We demonstrate that the brain establishes complex musical structures online over long timescales (>5 s) and actively segments continuous music streams in a manner comparable to language processing. These two neural signatures, phrase tracking and phrasal phase precession, provide new conceptual and technical tools to study the processes underpinning high-level structure building using noninvasive recording techniques.

When performing actions with robots, attribution of intentionality affects the sense of joint agency.

Sense of joint agency (SoJA) is the sense of control experienced by humans when acting with others to bring about changes in the shared environment. SoJA is proposed to arise from the sensorimotor predictive processes underlying action control and monitoring. Because SoJA is a ubiquitous phenomenon occurring when we perform actions with other humans, it is of great interest and importance to understand whether-and under what conditions-SoJA occurs in collaborative tasks with humanoid robots. In this study, using behavioral measures and neural responses measured by electroencephalography (EEG), we aimed to evaluate whether SoJA occurs in joint action with the humanoid robot iCub and whether its emergence is influenced by the perceived intentionality of the robot. Behavioral results show that participants experienced SoJA with the robot partner when it was presented as an intentional agent but not when it was presented as a mechanical artifact. EEG results show that the mechanism that influences the emergence of SoJA in the condition when the robot is presented as an intentional agent is the ability to form similarly accurate predictions about the sensory consequences of our own and others' actions, leading to similar modulatory activity over sensory processing. Together, our results shed light on the joint sensorimotor processing mechanisms underlying the emergence of SoJA in human-robot interaction and underscore the importance of attribution of intentionality to the robot in human-robot collaboration.

The Search for Sources of Conflicts: Supply and Demand in the Labor Market

Classical approaches towards categorizing conflict within the field of social sciences may not be applicable to the labor market context because they are beyond economic theories. To the best of our knowledge, currently, neither national nor foreign literature contains any conceptual systematization of conflicts that occur during the hiring process. Such systematization would combine conflict factors at the intersection of economic, sociological, and conflict theories. The article proposes a categorization that is based on the prominent conflict theories while taking into consideration potential employment conflicts within the labor market. The proposed categorization groups market participants (supply and demand sides) and sorts conflicts by type (systemic and non-systemic conflicts). Four primary sources of conflict are identified, including market mechanisms and salary expectations (systemic conflicts), company values and human capital (non-systemic conflicts). Systemic factors of conflicts such as supply/ demand matching and wage expectations are determined by market mechanisms. These economic factors are determined by objective and predictable processes, but sociological theories of conflict are typically excluded from the aforementioned context, which can result in a biased portrayal of macroeconomic processes. In addition, the policy of a particular company and a job seeker’s expectations for a specific job position are nonsystemic, they depend on such types of factors as company values and human capital.This categorization enables early identification of the source of conflict and potential reduction of its destructive effects.

EXPLORING CONCUSSION RECOVERY THROUGH THE LENS OF THE FREE ENERGY PRINCIPLE AND MARKOV BLANKET THEORY

This paper delves into the application of the Free Energy Principle (FEP) and the concept of the Markov blanket in understanding the neurocognitive implications of concussion. The FEP, a unifying theory in neuroscience, posits that the brain functions to minimize free energy, equating to a reduction in surprise or uncertainty regarding sensory inputs. The Markov blanket, defining the boundary between a system and its environment, is integral to this framework, particularly in understanding how the brain processes and responds to sensory information. We explore how a concussion might disrupt the brain's predictive processing and its ability to minimize free energy, leading to increased prediction errors and cognitive deficits. This disruption is hypothesized to manifest as an inability to accurately predict sensory inputs, resulting in impaired cognitive functions post-concussion. The paper also discusses the potential of neuroplasticity in concussion recovery, framed within the FEP as the brain's effort to re-establish minimized free energy under new constraints. We propose a methodological approach combining neuroimaging and computational modeling to empirically test these hypotheses. This theoretical exploration offers novel insights into the mechanisms underlying concussion-induced cognitive impairments and suggests new avenues for therapeutic intervention and rehabilitation strategies.

Neurodynamics of Relational Aesthetic Engagement in Creative Arts Therapies

Aesthetic experiences, emerging saliently in the arts, play a pivotal role in transformative learning and creative processes that elicit physiological, affective, and cognitive responses associated with mental health indices. Interactions between subjects and aesthetic objects (e.g., visual artwork, music, and moving bodies) often entail elements of surprise and uncertainty that drive the inference of the hidden causes in the subject’s internal and external environment. These generate dynamics that align with the action-oriented Predictive Processing framework of brain function. Creative Arts Therapies (CATs) harness these dynamics by cultivating relational engagement using the arts modalities, prompting affective and cognitive processing. In this manuscript, we offer a review and conceptual analysis of recent empirical findings and theoretical premises that underpin aesthetic experiences and their relation to the psychotherapeutic use of the arts with a broad spectrum of populations and mental health conditions. We present a neuroscience-based approach to aesthetic intra- and inter-personal experiences, integrating therapeutic change factors of externalization-concretization, embodiment, and symbolization with functional network configurations, and interpersonal brain-to-brain coupling, to support predictive processing, learning, and creativity. Present and future interdisciplinary collaborations are underlined to elucidate the neurodynamic mechanisms driving psychological transformations, bridging neuroaesthetics and CATs.

Effects of expectations and sensory unreliability on voice detection – A preregistered study

The phenomenon of “hearing voices” can be found not only in psychotic disorders, but also in the general population, with individuals across cultures reporting auditory perceptions of supernatural beings. In our preregistered study, we investigated a possible mechanism of such experiences, grounded in the predictive processing model of agency detection. We predicted that in a signal detection task, expecting less or more voices than actually present would drive the response bias toward a more conservative and liberal response strategy, respectively. Moreover, we hypothesized that including sensory noise would enhance these expectancy effects. In line with our predictions, the findings show that detection of voices relies on expectations and that this effect is especially pronounced in the case of unreliable sensory data. As such, the study contributes to our understanding of the predictive processes in hearing and the building blocks of voice hearing experiences.

Neural oscillations during predictive sentence processing in young children

The neural correlates of predictive processing in language, critical for efficient sentence comprehension, is well documented in adults. Specifically, adults exhibit alpha power (9–12 Hz) suppression when processing high versus low predictability sentences. This study explores whether young children exhibit similar neural mechanisms. We analyzed EEG data from 29 children aged 3–5 years listening to sentences of varying predictability. Our results revealed significant neural oscillation differences in the 5–12 Hz range between high and low predictability sentences, similar to adult patterns. Crucially, the degree of these differences correlated with children’s language abilities. These findings are the first to demonstrate the neural basis of predictive processing in young children and its association with language development.

Decoding Remapped Spatial Information in the Peri-Saccadic Period.

It has been suggested that, prior to a saccade, visual neurons predictively respond to stimuli that will fall in their receptive fields after completion of the saccade. This saccadic remapping process is thought to compensate for the shift of the visual world across the retina caused by eye movements. To map the timing of this predictive process in the brain, we recorded neural activity using electroencephalography during a saccade task. Human participants (male and female) made saccades between two fixation points while covertly attending to oriented gratings briefly presented at various locations on the screen. Data recorded during trials in which participants maintained fixation were used to train classifiers on stimuli in different positions. Subsequently, data collected during saccade trials were used to test for the presence of remapped stimulus information at the post-saccadic retinotopic location in the peri-saccadic period, providing unique insight into when remapped information becomes available. We found that the stimulus could be decoded at the remapped location ∼180 ms post-stimulus onset, but only when the stimulus was presented 100-200 ms before saccade onset. Within this range, we found that the timing of remapping was dictated by stimulus onset rather than saccade onset. We conclude that presenting the stimulus immediately before the saccade allows for optimal integration of the corollary discharge signal with the incoming peripheral visual information, resulting in a remapping of activation to the relevant post-saccadic retinotopic neurons.

Signal and noise in Skelton

ABSTRACT Predictive processing is one of the most significant emerging schools of thought in cognitive science. With its emphasis on anticipation and modifications as the result of ‘prediction error’, it has much to offer literary criticism, which itself has much to offer in return. This essay explores the particular pertinence of predictive processing to poetic form and to satire, with reference to three poems by John Skelton: Ware the Hauke (c. 1505), Speke Parott (1521) and Why Come Ye Nat To Courte? (1522). One key aspect of the cognitive model, the distinction between signal and noise, proves particularly germane to understanding the ways that Skelton complicates and enables readerly responses.

Updating predictions in a complex repertoire of actions and its neural representation

Even though actions we observe in everyday life seem to unfold in a continuous manner, they are automatically divided into meaningful chunks, that are single actions or segments, which provide information for the formation and updating of internal predictive models. Specifically, boundaries between actions constitute a hub for predictive processing since the prediction of the current action comes to an end and calls for updating of predictions for the next action. In the current study, we investigated neural processes which characterize such boundaries using a repertoire of complex action sequences with a predefined probabilistic structure. Action sequences consisted of actions that started with the hand touching an object (T) and ended with the hand releasing the object (U). These action boundaries were determined using an automatic computer vision algorithm. Participants trained all action sequences by imitating demo videos. Subsequently, they returned for an fMRI session during which the original action sequences were presented in addition to slightly modified versions thereof. Participants completed a post-fMRI memory test to assess the retention of original action sequences. The exchange of individual actions, and thus a violation of action prediction, resulted in increased activation of the action observation network and the anterior insula. At U events, marking the end of an action, increased brain activation in supplementary motor area, striatum, and lingual gyrus was indicative of the retrieval of the previously encoded action repertoire. As expected, brain activation at U events also reflected the predefined probabilistic branching structure of the action repertoire. At T events, marking the beginning of the next action, midline and hippocampal regions were recruited, reflecting the selected prediction of the unfolding action segment. In conclusion, our findings contribute to a better understanding of the various cerebral processes characterizing prediction during the observation of complex action repertoires.

Continuous chiral separation process for high-speed countercurrent chromatography established and scaled up: A case of Voriconazole enantioseparation.

An efficient method for the continuous separation of Voriconazole enantiomers was developed using sulfobutyl ether-β-cyclodextrin (SBE-β-CD) as a chiral selector in high-speed countercurrent chromatography (HSCCC) with different types. The separation was performed using a two-phase solvent system consisting of n-hexane/ethyl acetate/100mmol/L phosphate buffer solution (pH=3.0, containing 50mmol/L SBE-β-CD) (1.5:0.5:2, v/v/v). A fast and predictable scale-up process was achieved using an analytical DE HSCCC instrument. The optimized parameters were subsequently applied to a preparative Tauto HSCCC instrument, resulting in consistent separation time and enantiomeric purity, with throughput boosted by a remarkable 11-fold. Preparative HSCCC successfully separated 506mg of the racemate, delivering enantiomers exceeding 99% purity as confirmed by high-performance liquid chromatography analysis. This investigation presents an effective methodology for forecasting the HSCCC scale-up process and attaining continuous separation of chiral drugs.

Pain perception as hierarchical Bayesian inference: A test case for the theory of constructed emotion.

An intriguing perspective about human emotion, the theory of constructed emotion considers emotions as generative models according to the Bayesian brain hypothesis. This theory brings fresh insight to existing findings, but its complexity renders it challenging to test experimentally. We argue that laboratory studies of pain could support the theory because although some may not consider pain to be a genuine emotion, the theory must at minimum be able to explain pain perception and its dysfunction in pathology. We review emerging evidence that bear on this question. We cover behavioral and neural laboratory findings, computational models, placebo hyperalgesia, and chronic pain. We conclude that there is substantial evidence for a predictive processing account of painful experience, paving the way for a better understanding of neuronal and computational mechanisms of other emotions.

Counterfactual Explanations in the Big Picture: An Approach for Process Prediction-Driven Job-Shop Scheduling Optimization

In this study, we propose a pioneering framework for generating multi-objective counterfactual explanations in job-shop scheduling contexts, combining predictive process monitoring with advanced mathematical optimization techniques. Using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) for multi-objective optimization, our approach enhances the generation of counterfactual explanations that illuminate potential enhancements at both the operational and systemic levels. Validated with real-world data, our methodology underscores the superiority of NSGA-II in crafting pertinent and actionable counterfactual explanations, surpassing traditional methods in both efficiency and practical relevance. This work advances the domains of explainable artificial intelligence (XAI), predictive process monitoring, and combinatorial optimization, providing an effective tool for improving automated scheduling systems’ clarity, and decision-making capabilities.

Invariant representations in abstract concept grounding - the physical world in grounded cognition.

Grounded cognition states that mental representations of concepts consist of experiential aspects. For example, the concept "cup" consists of the sensorimotor experiences from interactions with cups. Typical modalities in which concepts are grounded are: The sensorimotor system (including interoception), emotion, action, language, and social aspects. Here, we argue that this list should be expanded to include physical invariants (unchanging features of physical motion; e.g., gravity, momentum, friction). Research on physical reasoning consistently demonstrates that physical invariants are represented as fundamentally as other grounding substrates, and therefore should qualify. We assess several theories of concept representation (simulation, conceptual metaphor, conceptual spaces, predictive processing) and their positions on physical invariants. We find that the classic grounded cognition theories, simulation and conceptual metaphor theory, have not considered physical invariants, while conceptual spaces and predictive processing have. We conclude that physical invariants should be included into grounded cognition theories, and that the core mechanisms of simulation and conceptual metaphor theory are well suited to do this. Furthermore, conceptual spaces and predictive processing are very promising and should also be integrated with grounded cognition in the future.

Rapid purification and scale-up of tilianin using counter-current chromatography with rectangular horizontal tubing

In counter-current chromatography (CCC), linear scale-up is an ideal amplification strategy. However, when transferring from analytical to predictable preparative processes with high throughput, linear scale-up would be challenging due to limitations imposed by differences in instrument parameters, such as gravitational forces, tubing cross-section area, tubing length, column volume and flow rate. Some effective scale-up strategies have been studied for different instrument parameters, but so far, these scale-up works have only been tested on standard circular (SC) tubing.The previous research of our group found that rectangular horizontal (RH) tubing can double the separation efficiency compared with conventional SC tubing, and has industrial production potential. This paper used the separation of tilianin from Dracocephalum moldavica L. as an example to demonstrate how to scale up the optimized process from analytical SC tubing to preparative RH tubing. After systematic optimization of solvent systems, sample concentration and flow rate on the analytical CCC, the optimized parameters obtained were successfully transferred to the preparative CCC. The results showed that a crude sample of 2.07 g was successfully separated using a solvent system of n-hexane - ethyl acetate - ethanol - water (1:4:1:5, v/v/v/v) in reversed phase mode, and the three consecutive separations produced a total of 380 mg tilianin in 75 min with high purities of 98.3%, as analyzed by HPLC. The total throughput achieved from the analytical to semi-preparative scale was improved by 138 times (from 12 mg/h to 1.66 g/h), while the column volume was increased by only 46.5 times (from 15.5 mL to 720 mL). This is the successful application of CCC for the separation and purification of tilianin. Given that SC tubing is the traditional configuration for CCC columns, this study is a necessary step to prove the applicability of RH tubing columns for routine use and potential large-scale industrial applications.

Binocularly suppressed stimuli induce brain activities related to aesthetic emotions

IntroductionAesthetic emotions are a class of emotions aroused by evaluating aesthetically appealing objects or events. While evolutionary aesthetics suggests the adaptive roles of these emotions, empirical assessments are lacking. Previous neuroscientific studies have demonstrated that visual stimuli carrying evolutionarily important information induce neural responses even when presented non-consciously. To examine the evolutionary importance of aesthetic emotions, we conducted a neuroscientific study using magnetoencephalography (MEG) to measure induced neural responses to non-consciously presented portrait paintings categorised as biological and non-biological and examined associations between the induced responses and aesthetic ratings.MethodsMEG and pre-rating data were collected from 23 participants. The pre-rating included visual analogue scales for object saliency, facial saliency, liking, and beauty scores, in addition to ‘biologi-ness,’ which was used for subcategorising stimuli into biological and non-biological. The stimuli were presented non-consciously using a continuous flash suppression paradigm or consciously using binocular presentation without flashing masks, while dichotomic behavioural responses were obtained (beauty or non-beauty). Time-frequency decomposed MEG data were used for correlation analysis with pre-rating scores for each category.ResultsBehavioural data revealed that saliency scores of non-consciously presented stimuli influenced dichotomic responses (beauty or non-beauty). MEG data showed that non-consciously presented portrait paintings induced spatiotemporally distributed low-frequency brain activities associated with aesthetic ratings, which were distinct between the biological and non-biological categories and conscious and non-conscious conditions.ConclusionAesthetic emotion holds evolutionary significance for humans. Neural pathways are sensitive to visual images that arouse aesthetic emotion in distinct ways for biological and non-biological categories, which are further influenced by consciousness. These differences likely reflect the diversity in mechanisms of aesthetic processing, such as processing fluency, active elaboration, and predictive processing. The aesthetic processing of non-conscious stimuli appears to be characterised by fluency-driven affective processing, while top-down regulatory processes are suppressed. This study provides the first empirical evidence supporting the evolutionary significance of aesthetic processing.