The human arcuate fasciculus provides specific advantages to process complex sequential stimuli, not hierarchies in general

Hierarchies are sets or sequences of elements connected in the form of a rooted tree. They possess the key properties: (1) all elements are combined into one structure; (2) one element is superior to all others; and (3) no element is superior to itself (that is, there are no cycles, direct or indirect)” (Fitch & Martins, 2014). Defined as such, hierarchies exist in multiple domains. Linguistic syntax, and tonal and action sequences display a multi-layered set-of-sets organization. Moreover, social (e.g. family and company structures) and spatial hierarchies (e.g. landmark-based navigation) also display asymmetrical and multi-layered relations between different elements and sets of elements. Humans can represent the hierarchical structure in all these domains, and to extend their hierarchical depth when necessary. In the same way that we can extend any arbitrarily long sentence, we can also join any two arbitrarily complex social groups such as the armies of two countries to form a joint inter-national army (or inter-continental, inter-planetary, inter-galactic, etc.). Humans are especially capable of generating hierarchies. While we are able to assemble these kinds of structures in language, music and complex action (Fitch & Martins, 2014), analogous capacities are missing in other species (Fitch & Friederici, 2012), even though they can process simpler structures to some extent (Wilson, Marslen-Wilson, & Petkov, 2017). The cognitive and neural substrata supporting this capacity are a matter of active research and discussion. In neurolinguistics, this capacity is usually mapped to the ventral portions of Brodmann’s area 44 (BA44), and its interactions with the posterior Superior Temporal Sulcus (Fitch, 2017; Friederici, 2017; Milne et al., 2016). Interestingly, these two regions are connected by a fiber tract, called the Arcuate Fasciculus (AF), which is exceptionally well-developed in humans (Rilling et al., 2008). The available data suggests the hypothesis that the human ability to represent linguistic hierarchy evolved over a general sequence-processing machinery already available in the primate brain, to which a highly-developed AF was added (Wilson et al., 2017). Some extended this framework to music and action, where hierarchical processing also recruits regions within the Inferior Frontal Gyrus (Fadiga, Craighero, & D’Ausilio, 2009; Fitch & Martins, 2014). Here, we present a critical challenge to this hypothesis. Consider that there are two groups of domains in which humans can represent hierarchies. In the first, signals are composed of ordered sequences. Here, the serial order of the physical stimuli determines the perceived content or meaning (‘Mary likes John’ vs. ‘John Mary likes’). Even though linguistic hierarchies are not serial themselves, the signal through which they are communicated and decoded is. In the second group, the presentation order of the elements within the set does not necessarily determine the final structure (think of visual or spatial landscapes, or social structures). While the exact serial input order is crucial to determine the structure of ordered sequences, the same is not true for other hierarchical sets. This taxonomy is important because while BA44 and the AF seem important to process hierarchies within the first group, they are mostly absent in the second (Kumaran, Melo, & Düzel, 2012; Ligneul, Obeso, Ruff, & Dreher, 2016; Martins et al., 2014). The human ability to represent hierarchies in the visual, spatial and social domains is not supported by these mechanisms but rather by the hippocampus, medial Prefrontal cortex, and other structures. The same has been demonstrated for semantic hierarchies (Neville, et al, 2017). Taken together, these observations yield a logical puzzle: 1. Primates have a general system to process non-hierarchical sequences. 2. The emergence of the human BA44 and AF allowed for the capacity to represent hierarchies to evolve in language. 3. The human ability to represent hierarchies in some domains does not activate the brain areas connected via the AF. There are two ways to solve this puzzle: The first is to assume that the capacity to represent hierarchies evolved several times, once within language, and for other domains in other time periods. The second entails that the capacity to process hierarchies was first present in the visual, spatial and social domains and then specific changes in BA44 and AF made this capacity available for language (or in general for domains hinging on specific serial order of the input). In either case, BA 44 and AF seem to be important to process complex structured sequences, but not hierarchies in general. On the one hand, this neural system might be involved in the core generative capacity for hierarchical processing, but only in language. On the other hand, it might connect a previously available capacity to represent sets of sets with a robust capacity to parse sequential information. The latter would be especially important when sequences contain hierarchical relations between elements that are distant in the serial order

Neurophysiophenomenology – predicting emotional arousal from brain arousal in a virtual reality roller coaster

Arousal is a core affect constituted of both bodily and subjective states that prepares an agent to respond to events of the natural environment. While the peripheral physiological components of arousal have been examined also under naturalistic conditions, its neural correlates were suggested mainly on the basis of simplifed experimental designs.   We used virtual reality (VR) to present a highly immersive and contextually rich scenario of roller coaster rides to evoke naturalistic states of emotional arousal. Simultaneously, we recorded EEG to validate the suggested neural correlates of arousal in alpha frequency oscillations (8-12Hz) over temporo-parietal cortical areas. To fnd the complex link between these alpha components and the participants’ continuous subjective reports of arousal, we employed a set of complementary analytical methods coming from machine learning and deep learning

The impact of ischemic stroke on connectivity gradients

The functional organization of the brain can be represented as a low-dimensional space that reflects its macroscale hierarchy. The dimensions of this space, described as connectivity gradients, capture the similarity of areas' connections along a continuous space. Studying how pathological perturbations with known effects on functional connectivity affect these connectivity gradients provides support for their biological relevance. Previous work has shown that localized lesions cause widespread functional connectivity alterations in structurally intact areas, affecting a network of interconnected regions. By using acute stroke as a model of the effects of focal lesions on the connectome, we apply the connectivity gradient framework to depict how functional reorganization occurs throughout the brain, unrestricted by traditional definitions of functional network boundaries. We define a three-dimensional connectivity space template based on functional connectivity data from healthy controls. By projecting lesion locations into this space, we demonstrate that ischemic strokes result in dimension-specific alterations in functional connectivity over the first week after symptom onset. Specifically, changes in functional connectivity were captured along connectivity Gradients 1 and 3. The degree of functional connectivity change was associated with the distance from the lesion along these connectivity gradients (a measure of functional similarity) regardless of the anatomical distance from the lesion. Together, these results provide support for the biological validity of connectivity gradients and suggest a novel framework to characterize connectivity alterations after stroke

Interactions between cardiac activity and conscious somatosensory perception

Fluctuations in the heart's activity can modulate the access of external stimuli to consciousness. The link between perceptual awareness and cardiac signals has been investigated mainly in the visual and auditory domain. Here, we investigated whether the phase of the cardiac cycle and the prestimulus heart rate influence conscious somatosensory perception. We also tested how conscious detection of somatosensory stimuli affects the heart rate. Electrocardiograms (ECG) of 33 healthy volunteers were recorded while applying near‐threshold electrical pulses at a fixed intensity to the left index finger. Conscious detection was not uniformly distributed across the cardiac cycle but significantly higher in diastole than in systole. We found no evidence that the heart rate before a stimulus influenced its detection, but hits (correctly detected somatosensory stimuli) led to a more pronounced cardiac deceleration than misses. Our findings demonstrate interactions between cardiac activity and conscious somatosensory perception, which highlights the importance of internal bodily states for sensory processing beyond the auditory and visual domain

Weight loss reduces head motion: Re-visiting a major confound in neuroimaging

Head motion during magnetic resonance imaging (MRI) induces image artifacts that affect virtually every brain measure. In parallel, cross‐sectional observations indicate a correlation of head motion with age, psychiatric disease status and obesity, raising the possibility of a systematic artifact‐induced bias in neuroimaging outcomes in these conditions, due to the differences in head motion. Yet, a causal link between obesity and head motion has not been tested in an experimental design. Here, we show that a change in body mass index (BMI) (i.e., weight loss after bariatric surgery) systematically decreases head motion during MRI. In this setting, reduced imaging artifacts due to lower head motion might result in biased estimates of neural differences induced by changes in BMI. Overall, our finding urges the need to rigorously control for head motion during MRI to enable valid results of neuroimaging outcomes in populations that differ in head motion due to obesity or other conditions

Anodal transcranial direct current stimulation over S1 differentially modulates proprioceptive accuracy in young and old adults

Background: Proprioception is a prerequisite for successful motor control but declines throughout the lifespan. Brain stimulation techniques such as anodal transcranial direct current stimulation (a-tDCS) are capable of enhancing sensorimotor performance across different tasks and age groups. Despite such growing evidence for a restorative potential of tDCS, its impact on proprioceptive accuracy has not been studied in detail yet. Objective: This study investigated online effects of a-tDCS over S1 on proprioceptive accuracy in young (YA) and old healthy adults (OA). Methods: The effect of 15 min of a-tDCS vs. sham on proprioceptive accuracy was assessed in a cross-over, double blind experiment in both age groups. Performance changes were tested using an arm position matching task in a robotic environment. Electrical field (EF) strengths in the target area S1 and control areas were assessed based on individualized simulations. Results: a-tDCS elicited differential changes in proprioceptive accuracy and EF strengths in the two groups: while YA showed a slight improvement, OA exhibited a decrease in performance during a-tDCS. Stronger EF were induced in target S1 and control areas in the YA group. However, no relationship between EF strength and performance change was found. Conclusion: a-tDCS over S1 elicits opposing effects on proprioceptive accuracy as a function of age, a result that is important for future studies investigating the restorative potential of a-tDCS in healthy aging and in the rehabilitation of neurological diseases that occur at advanced age. Modeling approaches could help elucidate the relationship between tDCS protocols, brain structure and performance modulation

Investigating Neuroanatomical Features in Top Athletes at the Single Subject Level.

In sport events like Olympic Games or World Championships competitive athletes keep pushing the boundaries of human performance. Compared to team sports, high achievements in many athletic disciplines depend solely on the individual's performance. Contrasting previous research looking for expertise-related differences in brain anatomy at the group level, we aim to demonstrate changes in individual top athlete's brain, which would be averaged out in a group analysis. We compared structural magnetic resonance images (MRI) of three professional track-and-field athletes to age-, gender- and education-matched control subjects. To determine brain features specific to these top athletes, we tested for significant deviations in structural grey matter density between each of the three top athletes and a carefully matched control sample. While total brain volumes were comparable between athletes and controls, we show regional grey matter differences in striatum and thalamus. The demonstrated brain anatomy patterns remained stable and were detected after 2 years with Olympic Games in between. We also found differences in the fusiform gyrus in two top long jumpers. We interpret our findings in reward-related areas as correlates of top athletes' persistency to reach top-level skill performance over years

Gender influences on brain responses to errors and post-error adjustments

Sexual dimorphisms have been observed in many species, including humans, and extend to the prevalence and presentation of important mental disorders associated with performance monitoring malfunctions. However, precisely which underlying differences between genders contribute to the alterations observed in psychiatric diseases is unknown. Here, we compare behavioural and neural correlates of cognitive control functions in 438 female and 436 male participants performing a flanker task while EEG was recorded. We found that males showed stronger performance-monitoring-related EEG amplitude modulations which were employed to predict subjects’ genders with ~72% accuracy. Females showed more post-error slowing, but both samples did not differ in regard to response-conflict processing and coupling between the error-related negativity (ERN) and consecutive behavioural slowing. Furthermore, we found that the ERN predicted consecutive behavioural slowing within subjects, whereas its overall amplitude did not correlate with post-error slowing across participants. These findings elucidate specific gender differences in essential neurocognitive functions with implications for clinical studies. They highlight that within- and between-subject associations for brain potentials cannot be interpreted in the same way. Specifically, despite higher general amplitudes in males, it appears that the dynamics of coupling between ERN and post-error slowing between men and women is comparable