The Dorsal Frontoparietal Network: A Core System for Emulated Action

Disruption of motor imagery performance following inhibition of the left inferior parietal lobe

The left inferior parietal lobe (IPL), a brain region localized to the ventro-dorsal stream, is known to be critical to motor imagery (MI) performance. Yet its specific role in processes underlying MI, namely the generation, maintenance, manipulation, and controllability of motor images, is conflicting in the literature. To determine the specific role of the left IPL in MI, the current study sought to examine the effect inhibition of the left IPL has on performance on two disparate measures thought to probe different MI processes within the same participants. Participants (N = 31) completed the hand laterality judgment task (HLJT), employed to probe processes related to manipulation and controllability, and mental chronometry, employed to probe processes related to generation and maintenance, after receiving either inhibitory transcranial magnetic stimulation to the left IPL (Active-TMS group), or with the coil angled away from the scalp (Sham group). Impaired performance on the HLJT was observed following active TMS relative to sham. Similar mental chronometry performance resulted regardless of left IPL inhibition. In showing that inhibition of the left IPL selectively disrupted performance on the HLJT but not mental chronometry, our findings indicate that the left IPL is specifically involved in image manipulation and controllability during MI. Ultimately, the current study extends our understanding of the role of the left IPL in MI.

Damage to the right temporoparietal junction, but not lateral prefrontal or insular cortex, amplifies the role of goal-directed attention

Whether an object captures attention depends on the interplay between its saliency and current behavioral predispositions of the observer. Neuroimaging work has implied a ventral attention network, comprising the temporoparietal junction (TPJ), lateral prefrontal cortex (lPFC) and the insula, in attentional orienting toward salient events. Activity of the TPJ is driven by novel and unexpected objects, while the lateral prefrontal cortex is involved in stimulus-driven as well as goal-directed processing. The insula in turn, is part of a saliency network, which has been implicated in detecting biologically salient signals. These roles predict that damage to the TPJ, lPFC, or insula should affect performance in tasks measuring the capture of attention by salient and behaviorally relevant events. Here, we show that patients with lesions to the right TPJ have a characteristic increase of attentional capture by relevant distracters. In contrast, damage to the lPFC or insular cortex only increases reaction times, irrespective of the task-relevant properties of distracters. These findings show that acquired damage to the TPJ pathologically amplifies the capture of attention by task-relevant information, and thus indicate that the TPJ has a decisive role in goal-directed orienting.

The Role of Premotor Areas in Dual Tasking in Healthy Controls and Persons With Multiple Sclerosis: An fNIRS Imaging Study

Persons with multiple sclerosis (pwMS) experience declines in physical and cognitive abilities and are challenged by dual-tasks. Dual-tasking causes a drop in performance, or what is known as dual-task cost (DTC). This study examined DTC of walking speed (WS) and cognitive performance (CP) in pwMS and healthy controls (HCs) and the effect of dual-tasking on cortical activation of bilateral premotor cortices (PMC) and bilateral supplementary motor area (SMA). Fourteen pwMS and 14 HCs performed three experimental tasks: (1) single cognitive task while standing (SingCog); (2) single walking task (SingWalk); and (3) dual-task (DualT) that included concurrent performance of the SingCog and SingWalk. Six trials were collected for each condition and included measures of cortical activation, WS and CP. WS of pwMS was significantly lower than HC, but neuropsychological (NP) measures were not significantly different. pwMS and HC groups had similar DTC of WS, while DTC of CP was only significant in the MS group; processing speed and visual memory predicted 55% of this DTC. DualT vs. SingWalk recruited more right-PMC activation only in HCs and was associated with better processing speed. DualT vs. SingCog recruited more right-PMC activation and bilateral-SMA activation in both HC and pwMS. Lower baseline WS and worse processing speed measures in pwMS predicted higher recruitment of right-SMA (rSMA) activation suggesting maladaptive recruitment. Lack of significant difference in NP measures between groups does not rule out the influence of cognitive factors on dual-tasking performance and cortical activations in pwMS, which might have a negative impact on quality of life.

The Psychophysiology of Action: A Multidisciplinary Endeavor for Integrating Action and Cognition

There is a vast amount of literature concerning the integration of action and cognition. Although this broad research area is of great interest for many disciplines like sports, psychology and cognitive neuroscience, only a few attempts tried to bring together different perspectives so far. Our goal is to provide a perspective to spark a debate across theoretical borders and integration of different disciplines via psychophysiology. In order to boost advances in this research field it is not only necessary to become aware of the different areas that are relevant but also to consider methodological aspects and challenges. We briefly describe the most relevant theoretical accounts to the question of how internal and external information processes or factors interact and, based on this, argue that research programs should consider the three dimensions: (a) dynamics of movements; (b) multivariate measures and; (c) dynamic statistical parameters. Only with an extended perspective on theoretical and methodological accounts, one would be able to integrate the dynamics of actions into theoretical advances.

Social Cognition for Human-Robot Symbiosis-Challenges and Building Blocks

The next generation of robot companions or robot working partners will need to satisfy social requirements somehow similar to the famous laws of robotics envisaged by Isaac Asimov time ago (Asimov, 1942). The necessary technology has almost reached the required level, including sensors and actuators, but the cognitive organization is still in its infancy and is only partially supported by the current understanding of brain cognitive processes. The brain of symbiotic robots will certainly not be a “positronic” replica of the human brain: probably, the greatest part of it will be a set of interacting computational processes running in the cloud. In this article, we review the challenges that must be met in the design of a set of interacting computational processes as building blocks of a cognitive architecture that may give symbiotic capabilities to collaborative robots of the next decades: (1) an animated body-schema; (2) an imitation machinery; (3) a motor intentions machinery; (4) a set of physical interaction mechanisms; and (5) a shared memory system for incremental symbiotic development. We would like to stress that our approach is totally un-hierarchical: the five building blocks of the shared cognitive architecture are fully bi-directionally connected. For example, imitation and intentional processes require the “services” of the animated body schema which, on the other hand, can run its simulations if appropriately prompted by imitation and/or intention, with or without physical interaction. Successful experiences can leave a trace in the shared memory system and chunks of memory fragment may compete to participate to novel cooperative actions. And so on and so forth. At the heart of the system is lifelong training and learning but, different from the conventional learning paradigms in neural networks, where learning is somehow passively imposed by an external agent, in symbiotic robots there is an element of free choice of what is worth learning, driven by the interaction between the robot and the human partner. The proposed set of building blocks is certainly a rough approximation of what is needed by symbiotic robots but we believe it is a useful starting point for building a computational framework.

Examining the Triple Code Model in numerical cognition: An fMRI study

The Triple Code Model (TCM) of numerical cognition argues for the existence of three representational codes for number: Arabic digits, verbal number words, and analog nonsymbolic magnitude representations, each subserved by functionally dissociated neural substrates. Despite the popularity of the TCM, no study to date has explored all three numerical codes within one fMRI paradigm. We administered three tasks, associated with each of the aforementioned numerical codes, in order to explore the neural correlates of numerosity processing in a sample of adults (N = 46). Independent task-control contrast analyses revealed task-dependent activity in partial support of the model, but also highlight the inherent complexity of a distributed and overlapping fronto-parietal network involved in all numerical codes. The results indicate that the TCM correctly predicts the existence of some functionally dissociated neural substrates, but requires an update that accounts for interactions with attentional processes. Parametric contrasts corresponding to differences in task difficulty revealed specific neural correlates of the distance effect, where closely spaced numbers become more difficult to discriminate than numbers spaced further apart. A conjunction analysis illustrated overlapping neural correlates across all tasks, in line with recent proposals for a fronto-parietal network of number processing. We additionally provide tentative results suggesting the involvement of format-independent numerosity-sensitive retinotopic maps in the early visual stream, extending previous findings of nonsymbolic stimulus selectivity. We discuss the functional roles of the components associated with the model, as well as the purported fronto-parietal network, and offer arguments in favor of revising the TCM.

Cooperative and Competitive Contextual Effects on Social Cognitive and Empathic Neural Responses

We aimed to differentiate the neural responses to cooperative and competitive contexts, which are the two of the most important social contexts in human society. Healthy male college students were asked to complete a Tetris-like task requiring mental rotation skills under individual, cooperative, and competitive contexts in an fMRI scanner. While the participants completed the task, pictures of others experiencing pain evoking emotional empathy randomly appeared to capture contextual effects on empathic neural responses. Behavioral results indicated that, in the presence of cooperation, participants solved the tasks more accurately and quickly than what they did when in the presence of competition. The fMRI results revealed activations in the dorsolateral prefrontal cortex (dlPFC) and dorsomedial prefrontal cortex (dmPFC) related to executive functions and theory of mind when participants performed the task under both cooperative and competitive contexts, whereas no activation of such areas was observed in the individual context. Cooperation condition exhibited stronger neural responses in the ventromedial prefrontal cortex (vmPFC) and dmPFC than competition condition. Competition condition, however, showed marginal neural responses in the cerebellum and anterior insular cortex (AIC). The two social contexts involved stronger empathic neural responses to other's pain than the individual context, but no substantial differences between cooperation and competition were present. Regions of interest analyses revealed that individual's trait empathy modulated the neural activity in the state empathy network, the AIC, and the dorsal anterior cingulate cortex (dACC) depending on the social context. These results suggest that cooperation improves task performance and activates neural responses associated with reward and mentalizing. Furthermore, the interaction between trait- and state-empathy was explored by correlation analyses between individual's trait empathy score and changing empathic brain activations along with the exposure to the cooperative and competitive social contexts.

Core networks and their reconfiguration patterns across cognitive loads

Different cognitively demanding tasks recruit globally distributed but functionally specific networks. However, the configuration of core networks and their reconfiguration patterns across cognitive loads remain unclear, as does whether these patterns are indicators for the performance of cognitive tasks. In this study, we analyzed functional magnetic resonance imaging data of a large cohort of 448 subjects, acquired with the brain at resting state and executing N-back working memory (WM) tasks. We discriminated core networks by functional interaction strength and connection flexibility. Results demonstrated that the frontoparietal network (FPN) and default mode network (DMN) were core networks, but each exhibited different patterns across cognitive loads. The FPN and DMN both showed strengthened internal connections at the low demand state (0-back) compared with the resting state (control level); whereas, from the low (0-back) to high demand state (2-back), some connections to the FPN weakened and were rewired to the DMN (whose connections all remained strong). Of note, more intensive reconfiguration of both the whole brain and core networks (but no other networks) across load levels indicated relatively poor cognitive performance. Collectively these findings indicate that the FPN and DMN have distinct roles and reconfiguration patterns across cognitively demanding loads. This study advances our understanding of the core networks and their reconfiguration patterns across cognitive loads and provides a new feature to evaluate and predict cognitive capability (e.g., WM performance) based on brain networks.

Real-Time Prediction of Observed Action Requires Integrity of the Dorsal Premotor Cortex: Evidence From Repetitive Transcranial Magnetic Stimulation

Studying brain mechanisms underlying the prediction of observed action, the dorsal premotor cortex (PMd) has been suggested a key area. The present study probed this notion using repetitive transcranial magnetic stimulation (rTMS) to test whether interference in this area would affect the accuracy in predicting the time course of object directed actions performed with the right hand. Young and healthy participants observed actions in short videos. These were briefly occluded from view for 600 ms and resumed immediately afterwards. The task was to continue the action mentally and to indicate after each occlusion, whether the action was resumed at the right moment (condition in-time) or shifted. In a first run, single-pulse transcranial magnetic stimulation (sTMS) was delivered over the left primary hand-area during occlusion. In the second run, rTMS over the left PMd was applied during occlusion in half of the participants [experimental group (EG)]. The control group (CG) received sham-rTMS over the same area. Under rTMS, the EG predicted less trials correctly than in the sTMS run. Sham-rTMS in the CG had no effects on prediction. The interference in PMd interacted with the type of manipulation applied to the action’s time course occasionally during occlusion. The performance decrease of the EG was most pronounced in conditions in which the continuations after occlusions were too late in the action’s course. The present results extend earlier findings suggesting that real-time action prediction requires the integrity of the PMd. Different functional roles of this area are discussed. Alternative interpretations consider either simulation of specific motor programming functions or the involvement of a feature-unspecific predictor.

Experience modulates motor imagery-based brain activity

Whether or not brain activation during motor imagery (MI), the mental rehearsal of movement, is modulated by experience (i.e. skilled performance, achieved through long-term practice) remains unclear. Specifically, MI is generally associated with diffuse activation patterns that closely resemble novice physical performance, which may be attributable to a lack of experience with the task being imagined vs. being a distinguishing feature of MI. We sought to examine how experience modulates brain activity driven via MI, implementing a within- and between-group design to manipulate experience across tasks as well as expertise of the participants. Two groups of 'experts' (basketball/volleyball athletes) and 'novices' (recreational controls) underwent magnetoencephalography (MEG) while performing MI of four multi-articular tasks, selected to ensure that the degree of experience that participants had with each task varied. Source-level analysis was applied to MEG data and linear mixed effects modelling was conducted to examine task-related changes in activity. Within- and between-group comparisons were completed post hoc and difference maps were plotted. Brain activation patterns observed during MI of tasks for which participants had a low degree of experience were more widespread and bilateral (i.e. within-groups), with limited differences observed during MI of tasks for which participants had similar experience (i.e. between-groups). Thus, we show that brain activity during MI is modulated by experience; specifically, that novice performance is associated with the additional recruitment of regions across both hemispheres. Future investigations of the neural correlates of MI should consider prior experience when selecting the task to be performed.

Heterogeneity within the frontoparietal control network and its relationship to the default and dorsal attention networks

The frontoparietal control network (FPCN) plays a central role in executive control. It has been predominantly viewed as a unitary domain general system. Here, we examined patterns of FPCN functional connectivity (FC) across multiple conditions of varying cognitive demands, to test for FPCN heterogeneity. We identified two distinct subsystems within the FPCN based on hierarchical clustering and machine learning classification analyses of within-FPCN FC patterns. These two FPCN subsystems exhibited distinct patterns of FC with the default network (DN) and the dorsal attention network (DAN). FPCN_A exhibited stronger connectivity with the DN than the DAN, whereas FPCN_B exhibited the opposite pattern. This twofold FPCN differentiation was observed across four independent datasets, across nine different conditions (rest and eight tasks), at the level of individual-participant data, as well as in meta-analytic coactivation patterns. Notably, the extent of FPCN differentiation varied across conditions, suggesting flexible adaptation to task demands. Finally, we used meta-analytic tools to identify several functional domains associated with the DN and DAN that differentially predict activation in the FPCN subsystems. These findings reveal a flexible and heterogeneous FPCN organization that may in part emerge from separable DN and DAN processing streams. We propose that FPCN_A may be preferentially involved in the regulation of introspective processes, whereas FPCN_B may be preferentially involved in the regulation of visuospatial perceptual attention.

Heterogeneity within the frontoparietal control network and its relationship to the default and dorsal attention networks

The frontoparietal control network (FPCN) plays a central role in executive control. It has been predominantly viewed as a unitary domain general system. Here, we examined patterns of FPCN functional connectivity (FC) across multiple conditions of varying cognitive demands, to test for FPCN heterogeneity. We identified two distinct subsystems within the FPCN based on hierarchical clustering and machine learning classification analyses of within-FPCN FC patterns. These two FPCN subsystems exhibited distinct patterns of FC with the default network (DN) and the dorsal attention network (DAN). FPCN_A exhibited stronger connectivity with the DN than the DAN, whereas FPCN_B exhibited the opposite pattern. This twofold FPCN differentiation was observed across four independent datasets, across nine different conditions (rest and eight tasks), at the level of individual-participant data, as well as in meta-analytic coactivation patterns. Notably, the extent of FPCN differentiation varied across conditions, suggesting flexible adaptation to task demands. Finally, we used meta-analytic tools to identify several functional domains associated with the DN and DAN that differentially predict activation in the FPCN subsystems. These findings reveal a flexible and heterogeneous FPCN organization that may in part emerge from separable DN and DAN processing streams. We propose that FPCN_A may be preferentially involved in the regulation of introspective processes, whereas FPCN_B may be preferentially involved in the regulation of visuospatial perceptual attention.

Resting State Default Mode Network Connectivity, Dual Task Performance, Gait Speed, and Postural Sway in Older Adults with Mild Cognitive Impairment

Aging is associated with an increased risk of falling. In particular, older adults with mild cognitive impairment (MCI) are more vulnerable to falling compared with their healthy counterparts. Major contributors to this increased falls risk include a decline in dual task performance, gait speed, and postural sway. Recent evidence highlights the potential influence of the default mode network (DMN), the frontoparietal network (FPN), and the supplementary motor area (SMA) on dual task performance, gait speed, and postural sway. The DMN is active during rest and deactivates during task-oriented processes, to maintain attention and stay on task. The FPN and SMA are involved in top-down attentional control, motor planning, and motor execution. The DMN shows less deactivation during task in older adults with MCI. This lack of deactivation is theorized to increase competition for resources between the DMN and task-related brain regions (e.g., the FPN and SMA), increasing distraction from the task and reducing task performance. However, no study has yet investigated the relationship between the between-network connectivity of the DMN with these regions and dual task walking, gait speed or postural sway. We hypothesized that greater functional connectivity both within the DMN and between DMN–FPN and DMN–SMA, will be associated with poorer performance during dual task walking, slower gait speed, and greater postural sway in older adults with MCI. Forty older adults with MCI were measured on a dual task-walking paradigm, gait speed over a 4-m walk, and postural sway using a sway-meter. Greater within-DMN connectivity was significantly correlated with poorer dual task performance. Furthermore, greater inter-network connectivity between the DMN and SMA was significantly correlated with slower gait speed and greater postural sway on the eyes open floor sway task. Thus, greater resting state DMN functional connectivity may be an underlying neural mechanism for reduced dual task ability, slower gait speed, and greater postural sway, resulting in the increased risk of mobility disability and falling in older adults with MCI.