Although there are many components within the human ear, the basic neural organ of hearing is called the cochlea. The cochlea has a spiral shape (see Figure) and with both impulse and response fluid canals with the very well known frequency response shown in the figure. Tiny hairs along the length of the basilar membrane, which is the wall between to the spiral cochlea impulse and response canals, are the neurons that that sense sound by fluid deflection of a tiny hair. The neural patterns in the EEG that come from basilar excitation are many and varied, but the neural network is still not well understood. In fact, science does not seem to have a very clear understanding of the underlying neural impulse patterns for even simple organisms.
One of the characteristics of human hearing, for example, is that we sense and enjoy music with the seven notes of the octave. We recognize that this particular 7-mer tonality is pleasing for humans, but science does not yet understand the neural network that is the basis for the 7-mer tonality. The basilar regions associated with sensation of sound from 200 to 20,000 Hz are shown in the figure along with how they map into the topology of the cochlea. The frequency diagrams show where along a hypothetical uncoiled basilar membrane we sense sound frequencies. However, there are frequencies below 200 Hz that are very important for enjoying music and there seems to be a problematic compression of these longer wavelengths beyond 200 Hz into the tip of the basilar.
The 7 notes of the octave are very suggestive, though, of a binary or bilateral difference sampling between groups of selected neurons and the top three rows of Pascal's triangle of the binomial theory describe how this binary sampling adds up to 7. This implies that the same kind of bilateralism that we recognize as the left-right symmetry is a part of hearing. Indeed, bilateralism is very common in all higher organisms and indeed also in the binary frequency analysis of sound and other spectral data with the Cooley-Tukey fast Fourier transform (FT) algorithm. The basic FT algorithm processes spectral data by sampling a time series with powers of two averaging and bilateralism is therefore an efficient way to sample and compress time series data into frequency amplitudes for representation in thought packets.
Therefore it seems very reasonable that along the basilar membrane, neurons from 20 mm to the end would be progressively paired into 7-mer's with the midpoint defined by middle C at 262 Hz, which peaks at 27 mm from the stapes. These progressive bilateral neural pairings would then form difference modes that would complement the sum and total modes and enhance sensation of the frequencies lower than ~1000 Hz as shown. These 7-order difference pairings would then effectively provide for our pleasure hearing the tones and chords of music.