fMRI prediction of naming change after adult temporal lobe epilepsy surgery: Activation matters.

OBJECTIVE: We aimed to predict language deficits after epilepsy surgery. In addition to evaluating surgical factors examined previously, we determined the impact of the extent of functional magnetic resonance imaging (fMRI) activation that was resected on naming ability. METHOD: Thirty-five adults (mean age 37.5 ± 10.9 years, 13 male) with temporal lobe epilepsy completed a preoperative fMRI auditory description decision task, which reliably activates frontal and temporal language networks. Patients underwent temporal lobe resections (20 left resection). The Boston Naming Test (BNT) was used to determine language functioning before and after surgery. Language dominance was determined for Broca and Wernicke area (WA) by calculating a laterality index following statistical parametric mapping processing. We used an innovative method to generate anatomic resection masks automatically from pre- and postoperative MRI tissue map comparison. This mask provided the following: (a) resection volume; (b) overlap between resection and preoperative activation; and (c) overlap between resection and WA. We examined postoperative language change predictors using stepwise linear regression. Predictors included parameters described above as well as age at seizure onset (ASO), preoperative BNT score, and resection side and its relationship to language dominance. RESULTS: Seven of 35 adults had significant naming decline (6 dominant-side resections). The final regression model predicted 38% of the naming score change variance (adjusted r2  = 0.28, P = 0.012). The percentage of top 10% fMRI activation resected (P = 0.017) was the most significant contributor. Other factors in the model included WA LI, ASO, volume of WA resected, and WA LI absolute value (extent of laterality). SIGNIFICANCE: Resection of fMRI activation during a word-definition decision task is an important factor for postoperative change in naming ability, along with other previously reported predictors. Currently, many centers establish language dominance using fMRI. Our results suggest that the amount of the top 10% of language fMRI activation in the intended resection area provides additional predictive power and should be considered when planning surgical resection.

Effects of neonatal fluoxetine exposure on behavior across development in rats selectively bred for an infantile affective trait.

Infants born to women with depressive symptoms are at higher risk for insecure attachment and behavioral problems. Thus current medical practice is to continue psychotropic medication of pregnant women with depression despite concerns about its behavioral teratology. There are few animal studies focused on long-term behavioral effects of prenatal antidepressant exposure; in addition, studies have not looked at individual differences in baseline affective state as a source of response variability. In this study, fluoxetine, a selective serotonin reuptake inhibitor (SSRI), was administered to male and female rat pups from postnatal days 2-7 to model exposure to antidepressants in the human third trimester. Four behavioral measures were conducted from the neonatal to adult age periods in Low and High lines selectively bred for their rate of ultrasonic vocalizations after brief maternal separation. Neonatal fluoxetine administration decreased distress calls in both lines, but to a greater extent in High line rats than Low line. Neonatal fluoxetine also impaired motor coordination in neonates. Neonatal fluoxetine administration decreased social behavior in both juvenile and adult subjects. Fluoxetine-related reductions in anxiety behavior were not observed at the two older ages. As expected, High line subjects displayed more anxiety behavior than Low line subjects at all three test ages. These results suggest that there are may be significant behavioral consequences of antidepressant use during late pregnancy on offspring maternal attachment and social behavior, with implications for increased risk of autism spectrum disorders.

Automated versus manual hippocampal segmentation in preoperative and postoperative patients with epilepsy.

OBJECTIVE: To compare manual and automated preoperative and postoperative hippocampal volume measurements in patients with intractable epilepsy. METHODS: We studied 34 patients referred to the Clinical Epilepsy Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH) for evaluation of intractable epilepsy and 21 normal volunteers who received 1.5 or 3 T GE Signa magnetic resonance imaging (MRI) scans. Hippocampal volumes were traced manually on each slice and assembled into three-dimensional volumes by investigators who were blinded to other data. Automated volumetric measurements were obtained using FreeSurfer. Statistical analysis was performed with GraphPad Prism. RESULTS: Automated hippocampal volumes were larger than manual volumes in both patients and normal volunteers (p < 0.05). Right to left hemisphere hippocampal ratio and percent of hippocampus resected did not differ significantly by segmentation method. It was not possible to obtain accurate total resection volumes with the automated method. SIGNIFICANCE: Values such as side-to-side ratio and percent resected may be more directly translatable between manual and automated methods than absolute measures of volume. Accurate determination of resection volumes is important for studies of the effects of surgery on both seizure control and postoperative neuropsychological deficits. Our preliminary data suggest that FreeSurfer may provide an accurate and simple method for quantitating hippocampal resections. However, it may be less valuable for large or extratemporal resections, or when distortions of normal anatomy are present. A PowerPoint slide summarizing this article is available for download in the Supporting Information section here.