Type-specific dendritic integration in mouse retinal ganglion cells

Neural computation relies on the integration of synaptic inputs across a neuron’s dendritic arbour. However, it is far from understood how different cell types tune this process to establish cell-type specific computations. Here, using two-photon imaging of dendritic Ca2+ signals, electrical recordings of somatic voltage and biophysical modelling, we demonstrate that four morphologically distinct types of mouse retinal ganglion cells with overlapping excitatory synaptic input (transient Off alpha, transient Off mini, sustained Off, and F-mini Off) exhibit type-specific dendritic integration profiles: in contrast to the other types, dendrites of transient Off alpha cells were spatially independent, with little receptive field overlap. The temporal correlation of dendritic signals varied also extensively, with the highest and lowest correlation in transient Off mini and transient Off alpha cells, respectively. We show that differences between cell types can likely be explained by differences in backpropagation efficiency, arising from the specific combinations of dendritic morphology and ion channel densities

Neuronal cell types and connectivity: Lessons from the retina

We describe recent progress toward defining neuronal cell types in the mouse retina and attempt to extract lessons that may be generally useful in the mammalian brain. Achieving a comprehensive catalog of retinal cell types now appears within reach, because researchers have achieved consensus concerning two fundamental challenges. The first is accuracy-defining pure cell types rather than settling for neuronal classes that are mixtures of types. The second is completeness-developing methods guaranteed to eventually identify all cell types, as well as criteria for determining when all types have been found. Case studies illustrate how these two challenges are handled by combining state-of-the-art molecular, anatomical, and physiological techniques. Progress is also being made in observing and modeling connectivity between cell types. Scaling up to larger brain regions, such as the cortex, will require not only technical advances but also careful consideration of the challenges of accuracy and completeness

Fatty Acid Profile and Biological Data of Four Endemic Cephalaria Species Grown in Turkey

The fatty acid compositions of the n-hexane extracts of the aerial parts of four Turkish Cephalaria species (C. paphlagonica, C. stellipilis, C. davisiana and C. elazigensis var. purpurea) were analyzed by GC-MS for the first time. The oil yields of these species were determined as ranging from 0.07% to 0.36 %. Seventeen fatty acids as methyl esters were identified. All extracts were found to contain significant quantities of palmitic, linoleic (LA), stearic and alpha-linolenic acid (ALA). ALA was the most abundant fatty acid in all species (29.00%, 30.51%, 32.49% and 34.87% for C. stellipilis, C. elazigensis, C. davisiana and C. paphlagonica, respectively). Other dominant fatty acid was palmitic acid, which ranged from 19.10% to 28.23% for all species. LA was detected in a considerable amount of 19.44 % for C. paphlagonica. The n-hexane extracts of the plants were also checked for their antimicrobial and antioxidant activities