Impact of neural cyberattacks on a realistic neuronal topology from the primary visual cortex of mice

Brain-computer interfaces (BCIs) are widely used in medical scenarios to treat neurological conditions, such as Parkinson’s disease or epilepsy, when a pharmacological approach is ineffective. Despite their advantages, these BCIs target relatively large areas of the brain, causing side effects. In this context, projects such as Neuralink aim to stimulate and inhibit neural activity with single-neuron resolution, expand their usage to other sectors, and thus democratize access to neurotechnology. However, these initiatives present vulnerabilities in their designs that cyberattackers can exploit to cause brain damage. Specifically, the literature has documented the applicability of neural cyberattacks, threats capable of stimulating or inhibiting individual neurons to alter spontaneous neural activity. However, these works were limited by a lack of realistic neuronal topologies to test the cyberattacks. Surpassed this limitation, this work considers a realistic neuronal representation of the primary visual cortex of mice to evaluate the impact of neural cyberattacks more realistically. For that, this publication evaluates two existing cyberattacks, Neuronal Flooding and Neuronal Jamming, assessing the impact that different voltages on a particular set of neurons and the number of neurons simultaneously under attack have on the amount of neural activity produced. As a result, both cyberattacks increased the number of neural activations, propagating their impact for approximately 600 ms, where the activity converged into spontaneous behavior. These results align with current evidence about the brain, highlighting that neurons will tend to their baseline behavior after the attack.