wouldn’t get any more door-knockers.
She thanked Christopher and hung up. The whole bizarre episode had fractured her mood; the TV and the blogs had lost their hypnotic attraction. She paced the living room, agitated. People who might have sat beside her in a classroom fifteen years before were facing batons, water-cannon and bullets. The sheer fatuousness of her own tribulations made her life here seem like a mockery.
So, what was she supposed to do? Jump on a plane to Tehran and get herself arrested at the airport? She and her mother had departed illegally; they didn’t even have Iranian passports any more. And as far as she could tell, her adopted country was already following the best possible course: keeping its grubby fingers right out this time. And if they weren’t, she doubted that the CIA was prepared to take advice from her.
The truth was, she had nothing to contribute. Whatever happened, it would all unfold without her.
Nasim picked up her phone and found the menu option for ‘I’m not as sick as I thought, I’m coming in after all.’
Instead of the usual reassuring tone confirming success, there was a disapproving buzz and an alert popped up.
‘AcTrack plug-in disabled,’ it read. ‘Unable to complete this function.’
John Redland’s group had the twelfth floor of Building 46 all to themselves. From her corner of the lab, Nasim could peer across Vassar Street at the Stata Centre, an apparition out of a cartoon fairy-tale with its facade of tilted surfaces intersecting at vertiginous angles. As an architect’s sketch or computer model it must have looked enchanting, but in real life this gingerbread house had developed all manner of leaks, cracks and snow-traps.
Nasim turned back to her computer screen, where a tentative wiring map for part of the brain of a zebra finch was slowly taking form. The map wasn’t based on any individual bird, nor was it the product of any single technique. Some of the finches who’d contributed to it had been genetically engineered so that their neurons fluoresced under UV light, with each cell body glowing in a random colour that made it stand out clearly from its neighbours; that was the famous Lichtman-Livet-Sanes ‘Brainbow’ technique, developed over at Harvard. Others had had their brains bathed in cocktails of synthetic molecules – tagged with distinctive radioisotopes – that were taken up only by cells bearing receptors for particular neurotransmitters. A third cohort had been imaged after selective labelling, with monoclonal antibodies, of the cellular adhesion molecules that bound one neuron to another. And a fourth set of birds had been subject to no chemical interventions at all, and simply had their brains peeled by an ATLUM – an Automatic Tape-collecting Lathe Ultra Microtome – into fine slices which could then be imaged by electron microscopes and reassembled in three dimensions.
Altogether, nearly a thousand finches had lived and died to create the map that lay in front of her. Nasim hadn’t personally touched a feather on their heads, though she’d watched her colleagues operating, injecting and dissecting. None of the procedures carried out on the living birds should have left them in pain, and with decent- sized cages, plenty of food and access to mates, their lives probably hadn’t been much more stressful than they would have been in the wild. Nasim was never sure exactly where she’d draw the line, though. If it had been a thousand chimpanzees instead, for a project equally distant from any urgent human need, she didn’t know if she would have found a way to rationalise it, or if she would have walked away.
The map on her screen described the posterior descending pathway, or PDP, of the birds’ vocalisation system. The contributors had all been adult males, each with a fixed song of their own that was somewhat different from the others’. Redland had chosen the PDP for the sake of those two characteristics: it controlled a single, precisely repeatable behaviour in each individual – the bird’s fixed song – but there was also a known variation between the contributors thrown into the mix: no two birds sang quite the same song. Unless the team’s mapping techniques could cope robustly with that degree of difference, making sense of anything as complex as the brains of rats who’d learnt to run different mazes would be a hopeless task.
Nasim slipped on her headphones and linked the latest draft of the zebra finch map to a software syrinx, a biomechanical model of the bird’s vocal tract. She had plenty of fancier, more quantitative ways to gauge her progress, but listening to the song these virtual neurons created seemed an apt way to judge success. The songs of the individual live birds had been recorded, and Nasim had heard them all; she knew exactly what the fast, rhythmic chirping of an adult zebra finch should sound like. As she tapped the PLAY button on the touchscreen, her shoulders tensed in anticipation.
The song was disorganised, weak and confused, more like an infant finch’s exploratory babbling than anything a confident adult would produce. She glanced at a histogram showing a set of simulated electrical measurements; the statistics confirmed that they were, still, nothing like the signals measured by micro-electrodes in the brains of real adult birds.
The different mapping techniques complemented each other, each one excelling at revealing certain aspects of the neural architecture, but for the data to be meaningfully combined she needed to find common signposts that could be used as points of alignment. It was easy to build, say, a composite human face by locating all the eyes and noses in a thousand photographs, then making sure that you merged eyes with eyes, rather than eyes with noses. But for a thousand birds with a thousand different songs encoded deep in their skulls, the signposts were subtle aspects of the neural network, and they had to be coaxed out of the partial, imperfect data that each individual map supplied. Right now, it sounded to Nasim as if she were merging pitch from one bird with tempo from another, to produce a musical concoction that was not so much generic as pureed.
She steeled herself and plunged back into the computer code for the map integration software. The task was proving more difficult than she’d expected, but she did not believe it was hopeless. She was sure that once she found the right perspective, the right mathematical point of view, the signposts would become clear.
Nasim usually brought a packed lunch with her, but all her routines were askew today. By two o’clock her concentration was failing, so she went downstairs to the Hungry Mind Cafe. She bought the vegetarian ragout and took it to a table where three of her colleagues were seated.
‘How’s the revolution going?’ Judith asked her.
‘There was a big demonstration in Shiraz yesterday,’ Nasim replied. ‘Ten thousand people, according to some witnesses. Not quite a general strike, but it’s spread far beyond just students now.’
‘Have you still got relatives in Iran?’ asked Mike.
‘Yes, but I haven’t really stayed in touch with them,’ Nasim confessed. When her father had been executed, her aunts and uncles on both sides of the family had declined to speak out against his killers, and Nasim had been so angry with them that she’d cut herself off from everyone, even before she and her mother had fled. Fifteen years later she was less inclined to judge them so harshly, but she’d never tried to rebuild bridges, and the blameless cousins she’d once played with were strangers to her now.
Hunting for a chance to change the subject, she gestured at the empty plates on the table. ‘Looks like you’ve all been here for a while. So what gossip have I missed?’
‘Mike broke up with his girlfriend,’ Shen announced.
Nasim looked at Mike to see if it was true; he didn’t seem too devastated, but he didn’t deny it. ‘I’m sorry,’ she said.
‘It was going nowhere,’ Mike replied stoically. ‘We were philosophically incompatible: she belonged to True Love Waits… I belonged to True Love Wilts.’
‘So how can we take your mind off this tragedy?’ Nasim wondered.
Shen said, ‘Actually, we’ve been playing Thirty-Second Pitch. You want to choose one?’
‘Hmm.’ Nasim’s mind was blank, then she said, ‘Mike, you have thirty seconds to make yourself indispensable to… Amazon.’
‘Amazon?’ He grimaced with distaste. ‘I’d rather work for the IRS.’
‘Twenty-five seconds.’
‘Okay, okay.’ He closed his eyes and took a deep breath. ‘I offer to write a psycho-linguistic compression algorithm for text. MP3s for the written word.’
‘Compression?’ Judith interjected sceptically. ‘I don’t think Kindle is facing bandwidth problems.’
‘Not compression for the sake of bandwidth,’ Mike explained, ‘compression to save the reader’s time. Abridgement. Like Reader’s Digest Condensed Books, but fully automated, and based on a rigorous scientific analysis of what readers will actually retain. With music, we know that it’s safe to strip away certain sounds that are masked by others… so surely we can figure out what words can be omitted from a great slab of Melville or
