Computational neuroscience in perspective

Abstract

Nowadays, the main questions related to brain functions are frequently taken as related to properties of the synaptic circuitry of the different regions which compose the brain structure. This line of thought was naturally infl uenced by the seminal discoveries starting with Cajal and Golgi (Nobel Prize awarded jointly in 1906), when the synapses were postulated as connections established between neurons. Reinforcing this view, Otto Loewi (1921) was the fi rst to present experimental evidences of the chemical bases for synaptic transmission. Even before the effective discoveries of the mechanisms behind the synaptic transmission, McCulloch and Pitts (1943) showed that simplifi ed neural networks are able to resemble complex properties of the brain. The proposition of the Hebbian theory by Donald Hebb, in 1949, added more enthusiasm to the view of the synaptic circuitry (or neural network) as the solely core of the brain function. Later, a debate led by John Eccles (1953), about the electrical or chemical processes involved in the synaptic transmission, culminated with the elucidation of the role of the acetylcholine as neurotransmitter. At that time, the ionic basis of the neuronal discharges was still under deep investigation and the complex interplay between the sodium and potassium currents demanded a new strategy to describe it. The advanced electrophysiological techniques were not enough to describe an action potential. Hodgkin and Huxley (1952) employed a very complex model, involving non-linear differential equations to represent experimental data and showing the intricate temporal dynamic. In 1973, Bliss and Lomo confi rmed the Hebbian theory with experiments performed in the hippocampus region, demonstrating that the chemical synapses could change their strength. All these fi ndings infl uenced the subsequent development of the neuroscience and the technology. The implementation of cyclic networks with feedbacks between neurons and adjustable synaptic weight provided the confi guration of dynamical systems with memory. Improvements of the neural network theory gained more and more attention, with effects that lasted for many years. The neural network theory regains strength and infl uenced the design of intelligent machines. This atmosphere of thoughts, dominated by the properties of synaptic circuitry as the solely core of the brain function, persists infl uencing our view about the brain and its mechanisms. The same lines of thoughts are still guiding the different approaches in the investigation of brain pathologies, such as epilepsy. However, a new scenario is becoming evident. The synaptic circuitry view of interfering into the neuronal interconnection with drugs acting in the synaptic neurotransmission is not being successful with the more than 40% of patients diagnosed with temporal lobe epilepsy. This is the most common type of epilepsy and affects 2% of the Brazilian population! The main suspicion about the ineffectiveness of the available drugs is that the origin of the seizures does not belong...