stuff ive found out from research papers on music and emotion

Defining affective musical parameters
Much of the current music&emotion research uses the circumplex model of emotion, which consists of two components on a 2d scale: valence (positive or negative) and arousal (amount of energy). This model can be easily mapped out in SC using a 2dSlider object. The PAD model extends this further, adding a 3rd axis called dominance, which is a measure of approach and avoidance response, ie the difference between anger and fear. Also mentioned are different 'types' of tempo: score tempo (absolute, eg bpm), preferred tempo (the speed at which people tap along - "60 to 120 bpm, no matter what the score tempo is", and perceived tempo, which relates to the sparsity of the music. They also note that staccato articulation (glitchiness plz) is higher in arousal levels whereas legato tends to be low. Harmonic modes can be ordered from brightest to darkest according to Persichetti, in this order: Lydian, Ionian, Mixolydian, Dorian, Aeolian, Phrygian and Locrian.

So all of these elements can be introduced into my musical grammar. So far I have chosen three polarities: happy/sad, bored/excited, euphoria/dysphora. Happy/sad is simply determined by mode. Bored/excited determined by perceived tempo/staccato-legato. Euphoric/dysphoric would be how the melody is reolved as well as increasing aleatory/glitchy elements.
These were the initial ones I wanted to use, however from this research I have found out the placing of emotions such as anger and fear on the valence-arousal-domination scale and so will try to include this information somehow.

A more scientific approach
Much of the research on music and emotion is based on subjective descriptions of both the music and the response, although the valence-arousal-domination scale is good more precise methods could be found. It would also be more appropriate to measure the participant's neural activity as opposed to asking them to verbalise their responses. Music programming languages provide a good environment to study the effects of frequencies on brainwaves, as the level of control over the sonic output is roughly equivalent to the level of feeeback we can measure, ie its all numbers now.

A possible example is the solfeggio scale [396 417 528 639 741 852 963 Hz], which is said to have a soothing and healing effect due to the 'sacred geometry' of the frequencies, and is used for meditation. Ignoring its nebulous origins (bible code), it does provide an interesting and precise hypothesis which could be tested using SC & a ECG machine very easily...eg create a sequence based on these specific frequencies and see if brainwave patterns differ with random mutations (could even use a genetic algorithm to create The Most Trancey sequence ever by creating a GUI for real-time user feedback). Also, on the trance-state aspect of music, gong and bell sounds are used for meditation all over the world due to their wide spectrum of harmonicity, and it is relatively easy to recreate these kinds of sounds using additive synthesis.The harmonics could then be fine-tuned to precise mathematical formulas. I like the idea of music as 'brain food'. Juslin et al note that it is very important to young people in defining self-identity, and essentially listening to bad music is like feeding children junk food for the soul (sort of). Music that is attuned to creating mental states would be like eating wholegrains/pure vitamins except mainlined straight into ur brainz..............


So to recap: there is plenty of research on affective music using conventional means, and lots of room to explore non-conventional means.