Rapid emergence of latent knowledge in the sensory cortex drives learning
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Latent circuit inference from heterogeneous neural responses during cognitive tasks
Higher cortical areas carry a wide range of sensory, cognitive and motor signals mixed in heterogeneous responses of single neurons tuned to multiple task variables. Dimensionality reduction methods that rely on correlations between neural activity and task variables leave unknown how heterogeneous responses arise from connectivity to drive behavior. We develop the latent circuit model, a dimensionality reduction approach in which task variables interact via low-dimensional recurrent connectivity to produce behavioral output. We apply the latent circuit inference to recurrent neural networks trained to perform a context-dependent decision-making task and find a suppression mechanism in which contextual representations inhibit irrelevant sensory responses. We validate this mechanism by confirming the behavioral effects of patterned connectivity perturbations predicted by the latent circuit model. We find similar suppression of irrelevant sensory responses in the prefrontal cortex of monkeys performing the same task. We show that incorporating causal interactions among task variables is critical for identifying behaviorally relevant computations from neural response data.
Alexithymia may explain the genetic relationship between autism and sensory sensitivity
Sensory symptoms are highly prevalent amongst autistic individuals and are now considered in the diagnostic criteria. Whilst evidence suggests a genetic relationship between autism and sensory symptoms, sensory symptoms are neither universal within autism nor unique to autism. One explanation for the heterogeneity within autism and commonality across conditions with respect to sensory symptoms, is that it is alexithymia (a condition associated with difficulties identifying and describing one’s own emotions) that has a genetic relationship with sensory symptoms, and that alexithymia commonly co-occurs with autism and with several other conditions. Using parent-reports of symptoms in a sample of adolescent twins, we sought to examine the genetic association between autism, alexithymia and sensory symptoms. Results showed that the genetic correlation between autism and sensory symptoms was not significant after controlling for alexithymia. In contrast, after controlling for variance in alexithymia explained by autism, the genetic correlation between alexithymia and sensory symptoms was significant (and the proportion of variance explained by genetic factors remained consistent after controlling for autism). These results suggest that 1) alexithymia and sensory symptoms share aetiology that is not accounted for by their association with autism and 2) that the genetic association between sensory symptoms and autism may be, in part or wholly, a product of alexithymia. Future research should seek to examine the contribution of alexithymia to sensory symptoms across other conditions.
Phase transitions of civil unrest across countries and time
Phase transitions, characterized by abrupt shifts between macroscopic patterns of organization, are ubiquitous in complex systems. Despite considerable research in the physical and natural sciences, the empirical study of this phenomenon in societal systems is relatively underdeveloped. The goal of this study is to explore whether the dynamics of collective civil unrest can be plausibly characterized as a sequence of recurrent phase shifts, with each phase having measurable and identifiable latent characteristics. Building on previous efforts to characterize civil unrest as a self-organized critical system, we introduce a macro-level statistical model of civil unrest and evaluate its plausibility using a comprehensive dataset of civil unrest events in 170 countries from 1946 to 2017. Our findings demonstrate that the macro-level phase model effectively captures the characteristics of civil unrest data from diverse countries globally and that universal mechanisms may underlie certain aspects of the dynamics of civil unrest. We also introduce a scale to quantify a country’s long-term unrest per unit of time and show that civil unrest events tend to cluster geographically, with the magnitude of civil unrest concentrated in specific regions. Our approach has the potential to identify and measure phase transitions in various collective human phenomena beyond civil unrest, contributing to a better understanding of complex social systems.
Person-centered analyses reveal that developmental adversity at moderate levels and neural threat/safety discrimination are associated with lower anxiety in early adulthood
Parsing heterogeneity in the nature of adversity exposure and neurobiological functioning may facilitate better understanding of how adversity shapes individual variation in risk for and resilience against anxiety. One putative mechanism linking adversity exposure with anxiety is disrupted threat and safety learning. Here, we applied a person-centered approach (latent profile analysis) to characterize patterns of adversity exposure at specific developmental stages and threat/safety discrimination in corticolimbic circuitry in 120 young adults. We then compared how the resultant profiles differed in anxiety symptoms. Three latent profiles emerged: (1) a group with lower lifetime adversity, higher neural activation to threat, and lower neural activation to safety; (2) a group with moderate adversity during middle childhood and adolescence, lower neural activation to threat, and higher neural activation to safety; and (3) a group with higher lifetime adversity exposure and minimal neural activation to both threat and safety. Individuals in the second profile had lower anxiety than the other profiles. These findings demonstrate how variability in within-person combinations of adversity exposure and neural threat/safety discrimination can differentially relate to anxiety, and suggest that for some individuals, moderate adversity exposure during middle childhood and adolescence could be associated with processes that foster resilience to future anxiety.
Effect of regional crosstalk between sympathetic nerves and sensory nerves on temporomandibular joint osteoarthritic pain
Temporomandibular joint osteoarthritis (TMJ-OA) is a common disease often accompanied by pain, seriously affecting physical and mental health of patients. Abnormal innervation at the osteochondral junction has been considered as a predominant origin of arthralgia, while the specific mechanism mediating pain remains unclear. To investigate the underlying mechanism of TMJ-OA pain, an abnormal joint loading model was used to induce TMJ-OA pain. We found that during the development of TMJ-OA, the increased innervation of sympathetic nerve of subchondral bone precedes that of sensory nerves. Furthermore, these two types of nerves are spatially closely associated. Additionally, it was discovered that activation of sympathetic neural signals promotes osteoarthritic pain in mice, whereas blocking these signals effectively alleviates pain. In vitro experiments also confirmed that norepinephrine released by sympathetic neurons promotes the activation and axonal growth of sensory neurons. Moreover, we also discovered that through releasing norepinephrine, regional sympathetic nerves of subchondral bone were found to regulate growth and activation of local sensory nerves synergistically with other pain regulators. This study identified the role of regional sympathetic nerves in mediating pain in TMJ-OA. It sheds light on a new mechanism of abnormal innervation at the osteochondral junction and the regional crosstalk between peripheral nerves, providing a potential target for treating TMJ-OA pain.
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