Fuck art

[Chruser]

I haven't painted anything for almost six months. I doodle on occasion, but nothing "interesting" has ensued.

Furthermore, I dropped out of the Umeå Institute of Design (without telling anyone beforehand) for a large array of reasons; loss of motivation and depression being two of them. Subsequently, I submitted a last-day application to a fine arts school (similar to a pre-Umeå one I attended), and figured I would get rejuvenated in the freedom of summer and enjoy studying fine arts once again. That didn't happen.

I abhor my new art school (despite the fact that I'm "learning new things") and find the prospect of making a living as a fine artist, illustrator or designer of any kind to be harrowing. That being said, I do enjoy to draw, but I have realized that I have no desire to do it for anyone but myself. Quite the turn of events, one might think.

Anyway, during summer, I regained my pre-art interests in physics and computer science (largely due to having read Kurzweil's "The Singularity is Near" and Kaczynski's "Industrial Society and Its Future"), so perhaps I'll study Engineering Physics, Autonomous Systems or Computational Neuroscience instead and do art in my spare time, assuming there will be any.

Thoughts?

[Tuttifrutti]

Umm... What is Computational Neuroscience? :D

I think you should just do whatever you think will make you happy and you won't be depressed about doing for the rest of your life.

[Kazilla]

Computational, im assuming has to do with computers - and neuroscience is the study of the brain correct? So im going to assume that

Computational Neuroscience is the study of the brain with the use of computers.

[Tuttifrutti]

If you're right, I will bow down at your feet. :P

[Kazilla]

Computational neuroscience is an interdisciplinary science that links the diverse fields of neuroscience, cognitive science, electrical engineering, computer science, physics and mathematics. Historically, the term was introduced by Eric L. Schwartz, who organized a conference, held in 1985 in Carmel, California at the request of the Systems Development Foundation, to provide a summary of the current status of a field which until that point was referred to by a variety of names, such as neural modeling, brain theory and neural networks. The proceedings of this definitional meeting were later published as the book "Computational Neuroscience", MIT Press(1990). The early historical roots of the field can be traced to the work of people such as Hodgkin & Huxley, Hubel & Wiesel, and David Marr, to name but a few. Hodgkin & Huxley developed the voltage clamp and created the first mathematical model of the action potential. Hubel & Wiesel discovered that neurons in primary visual cortex, the first cortical area to process information coming from the retina, have oriented receptive fields and are organized in columns (Hubel & Wiesel, 1962). David Marr's work focused on the interactions between neurons, suggesting computational approaches to the study of how functional groups of neurons within the hippocampus and neocortex interact, store, process, and transmit information. Computational modeling of biophysically realistic neurons and dendrites began with the work of Wilfrid Rall, with the first multicompartmental model using cable theory.

Computational neuroscience is distinct from psychological connectionism and theories of learning from disciplines such as machine learning, neural networks and statistical learning theory in that it emphasizes descriptions of functional and biologically realistic neurons (and neural systems) and their physiology and dynamics. These models capture the essential features of the biological system at multiple spatial-temporal scales, from membrane currents, protein and chemical coupling to network oscillations, columnar and topographic architecture and learning and memory. These computational models are used to test hypotheses that can be directly verified by current or future biological experiments.

Currently, the field is undergoing a rapid expansion. There are many software packages, such as GENESIS and NEURON, that allow rapid and systematic in silico modeling of realistic neurons. Blue Brain, a collaboration between IBM and École Polytechnique Fédérale de Lausanne, aims to construct a biophysically detailed simulation of a cortical column on the Blue Gene supercomputer.

[Sum Yung Guy]

Jesus H Christ, Chruser is going to be the one to bring the singularity upon us...