By NAVEEN JOSHI
AI’s early beginnings and steady development over the years have been largely possible due to neuroscientific studies and research. Moving forward, AI and neuroscience continue to be heavily interdependent for their respective advancements.
If you think about it, both AI and neuroscience deal with the same thing. Experts in both fields intend to constantly discover the depths and myriad capabilities of the human brain. There are several aspects of AI and neuroscience that overlap with each other. While they exist to serve different end purposes, it is not a stretch to say that AI and neuroscience are closely linked. In fact, the learnings from neuroscience act as cornerstones for data experts while building AI-powered systems.
At its core, AI is meant to replicate the workings of the human brain to make machines and digital applications as intuitive and efficient as possible. To achieve this, engineers in the field of AI build neural networks (with intelligent algorithms) that mimic the structure and processes of the human nervous system. At the same time, neuroscientists can benefit from deep learning and other AI components to find cures and better solutions for complex illnesses such as Alzheimer’s and Amyotrophic Lateral Sclerosis (ALS).
How AI Revolutionizes Neuroscience
Incredibly, AI and deep learning can help humans understand how their own brains work. As we know, the human body is a complex entity including several organs, cells, tissues, blood vessels, neurons, glands and several other components. The brain is our body’s chief coordinator regarding things we can control (external muscle movements, decision-making, speech) and the ones we cannot (knee-jerk reactions, blood circulation, digestion). AI’s findings can enhance what humans know about the brain. They can tell us how the cerebrum, brain stem and cerebellum can be optimized with advanced medicines and healthcare hacks to cure conditions such as Tourette’s syndrome. Currently, neurological experts continue to delve deeper into how our brain relays impulses to different parts of the body for performing various movements. By discovering new learnings through AI, health experts will be able to unlock the hidden capabilities of our brains. With a better understanding of the brain’s different lobes, health experts will be able to definitively deal with paralysis and other movement-related conditions suffered by millions worldwide.
With deeper, AI-generated knowledge about the brain’s structure and functions, neuroscientists can create better simulations of the brain for training neurology students in medical institutes. Moreover, AI’s pattern recognition abilities can allow scientists to efficiently test newer hypotheses and publish their findings for medical advancements. Several aspects related to the human brain are still relatively vague or undiscovered yet. If AI uncovers these hidden details through its range of powers and abilities, neuroscience can make several strides towards perfection.
Speaking of the unknown, big data can help health experts with understanding the abstract and often unquantifiable aspects and functions of the human nervous system. For instance, AI models can be used to accurately simulate the various neuron-to-neuron connections in the body. Memory storage chips embedded in such systems could be used to delete certain memories or specific cognitive mechanisms to get substantive answers about memory loss in the elderly and reasons why individuals go into a coma after sustaining nasty head injuries or revisiting traumatic life experiences. Other areas where AI’s data crunching and anomaly detection could be used is to track the early signs and symptoms of epilepsy in patients. Measures such as electrical impulse treatments can help resolve the situation when epileptic attacks surface in such individuals.
One of the most fascinating aspects of neuroscience is the so-called ‘neural codes’—the underlying patterns in neurons and brain cells that are responsible for human behavior, mood swings and other abstract mental phenomena. With big data and unsupervised deep learning processes, neurologists will be able to ‘crack’ these codes to get a better understanding of human behavior. What’s more, these studies can then be applied in various fields, such as occupational health and safety or forensics.
Obtaining the Data Needed for Neuroscience Advancements
Currently, neuroscientists engage in understanding protein patterns and cranial regions to get information about the brain’s working. AI-powered models can provide them with the tools to study and examine neurons at the genetic level. Apart from this, advanced computer vision can assist neurologists with recreating actual neural linkages to get accurate information about their working (from a genomic perspective). Learnings from such studies can be priceless in the field of advanced genomics. As we move into the future of healthcare, generated data about the physical connections between neurons is becoming increasingly outdated. With AI, neurologists can create specialized simulations to get in-depth data regarding the process of impulse formation and transfer throughout the body.
AI is used for speeding the research process related to brain mapping or functional brain imaging. These processes generate vast quantities of statistical and visual data that can be processed, reconstructed, and annotated. Computer vision models can help with analyzing all types of images related to chemical balance and neural health. These types of mapping and imaging procedures can cut down on the time and human effort spent in compiling data. Projects such as Neurodata Without Borders (NWB) are invaluable sources of AI-generated brain data for neurologists. Thus, AI’s increasing involvement in neuroscience can be immensely beneficial for the healthcare industry.
How Neuroscience Improves AI Technologies
While AI is developing at a rapid pace and making giant strides in most industries, there are many aspects of the technology which could be improved. Most crucially, as specified earlier, AI intends to replicate the workings of the human brain in automated systems to make them better. However, the truth is that data scientists and analysts are still probably decades away from recreating genuine human intelligence in a lab. While neuroscience is not the only solution, it can certainly improve certain facets of AI in its own ways.
Firstly, neuroscience can be used for verifying and validating AI’s current models and technologies. In truth, AI’s algorithms follow completely different logical patterns while trying to mimic existing functions of the brain (The brain’s logical patterns for performing tasks are relatively unknown). This may not necessarily be a problem. In fact, it allows data experts to create benchmarks regarding the effectiveness of such algorithms to generate results compared to a human brain. As a result, neuroscience can be used to improve the quality of algorithms in AI.
Traditionally, logic-based procedures and mathematical models have featured in the working of a generic AI model. To enhance things up, neuroscience can complement these methods by classifying specific biological aspects which can be useful for an AI system to understand the various cognitive details related to the human brain.
An important challenge in AI training and research is transfer learning, which is a technique of training AI models by using pre-trained algorithms and neural networks. To process information in specific scenarios, AI systems need to use existing algorithms as a reference point before making balanced, risk-free decisions. Neuroscience involves the collection and intensive analysis of thousands of medical records. The massive reserves of information are essential for an AI system to know about the nervous system and its working. The medical records can be useful for an AI system as, through machine learning and other components, it can understand how the human brain and other related organs usually operate. Algorithms trained in the initial stages of this process can be used in transfer learning later. Ultimately, the vast sources of data from neuroscientific studies can provide an AI system with a basic understanding of how human intelligence works. Data generated from neuroscience is invaluable for AI’s long-term development.
AI and Neuroscience: A Symbiotic Relationship
Essentially, the concept of designing AI models to have them mimic the human nervous system was possible mainly due to neuroscientific research. The artificial neural networks of today are modeled on the network of nerves running throughout our bodies. Again, neuroscience has made replication possible. Similarly, AI systems are helping us paint an increasingly accurate picture of the human brain and its functioning. As a result, progress in each of these fields is not just critical for the other, but also valuable for other fields and industries that rely on them.
