In electronic terms, the brain has to be viewed as an analog system not digital. The difference is obvious to theorists and electronic engineers but may not mean much to other people. A tape recording is an analog record that stores a waveform analogous to sound waves or electronic waves generated by sound interacting with a microphone.

There are a host of properties of living systems that set them a part from non-living systems. The most fundamental properties of a living system are not possessed by any nonliving system are a preprogrammed metabolism (DNA), self-replication, self-reference, self-modification, spontaneous activity, growth and repair. Information processing in the brain is not electronic. It is electro-chemical and involves a neuronal version of quantum mechanics. The quanta are packets of chemicals, neurotransmitters.

Analog

Analog devices are closely related to the phenomena they represent. Analog computers use circuits that compute in real time. For example, you can arrange transistors to add or subtract two incoming signals - this can be done with a few transistors and the circuit can operate in real time 24 hours a day with instantaneous results. You could add other simple circuits to notice and make decisions about the difference between the two signals. This is an efficient approach to real-time computing. You would construct such a computer if you wanted a simple, efficient and reliable system that sensed, decided and acted in real time continuously over many years. This is the essence of living brains.

In contrast, a digital computer requires a more elaborate structure - the input signals have to encoded into a binary stream and stored in memory along with program instructions. The data can later be directed to a CPU that combines the incoming data with a program using logic, arithmetic instruction and memory addresses to arrive at the result. Results of CPU manipulations are then stored in memory, decoded and displayed.

The most important distinction between digital computing device and the brain is that the digital device separates data and the procedures that operate on the data. A brain integrates data and procedures so that you can never separate data, programs and hardware. The digital machine is more complex than an analogue computer, less reliable and consumes more space and energy than the analogue computer to accomplish the same task

A brain takes the analog approach and accomplishes sophisticated computations in real time, efficiently, usually without storing any data. There are no brain programs that resemble computer programs stored in a coded format since all the programming and all the data is built into neuronal networks.

Early studies of neurons focused on the on-off characteristic of action potentials and a misleading comparison has been made with the transistor switch in digital circuits. An action potential does not have the meaning of a 0 or 1 digital switch since there is no evidence at all of binary coding in the brain.

The action potential or spike is an analog signal that interacts complexly with other signals arriving at the receiving neuron. Each neuron is a computer in its own right and may have the signal-processing value of hundreds or thousands of transistors in a digital computer. Neuronal computation only makes sense when the neuronal interconnections are revealed by careful microscopic and electrochemical study. Neurons are living cells and unlike transistors, they breathe, eat, excrete, expand and contract, send and receive chemical messages. They get sick and die if conditions are not right. Neurons also pulse – they are spontaneously active; they can send messages whenever they feel like it. Neurons are not send-receive robots; they have their own ideas about what is going on.

Neurons are tree-like with branch-like extensions from the cell body that connect to other neurons by synapses. Koch reported  that neurons have numerous electrically active components in the incoming branches. These actively modify the effect of incoming messages. Computer simulations show that active elements probably multiply the influence of adjacent synapses. The timing and distribution of incoming spikes is important. Cells in monkeys' brains can adjust the intervals between spikes in increments as little as one hundredth of as second. Spikes propagate in the "forward" direction toward the synapses that relay outgoing messages and move back along the neuron's input branches toward the cell body. Synapses adapt to the incoming rate of spikes and are responsive to changes in electrical activity over a range of background levels.

Neurons are often spontaneous signal emitters; their outputs are sometimes rhythmic or periodic pulses that inhibit, excite or tune downstream neurons. Neuronal oscillators may also keep time and regulate body hormonal levels with pulses of chemical secretions. Oscillators are common in analog electronic circuits and are often the basis of tuning circuits to incoming waveforms. The spontaneous activity of oscillators is the essence of consciousness and brain activity in general and anyone who thinks of neurons as receive and send robots will come to all the wrong conclusions about how the brain works.

Koch suggests that the brain should be viewed as a hybrid computer, one that employs both digital pulses (between neurons) and analog computations (within them). I do not share Koch’s notion that there is any digital processing going on in the brain – a spike is an analog signal, equivalent to waves in a frequency modulated radio transmission – but much slower.

The prerequisite of digital computing is not the wave form (desk top computers use 1.5 to 5 volt rectangular waves or pulses) but the binary nodes that decide the meaning of inputs. You would have to find neurons wired up to make the logical decisions – and, or, not-or, not-and; your would also find memory storage in binary code – large arrays of transistor switches with a reader that can tell if each switch is on or off. I will be surprised if a single instance of digital computation is discovered in animal brains.   See Modular Mind