Dissociation of circadian and light inhibition of melatonin release through forced desynchronization in the rat

Pineal melatonin release exhibits a circadian rhythm with a tight nocturnal pattern. Melatonin synthesis is regulated by the master circadian clock within the hypothalamic suprachiasmatic nucleus (SCN) and is also directly inhibited by light. The SCN is necessary for both circadian regulation and light inhibition of melatonin synthesis and thus it has been difficult to isolate these two regulatory limbs to define the output pathways by which the SCN conveys circadian and light phase information to the pineal. A 22-h light-dark (LD) cycle forced desynchrony protocol leads to the stable dissociation of rhythmic clock gene expression within the ventrolateral SCN (vlSCN) and the dorsomedial SCN (dmSCN). In the present study, we have used this protocol to assess the pattern of melatonin release under forced desynchronization of these SCN subregions. In light of our reported patterns of clock gene expression in the forced desynchronized rat, we propose that the vlSCN oscillator entrains to the 22-h LD cycle whereas the dmSCN shows relative coordination to the light-entrained vlSCN, and that this dual-oscillator configuration accounts for the pattern of melatonin release. We present a simple mathematical model in which the relative coordination of a single oscillator within the dmSCN to a single light-entrained oscillator within the vlSCN faithfully portrays the circadian phase, duration and amplitude of melatonin release under forced desynchronization. Our results underscore the importance of the SCN`s subregional organization to both photic input processing and rhythmic output control.

Chaotic phase synchronization and desynchronization in an oscillator network for object selection

Object selection refers to the mechanism of extracting objects of interest while ignoring other objects and background in a given visual scene. It is a fundamental issue for many computer vision and image analysis techniques and it is still a challenging task to artificial Visual systems. Chaotic phase synchronization takes place in cases involving almost identical dynamical systems and it means that the phase difference between the systems is kept bounded over the time, while their amplitudes remain chaotic and may be uncorrelated. Instead of complete synchronization, phase synchronization is believed to be a mechanism for neural integration in brain. In this paper, an object selection model is proposed. Oscillators in the network representing the salient object in a given scene are phase synchronized, while no phase synchronization occurs for background objects. In this way, the salient object can be extracted. In this model, a shift mechanism is also introduced to change attention from one object to another. Computer simulations show that the model produces some results similar to those observed in natural vision systems.

A network of integrate and fire neurons for visual selection

Biological systems have facility to capture salient object(s) in a given scene, but it is still a difficult task to be accomplished by artificial vision systems. In this paper a visual selection mechanism based on the integrate and fire neural network is proposed. The model not only can discriminate objects in a given visual scene, but also can deliver focus of attention to the salient object. Moreover, it processes a combination of relevant features of an input scene, such as intensity, color, orientation, and the contrast of them. In comparison to other visual selection approaches, this model presents several interesting features. It is able to capture attention of objects in complex forms, including those linearly nonseparable. Moreover, computer simulations show that the model produces results similar to those observed in natural vision systems.