Novel Cognitive Functions Arise at the Convergence of Macroscale Gradients

Functions in higher-order brain regions are the source of extensive debate. Although past trends have been to describe the brain—especially posterior cortical areas—in terms of a set of functional modules, a new emerging paradigm focuses on the integration of proximal functions. In this review, we synthesize emerging evidence that a variety of novel functions in the higher-order brain regions are due to convergence: convergence of macroscale gradients brings feature-rich representations into close proximity, presenting an opportunity for novel functions to arise. Using the TPJ as an example, we demonstrate that convergence is enabled via three properties of the brain: (1) hierarchical organization, (2) abstraction, and (3) equidistance. As gradients travel from primary sensory cortices to higher-order brain regions, information becomes abstracted and hierarchical, and eventually, gradients meet at a point maximally and equally distant from their sensory origins. This convergence, which produces multifaceted combinations, such as mentalizing another person's thought or projecting into a future space, parallels evolutionary and developmental characteristics in such regions, resulting in new cognitive and affective faculties.

Higher-order interaction of brain microstructural and functional connectome

Despite a relatively fixed anatomical structure, the human brain can support rich cognitive functions, triggering particular interest in investigating structure-function relationships. Myelin is a vital brain microstructure marker, yet the individual microstructure-function relationship is poorly understood. Here, we explore the brain microstructure-function relationships using a higher-order framework. Global (network-level) higher-order microstructure-function relationships negatively correlate with male participants' personality scores and decline with aging. Nodal (node-level) higher-order microstructure-function relationships are not aligned uniformly throughout the brain, being stronger in association cortices and lower in sensory cortices, showing gender differences. Notably, higher-order microstructure-function relationships are maintained from the whole-brain to local circuits, which uncovers a compelling and straightforward principle of brain structure-function interactions. Additionally, targeted artificial attacks can disrupt these higher-order relationships, and the main results are robust against several factors. Together, our results increase the collective knowledge of higher-order structure- function interactions that may underlie cognition, individual differences, and aging.

Sequence learning attenuates cortical responses in both frontal and perceptual cortices in early infancy

Prior work using a variety of imaging modalities has found that the frontal lobe is involved in higher-order sequential and statistical learning in young infants. Separate lines of work have found evidence of modulation of posterior sensory cortices during and after learning tasks. How do these processes relate together? Here, we build from a well-regarded EEG task that found evidence that the frontal lobe of young infants tracked higher-order sequential information (Basirat et al., 2014) and ask whether posterior perceptual cortices respond differentially to predictable vs. unpredictable sequences as well. First, replicating and extending past work, we found evidence of frontal lobe involvement in this task. Second, consistent with our hypotheses, we found that there is a corresponding attenuation of neural responses in the posterior perceptual cortices (temporal and occipital) to predictable compared to unpredictable audiovisual sequences. This study provides convergent evidence that the frontal lobe is crucial for higher-level learning in young infants but that it likely works as part of a large, distributed network of regions to modulate infant neural responses as a result of learning. Overall, this work challenges the view that the infant brain is not dynamic and disconnected, lacking in long-range neural connections. Instead, this paper reveals patterns of a highly dynamic and interconnected infant brain that change rapidly as a result of new, learnable experiences.

Overlapping Representation of Basic Tastes in the Human Gustatory Cortex

The topological representation is a fundamental property of human primary sensory cortices. The human gustatory cortex (GC) responds to the five basic tastes: bitter, salty, sweet, umami, and sour. However, the topological representation of the human gustatory cortex remains controversial. Through functional magnetic resonance imaging(fMRI) measurements of human responses to the five basic tastes, the current study aimed to delineate the taste representations within the GC. During the scanning, the volunteers tasted solutions of the five basic tastes, then washed their mouths with the tasteless solution. The solutions were then sucked from the volunteers' mouths, eliminating the action of swallowing. The results showed that the bilateral mid-insula activated most during the taste task, and the active areas were mainly in the precentral and central insular sulcus. However, the regions responding to the five basic tastes are substantially overlapped, and the analysis of contrasts between each taste response and the averaged response to the remaining tastes does not report any significant results. Furthermore, in the gustatory insular cortex, the multivariate pattern analysis (MVPA) was unable to distinguish the activation patterns of the basic tastes, suggesting the possibility of weakly clustered distribution of the taste-preference neural activities in the human insular cortex. In conclusion, the presented results suggest overlapping representations of the basic tastes in the human gustatory insular cortex.

Neural contributors to trauma resilience: a review of longitudinal neuroimaging studies

Resilience in the face of major life stressors is changeable over time and with experience. Accordingly, differing sets of neurobiological factors may contribute to an adaptive stress response before, during, and after the stressor. Longitudinal studies are therefore particularly effective in answering questions about the determinants of resilience. Here we provide an overview of the rapidly-growing body of longitudinal neuroimaging research on stress resilience. Despite lingering gaps and limitations, these studies are beginning to reveal individual differences in neural circuit structure and function that appear protective against the emergence of future psychopathology following a major life stressor. Here we outline a neural circuit model of resilience to trauma. Specifically, pre-trauma biomarkers of resilience show that an ability to modulate activity within threat and salience networks predicts fewer stress-related symptoms. In contrast, early post-trauma biomarkers of subsequent resilience or recovery show a more complex pattern, spanning a number of major circuits including attention and cognitive control networks as well as primary sensory cortices. This novel synthesis suggests stress resilience may be scaffolded by stable individual differences in the processing of threat cues, and further buttressed by post-trauma adaptations to the stressor that encompass multiple mechanisms and circuits. More attention and resources supporting this work will inform the targets and timing of mechanistic resilience-boosting interventions.

Altered effective connectivity in sensorimotor cortices is a signature of severity and clinical course in depression

Functional neuroimaging research on depression has traditionally targeted neural networks associated with the psychological aspects of depression. In this study, instead, we focus on alterations of sensorimotor function in depression. We used resting-state functional MRI data and dynamic causal modeling (DCM) to assess the hypothesis that depression is associated with aberrant effective connectivity within and between key regions in the sensorimotor hierarchy. Using hierarchical modeling of between-subject effects in DCM with parametric empirical Bayes we first established the architecture of effective connectivity in sensorimotor cortices. We found that in (interoceptive and exteroceptive) sensory cortices across participants, the backward connections are predominantly inhibitory, whereas the forward connections are mainly excitatory in nature. In motor cortices these parities were reversed. With increasing depression severity, these patterns are depreciated in exteroceptive and motor cortices and augmented in the interoceptive cortex, an observation that speaks to depressive symptomatology. We established the robustness of these results in a leave-one-out cross-validation analysis and by reproducing the main results in a follow-up dataset. Interestingly, with (nonpharmacological) treatment, depression-associated changes in backward and forward effective connectivity partially reverted to group mean levels. Overall, altered effective connectivity in sensorimotor cortices emerges as a promising and quantifiable candidate marker of depression severity and treatment response.

Genetic influences on brain representations of natural audiovisual experiences

Natural sensory inputs in everyday situations induce unique experiences that vary between individuals, even when inputs are identical. This experiential uniqueness stems from the representations of sensory signals in each brain. We investigated whether genetic factors control individual differences in sensory representations in the brain by studying the brain representations of natural audiovisual signals in twin-pairs. We measured the brain response to natural movies in twins using functional magnetic resonance imaging and quantified the genetic influence on the multivoxel-pattern similarity of movie clip representations between each twin. The whole-brain analysis revealed a genetic influence on the multivoxel-pattern similarity in widespread brain regions, which included the occipitotemporal sensory cortices as well as the frontoparietal association cortices and subcortical structures. Our findings suggest that genetic factors exhibit an effect on natural audiovisual signaling by controlling audiovisual representations in the brain.

Genetic influences on brain representations of natural audiovisual experiences

Natural sensory inputs in everyday situations induce unique experiences that vary between individuals, even when inputs are identical. This experiential uniqueness stems from the representations of sensory signals in each brain. We investigated whether genetic factors control individual differences in sensory representations in the brain by studying the brain representations of natural audiovisual signals in twin-pairs. We measured the brain response to natural movies in twins using functional magnetic resonance imaging and quantified the genetic influence on the multivoxel-pattern similarity of movie clip representations between each twin. The whole-brain analysis revealed a genetic influence on the multivoxel-pattern similarity in widespread brain regions, which included the occipitotemporal sensory cortices as well as the frontoparietal association cortices and subcortical structures. Our findings suggest that genetic factors exhibit an effect on natural audiovisual signaling by controlling audiovisual representations in the brain.

An Approach for Stabilizing Abnormal Neural Activity in ADHD Using Chaotic Resonance

Reduced integrity of neural pathways from frontal to sensory cortices has been suggested as a potential neurobiological basis of attention-deficit hyperactivity disorder. Neurofeedback has been widely applied to enhance reduced neural pathways in attention-deficit hyperactivity disorder by repeated training on a daily temporal scale. Clinical and model-based studies have demonstrated that fluctuations in neural activity underpin sustained attention deficits in attention-deficit hyperactivity disorder. These aberrant neural fluctuations may be caused by the chaos–chaos intermittency state in frontal-sensory neural systems. Therefore, shifting the neural state from an aberrant chaos–chaos intermittency state to a normal stable state with an optimal external sensory stimulus, termed chaotic resonance, may be applied in neurofeedback for attention-deficit hyperactivity disorder. In this study, we applied a neurofeedback method based on chaotic resonance induced by “reduced region of orbit” feedback signals in the Baghdadi model for attention-deficit hyperactivity disorder. We evaluated the stabilizing effect of reduced region of orbit feedback and its robustness against noise from errors in estimation of neural activity. The effect of chaotic resonance successfully shifted the abnormal chaos-chaos intermittency of neural activity to the intended stable activity. Additionally, evaluation of the influence of noise due to measurement errors revealed that the efficiency of chaotic resonance induced by reduced region of orbit feedback signals was maintained over a range of certain noise strengths. In conclusion, applying chaotic resonance induced by reduced region of orbit feedback signals to neurofeedback methods may provide a promising treatment option for attention-deficit hyperactivity disorder.