Diverging volumetric trajectories following pediatric traumatic brain injury.

Traumatic brain injury (TBI) is a significant public health concern, and can be especially disruptive in children, derailing on-going neuronal maturation in periods critical for cognitive development. There is considerable heterogeneity in post-injury outcomes, only partially explained by injury severity. Understanding the time course of recovery, and what factors may delay or promote recovery, will aid clinicians in decision-making and provide avenues for future mechanism-based therapeutics. We examined regional changes in brain volume in a pediatric/adolescent moderate-severe TBI (msTBI) cohort, assessed at two time points. Children were first assessed 2-5 months post-injury, and again 12 months later. We used tensor-based morphometry (TBM) to localize longitudinal volume expansion and reduction. We studied 21 msTBI patients (5 F, 8-18 years old) and 26 well-matched healthy control children, also assessed twice over the same interval. In a prior paper, we identified a subgroup of msTBI patients, based on interhemispheric transfer time (IHTT), with significant structural disruption of the white matter (WM) at 2-5 months post injury. We investigated how this subgroup (TBI-slow, N = 11) differed in longitudinal regional volume changes from msTBI patients (TBI-normal, N = 10) with normal WM structure and function. The TBI-slow group had longitudinal decreases in brain volume in several WM clusters, including the corpus callosum and hypothalamus, while the TBI-normal group showed increased volume in WM areas. Our results show prolonged atrophy of the WM over the first 18 months post-injury in the TBI-slow group. The TBI-normal group shows a different pattern that could indicate a return to a healthy trajectory

Pivotal Role of Anterior Cingulate Cortex in Working Memory after Traumatic Brain Injury in Youth

In this fMRI study, the functions of the anterior cingulate cortex (ACC) were studied in a group of adolescents who had sustained a moderate to severe traumatic brain injury (TBI). A spatial working memory task with varying working memory loads, representing experimental conditions of increasing difficulty, was administered. In a cross-sectional comparison between the patients and a matched control group, patients performed worse than Controls, showing longer reaction times and lower response accuracy on the spatial working memory task. Brain imaging findings suggest a possible double-dissociation: activity of the ACC in the TBI group, but not in the Control group, was associated with task difficulty; conversely, activity of the left sensorimotor cortex (lSMC) in the Control group, but not in the TBI group, was correlated with task difficulty. In addition to the main cross-sectional study, a longitudinal study of a group of adolescent patients with moderate to severe TBI was done using fMRI and the same spatial working memory task. The patient group was studied at two time-points: one time-point during the post-acute phase and one time-point 12 months later, during the chronic phase. Results indicated that patients’ behavioral performance improved over time, suggesting cognitive recovery. Brain imaging findings suggest that, over this 12-month period, patients recruited less of the ACC and more of the lSMC in response to increasing task difficulty. The role of ACC in executive functions following a moderate to severe brain injury in adolescence is discussed within the context of conflicting models of the ACC functions in the existing literature

Functional Brain Hyperactivations Are Linked to an Electrophysiological Measure of Slow Interhemispheric Transfer Time after Pediatric Moderate/Severe Traumatic Brain Injury.

Increased task-related blood oxygen level dependent (BOLD) activation is commonly observed in functional magnetic resonance imaging (fMRI) studies of moderate/severe traumatic brain injury (msTBI), but the functional relevance of these hyperactivations and how they are linked to more direct measures of neuronal function remain largely unknown. Here, we investigated how working memory load (WML)-dependent BOLD activation was related to an electrophysiological measure of interhemispheric transfer time (IHTT) in a sample of 18 msTBI patients and 26 demographically matched controls from the UCLA RAPBI (Recovery after Pediatric Brain Injury) study. In the context of highly similar fMRI task performance, a subgroup of TBI patients with slow IHTT had greater BOLD activation with higher WML than both healthy control children and a subgroup of msTBI patients with normal IHTT. Slower IHTT treated as a continuous variable was also associated with BOLD hyperactivation in the full TBI sample and in controls. Higher WML-dependent BOLD activation was related to better performance on a clinical cognitive performance index, an association that was more pronounced within the patient group with slow IHTT. Our previous work has shown that a subgroup of children with slow IHTT after pediatric msTBI has increased risk for poor white matter organization, long-term neurodegeneration, and poor cognitive outcome. BOLD hyperactivations after msTBI may reflect neuronal compensatory processes supporting higher-order capacity demanding cognitive functions in the context of inefficient neuronal transfer of information. The link between BOLD hyperactivations and slow IHTT adds to the multi-modal validation of this electrophysiological measure as a promising biomarker

Decoding Continuous Variables from Neuroimaging Data: Basic and Clinical Applications

The application of statistical machine learning techniques to neuroimaging data has allowed researchers to decode the cognitive and disease states of participants. The majority of studies using these techniques have focused on pattern classification to decode the type of object a participant is viewing, the type of cognitive task a participant is completing, or the disease state of a participant's brain. However, an emerging body of literature is extending these classification studies to the decoding of values of continuous variables (such as age, cognitive characteristics, or neuropsychological state) using high-dimensional regression methods. This review details the methods used in such analyses and describes recent results. We provide specific examples of studies which have used this approach to answer novel questions about age and cognitive and disease states. We conclude that while there is still much to learn about these methods, they provide useful information about the relationship between neural activity and age, cognitive state, and disease state, which could not have been obtained using traditional univariate analytical methods

Decoding Developmental Differences and Individual Variability in Response Inhibition Through Predictive Analyses Across Individuals

Response inhibition is thought to improve throughout childhood and into adulthood. Despite the relationship between age and the ability to stop ongoing behavior, questions remain regarding whether these age-related changes reflect improvements in response inhibition or in other factors that contribute to response performance variability. Functional neuroimaging data shows age-related changes in neural activity during response inhibition. While traditional methods of exploring neuroimaging data are limited to determining correlational relationships, newer methods can determine predictability and can begin to answer these questions. Therefore, the goal of the current study was to determine which aspects of neural function predict individual differences in age, inhibitory function, response speed, and response time variability. We administered a stop-signal task requiring rapid inhibition of ongoing motor responses to healthy participants aged 9–30. We conducted a standard analysis using GLM and a predictive analysis using high-dimensional regression methods. During successful response inhibition we found regions typically involved in motor control, such as the ACC and striatum, that were correlated with either age, response inhibition (as indexed by stop-signal reaction time; SSRT), response speed, or response time variability. However, when examining which variables neural data could predict, we found that age and SSRT, but not speed or variability of response execution, were predicted by neural activity during successful response inhibition. This predictive relationship provides novel evidence that developmental differences and individual differences in response inhibition are related specifically to inhibitory processes. More generally, this study demonstrates a new approach to identifying the neurocognitive bases of individual differences

The UCLA Study of Children with Moderate-to-Severe Traumatic Brain Injury: Event-Related Potential Measure of Interhemispheric Transfer Time

Traumatic brain injury (TBI) frequently results in diffuse axonal injury and other white matter damage. The corpus callosum (CC) is particularly vulnerable to injury following TBI. Damage to this white matter tract has been associated with impaired neurocognitive functioning in children with TBI. Event-related potentials can identify stimulus-locked neural activity with high temporal resolution. They were used in this study to measure interhemispheric transfer time (IHTT) as an indicator of CC integrity in 44 children with moderate/severe TBI at 3-5 months post-injury, compared with 39 healthy control children. Neurocognitive performance also was examined in these groups. Nearly half of the children with TBI had IHTTs that were outside the range of the healthy control group children. This subgroup of TBI children with slow IHTT also had significantly poorer neurocognitive functioning than healthy controls-even after correction for premorbid intellectual functioning. We discuss alternative models for the relationship between IHTT and neurocognitive functioning following TBI. Slow IHTT may be a biomarker that identifies children at risk for poor cognitive functioning following moderate/severe TBI

Leptin Replacement Improves Cognitive Development

Leptin changes brain structure, neuron excitability and synaptic plasticity. It also regulates the development and function of feeding circuits. However, the effects of leptin on neurocognitive development are unknown.To evaluate the effect of leptin on neurocognitive development.A 5-year-old boy with a nonconservative missense leptin gene mutation (Cys-to-Thr in codon 105) was treated with recombinant methionyl human leptin (r-metHuLeptin) at physiologic replacement doses of 0.03 mg/kg/day. Cognitive development was assessed using the Differential Ability Scales (DAS), a measure of general verbal and nonverbal functioning; and selected subtests from the NEPSY, a measure of neuropsychological functioning in children.Prior to treatment, the patient was morbidly obese, hypertensive, dyslipidemic, and hyperinsulinemic. Baseline neurocognitive tests revealed slower than expected rates of development (developmental age lower than chronological age) in a majority of the areas assessed. After two years, substantial increases in the rates of development in most neurocognitive domains were apparent, with some skills at or exceeding expectations based on chronological age. We also observed marked weight loss and resolution of hypertension, dyslipidemia and hyperinsulinemia.We concluded that replacement with r-metHuLeptin is associated with weight loss and changes in rates of development in many neurocognitive domains, which lends support to the hypothesis that, in addition to its role in metabolism, leptin may have a cognitive enhancing role in the developing central nervous system.ClinicalTrials.gov NCT00659828

Genetics of childhood-onset schizophrenia.

Schizophrenia is a heritable disorder. The genetic architecture of schizophrenia is complex and heterogeneous. This article discusses genetic studies of childhood-onset schizophrenia (COS) and compares findings in familial aggregation, common allele, and rare allele studies of COS with those for adult-onset schizophrenia (AOS). COS seems to be a rare variant of AOS with greater familial aggregation of schizophrenia spectrum disorders and higher occurrence of rare allelic variants. The usefulness of genetic screening for diagnosis and individualized treatment is limited; however, identifying common pathways through which multiple genes adversely affect neural systems offers great promise toward developing novel pharmacologic interventions