Contents:
1. The Definition of the Mind.
Any scientific study of the phenomenon should answer the following questions: What is the phenomenon? What does it do? Why does it do it? How does it do it? They are called phenomenological, functional, teleological, and causal questions. The phenomenological question is the foundational level of analysis and the causal question is the ultimate level. We cannot skip any of the questions if the aim is to understand the phenomenon. This seems to be an obvious statement. But when it comes to the Mind, nothing is obvious. The Macmillan Dictionary of Psychology states: “Consciousness is a fascinating but elusive phenomenon: it is impossible to specify what it is, what it does, or why it has evolved. Nothing worth reading has been written on it.” The science named ‘knowledge of the mind’ (from Greek psyche-logos) cannot define the object of its research. This is an admission of failure. Moreover, cognitive science as an interdisciplinary field that includes psychology, biology, neuroscience, and other disciplines does not define it either. So, what do they study?
The chapter cites prominent researchers who give various reasons for not defining the Mind. Some believe that it is impossible to define. Some think the problem is too hard, so we should declare the Mind some ‘fundamental’ property of nature and be done with the question. Some say that we should not risk giving a specific definition because we do not have enough knowledge, and prefer to wait for someone else to do it sometime in the future. However, these are just excuses that are an implicit admission of failure.
A definition is not some absolute truth given once and for all. It is just a hypothesis that answers the question of what kind of a physical phenomenon is the object of research. Thus, it must be stated in physical terms that are testable, potentially irrefutable, or confirmable. This is just the first step towards answering all further questions about the phenomenon. If we can’t make it, all our research is just marking time. The Teleological Transduction Theory (TTT), which will be worked out in this and further parts of the “Symphony of Matter and Mind” project, takes the risk and starts with a physical definition of the Mind. This step allows it to move to functional, teleological, and, ultimately, causal questions about the workings of the Mind as a physical process.
2. The Algorithmic Flowchart of the Mind
This chapter expands on the original definition of the Mind by detailing the functional aspect. The Mind is a physical process with a specific purpose and, thus, has a certain algorithmic procedure for performing the task. TTT offers an elegant algorithmic flowchart of the Mind and calls it the Perception-Apperception-Action Lemniscate (PAAL). The terms in the name are taken from psychology. However, in this flowchart, they acquire a physical and technical meaning which allows us to progress in answering the question of how the functional flow is physically realized in the brain. It provides the basis for a fundamentally new approach to brain mapping.
Most of the flowcharts suggested in other models try to correlate anatomical descriptions to mental functions described by psychology. TTT describes the brain as a set of technical modules performing specific functions within the general function of the Mind, specified in the proposed definition. There is another ‘game-changing’ difference from standard linear schemes used in cognitive science. PAAL is a non-linear operationally closed iterative loop that provides for the predictive coding in the brain. It shows that the Mind works not as a passive ‘mirror of reality’ but as an active reality modeling process.
3. The Code of the Mind.
This chapter addresses the fundamental question of how the brain encodes reality signals to create a model of reality. The litmus test for any model of neural coding is whether the proposed coding strategy matches the efficiency and speed with which the brain performs its functions.
All models of the neural code that are regarded as standard in neuroscience, and according to which practical researchers analyze neural activity, consider it to consist of identical spikes. Despite differing views on specific coding strategies, there is a shared attitude toward neurons as ‘digital’ devices producing 1s or 0s (discrete on-off states). The chapter elaborates on why this idea does not correspond to the brain’s speed and efficiency. In short, we would not survive if the neural code were purely digital.
The digital coding strategy is slow and inefficient as it requires a large number of bits to represent a signal. In artificial devices, this deficiency is compensated by the enormous speeds of processors, reaching billions of Hz. Neurons operate at frequencies of tens or hundreds of Hz, which is simply too slow to accumulate enough bits for an adequate representation of reality signals in on-line mode. The brain compensates for physical speed limitations by adding an analog aspect to its coding strategy.
The chapter details the brain’s hybrid analog-digital strategy and provides examples of how the technology works in different perceptual modalities. It concludes by proposing the Symphonic Neural Code (SNC) hypothesis, which sheds light on the mystery of the brain’s high performance and efficiency.
4. Neuron as Information Creator.
Using the SNC hypothesis, the chapter goes to the level of an individual neuron and shows how it performs the encoding function as an analog-to-digital-to-analog converter (ADAC). It methodically looks at a neuron from biological, technical, computational, and physical perspectives. It describes the encoding process down to the finest details of the inter-cellular and intra-cellular levels. It provides a new perspective on the encoding function by employing wave physics concepts. This runs counter to the standard attitude to a neuron as a linear integrate-and-fire device. The classic Hodgkin-Huxley model, used in standard models of neural activity, says nothing about coding and only describes the transmission of electrical current along neural ‘wires’. TTT complements this model by offering a model of the oscillatory dynamics of a neuron that encodes the input by the internal parameters of its non-linear and adaptive impulse response. The chapter also offers the PAAL operational flow diagram at the level of a single neuron.
5. Discreteness and Continuity of the Mind.
The debate about whether the Mind is continuous or discrete has been going on in neuroscience for decades. Both sides provide sound arguments based on empirical data about physiological and mental processes. However, to resolve the issue, we should look at the physics and technology. The chapter formulates principles of signal encoding that cannot be avoided by any processing system, including the brain. From these principles, it becomes evident that initial measurement by the sensory systems is inevitably a discrete sampling and quantization process. However, the discreteness of the primary processing of continuous signals should be transformed into the continuity of their representations. TTT offers a reconciling solution to the old debate: analog-digital-analog Symphonic Neural Code means that the Mind is both discrete and continuous. The chapter proposes a hypothesis about how the brain manages to create continuous representations of signals and a coherent picture of the world, despite the inevitable discretization during initial sensory processing.
6. Filters of the Brain.
Continuing the technical perspective of the previous chapter, this chapter offers a detailed account of how neurons and their populations acting as signal processing filters perform the initial sampling and quantization followed by modulation and integration at the final technological step of creating continuous representations of the continuous signals of reality. The theoretical and mathematical modeling of the process is supplemented by experimental examples demonstrating how the process happens in the brain. To sum it up, the chapter offers a comprehensive hypothesis about the technological chain of the brain consisting of filters-converters, filters-modulators, and filters-integrators. This hypothesis is a fundamentally new approach that provides a basis for building a new brain map as a filter configuration.
7. Spectrogram of the Mind.
The signals change in time and space. The filters of the brain need to process both aspects when encoding representations. Thus, the representation can be called a spectrogram that contains amplitude-frequency parameters of a signal (space axis) and its phase trajectory (time axis). These conjugate variables are in an inverse relationship: the more focus on one, the less on the other. Finding the optimal spectrogram window for the most accurate representation of a signal in both aspects is a problem solved by the brain by active adaptation of the settings of the filters’ impulse response.
The chapter proposes a theoretical and mathematical model that answers the question of how neurons ‘place’ a signal along the spatial axis, performing a Fourier type of analysis, and along the time axis, performing a wavelet type of analysis. The chapter also provides specific examples of how different perceptual modalities perform coding by adaptively changing the size and shape of the spectrogram window, balancing the optimal ratio of frequency and phase components depending on the type of signal and conditions.
8. The Amazing Self-Learning Machine.
The chapter shows how the PAAL algorithm allows the brain to solve the problem of a living system survival by providing the conditions for adaptive self-learning. It also highlights the similarities and differences between modern artificial intelligence algorithms and the algorithm of the living Mind. The crucial difference is that the natural algorithm’s operational flow includes the internal evaluation function, thus a system is a ‘student’ and a ‘supervisor’ rolled into one entity that does not need an external programmer and goal-setter. This is the technical solution of the philosophical problem of free will. The chapter describes the evaluating systems of the brain that are in the middle of the operational flow of the Mind.
It also sums up the previous chapters by offering a full version of the definition of the Mind by taking into account all functional, computational, representational, and technical and implementational issues covered in the book. This paves the way for further disclosure of the details of brain technologies and their physical implementation in the next parts of the “Symphony of Matter and Mind” project.