A material has been created that imitates how the brain stores information
Researchers have developed a material that can replicate the way the brain stores information. The material works by copying the synapses of neurons, allowing it to mimic learning that occurs during deep sleep. The team of researchers, from the Universitat Autònoma de Barcelona (UAB), built the magnetic material using a type of computation called neuromorphic computing.
Neuromorphic computing is a computing concept that uses artificial neurons to mimic behavior of the brain and the synaptic functions, or communication signals, of neurons. One imitation of the brain function is neuronal plasticity, which is the “ability to store information or forget it depending on the duration and repetition of the electrical impulses that stimulate neurons,” as stated in the study. This form of plasticity is linked to memory and learning within the brain.
The study was published in the journal Materials Horizons.
Materials that emulate learning
The research team discovered certain materials that mimic neuron synapses. The materials include memresistive (electronic memory) materials, ferroelectrics, phase change memory materials, topological insulators and magneto-ionic materials. The team noted that magneto-ionic materials were the most recent materials and are formed by changes in the magnetic properties that are produced by the movement of ions, or atoms, within the material.
The movement is caused by applying an electric field to the ions. In the magneto-ionic materials, researchers know how the magnetism is controlled when an electric field is applied, but it is difficult to control the progression of magnetic properties when voltage is stopped. This makes it difficult to imitate brain functioning, such as the process of learning that occurs even while the brain is in a deep state of sleep and has no external stimulation.
The study was led by UAB Department of Physics’ researchers Jordi Sort and Enric Menéndez, in collaboration with the ALBA Synchrotron, the Catalan Institute of Nanoscience and Nanotechnology (ICN2) and the ICMAB. The team proposed a novel way of controlling the evolution of magnetization in the stimulated and post-stimulus states of brain functioning.
A new material was created that had a thin layer of cobalt mononitride (CoN). When an electric field was applied, the buildup of N (nitrogen) ions at the line between the layer and a liquid electrolyte could be controlled. “The new material works with the movement of ions controlled by electrical voltage, in a manner analogous to our brain, and at speeds similar to those produced in neurons, of the order of milliseconds,” said Jordi Sort, research professor at ICREA and Enric Menéndez, tenure-track professor of Serra Húnter at the Department of Physics at UAB.
“We have developed an artificial synapse that in the future may be the basis of a new computing paradigm, alternative to the one used by current computers”, Sort and Menéndez continued. The team discovered that they could emulate processes such as memory, information processing, information retrieval by applying voltage pulses. Also, for the first time, they could mimic the controlled updating of information without applying voltage. The control used in the study was created by modifying the thickness of the cobalt mononitride (CoN) layers - which determines the speed of the ions motion - and the frequency of the pulses from the volts.
The setup of the material allows the magnetoionic properties to be controlled both when the voltage is applied and when the voltage is removed. Once the voltage stimulus recedes, the magnetization can be either increased or decreased, based on the thickness of the material and how the voltage was applied.
The results from the study
The new result from the material opens a whole range of possibilities for neuromorphic computing functions, creating efficiency in perception, learning and memory using neural networks. The example given is the possibility of mimicking neural learning that happens after bran stimulation, during sleep. Currently, the functionality cannot by copied by any other existing neuromorphic material.
“When the thickness of the cobalt mononitride layer is below 50 nanometers and with a voltage applied at a frequency greater than 100 cycles per second, we have managed to emulate an additional logic function,” stated Sort and Menendez.
The researchers mentioned the significance of the study and the emulation of brain function. “Once the voltage is applied, the device can be programmed to learn or to forget, without the need for any additional input of energy, mimicking the synaptic functions that take place in the brain during deep sleep, when information processing can continue without applying any external signal,” stated Sort and Menendez.