Working memory is a temporary storage system under attentional control. It is believed to play a central role in online processing of complex cognitive information and may also play a role in social cognition and interpersonal interactions. Adolescents with a disorder on the autism spectrum display problems in precisely these domains. Social impairments, communication difficulties, and repetitive interests and activities are core domains of autism spectrum disorders (ASD), and executive function problems are often seen throughout the spectrum. As the main cognitive theories of ASD, including the theory of mind deficit hypotheses, weak central coherence account, and the executive dysfunction theory, still fail to explain the broad spectrum of symptoms, a new perspective on the etiology of ASD is needed. Deficits in working memory are central to many theories of psychopathology, and are generally linked to frontal-lobe dysfunction. This article will review neuropsychological and (functional) brain imaging studies on working memory in adolescents with ASD. Although still disputed, it is concluded that within the working memory system specific problems of spatial working memory are often seen in adolescents with ASD. These problems increase when information is more complex and greater demands on working memory are made. Neuroimaging studies indicate a more global working memory processing or connectivity deficiency, rather than a focused deficit in the prefrontal cortex. More research is needed to relate these working memory difficulties and neuroimaging results in ASD to the behavioral difficulties as seen in individuals with a disorder on the autism spectrum.

Resective epilepsy surgery is an evidence-based curative treatment option for patients with drug-resistant focal epilepsy. The major preoperative predictor of a good surgical outcome is detection of an epileptogenic lesion by magnetic resonance imaging (MRI). Application of ultra-high field (UHF) MRI, i.e. field strengths ≥ 7 Tesla (T), may increase the sensitivity to detect such a lesion. A keyword search strategy was submitted to Pubmed, EMBASE, Cochrane Database and clinicaltrials.gov to select studies on UHF MRI in patients with epilepsy. Follow-up study selection and data extraction were performed following PRISMA guidelines. We focused on I) diagnostic gain of UHF- over conventional MRI, II) concordance of MRI-detected lesion, seizure onset zone and surgical decision-making, and III) postoperative histopathological diagnosis and seizure outcome. Sixteen observational cohort studies, all using 7T MRI were included. Diagnostic gain of 7T over conventional MRI ranged from 8% to 67%, with a pooled gain of 31%. Novel techniques to visualize pathological processes in epilepsy and lesion detection are discussed. Seizure freedom was achieved in 73% of operated patients; no seizure outcome comparison was made between 7T MRI positive, 7T negative and 3T positive patients. 7T could influence surgical decision-making, with high concordance of lesion and seizure onset zone. Focal cortical dysplasia (54%), hippocampal sclerosis (12%) and gliosis (8.1%) were the most frequently diagnosed histopathological entities. UHF MRI increases, yet variably, the sensitivity to detect an epileptogenic lesion, showing potential for use in clinical practice. It remains to be established whether this results in improved seizure outcome after surgical treatment. Prospective studies with larger cohorts of epilepsy patients, uniform scan and sequence protocols, and innovative post-processing technology are equally important as further increasing field strengths. Besides technical ameliorations, improved correlation of imaging features with clinical semiology, histopathology and clinical outcome has to be established.

The aim was to evaluate whether morphological criteria in addition to the size criterion results in better diagnostic performance of MRI for the detection of cervical lymph node metastases in patients with head and neck squamous cell carcinoma (HNSCC). Two radiologists evaluated 44 consecutive patients in which lymph node characteristics were assessed with histopathological correlation as gold standard. Assessed criteria were the short axial diameter and morphological criteria such as border irregularity and homogeneity of signal intensity on T2-weighted and contrast-enhanced T1-weighted images. Multivariate logistic regression analysis was performed: diagnostic odds ratios (DOR) with 95% confidence intervals (95% CI) and areas under the curve (AUCs) of receiver-operating characteristic (ROC) curves were determined. Border irregularity and heterogeneity of signal intensity on T₂-weighted images showed significantly increased DORs. AUCs increased from 0.67 (95% CI: 0.61–0.73) using size only to 0.81 (95% CI: 0.75–0.87) using all four criteria for observer 1 and from 0.68 (95% CI: 0.62–0.74) to 0.96 (95% CI: 0.94–0.98) for observer 2 (p < 0.001). This study demonstrated that the morphological criteria border irregularity and heterogeneity of signal intensity on T2-weighted images in addition to size significantly improved the detection of cervical lymph nodes metastases.

OBJECTIVE. Dysplasia at the bottom of a sulcus is a subtle but distinct malformation of cortical development relevant to epilepsy. The purpose of this study was to review the imaging features important to the clinical diagnosis of this lesion.MATERIALS AND METHODS. All cases recognized as typical bottom-of-sulcus dysplasia in our comprehensive epilepsy program over the period 2002–2007 were included in the study.RESULTS. In the 20 cases recognized, three major features were identified: cortical thickening at the bottom of a sulcus; a funnel-shaped extension of the lesion toward the ventricular surface, commonly with abnormal signal intensity; and an abnormal gyral pattern related to the bottom-of-sulcus dysplasia, sometimes with a puckered appearance. The pathologic features of the resected lesions were typical of focal cortical dysplasia.CONCLUSION. Bottom-of-sulcus dysplasia is a distinctive malformation of cortical development that can be diagnosed on the basis of imaging characteristics. Reliable iden...

It is often difficult to predict seizure recurrence in subjects who have suffered a first-ever epileptic seizure. In this study, the predictive value of physiological signals measured using Electroencephalography (EEG) and functional MRI (fMRI) is assessed. In particular those patients developing epilepsy (i.e. a second unprovoked seizure) that were initially evaluated as having a low risk of seizure recurrence are of interest. In total, 26 epilepsy patients, of which 8 were initially evaluated as having a low risk of seizure recurrence (i.e. converters), and 17 subjects with only a single seizure were included. All subjects underwent routine EEG as well as fMRI measurements. For diagnostic classification, features related to the temporal dynamics were determined for both the processed EEG and fMRI data. Subsequently, a logistic regression classifier was trained on epilepsy and first-seizure subjects. The trained model was tested using the clinically relevant converters group. The sensitivity, specificity, and AUC (mean ± SD) of the regression model including metrics from both modalities were 74 ± 19%, 82 ± 18%, and 0.75 ± 0.12, respectively. Positive and negative predictive values (mean ± SD) of the regression model with both EEG and fMRI features are 84 ± 14% and 78 ± 12%. Moreover, this EEG/fMRI model showed significant improvements compared to the clinical diagnosis, whereas the models using metrics from either EEG or fMRI do not reach significance (p > 0.05). Temporal metrics computationally derived from EEG and fMRI time signals may clinically aid and synergistically improve the predictive value in a first-seizure sample.