Brain-Mind Models

The brain, like a computer, is an information handling device. It collects and organizes information, and then uses it to control mental and physical activities. The concrete, physical mechanisms of the brain drive the abstract, spiritual activities of the mind. There are more than hundred billion neurons in the brain, organized in networks in which each neuron is connected to many others. If we could follow the activity of each neuron, we would have a description of the physical processes that underlie our mental activities. But this is not feasible. Instead, brain-mind models use networks of nodes in which each node represents a group of many neurons. The nodes retain some properties of individual neurons and some properties of the group as a whole.

Nodes and Neurons: Similarities and Differences

A node is similar in structure to a neuron. It has input channels, a central body, and output channels. Nodes are connected in networks, similar to neural networks. Like neurons, a node can be in a quiet or in a firing state. A firing node sends signals through its axonic branches to the dendrites of the nodes that are connected to it.  The body of the node can perform sophisticated calculations that cannot be performed by a single neuron. In the brain, such calculations are done by entire networks of neurons.  Whether the receiving node will be in a quiet or a firing state depends on the outcome of those calculations. Another difference is that signals between two nodes can flow in both directions, whereas they can flow only in one direction between two neurons.

It is possible to develop a mathematical model that simulates the main parts and activities of a single neuron. Such a model will have dendrites, soma, and axon with its branches. Propagation of pulses in the dendrites, their integration by the soma, firing, and sending out signals through the axon can also be simulated. It is also possible to build a network of such model-neurons in which signals pass from one neuron to another through their common synapses. However, extending this approach to a model of the entire brain, with its billions of neurons and thousands of synapses per neurons, is far beyond the capabilities of present day computers.

Like neurons, nodes are connected to one another by a synapse. A synapse is characterized by a synaptic weight, which is a rough measure to the degree of association between the concepts that the nodes represent. Consider nodes whose firing threshold is one. If the synaptic weight from node A to node B is one, then if A fires, the signals that it sends to B will activate B. If the weight is less than one and positive, contributions from other firing nodes will be necessary to make B fire. If the synaptic weight is negative, firing of A inhibits B. In order for B to fire, it will have to receive signals that will cancel the negative contribution of A. Unlike neurons, in which a synapse allow signals flow in one directions, information between two nodes can flow in two directions. To accommodate it, two independent synapses, one in each direction, connect two nodes. In the brain, such functionality may be obtained by intermediary neurons.

Micropsychology: relating computers and brains

There are many similarities between brains and computers. Computers use a hierarchy of programs to process information. At the lower levels are programs that handle bits and bytes. Lower level programs serve as building blocks of high level programs. For example, a spell-checker is a program that handles words and sentences. It gets information from the outside and analyzes it using its stored dictionary and grammatical rules. It then searches for corrections when appropriate, and displays the results. All those higher level operations are carried out by low level operations that handle bits and bytes. All higher level operations of computers, including word processing, Internet applications, and controlling machines are based on fundamental instructions that handle bits and bytes.

Similarly, the brain performs a hierarchy of mental operations. At the basis are fundamental operations that handle information at the level of a nerve cell. At the high-end are mental operations such as thinking and controlling complex activities of the body. The high-end operations are composed of fundamental operations at the cell level.

Micropsychology deals with the fundamental operations of the brain; with the bits and bytes of the mental operations. Psychology, on the other hand, deals with macro-behaviors, which are built with the fundamental micropsychological operations.

Computers use the same fundamental operations to do all the high level applications. Their fundamental operations do not depend on the meaning of the handled information. The same bits and bytes instructions are used for all applications. That is also the case with the brain. The same basic operations at the cell level are used for all mental activities, regardless of the meanings of the activity. The same basic operations underlie solving a puzzle and finding a mate.

However, there are differences between brains and computers. Usually, computers rely on random access memory (RAM), whereas brains rely on associative memory. In RAM, given information may be placed in any memory cell. In associative memory, the meaning of the information depends on the cell that holds it and on the relationships between that cell and other cells. For example, a certain cell in the memory of the bank’s computer, say cell number thousand, stores the balance of my account. The next day, when information is updated, cell number thousand may store a customer name, and my balance will reside in cell number seventy. The brain stores its information differently. The meaning of the information depends on the cell that holds it and on physical connections between that cell and other cells.  For example, a certain cell in a brain represents a bright point at a certain location in the field of view. Another cell represents a face, which is a pattern of bright and dark points in the field of view. The cell that represents face has connections to the cells that represent single points. Information in the brain is updated by the modification of connections between cells. Those modifications embody changes in the associations between information entities.