Dopamine neurons modulate neural encoding and expression of depression-related behaviour

Major depression is characterized by diverse debilitating symptoms that include hopelessness and anhedonia1. Dopamine neurons involved in reward and motivation are among many neural populations that have been hypothesized to be relevant, and certain antidepressant treatments, including medications and brain stimulation therapies, can influence the complex dopamine system. Until now it has not been possible to test this hypothesis directly, even in animal models, as existing therapeutic interventions are unable to specifically target dopamine neurons. Here we investigated directly the causal contributions of defined dopamine neurons to multidimensional depression-like phenotypes induced by chronic mild stress, by integrating behavioural, pharmacological, optogenetic and electrophysiological methods in freely moving rodents. We found that bidirectional control (inhibition or excitation) of specified midbrain dopamine neurons immediately and bidirectionally modulates (induces or relieves) multiple independent depression symptoms caused by chronic stress. By probing the circuit implementation of these effects, we observed that optogenetic recruitment of these dopamine neurons potently alters the neural encoding of depression-related behaviours in the downstream nucleus accumbens of freely moving rodents, suggesting that processes affecting depression symptoms may involve alterations in the neural encoding of action in limbic circuitry

Straight-Line Drawings of Protein Interactions

This paper presents the first attempt at automatically generating drawings of protein interaction graphs. Such graphs are large and not necessarily connected. A straight-line drawing method based on the spring embedder metaphor has been found highly suitable for this task. The drawings produced exhibit edge length uniformity, even vertex distribution, and preserve graph topology well. This method is capable of generating both two- and three-dimensional layouts. A preliminary evaluation has been carried out based on a representative collection of interaction graphs

Merl A Mitsubishi Electric Research Laboratory

Many problems in computer-aided design and graphics involve the process of setting and adjusting input parameters to obtain desirable output values. Exploring di#erent parameter settings can be a di#cult and tedious task in most such systems. In the Design Gallery TM #DG# approach, parameter setting is made easier by dividing the task more equitably between user and computer. DG interfaces present the user with the broadest selection, automatically generated and organized, of perceptually di#erent designs that can be produced by varying a given set of input parameters. The DG approach has been applied to several di#cult parameter-setting tasks from the #eld of computer graphics: light selection and placement for image rendering; opacity and color transferfunction speci#cation for volume rendering; and motion control for articulated- #gure and particle-system animation. The principal technical challenges posed by the DG approach are dispersion ##nding a set of input-parameter vectors that optimally disperses the resulting output values# and arrangement #arranging the resulting designs for easy browsing by the user#. We showhow e#ective arrangement can be achieved with 2D and 3D graph drawing. While navigation is easier in the 2D interface, the 3D interface has proven to be surprisingly usable, and the 3D drawings sometimes provide insights that are not so obvious in the 2D drawings

Design Galleries: A General Approach to Setting Parameters for Computer Graphics and Animation

Image rendering maps scene parameters to output pixel values; animation maps motion-control parameters to trajectory values. Because these mapping functions are usually multidimensional, nonlinear, and discontinuous, finding input parameters that yield desirable output values is often a painful process of manual tweaking. Interactive evolution and inverse design are two general methodologies for computer-assisted parameter setting in which the computer plays a prominent role. In this paper we present another such methodology. Design Gallery TM (DG) interfaces present the user with the broadest selection, automatically generated and organized, of perceptually different graphics or animations that can be produced by varying a given input-parameter vector. The principal technical challenges posed by the DG approach are dispersion, nding a set of input-parameter vectors that optimally disperses the resulting output-value vectors, and arrangement, organizing the resulting graphics for easy and intuitive browsing by the user. We describe the use of DG interfaces for several parameter-setting problems: light selection and placement for image rendering, both standard and image-based; opacity and color transfer-function specification for volume rendering; and motion control for particle-system and articulated-figure animation

Design Galleries: A General Approach to Setting Parameters for Computer Graphics and Animation

Image rendering maps scene parameters to output pixel values; animation maps motion-control parameters to trajectory values. Because these mapping functions are usually multidimensional, nonlinear, and discontinuous, #nding input parameters that yield desirable output values is often a painful process of manual tweaking. Interactiveevolution and inverse design are two general methodologies for computer-assisted parameter setting in which the computer plays a prominent role. In this paper we present another such methodology