Timothy Ham

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.

The Salience Network (SN) consists of the dorsal anterior cingulate cortex (dACC) and bilateral insulae. The network responds to behaviorally salient events, and an important question is how its nodes interact. One theory is that the dACC provides the earliest cortical signal of behaviorally salient events, such as errors. Alternatively, the anterior right insula (aRI) has been proposed to provide an early cognitive control signal. As these regions frequently coactivate, it has been difficult to disentangle their roles using conventional methods. Here we use dynamic causal modeling and a Bayesian model evidence technique to investigate the causal relationships between nodes in the SN after errors. Thirty-five human subjects performed the Simon task. The task has two conditions (congruent and incongruent) producing two distinct error types. Neural activity associated with errors was investigated using fMRI. Subjects made a total of 1319 congruent and 1617 incongruent errors. Errors resulted in robust activation of the SN. Dynamic causal modeling analyses demonstrated that input into the SN was most likely via the aRI for both error types and that the aRI was the only region intrinsically connected to both other nodes. Only incongruent errors produced behavioral adaptation, and the strength of the connection between the dACC and the left insulae correlated with the extent of this behavioral change. We conclude that the aRI, not the dACC, drives the SN after errors on an attentionally demanding task, and that a change in the effective connectivity of the dACC is associated with behavioral adaptation after errors.

The maintenance of wellbeing across the lifespan depends on the preservation of cognitive function. We propose that successful cognitive aging is determined by interactions both within and between large-scale functional brain networks. Such connectivity can be estimated from task-free functional magnetic resonance imaging (fMRI), also known as resting-state fMRI (rs-fMRI). However, common correlational methods are confounded by age-related changes in the neurovascular signaling. To estimate network interactions at the neuronal rather than vascular level, we used generative models that specified both the neural interactions and a flexible neurovascular forward model. The networks' parameters were optimized to explain the spectral dynamics of rs-fMRI data in 602 healthy human adults from population-based cohorts who were approximately uniformly distributed between 18 and 88 years (www.cam-can.com). We assessed directed connectivity within and between three key large-scale networks: the salience network, dorsal attention network, and default mode network. We found that age influences connectivity both within and between these networks, over and above the effects on neurovascular coupling. Canonical correlation analysis revealed that the relationship between network connectivity and cognitive function was age-dependent: cognitive performance relied on neural dynamics more strongly in older adults. These effects were driven partly by reduced stability of neural activity within all networks, as expressed by an accelerated decay of neural information. Our findings suggest that the balance of excitatory connectivity between networks, and the stability of intrinsic neural representations within networks, changes with age. The cognitive function of older adults becomes increasingly dependent on these factors. SIGNIFICANCE STATEMENT: Maintaining cognitive function is critical to successful aging. To study the neural basis of cognitive function across the lifespan, we studied a large population-based cohort (n = 602, 18-88 years), separating neural connectivity from vascular components of fMRI signals. Cognitive ability was influenced by the strength of connection within and between functional brain networks, and this positive relationship increased with age. In older adults, there was more rapid decay of intrinsic neuronal activity in multiple regions of the brain networks, which related to cognitive performance. Our data demonstrate increased reliance on network flexibility to maintain cognitive function, in the presence of more rapid decay of neural activity. These insights will facilitate the development of new strategies to maintain cognitive ability.

PURPOSE OF REVIEW: Traumatic brain injury (TBI) often results in traumatic axonal injury (TAI). This is difficult to identify using conventional neuroimaging methods. We review recent work that uses advanced imaging methods to identify TAI following mild (m)TBI. RECENT FINDINGS: Susceptibility-weighted imaging (SWI) is a highly sensitive way of identifying microbleeds, which are a marker of TAI. Diffusion tensor imaging (DTI) provides a more flexible way of investigating white matter injury. Recent studies largely confirm that DTI is sensitive to white matter damage after mTBI. Distinct DTI abnormalities are observed in the acute and subacute/chronic stages. DTI measurements change dynamically after an injury, reflecting the evolving pathological processes. DTI abnormalities correlate with cognitive and neuropsychiatric impairments. Importantly, DTI can contribute to the prediction of clinical outcome and has begun to be applied to the study of sports and blast injury. SUMMARY: DTI and SWI are important advances in MRI that allow more detailed investigation of white matter injury. SWI is a highly sensitive way of identifying microbleeds. DTI is a flexible way of quantifying white matter integrity, and provides a method of diagnosing clinically significant white matter injury when conventional imaging is normal.

BACKGROUND: Cognitive impairment is a common and disabling consequence of traumatic brain injury (TBI) but its impact on health-related quality of life is not well understood. OBJECTIVE: To investigate the relationship between cognitive impairment and health-related quality of life (HRQoL) after TBI. METHODS: Retrospective, cross-sectional study of a specialist TBI outpatient clinic patient sample. OUTCOME MEASURES: Addenbrooke's Cognitive Examination Tool - Revised (ACE-R), and SF-36 quality of life, Beck Depression Inventory II (BDI-II), Pittsburgh Sleep Quality Index (PSQI) and Epworth Sleepiness Scale (ESS) questionnaires. RESULTS: 240 adults were assessed: n = 172 (71.7%) moderate-severe, 41 (23.8%) mild, 27 (11.3%) symptomatic TBI, 174 (72.5%) male, median age (range): 44 (22-91) years. TBI patients reported poorer scores on all domains of SF-36 compared to age-matched UK normative data. Cognitively impaired patients reported poorer HRQoL on the physical, social role and emotional role functioning, and mental health domains. Cognitive impairment predicted poorer HRQoL on the social and emotional role functioning domains, independently of depressive symptoms, sleep disturbance, daytime sleepiness and TBI severity. Mediation analysis revealed that the effect of depressive symptoms on the emotional role functioning domain of HRQoL was partially mediated by cognitive dysfunction. CONCLUSION: Cognitive impairment is associated with worse health-related quality of life after TBI and partially mediates the effect of depressive symptoms on emotional role functioning.