The idea that verbal and non-verbal forms of memory are segregated in their entirety, and localized to the left and right hippocampi, is arguably the most influential concept in the neuropsychology of temporal lobe epilepsy, forming a cornerstone of pre-surgical decision making, and a frame for interpreting postoperative outcome. This critical review begins by examining some of the unexpressed but inescapable assumptions of the material-specificity model: (i) verbal and non-verbal memory are unitary and internally homogenous constructs; and (ii) left and right memory systems are assumed to be independent, self-contained modules. The next section traces the origins of an alternative view, emanating largely from three challenges to these assumptions: (i) verbal memory is systematically fractionated by left mesial temporal foci; (ii) the resulting components are differentially localized within the left temporal lobe; and (iii) verbal and non-verbal memory functions are not entirely lateralized. It is argued here that the perirhinal cortex is a key node in a more extensive network mediating protosemantic associative memory. Impairment of this fundamental memory system is a proximal neurocognitive marker of mesial temporal epileptogenesis.

We suggest that this reduced connectivity in left temporal lobe epilepsy may reflect a disturbance of the language network during resting state in patients and may be related to subtle language difficulties in this patient population.

Neuroimaging is increasingly used to supplement the clinical diagnosis of dementia with Lewy bodies (DLB) by showing reduced occipital metabolism and perfusion and reduced striatal dopaminergic innervation. We aimed to optimize the interpretation of 18 F-FDG PET images for differentiating DLB from Alzheimer disease (AD) and to compare the results with dopamine transporter imaging using 123 I-b-carbomethoxy-3ß-(4-iodophenyl)-tropane ( 123 I-b-CIT) SPECT. Methods: Fourteen subjects with a clinical diagnosis of DLB and 10 with AD underwent both 18 F-FDG PET and 123 I-b-CIT SPECT. Four DLB and 1 AD diagnoses were subsequently confirmed at autopsy. Diagnostic accuracy was calculated for visual interpretation by 3 readers of standard 3-plane and stereotactic surface projection 18 F-FDG PET images, receiver-operating-characteristic analysis of regional 18 F-FDG uptake, and a cutoff value for the striatal-to-occipital binding ratio of b-CIT defined by receiver-operating-characteristic analysis. Results: Visual interpretation of 3-plane 18 F-FDG PET images had a sensitivity of 83% and specificity of 93% for DLB, slightly higher than the results with the stereotactic surface projection images. Regionally, hypometabolism in the lateral occipital cortex had the highest sensitivity (88%), but relative preservation of the mid or posterior cingulate gyrus (cingulate island sign) had the highest specificity (100%). Region-of-interest analysis revealed that occipital hypometabolism and relative preservation of the posterior cingulate both had a sensitivity of 77% and specificity of 80%. b-CIT achieved 100% accuracy and greater effect size than did 18 F-FDG PET (Cohen d 5 4.1 vs. 1.9). Conclusion: Both 18 F-FDG PET and 123 I-b-CIT SPECT appear useful for the diagnosis of DLB, although the latter provides more robust results. The cingulate island sign may enhance the specificity of 18 F-FDG PET.

These frequently seen ipsilateral changes are not caused by gliosis and may reflect a nonspecific increase in water content in the temporal lobe. This may be due to myelin abnormalities or some other as yet unidentified pathologic factor.

SMCs were related to solely by poorer mood (greater depressive and anxious symptomatology) in the cognitively healthy elderly however mean levels were subclinical. This finding argues for the assessment of affective symptomatology in conjunction with cognitive assessment in elderly memory complainers. Future AIBL research will focus on assessing other AD biomarkers, such as brain atrophy and Aβ plasma markers, in relation to complaint severity. Once our 36-month follow-up data are collected, we propose to assess whether SMCs can predict future cognitive decline.