Lars Marstaller

Multimodal functional imaging of motor imagery using a novel paradigm

Neuroimaging studies have shown that the neural mechanisms of motor imagery (MI) overlap substantially with the mechanisms of motor execution (ME). Surprisingly, however, the role of several regions of the motor circuitry in MI remains controversial, a variability that may be due to differences in neuroimaging techniques, MI training, instruction types, or tasks used to evoke MI. The objectives of this study were twofold: (i) to design a novel task that reliably invokes MI, provides a reliable behavioral measure of MI performance, and is transferable across imaging modalities; and (ii) to measure the common and differential activations for MI and ME with functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG). We present a task in which it is difficult to give accurate responses without the use of either motor execution or motor imagery. The behavioral results demonstrate that participants performed similarly on the task when they imagined vs. executed movements and this performance did not change over time. The fMRI results show a spatial overlap of MI and ME in a number of motor and premotor areas, sensory cortices, cerebellum, inferior frontal gyrus, and ventrolateral thalamus. MI uniquely engaged bilateral occipital areas, left parahippocampus, and other temporal and frontal areas, whereas ME yielded unique activity in motor and sensory areas, cerebellum, precuneus, and putamen. The MEG results show a robust event-related beta band desynchronization in the proximity of primary motor and premotor cortices during both ME and MI. Together, these results further elucidate the neural circuitry of MI and show that our task robustly and reliably invokes motor imagery, and thus may prove useful for interrogating the functional status of the motor circuitry in patients with motor disorders.

Aging and large-scale functional networks: White matter integrity, gray matter volume, and functional connectivity in the resting state

Healthy aging is accompanied by neurobiological changes that affect the brains functional organization and the individuals cognitive abilities. The aim of this study was to investigate the effect of global age-related differences in the cortical white and gray matter on neural activity in three key large-scale networks. We used functional-structural covariance network analysis to assess resting state activity in the default mode network (DMN), the fronto-parietal network (FPN), and the salience network (SN) of young and older adults. We further related this functional activity to measures of cortical thickness and volume derived from structural MRI, as well as to measures of white matter integrity (fractional anisotropy [FA], mean diffusivity [MD], and radial diffusivity [RD]) derived from diffusion-weighted imaging. First, our results show that, in the direct comparison of resting state activity, young but not older adults reliably engage the SN and FPN in addition to the DMN, suggesting that older adults recruit these networks less consistently. Second, our results demonstrate that age-related decline in white matter integrity and gray matter volume is associated with activity in prefrontal nodes of the SN and FPN, possibly reflecting compensatory mechanisms. We suggest that age-related differences in gray and white matter properties differentially affect the ability of the brain to engage and coordinate large-scale functional networks that are central to efficient cognitive functioning.

The evolution of representation in simple cognitive networks

Representations are internal models of the environment that can provide guidance to a behaving agent, even in the absence of sensory information. It is not clear how representations are developed and whether they are necessary or even essential for intelligent behavior. We argue here that the ability to represent relevant features of the environment is the expected consequence of an adaptive process, give a formal definition of representation based on information theory, and quantify it with a measure R. To measure how R changes over time, we evolve two types of networks—an artificial neural network and a network of hidden Markov gates—to solve a categorization task using a genetic algorithm. We find that the capacity to represent increases during evolutionary adaptation and that agents form representations of their environment during their lifetime. This ability allows the agents to act on sensorial inputs in the context of their acquired representations and enables complex and context-dependent behavior. We examine which concepts (features of the environment) our networks are representing, how the representations are logically encoded in the networks, and how they form as an agent behaves to solve a task. We conclude that R should be able to quantify the representations within any cognitive system and should be predictive of an agents long-term adaptive success.

Individual differences in the gesture effect on working memory

Co-speech gestures have been shown to interact with working memory (WM). However, no study has investigated whether there are individual differences in the effect of gestures on WM. Combining a novel gesture/no-gesture task and an operation span task, we examined the differences in WM accuracy between individuals who gestured and individuals who did not gesture in relation to their WM capacity. Our results showed individual differences in the gesture effect on WM. Specifically, only individuals with low WM capacity showed a reduced WM accuracy when they did not gesture. Individuals with low WM capacity who did gesture, as well as high-capacity individuals (irrespective of whether they gestured or not), did not show the effect. Our findings show that the interaction between co-speech gestures and WM is affected by an individual’s WM load.

Adaptive Motor Imagery: A Multimodal Study of Immobilization-Induced Brain Plasticity

The consequences of losing the ability to move a limb are traumatic. One approach that examines the impact of pathological limb nonuse on the brain involves temporary immobilization of a healthy limb. Here, we investigated immobilization-induced plasticity in the motor imagery (MI) circuitry during hand immobilization. We assessed these changes with a multimodal paradigm, using functional magnetic resonance imaging (fMRI) to measure neural activation, magnetoencephalography (MEG) to track neuronal oscillatory dynamics, and transcranial magnetic stimulation (TMS) to assess corticospinal excitability. fMRI results show a significant decrease in neural activation for MI of the constrained hand, localized to sensorimotor areas contralateral to the immobilized hand. MEG results show a significant decrease in beta desynchronization and faster resynchronization in sensorimotor areas contralateral to the immobilized hand. TMS results show a significant increase in resting motor threshold in motor cortex contralateral to the constrained hand, suggesting a decrease in corticospinal excitability in the projections to the constrained hand. These results demonstrate a direct and rapid effect of immobilization on MI processes of the constrained hand, suggesting that limb nonuse may not only affect motor execution, as evidenced by previous studies, but also MI. These findings have important implications for the effectiveness of therapeutic approaches that use MI as a rehabilitation tool to ameliorate the negative effects of limb nonuse.

The multisensory perception of co-speech gestures: a review and meta-analysis of neuroimaging studies

Co-speech gestures constitute a unique form of multimodal communication because here the hand movements are temporally synchronized and semantically integrated with speech. Recent neuroimaging studies indicate that the perception of co-speech gestures might engage a core set of frontal, temporal, and parietal areas. However, no study has compared the neural processes during perception of different types of co-speech gestures, such as beat, deictic, iconic, and metaphoric co-speech gestures. The purpose of this study was to review the existing literature on the neural correlates of co-speech gesture perception and to test whether different types of co-speech gestures elicit a common pattern of brain activity in the listener. To this purpose, we conducted a meta-analysis of neuroimaging studies, which used different types of co-speech gestures to investigate the perception of multimodal (co-speech gestures) in contrast to unimodal (speech or gestures) stimuli. The results show that co-speech gesture perception consistently engages temporal regions related to auditory and movement perception as well as frontal-parietal regions associated with action understanding. The results of this study suggest that brain regions involved in multisensory processing and action understanding constitute the general core of co-speech gesture perception.

Individual differences in structural and functional connectivity predict speed of emotion discrimination

In social interactions, individuals who are slower at differentiating between facial expressions signalling direct and indirect threat might be at a serious disadvantage. However, the neurobiological underpinnings of individual differences in face processing are not yet fully understood. The aim of this study was to use multimodal neuroimaging to investigate how the speed of emotion recognition is related to the structural and functional connectivity underlying the differentiation of direct and indirect threat displays. Our results demonstrate that individuals, who are faster at discriminating angry faces, engaged areas of the extended emotional system more strongly than individuals with slower reaction times, showed higher white matter integrity in the inferior longitudinal fasciculus (ILF), as well as stronger functional connectivity with the right amygdala. In contrast, individuals, who were faster at discriminating fearful faces, engaged visual-attentional regions outside of the face processing network more strongly than individuals with slower reaction times, showed higher white matter integrity in the ILF, as well as reduced functional connectivity with the right amygdala. Our findings suggest that the high survival value of rapid and appropriate responses to threat has defined but separate neurobiological correlates for angry and fearful facial expressions.

The relation of structural integrity and task-related functional connectivity in the aging brain

The relations among structural integrity, functional connectivity (FC), and cognitive performance in the aging brain are still understudied. Here, we used multimodal and multivariate approaches to specifically examine age-related changes in task-related FC, gray-matter volumetrics, white-matter integrity, and performance. Our results are two-fold, showing (i) age-related differences in FC of the working memory network and (ii) age-related recruitment of a compensatory network associated with better accuracy on the task. Increased connectivity in the compensatory network correlates positively with preserved white-matter integrity in bilateral frontoparietal tracks and with larger gray-matter volume of right inferior parietal lobule. These findings demonstrate the importance of structural integrity and FC in working memory performance associated with healthy aging.

Adaptive contextualization: a new role for the default mode network in affective learning

Safety learning describes the ability to learn that certain cues predict the absence of a dangerous or threatening event. Although incidental observations of activity within the default mode network (DMN) during the processing of safety cues have been reported previously, there is as yet no evidence demonstrating that the DMN plays a functional rather than a corollary role in safety learning. Using functional magnetic resonance imaging and a Pavlovian fear conditioning and extinction paradigm, we investigated the neural correlates of danger and safety learning. Our results provide evidence for a functional role of the DMN by showing that (i) the DMN is activated by safety but not danger cues, (ii) the DMN is anti‐correlated with a fear‐processing network, and (iii) DMN activation increases with safety learning. Based on our results, we formulate a novel proposal, arguing that activity within the DMN supports the contextualization of safety memories, constrains the generalization of fear, and supports adaptive fear learning. Our findings have important implications for our understanding of affective and stress disorders, which are characterized by aberrant DMN activity, as they suggest that therapies targeting the DMN through mindfulness practice or brain stimulation might help prevent pathological over‐generalization of fear associations. Hum Brain Mapp 38:1082–1091, 2017.

A common functional neural network for overt production of speech and gesture.

The perception of co-speech gestures, i.e., hand movements that co-occur with speech, has been investigated by several studies. The results show that the perception of co-speech gestures engages a core set of frontal, temporal, and parietal areas. However, no study has yet investigated the neural processes underlying the production of co-speech gestures. Specifically, it remains an open question whether Brocas area is central to the coordination of speech and gestures as has been suggested previously. The objective of this study was to use functional magnetic resonance imaging to (i) investigate the regional activations underlying overt production of speech, gestures, and co-speech gestures, and (ii) examine functional connectivity with Brocas area. We hypothesized that co-speech gesture production would activate frontal, temporal, and parietal regions that are similar to areas previously found during co-speech gesture perception and that both speech and gesture as well as co-speech gesture production would engage a neural network connected to Brocas area. Whole-brain analysis confirmed our hypothesis and showed that co-speech gesturing did engage brain areas that form part of networks known to subserve language and gesture. Functional connectivity analysis further revealed a functional network connected to Brocas area that is common to speech, gesture, and co-speech gesture production. This network consists of brain areas that play essential roles in motor control, suggesting that the coordination of speech and gesture is mediated by a shared motor control network. Our findings thus lend support to the idea that speech can influence co-speech gesture production on a motoric level.