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132).TCC exhibited stronger effects on spontaneous neural activity than the BW condition, as reflected in significantly increased fALFF in the left medial superior frontal gyrus (Cohen's d = 0.862). There was a significant positive correlation between the increase in fALFF in the left medial superior frontal gyrus and the enhancement in inhibitory control performance. The change in fALFF in the left medial superior frontal gyrus was able to explain the change in inhibitory control performance induced by TCC. In conclusion, our results indicated that 8 weeks of TCC intervention could improve processing efficiency related to inhibitory control and alter spontaneous neural activity in young adults, and TCC had potential advantages over BW intervention for optimizing spontaneous neural activity.Memories of the past can guide humans to avoid harm. The logical consequence of this is if memories are changed, avoidance behavior should be affected. More than 80 years of false memory research has shown that people's memory can be re-constructed or distorted by receiving suggestive false feedback. The current study examined whether manipulating people's memories of learned associations would impact fear related behavior. A modified sensory preconditioning paradigm of fear learning was used. Critically, in a memory test after fear learning, participants received verbal false feedback to change their memory associations. After receiving the false feedback, participants' beliefs and memories ratings for learned associations decreased significantly compared to the no feedback condition. Furthermore, in the false feedback condition, participants no longer showed avoidance to fear conditioned stimuli and relevant subjective fear ratings dropped significantly. Our results suggest that manipulating memory associations might minimize avoidance behavior in fear conditioning. These data also highlight the role of memory in higher order conditioning.The early life environment markedly influences brain and behavioral development, with adverse experiences associated with increased risk of anxiety and depressive phenotypes, particularly in females. Indeed, early life adversity (ELA) in humans (i.e., caregiver deprivation, maltreatment) and rodents (i.e., maternal separation, resource scarcity) is associated with sex-specific emergence of anxious and depressive behaviors. Although these disorders show clear sex differences in humans, little attention has been paid toward evaluating sex as a biological variable in models of affective dysfunction; however, recent rodent work suggests sex-specific effects. Two widely used rodent models of ELA approximate caregiver deprivation (i.e., maternal separation) and resource scarcity (i.e., limited bedding). While these approaches model aspects of ELA experienced in humans, they span different portions of the pre-weaning developmental period and may therefore differentially contribute to underlying mechanistic risk. Thimbined role of PV and sex hormones driving differences in behavioral outcomes associated with affective dysfunction following ELA. This review evaluates the literature across models of ELA to characterize neural (PV) and behavioral (anxiety- and depressive-like) outcomes as a function of sex and age. Additionally, we detail a putative mechanistic role of PV on ELA-related outcomes and discuss evidence suggesting hormone influences on PV expression/function which may help to explain sex differences in ELA outcomes.Negative allosteric modulators, such as lynx1 and lynx2, directly interact with nicotinic acetylcholine receptors (nAChRs). The nAChRs are integral to cholinergic signaling in the brain and have been shown to mediate different aspects of cognitive function. Given the interaction between lynx proteins and these receptors, we examined whether these endogenous negative allosteric modulators are involved in cognitive behaviors associated with cholinergic function. We found both cell-specific and overlapping expression patterns of lynx1 and lynx2 mRNA in brain regions associated with cognition, learning, memory, and sensorimotor processing, including the prefrontal cortex (PFC), cingulate cortex, septum, hippocampus, amygdala, striatum, and pontine nuclei. Since lynx proteins are thought to play a role in conditioned associations and given the expression patterns across brain regions, we first assessed whether lynx knockout mice would differ in a cognitive flexibility task. We found no deficits in reversal learning in either the lynx1-/- or lynx2-/- knockout mice. Thereafter, sensorimotor gating was examined with the prepulse inhibition (PPI) assessment. Interestingly, we found that both male and female lynx1-/- mice exhibited a deficit in the PPI behavioral response. Given the comparable expression of lynx2 in regions involved in sensorimotor gating, we then examined whether removal of the lynx2 protein would lead to similar behavioral effects. Unexpectedly, we found that while male lynx2-/- mice exhibited a decrease in the baseline startle response, no differences were found in sensorimotor gating for either male or female lynx2-/- mice. Taken together, these studies provide insight into the expression patterns of lynx1 and lynx2 across multiple brain regions and illustrate the modulatory effects of the lynx1 protein in sensorimotor gating.Maternal separation has been shown to disrupt proper brain development and maturation, having profound consequences on the neuroendocrine systems in charge of the stress response, and has been shown to induce behavioral and cognitive abnormalities. At the behavioral level, maternal separation has been shown to increase offensive play-fighting in juvenile individuals and reduce social interest in adulthood. Since most of the studies that have evaluated the consequences of maternal separation on social behavior have focused on behavioral analysis, there is a need for a further understanding of the neuronal mechanisms underlying the changes in social behavior induced by maternal separation. Therefore, the aim of the present research was to assess the long-term effects of maternal separation on social interaction behavior and to assess the activity of several brain regions involved in the processing of social cues and reward upon social novelty exposure, using c-Fos immunohistochemistry as a marker of neuronal acted to be linked to early life adversity.While machine learning techniques have been transformative in solving a range of problems, an important challenge is to understand why they arrive at the decisions they output. Some have argued that this necessitates augmenting machine intelligence with understanding such that, when queried, a machine is able to explain its behaviour (i.e., explainable AI). In this article, we address the issue of machine understanding from the perspective of active inference. This paradigm enables decision making based upon a model of how data are generated. The generative model contains those variables required to explain sensory data, and its inversion may be seen as an attempt to explain the causes of these data. Here we are interested in explanations of one's own actions. This implies a deep generative model that includes a model of the world, used to infer policies, and a higher-level model that attempts to predict which policies will be selected based upon a space of hypothetical (i.e., counterfactual) explanations-and which can subsequently be used to provide (retrospective) explanations about the policies pursued. We illustrate the construct validity of this notion of understanding in relation to human understanding by highlighting the similarities in computational architecture and the consequences of its dysfunction.The brain is a prediction machine. Yet the world is never entirely predictable, for any animal. Unexpected events are surprising, and this typically evokes prediction error signatures in mammalian brains. In humans such mismatched expectations are often associated with an emotional response as well, and emotional dysregulation can lead to cognitive disorders such as depression or schizophrenia. Emotional responses are understood to be important for memory consolidation, suggesting that positive or negative 'valence' cues more generally constitute an ancient mechanism designed to potently refine and generalize internal models of the world and thereby minimize prediction errors. On the other hand, abolishing error detection and surprise entirely (as could happen by generalization or habituation) is probably maladaptive, as this might undermine the very mechanism that brains use to become better prediction machines. This paradoxical view of brain function as an ongoing balance between prediction and surprise suggests a compelling approach to study and understand the evolution of consciousness in animals. In particular, this view may provide insight into the function and evolution of 'active' sleep. Here, we propose that active sleep - when animals are behaviorally asleep but their brain seems awake - is widespread beyond mammals and birds, and may have evolved as a mechanism for optimizing predictive processing in motile creatures confronted with constantly changing environments. To explore our hypothesis, we progress from humans to invertebrates, investigating how a potential role for rapid eye movement (REM) sleep in emotional regulation in humans could be re-examined as a conserved sleep function that co-evolved alongside selective attention to maintain an adaptive balance between prediction and surprise. This view of active sleep has some interesting implications for the evolution of subjective awareness and consciousness in animals.The term "regenerative medicine" (RM) indicates an emerging trend in biomedical sciences that aims at replacing, engineering, or regenerating human cells, tissues, or organs to restore or establish normal function. So far, the focus of RM has been the physical body. Neuroscience, however, is now suggesting that mental disorders can be broadly characterized by a dysfunction in the way the brain computes and integrates the representations of the inner and outer body across time [bodily self-consciousness (BSC)]. In this perspective, we proposed a new kind of clinical intervention, i.e., "Regenerative Virtual Therapy" (RVT), which integrates knowledge from different disciplines, from neuroscience to computational psychiatry, to regenerate a distorted or faulty BSC. The main goal of RVT was to use technology-based somatic modification techniques to restructure the maladaptive bodily representations behind a pathological condition. Specifically, starting from a Bayesian model of our BSC (i.e., body matrix), we suggested the use of mindful attention, cognitive reappraisal, and brain stimulation techniques merged with high-rewarding and novel synthetic multisensory bodily experience (i.e., a virtual reality full-body illusion in sync with a low predictabIlity interoceptive modulation) to rewrite a faulty experience of the body and to regenerate the wellbeing of an individual. The use of RVT will also offer an unprecedented experimental overview of the dynamics of our bodily representations, allowing the reverse-engineering of their functioning for hacking them using advanced technologies.