Редактирование: Whole brain emulation (раздел)

=== Senses ===

<blockquote>See: [[Physical Enhancement#Sensory Augmentation|Sensory Augmentation]]</blockquote>

==== Vision ====

Vision
Visual photorealism has been sought in computer graphics for about 30 years, and this 
appears to be a fairly mature area at least for static images and scenes. Much effort is 
currently going into such technology, for use in computer games and movies. 
 
(McGuigan, 2006) proposes a “graphics Turing test” and estimates that for 30 Hz interactive 
visual updates 518.4‐1036.8 TFLOPS would be enough for Monte Carlo global illumination. 
This might actually be an overestimate since he assumes generation of complete pictures. 
Generating only the signal needed for the retinal receptors (with higher resolution for the fovea than the periphery) could presumably reduce the demands. Similarly, more efficient 
implementations of the illumination model (or a cheaper one) would also reduce demands 
significantly.

==== Hearing ====

The full acoustic field can be simulated over the frequency range of human hearing by 
solving the differential equations for air vibration (Garriga, Spa et al., 2005). While accurate, 
this method has a computational cost that scales with the volume simulated, up to 16 TFLOPS 
for a 2×2×2 m room. This can likely be reduced by the use of adaptive mesh methods, or ray‐ 
or beam‐tracing of sound (Funkhouser, Tsingos et al., 2004).  
 
Sound generation occurs not only from sound sources such as instruments, loudspeakers, and 
people but also from normal interactions between objects in the environment. By simulating 
surface vibrations, realistic sounds can be generated as objects collide and vibrate. A basic 
model with N surface nodes requires 0.5292 N GFLOPS, but this can be significantly reduced 
by taking perceptual shortcuts (Raghuvanshi and Lin, 2006; Raghuvanshi and Lin, 2007). This 
form of vibration generation can likely be used to synthesize realistic vibrations for touch.

==== Smell and Taste ====

So far no work has been done on simulated smell and taste in virtual reality, mainly due to 
the lack of output devices. Some simulations of odorant diffusion have been done in 
underwater environments (Baird RC, Johari H et al., 1996 ) and in the human and rat nasal 
cavity (Keyhani, Scherer et al., 1997; Zhao, Dalton et al., 2006). In general, an odor simulation 
would involve modelling diffusion and transport of chemicals through air flow; and the 
relatively low temporal and spatial resolution of human olfaction would likely allow a fairly 
simple model. A far more involved issue is what odorant molecules to simulate. Humans 
have 350 active olfactory receptor genes, but we can likely detect more variation due to 
different diffusion in the nasal cavity (Shepherd, 2004).

No work has been done on simulating smell and taste in a virtual environment, most likely due to lack of output for this data. The low quality of human olfaction would allow for a simple model.

Taste relies only on a few types of receptor, but the tongue also detects texture and the placement of then nose forces on to smell objects entering the mouth. The former may require complex simulations of the physics of virtual objects in the case of virtual environments, and pressure/temperature sensors for simulacra.

==== Haptics ====

The haptic senses of touch, proprioception, and balance are crucial for performing skilled 
actions in real and virtual environments (Robles‐De‐La‐Torre, 2006).  
 
Tactile sensation relates both to the forces affecting the skin (and hair) and to how they are 
changing as objects or the body are moved. To simulate touch, stimuli collision detection is 
needed to calculate forces on the skin (and possibly deformations) as well as the vibrations 
when it is moved over a surface or exploring it with a hard object (Klatzky, Lederman et al., 
2003). To achieve realistic haptic rendering, updates in the kilohertz range may be necessary 
(Lin and Otaduy, 2005). In environments with deformable objects various nonlinearities in 
response and restitution have to be taken into account (Mahvash and Hayward, 2004). 
Proprioception, the sense of how far muscles and tendons are stretched (and by inference, 
limb location) is important for maintaining posture and orientation. Unlike the other senses, 
proprioceptive signals would be generated by the body model internally. Simulated Golgi 
organs, muscle spindles, and pulmonary stretch receptors would then convert body states 
into nerve impulses. 
 
The balance signals from the inner ear appears relatively simple to simulate, since it is only 
dependent on the fluid velocity and pressure in the semicircular channels (which can likely 
be assumed to be laminar and homogeneous) and gravity effects on the utricle and saccule. 
Compared to other senses, the computational demands are minuscule.  
 
Thermoreception could presumably be simulated by giving each object in the virtual 
environment a temperature, activating thermoreceptors in contact with the object. 
Nocireception (pain) would be simulated by activating the receptors in the presence of 
excessive forces or temperatures; the ability to experience pain from simulated inflammatory 
responses may be unnecessary verisimilitude.