Never be afraid to get dirty, but be sufficiently sure-footed to avoid the abyss of contamination.

Neuroscience and Engineering

It was Friday morning at ISIT, and some people had already left. Like the previous days, the morning started with a plenary talk. Unlike the previous days, Friday’s speaker was from outside the information theory community.

The speaker was Emery Brown, a professor in the Department of Brain and Cognitive Sciences at MIT and in the Department of Anesthesia and Critical Care at Harvard Medical School. He discussed his group’s work to build signal processing algorithms in neuroscience, and he showed videos that showcased the performance of those algorithms. One video in particular stuck out in my mind. It featured an animated rat moving around an enclosure and an estimate of its position. The animated rat and its estimated position corresponded to an experiment his group conducted on a live rat using signals from roughly thirty neurons to track the rat’s position.

The experiment was designed to test memory formation. The rat was introduced to the enclosure in question a few days before his group tracked its position. Furthermore, the neurons used were from the hippocampus, which is thought to play a role in memory. Indeed, Brown placed this work in the context of a series of experiments attempting to understand how the brain handles memory. However, there was something compelling about the experiment itself.

While those who study this experiment might not claim to understand exactly how memory works in the brain, they may still claim that what limited understanding of memory they have enables them to track a rat’s position under the conditions of the experiment. This concrete way to describe the utility of the experiment appealed to my sense of research aesthetics.

Research aesthetics was just one of several topics I discussed with Ram Srinivasan, a postdoctoral researcher in Neurosurgery at Massachusetts General Hospital and student at Harvard Medical School. Ram earned his PhD in EECS from MIT, where he worked in part with researchers from Emery Brown’s lab. He was also coadvised by Sanjoy Mitter, and his dissertation touched on the interplay between electrical engineering and neuroscience. It became clear from our discussions that his interest in this interplay dated back to his undergraduate days at Caltech.

The issue of aesthetics came up early in our conversation. We discussed the challenge of posing a concrete question. For instance, the context in which one asks another person if he is stressed can affect the answer. To contrast this with a concrete question, Ram mentioned a behavioral sciences paper that refuted a stereotype to show that women are no more talkative than men. How did the authors show this? The researchers had individuals carry around voice recorders over a period of days and found that both men and women spoke about the same number of words per day. In this case, word count in natural conversations gave a concrete way to measure talkativeness.

We discussed issues with applying standard ideas from control theory to the brain. For instance, one might engineer a control system such that sensing and actuation are distinct components. If one were to describe the brain as a control system, the delineation of sensing and actuation is an artificial choice of modeling. Such a choice may be informed by the specific application of the model. A separate but related issue is whether a distinction between motor and sensory regions in an organism actually exists. While standard dogma describes such a separation, an evolving perspective is that action and sensation are intertwined at multiple scales, from cell to organism.

In his own research, Ram is further exploring the brain-machine interface at the basic science and algorithmic levels. Having worked largely with data from collaborators and simulations during his PhD, his postdoctoral lab affords him the opportunity to design his own experiments to record single-neuron activity from awake humans. This work employs wet lab experiments to understand how movements are initiated. Additionally, he is beginning to reexamine the premise that the brain-machine interface is an estimation problem. He says his current position has given him a new perspective on the challenges of experimental design and the ways in which science and engineering research proposals can synergize to develop neurotechnology. Hopefully this new perspective will allow him to build on his earlier successes.

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