The Human Cerebellum as a Hub of the Predictive Brain

Music reward sensitivity is associated with greater information transfer capacity within dorsal and motor white matter networks in musicians

There are pronounced differences in the degree to which individuals experience music-induced pleasure which are linked to variations in structural connectivity between auditory and reward areas. However, previous studies exploring the link between white matter structure and music reward sensitivity (MRS) have relied on standard diffusion tensor imaging methods, which present challenges in terms of anatomical accuracy and interpretability. Further, the link between MRS and connectivity in regions outside of auditory-reward networks, as well as the role of musical training, have yet to be investigated. Therefore, we investigated the relation between MRS and structural connectivity in a large number of directly segmented and anatomically verified white matter tracts in musicians (n = 24) and non-musicians (n = 23) using state-of-the-art tract reconstruction and fixel-based analysis. Using a manual tract-of-interest approach, we additionally tested MRS-white matter associations in auditory-reward networks seen in previous studies. Within the musician group, there was a significant positive relation between MRS and fiber density and cross section in the right middle longitudinal fascicle connecting auditory and inferior parietal cortices. There were also positive relations between MRS and fiber-bundle cross-section in tracts connecting the left thalamus to the ventral precentral gyrus and connecting the right thalamus to the right supplementary motor area, however, these did not survive FDR correction. These results suggest that, within musicians, dorsal auditory and motor networks are crucial to MRS, possibly via their roles in top-down predictive processing and auditory-motor transformations.

The Predictive Role of the Posterior Cerebellum in the Processing of Dynamic Emotions

Recent studies have bolstered the important role of the cerebellum in high-level socio-affective functions. In particular, neuroscientific evidence shows that the posterior cerebellum is involved in social cognition and emotion processing, presumably through its involvement in temporal processing and in predicting the outcomes of social sequences. We used cerebellar transcranial random noise stimulation (ctRNS) targeting the posterior cerebellum to affect the performance of 32 healthy participants during an emotion discrimination task, including both static and dynamic facial expressions (i.e., transitioning from a static neutral image to a happy/sad emotion). ctRNS, compared to the sham condition, significantly reduced the participants' accuracy to discriminate static sad facial expressions, but it increased participants' accuracy to discriminate dynamic sad facial expressions. No effects emerged with happy faces. These findings may suggest the existence of two different circuits in the posterior cerebellum for the processing of negative emotional stimuli: a first-time-independent mechanism which can be selectively disrupted by ctRNS, and a second time-dependent mechanism of predictive "sequence detection" which can be selectively enhanced by ctRNS. This latter mechanism might be included among the cerebellar operational models constantly engaged in the rapid adjustment of social predictions based on dynamic behavioral information inherent to others' actions. We speculate that it might be one of the basic principles underlying the understanding of other individuals' social and emotional behaviors during interactions.

The cerebellum monitors errors and entrains executive networks

Frontal midline θ (Fmθ) activity occurs in medial prefrontal cortices (mPFC), when expected and actual outcomes conflict. Cerebellar forward models could inform the mPFC about this mismatch. To verify this hypothesis we correlated the mPFC activation during a visuomotor tracking task (VM) with performance accuracy, in control and cerebellum-lesioned participants. Additionally, purely visual (V), motor (M) and a motor plus visual tasks (V + M) were performed. An Independent Component, with a mid-frontal topography scalp map and equivalent dipole location in the dorsal anterior cingulate cortex accounted for Fmθ. In control participants Fmθ power increased during VM, when the error level crossed a threshold, but not during V + M, M and V. This increase scaled with tracking error. Fmθ power failed to increase during VM in cerebellar participants, even at highest tracking errors. Thus, in control participants, activation of mPFC is induced when a continuous monitoring effort for online error detection is required. The presence of a threshold error for enhancing Fmθ, suggests the switch from an automatic to an executive tracking control, which recruits the mPFC. Given that the cerebellum stores forward models, the absence of Fmθ increases during tracking errors in cerebellar participants indicates that cerebellum is necessary for supplying the mPFC with prediction error-related information. This occurs when automatic control falters, and a deliberate correction mechanism needs to be triggered. Further studies are needed to verify if this alerting function also occurs in the context of the other cognitive and non-cognitive functions in which the cerebellum is involved.

Emotional Resilience Predicts Preserved White Matter Microstructure Following Mild Traumatic Brain Injury

BACKGROUND

Adult patients with mild traumatic brain injury (mTBI) exhibit distinct phenotypes of emotional and cognitive functioning identified by latent profile analysis of clinical neuropsychological assessments. When discerned early after injury, these latent clinical profiles have been found to improve prediction of long-term outcomes from mTBI. The present study hypothesized that white matter (WM) microstructure is better preserved in an emotionally resilient mTBI phenotype compared with a neuropsychiatrically distressed mTBI phenotype.

METHODS

The present study used diffusion magnetic resonance imaging to investigate and compare WM microstructure in major association, projection, and commissural tracts between the two phenotypes and over time. Diffusion magnetic resonance images from 172 patients with mTBI were analyzed to compute individual diffusion tensor imaging maps at 2 weeks and 6 months after injury.

RESULTS

By comparing the diffusion tensor imaging parameters between the two phenotypes at global, regional, and voxel levels, emotionally resilient patients were shown to have higher axial diffusivity compared with neuropsychiatrically distressed patients early after mTBI. Longitudinal analysis revealed greater compromise of WM microstructure in neuropsychiatrically distressed patients, with greater decrease of global axial diffusivity and more widespread decrease of regional axial diffusivity during the first 6 months after injury compared with emotionally resilient patients.

CONCLUSIONS

These results provide neuroimaging evidence of WM microstructural differences underpinning mTBI phenotypes identified from neuropsychological assessments and show differing longitudinal trajectories of these biological effects. These findings suggest that diffusion magnetic resonance imaging can provide short- and long-term imaging biomarkers of resilience.

Two is company: The posterior cerebellum and sequencing for pairs versus individuals during social preference prediction

Previous studies have identified that the posterior cerebellum, which plays a role in processing temporal sequences in social events, is consistently and robustly activated when we predict future action sequences based on personality traits (Haihambo Haihambo et al. Social Cognitive and Affective Neuroscience 17(2), 241-251, 2022) and intentions (Haihambo et al. Cognitive, Affective, and Behavioral Neuroscience 23(2), 323-339, 2023). In the current study, we investigated whether these cerebellar areas are selectively activated when we predict the sequences of (inter)actions based on protagonists' preferences. For the first time, we also compared predictions based on person-to-person interactions or single person activities. Participants were instructed to predict actions of one single or two interactive protagonists by selecting them and putting them in the correct chronological order after being informed about one of the protagonists' preferences. These conditions were contrasted against nonsocial (involving objects) and nonsequencing (prediction without generating a sequence) control conditions. Results showed that the posterior cerebellar Crus 1, Crus 2, and lobule IX, alongside the temporoparietal junction and dorsal medial prefrontal cortex were more robustly activated when predicting sequences of behavior of two interactive protagonists, compared to one single protagonist and nonsocial objects. Sequence predictions based on one single protagonist recruited lobule IX activation in the cerebellum and more ventral areas of the medial prefrontal cortex compared to a nonsocial object. These cerebellar activations were not found when making predictions without sequences. Together, these findings suggest that cerebellar mentalizing areas are involved in social mentalizing processes which require temporal sequencing, especially when they involve social interactions, rather than behaviors of single persons.

Electrical stimulation of the cerebellum facilitates automatic but not controlled word retrieval

Recent research has indicated that the cerebellum is engaged in language functions, yet the role of the cerebellum in lexical-semantic memory is poorly understood. In a double-blind randomized controlled experiment, we therefore targeted the cerebellum by transcranial direct current stimulation (tDCS) to assess and compare the contribution of the cerebellar processing to automatic and controlled retrieval of words in healthy adults (n = 136). Anodal cerebellar tDCS facilitated retrieval of semantically related words in free-associative chains, which was not due to a non-specific acceleration of processing speed. The stimulation had no influence on controlled word retrieval that employed inhibition or switching. The effect of cathodal tDCS was opposite to the anodal stimulation, but statistically non-significant. Our data show that the cerebellum is engaged extracting associative information from the system of semantic representations, established and strengthened/automated by learning, and indicates a domain-general role of this structure in automation of behavior, cognition and language.

An information theoretic score for learning hierarchical concepts

How do humans learn the regularities of their complex noisy world in a robust manner? There is ample evidence that much of this learning and development occurs in an unsupervised fashion via interactions with the environment. Both the structure of the world as well as the brain appear hierarchical in a number of ways, and structured hierarchical representations offer potential benefits for efficient learning and organization of knowledge, such as concepts (patterns) sharing parts (subpatterns), and for providing a foundation for symbolic computation and language. A major question arises: what drives the processes behind acquiring such hierarchical spatiotemporal concepts? We posit that the goal of advancing one's predictions is a major driver for learning such hierarchies and introduce an information-theoretic score that shows promise in guiding the processes, and, in particular, motivating the learner to build larger concepts. We have been exploring the challenges of building an integrated learning and developing system within the framework of prediction games, wherein concepts serve as (1) predictors, (2) targets of prediction, and (3) building blocks for future higher-level concepts. Our current implementation works on raw text: it begins at a low level, such as characters, which are the hardwired or primitive concepts, and grows its vocabulary of networked hierarchical concepts over time. Concepts are strings or n-grams in our current realization, but we hope to relax this limitation, e.g., to a larger subclass of finite automata. After an overview of the current system, we focus on the score, named CORE. CORE is based on comparing the prediction performance of the system with a simple baseline system that is limited to predicting with the primitives. CORE incorporates a tradeoff between how strongly a concept is predicted (or how well it fits its context, i.e., nearby predicted concepts) vs. how well it matches the (ground) "reality," i.e., the lowest level observations (the characters in the input episode). CORE is applicable to generative models such as probabilistic finite state machines (beyond strings). We highlight a few properties of CORE with examples. The learning is scalable and open-ended. For instance, thousands of concepts are learned after hundreds of thousands of episodes. We give examples of what is learned, and we also empirically compare with transformer neural networks and n-gram language models to situate the current implementation with respect to state-of-the-art and to further illustrate the similarities and differences with existing techniques. We touch on a variety of challenges and promising future directions in advancing the approach, in particular, the challenge of learning concepts with a more sophisticated structure.

Resting state brain subnetwork relates to prosociality and compassion in adolescents

Adolescence is a crucial time for social development, especially for helping (prosocial) and compassionate behaviors; yet brain networks involved in adolescent prosociality and compassion currently remain underexplored. Here, we sought to evaluate a recently proposed domain-general developmental (Do-GooD) network model of prosocial cognition by relating adolescent functional and structural brain networks with prosocial and compassionate disposition. We acquired resting state fMRI and diffusion MRI from 95 adolescents (ages 14–19  years; 46 males; 49 females) along with self-report questionnaires assessing prosociality and compassion. We then applied the Network-Based Statistic (NBS) to inductively investigate whether there is a significant subnetwork related to prosociality and compassion while controlling for age and sex. Based on the Do-GooD model, we expected that this subnetwork would involve connectivity to the ventromedial prefrontal cortex (VMPFC) from three domain-general networks, the default mode network (DMN), the salience network, and the control network, as well as from the DMN to the mirror neuron systems. NBS revealed a significant functional (but not structural) subnetwork related to prosociality and compassion connecting 31 regions (p = 0.02), showing DMN and DLPFC connectivity to the VMPFC; DMN connectivity to mirror neuron systems; and connectivity between the DMN and cerebellum. These findings largely support and extend the Do-GooD model of prosocial cognition in adolescents by further illuminating network-based relationships that have the potential to advance our understanding of brain mechanisms of prosociality.

A Quantum Predictive Brain: Complementarity Between Top-Down Predictions and Bottom-Up Evidence

Predictive brain theory challenges the general assumption of a brain extracting knowledge from sensations and considers the brain as an organ of inference, actively constructing explanations about reality beyond its sensory evidence. Predictive brain has been formalized through Bayesian updating, where top-down predictions are compared with bottom-up evidence. In this article, we propose a different approach to predictive brain based on quantum probability-we call it Quantum Predictive Brain (QPB). QPB is consistent with the Bayesian framework, but considers it as a special case. The tenet of QPB is that top-down predictions and bottom-up evidence are complementary, as they cannot be co-jointly determined to pursue a univocal model of brain functioning. QPB can account for several high-order cognitive phenomena (which are problematic in current predictive brain theories) and offers new insights into the mechanisms of neural reuse.

Temporal Predictions in Space: Isochronous Rhythms Promote Forward Projections of the Body

A regular rhythmic stimulation increases people's ability to anticipate future events in time and to move their body in space. Temporal concepts are usually prescribed to spatial locations through a past-behind and future-ahead mapping. In this study, we tested the hypothesis that a regular rhythmic stimulation could promote the forward-body (i.e., toward the future) projections in the peri-personal space. In a Visual Approach/Avoidance by the Self Task (VAAST), participants (N = 24) observed a visual scene on the screen (i.e., a music studio with a metronome in the middle). They were exposed to 3 s of auditory isochronous or non-isochronous rhythms, after which they were asked to make as quickly as possible a perceptual judgment on the visual scene (i.e., whether the metronome pendulum was pointing to the right or left). The responses could trigger a forward or backward visual flow, i.e., approaching or moving them away from the scene. Results showed a significant interaction between the rhythmic stimulation and the movement projections (p < 0.001): participants were faster for responses triggering forward-body projections (but not backward-body projections) after the exposure to isochronous (but not non-isochronous) rhythm. By highlighting the strong link between isochronous rhythms and forward-body projections, these findings support the idea that temporal predictions driven by a regular auditory stimulation are grounded in a perception-action system integrating temporal and spatial information.

Environmentally Toxic Solid Nanoparticles in Noradrenergic and Dopaminergic Nuclei and Cerebellum of Metropolitan Mexico City Children and Young Adults with Neural Quadruple Misfolded Protein Pathologies and High Exposures to Nano Particulate Matter

Quadruple aberrant hyperphosphorylated tau, beta-amyloid, α-synuclein and TDP-43 neuropathology and metal solid nanoparticles (NPs) are documented in the brains of children and young adults exposed to Metropolitan Mexico City (MMC) pollution. We investigated environmental NPs reaching noradrenergic and dopaminergic nuclei and the cerebellum and their associated ultrastructural alterations. Here, we identify NPs in the locus coeruleus (LC), substantia nigrae (SN) and cerebellum by transmission electron microscopy (TEM) and energy-dispersive X-ray spectrometry (EDX) in 197 samples from 179 MMC residents, aged 25.9 ± 9.2 years and seven older adults aged 63 ± 14.5 years. Fe, Ti, Hg, W, Al and Zn spherical and acicular NPs were identified in the SN, LC and cerebellar neural and vascular mitochondria, endoplasmic reticulum, Golgi, neuromelanin, heterochromatin and nuclear pore complexes (NPCs) along with early and progressive neurovascular damage and cerebellar endothelial erythrophagocytosis. Strikingly, FeNPs 4 ± 1 nm and Hg NPs 8 ± 2 nm were seen predominantly in the LC and SN. Nanoparticles could serve as a common denominator for misfolded proteins and could play a role in altering and obstructing NPCs. The NPs/carbon monoxide correlation is potentially useful for evaluating early neurodegeneration risk in urbanites. Early life NP exposures pose high risk to brains for development of lethal neurologic outcomes. NP emissions sources ought to be clearly recognized, regulated, and monitored; future generations are at stake.