Faculty Bibliography

BACKGROUND: Given that post-traumatic headache is one of the most prevalent and long-lasting post-concussion sequelae, causes significant morbidity, and might be associated with slower neurocognitive recovery, we sought to evaluate the use of concussion screening scores in a concussion clinic population to assess for post-traumatic headache. METHODS: This is a retrospective cross-sectional study of 254 concussion patients from the New York University (NYU) Concussion Registry. Data on the headache characteristics, concussion mechanism, concussion screening scores were collected and analyzed. RESULTS: 72% of the patients had post-traumatic headache. About half (56.3%) were women. The mean age was 35 (SD 16.2). 90 (35%) patients suffered from sport-related concussions (SRC). Daily post-traumatic headache patients had higher Sport Concussion Assessment Tool (SCAT)-3 symptom severity scores than the non-daily post-traumatic headache and the headache-free patients (50.2 [SD 28.2] vs. 33.1 [SD 27.5] vs. 21.6 SD23], p < 0.001). Patients with SRC had lower headache intensity (4.47 [SD 2.5] vs. 6.24 [SD 2.28], p < 0.001) and SCAT symptom severity scores (33.9 [SD 27.4] vs. 51.4 [SD 27.7], p < 0.001) than the other patients, but there were no differences in post-traumatic headache prevalence, frequency, and Standardized Assessment of Concussion (SAC) scores. CONCLUSION: The presence and frequency of post-traumatic headache are associated with the SCAT-3 symptom severity score, which is the most important predictor for post-concussion recovery. The SCAT-3 symptom severity score might be a useful tool to help characterize patients' post-traumatic headache.

Neuropsychologists regularly conduct sport-related concussion (SRC) evaluations, although research has not tracked these assessment practices. As part of a survey of neuropsychological test usage, we analyzed data from 215 neuropsychologists who conduct SRC evaluations. Only 15% reported conducting baseline assessments of athletes as part of a sports program and 92% evaluate athletes' post-concussion without baseline data. The majority of respondents use a full battery, considered the most reliable approach for assessing concussion symptoms in athletes. Only 6% use computerized tests exclusively (>50% ImPACT). We discuss the implications of these results and address challenges faced by neuropsychologists who perform SRC evaluations.

Cognitive impairment affects more than half of all individuals living with multiple sclerosis (MS). We hypothesized that training at home with an adaptive online cognitive training program would have greater cognitive benefit than ordinary computer games in cognitively-impaired adults with MS. This was a double-blind, randomized, active-placebo-controlled trial. Participants with MS were recruited through Stony Brook Medicine and randomly assigned to either the adaptive cognitive remediation (ACR) program or active control of ordinary computer games for 60 hours over 12 weeks. Training was remotely-supervised and delivered through a study-provided laptop computer. A computer generated, blocked stratification table prepared by statistician provided the randomization schedule and condition was assigned by a study technician. The primary outcome, administered by study psychometrician, was measured by change in a neuropsychological composite measure from baseline to study end. An intent-to-treat analysis was employed and missing primary outcome values were imputed via Markov Chain Monte Carlo method. Participants in the ACR (n = 74) vs. active control (n = 61) training program had significantly greater improvement in the primary outcome of cognitive functioning (mean change in composite z score+/-SD: 0.25+/-0.45 vs. 0.09+/-0.37, p = 0.03, estimated difference = 0.16 with 95% CI: 0.02-0.30), despite greater training time in the active control condition (mean+/-SD:56.9 +/- 34.6 vs. 37.7 +/-23 .8 hours played, p = 0.006). This study provides Class I evidence that adaptive, computer-based cognitive remediation accessed from home can improve cognitive functioning in MS. This telerehabilitation approach allowed for rapid recruitment and high compliance, and can be readily applied to other neurological conditions associated with cognitive dysfunction. TRIAL REGISTRATION: Clinicaltrials.gov NCT02141386.

OBJECTIVES: The aim of this study was to evaluate the reliability and validity of three computerized neurocognitive assessment tools (CNTs; i.e., ANAM, DANA, and ImPACT) for assessing mild traumatic brain injury (mTBI) in patients recruited through a level I trauma center emergency department (ED). METHODS: mTBI (n=94) and matched trauma control (n=80) subjects recruited from a level I trauma center emergency department completed symptom and neurocognitive assessments within 72 hr of injury and at 15 and 45 days post-injury. Concussion symptoms were also assessed via phone at 8 days post-injury. RESULTS: CNTs did not differentiate between groups at any time point (e.g., M 72-hr Cohen's d=-.16, .02, and .00 for ANAM, DANA, and ImPACT, respectively; negative values reflect greater impairment in the mTBI group). Roughly a quarter of stability coefficients were over .70 across measures and test-retest intervals in controls. In contrast, concussion symptom score differentiated mTBI vs. control groups acutely), with this effect size diminished over time (72-hr and day 8, 15, and 45 Cohen's d=-.78, -.60, -.49, and -.35, respectively). CONCLUSIONS: The CNTs evaluated, developed and widely used to assess sport-related concussion, did not yield significant differences between patients with mTBI versus other injuries. Symptom scores better differentiated groups than CNTs, with effect sizes weaker than those reported in sport-related concussion studies. Nonspecific injury factors, and other characteristics common in ED settings, likely affect CNT performance across trauma patients as a whole and thereby diminish the validity of CNTs for assessing mTBI in this patient population. (JINS, 2017, 23, 293-303).

The differential contribution of medial-temporal lobe regions to verbal declarative memory is debated within the neuroscience, neuropsychology, and cognitive psychology communities. We evaluate whether the extent of surgical resection within medial-temporal regions predicts longitudinal verbal learning and memory outcomes. This single-center retrospective observational study involved patients with refractory temporal lobe epilepsy undergoing unilateral anterior temporal lobe resection from 2007 to 2015. Thirty-two participants with Engel Classes 1 and 2 outcomes were included (14 left, 18 right) and followed for a mean of 2.3 years after surgery (+/-1.5 years). Participants had baseline and postsurgical neuropsychological testing and high-resolution T1-weighted MRI scans. Postsurgical lesions were manually traced and coregistered to presurgical scans to precisely quantify resection extent of medial-temporal regions. Verbal learning and memory change scores were regressed on hippocampal, entorhinal, and parahippocampal resection volume after accounting for baseline performance. Overall, there were no significant differences in learning and memory change between patients who received left and right anterior temporal lobe resection. After controlling for baseline performance, the extent of left parahippocampal resection accounted for 27% (p = .021) of the variance in verbal short delay free recall. The extent of left entorhinal resection accounted for 37% (p = .004) of the variance in verbal short delay free recall. Our findings highlight the critical role that the left parahippocampal and entorhinal regions play in recall for verbal material.

MOTIVATION:Boolean networks (BNs) are commonly used to model genetic regulatory networks (GRNs). Due to the sensibility of the dynamical behavior to changes in the updating scheme (order in which the nodes of a network update their state values), it is increasingly common to use different updating rules in the modeling of GRNs to better capture an observed biological phenomenon and thus to obtain more realistic models.In Aracena et al. equivalence classes of deterministic update schedules in BNs, that yield exactly the same dynamical behavior of the network, were defined according to a certain label function on the arcs of the interaction digraph defined for each scheme. Thus, the interaction digraph so labeled (update digraphs) encode the non-equivalent schemes. RESULTS:We address the problem of enumerating all non-equivalent deterministic update schedules of a given BN. First, we show that it is an intractable problem in general. To solve it, we first construct an algorithm that determines the set of update digraphs of a BN. For that, we use divide and conquer methodology based on the structural characteristics of the interaction digraph. Next, for each update digraph we determine a scheme associated. This algorithm also works in the case where there is a partial knowledge about the relative order of the updating of the states of the nodes. We exhibit some examples of how the algorithm works on some GRNs published in the literature. AVAILABILITY AND IMPLEMENTATION:An executable file of the UpdateLabel algorithm made in Java and the files with the outputs of the algorithms used with the GRNs are available at: www.inf.udec.cl/ ∼lilian/UDE/ CONTACT: lilisalinas@udec.cl SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.