understanding the brain is clearly a biological problem but acquiring the map of the brain even though the human brain may seem like a small object if you start looking at it nanometer by nanometer you end up with literally an exabyte of data I think it's fair to say that without Google research help we would have failed Google deep Minds AI brain has been making waves in the scientific Community recent breakthroughs by brain are shedding light on the complexities of the human mind but what exactly is Google deep mind uncovering about our thoughts emotions in the very essence of Being Human let's find out Google deepmind AI brain Google Deep Mind collaborated with researchers from Harvard University to achieve a remarkable feat they created an artificial brain for a virtual rat that can control its movements in an ultra realistic physics simulation this groundbreaking work published in the journal Nature provides new opportunities for studying brain function and controlling complex behaviors the the artificial brain mimics the structure and function of a real rat's brain in the simulation the virtual rat can navigate its environment react to stimuli and perform tasks that require coordination in decision-making this level of realism in the simulation allows scientists to study brain functions in ways that were previously impossible one of the most exciting aspects of This research is its potential to enhance our understanding of the human brain by studying how the artificial brain controls the virtual rat researchers can gain insights into the neural mechanisms underlying movement learning and behavior this could lead to discoveries about brain function and contribute to the development of treatments for neurological disorders furthermore This research has big implications for the field of Robotics the principles learned from the artificial brain could be applied to create more advanced and adaptive robots these robots could potentially perform tasks with a level of autonomy and flexibility that current robots cannot achieve for instance robots with artificial brains could navigate complex environments learn from their experiences and adapt to new situations much like a real animal how it works they created an accurate biomechanical model of a rat's body using a sophisticated physics simulator called mushuk this virtual rat was created to imitate the physical constraint and mechanics of a real rodent to achieve such realism it had to follow the basic laws of physics like gravity and friction and mimic the musculoskeletal movements of an actual rat's body to construct this highly detailed model the researchers Drew from an extensive data set of highresolution motion data recorded from real rats these recordings captured the rats performing a wide range of natural behaviors and movements providing an incredibly rich source of information the data set included every conceivable action a rat might Undertake from running and climbing to more subtle Motions like grooming or exploring its environment this depth and breadth of data were crucial in ensuring that the virtual model could accurately reflect the complexity of a real rat's movements building an anatomically accurate rat body was just the beginning of this ambitious project the next critical step was to develop an artificial neural network capable of controlling this virtual body's biomechanics and replicating the diverse range of movements observed in the biological data this is where Google deep mind's expertise in machine learning played a pivotal role they apply Advanced deep reinforcement learning techniques to train the artificial neural network which would serve as the virtual rat's brain this collaboration combined deep Minds expertise in artificial intelligence and machine learning with Harvard's deep understanding of biomechanics and neurofunction to control the virtual rat's movements the researchers employed a method called inverse Dynamics modeling this approach is based on the way our brains are theorized to control complex movements inverse Dynamics modeling involves calculating the necessary forces and torqus needed at various joints to produce a desired motion it's like figuring out what muscle actions are required to move your arm to a specific position in the context of the virtual rat inverse Dynamics modeling helped the artificial neural network learn how to generate precise movements by understanding the mechanics of the rat's body the neural network had to determine which muscle contractions in joint movements would result in the rat walking running or performing other tasks accurately by using this method the virtual rat's brain could simulate the coordination and control seen in a real rat's movements the researchers at Deep mine and Harvard fed the virtual rats neural network with reference motion trajectories derived from the real rat data these trajectories acted as inputs providing a detailed map of the desired movements the virtual rat needed to replicate essentially the neural network had to learn how to translate these motion paths into coordinated muscle actions and Joint movements the research Discovery the neural network can apply what it learned to new situations the virtual rat could move and behave in realistic ways it was isn't specifically trained for just like a real brain the neural network could adapt its knowledge to different tasks and situations this ability to generalize shows how advanced the AI created by Deep Mind in Harvard is the neural Network's capacity to generalize its learning to new scenarios is similar to how a real rat or even a human learns once basic movement patterns and behaviors are mastered these can be adapted and applied to novel tasks for instance a real rat that learns to navigate a maze can apply its knowledge to different mazes with varying obstacles similarly the virtual rat's neural network could take what it learned from specific training data and apply it to New untrained situations producing movements that were still realistic in biomechanically sound with this virtual rat brain successfully controlling the biomechanical model researchers could delve deeper into the workings of the neural network they could gain valuable insights into how real rat brains might control movement this step is crucial for understanding the neural mechanisms underlying motor control and behavior the researchers discovered that the virtual brains neural activity patterns were very similar to those recorded from real rats brains while they were moving this amazing similarity suggests that the AI had figured out ways to control movement just like real brains do in other words the AI not only learned to move the virtual rat but also developed brain activity patterns similar to those of actual rats a key feature of the virtual brain was its ability to switch between different modes based on the situation this behavior is very similar to how a real rat's brain changes its activity patterns for different actions like grooming running or standing up for example when a rat goes from running to grooming its brain activity changes to meet the different needs of these activities the virtual rat's brain showed a similar ability adjusting its neural activity patterns to fit the specific tasks it was doing the ability to switch between different modes is essential for how natural brains work it helps animals quickly adapt to changing situations and perform various tasks well the virtual rat's brain showed this flexibility meaning the Deep learning algorithm learned some key principles of how real brains control movement these transitions in the virtual brain weren't pre-programmed but came from the learning process this suggests the neural Network understood different situations and behaviors on its own managing the transition smoothly researchers saw how the virtual brain moved effortlessly from one activity to another adjusting its neural patterns in ways similar to live animals the success of the virtual brain in mimicking these complex neurodynamics opens up exciting possibilities for future research it provides a powerful tool for exploring how brains generate and control diverse behaviors by studying the virtual brain scientists can gain insights into the underlying mechanisms of brain function that are difficult to investigate in living animals due to the complexity and ethical constraints of biological experiments another important Discovery came from studying how random changes in the virtual brain's activity affected the rat's movements clear patterns showed how these neural fluctuations led to specific movement changes you can't see this kind of detail just by watching the the overall movements but examining it closely can reveal how the brain codes information because the virtual system was fully observable and controllable researchers were able to gain these insights the future Direction there is still a lot to learn in this area but the virtual rat brain has created a new way to study motor control and brain function that wasn't possible before instead of just recording neural signals during Behavior neuroscientists can now explore and manipulate a complete model of the brain body and environment in a simulation this marks a new era which some are calling virtual Neuroscience virtual Neuroscience allows researchers to study brain function in ways that were previously impossible traditional methods of studying the brain often involve invasive techniques and are limited by the complexity and ethical concerns associated with live animal research however with a virtual brain scientists can explore neural processes in a highly controlled and detailed manner free fre from these limitations one significant advantage of this approach is that it enables testing and refining theories about how neural circuits Implement specific computational processes for example researchers can investigate how the brain estimates the state of the body and environment predicts future States optimizes costs and rewards and orchestrates coordinated patterns of movement these are fundamental questions in neuroscience and the virtual rat brain offers a powerful tool for addressing them State estimation involves the brain's ability to understand and predict the current state of the body and its surroundings by using the virtual rat brain scientists can simulate various conditions and observe how the neural network adjusts its state estimation in real time this can provide insights into the mechanisms underlying this critical function predictive modeling is another area where the virtual rat brain can be invaluable the brain constantly makes predictions about future events based on past experiences and current sensory input by studying the virtual rat researchers can see how these predictions are generated and how they influence behavior this can help unravel the complex interplay between prediction and action in the brain if you have made it this far let us know what you think in the comments section below for more interesting topics make sure you watch the recommended video that you see on the screen right now thanks for watching