The default mode network (DMN) is a set of functionally connected brain regions which shows deactivation (task induced deactivation, TID) during a cognitive task. Evidence shows an age-related decline in task-load-related modulation of the activity within the DMN during cognitive tasks. However, the effect of age on the functional coupling within the DMN and their relation to cognitive performance has hitherto been unexplored. Using functional magnetic resonance imaging, we investigated functional connectivity within the DMN in older and younger subjects during a working memory task with increasing task load. Older adults showed decreased connectivity and ability to suppress low frequency oscillations of the DMN. Additionally, the strength of the functional coupling of posterior cingulate (pCC) with medial prefrontal cortex (PFC) correlated positively with performance and was lower in older adults. pCC was also negatively coupled with task-related regions, namely the dorsolateral PFC and cingulate regions. Our results show that in addition to changes in canonical task-related brain regions, normal aging is also associated with alterations in the activity and connectivity of brain regions within the DMN. These changes may be a reflection of a deficit in cognitive control associated with advancing age that results in deficient resource allocation to the task at hand.

While much research has elucidated the neurobiology of fear learning, the neural systems supporting the generalization of learned fear are unknown. Using functional magnetic resonance imaging (fMRI), we show that regions involved in the acquisition of fear support the generalization of fear to stimuli that are similar to a learned threat, but vary in fear intensity value. Behaviorally, subjects retrospectively misidentified a learned threat as a more intense stimulus and expressed greater skin conductance responses (SCR) to generalized stimuli of high intensity. Brain activity related to intensity-based fear generalization was observed in the striatum, insula, thalamus/periacqueductal gray, and subgenual cingulate cortex. The psychophysiological expression of generalized fear correlated with amygdala activity, and connectivity between the amygdala and extrastriate visual cortex was correlated with individual differences in trait anxiety. These findings reveal the brain regions and functional networks involved in flexibly responding to stimuli that resemble a learned threat. These regions may comprise an intensity-based fear generalization circuit that underlies retrospective biases in threat value estimation and overgeneralization of fear in anxiety disorders.

Accumulating evidence from non-human primates and computational modeling suggests that dopaminergic signals arising from the midbrain (substantia nigra/ventral tegmental area) mediate striatal gating of the prefrontal cortex during the selective updating of working memory. Using event-related functional magnetic resonance imaging, we explored the neural mechanisms underlying the selective updating of information stored in working memory. Participants were scanned during a novel working memory task that parses the neurophysiology underlying working memory maintenance, overwriting, and selective updating. Analyses revealed a functionally coupled network consisting of a midbrain region encompassing the substantia nigra/ventral tegmental area, caudate, and dorsolateral prefrontal cortex that was selectively engaged during working memory updating compared to the overwriting and maintenance of working memory content. Further analysis revealed differential midbrain-dorsolateral prefrontal interactions during selective updating between low-performing and high-performing individuals. These findings highlight the role of this meso-cortico-striatal circuitry during the selective updating of working memory in humans, which complements previous research in behavioral neuroscience and computational modelin

Shared intentionality, or collaborative interactions in which individuals have a shared goal and must coordinate their efforts, is a core component of human interaction. However, the biological bases of shared intentionality and, specifically, the processes by which the brain adjusts to the sharing of common goals, remain largely unknown. Using functional near infrared spectroscopy (fNIRS), coordination of cerebral hemodynamic activation was found in subject pairs when completing a puzzle together in contrast to a condition in which subjects completed identical but individual puzzles (same intention without shared intentionality). Interpersonal neural coordination was also greater when completing a puzzle together compared to two control conditions including the observation of another pair completing the same puzzle task or watching a movie with a partner (shared experience). Further, permutation testing revealed that the time course of neural activation of one subject predicted that of their partner, but not that of others completing the identical puzzle in different partner sets. Results indicate unique brain-to-brain coupling specific to shared intentionality beyond what has been previously found by investigating the fundamentals of social exchange.

The present study investigated the effects of approach versus avoidance motivation on declarative learning. Human participants navigated a virtual reality version of the Morris water task, a classic spatial memory paradigm, adapted to permit the experimental manipulation of motivation during learning. During this task, participants were instructed to navigate to correct platforms while avoiding incorrect platforms. To manipulate motivational states participants were either rewarded for navigating to correct locations (approach) or punished for navigating to incorrect platforms (avoidance). Participants' skin conductance levels (SCLs) were recorded during navigation to investigate the role of physiological arousal in motivated learning. Behavioral results revealed that, overall, approach motivation enhanced and avoidance motivation impaired memory performance compared to nonmotivated spatial learning. This advantage was evident across several performance indices, including accuracy, learning rate, path length, and proximity to platform locations during probe trials. SCL analysis revealed three key findings. First, within subjects, arousal interacted with approach motivation, such that high arousal on a given trial was associated with performance deficits. In addition, across subjects, high arousal negated or reversed the benefits of approach motivation. Finally, low-performing, highly aroused participants showed SCL responses similar to those of avoidance -motivation participants, suggesting that for these individuals, opportunities for reward may evoke states of learning similar to those typically evoked by threats of punishment. These results provide a novel characterization of how approach and avoidance motivation influence declarative memory and indicate a critical and selective role for arousal in determining how reinforcement influences goal-oriented learning.[Supplemental material is available for this article.]Memories are not direct reflections of the environment, but are instead selective. How does this selectivity arise? Prior research suggests that motivation enhances learning and memory for behaviorally relevant information (Shohamy and Adcock 2010), but there are qualitatively different ways of motivating individuals to learn. For example, a student could equally be motivated to perform well on a test either to earn a good grade or to avoid failing a course. Previous research has demonstrated different effects on cognition and behavior by motivation to earn rewards versus motivation to avoid punishments (Elliot 2008;Lang and Bradley 2010), suggesting that these states would also produce different effects on declarative learning. The goal of this study was to characterize the shared and specific effects of approach versus avoidance motivation on the encoding and use of declarative information, specifically information about spatial environments.Previous research has demonstrated that motivation to learn enhances declarative memory. Specifically, reward incentives for successful encoding have been dem...

Background-Cognitive abilities decline with age with large individual variability. Genetic variations have been suggested to be an important source for some of this heterogeneity. Among these variations, those related to the dopaminergic system, particularly the valine 158 methionine polymorphism in catechol-O-methyltransferase (COMTval 158 met), have been implicated in modulating age-related changes in executive function.

Adaptive motivated behavior requires predictive internal representations of the environment, and surprising events are indications for encoding new representations of the environment. The medial temporal lobe memory system, including the hippocampus and surrounding cortex, encodes surprising events and is influenced by motivational state. Because behavior reflects the goals of an individual, we investigated whether motivational valence (i.e., pursuing rewards versus avoiding punishments) also impacts neural and mnemonic encoding of surprising events. During functional magnetic resonance imaging (fMRI), participants encountered perceptually unexpected events either during the pursuit of rewards or avoidance of punishments. Despite similar levels of motivation across groups, reward and punishment facilitated the processing of surprising events in different medial temporal lobe regions. Whereas during reward motivation, perceptual surprises enhanced activation in the hippocampus, during punishment motivation surprises instead enhanced activation in parahippocampal cortex. Further, we found that reward motivation facilitated hippocampal coupling with ventromedial PFC, whereas punishment motivation facilitated parahippocampal cortical coupling with orbitofrontal cortex. Behaviorally, post-scan testing revealed that reward, but not punishment, motivation resulted in greater memory selectivity for surprising events encountered during goal pursuit. Together these findings demonstrate that neuromodulatory systems engaged by anticipation of reward and punishment target separate components of the medial temporal lobe, modulating medial temporal lobe sensitivity and connectivity. Thus, reward and punishment motivation yield distinct neural contexts for learning, with distinct consequences for how surprises are incorporated into predictive mnemonic models of the environment.

Background Converging evidence implicates the anterior hippocampus in the proximal pathophysiology of schizophrenia. Although resting state functional connectivity (FC) holds promise for characterizing anterior hippocampal circuit abnormalities and their relationship to treatment response, this technique has not yet been used in first-episode psychosis (FEP) patients in a manner that distinguishes the anterior from posterior hippocampus. Methods We used masked-hippocampal-group-independent component analysis with dual regression to contrast subregional hippocampal–whole brain FC between healthy controls (HCs) and antipsychotic naïve FEP patients (N = 61, 36 female). In a subsample of FEP patients (N = 27, 15 female), we repeated this analysis following 8 weeks of second-generation antipsychotic treatment and explored whether baseline FC predicted treatment response using random forest. Results Relative to HC, untreated FEP subjects displayed reproducibly lower FC between the left anteromedial hippocampus and cortical regions including the anterior cingulate and insular cortex (P < .05, corrected). Anteromedial hippocampal FC increased in FEP patients following treatment (P < .005), and no longer differed from HC. Random forest analysis showed baseline anteromedial hippocampal FC with four brain regions, namely the insular–opercular cortex, superior frontal gyrus, precentral gyrus, and postcentral gyrus predicted treatment response (area under the curve = 0.95). Conclusions Antipsychotic naïve FEP is associated with lower FC between the anterior hippocampus and cortical regions previously implicated in schizophrenia. Preliminary analysis suggests that random forest models based on hippocampal FC may predict treatment response in FEP patients, and hence could be a useful biomarker for treatment development.