Differential role of anterior prefrontal and premotor cortex in the processing of relational information

The significance of structural rich club hubs for the processing of hierarchical stimuli

The brain's structural network follows a hierarchy that is described as rich club (RC) organization, with RC hubs forming the well-interconnected top of this hierarchy. In this study, we tested whether RC hubs are involved in the processing of hierarchically higher structures in stimulus sequences. Moreover, we explored the role of previously suggested cortical gradients along anterior-posterior and medial-lateral axes throughout the frontal cortex. To this end, we conducted a functional magnetic resonance imaging (fMRI) experiment and presented participants with blocks of digit sequences that were structured on different hierarchically nested levels. We additionally collected diffusion weighted imaging data of the same subjects to identify RC hubs. This classification then served as the basis for a region of interest analysis of the fMRI data. Moreover, we determined structural network centrality measures in areas that were found as activation clusters in the whole-brain fMRI analysis. Our findings support the previously found anterior and medial shift for processing hierarchically higher structures of stimuli. Additionally, we found that the processing of hierarchically higher structures of the stimulus structure engages RC hubs more than for lower levels. Areas involved in the functional processing of hierarchically higher structures were also more likely to be part of the structural RC and were furthermore more central to the structural network. In summary, our results highlight the potential role of the structural RC organization in shaping the cortical processing hierarchy.

Functional reconfiguration of task-active frontoparietal control network facilitates abstract reasoning

While the brain's functional network architecture is largely conserved between resting and task states, small but significant changes in functional connectivity support complex cognition. In this study, we used a modified Raven's Progressive Matrices Task to examine symbolic and perceptual reasoning in human participants undergoing fMRI scanning. Previously, studies have focused predominantly on discrete symbolic versions of matrix reasoning, even though the first few trials of the Raven's Advanced Progressive Matrices task consist of continuous perceptual stimuli. Our analysis examined the activation patterns and functional reconfiguration of brain networks associated with resting state and both symbolic and perceptual reasoning. We found that frontoparietal networks, including the cognitive control and dorsal attention networks, were significantly activated during abstract reasoning. We determined that these same task-active regions exhibited flexibly-reconfigured functional connectivity when transitioning from resting state to the abstract reasoning task. Conversely, we showed that a stable network core of regions in default and somatomotor networks was maintained across both resting and task states. We propose that these regionally-specific changes in the functional connectivity of frontoparietal networks puts the brain in a "task-ready" state, facilitating efficient task-based activation.

Understanding the Computational Demands Underlying Visual Reasoning

Visual understanding requires comprehending complex visual relations between objects within a scene. Here, we seek to characterize the computational demands for abstract visual reasoning. We do this by systematically assessing the ability of modern deep convolutional neural networks (CNNs) to learn to solve the synthetic visual reasoning test (SVRT) challenge, a collection of 23 visual reasoning problems. Our analysis reveals a novel taxonomy of visual reasoning tasks, which can be primarily explained by both the type of relations (same-different versus spatial-relation judgments) and the number of relations used to compose the underlying rules. Prior cognitive neuroscience work suggests that attention plays a key role in humans' visual reasoning ability. To test this hypothesis, we extended the CNNs with spatial and feature-based attention mechanisms. In a second series of experiments, we evaluated the ability of these attention networks to learn to solve the SVRT challenge and found the resulting architectures to be much more efficient at solving the hardest of these visual reasoning tasks. Most important, the corresponding improvements on individual tasks partially explained our novel taxonomy. Overall, this work provides a granular computational account of visual reasoning and yields testable neuroscience predictions regarding the differential need for feature-based versus spatial attention depending on the type of visual reasoning problem.

The Potential of a Relational Training Intervention to Improve Older Adults' Cognition

Behavioral gerontology rarely focuses on improving older adults' cognitive function. This gap in the literature should be addressed, as our aging population means that greater numbers of older adults are experiencing cognitive decline and reduced functional independence. If cognitive training interventions are to be socially significant, they should target improvements in core executive functions (EFs) that are critical for everyday cognition and functioning independence. Evidence from the cognitive sciences suggests that a cognitive training intervention targeting "relational knowledge" and "cognitive flexibility," which are core EFs, could translate to improvements in cognition and functioning for older adults. Behavioral researchers, interested in the effects of relational training on cognition, have shown a relationship between complex and flexible arbitrarily applicable relational responding (AARRing) and improved performance on measures of intelligence in children and young adults. However, data examining the impact of AARRing on the cognition of older adults are lacking. This article suggests that complex and flexible AARRing may be synonymous with the aforementioned EFs of relational knowledge and cognitive flexibility, and that a behaviorally oriented relational training intervention might improve cognition and functioning for healthy older adults or those experiencing cognitive decline. The article initially presents a brief overview of research in behavioral gerontology and older adult cognition, followed by a detailed explanation of how training complexity and flexibility in AARRing could result in improvements in core EFs. Specific suggestions for designing a relational training intervention and assessing relevant outcomes are provided.

Beyond the feedforward sweep: feedback computations in the visual cortex

Visual perception involves the rapid formation of a coarse image representation at the onset of visual processing, which is iteratively refined by late computational processes. These early versus late time windows approximately map onto feedforward and feedback processes, respectively. State-of-the-art convolutional neural networks, the main engine behind recent machine vision successes, are feedforward architectures. Their successes and limitations provide critical information regarding which visual tasks can be solved by purely feedforward processes and which require feedback mechanisms. We provide an overview of recent work in cognitive neuroscience and machine vision that highlights the possible role of feedback processes for both visual recognition and beyond. We conclude by discussing important open questions for future research.

The Neural Correlates of Relational Reasoning: A Meta-analysis of 47 Functional Magnetic Resonance Studies

It is a core cognitive ability of humans to represent and reason about relational information, such as “the train station is north of the hotel” or “Charles is richer than Jim.” However, the neural processes underlying the ability to draw conclusions about relations are still not sufficiently understood. Central open questions are as follows: (1) What are the neural correlates of relational reasoning? (2) Where can deductive and inductive reasoning be localized? (3) What is the impact of different informational types on cerebral activity? For that, we conducted a meta-analysis of 47 neuroimaging studies. We found activation of the frontoparietal network during both deductive and inductive reasoning, with additional activation in an extended network during inductive reasoning in the basal ganglia and the inferior parietal cortex. Analyses revealed a double dissociation concerning the lateral and medial Brodmann's area 6 during deductive and inductive reasoning, indicating differences in terms of processing verbal information in deductive and spatial information in inductive tasks. During semantic and symbolic tasks, the frontoparietal network was found active, whereas geometric tasks only elicited prefrontal activation, which can be explained by the reduced demand for the construction of a mental representation in geometric tasks. Our study provides new insights into the cognitive mechanisms underlying relational reasoning and clarifies previous controversies concerning involved brain areas.

Cognitive training in the elderly: a randomized trial to evaluate the efficacy of a self-administered cognitive training program

OBJECTIVES

To evaluate the efficacy of a self-administered cognitive training program for improving cognition in normal elderly persons.

METHOD

A multisite, randomized control, double-blind trial was conducted with 28 experimental participants (M_age = 70.7 ± 8.89) and 28 active controls (M_age = 74.4 ± 9.39). Treatment conditions: experimental intervention (EI) consisted of three modules: (1) executive functioning, (2) memory, and (3) emotion training. Active control (AC) consisted of word searches, reading short stories, and answering multiple-choice questions. Treatments were self-administered one hour/five days a week for four weeks. Pre-and post-training neuropsychological outcome measures were utilized as determinants of program success.

RESULTS

Compared to the AC group, the EI group displayed significant gains on targeted executive (p = .002) and memory (p < .001) composites, but not the emotion (p = .105) composite. Training-induced benefits were also observed for the EI group on untrained items within global cognition (BCRS, p = .002) and functional abilities (DAD, p < .001; FRS, p = .042). The percentage of participants who showed reliable performance improvements was greater for the EI than AC on executive (55.5% vs. 12.5%), memory (55% vs. 19.5%) and functional (41% vs. 7.5%) ability. Participant recruitment and compliance rates were enhanced by the involvement of a physician.

CONCLUSION

Results support the efficacy of self-directed cognitive training in reliably improving cognitive and functional abilities in normal older adults. While physicians are critical in enhancing the delivery of regimented treatment, the present study illustrates the potential for self-directed prophylactic training in deterring the development of cognitive decline.

Not-So-CLEVR: learning same-different relations strains feedforward neural networks

The advent of deep learning has recently led to great successes in various engineering applications. As a prime example, convolutional neural networks, a type of feedforward neural network, now approach human accuracy on visual recognition tasks like image classification and face recognition. However, here we will show that feedforward neural networks struggle to learn abstract visual relations that are effortlessly recognized by non-human primates, birds, rodents and even insects. We systematically study the ability of feedforward neural networks to learn to recognize a variety of visual relations and demonstrate that same-different visual relations pose a particular strain on these networks. Networks fail to learn same-different visual relations when stimulus variability makes rote memorization difficult. Further, we show that learning same-different problems becomes trivial for a feedforward network that is fed with perceptually grouped stimuli. This demonstration and the comparative success of biological vision in learning visual relations suggests that feedback mechanisms such as attention, working memory and perceptual grouping may be the key components underlying human-level abstract visual reasoning.

Reconfiguration of Brain Network Architectures between Resting-State and Complexity-Dependent Cognitive Reasoning

Our capacity for higher cognitive reasoning has a measurable limit. This limit is thought to arise from the brain's capacity to flexibly reconfigure interactions between spatially distributed networks. Recent work, however, has suggested that reconfigurations of task-related networks are modest when compared with intrinsic "resting-state" network architecture. Here we combined resting-state and task-driven functional magnetic resonance imaging to examine how flexible, task-specific reconfigurations associated with increasing reasoning demands are integrated within a stable intrinsic brain topology. Human participants (21 males and 28 females) underwent an initial resting-state scan, followed by a cognitive reasoning task involving different levels of complexity, followed by a second resting-state scan. The reasoning task required participants to deduce the identity of a missing element in a 4 × 4 matrix, and item difficulty was scaled parametrically as determined by relational complexity theory. Analyses revealed that external task engagement was characterized by a significant change in functional brain modules. Specifically, resting-state and null-task demand conditions were associated with more segregated brain-network topology, whereas increases in reasoning complexity resulted in merging of resting-state modules. Further increments in task complexity did not change the established modular architecture, but affected selective patterns of connectivity between frontoparietal, subcortical, cingulo-opercular, and default-mode networks. Larger increases in network efficiency within the newly established task modules were associated with higher reasoning accuracy. Our results shed light on the network architectures that underlie external task engagement, and highlight selective changes in brain connectivity supporting increases in task complexity.SIGNIFICANCE STATEMENT Humans have clear limits in their ability to solve complex reasoning problems. It is thought that such limitations arise from flexible, moment-to-moment reconfigurations of functional brain networks. It is less clear how such task-driven adaptive changes in connectivity relate to stable, intrinsic networks of the brain and behavioral performance. We found that increased reasoning demands rely on selective patterns of connectivity within cortical networks that emerged in addition to a more general, task-induced modular architecture. This task-driven architecture reverted to a more segregated resting-state architecture both immediately before and after the task. These findings reveal how flexibility in human brain networks is integral to achieving successful reasoning performance across different levels of cognitive demand.

Prefrontal Cortex Activation Reflects Efficient Exploitation of Higher-order Statistical Structure

Because everyday actions are statistically structured, knowing which action a person has just completed allows predicting the most likely next action step. Taking even more than the preceding action into account improves this predictability but also causes higher processing costs. Using fMRI, we investigated whether observers exploit second-order statistical regularities preferentially if information on possible upcoming actions provided by first-order regularities is insufficient. We hypothesized that anterior pFC balances whether or not second-order information should be exploited. Participants watched videos of actions that were structured by first- and second-order conditional probabilities. Information provided by the first and by the second order was manipulated independently. BOLD activity in the action observation network was more attenuated the more information on upcoming actions was provided by first-order structure, reflecting expectation suppression for more predictable actions. Activation in posterior parietal sites decreased further with second-order information but increased in temporal areas. As expected, second-order information was integrated more when less first-order information was provided, and this interaction was mediated by anterior pFC (BA 10). Observers spontaneously used both the present and the preceding action to predict the upcoming action, and integration of the preceding action was enhanced when the present action was uninformative.

General and specialized brain correlates for analogical reasoning: A meta-analysis of functional imaging studies

Reasoning by analogy allows us to link distinct domains of knowledge and to transfer solutions from one domain to another. Analogical reasoning has been studied using various tasks that have generally required the consideration of the relationships between objects and their integration to infer an analogy schema. However, these tasks varied in terms of the level and the nature of the relationships to consider (e.g., semantic, visuospatial). The aim of this study was to identify the cerebral network involved in analogical reasoning and its specialization based on the domains of information and task specificity. We conducted a coordinate-based meta-analysis of 27 experiments that used analogical reasoning tasks. The left rostrolateral prefrontal cortex was one of the regions most consistently activated across the studies. A comparison between semantic and visuospatial analogy tasks showed both domain-oriented regions in the inferior and middle frontal gyri and a domain-general region, the left rostrolateral prefrontal cortex, which was specialized for analogy tasks. A comparison of visuospatial analogy to matrix problem tasks revealed that these two relational reasoning tasks engage, at least in part, distinct right and left cerebral networks, particularly separate areas within the left rostrolateral prefrontal cortex. These findings highlight several cognitive and cerebral differences between relational reasoning tasks that can allow us to make predictions about the respective roles of distinct brain regions or networks. These results also provide new, testable anatomical hypotheses about reasoning disorders that are induced by brain damage. Hum Brain Mapp 37:1953-1969, 2016. © 2016 Wiley Periodicals, Inc.

Hemispheric lateralization in reasoning

A growing body of evidence suggests that reasoning in humans relies on a number of related processes whose neural loci are largely lateralized to one hemisphere or the other. A recent review of this evidence concluded that the patterns of lateralization observed are organized according to two complementary tendencies. The left hemisphere attempts to reduce uncertainty by drawing inferences or creating explanations, even at the cost of ignoring conflicting evidence or generating implausible explanations. Conversely, the right hemisphere aims to reduce conflict by rejecting or refining explanations that are no longer tenable in the face of new evidence. In healthy adults, the hemispheres work together to achieve a balance between certainty and consistency, and a wealth of neuropsychological research supports the notion that upsetting this balance results in various failures in reasoning, including delusions. However, support for this model from the neuroimaging literature is mixed. Here, we examine the evidence for this framework from multiple research domains, including an activation likelihood estimation analysis of functional magnetic resonance imaging studies of reasoning. Our results suggest a need to either revise this model as it applies to healthy adults or to develop better tools for assessing lateralization in these individuals.

Brain functional connectivity density and individual fluid reasoning capacity in healthy young adults

Functional connectivity density (FCD) is a newly developed data-driven method to measure the number of functional connections of each voxel, possibly providing new insight into the neural correlates of fluid reasoning. Here, we recruited 211 healthy young adults (91 men and 120 women) to investigate associations between the global FCD and fluid reasoning capacity as measured by the Raven's Standard Progressive Matrices. Raven's Standard Progressive Matrices scores were correlated negatively with the global FCD in multiple brain regions of the frontal, parietal, occipital, and temporal cortices in male participants. No significant correlation was found in female participants. Our findings confirmed the association between fluid reasoning and functional connectivity of multiple cognitive-related brain regions. The positive correlation with the functional connectivity strength and the negative correlation between fluid reasoning and FCD suggest that individuals with superior fluid reasoning capacity may possess a small number of strong functional connections. The sex dichotomy of this association indicates that the fluid reasoning capacity of men and women may have different neural substrates.

Neural substrates of impulsive decision making modulated by modafinil in alcohol-dependent patients

BACKGROUND

Impulsive decision making is a hallmark of frequently occurring addiction disorders including alcohol dependence (AD). Therefore, ameliorating impulsive decision making is a promising target for the treatment of AD. Previous studies have shown that modafinil enhances cognitive control functions in various psychiatric disorders. However, the effects of modafinil on delay discounting and its underlying neural correlates have not been investigated as yet. The aim of the current study was to investigate the effects of modafinil on neural correlates of impulsive decision making in abstinent AD patients and healthy control (HC) subjects.

METHOD

A randomized, double-blind, placebo-controlled, within-subjects cross-over study using functional magnetic resonance imaging (fMRI) was conducted in 14 AD patients and 16 HC subjects. All subjects participated in two fMRI sessions in which they either received a single dose of placebo or 200 mg of modafinil 2 h before the session. During fMRI, subjects completed a delay-discounting task to measure impulsive decision making.

RESULTS

Modafinil improved impulsive decision making in AD pateints, which was accompanied by enhanced recruitment of frontoparietal regions and reduced activation of the ventromedial prefrontal cortex. Moreover, modafinil-induced enhancement of functional connectivity between the superior frontal gyrus and ventral striatum was specifically associated with improvement in impulsive decision making.

CONCLUSIONS

These findings indicate that modafinil can improve impulsive decision making in AD patients through an enhanced coupling of prefrontal control regions and brain regions coding the subjective value of rewards. Therefore, the current study supports the implementation of modafinil in future clinical trials for AD.

A high performance 3D cluster-based test of unsmoothed fMRI data

Cluster-size tests (CST) based on random field theory have been widely adopted in fMRI data analysis to detect brain activation. However, most existing approaches can be used appropriately only when the image is highly smoothed in the spatial domain. Unfortunately, spatial smoothing degrades spatial specificity. Recently, a threshold-free cluster enhancement technique was proposed which does not require spatial smoothing, but this method can be used only for group level analysis. Advances in imaging technology now yield high quality high spatial resolution imaging data in single subjects and an inference approach that retains the benefits of greater spatial resolution is called for. In this work, we present a new CST with a correction for voxelation to address this problem. The theoretical formulation of the new approach based on Gaussian random fields is developed to estimate statistical significance using 3D statistical parametric maps without assuming spatial smoothness. Simulated phantom and resting-state fMRI experimental data are then used to compare the voxelation-corrected procedure to the widely used standard random field theory. Unlike standard random field theory approaches, which require heavy spatial smoothing, the new approach has a higher sensitivity for localizing activation regions without the requirement of spatial smoothness.

Relationship between abstract thinking and eye gaze pattern in patients with schizophrenia

Background

Effective integration of visual information is necessary to utilize abstract thinking, but patients with schizophrenia have slow eye movement and usually explore limited visual information. This study examines the relationship between abstract thinking ability and the pattern of eye gaze in patients with schizophrenia using a novel theme identification task.

Methods

Twenty patients with schizophrenia and 22 healthy controls completed the theme identification task, in which subjects selected which word, out of a set of provided words, best described the theme of a picture. Eye gaze while performing the task was recorded by the eye tracker.

Results

Patients exhibited a significantly lower correct rate for theme identification and lesser fixation and saccade counts than controls. The correct rate was significantly correlated with the fixation count in patients, but not in controls.

Conclusions

Patients with schizophrenia showed impaired abstract thinking and decreased quality of gaze, which were positively associated with each other. Theme identification and eye gaze appear to be useful as tools for the objective measurement of abstract thinking in patients with schizophrenia.

A bilateral frontoparietal network underlies visuospatial analogical reasoning

Our ability to reason by analogy facilitates problem solving and allows us to communicate ideas efficiently. In this study, we examined the neural correlates of analogical reasoning and, more specifically, the contribution of rostrolateral prefrontal cortex (RLPFC) to reasoning. This area of the brain has been hypothesized to integrate relational information, as in analogy, or the outcomes of subgoals, as in multi-tasking and complex problem solving. Using fMRI, we compared visuospatial analogical reasoning to a control task that was as complex and difficult as the analogies and required the coordination of subgoals but not the integration of relations. We found that analogical reasoning more strongly activated bilateral RLPFC, suggesting that anterior prefrontal cortex is preferentially recruited by the integration of relational knowledge. Consistent with the need for inhibition during analogy, bilateral, and particularly right, inferior frontal gyri were also more active during analogy. Finally, greater activity in bilateral inferior parietal cortex during the analogy task is consistent with recent evidence for the neural basis of spatial relation knowledge. Together, these findings indicate that a network of frontoparietal areas underlies analogical reasoning; we also suggest that hemispheric differences may emerge depending on the visuospatial or verbal/semantic nature of the analogies.

Rostral premotor cortex as a gateway between motor and cognitive networks

This article presents a hypothesis that the rostral premotor-subcortical networks may serve as a gateway between the cognitive and motor networks. Accumulating evidence has propelled an idea that motor and cognitive behaviors considerably share neural substrates and probably computational principles regardless of the species. Here I conducted a meta-analysis of previous neuroimaging studies on motor planning and different cognitive tasks (mental calculation, visuospatial processing and cognitive control), which showed overlap of all activations in the rostral premotor cortex, with a possible rostro-caudal functional gradient. It was also suggested that the rostral premotor areas might form circuits with specific portions of the cerebellum and the basal ganglia. The rostral premotor areas may provide context-dependent connectivity and mediate information flow between the cognitive and motor networks, thereby making the two networks operating interactively or independently.

A dissociation between social mentalizing and general reasoning

It has recently been suggested that brain areas crucial for mentalizing, including the medial prefrontal cortex (mPFC), are not activated exclusively during mentalizing about the intentions, beliefs, morals or traits of the self or others, but also more generally during cognitive reasoning including relational processing about objects. Contrary to this notion, a meta-analysis of cognitive reasoning tasks demonstrates that the core mentalizing areas are not systematically recruited during reasoning, but mostly when these tasks describe some human agency or general evaluative and enduring traits about humans, and much less so when these social evaluations are absent. There is a gradient showing less mPFC activation as less mentalizing content is contained in the stimulus material used in reasoning tasks. Hence, it is more likely that cognitive reasoning activates the mPFC because inferences about social agency and mind are involved.

A hierarchy for relational reasoning in the prefrontal cortex

The human brain possesses a unique capacity to reason about abstract relationships among items in our environment. The neural organization of reasoning abilities has remained elusive. Two approaches toward investigating human reasoning have involved studying visuo-spatial reasoning abilities and studying analogical reasoning. These approaches have both revealed anterior prefrontal cortex (PFC) involvement, but no prior studies have jointly investigated these two forms of reasoning to understand any potential convergence of activation within the PFC. Using fMRI, we tested the extent to which these two forms of reasoning (visuo-spatial and analogical) overlap in PFC activation. We conducted a visuo-spatial reasoning task that required processing multiple changes across three abstract pictures. This task activated a progressively anterior series of PFC regions when multiple relations had to be integrated. We also conducted a four-term analogy task in a stage-wise manner and compared results from this task to semantic and perceptual control conditions that did not require integrating relations across the problems. We found greater activation for analogical reasoning in the series of PFC regions that were sequentially involved in the visuo-spatial reasoning task. These findings indicate that stages of neural processing overlap for different domains within human reasoning. The pattern of differences across the analogy task suggests a hierarchical organization for relational reasoning across domains in which posterior frontal cortex is active across concrete reasoning tasks, while progressively more anterior regions are recruited to process increasingly abstract representations in reasoning.