SIX MILLION TIMES someone has opted to download one of O'Meara's applications since he first released WhiteCap in 1999. And while it sometimes seems as though there are almost as many visual plug-ins on the market, G-Force in particular has established itself as one of the leading "visual enhancers" for the MP3-listening public. (Apple recently bundled it as the default plug-in for their acclaimed iTunes product.) Spend a few minutes with the software running alongside a favorite disk and you'll instantly see why: While many plug-ins cycle through repetitive patterns, in G-Force the screen morphs almost seamlessly from one radically different configuration (called "configs") to another, shifting from organic, pulsing blobs to spinning wire-frames to effects that defy classification. (Imagine triggering the Star Wars "hyperspace" effect while navigating through a galaxy of exploding fireworks.)
The most intriguing thing about software like G-Force is that the images it produces are in a real sense set to the music. They are not random slide shows -- many of the configs that come with G-Force alter their behavior in response to the changing waveforms of the audio signal. The conjunction is immediately apparent to first-time viewers: a sudden shift from muted strings to a roaring brass section might release a swarm of pixels, while the rest of the visuals pulse in lockstep with the percussion section. Years ago the philosopher of consciousness Thomas Nagel published a now-classic essay called "What Is It Like to Be a Bat?" I think software like G-Force gives us a clue: sound patterns translated into spatial information. You're listening to a song, and not flying through a cave, of course, but it's hard to think of another media experience where sound and image are more organically intertwined. Music videos have been wrapping themselves around pop songs since the days of "Video Killed the Radio Star," but that wrapping was an extra layer that required sentient humans to individually "interpret" each song. G-Force does its interpretations on the fly. The images you see are just another way of looking at the sound data.
At first glance, those images might remind you of the last time you took peyote and spent a long evening with Piper at the Gates of Dawn. But it's possible that the plug-in diaspora might be bad news for the hallucinogen providers. "I believe video to music acts as a multiplier to an otherwise purely audio experience like the way say, heroin, brings a new dimension to otherwise normal perception," O'Meara explained to me, in an email correspondence. "In this way, we do experience a new form of content from visualized music because the end product is a compound of music and video, not just a mixture." If part of the quest of psychedelia is trying to experience a synesthetic blurring of aural and visual information, then G-Force's pulsing waveforms give you a significant head start. Indeed, the first thing I thought when I saw G-Force is that the software was probably the greatest thing that ever happened to dorm-room stoners. But after a few minutes, I found myself thinking: Why even bother with the drugs? G-Force does acid better than acid.

OR AT LEAST it comes close. While G-Force is remarkably free of repetition -- partially because of the huge number of configs available, and partially because configs and color schemes can be combined to form new patterns -- the software's engagement with the sound information is relatively limited. For the most part, it simply translates the digital information from your MP3 file, and paints a waveform on the screen -- and then transforms that wave according to the rules of the current config. The result is an image that does an adequate job of translating changes in amplitude into visual data. On the most elemental level, when you listen to a song, your brain is doing something similar: translating the waves that reverberate in your ears into the sounds of music. But those sounds are obviously far more resonant than G-Force's simple waveforms: You hear changes in amplitude, of course, but you also hear a thousand other things -- chord changes, noise, different instruments, voice timbres, room tones, and so on. Under the influence of mind-altering drugs, the visual information conjured up by your brain is potentially responding to all that information in real-time: The arrival of the chorus in a song might trigger a new visual palette, while a striking correlation between the lyrics and the melody might push your "eyelid movies" in a new direction. But software like G-Force doesn't know anything about lyrics or song structure because that information is far more difficult to model mathematically.
Could a visual plug-in do a more faithful job of representing musical information? "To do that job right," O'Meara says, "requires a landslide of smart software. Our higher brain functions do a lot to decode such information." O'Meara himself reveals that he's "looking into a closely related project," though he declines to go into detail about it. But a more sophisticated visual interface to music is certainly conceivable. You could start by training the software to detect more subtle patterns in the datastream. The sound of the human voice lies in a relatively narrow part of the frequency spectrum, which is why you can use an equalizer to make the vocals louder or softer in a mix. Theoretically, you could train software like G-Force to "listen" for a sudden change in that part of the spectrum, and trigger a new config when the lead vocals start or stop in a song. You'd listen to the all-instrumental song intro with one config playing on the screen, and the second the vocals arrives, the screen would transform itself into a new landscape.
Another approach would be to use smart people, rather than smart software, and attach metadata to specific points in a song file. If users have already collectively built a database of CD titles and track information at CDDB, they could potentially start annotating subsections of songs as well. Call it HMML -- hypertext musical markup language. You'd take a given song and break it into the relevant categories: The first verse starts 32 seconds in; the chorus starts at 1:21; guitar solo from 2:15 to 2:45, etc. With a standardized set of tags, you could program G-Force to trigger a certain type of config anytime it encountered a drum solo or a French horn. The software wouldn't be any more sophisticated at parsing the musical data on its own, but the tags would give it a cheat sheet.
There's one other alternative, and it's the most radical one of all: Teach the software about music by teaching it to listen to our brains. A number of technology startups have been experimenting with neurofeedback devices that measure brain waves themselves, and translate them into computer-generated images and sounds, the way G-Force translates MP3 data. Certain brain-wave patterns appear in moments of intense concentration; others in states of meditative calm; others in states of distraction or fear. A series of EEG sensors applied to your skull register changes in the patterns of your brain waves, and transform them into a medium that you can perceive directly, often in the form of shifting colors and textures on a computer screen. As your brain drifts from one state to another, the image changes accordingly, giving you real-time feedback about your brain's EEG activity. Presumably, those data points could be integrated into the G-Force application alongside the soundwave data: If the launch into the chorus of "Smells Like Teen Spirit" triggers a surge of adrenaline through your body, the EEG might detect a change in your brain's overall state and send that information back to the screen; if listening to Ravi Shankar lulls you into a trance, G-Force could automatically supply an onscreen mandala to accompany your meditations.
Which brings us back to Andy O'Meara, and his unusual mix of techno-Christianity. Certain brain-wave states are associated with feelings of powerful spiritual calm -- some neurofeedback practitioners use the tools to help "drive" their brains towards those states. "Music is my life in that it's air that I need to breathe," O'Meara writes on his Web site. "Trance/techno/electronica, dance/house, ambient/tribal, acoustic/folk, and alternative all have the ability to operate switches, knobs, and levers deep inside me I will never understand." Anyone passionate about music will recognize that feeling in a heartbeat. The question is: Can software learn to recognize it too?

Steven Johnson is FEED's editor-in-chief and the author of Interface Culture: How New Technology Transforms the Way We Create and Communicate.

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