Spatial patterns of phosphorylation-dependent TDP-43-immunoreactive neuronal cytoplasmic inclusions (NCI) in frontotemporal lobar degeneration with TDP-43 proteinopathy (FTLD-TDP)

The transactive response (TAR) DNA-binding protein of 43kDa (TDP-43) is an RNA binding protein encoded by the TARDPB gene. Abnormal aggregations of TDP-43 in neurons in the form of neuronal cytoplasmic inclusions (NCI) are the pathological hallmark of frontotemporal lobar degeneration with TDP-43 proteinopathy (FTLD-TDP). To investigate the role of TDP-43 in FTLD-TDP, the spatial patterns of the NCI were studied in frontal and temporal cortex of FTLD-TDP cases using a phosphorylation dependent anti-TDP-43 antibody (pTDP-43). In many regions, the NCI formed clusters and the clusters were distributed regularly parallel to the tissue boundary. In about 35% of cortical regions, cluster size of the NCI was within the size range of the modular columns of the cortex. The spatial patterns of the pTDP-immunoreactive inclusions were similar to those revealed by a phosphorylation-independent anti-TDP-43 antibody and also similar to inclusions characterized by other molecular pathologies such as tau, ?-synuclein and ‘fused in sarcoma’ (FUS). In conclusion, the data suggest degeneration of cortical and hippocampal anatomical pathways associated with accumulation of cellular pTDP-43 is characteristic of FTLD-TDP. In addition, the data are consistent with the hypothesis of cell to cell transfer of pTDP-43 within the brain.

A comparison of spatial patterns of TDP-43 cellular inclusions in familial and sporadic frontotemporal lobar degeneration with TDP-43 proteinopathy

Abnormal protein aggregates of transactive response (TAR) DNA-binding protein (TDP-43) in the form of neuronal cytoplasmic inclusions (NCI), oligodendroglial inclusions (GI), neuronal internuclear inclusions (NII), and dystrophic neurites (DN) are the pathological hallmark of frontotemporal lobar degeneration with TDP-43 proteinopathy (FTLD-TDP). To investigate the role of phosphorylated TDP-43 (pTDP-43) in neurodegeneration in FTLD-TDP, the spatial patterns of the pTDP-43-immunoreactive NCI, GI, NII, and DN were studied in frontal and temporal cortex in three groups of cases: (1) familial FTLD-TDP caused by progranulin (GRN) mutation, (2) a miscellaneous group of familial cases containing cases caused by valosin-containing protein (VCP) mutation, ubiquitin associated protein 1 (UBAP1) mutation, and cases not associated with currently known genes, and (3) sporadic FTLD-TDP. In a significant number of brain regions, the pTDP-43-immunoreactive inclusions developed in clusters and the clusters were distributed regularly parallel to the tissue boundary. The spatial patterns of the inclusions were similar to those revealed by a phosphorylation-independent anti-TDP-43 antibody. The spatial patterns and cluster sizes of the pTDP-43-immunoreactive inclusions were similar in GRN mutation cases, remaining familial cases, and in sporadic FTLD-TDP. Hence, pathological changes initiated by different genetic factors in familial cases and by unknown causes in sporadic FTLD-TDP appear to follow a parallel course resulting in very similar patterns of degeneration of frontal and temporal lobes.

Perception of global image contrast is predicted by the same spatial integration model of gain control as detection and discrimination

How are the image statistics of global image contrast computed? We answered this by using a contrast-matching task for checkerboard configurations of ‘battenberg’ micro-patterns where the contrasts and spatial spreads of interdigitated pairs of micro-patterns were adjusted independently. Test stimuli were 20 × 20 arrays with various sized cluster widths, matched to standard patterns of uniform contrast. When one of the test patterns contained a pattern with much higher contrast than the other, that determined global pattern contrast, as in a max() operation. Crucially, however, the full matching functions had a curious intermediate region where low contrast additions for one pattern to intermediate contrasts of the other caused a paradoxical reduction in perceived global contrast. None of the following models predicted this: RMS, energy, linear sum, max, Legge and Foley. However, a gain control model incorporating wide-field integration and suppression of nonlinear contrast responses predicted the results with no free parameters. This model was derived from experiments on summation of contrast at threshold, and masking and summation effects in dipper functions. Those experiments were also inconsistent with the failed models above. Thus, we conclude that our contrast gain control model (Meese & Summers, 2007) describes a fundamental operation in human contrast vision.