Prefrontal cortical contributions to working memory loading, maintenance and recall are parsed by hippocampal-prefrontal oscillatory assembly dynamics

Working memory enables incorporation of recent experience into subsequent decision-making. This processing recruits both prefrontal cortex and hippocampus, where neurons encode task cues, rules and outcomes. However, precisely which information is carried when, and by which neurons, remains unclear. Using population decoding of activity in rat medial prefrontal cortex (mPFC) and dorsal hippocampal CA1, we confirm that mPFC populations lead in maintaining sample information across delays of an operant non-match to sample task, despite individual neurons firing only transiently. During sample encoding, distinct mPFC subpopulations joined distributed CA1-mPFC cell assemblies hallmarked by 4-5Hz rhythmic modulation; CA1-mPFC assemblies re-emerged during choice episodes, but were not 4-5Hz modulated. Delay-dependent errors arose when attenuated rhythmic assembly activity heralded collapse of sustained mPFC encoding; pharmacological disruption of CA1-mPFC assembly rhythmicity impaired task performance. Our results map component processes of memory-guided decisions onto heterogeneous CA1-mPFC subpopulations and the dynamics of physiologically distinct, distributed cell assemblies.

Interactive Development of Adaptive Learning and Memory

Across development, interactions between value-based learning and memory processes promote the formation of mental models that enable flexible goal pursuit. Value cues in the environment signal information that may be useful to prioritize in memory; these prioritized memories in turn form the foundation of structured knowledge representations that guide subsequent learning. Critically, neural and cognitive component processes of learning and memory undergo marked shifts from infancy to adulthood, leading to developmental change in the construction of mental models and how they are used to guide goal-directed behavior. This review explores how changes in reciprocal interactions between value-based learning and memory influence adaptive behavior across development and highlights avenues for future research.

Dissecting Motor and Cognitive Component Processes of a Finger-Tapping Task With Hybrid Dopamine Positron Emission Tomography and Functional Magnetic Resonance Imaging

Striatal dopamine is involved in facilitation of motor action as well as various cognitive and emotional functions. Positron emission tomography (PET) is the primary imaging method used to investigate dopamine function in humans. Previous PET studies have shown striatal dopamine release during simple finger tapping in both the putamen and the caudate. It is likely that dopamine release in the putamen is related to motor processes while dopamine release in the caudate could signal sustained cognitive component processes of the task, but the poor temporal resolution of PET has hindered firm conclusions. In this study we simultaneously collected [11C]Raclopride PET and functional Magnetic Resonance Imaging (fMRI) data while participants performed finger tapping, with fMRI being able to isolate activations related to individual tapping events. The results revealed fMRI-PET overlap in the bilateral putamen, which is consistent with a motor component process. Selective PET responses in the caudate, ventral striatum, and right posterior putamen, were also observed but did not overlap with fMRI responses to tapping events, suggesting that these reflect non-motor component processes of finger tapping. Our findings suggest an interplay between motor and non-motor-related dopamine release during simple finger tapping and illustrate the potential of hybrid PET-fMRI in revealing distinct component processes of cognitive functions.

Exploring factors that mitigate the continued influence of misinformation

Background The term “continued influence effect” (CIE) refers to the phenomenon that discredited and obsolete information continues to affect behavior and beliefs. The practical relevance of this work is particularly apparent as we confront fake news everyday. Thus, an important question becomes, how can we mitigate the continued influence of misinformation? Decades of research have identified several factors that contribute to the CIE reduction, but few have reported successful elimination. Across three studies, we evaluated the relative contribution of three factors (i.e., targeting the misinformation, providing an alternative explanation, and relative importance of the misinformation content) to the reduction of the CIE. Results Across three studies and two different CIE measures, we found that alternative provision consistently resulted in CIE reduction. Furthermore, under certain conditions, the combination of alternative inclusion and direct targeting of misinformation in the correction statement resulted in successful elimination of the CIE, such that individuals who encountered that type of correction behaved similarly to baseline participants who never encountered the (mis)information. In contrast, under one CIE measure, participants who received correction statements that failed to include those elements referenced the (mis)information as frequently as baseline participants who never encountered a correction. Finally, we delineated several component processes involved in misinformation outdating and found that the extent of outdating success varied as a function of the causality of misinformation. Conclusions The damaging effects of fake news are undeniable, and the negative consequences are exacerbated in the digital age. Our results contribute to our understanding of how fake news persists and how we may begin to mitigate their effects.

Cognitive and Affective Empathy Relate Differentially to Emotion Regulation

The constructs of empathy (i.e., understanding and/or sharing another’s emotion) and emotion regulation (i.e., the processes by which one manages emotions) have largely been studied in relative isolation of one another. To better understand the interrelationships between their various component processes, this manuscript reports two studies that examined the relationship between empathy and emotion regulation using a combination of self-report and task measures. In study 1 (N = 137), trait cognitive empathy and affective empathy were found to share divergent relationships with self-reported emotion dysregulation. Trait emotion dysregulation was negatively related to cognitive empathy but did not show a significant relationship with affective empathy. In the second study (N = 92), the magnitude of emotion interference effects (i.e., the extent to which inhibitory control was impacted by emotional relative to neutral stimuli) in variants of a Go/NoGo and Stroop task were used as proxy measures of implicit emotion regulation abilities. Trait cognitive and affective empathy were differentially related to both task metrics. Higher affective empathy was associated with increased emotional interference in the Emotional Go/NoGo task; no such relationship was observed for trait cognitive empathy. In the Emotional Stroop task, higher cognitive empathy was associated with reduced emotional interference; no such relationship was observed for affective empathy. Together, these studies demonstrate that greater cognitive empathy was broadly associated with improved emotion regulation abilities, while greater affective empathy was typically associated with increased difficulties with emotion regulation. These findings point to the need for assessing the different components of empathy in psychopathological conditions marked by difficulties in emotion regulation.

Recommendations for the Development of Socioeconomically-Situated and Clinically-Relevant Neuroimaging Models of Pain

Pain is a complex, multidimensional experience that emerges from interactions among sensory, affective, and cognitive processes in the brain. Neuroimaging allows us to identify these component processes and model how they combine to instantiate the pain experience. However, the clinical impact of pain neuroimaging models has been limited by inadequate population sampling – young healthy college students are not representative of chronic pain patients. The biopsychosocial approach to pain management situates a person's pain within the diverse socioeconomic environments they live in. To increase the clinical relevance of pain neuroimaging models, a three-fold biopsychosocial approach to neuroimaging biomarker development is recommended. The first level calls for the development of diagnostic biomarkers via the standard population-based (nomothetic) approach with an emphasis on diverse sampling. The second level calls for the development of treatment-relevant models via a constrained person-based (idiographic) approach tailored to unique individuals. The third level calls for the development of prevention-relevant models via a novel society-based (social epidemiologic) approach that combines survey and neuroimaging data to predict chronic pain risk based on one's socioeconomic conditions. The recommendations in this article address how we can leverage pain's complexity in service of the patient and society by modeling not just individuals and populations, but also the socioeconomic structures that shape any individual's expectations of threat, safety, and resource availability.

Face Perception Deficits in Developmental Prosopagnosia

<p>Face recognition is a fundamental cognitive function that is essential for social interaction – yet not everyone has it. Developmental prosopagnosia is a lifelong condition in which people have severe difficulty recognising faces but have normal intellect and no brain damage. Despite much research, the component processes of face recognition that are impaired in developmental prosopagnosia are not well understood. Two core processes are face perception, being the formation of visual representations of a currently seen face, and face memory, being the storage, maintenance, and retrieval of those representations. Most studies of developmental prosopagnosia focus on face memory deficits, but a few recent studies indicate that face perception deficits might also be important. Characterising face perception in developmental prosopagnosia is crucial for a better understanding of the condition. In this thesis, I addressed this issue in a large-scale experiment with 108 developmental prosopagnosics and 136 matched controls. I assessed face perception abilities with multiple measures and ran a broad range of analyses to establish the severity, scope, and nature of face perception deficits in developmental prosopagnosia. Three major results stand out. First, face perception deficits in developmental prosopagnosia were severe, and could be comparable in size to face memory deficits. Second, the face perception deficits were widespread, affecting the whole sample rather than a subset of individuals. Third, the deficits were mainly driven by impairments to mechanisms specialised for processing upright faces. Further analyses revealed several other features of the deficits, including the use of atypical and inconsistent strategies for perceiving faces, difficulties matching the same face across different pictures, equivalent impact of lighting and viewpoint variations in face images, and atypical perceptual and non-perceptual components of test performance. Overall, my thesis shows that face perception deficits are more central to developmental prosopagnosia than previously thought and motivates further research on the issue.</p>

Face Perception Deficits in Developmental Prosopagnosia

<p>Face recognition is a fundamental cognitive function that is essential for social interaction – yet not everyone has it. Developmental prosopagnosia is a lifelong condition in which people have severe difficulty recognising faces but have normal intellect and no brain damage. Despite much research, the component processes of face recognition that are impaired in developmental prosopagnosia are not well understood. Two core processes are face perception, being the formation of visual representations of a currently seen face, and face memory, being the storage, maintenance, and retrieval of those representations. Most studies of developmental prosopagnosia focus on face memory deficits, but a few recent studies indicate that face perception deficits might also be important. Characterising face perception in developmental prosopagnosia is crucial for a better understanding of the condition. In this thesis, I addressed this issue in a large-scale experiment with 108 developmental prosopagnosics and 136 matched controls. I assessed face perception abilities with multiple measures and ran a broad range of analyses to establish the severity, scope, and nature of face perception deficits in developmental prosopagnosia. Three major results stand out. First, face perception deficits in developmental prosopagnosia were severe, and could be comparable in size to face memory deficits. Second, the face perception deficits were widespread, affecting the whole sample rather than a subset of individuals. Third, the deficits were mainly driven by impairments to mechanisms specialised for processing upright faces. Further analyses revealed several other features of the deficits, including the use of atypical and inconsistent strategies for perceiving faces, difficulties matching the same face across different pictures, equivalent impact of lighting and viewpoint variations in face images, and atypical perceptual and non-perceptual components of test performance. Overall, my thesis shows that face perception deficits are more central to developmental prosopagnosia than previously thought and motivates further research on the issue.</p>

Centralized resource allocation with the possibility of downsizing in two-stage network production systems

The network data envelopment analysis (NDEA) technique has been recently developed to measure the relative efficiency of complex production systems. NDEA models provide more meaningful and informative results in comparison to the conventional black-box DEA approach that ignores the operations of the component processes. Regarding the centralized decision-making systems, normal management imposes common resource constraints to maximize produced outputs and minimize consumed inputs. The present study seeks to introduce new centralized resource allocation models in two-stage network production systems. This intra-organizational perspective also provides the possibility of closing down some of the existing units to improve system efficiency. To do so, three scenarios of centralized DEA models are introduced to take advantage of this possibility. A simple numerical example is used for illustration purposes. An empirical application of the proposed approach to the twenty branches of a university is also presented to show the applicability of the new approach.