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A potential spatial working memory training task to improve both episodic memory and fluid intelligence.
One current challenge in cognitive training is to create a training regime that benefits multiple cognitive domains, including episodic memory, without relying on a large battery of tasks, which can be time-consuming and difficult to learn. By giving careful consideration to the neural correlates underlying episodic and working memory, we devised a computerized working memory training task in which neurologically healthy participants were required to monitor and detect repetitions in two streams of spatial information (spatial location and scene identity) presented simultaneously (i.e. a dual n-back paradigm). Participants' episodic memory abilities were assessed before and after training using two object and scene recognition memory tasks incorporating memory confidence judgments. Furthermore, to determine the generalizability of the effects of training, we also assessed fluid intelligence using a matrix reasoning task. By examining the difference between pre- and post-training performance (i.e. gain scores), we found that the trainers, compared to non-trainers, exhibited a significant improvement in fluid intelligence after 20 days. Interestingly, pre-training fluid intelligence performance, but not training task improvement, was a significant predictor of post-training fluid intelligence improvement, with lower pre-training fluid intelligence associated with greater post-training gain. Crucially, trainers who improved the most on the training task also showed an improvement in recognition memory as captured by d-prime scores and estimates of recollection and familiarity memory. Training task improvement was a significant predictor of gains in recognition and familiarity memory performance, with greater training improvement leading to more marked gains. In contrast, lower pre-training recollection memory scores, and not training task improvement, led to greater recollection memory performance after training. Our findings demonstrate that practice on a single working memory task can potentially improve aspects of both episodic memory and fluid intelligence, and that an extensive training regime with multiple tasks may not be necessary.
Tools of the trade: psychophysiological interactions and functional connectivity.
Psychophysiological interactions (PPIs) analysis is a method for investigating task-specific changes in the relationship between activity in different brain areas, using functional magnetic resonance imaging (fMRI) data. Specifically, PPI analyses identify voxels in which activity is more related to activity in a seed region of interest (seed ROI) in a given psychological context, such as during attention or in the presence of emotive stimuli. In this tutorial, we aim to give a simple conceptual explanation of how PPI analysis works, in order to assist readers in planning and interpreting their own PPI experiments.
Anxious individuals have difficulty learning the causal statistics of aversive environments.
Statistical regularities in the causal structure of the environment enable us to predict the probable outcomes of our actions. Environments differ in the extent to which action-outcome contingencies are stable or volatile. Difficulty in being able to use this information to optimally update outcome predictions might contribute to the decision-making difficulties seen in anxiety. We tested this using an aversive learning task manipulating environmental volatility. Human participants low in trait anxiety matched updating of their outcome predictions to the volatility of the current environment, as predicted by a Bayesian model. Individuals with high trait anxiety showed less ability to adjust updating of outcome expectancies between stable and volatile environments. This was linked to reduced sensitivity of the pupil dilatory response to volatility, potentially indicative of altered norepinephrinergic responsivity to changes in this aspect of environmental information.
How can a Bayesian approach inform neuroscience?
In this review we consider how Bayesian logic can help neuroscientists to understand behaviour and brain function. Firstly, we review some key characteristics of Bayesian systems - they integrate information making rational use of uncertainty, they apply prior knowledge in the interpretation of new observations, and (for several reasons) they are very effective learners. Secondly, we illustrate how some well-known psychological phenomena including visual illusions, categorical perception and attention can be understood in terms of Bayesian inference. We also consider how formal models can clarify our understanding of psychological constructs, by giving a truly computational definition of psychological processes. Finally, we consider how probabilistic representations and hence Bayesian algorithms could be implemented by neural populations. In particular, we explore how different types of population coding may lead to different predictions about activity in both single-unit and imaging studies, and draw a distinction in this context between the representation of parameters and implementation of computations.
Distinct and overlapping functional zones in the cerebellum defined by resting state functional connectivity.
The cerebellum processes information from functionally diverse regions of the cerebral cortex. Cerebellar input and output nuclei have connections with prefrontal, parietal, and sensory cortex as well as motor and premotor cortex. However, the topography of the connections between the cerebellar and cerebral cortices remains largely unmapped, as it is relatively unamenable to anatomical methods. We used resting-state functional magnetic resonance imaging to define subregions within the cerebellar cortex based on their functional connectivity with the cerebral cortex. We mapped resting-state functional connectivity voxel-wise across the cerebellar cortex, for cerebral-cortical masks covering prefrontal, motor, somatosensory, posterior parietal, visual, and auditory cortices. We found that the cerebellum can be divided into at least 2 zones: 1) a primary sensorimotor zone (Lobules V, VI, and VIII), which contains overlapping functional connectivity maps for domain-specific motor, somatosensory, visual, and auditory cortices; and 2) a supramodal zone (Lobules VIIa, Crus I, and II), which contains overlapping functional connectivity maps for prefrontal and posterior-parietal cortex. The cortical connectivity of the supramodal zone was driven by regions of frontal and parietal cortex which are not directly involved in sensory or motor processing, including dorsolateral prefrontal cortex and the frontal pole, and the inferior parietal lobule.
Encoding of Vicarious Reward Prediction in Anterior Cingulate Cortex and Relationship with Trait Empathy.
UNLABELLED: Empathy--the capacity to understand and resonate with the experiences of others--can depend on the ability to predict when others are likely to receive rewards. However, although a plethora of research has examined the neural basis of predictions about the likelihood of receiving rewards ourselves, very little is known about the mechanisms that underpin variability in vicarious reward prediction. Human neuroimaging and nonhuman primate studies suggest that a subregion of the anterior cingulate cortex in the gyrus (ACCg) is engaged when others receive rewards. Does the ACCg show specialization for processing predictions about others' rewards and not one's own and does this specialization vary with empathic abilities? We examined hemodynamic responses in the human brain time-locked to cues that were predictive of a high or low probability of a reward either for the subject themselves or another person. We found that the ACCg robustly signaled the likelihood of a reward being delivered to another. In addition, ACCg response significantly covaried with trait emotion contagion, a necessary foundation for empathizing with other individuals. In individuals high in emotion contagion, the ACCg was specialized for processing others' rewards exclusively, but for those low in emotion contagion, this region also responded to information about the subject's own rewards. Our results are the first to show that the ACCg signals probabilistic predictions about rewards for other people and that the substantial individual variability in the degree to which the ACCg is specialized for processing others' rewards is related to trait empathy. SIGNIFICANCE STATEMENT: Successfully cooperating, competing, or empathizing with others can depend on our ability to predict when others are going to get something rewarding. Although many studies have examined how the brain processes rewards we will get ourselves, very little is known about vicarious reward processing. Here, we show that a subregion of the anterior cingulate cortex in the gyrus (ACCg) shows a degree of specialization for processing others' versus one's own rewards. However, the degree to which the ACCg is specialized varies with people's ability to empathize with others. This new insight into how vicarious rewards are processed in the brain and vary with empathy may be key for understanding disorders of social behavior, including psychopathy and autism.
Dissecting empathy: high levels of psychopathic and autistic traits are characterized by difficulties in different social information processing domains.
Individuals with psychopathy or autism spectrum disorder (ASD) can behave in ways that suggest lack of empathy towards others. However, many different cognitive and affective processes may lead to unempathic behavior and the social processing profiles of individuals with high psychopathic vs. ASD traits are likely different. Whilst psychopathy appears characterized by problems with resonating with others' emotions, ASD appears characterized by problems with cognitive perspective-taking. In addition, alexithymia has previously been associated with both disorders, but the contribution of alexithymia needs further exploration. In a community sample (N = 110) we show for the first time that although affective resonance and cognitive perspective-taking are related, high psychopathic traits relate to problems with resonating with others' emotions, but not cognitive perspective taking. Conversely, high ASD traits relate to problems with cognitive perspective-taking but not resonating with others' emotions. Alexithymia was associated with problems with affective resonance independently of psychopathic traits, suggesting that different component processes (reduced tendency to feel what others feel and reduced ability to identify and describe feelings) comprise affective resonance. Alexithymia was not associated with the reduced cognitive perspective-taking in high ASD traits. Our data suggest that (1) elevated psychopathic and ASD traits are characterized by difficulties in different social information processing domains and (2) reduced affective resonance in individuals with elevated psychopathic traits and the reduced cognitive perspective taking in individuals with elevated ASD traits are not explained by co-occurring alexithymia. (3) Alexithymia is independently associated with reduced affective resonance. Consequently, our data point to different component processes within the construct of empathy that are suggestive of partially separable cognitive and neural systems.
A synthesis of qualitative research exploring the barriers to staying in work with chronic musculoskeletal pain.
PURPOSE: Qualitative research can help to advance our understanding, management and prevention of work disability. Our aim was to integrate qualitative research findings in order to increase our understanding of barriers to stay in work with chronic pain. METHODS: We searched five electronic bibliographic databases until September 2012, supplemented by citation tracking and hand-searching. We used meta-ethnography to synthesis our findings. Central to meta-ethnography is identifying “concepts” and developing a conceptual model. Concepts were compared and organised into categories. RESULTS: The following categories can have an impact on the decision to remain in work: struggling to affirm myself as a good worker; balancing life and work in the face of unpredictable symptoms; my work colleagues don't believe me; the system does not facilitate return to work; the battle for legitimacy. CONCLUSIONS: Our innovation is to present an internationally relevant model based on a conceptual synthesis. This model highlights the adversarial work experience of people with chronic. The papers span 15 years of qualitative research. A significant finding is that these themes continue to pervade the current work environment for those in pain, and this has clear implications for education, social care and policy. IMPLICATIONS FOR REHABILITATION: People with chronic pain face an adversarial struggle to maintain their credibility at work. Strategies to maintain personal credibility can have an adverse effect on working lives. Changes at a systems level are needed to facilitate continuance and return to work. Cultural changes in the way that we view people with pain would help to keep people in work.
On the importance of cognitive profiling: A graphical modelling analysis of domain-specific and domain-general deficits after stroke.
Cognitive problems following stroke are typically analysed using either short but relatively uninformative general tests or through detailed but time consuming tests of domain specific deficits (e.g., in language, memory, praxis). Here we present an analysis of neuropsychological deficits detected using a screen designed to fall between other screens by being 'broad' (testing multiple cognitive abilities) but 'shallow' (sampling the abilities briefly, to be time efficient) - the BCoS. Assessment using the Birmingham Cognitive Screen (BCoS) enables the relations between 'domain specific' and 'domain general' cognitive deficits to be evaluated as the test generates an overall cognitive profile for individual patients. We analysed data from 287 patients tested at a sub-acute stage of stroke (<3 months). Graphical modelling techniques were used to investigate the associative structure and conditional independence between deficits within and across the domains sampled by BCoS (attention and executive functions, language, memory, praxis and number processing). The patterns of deficit within each domain conformed to existing cognitive models. However, these within-domain patterns underwent substantial change when the whole dataset was modelled, indicating that domain-specific deficits can only be understood in relation to linked changes in domain-general processes. The data point to the importance of using over-arching cognitive screens, measuring domain-general as well as domain-specific processes, in order to account for neuropsychological deficits after stroke. The paper also highlights the utility of using graphical modelling to understand the relations between cognitive components in complex datasets.