Logic Gates and Neurons:
Intelligent Design and Programming Found in Computers and Neuroscience

by Dallas F. Bell, Jr.

1. Introduction

A renowned scholar in the field of cognitive neuroscience recently gave a talk to a few hundred university professors. With a wide smile, he said some people still believe in God. The audience began to snicker. Fighting back laughter, the speaker continued and said that those same people also believe in something called sin. The speaker and his audience burst into laughter at the absurdity of those notions taking several moments before he could resume the lecture. That same week the inventor of the magnetic resonance imaging (MRI) machine, which is greatly used in neuroscience, and hundreds of millions of people with intellect, education, and experience similar to the speaker and his audience attended a church to worship God and confess their failure to comply with natural law--sin.

The professor and his audience of professors expressed a dyad logic set of (no God, no sin) with a truth value set of (0,0) regarding compliance with reality which are monads of systematic theology. (Please see the paper by Dallas F. Bell, Jr. titled Rationality Tables: Applying Polarizing Nonmaterial Monads in Risk Analysis.) The professors' consistent triad logic set would be (no sin, no justice, no love) with a truth value set of (0,0,0). The values of no justice and no love absurdly nullify the purpose and construction of the social institution dyads of family, church, business, and government.

How do the views of the professors and opposing views occur like those held by the inventor of the MRI with a logic set of (God, justice, love) or (1,1,1)? Systematic political science presents the behavioral model where each person's chosen theological track leads to an epistemological track which provides the rationality for all individual behavior in pursuing common needs. People with the same tracks form societal groups with the same eschatological beliefs based on their theology. This paper will focus on the brain's intelligent design and theological programming that leads to logic needed for subsequent behavior. First, the intelligent design and programming of computers will be addressed to aid in the understanding of neuroscience.

2. Logic Gates (Computers)

A logic gate is a structure of switches used to calculate, via logic, in digital circuits thereby creating digital computers. Logic gates produce predictable output based on the input. Generally, the input is one of two selected voltages represented as (0) and (1). An "and" gate has the following truth table of sets.

input      output
(0,0) then (0)
(1,0)      (0)
(0,1)      (0)
(1,1)      (1)

An "or" gate is shown below.

input      output
(0,0) then (0)
(1,0)      (1)
(0,1)      (1)
(1,1)      (1)

Inverters or "not" gates allow the alternate gates of "not and" called "nand", and "not or" called "nor". A "nand" gate has the following sets.

input      output
(0,0) then (1)
(1,0)      (1)
(0,1)      (1)
(1,1)      (0)

A "nor" gate is shown below.

input     output
(0,0) then (1)
(1,0)      (0)
(0,1)      (0)
(1,1)      (0)

The (0) has low voltage and the (1) has higher voltage. The range is between 0.7 volts in emitter coupled logic to approximately 28 volts in relay logic. The function of different gates can be seen below.

or: high input creates high output
nor: high input creates low output
and: low input creates low output
nand: low input creates high output

Logic gates cannot store a value nor have memory, because when and if an input changed the output would immediately react. However, the inherent properties of a capacitor allow a charge to be stored. Feedback may preserve input if the output is routed through the logic again using a latch or clock.

The first logic gates were mechanically made in 1837. Today microprocessors may contain over a million individual gates for the processor and use hundreds and thousands of millions of gates for memory. Employing some additional language constructs, most programming languages use lambda calculus.

3. Neurons (Neuroscience)

In the brain, nerve cells known as neurons function in a more complex yet similar way to logic gates in digital computers. Unlike most cells, neurons have a structure of axons and dendrites for transmitting signals. A neuron receives a range of input from its dendrites, integrates them, and produces an output in the axon depending on the type and frequency of the input signal. That signal provides input to other neurons or cells such as muscle cells.

The input to a neuron must surpass a threshold to cause it to react. The input signal depends on whether the synapse, the collection of signals between the axon and dendrites of neurons, is strong, or weak, or excitatory, or inhibitory. A neuron with two inputs can act in different modes depending on the type and strength of its inputs.

The output of a neuron's axons is a series of pulses of on and off signals as seen in computers' logic gates. Neurons are much more complex and versatile than computers, since they integrate thousands of inputs from dendrites, and process them both temporally and spatially. Computers must execute a function or program in a sequence of steps.

The logical function of two strong excitatory inputs of logic "or" the neuron will be stimulated if either input is active. In the logic "and" of two weak excitatory inputs both must be active to stimulate the neuron. With a logic of "if", having one weak and one strong excitatory input, the strong input must be active for the weak input to generate effect. The activity of the neuron depends on the activity of the weak signal, but only if the strong signal is active.

The logical functions of mixed inputs of a strong inhibitory input and a weak excitatory input of logic "if-not" the inhibitory input will overwhelm the excitatory input if it is active. The neural activity depends on the weak excitatory input, but only if the strong inhibitory input is active.

Neurons, unlike computer logic gates, are adaptable. Internal and external factors may cause the neurons' functions. Neurons can memorize information for a short-term by a electrochemical process or long-term by structural means. With electrical memory, ions flow due to transmission and basic information processing lasting 1 to 100 milliseconds.

Chemical change may create a second to a minute of memory as balances and secondary messengers affect receptors and ion channels in the cell membranes. Memory lasting for 1 to 24 hours occurs by molecular synthesis and gene expression leads to long-term modification. Structural changes in the cell itself last from 1 to 365 days. This alters information processing and also changes membrane extensions i.e. synapses and dendrites connecting to other neurons and the outside. In cellular memory the brain can relate temporal and spatial information deemed critical for sequencing motor movements.

Ion channels are membrane proteins that function as electrical signal transducers. They govern the electrical properties of all living cells. The function of ion channels is regulated by a number of signaling molecules. Their classifications include K+, Na+, non-selective cation channels, etc. Ion channels are divided into voltage-gated and ligand-gated channels based on the type of physiological stimulus activator.

There are one hundred billion or more neurons in a human brain. There are three times more glial cells. Glial cells modulate the rate of nerve impulse propagation and control the uptake of neurotransmitters. The brain is theologically programmed to comply with material and nonmaterial realities with truth values of (1) or accept their alternative of noncompliance with realities which have truth values of (0). The internal choice of each individual then allows the neurons to act as logic gates to process input consistent with the logic chosen by freewill.

4. Conclusion

Both logic gates in computers and neurons studied in neuroscience reflect similar intelligent design and programming. Obviously, design requires there to have been a designer with purpose and therefore intellect. We can see how the professor discussed in the introduction of this paper reached his system of logic which rejected intelligent design. His stare decisis logic set (0,0) or (no God, no purpose) caused his neuron logic gates to accept other logic sets for consistency such as the untrue dyads of (no purpose, no order).

Conversely, a well-known scientist with decades of espousing the same untrue logic values recently changed his view when studying DNA. His logic set is not perfectly (1) but is no longer (0). Using Bayes' averaging his previously position of 0% probability of the existence of God was adjusted by the 100% proof of the Divine DNA designer. It could be assumed he now has a mathematically 50% belief in the existence of God. Given there are observed to be no nonbelievers in foxholes or on deathbeds evidencing the fact that all people are programmed with a belief in God, it is doubtful anyone can truly have a 0% belief in the probability of God's existence.

On the other hand, how could there be a 100% belief in the probability of God's existence? Children begin exhibiting a 100% belief at an early age, but authority figures such as parents or educators may cause this choice of belief to change to a lesser percent. According to the monads of systematic theology, if the natural or programmed belief in God is augmented with submission to God's atoning plan then the Holy Spirit creates a perfect certainty. That 100% belief or acceptance of the true theological neuron program would seem foolish to anyone without Divine assistance.

Subjects were recently analyzed using event-related functional MRI to examine neural activation with anticipated probable material gains and losses or expected value (EV). Group results indicated the subcortical nucleus accumbens (NAcc) activated proportional to anticipated gain and the cortical mesial prefrontal cortex (MPFC) also activated to anticipated gain. Individual results indicated that NAcc activation correlated with probability. These discoveries indicate that the mesolimbic brain regions support EV and cortical regions represent a probabilistic component and may integrate both. Efforts like this continue to affirm that neurons provide both the material proof and the method for processing the ultimate reality of their Divine designer.

Acknowledgements

The author appreciates the pioneering efforts of all those that have directly and indirectly contributed to making this paper possible.

-----------------ALL RIGHTS RESERVED © 2006 DALLAS F. BELL, JR.--------------