Picking the Brain

[This post based on the  Securing Wireless Neurotransmitters, Marin et al., 2018 ] How can we make sure Brain-Computer Interfaces (BCIs) don't get hacked? A brain implant is a huge security risk. Currently, an attacker who successfully hacks such an implant could gain total control over a patient's life. In the future, if/when BCIs are able to read and write neural data at the thought level, a hacker could literally rewrite someone's thoughts, memories, and beliefs by compromising a target's BCI. The paper we discuss here proposes a method for securing current neurostimulators, with applications to all current and future wireless medical devices and BCIs.  Executed Hack Other researchers have already demonstrated that the implanted medical devices used for treating conditions like diabetes or irregular heartbeats are vulnerable to attack, and for the first time, this study demonstrated attacks on a device implanted in the brain. The researchers were able to carr...

[Elon Musk & Neuralink's "An Integrated Brain-Machine Interface Platform With Thousands Of Channels"  inspires this post.] What is Neuralink's primary goal, and what have they done to achieve it? Neuralink's primary goal is to make a high-bandwidth, high-resolution brain computer interface that is also highly scalable and suitable for chronic implantation. While each of the four components of this goal -- bandwidth, resolution, scaling, longevity -- is difficult on its own, Neuralink has made significant progress on each one over the last few years. This post will summarize what Neuralink has achieved in each category, according to their published paper (note: apparently even more has happened than just what they've publicly announced). Bandwidth The very high electrode density in Neuralink's device requires a very high bandwidth transmission interface. Even the USB-C interface (which can carry up to 40Gb/s) discussed in the paper, isn't fast...

[This post based on the  Brain-Computer Interfaces Handbook, Chapter 37 ] What is a bi-directional brain-computer interface? Bi-directional brain-computer interfaces (BCIs) are BCIs that can both read and write data from the brain. For example, a bi-directional BCI might read motor data from the brain to control a prosthetic arm, and then write sensory data back to the brain about where that prosthetic is in space. Bi-directional BCIs can be divided into their afferent (write) and efferent (read) elements, modeled after afferent and efferent neurons in the body: A fferent Neurons: A ssimilate  information in the brain by sending info towards the Central Nervous System (CNS). E fferent Neurons: E xport  information away from the brain/CNS and towards the rest of the body. Thus, in the example above, the afferent element is the sensory data about where the prosthetic is in space, and the efferent element is the motor data that controls the prosthetic arm's ...

[This post based on the  Brain-Computer Interfaces Handbook, Section 1.1 ] Why are Brain-Computer Interfaces (BCIs) important, and how do we classify them?  BCIs enable humans to affect the world in ways other than physical movements by providing new output pathways. These new 'output pathways' can enable us to restore lost functions to patients with neural damage, as well as provide new capabilities to healthy users. One example of how these new output pathways can be used is this  2015 study in which a BCI was used to control a quadcopter. An analysis of that BCI based on the classification criteria presented here is at the end of this post. Usually, BCIs use the following pipeline to read and understand data: In this post, we'll analyze how we classify BCIs based on the first two steps of that pipeline. Step 1 For the first step (Brain Activity Pattern Generation), there are two main classes of how the BCI affects the brain activity generation step: Act...