Morphological-molecular taxonomy and population genetic structure of common and Egyptian soles of the Adriatic Sea

A total of 352 specimens were analyzed to achieve the different aims of this thesis. 255 central-northern Adriatic specimens of S. solea and S. aegyptiaca were molecularly analysed using microsatellite locus Sos(AC)40 and 205 also morphologically due to evaluate the abundance and the distribution of the cryptic species S. aegyptiaca and to confirm morphologic analyses. Morphological and molecular analyses comparated show a correspondence of 96%. A combined morphologic approach could be proposed to apply multiple criteria on the analyzed external morphological keys. The Adriatic Egyptian soles may lives in shallow waters (up 30 m) and in brackish lagoon. 127 samples of Adriatic common sole added to 326 samples of previous studies showed, using mitochondrial marker (CytB), that the Adriatic Sea as contact zone between Tyrrhenian and Aegean Sea, the divergence within the Adriatic Sea is low but significant between central-north and south, with a longitudinal strong gene flow in central-northern side. It’s also showed as in the Adriatic Sea two near-panmictic populations of common sole exist.

Simulating event related potentials in tasks involving conflict resolution: a neural network

In this thesis, the main Executive Control theories are exposed. Methods typical of Cognitive and Computational Neuroscience are introduced and the role of behavioural tasks involving conflict resolution in the response elaboration, after the presentation of a stimulus to the subject, are highlighted. In particular, the Eriksen Flanker Task and its variants are discussed. Behavioural data, from scientific literature, are illustrated in terms of response times and error rates. During experimental behavioural tasks, EEG is registered simultaneously. Thanks to this, event related potential, related with the current task, can be studied. Different theories regarding relevant event related potential in this field - such as N2, fERN (feedback Error Related Negativity) and ERN (Error Related Negativity) – are introduced. The aim of this thesis is to understand and simulate processes regarding Executive Control, including performance improvement, error detection mechanisms, post error adjustments and the role of selective attention, with the help of an original neural network model. The network described here has been built with the purpose to simulate behavioural results of a four choice Eriksen Flanker Task. Model results show that the neural network can simulate response times, error rates and event related potentials quite well. Finally, results are compared with behavioural data and discussed in light of the mentioned Executive Control theories. Future perspective for this new model are outlined.