Neuron oscillations reveal the stability of structures linked to bodily movements
Study of noise in the electrical signal transmission potential of nervous system cells may contribute to future diagnoses and therapies
Noise from neurons and synapses of the nervous system, acting in complex circuits, may be associated with the variability of brain behaviors and even human creativity – Photo: ManuelSchottdorf / Wikimédia Commons
In the future, the results of the study, presented in an article in the scientific journal Chaos, Solitons and Fractals, may contribute to developing diagnoses and therapies related to the nervous system. “Our objective was to quantitatively study the stability of biological neural circuits known as Central Pattern Generators (CPGs)”, professor Reynaldo Daniel Pinto, from the IFSC, who participated in the study, told Jornal da USP. “We did this by altering the connectivity, that is, the synapses between the neurons of the circuit.”
“These circuits exist in practically all animals, encompassing vertebrates and invertebrates, and are specialized in the automatic production of essential rhythms”, the researcher pointed out. “They generate repetitive behaviors without the need for conscious thought, such as walking, running, swimming, breathing, chewing and moving food through the digestive tract, allowing the brain to keep its focus on other tasks.”
The neurons of the CPGs are organized into local networks interconnected by electrical synapses, bidirectional physical connections between cell membranes that allow the passage of electrical current as if they were resistors, and chemical synapses, unidirectional and mediated by neurotransmitters. “The discovery of the CPGs entailed breaking the dogma of ‘centralized control,’ according to which the brain would need to command every movement of the body”, said Pinto. “Today we know that the nervous system operates hierarchically; there is a peripheral autonomy in which the brain can merely send a simple ‘on/off’ or ‘go faster/slower’ signal, delegating the detailed execution to the local CPGs.”
“A single circuit is capable of producing rhythms that are robust and, at the same time, flexible. This occurs, for example, in the CPGs of the spinal cord of animals that command the alternation of the legs and transitions between gaits—walking, trotting, and galloping, without constant cerebral intervention”, the professor emphasized. “There are also autonomous spinal circuits that make us lift our foot when we step barefoot on a sharp object, or that retract our hand when we touch something very hot, even before this information reaches the brain.”
Origin of noise
Understanding these mechanisms in peripheral CPGs has helped explain activity patterns in the central nervous system, such as alpha and gamma waves, which are associated with sleep, relaxation, attention, and memory, the IFSC researcher noted. “In addition, researchers have found that even with a small number of neurons—on the order of a dozen—CPGs function as complex systems in which behavior is an emergent property of the circuit as a whole, reflecting the same operating principle as the brain itself”, Pinto clarified.
The professor explained that, in simplified terms, a neuron’s average electrical potential can be understood as the net difference in electrical charge between the inside and outside of its cell membrane at a given instant. “The dynamics of this charge balance are produced by the opening and closing of ion channels, very small structures that span the cell membrane and connect its interior to the exterior”, he said.
“It is these channels that allow the selective passage of electrical charges, that is, of ions, across the cell membrane. Due to the reduced size of the ions and channels, all of this charge movement is subject to microscopic thermal agitation, which is known as Brownian motion”, he stated.
Local fluctuations can lead to the opening and closing of other nearby channels, and propagate through the membrane. “The integration of these local fluctuations throughout the neuron leads to small oscillations of the global membrane potential that are practically impossible to predict, but which may, in certain situations, alter the electrical dynamics of the neuron and influence the behavior of the circuit as a whole”, he emphasized.
“It is these unpredictable oscillations that occur naturally in real biological neurons that we consider as noise in our work. This type of noise appears in every neuron and synapse of the nervous system” – Reynaldo Pinto
“However, although the term noise is commonly associated with undesirable phenomena, the opposite may be true in the nervous system: we can speculate that this intrinsic noise, acting in complex systems, gives rise to the extraordinarily rich variability of brain behavior and even to human creativity.”
Neuronal responses
The researchers altered the connectivity of a CPG in the stomatogastric ganglion of crustaceans, which is responsible for chewing and filtering food in the stomach, using a method known as dynamic clamp, which couples computational models in real time with biological neural circuits. “We inserted electrodes into a pair of mutually inhibitory neurons and, through these electrodes, were able to measure membrane potentials and inject electrical currents into the neurons”, Pinto said. “The electrodes were connected to a computer, where mathematical models calculated the current that one of the synapses between the neurons would inject into the other, based on real-time measurements of membrane potential.”
“A neuron’s response depends on the sum of all currents acting on it. By manipulating the magnitude and sign of this calculated current before injecting it into the biological neuron through the electrode, we can weaken, cancel, or even reverse a real synapse, transforming it from inhibitory to excitatory”, the IFSC professor explained. “Because these synaptic changes affect the circuit’s rhythm, we sought to characterize its stability quantitatively by examining what happens to quantities known as dynamic invariants—the relationships among pattern characteristics that are important for motor behavior, such as the duration of one neuron’s firing period relative to the duration of the full cycle.”
The study showed that the variability needed to compute the stability of dynamic invariants comes precisely from the small cycle-to-cycle fluctuations produced by intrinsic noise. “In our experiments, we manipulated one of the CPG’s strongest and most important inhibitory synapses, effectively canceling it and even slightly reversing it. Even under these extreme conditions, the circuit continued to produce the dynamic invariants in a stable manner”, Pinto said.
“We concluded that CPG function remains robust even after profound changes in connectivity, demonstrating the presence of redundancies capable of maintaining stable circuit function under natural noise conditions, even in extreme situations.”
According to the professor, one contribution of the study to research on the brain and nervous system is demonstrating how intrinsic noise can be used as a quantitative analysis tool, especially in systems with strongly oscillatory behavior. “We showed that noise can be harnessed to extract precise information about the system’s level of stability”, he noted.
“In CPGs, rhythmic periodicity and stability are desirable. In other neural circuits, however, similar behavior that macroscopically takes over network dynamics may be associated with disease”, he observed. “One possible application would be to conduct similar analyses to assess the stability of oscillations produced by epileptogenic foci, with the goal of developing closed-loop neuromodulation systems—known as closed-loop stimulation—capable of disrupting that stability, or pharmacological interventions that destabilize the focus without having to destroy or physically remove it.”
The study involved researchers Marcelo Reyes, from the Federal University of ABC (UFABC); Pedro Carelli, from the Federal University of Pernambuco (UFPE); Reynaldo Daniel Pinto, from the IFSC; and Ramon Huerta, Mikhail Rabinovich, and Allen Selverston, from the University of California, San Diego (UCSD), in the United States. The article Intrinsic noise reveals the stability of a neuronal network was published in the scientific journal Chaos, Solitons and Fractals.
For more information, contact professor Reynaldo Daniel Pinto at reynaldo@ifsc.usp.br
*Intern under the supervision of Simone Gomes
English version: Nexus Traduções, edited by Denis Pacheco
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