The Journal of neuroscience : the official journal of the Society for Neuroscience
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Slow oscillations during slow-wave sleep (SWS) may facilitate memory consolidation by regulating interactions between hippocampal and cortical networks. Slow oscillations appear as high-amplitude, synchronized EEG activity, corresponding to upstates of neuronal depolarization and downstates of hyperpolarization. Memory reactivations occur spontaneously during SWS, and can also be induced by presenting learning-related cues associated with a prior learning episode during sleep. This technique, targeted memory reactivation (TMR), selectively enhances memory consolidation. Given that memory reactivation is thought to occur preferentially during the slow-oscillation upstate, we hypothesized that TMR stimulation effects would depend on the phase of the slow oscillation. Participants learned arbitrary spatial locations for objects that were each paired with a characteristic sound (eg, cat-meow). Then, during SWS periods of an afternoon nap, one-half of the sounds were presented at low intensity. When object location memory was subsequently tested, recall accuracy was significantly better for those objects cued during sleep. We report here for the first time that this memory benefit was predicted by slow-wave phase at the time of stimulation. For cued objects, location memories were categorized according to amount of forgetting from pre- to post-nap. Conditions of high versus low forgetting corresponded to stimulation timing at different slow-oscillation phases, suggesting that learning-related stimuli were more likely to be processed and trigger memory reactivation when they occurred at the optimal phase of a slow oscillation. These findings provide insight into mechanisms of memory reactivation during sleep, supporting the idea that reactivation is most likely during cortical upstates. ⋯ Slow-wave sleep (SWS) is characterized by synchronized neural activity alternating between active upstates and quiet downstates. The slow-oscillation upstates are thought to provide a window of opportunity for memory consolidation, particularly conducive to cortical plasticity. Recent evidence shows that sensory cues associated with previous learning can be delivered subtly during SWS to selectively enhance memory consolidation. Our results demonstrate that this behavioral benefit is predicted by slow-oscillation phase at stimulus presentation time. Cues associated with high versus low forgetting based on analysis of subsequent recall performance were delivered at opposite slow-oscillation phases. These results provide evidence of an optimal slow-oscillation phase for memory consolidation during sleep, supporting the idea that memory processing occurs preferentially during cortical upstates.
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Given the information overload often imparted to human cognitive-processing systems, suppression of irrelevant and distracting information is essential for successful behavior. Using a hybrid block/event-related fMRI design, we characterized proactive and reactive brain mechanisms for filtering distracting stimuli. Participants performed a flanker task, discriminating the direction of a target arrow in the presence versus absence of congruent or incongruent flanking distracting arrows during either Pure blocks (distracters always absent) or Mixed blocks (distracters on 80% of trials). ⋯ The results suggest that when distraction is likely, a region in right frontal cortex proactively implements attentional control mechanisms to help filter out any distracting stimuli that might occur. In contrast, when distracting input occurs infrequently, this region is more reactively engaged to help limit the negative consequences of the distracters on behavioral performance. Our results thus help illuminate how the brain flexibly responds under differing attentional demands to engender effective behavior.
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The neural mechanisms underlying the development and maintenance of chronic neuropathic pain remain unclear. Evidence from human investigations suggests that neuropathic pain is associated with altered thalamic burst firing and thalamocortical dysrhythmia. Additionally, experimental animal investigations show that neuropathic pain is associated with altered infra-slow (<0.1 Hz) frequency oscillations within the dorsal horn and somatosensory thalamus. ⋯ In this study, we report in individuals with neuropathic pain increased oscillatory neural activity within the ascending pain pathway with evidence that these changes result from altered neural-astrocyte coupling. We propose a series of neural and glial events after nerve injury that result in the generation of altered thalamocortical activity and a persistent neuropathic pain state. Defining the underlying mechanisms responsible for neuropathic pain is critical if we are to develop more effective treatment regimens.
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Similar to other addiction disorders, the cues inherent in many gambling procedures are thought to play an important role in mediating their addictive nature. Animal models of gambling-related behavior, while capturing dimensions of economic decision making, have yet to address the impact that these salient cues may have in promoting maladaptive choice. Here, we determined whether adding win-associated audiovisual cues to a rat gambling task (rGT) would influence decision making. ⋯ This is the first clear demonstration that reward-paired cues can bias cost/benefit decision making against a subject's best interests in a manner concordant with elevated addiction susceptibility. Choice on the cued task was uniquely sensitive to modulation by D3 receptor ligands, yet these drugs did not alter decision making on the uncued task. The relatively unprecedented sensitivity of choice on the cued task to D3-receptor-mediated neurotransmission data suggest that similar neurobiological processes underlie the ability of cues to both bias animals toward risky options and facilitate drug addiction.
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Brain monitoring of errors in one's own and other's actions is crucial for a variety of processes, ranging from the fine-tuning of motor skill learning to important social functions, such as reading out and anticipating the intentions of others. Here, we combined immersive virtual reality and EEG recording to explore whether embodying the errors of an avatar by seeing it from a first-person perspective may activate the error monitoring system in the brain of an onlooker. We asked healthy participants to observe, from a first- or third-person perspective, an avatar performing a correct or an incorrect reach-to-grasp movement toward one of two virtual mugs placed on a table. At the end of each trial, participants reported verbally how much they embodied the avatar's arm. Ratings were maximal in first-person perspective, indicating that immersive virtual reality can be a powerful tool to induce embodiment of an artificial agent, even through mere visual perception and in the absence of any cross-modal boosting. Observation of erroneous grasping from a first-person perspective enhanced error-related negativity and medial-frontal theta power in the trials where human onlookers embodied the virtual character, hinting at the tight link between early, automatic coding of error detection and sense of embodiment. Error positivity was similar in 1PP and 3PP, suggesting that conscious coding of errors is similar for self and other. Thus, embodiment plays an important role in activating specific components of the action monitoring system when others' errors are coded as if they are one's own errors. ⋯ Detecting errors in other's actions is crucial for social functions, such as reading out and anticipating the intentions of others. Using immersive virtual reality and EEG recording, we explored how the brain of an onlooker reacted to the errors of an avatar seen from a first-person perspective. We found that mere observation of erroneous actions enhances electrocortical markers of error detection in the trials where human onlookers embodied the virtual character. Thus, the cerebral system for action monitoring is maximally activated when others' errors are coded as if they are one's own errors. The results have important implications for understanding how the brain can control the external world and thus creating new brain-computer interfaces.