Caracterização do comportamento reprodutivo do cavalo-marinho de focinho comprido (Hippocampus guttulatus, Cuvier 1928)

Dissertação de Mestrado, Biologia Marinha, Especialização em Pescas e Aquacultura, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2009

Sobrevivência e crescimento de juvenis de cavalos-marinhos (Hippocampus sp.): caso de estudo: Hippocampus erectus (Perry, 1810)

Dissertação de mest., Ciências, Faculdade de Ciências do Mar e do Ambiente, Univ. do Algarve, 2009

Multi-scale keypoints in V1 and face detection

End-stopped cells in cortical area V1, which combine out- puts of complex cells tuned to different orientations, serve to detect line and edge crossings (junctions) and points with a large curvature. In this paper we study the importance of the multi-scale keypoint representa- tion, i.e. retinotopic keypoint maps which are tuned to different spatial frequencies (scale or Level-of-Detail). We show that this representation provides important information for Focus-of-Attention (FoA) and object detection. In particular, we show that hierarchically-structured saliency maps for FoA can be obtained, and that combinations over scales in conjunction with spatial symmetries can lead to face detection through grouping operators that deal with keypoints at the eyes, nose and mouth, especially when non-classical receptive field inhibition is employed. Al- though a face detector can be based on feedforward and feedback loops within area V1, such an operator must be embedded into dorsal and ventral data streams to and from higher areas for obtaining translation-, rotation- and scale-invariant face (object) detection.

Object categorisations using templates constructed from multi-scale line and edge representations

Object categorisation is linked to detection, segregation and recognition. In the visual system, these processes are achieved in the ventral \what"and dorsal \where"pathways [3], with bottom-up feature extractions in areas V1, V2, V4 and IT (what) in parallel with top-down attention from PP via MT to V2 and V1 (where). The latter is steered by object templates in memory, i.e. in prefrontal cortex with a what component in PF46v and a where component in PF46d.

Face segregation and recognition by cortical multi-scale line and edge coding

Models of visual perception are based on image representations in cortical area V1 and higher areas which contain many cell layers for feature extraction. Basic simple, complex and end-stopped cells provide input for line, edge and keypoint detection. In this paper we present an improved method for multi-scale line/edge detection based on simple and complex cells. We illustrate the line/edge representation for object reconstruction, and we present models for multi-scale face (object) segregation and recognition that can be embedded into feedforward dorsal and ventral data streams (the “what” and “where” subsystems) with feedback streams from higher areas for obtaining translation, rotation and scale invariance.

Co-localization of GnRH ligands and their receptors in the European sea bass, Dicentrarchus labrax

The migration of the hypophysiotropic GnRH (GnRH-I) neurons during early development is a crucial step in establishing a normally functioning reproductive system in all vertebrates. These neurons derive from progenitor cells in the olfactory placode and subsequently migrate to their final position in the ventral forebrain, where they mediate hypophysiotropic control over Lh. We use zebrafish as a model to investigate the path and the factors that mediate the migration of the GnRH-I neurons during early development. A transgenic line of zebrafish, in which GnRH- I neurons specifically express a reporter gene (GFP) has been developed in our lab. This was achieved by integrating a GnRH-I promoter/GFP reporter transgene into the zebrafish genome. The resulting transgenic line allows us to track the route of the GnRH-I neuronal migration in real time and in vivo. We have used this line to conduct time lapse imaging to ascertain the exact migrational path and the final position in the ventral forebrain of the GnRH-I neurons.