Lateral connections in the primary visual cortex (area V1 or striate cortex) have long been hypothesized to be responsible of several visual processing mechanisms such as brightness induction, chromatic induction, visual discomfort and bottom-up visual attention (also named saliency). Many computational models have been developed to independently predict these and other visual processes, but no computational model has been able to reproduce all of them simultaneously. In this work we show that a biologically plausible computational model of lateral interactions of V1 is able to simultaneously predict saliency and all the aforementioned visual processes. Our model's (named Neurodynamic Saliency WAvelet Model or NSWAM) architecture is based on Pennachio's neurodynamic model of lateral connections of V1 (defined as a network of firing rate neurons, sensitive to visual features such as brightness, color, orientation and scale). We tested NSWAM saliency predictions using images from eye tracking datasets, showing that it is an improvement with respect to previous models as well as consistent with human psychophysics. Hence, we show that our biologically plausible model of lateral connections can simultaneously explain different visual proceses present in V1 (without applying any type of training or optimization and keeping the same parametrization for all the visual processes). This can be useful for the definition of a unified architecture of the primary visual cortex.