Emerging Theories of Allostatic-Interoceptive Overload in Neurodegeneration.

Recent integrative multilevel models offer novel insights into the etiology and course of neurodegenerative conditions. The predictive coding of allostatic-interoception theory posits that the brain adapts to environmental demands by modulating internal bodily signals through the allostatic-interoceptive system. Specifically, a domain-general allostatic-interoceptive network exerts adaptive physiological control by fine-tuning initial top-down predictions and bottom-up peripheral signaling. In this context, adequate adaptation implies the minimization of prediction errors thereby optimizing energy expenditure. Abnormalities in top-down interoceptive predictions or peripheral signaling can trigger allostatic overload states, ultimately leading to dysregulated interoceptive and bodily systems (endocrine, immunological, circulatory, etc.). In this context, environmental stress, social determinants of health, and harmful exposomes (i.e., the cumulative life-course exposition to different environmental stressors) may interact with physiological and genetic factors, dysregulating allostatic interoception and precipitating neurodegenerative processes. We review the allostatic-interoceptive overload framework across different neurodegenerative diseases, particularly in the behavioral variant frontotemporal dementia (bvFTD). We describe how concepts of allostasis and interoception could be integrated with principles of predictive coding to explain how the brain optimizes adaptive responses, while maintaining physiological stability through feedback loops with multiple organismic systems. Then, we introduce the model of allostatic-interoceptive overload of bvFTD and discuss its implications for the understanding of pathophysiological and neurocognitive abnormalities in multiple neurodegenerative conditions.

Theoretical-Methodological Foundations for the Global Integration Method (Método de Integração Global-MIG) in the Treatment of Autism Spectrum Disorder.

Currently, there is no intervention model for autism spectrum disorder (ASD) that addresses all levels and factors of the International Classification of Functioning, Disability and Health (ICF, WHO). The most researched programs focus on naturalistic, developmental and behavioral approaches to socio-communication. Less attention has been paid to motor and environmental reactivity aspects (behavior/interest restriction and sensory reactivity). The evidence rationale for the Global Integration Method (MIG, "Método de Integração Global"), a model addressing sensorimotor reactivity in addition to socio-communication, is presented. MIG is an integrative, interdisciplinary, family-oriented intervention and naturalistic program that addresses all levels and moderating factors of ASD's impact. MIG's theoretical rationale is based on the predictive coding impairment and embodied cognition hypotheses. MIG incorporates both bottom-up (flexible therapeutic suit, social-motor synchronization) and top-down (schematic social information processing, narratives, imagery) strategies to promote the building and use of accurate, flexible and context-sensitive internal predictive models. MIG is based on the premises that predictive coding improves both socio-communication and environmental reactivity, and that the postural stabilization provided by the flexible therapeutic suit frees information processing resources for socio-cognitive learning. MIG builds on interdisciplinary, professionally and parentally mediated work based on behavioral principles of intensive training in a situated environment.

Detección de novedad y codificación predictiva en el sistema auditivo: Impacto clínico en disfunciones auditivas y vestibulares. Revisión de la literatura / Deviance detection and predictive coding in the auditory system: Clinical impact in auditory and vestibular dysfunctions

Una propiedad fundamental de los sistemas sensoriales es su capacidad para detectar estímulos novedosos en el entorno. El sistema nervioso posee neuronas que disminuyen su respuesta a los estímulos sonoros que se repiten a lo largo del tiempo y otras neuronas que aumentan su frecuencia de disparo ante estímulos novedosos, siendo la diferencia entre ambas respuestas conocida como adaptación-específica a estímulos. En las últimas décadas, se ha propuesto que el cerebro establece, continuamente, predicciones de los estímulos novedosos y del entorno basándose en sus experiencias previas y en modelos de representación internos, teoría denominada codificación predictiva. En esta revisión, abordaremos algunos conceptos de la adaptación-específica a estímulos y codificación predictiva, centrándonos principalmente en el sistema auditivo. Por último, propondremos una explicación teórica basada en el marco de la codificación predictiva para algunas disfunciones neuropsiquiátricas, auditivas y vestibulares.

A fundamental property of sensory systems is their ability to detect novel stimuli in the environment. The nervous system possesses neurons that decrease their response to sound stimuli that are repeated over time and other neurons that increase their firing rate to novel stimuli, the difference between the two responses being known as stimulus-specific adaptation. In recent decades, it has been proposed that the brain continuously makes predictions of novel stimuli and the environment based on its previous experiences and internal representational models, a theory called predictive coding. In this review, we will address some concepts of stimulus-specific adaptation and predictive coding, focusing mainly on the auditory system. Finally, we will propose a theoretical explanation based on the predictive coding framework for some neuropsychiatric, auditory, and vestibular dysfunctions.

A predictive coding framework of allostatic-interoceptive overload in frontotemporal dementia.

Recent allostatic-interoceptive explanations using predictive coding models propose that efficient regulation of the body's internal milieu is necessary to correctly anticipate environmental needs. We review this framework applied to understanding behavioral variant frontotemporal dementia (bvFTD) considering both allostatic overload and interoceptive deficits. First, we show how this framework could explain divergent deficits in bvFTD (cognitive impairments, behavioral maladjustment, brain atrophy, fronto-insular-temporal network atypicality, aberrant interoceptive electrophysiological activity, and autonomic disbalance). We develop a set of theory-driven predictions based on levels of allostatic interoception associated with bvFTD phenomenology and related physiopathological mechanisms. This approach may help further understand the disparate behavioral and physiopathological dysregulations of bvFTD, suggesting targeted interventions and strengthening clinical models of neurological and psychiatric disorders.

Allostatic-Interoceptive Overload in Frontotemporal Dementia.

BACKGROUND: The predictive coding theory of allostatic-interoceptive load states that brain networks mediating autonomic regulation and interoceptive-exteroceptive balance regulate the internal milieu to anticipate future needs and environmental demands. These functions seem to be distinctly compromised in behavioral variant frontotemporal dementia (bvFTD), including alterations of the allostatic-interoceptive network (AIN). Here, we hypothesize that bvFTD is typified by an allostatic-interoceptive overload. METHODS: We assessed resting-state heartbeat evoked potential (rsHEP) modulation as well as its behavioral and multimodal neuroimaging correlates in patients with bvFTD relative to healthy control subjects and patients with Alzheimer's disease (N = 94). We measured 1) resting-state electroencephalography (to assess the rsHEP, prompted by visceral inputs and modulated by internal body sensing), 2) associations between rsHEP and its neural generators (source location), 3) cognitive disturbances (cognitive state, executive functions, facial emotion recognition), 4) brain atrophy, and 5) resting-state functional magnetic resonance imaging functional connectivity (AIN vs. control networks). RESULTS: Relative to healthy control subjects and patients with Alzheimer's disease, patients with bvFTD presented more negative rsHEP amplitudes with sources in critical hubs of the AIN (insula, amygdala, somatosensory cortex, hippocampus, anterior cingulate cortex). This exacerbated rsHEP modulation selectively predicted the patients' cognitive profile (including cognitive decline, executive dysfunction, and emotional impairments). In addition, increased rsHEP modulation in bvFTD was associated with decreased brain volume and connectivity of the AIN. Machine learning results confirmed AIN specificity in predicting the bvFTD group. CONCLUSIONS: Altogether, these results suggest that bvFTD may be characterized by an allostatic-interoceptive overload manifested in ongoing electrophysiological markers, brain atrophy, functional networks, and cognition.

Predictive processing: Is the future just a memory?

Predictive processing seems like a radical departure from traditional theories of information processing in the brain, but a broader view of predictions highlights many similarities with standard frameworks. Predictive processing is memory and competitive bias in a new outlook-and we should use this correspondence to advance research on both fronts.

Forensic Speaker Verification Using Ordinary Least Squares.

In Brazil, the recognition of speakers for forensic purposes still relies on a subjectivity-based decision-making process through a results analysis of untrustworthy techniques. Owing to the lack of a voice database, speaker verification is currently applied to samples specifically collected for confrontation. However, speaker comparative analysis via contested discourse requires the collection of an excessive amount of voice samples for a series of individuals. Further, the recognition system must inform who is the most compatible with the contested voice from pre-selected individuals. Accordingly, this paper proposes using a combination of linear predictive coding (LPC) and ordinary least squares (OLS) as a speaker verification tool for forensic analysis. The proposed recognition technique establishes confidence and similarity upon which to base forensic reports, indicating verification of the speaker of the contested discourse. Therefore, in this paper, an accurate, quick, alternative method to help verify the speaker is contributed. After running seven different tests, this study preliminarily achieved a hit rate of 100% considering a limited dataset (Brazilian Portuguese). Furthermore, the developed method extracts a larger number of formants, which are indispensable for statistical comparisons via OLS. The proposed framework is robust at certain levels of noise, for sentences with the suppression of word changes, and with different quality or even meaningful audio time differences.

Temporal Uncertainty and Temporal Estimation Errors Affect Insular Activity and the Frontostriatal Indirect Pathway during Action Update: A Predictive Coding Study.

Action update, substituting a prepotent behavior with a new action, allows the organism to counteract surprising environmental demands. However, action update fails when the organism is uncertain about when to release the substituting behavior, when it faces temporal uncertainty. Predictive coding states that accurate perception demands minimization of precise prediction errors. Activity of the right anterior insula (rAI) is associated with temporal uncertainty. Therefore, we hypothesize that temporal uncertainty during action update would cause the AI to decrease the sensitivity to ascending prediction errors. Moreover, action update requires response inhibition which recruits the frontostriatal indirect pathway associated with motor control. Therefore, we also hypothesize that temporal estimation errors modulate frontostriatal connections. To test these hypotheses, we collected fMRI data when participants performed an action-update paradigm within the context of temporal estimation. We fit dynamic causal models to the imaging data. Competing models comprised the inferior occipital gyrus (IOG), right supramarginal gyrus (rSMG), rAI, right presupplementary motor area (rPreSMA), and the right striatum (rSTR). The winning model showed that temporal uncertainty drove activity into the rAI and decreased insular sensitivity to ascending prediction errors, as shown by weak connectivity strength of rSMG→rAI connections. Moreover, temporal estimation errors weakened rPreSMA→rSTR connections and also modulated rAI→rSTR connections, causing the disruption of action update. Results provide information about the neurophysiological implementation of the so-called horse-race model of action control. We suggest that, contrary to what might be believed, unsuccessful action update could be a homeostatic process that represents a Bayes optimal encoding of uncertainty.

A touch with words: Dynamic synergies between manual actions and language.

Manual actions are a hallmark of humanness. Their underlying neural circuitry gives rise to species-specific skills and interacts with language processes. In particular, multiple studies show that hand-related expressions - verbal units evoking manual activity - variously affect concurrent manual actions, yielding apparently controversial results (interference, facilitation, or null effects) in varied time windows. Through a systematic review of 108 experiments, we show that such effects are driven by several factors, such as the level of verbal processing, action complexity, and the time-lag between linguistic and motor processes. We reconcile key empirical patterns by introducing the Hand-Action-Network Dynamic Language Embodiment (HANDLE) model, an integrative framework based on neural coupling dynamics and predictive-coding principles. To conclude, we assess HANDLE against the backdrop of other action-cognition theories, illustrate its potential applications to understand high-level deficits in motor disorders, and discuss key challenges for further development. In sum, our work aligns with the 'pragmatic turn', moving away from passive and static representationalist perspectives to a more dynamic, enactive, and embodied conceptualization of cognitive processes.

Functional constraints in the evolution of brain circuits.

Regardless of major anatomical and neurodevelopmental differences, the vertebrate isocortex shows a remarkably well-conserved organization. In the isocortex, reciprocal connections between excitatory and inhibitory neurons are distributed across multiple layers, encompassing modular, dynamical and recurrent functional networks during information processing. These dynamical brain networks are often organized in neuronal assemblies interacting through rhythmic phase relationships. Accordingly, these oscillatory interactions are observed across multiple brain scale levels, and they are associated with several sensory, motor, and cognitive processes. Most notably, oscillatory interactions are also found in the complete spectrum of vertebrates. Yet, it is unknown why this functional organization is so well conserved in evolution. In this perspective, we propose some ideas about how functional requirements of the isocortex can account for the evolutionary stability observed in microcircuits across vertebrates. We argue that isocortex architectures represent canonical microcircuits resulting from: (i) the early selection of neuronal architectures based on the oscillatory excitatory-inhibitory balance, which lead to the implementation of compartmentalized oscillations and (ii) the subsequent emergence of inferential coding strategies (predictive coding), which are able to expand computational capacities. We also argue that these functional constraints may be the result of several advantages that oscillatory activity contributes to brain network processes, such as information transmission and code reliability. In this manner, similarities in mesoscale brain circuitry and input-output organization between different vertebrate groups may reflect evolutionary constraints imposed by these functional requirements, which may or may not be traceable to a common ancestor.

Temporal prediction errors modulate task-switching performance.

We have previously shown that temporal prediction errors (PEs, the differences between the expected and the actual stimulus' onset times) modulate the effective connectivity between the anterior cingulate cortex and the right anterior insular cortex (rAI), causing the activity of the rAI to decrease. The activity of the rAI is associated with efficient performance under uncertainty (e.g., changing a prepared behavior when a change demand is not expected), which leads to hypothesize that temporal PEs might disrupt behavior-change performance under uncertainty. This hypothesis has not been tested at a behavioral level. In this work, we evaluated this hypothesis within the context of task switching and concurrent temporal predictions. Our participants performed temporal predictions while observing one moving ball striking a stationary ball which bounced off with a variable temporal gap. Simultaneously, they performed a simple color comparison task. In some trials, a change signal made the participants change their behaviors. Performance accuracy decreased as a function of both the temporal PE and the delay. Explaining these results without appealing to ad hoc concepts such as "executive control" is a challenge for cognitive neuroscience. We provide a predictive coding explanation. We hypothesize that exteroceptive and proprioceptive minimization of PEs would converge in a fronto-basal ganglia network which would include the rAI. Both temporal gaps (or uncertainty) and temporal PEs would drive and modulate this network respectively. Whereas the temporal gaps would drive the activity of the rAI, the temporal PEs would modulate the endogenous excitatory connections of the fronto-striatal network. We conclude that in the context of perceptual uncertainty, the system is not able to minimize perceptual PE, causing the ongoing behavior to finalize and, in consequence, disrupting task switching.

Dynamical predictions of insular hubs for social cognition and their application to stroke.

The insular cortex (IC) is considered a rich hub for context-sensitive emotions/social cognition. Patients with focal IC stroke provide unique opportunities to study socio-emotional processes. Nevertheless, Couto et al. (2013b) have recently reported controversial results regarding IC involvement in emotion and social cognition. Similarly, patients with similar lesions show high functional variability, ranging from almost totally preserved to strongly impaired behavior. Critical evidence suggests that the variability of these patients in the above domains can be explained by enhanced neuroplasticity, compensatory processes, and functional remapping after stroke. Therefore, socio-emotional processes would depend on long-distance connections between the IC and frontotemporal regions. We propose that predictive coding and effective connectivity represent a novel approach to explore functional connectivity and assess compensatory, contralateral, and subsidiary network differences among focal stroke patients. This approach would help explain why socio-emotional performance is so variable within this population.