In this blog I describe in detail what has been learned by neuroscientists about the waves in our brains. It is a lengthy composition intended to replace what would have been a very technical book. I include information derived from more recent neuroscience investigations to expand on points I made especially in my first book, Nerve Endings of the Soul: Interaction Between the Mind of God and the Mind of Man Through Neural Synaptic Networks. I endeavor to make the content understandable to lay readers, but it has been necessary to include some technical language which I try to explain along the way as accurately as I can. I have directed this blog to individuals who are interested in seeing the concordance that exists between neuroscientific data and applicable Scripture relevant to dualist interaction between the immaterial mind of Man and the physical brain. Ultimately, I shall address interaction between the Mind of God and the neural networks of the human brain that enable a bidirectional, personal communion between the Holy Spirit and the spirit and soul of Man. That part of my composition will expand on material I presented in my second book, The Boundless Love of God: A Holy Spirit Story. God created mankind to have an intimate, personal communion with Him. It was a communion that was lost at the Fall but restored by the life, death and resurrection of Jesus Christ who sent as He promised the Holy Spirit to indwell the spirit and soul of mankind in repentance. My next blog, “Minds in Communion,” will expand on this latter point. Let us see what neuroscience has learned about waves in our brains that will help us understand this interaction.
Brain Waves Description
Brain waves, also referred to as oscillations, are periodic fluctuations of electrical excitability in neurons, singly or in groups. Fluctuating changes in the membrane potential of neurons create an extracellular current which can be measured by electrical recordings from the brain. The electroencephalogram (EEG) has been used to study the brain waves of humans for many years. They are of multiple frequencies including in order from lowest to highest delta, theta, alpha, beta and gamma. The frequencies range from 0.05 Hertz (Hz) to as high as 500 Hz. (1) They have spatial and temporal relationships with brain functions and brain states (and we shall see with cognitive activity). However, EEG’s are monitored through the skull and have poor resolution and correlation with specific cognitive activities. They also do not show the trajectories of brain waves through the brain which are being increasingly documented.
As was pointed out in Part One of this blog, it is now possible to monitor brain wave frequencies and amplitudes directly by electrocorticography (ECoG) by placing monitors directly on the cortex of the brain during certain surgical procedures. ECoG can be done in awake patients undergoing surgery for epilepsy. Trajectories of waves can be traced through the monitored parts of the brain. The procedure can be coordinated with functional magnetic resonance imaging (fMRI) and spectrograms. Technological advances that are becoming increasingly available allow investigators to learn more about cerebral cortical function within and between functional regions of the brain and how it relates to cognition and sensorimotor functions.
Brain waves are reflective of nerve impulses that consist of propagating action potentials referred to as spike trains. They are immensely complex as we shall see. Waves generated within certain parts of the brain may have specific relationships with the waves of other parts of the brain such as the cerebral, frontoparietal or visual cortex, so their trajectories are of interest. Nerve impulses are continuously active within nerve cells constituting a stochastic, or random, background of wave activity. At rest neural networks stay at various subthreshold levels of polarization insufficient to stimulate action potentials. This status makes them highly responsive to electrochemical inputs that are sufficiently strong to cause depolarization and the generation of action potentials. Spike trains of action potentials are transmitted with specified trajectories by a process to be discussed. The fluctuations of brain waves can be switched within milliseconds between different states of amplitude and frequency in response to inputs of wave trains accounting for the fluidity of cortical activities and of the mind. By a process such as cross frequency coupling (CFC) a neural network with a theta frequency can be linked with a network of impulses with a higher gamma frequency to facilitate a very rapid change in the trajectory of a train of spikes from one region to another. Spike trains of action potentials transmit specified information (explained in both of my books) within neural codes to functional parts of the brain so that, for example, the aroma of a rose is sensed or an arm is raised. We have seen in Part One of this blog that the immaterial mind interacts causally and receptively with this process. Most current neuroscience studies are confirming this dualist relationship.
The Mechanics of Synaptic Transmission
Synaptic exocytosis serves as the regulator of the activity that generates coherent patterns of impulse transmission. Quantum mechanical action is the switch, or trigger, within microstructures of ionic channels and synapses that stimulates exocytosis. Because quantum processes involve signal times smaller than the pico- and femtosecond scale they correspond to electronic transitions. These include electron transfers and changes in molecular bonds in ionic channels and synapses that cause the release of synaptic vesicles across synaptic clefts. The probability of synaptic vesicle exocytosis per excitatory impulse is less than 100% due to voltage potential barriers within the microstructures. An incoming nerve impulse excites electronic configurations to metastable levels at these sites. It is in this way that neural networks stay close to instability with subthreshold levels of depolarization that are insufficient to stimulate action potentials. The microstructures of groups of neurons can be switched to new states by the collective action of incoming action potentials sufficient to cause depolarization leading to synaptic exocytosis and the transmission of brain waves along neural networks. Quantum tunneling triggers this process by which wave impulses are able to pass through voltage potential barriers to cause exocytosis. (2) I elaborate on the details of synaptic transmission and quantum tunneling in my book, Nerve Endings of the Soul: interaction Between the Mind of God and the Mind of Man through Neural Synaptic Networks.
An Historical Review
For a historical understanding of brain waves I refer to the pioneering work of the Nobel Laureate Sir John C. Eccles. In his book published in 1977 with Karl R. Popper, The Self and Its Brain (3), how cortical modules of pyramidal cells relate to the self-conscious mind is considered. They proposed that the self-conscious mind actively scans and reads out the wave forms and frequencies of the multitude of cerebral modules in the neocortex, the principal site of cognition that act as detectors of specific scanning wave patterns. They describe this as the highest level of brain activity. The self-conscious mind selects from the background wave patterns of modules by focusing attention, or interest, on specific objects or activities integrating what is selected from moment to moment to give unity to experiences. Matching of wave frequencies, amplitudes and phases of the mind with the modular wave functions is selected by the scanning process of the mind resulting in neuronal synchronization. Moreover, the self-conscious mind can modify the spatiotemporal wave patterns of modules, thereby exercising both an interpretive and controlling role upon the impulses. The authors stressed that the integrating unity of conscious experience is determined by the self-conscious mind and not by the neural machinery of the cerebral cortex and its modules. Not only does the mind read out selectively from the ongoing activities of the modular machinery but it also modifies these activities, a causal interaction.
Perception and intention are characterized by dynamic, coherent actions of specific areas in the brain with increases in regional blood flow. Activation generates spatiotemporal patterns of nerve impulses with specific frequencies, amplitudes and phases. These patterns draw upon memory codes maintained in neural networks, including the learned inventory of pyramidal cells. Cortical modules consist of many thousands of modifiable synapses which can act coherently with other neural bundles to generate action potentials that bring about specific functions. Exocytosis probability can be increased in neural modules since there is a constant subthreshold background activity that can be modulated by exocytosis in large numbers of synapses that generate top-down inputs of impulses that can stimulate spike trains of encoded information in recipient networks. (2) Coupling of wave frequencies between networks can establish oscillatory synchronization that can also increase the probability of neural exocytosis. So we see that waves do characterize brain function in specific ways. It has been suggested that mentation is also accompanied by wave oscillations, a topic that will be elaborated upon in paragraphs to come.
Bringing Up to Date
I now turn our attention to the more recent work of neuroscientists. As these articles are discussed we shall have reference to cortical modules, their structure and function as detectors, how they relate to neural wave patterns and codes, focused attention, how what is perceived by modular scanning is interpreted by the mind and how the causal effects of the mind are accomplished within the context of brain waves. We will consider what gives direction to the trajectories of brain waves, how the trajectories are formed and how they relate to cognition of the immaterial mind. I will do my best to make the content understandable, but waves in our brains is a complex and dynamic study.
Gyorgy Buzsaki and Brendon Watson (1) published an artlcle in 2012 that discussed brain rhythms and neural syntax and the implications for efficient coding of cognitive content. Brain rhythms, or oscillations, can interact with each other by several mechanisms. One example is phase coupling that involves the entrainment of oscillators with similar frequencies in which the phase of a given frequency is entrained by another. When multiple rhythms are present simultaneously, the phase of the slow rhythms, e.g. theta, modulates the power of the faster ones, e.g. gamma. A second interaction referred to as CFC creates packets of higher frequency waves that transmit information from one region of the brain to another conforming to syntactical rules. So we see that the various types of synchronization appear to serve the transmission of information from region to region, and the causal role of the mind is also to be considered. The syntactical rules apply to both sender and recipient so that encoded communication is meaningful and with purpose.
The temporal pacing of neuronal waves is accomplished by rhythmic inhibitory volleys of impulses. The balanced activity between stimulatory and inhibitory impulses is important to the generation of shorter frames of encoded messages. Oscillations have well-defined onsets and offsets with maximum and minimum spiking activity in the information-transmitting neural cells. Coupled with CFC this activity serves to establish syntactical rules within codes. Packets of gamma oscillations may be grouped by slower theta oscillations via CFC to associate linguistically encoded letters with words, and the theta waves can combine the words into sentences so that meaningful information can be transmitted across larger brain regions. CFC is considered the backbone of a neural syntax which induces segmentation and the linkage of spike trains into cell assemblies that transmit encoded oscillations. The words to which we refer are the oscillations of linguistic codes within neural wave patterns that vary in timing and rate that the mind learns to interpret over a lifetime, archiving them into memory by neural plasticity. Information trajectories and processing depend on the synchronization of neuronal oscillations, including those of the pyramidal neurons. It is believed that gamma cell assemblies constitute a useable packet of information with specific content with meaning and purpose.
There is a staggering number of ion channels in neural networks. This great number allows neurons to encode information within trains of action potentials with a wide range of frequencies, amplitudes, phases and shapes. The different channel types determine the diverse firing behavior of neurons that can change on a sub-millisecond timescale as was pointed out above. Action potentials serve a wide range of functions in neuronal networks by encoding information in their frequencies and patterns. The rich firing behavior of neurons depends on the numerous voltage-dependent ion channels and synapses and accounts for the incalculable number of neural codes that are generated over a lifetime and archived in memory. (4)
Let us revisit the dynamics of neuronal circuits. Neurons join a circuit one moment and another the next moment. The firing of action potentials also can rapidly change, as can the attentional focus of an immaterial mind! The waves of groups of neurons can entrain the waves of other neuron groups to form synchronous oscillations so that encoded information can be communicated between brain regions. For any task multiple brain networks may be active and integrated by the process of synchronization. Also of great complexity is the coupling and uncoupling of different wave frequencies transmitting information between local and global regions of the brain. Coherent brain waves can be changed in milliseconds! Doctor John Lieff has noted that there is no known center in the brain that directs this complex circuitry of rhythms and frequencies. Absent a center for this complexity isn’t the best explanation an immaterial mind interacting with each molecule, each cell and each brain region, with each neural code? (5) There is an important question to be asked. Does the mind itself generate waves? I shall address this important question as you read on.
Challenge to Neuroscientists
It is a challenging goal of neuroscientists to interpret, or to decode, the mental content of brain activity. Kendrick Kay and coworkers (6) designed a decoding method to characterize the relationship between visual stimuli and fMRI activity in visual areas. Their model consisted of a tuning of individual voxels for space, orientation and spatial frequency, estimated directly from neural responses evoked by natural images viewed by study subjects. Distinct voxel activity patterns were obtained for each subject. The stimulus related information that was decoded from voxel activity remained stable over time. fMRI signals contained a considerable amount of stimulus-related information that could be decoded. The ultimate goal of the investigators is to reconstruct the actual images seen by an observer from neural response patterns.
Another challenge to neuroscientists is to understand the role of neural oscillatory activity in sensory and cognitive functions. These include focused attention and intent to generate specific functions such as verbal communication, movement of an extremity or forming an original idea. Erol Basar and coworkers (7) have studied oscillatory brain activity and have identified a new trend in neuroscience, to understand the mechanisms by which the immense number of neurons interact to produce higher cognitive functions. Theirs is an important and detailed article that sheds much light on how cognition relates to brain waves. Neuronal populations interact across extended regions of the brain through large nerve bundles in modules and in tracts of axons. Each part of the brain has specific dynamics based on the history of life experiences and the input of neural stimulations. Their interactions generate new neural patterns which are dynamic flows with continuous distributions and trajectories through the brain. Brain oscillations are basic events with natural frequencies reflected in EEG oscillations. Most functions require an integrated action of neurons in many regions of the brain. We have seen that gamma oscillations serve to transmit information through brain regions. Theta, alpha, delta and beta oscillations also have specific functions, and during functional states major operating rhythms can change their functional roles within milliseconds, as we have seen, reflecting the numerous brain functions of the cognitive mind to which we are coming closer!
Neuronal Synchrony and Trajectories
Sensory input consists of the transmission of specific wave frequencies, amplitudes, phases and shapes. Brain areas exist that share these wave characteristics and can be entrained by the sensory input setting up synchronous wave patterns across areas of the brain that transmit information. One mechanism mentioned above is CFC. Wave frequencies may also involve phase and time coupling. For example, the state of attention is associated with 40Hz wave frequencies. The coupling of these frequencies with the frequencies of specific sensory modules facilitates the transfer of information within coherent, synchronous wave packets between brain regions that are the focus of attention. When resting wave frequencies in specialized modules are entrained by matching input frequencies of sensory input the synchronous, coherent oscillations of the generated spike trains are given trajectories through the brain that bring about perception. Cognitive tasks have been observed to give rise to marked theta band increases in evoked action potential components. Theta responses appear to serve as carrier signals for cognitive processing.
A unique type of oscillatory activity cannot be given to only one function. Neural oscillations have multifold functions and provide codes for functional activity. These are very dynamic activities about which much more will be learned in time. Evoked brain potentials range from delta to gamma frequencies and are real brain responses that are related to cognitive brain functions.
Thoughts do give rise to action via an intention network that exists in the human brain. Conscious motor intention, such as the intent to raise an arm, increases the excitability of target-specific motor circuits in the supplementary motor area. (8) By employing fMRI investigators found in study subjects that movement intentions could be decoded from brain signals. The conclusion they reached is that cognitive brain activity occurs before any movement execution. Conscious voluntary intention determines the trajectory of motor representation via oscillatory synchronization, or tuning, of corticospinal excitability specific for a motor response. Goal directed excitation favors the recruitment of specific spinal motor neuron pools to bring about the desired movement. And it is a mind that establishes a goal!
Dendrites and Traveling Waves
The neocortex is the center for cognition. Cortical modules consist of six laminae which house pyramidal cells and their numerous axons and dendrites. The apical dendrites in lamina I and II are located in the most superficial part of the cortex and finish in extensive tuft-like branching. These are the basic anatomical units of the neocortex and are the cortical units for reception, giving them a preeminent role in cerebral function. Attention is a top-down process that targets apical dendrites in layer I. (9) Dendritic domains have distinct synaptic inputs, excitability, modulation and plasticity, features that allow synapses throughout the dendritic tree to contribute to action potential generation. These properties support a variety of coincidence-detection mechanisms underlying advanced cognitive functions. Humans have the most elaborate and spine-rich dendritic trees that receive input from other cortical regions. Dendritic spines vary in their size and shape and are highly plastic so that they change with experience. Dendritic synapses appear to work in concert to generate action potentials. The coincident activation of a sufficiently large number of inputs from dendritic trees can cause pyramidal cells to reach the action potential threshold to generate action potentials, a process of so-called coincidence detection. The separation of basal and apical dendrites on all pyramidal neurons implies that these dendrites have distinct functions that could include receptivity to cognitive wave train input, especially by the apical dendrites. (10)
It is often the case that neuroscientists do not address the role of the immaterial mind in cognitive processes that include attention and motor functions. In the article by Spratling I quote several sentences in his Conclusion to which I will offer a comment.
“In addition, by influencing activation each dendrite can affect learning in a biologically plausible manner, neurons are likely to learn correlations between the separate information streams targeting the apical and basal dendrites. Apical inputs can therefore influence learning at the basal dendrite and may be considered a source of reinforcement or supervision. This interpretation is bolstered by the fact that the apical dendrites in layer I not only receive projections from other cortical regions but are also targeted by the limbic system, a widely projecting set of interconnected brain structures concerned with emotion and memory.” (9)
The several words in bold type can be attributed to cognitive processes of an immaterial and personal mind. Instead, the author relegates these activities to computations by the brain, a common thread in reductive materialism where cognitive activities are attributed to the functions of components of the material brain. The function of neurons cannot account for learning, supervision, emotion and cognitive memory, all of which depend on the interpretation by a mind of neural codes!
The receptor field of dendritic trees of the neocortex selectively initiates action potentials when it detects specific wave patterns. It has been reported by Stewart Heitmann and coworkers (11) that the dendritic field has spatially organized receptors that act as filters of the input of wave patterns that decode the information contained within their wavelength, coherence and direction. There is emerging evidence that dendritic integration within cortical modules is sensitive to the relative timing and spatial location of synaptic input on the dendritic arbors. This observation reflects Eccles’ description of “detector” modules (3) in the neocortex that respond to scanning by the self-conscious mind with, I suggest, its specific wave frequencies.
The authors describe spatially organized waves of neuronal activity that propagate across the cortex during sensory or behavioral tasks. Waves of action potentials are given direction in their spike trains by this dendritic receptor mechanism so that motor impulses are directed to specific muscle groups to bring about desired action. An arrangement of excitatory and inhibitory receptors in the dendritic receptor field acts as the spatial filter of incoming wave patterns, allowing for the discrimination of encoded nerve impulses to be directed through axonal networks to appropriate receptor groups. The authors describe traveling oscillatory waves that encode information within motor commands from the neocortex (and I add from the intention of the cognitive mind). The spatial filtering by dendritic trees leads to their decoding to generate the trajectories for propagating downstream neural impulses that induce specified motor activity according to the neural code, such as limb movement and speech. Muller and coworkers (12) suggest that traveling waves have a functional role in associating cell assemblies by phase coupling (13) and activating them in the cortex. They propagate in the direction of maximal information transmission and are considered relevant for human cognition that is supported by neural patterns organized across both time and space. Traveling waves may have a role in brain connectivity and oscillations of cognition by showing when behavioral information is represented and where impulse signals are propagated.
William A. Phillips (14) has presented evidence for the hypothesis that input to the apical tufts of neocortical pyramidal cells relates to cognition. Inputs to apical tufts comes from a number of sources including direct feedback from higher cortical regions, indirect feedback from the thalamus and long-range lateral connections within and between cortical regions. Again, we can look forward to future studies that investigate how the immaterial mind interacts with the apical tufts of pyramidal cells, the predominate cell type in the neocortex for cognition.
Mind and Dualism
We can now see that patterns of wave frequencies are generated by sensory receptors and by cognitive activity that interact with the modular and synaptic networks of the neocortex. Neural networks are spatially arranged within the neocortex. Networks express specific wave frequencies that can be entrained by incoming wave fronts with coherent frequencies. Frequencies are thereby synchronized, such as by CFC or phase coupling, and transmitted along coherent neural networks with specific trajectories to intended final receptors. It is a complex process that is under active study. In Part One of this blog it was emphasized that many neuroscientists simply do not address the functional relationship of the mind to these processes, attributing all cognitive activity to the physical brain. As we proceed focus will be directed to interaction between the immaterial mind and the material synaptic networks of the brain. We have seen how over time there has been an evolution of understanding of these processes through the work of neuroscientists from across the world. The main question I ask the reader to consider is, how does the immaterial mind relate to these processes in a dualist interaction?
Cognitive Dynamics
Pascal Fries (15) points out that neuronal networks oscillate with rhythmic fluctuations that produce temporal windows for communication. Coherently oscillating neuron groups interact since their communication windows for input and output are open at the same time. The highly flexible pattern of coherence defines the communication structure that provides for our cognitive flexibility. It does not depend on the anatomical communication structure of the brain. Only coherently oscillating neuronal groups can communicate effectively since input and output windows for communication are open at the same time. Cognitive top-down control has flexibility in the routing of signals through the brain within milliseconds on top of the anatomical structure of synaptic networks. It is coherent oscillation within neuronal groups that are phase-locked or in synchrony that provide the means for effective communication between functional regions of the brain (and with the immaterial cognitive mind, I suggest!). For a sending group of neurons to communicate a coded message of information to a receiving group the output of the sending group must arrive at the receiving group when it is excitable irrespective of distance and the neuron groups are coherent with each other. Fries gives the example that in a unidirectional communication sending group oscillations may entrain the oscillation intrinsically generated in the receiving group, as in a cortical module, or it could drive an oscillation in the receiving group. Communications are facilitated in a selective, structured manner so that spike trains of action potentials are given trajectories down specific networks. Neuronal coherence causes communication to be selective since it is determined by focused attention, further accounting for the trajectories of neuronal transmission through the brain.
Fries summarizes the general mechanisms for the preferential routing of selected encoded spike trains. When the oscillatory rhythm of a sending group is passed to other groups of neurons, then the subthreshold membrane potential fluctuations of the receiving neurons become entrained to the selected rhythm. The entrained neuronal groups are therefore sensitive to the selected input, selectively routed along only coherent groups of synaptic networks.
Earl K. Miller and Timothy J. Buschman (16) have studied brain rhythms for cognition. They asked what a thought looks like in neurobiological terms. It is universally considered to involve a neural ensemble that together represents an item of information. Neurons at the higher areas of the cortex important to cognition are highly multivariate and dynamic, participating in many overlapping ensembles. The brain has mechanisms that coordinate interactions between neurons to form ensembles and networks of ensembles that produce clear and coherent thought and action. The flow of neuronal traffic is managed by rhythmic synchrony between neuronal groups so that ensembles are part of a larger functional network primed to transmit specified information. Changing rhythmic synchronization between neuronal groups alters their communication and thereby changes the direction of flow of information through the brain, a process that can occur within milliseconds as we have seen. The authors state that there must be some sort of mechanism for selecting specific neurons for membership in specific ensembles. It is my suggestion that that mechanism is the cognitive mind, giving neurons in the higher neocortex heterogeneity in function so that they can transmit many sorts of information at different times, a process called multiplexing. Signals that underlie cognition operate discretely with pulses of activity that rout packets of information, shaping the flow of encoded neural signals. “…the brain’s physical infrastructure (i.e. its anatomy) dictates where neural signals can flow; synchronized rhythms dictate where signals do flow.”
The Neural Codes of Overt and Covert Speech
Through Part Two of this blog references have been made to cognition, attention and intent, and we have seen that waves are transmitted intrinsically through neural networks to bring about specific functions such as to move an extremity. What is left is to address the question raised above, how does the immaterial mind relate to these processes in a dualist interaction? Does the human mind generate waves extrinsic to the brain itself that can act causally on it? Stephanie Martin and eight coworkers published an article in Frontiers in Neuroengineering that addresses this question with exciting findings. (17) I conclude this blog with a discussion of their findings.
The model used was ECoG in seven epileptic patients who performed an out loud and silent reading task. Subjects read short stories that were presented to them both aloud and silently. A high gamma (70-150 Hz) neural decoding model was built “to reconstruct spectrotemporal auditory features of self-generated overt speech.” The decoding model trained from overt, spoken speech was used to decode the neural activity of covert, silently read speech (which did not involve auditory sensory input, only input from mentation!). Spectrograms were generated in controls and in subjects who used overt and covert speech to reconstruct neural responses with a high statistical accuracy. Evidence was provided that showed that representations of overt and covert speech could be reconstructed sharing a neural substrate. In other words, out loud speech and read text could be reconstructed in neural networks monitored via ECoG. No wires connected the test subjects to the cortical monitors, indicating that the cerebral network responded to waves generated by the mind of the test subjects. The high gamma band reliably tracked neuronal activity and correlated with the spike rate of the underlying neural population. The key test of reconstructive accuracy, according to the authors, was the ability to use the reconstruction to identify specific speech utterances. This was possible especially for overt speech.
This is an important study on which I will base comments in my next blog, “Minds in Communion.” I will consider how the Holy Spirit communicates with us via the synaptic networks of our brain, a topic I addressed in detail in my book, Nerve Endings of the Soul: Interaction Between the Mind of God and the Mind of Man Through Neural Synaptic Networks. We now have evidence that is consistent with dualist interaction between the immaterial mind of humans and the Mind of God and the material neural networks of the human brain. The mind of Man communicates bidirectionally via the synaptic networks of the brain. Since the mind of Man is created in the image of the Mind of God it is reasonable that He can enter our dimensions and commune with Man via these same synaptic networks.
Summation
Humans learn to interpret neural codes transmitted within their brains as perceptions, such as witnessing the beauty of a flower garden or the voice of a loved one, or as intent to move an extremity. Over a lifetime of experience countless neural codes are established by synaptic plasticity, and they are archived in memory within neural networks. Cognitive actions of will, for example to move an extremity, draw upon memory stores. It is increasingly documented that the immaterial mind can exert causal effects on the synaptic networks of the physical brain. It gives validation to dualist interaction between what is immaterial, the mind, and what is material, the extensive neural networks of the brain. Neuroscientists are increasingly acknowledging this bidirectional dualist interaction that gives credence to communion between the Mind of God by His Holy Spirit and the mind and soul of Man through the brain.
References
1. Gyorgy Buzsaki and Brendon O. Watson, “Brain Rhythms and Neural Syntax: Implications for Efficient Coding of Cognitive Content and Neuropsychiatric Disease,” Dialogues in Clinical Neuroscience, Vol 14, No. 4, 2012.
2. Friedrich Beck, “Synaptic Quantum Tunnelling in Brain Activity,” NeuroQuantology, Vol 6, Issue 2, June 2008.
3. Karl R. Popper and John C. Eccles, The Self and Its Brain: An Argument for Interactionism, Springer-Verlag, Berlin Heidelberg, London, New York, 1977.
4. Bruce P. Bean, “The Action Potential in Mammalian Central Neurons,” Nature Reviews/Neuroscience, Vol 8, June 2007.
5. Jon Lieff, “Neuronal Networks and Brain Waves,” Searching for the Mind, December 7, 2014.
6. Kendrick N. Kay et al, “Identifying Natural Images from Human Brain Activity,” Nature, Vol 452 (7185), March 20, 2008.
7. Erol Basar et al, “Oscillatory Brain Theory: A New Trend in Neuroscience,” IEEE: Engineering in Medicine and Biology, May/June 1999.
8. Volker R. Zschorlich and Rudiger Kohling, “How Thoughts Give Rise to Action – Conscious Motor Intention Increases the Excitability of Target-Specific Motor Circuits,” PLOS ONE, Vol 8, Issue 12, December 2013.
9. M. W. Spratling, “Cortical Region Interactions and the Functional Role of Apical Dendrites,” Behavioral and Cognitive Neuroscience Reviews, Vol 1(3), 2002.
10. Nelson Spruston, “Pyramidal Neurons: Dendritic Structure and Synaptic Integration,” Nature Reviews, Vol 9, March 2008.
11. Stewart Heitmann et al, “A Dendritic Mechanism for Decoding Traveling Waves: Principles and Applications to Motor Cortex,” PLOS Computational Biology, Vol 9, Issue 10, October 2013.
12. Lyle Muller et al, “Cortical Traveling Waves: Mechanisms and Computational Principles,” Nat Rev Neuroscience, Vol 19(5), May 2018.
13. Honghui Zhang et al, “Theta and Alpha Oscillations Are Traveling Waves in the Human Cortex,” Neuron, Vol 98, June 27, 2018.
14. William A. Phillips, “Cognitive Functions of Intracellular Mechanisms for Contextual Amplification,” Brain and Cognition, Vol 112, March 2017.
15. Pascal Fries, “A Mechanism for Cognitive Dynamics: Neuronal Communication through Neuronal Coherence,” Trends in Cognitive Science, Vol 9(10), 2005.
16. Earl K. Miller and Timothy J. Buschman, “Brain Rhythms for Cognition and Consciousness,” Neurosciences and the Human Person: New Perspectives on Human Activities, Political Academy of Sciences, Scripta Varia, Vol 121, Vatican City, 2013.
17. Stephanie Martin et al, “Decoding Spectrotemporal Features of Overt and Covert Speech from the Human Cortex,” Frontiers in Neuroengineering, Vol 7, Article 14, May 2014.