The neural correlates of belief-bias inhibition: The impact of logic training

Functional Magnetic Resonance Imaging (fMRI) was used to investigate the brain activity associated with response change in a belief bias paradigm before and after logic training. Participants completed two sets of belief biased reasoning tasks. In the first set they were instructed to respond based on their empirical beliefs, and in the second – following logic training – they were instructed to respond logically. The comparison between conflict problems in the second scan versus in the first scan revealed differing activation for the left inferior frontal gyrus, left middle frontal gyrus, cerebellum, and precuneus. The scan was time locked to the presentation of the minor premise, and thus demonstrated effects of belief–logic conflict on neural activation earlier in the time course than has previously been shown in fMRI. These data, moreover, indicated that logical training results in changes in brain activity associated with cognitive control processing

Longitudinal multi-centre brain imaging studies: guidelines and practical tips for accurate and reproducible imaging endpoints and data sharing

Abstract Background Research involving brain imaging is important for understanding common brain diseases. Study endpoints can include features and measures derived from imaging modalities, providing a benchmark against which other phenotypical data can be assessed. In trials, imaging data provide objective evidence of beneficial and adverse outcomes. Multi-centre studies increase generalisability and statistical power. However, there is a lack of practical guidelines for the set-up and conduct of large neuroimaging studies. Methods We address this deficit by describing aspects of study design and other essential practical considerations that will help researchers avoid common pitfalls and data loss. Results The recommendations are grouped into seven categories: (1) planning, (2) defining the imaging endpoints, developing an imaging manual and managing the workflow, (3) performing a dummy run and testing the analysis methods, (4) acquiring the scans, (5) anonymising and transferring the data, (6) monitoring quality, and (7) using structured data and sharing data. Conclusions Implementing these steps will lead to valuable and usable data and help to avoid imaging data wastage

Would the field of cognitive neuroscience be advanced by sharing functional MRI data?

During the past two decades, the advent of functional magnetic resonance imaging (fMRI) has fundamentally changed our understanding of brain-behavior relationships. However, the data from any one study add only incrementally to the big picture. This fact raises important questions about the dominant practice of performing studies in isolation. To what extent are the findings from any single study reproducible? Are researchers who lack the resources to conduct a fMRI study being needlessly excluded? Is pre-existing fMRI data being used effectively to train new students in the field? Here, we will argue that greater sharing and synthesis of raw fMRI data among researchers would make the answers to all of these questions more favorable to scientific discovery than they are today and that such sharing is an important next step for advancing the field of cognitive neuroscience

Brain-Performance Correlates of Working Memory Retrieval in Schizophrenia: A Cognitive Modeling Approach

Correlations of cognitive functioning with brain activation during a sternberg item recognition paradigm (SIRP) were investigated in patients with schizophrenia and in healthy controls studied at 8 sites. To measure memory scanning times, 4 response time models were fit to SIRP data. The best fitting model assumed exhaustive serial memory scanning followed by self-terminating memory search and involved one intercept parameter to represent SIRP processes not contributing directly to memory scanning. Patients displayed significantly longer response times with increasing memory load and differed on the memory scanning, memory search, and intercept parameters of the best fitting probability model. Groups differed in the correlation between the memory scanning parameter and linear brain response to increasing memory load within left inferior and left middle frontal gyrus, bilateral caudate, and right precuneus. The pattern of findings in these regions indicated that high scanning capacity was associated with high neural capacity among healthy subjects but that scanning speed was uncoupled from brain response to increasing memory load among schizophrenia patients. Group differences in correlation of the best fitting model's scanning parameter with a quadratic trend in brain response to increasing memory load suggested inefficient or disordered patterns of neural inhibition among individuals with schizophrenia, especially in the left perirhinal and entorhinal cortices. The results show at both cognitive and neural levels that disordered memory scanning contributes to deficient SIRP performance among schizophrenia patients

Information content and reward processing in the human striatum during performance of a declarative memory task

Negative feedback can signal poor performance, but it also provides information that can help learners reach the goal of task mastery. The primary aim of this study was to test the hypothesis that the amount of information provided by negative feedback during a paired-associate learning task influences feedback-related processing in the caudate nucleus. To do this, we manipulated the number of response options: With two options, positive and negative feedback provide equal amounts of information, whereas with four options, positive feedback provides more information than does negative feedback. We found that positive and negative feedback activated the caudate similarly when there were two response options. With four options, the caudate’s response to negative feedback was reduced. A secondary goal was to investigate the link between brain-based measures of feedback-related processing and behavioral indices of learning. Analysis of the posttest measures showed that trials with positive feedback were associated with higher posttest confidence ratings. Additionally, when positive feedback was delivered, caudate activity was greater for trials with high than with low posttest confidence. This experiment demonstrated the context sensitivity of feedback processing and provided evidence that feedback processing in the striatum can contribute to the strengthening of the representations available within declarative memory

Brain Structural Networks Associated with Intelligence and Visuomotor Ability

Increasing evidence indicates that multiple structures in the brain are associated with intelligence and cognitive function at the network level. The association between the grey matter (GM) structural network and intelligence and cognition is not well understood. We applied a multivariate approach to identify the pattern of GM and link the structural network to intelligence and cognitive functions. Structural magnetic resonance imaging was acquired from 92 healthy individuals. Source-based morphometry analysis was applied to the imaging data to extract GM structural covariance. We assessed the intelligence, verbal fluency, processing speed, and executive functioning of the participants and further investigated the correlations of the GM structural networks with intelligence and cognitive functions. Six GM structural networks were identified. The cerebello-parietal component and the frontal component were significantly associated with intelligence. The parietal and frontal regions were each distinctively associated with intelligence by maintaining structural networks with the cerebellum and the temporal region, respectively. The cerebellar component was associated with visuomotor ability. Our results support the parieto-frontal integration theory of intelligence by demonstrating how each core region for intelligence works in concert with other regions. In addition, we revealed how the cerebellum is associated with intelligence and cognitive functions

The role of prediction and outcomes in adaptive cognitive control

Humans adaptively perform actions to achieve their goals. This flexible behaviour requires two core abilities: the ability to anticipate the outcomes of candidate actions and the ability to select and implement actions in a goal-directed manner. The ability to predict outcomes has been extensively researched in reinforcement learning paradigms, but this work has often focused on simple actions that are not embedded in hierarchical and sequential structures that are characteristic of goal-directed human behaviour. On the other hand, the ability to select actions in accordance with high-level task goals, particularly in the presence of alternative responses and salient distractors, has been widely researched in cognitive control paradigms. Cognitive control research, however, has often paid less attention to the role of action outcomes. The present review attempts to bridge these accounts by proposing an outcome-guided mechanism for selection of extended actions. Our proposal builds on constructs from the hierarchical reinforcement learning literature, which emphasises the concept of reaching and evaluating informative states, i.e., states that constitute subgoals in complex actions. We develop an account of the neural mechanisms that allow outcome-guided action selection to be achieved in a network that relies on projections from cortical areas to the basal ganglia and back-projections from the basal ganglia to the cortex. These cortico-basal ganglia-thalamo-cortical ‘loops’ allow convergence – and thus integration – of information from non-adjacent cortical areas (for example between sensory and motor representations). This integration is essential in action sequences, for which achieving an anticipated sensory state signals the successful completion of an action. We further describe how projection pathways within the basal ganglia allow selection between representations, which may pertain to movements, actions, or extended action plans. The model lastly envisages a role for hierarchical projections from the striatum to dopaminergic midbrain areas that enable more rostral frontal areas to bias the selection of inputs from more posterior frontal areas via their respective representations in the basal ganglia.This work is supported by the Biotechnology and Biological Sciences Research Council (BBSRC) Grant BB/I019847/1, awarded to NY and FW