The term ‘perception’ has three kinds of meaning in PCT discussions: a perceptual signal, a rate of firing in the nervous system; a numerical variable in a model of a behaving system that may be implemented as a computer program; and the experience of perceiving. An aim of PCT is to justify our belief that the former two correlate not only with each other (a hoped-for outcome of neuroscience research), but also with our experience of perceiving, and indeed nerve firings and model variables would be a big shrug without that correlation to subjective experience.
In neuroscience terms, we talk about a perceptual signal as some sort of aggregate or average of rates of firing in a bundle of nerves.
Neural spike trains present analytical challenges due to their noisy, spiking nature. Many studies of neuroscientific and neural prosthetic importance rely on a smoothed, denoised estimate of a spike train’s underlying firing rate.
Methods for Estimating Neural Firing Rates, and Their Application to Brain-Machine Interfaces
“Firing rate” in the neurophysiological sense is an idealized theoretical concept.
(That said, many neuroscience researchers look instead for temporal patterning in neural spike chains, in preference to firing rates. Peter Cariani at Mass Eye and Ear never did come around from that conviction, and dropped away from CSGnet. One explanation for the preference is that they imagine it might account for pattern recognition, which living organisms do well but computers don’t. HPCT ought to provide a good account of pattern recognition; I am not aware that it does.)
In a PCT model of a kind of behavior, perceptual signals are quantitative variables which are claimed, sometimes explicitly, to correspond to perceptual signals in the neurophysiology sense. These variables in the model are theoretical constructs. We can derive them from instrumental measures of physical phenomena that demonstrably impinge upon the relevant sensors. In principle, we can even measure rates of firing from those
In practice, and in talk, we always revert to perception as experience, or as we imagine it to be experienced. Even if we don’t acknowledge this explicitly, 'fess up—it’s always the foundation of which the other two are theoretical analogs. When we talk about perceptions, almost always we mean aspects of what we experience, even when we use the language of model variables and neural firing rates.
A virtue of triangulating subjective experience to model variables and imputed neural activity is objectification. Physical science looks for quantifiable analogs or correlates of ordinary experience. But the direct investigation of subjective experience is actually a well established discipline with a long history. These disciplines (plural, actually) specify practices and conditions and indicate experiences that can result and how to recognize them. Experimental method: establish these conditions, do these things, and if your experiment is successful you will see these results as others have done before.
In their instructional material, many of the diverse schools of Vedanta, Buddhism, etc. carry culture-specific imaginings. This is to be expected: a great deal of the furniture and traffic of subjective mental experience is the product of memory and imagination. The disciplines teach discrimination, and this they have in common with Western science, which in its history has all too often been misled by imagining.
Prominent Buddhist teachers have joined with scientists in exploring the relation between these two ways, objectification by modeling and direct, disciplined investigation of subjective experience. The Dalai Lama wrote The Universe in a Single Atom: The Convergence of Science and Spirituality (2005), and there are many other books, videos, etc. on the relation of Buddhism and physics. PCT is eminently relevant.
So how much can we do on just the basis of perception as experience?