Valerie Bonnelle

White Matter Damage and Cognitive Impairment after Traumatic Brain Injury.

White matter disruption is an important determinant of cognitive impairment after brain injury, but conventional neuroimaging underestimates its extent. In contrast, diffusion tensor imaging provides a validated and sensitive way of identifying the impact of axonal injury. The relationship between cognitive impairment after traumatic brain injury and white matter damage is likely to be complex. We applied a flexible technique—tract-based spatial statistics—to explore whether damage to specific white matter tracts is associated with particular patterns of cognitive impairment. The commonly affected domains of memory, executive function and information processing speed were investigated in 28 patients in the post-acute/chronic phase following traumatic brain injury and in 26 age-matched controls. Analysis of fractional anisotropy and diffusivity maps revealed widespread differences in white matter integrity between the groups. Patients showed large areas of reduced fractional anisotropy, as well as increased mean and axial diffusivities, compared with controls, despite the small amounts of cortical and white matter damage visible on standard imaging. A stratified analysis based on the presence or absence of microbleeds (a marker of diffuse axonal injury) revealed diffusion tensor imaging to be more sensitive than gradient-echo imaging to white matter damage. The location of white matter abnormality predicted cognitive function to some extent. The structure of the fornices was correlated with associative learning and memory across both patient and control groups, whilst the structure of frontal lobe connections showed relationships with executive function that differed in the two groups. These results highlight the complexity of the relationships between white matter structure and cognition. Although widespread and, sometimes, chronic abnormalities of white matter are identifiable following traumatic brain injury, the impact of these changes on cognitive function is likely to depend on damage to key pathways that link nodes in the distributed brain networks supporting high-level cognitive functions.

Distinct frontal systems for response inhibition, attentional capture, and error processing

Stopping an action in response to an unexpected event requires both that the event is attended to, and that the action is inhibited. Previous neuroimaging investigations of stopping have failed to adequately separate these cognitive elements. Here we used a version of the widely used Stop Signal Task that controls for the attentional capture of stop signals. This allowed us to fractionate the contributions of frontal regions, including the right inferior frontal gyrus and medial frontal cortex, to attentional capture, response inhibition, and error processing. A ventral attentional system, including the right inferior frontal gyrus, has been shown to respond to unexpected stimuli. In line with this evidence, we reasoned that lateral frontal regions support attentional capture, whereas medial frontal regions, including the presupplementary motor area (pre-SMA), actually inhibit the ongoing action. We tested this hypothesis by contrasting the brain networks associated with the presentation of unexpected stimuli against those associated with outright stopping. Functional MRI images were obtained in 26 healthy volunteers. Successful stopping was associated with activation of the right inferior frontal gyrus, as well as the pre-SMA. However, only activation of the pre-SMA differentiated stopping from a high-level baseline that controlled for attentional capture. As expected, unsuccessful attempts at stopping activated the anterior cingulate cortex. In keeping with work in nonhuman primates these findings demonstrate that successful motor inhibition is specifically associated with pre-SMA activation.

Salience network integrity predicts default mode network function after traumatic brain injury

Efficient behavior involves the coordinated activity of large-scale brain networks, but the way in which these networks interact is uncertain. One theory is that the salience network (SN)—which includes the anterior cingulate cortex, presupplementary motor area, and anterior insulae—regulates dynamic changes in other networks. If this is the case, then damage to the structural connectivity of the SN should disrupt the regulation of associated networks. To investigate this hypothesis, we studied a group of 57 patients with cognitive impairments following traumatic brain injury (TBI) and 25 control subjects using the stop-signal task. The pattern of brain activity associated with stop-signal task performance was studied by using functional MRI, and the structural integrity of network connections was quantified by using diffusion tensor imaging. Efficient inhibitory control was associated with rapid deactivation within parts of the default mode network (DMN), including the precuneus and posterior cingulate cortex. TBI patients showed a failure of DMN deactivation, which was associated with an impairment of inhibitory control. TBI frequently results in traumatic axonal injury, which can disconnect brain networks by damaging white matter tracts. The abnormality of DMN function was specifically predicted by the amount of white matter damage in the SN tract connecting the right anterior insulae to the presupplementary motor area and dorsal anterior cingulate cortex. The results provide evidence that structural integrity of the SN is necessary for the efficient regulation of activity in the DMN, and that a failure of this regulation leads to inefficient cognitive control.

Default Mode Network Connectivity Predicts Sustained Attention Deficits after Traumatic Brain Injury

Traumatic brain injury (TBI) frequently produces impairments of attention in humans. These can result in a failure to maintain consistent goal-directed behavior. A predominantly right-lateralized frontoparietal network is often engaged during attentionally demanding tasks. However, lapses of attention have also been associated with increases in activation within the default mode network (DMN). Here, we study TBI patients with sustained attention impairment, defined on the basis of the consistency of their behavioral performance over time. We show that sustained attention impairments in patients are associated with an increase in DMN activation, particularly within the precuneus and posterior cingulate cortex. Furthermore, the interaction of the precuneus with the rest of the DMN at the start of the task, i.e., its functional connectivity, predicts which patients go on to show impairments of attention. Importantly, this predictive information is present before any behavioral evidence of sustained attention impairment, and the relationship is also found in a subgroup of patients without focal brain damage. TBI often results in diffuse axonal injury, which produces cognitive impairment by disconnecting nodes in distributed brain networks. Using diffusion tensor imaging, we demonstrate that structural disconnection within the DMN also correlates with the level of sustained attention. These results show that abnormalities in DMN function are a sensitive marker of impairments of attention and suggest that changes in connectivity within the DMN are central to the development of attentional impairment after TBI.

Traumatic brain injury impairs small-world topology

Objective: We test the hypothesis that brain networks associated with cognitive function shift away from a “small-world” organization following traumatic brain injury (TBI). Methods: We investigated 20 TBI patients and 21 age-matched controls. Resting-state functional MRI was used to study functional connectivity. Graph theoretical analysis was then applied to partial correlation matrices derived from these data. The presence of white matter damage was quantified using diffusion tensor imaging. Results: Patients showed characteristic cognitive impairments as well as evidence of damage to white matter tracts. Compared to controls, the graph analysis showed reduced overall connectivity, longer average path lengths, and reduced network efficiency. A particular impact of TBI is seen on a major network hub, the posterior cingulate cortex. Taken together, these results confirm that a network critical to cognitive function shows a shift away from small-world characteristics. Conclusions: We provide evidence that key brain networks involved in supporting cognitive function become less small-world in their organization after TBI. This is likely to be the result of diffuse white matter damage, and may be an important factor in producing cognitive impairment after TBI.

Damage to the Salience Network and Interactions with the Default Mode Network

Interactions between the Salience Network (SN) and the Default Mode Network (DMN) are thought to be important for cognitive control. However, evidence for a causal relationship between the networks is limited. Previously, we have reported that traumatic damage to white matter tracts within the SN predicts abnormal DMN function. Here we investigate the effect of this damage on network interactions that accompany changing motor control. We initially used fMRI of the Stop Signal Task to study response inhibition in humans. In healthy subjects, functional connectivity (FC) between the right anterior insula (rAI), a key node of the SN, and the DMN transiently increased during stopping. This change in FC was not seen in a group of traumatic brain injury (TBI) patients with impaired cognitive control. Furthermore, the amount of SN tract damage negatively correlated with FC between the networks. We confirmed these findings in a second group of TBI patients. Here, switching rather than inhibiting a motor response: (1) was accompanied by a similar increase in network FC in healthy controls; (2) was not seen in TBI patients; and (3) tract damage after TBI again correlated with FC breakdown. This shows that coupling between the rAI and DMN increases with cognitive control and that damage within the SN impairs this dynamic network interaction. This work provides compelling evidence for a model of cognitive control where the SN is involved in the attentional capture of salient external stimuli and signals the DMN to reduce its activity when attention is externally focused.

Individual prediction of white matter injury following traumatic brain injury

Traumatic brain injury (TBI) often results in traumatic axonal injury (TAI). This can be difficult to identify using conventional imaging. Diffusion tensor imaging (DTI) offers a method of assessing axonal damage in vivo, but has previously mainly been used to investigate groups of patients. Machine learning techniques are increasingly used to improve diagnosis based on complex imaging measures. We investigated whether machine learning applied to DTI data can be used to diagnose white matter damage after TBI and to predict neuropsychological outcome in individual patients.

Individual Differences in Premotor Brain Systems Underlie Behavioral Apathy

Lack of physical engagement, productivity, and initiative—so-called “behavioral apathy”—is a common problem with significant impact, both personal and economic. Here, we investigate whether there might be a biological basis to such lack of motivation using a new effort and reward-based decision-making paradigm, combined with functional and diffusion-weighted imaging. We hypothesized that behavioral apathy in otherwise healthy people might be associated with differences in brain systems underlying either motivation to act (specifically in effort and reward-based decision-making) or in action processing (transformation of an intention into action). The results demonstrate that behavioral apathy is associated with increased effort sensitivity as well as greater recruitment of neural systems involved in action anticipation: supplementary motor area (SMA) and cingulate motor zones. In addition, decreased structural and functional connectivity between anterior cingulate cortex (ACC) and SMA were associated with increased behavioral apathy. These findings reveal that effort sensitivity and translation of intentions into actions might make a critical contribution to behavioral apathy. We propose a mechanism whereby inefficient communication between ACC and SMA might lead to increased physiological cost—and greater effort sensitivity—for action initiation in more apathetic people.

Characterization of reward and effort mechanisms in apathy

Highlights • Apathy in the normal population is dissociable from depression and anhedonia.• Apathy in the normal population is related to the modulation of physical effort people are willing to engage.• Apathy in the normal population is associated with higher subjective effort costs for small rewards.

Quantifying motivation with effort-based decision-making paradigms in health and disease

Motivation can be characterized as a series of cost-benefit valuations, in which we weigh the amount of effort we are willing to expend (the cost of an action) in return for particular rewards (its benefits). Human motivation has traditionally been measured with self-report and questionnaire-based tools, but an inherent limitation of these methods is that they are unable to provide a mechanistic explanation of the processes underlying motivated behavior. A major goal of current research is to quantify motivation objectively with effort-based decision-making paradigms, by drawing on a rich literature from nonhuman animals. Here, we review this approach by considering the development of these paradigms in the laboratory setting over the last three decades, and their more recent translation to understanding choice behavior in humans. A strength of this effort-based approach to motivation is that it is capable of capturing the wide range of individual differences, and offers the potential to dissect motivation into its component elements, thus providing the basis for more accurate taxonomic classifications. Clinically, modeling approaches might provide greater sensitivity and specificity to diagnosing disorders of motivation, for example, in being able to detect subclinical disorders of motivation, or distinguish a disorder of motivation from related but separate syndromes, such as depression. Despite the great potential in applying effort-based paradigms to index human motivation, we discuss several caveats to interpreting current and future studies, and the challenges in translating these approaches to the clinical setting.