UPDATE: 21st May, 2022: Dr Ryan Field (the presenter I mention in the original piece) has been kind enough to share some detailed responses to some of my questions in the comments below — definitely check out his comment after you read this piece!
I was lucky enough to attend the Psych Symposium in London last week, and one of the more intriguing presentations was by Dr Ryan Field of Kernel in which he showcased the Kernel Flow brain imaging device. Kernel have recently partnered with Cybin (one of the larger psychedelic drug companies, and one of the more advanced, in terms of clinical trial pipelines) to use the Kernel Flow device in a pilot study of the effects of ketamine on the brain.
So, what is the Kernel Flow device? It’s a wearable brain imaging device that looks like a kind of segmented helmet, and is based on time-domain functional Near Infrared Spectroscopy (TD-fNIRS) technology.
The basic technology of fNIRS has been around since the 1980s, and it involves shining near-infrared light through the head. Haemoglobin in the blood is a good absorber of near-infrared light, and fNIRS is capable of distinguishing concentrations of oxy- and deoxy-haemoglobin so it’s possible to get information about haemodynamic changes in the brain, with a similar signal to the BOLD signal used in standard functional MRI. Because it’s completely non-invasive, harmless, and relatively lightweight and portable, fNIRS is a popular technique in some of the cutest neuroimaging studies ever conducted, on babies and infants.
The technique has strong limitations though. The infra-red light gets scattered by passing through the scalp and skull, and this limits the spatial resolution of fNIRS to about 2–3cm; an order of magnitude bigger than typical spatial resolutions used in fMRI. The temporal resolution is typically around 10Hz (or, sampling ten times per second) which is not as good as other methods such as EEG, but much better than fMRI. In addition, the penetration depth of the light is pretty low — around 1.5–2cm. This means it’s only really good for recording from the most superficial layers of the cortex. For a really good overview of fNIRS principles and techniques, see this review paper from 2018.
Time-domain fNIRS is a relatively recent development where pico-second scale (i.e. very, very short) infrared laser pulses are used, and this allows acquisition of additional information derived from the timing of arrival of photons at the detectors. Since the photons are only travelling a few centimetres at the speed of light, you need exquisitely precise methods to measure the timing variations; only possible with modern computer chips that can do pico-second level timing.
Traditional fNIRS devices use a cap that’s tethered with a cable to an amplifier and interface box, and then a computer to record the data. What the team at Kernel have done is minituarise the whole apparatus, made it wireless, and put it into a wearable helmet-like device. This is definitely a significant and impressive technical achievement. However, the amount of real data they’ve presented so far is pretty thin, and as a neuroimager and neuroscientist, I have questions. Lots of them.
The Kernel team have published one formal paper, which has lots of details on the technical specifications of the device, but only a brief discussion of its actual performance, and some very preliminary data from two subjects doing a finger-tapping task, with recordings from primary motor cortex. They claim their sampling rate is 200Hz, which is technically impressive, but given that the signals recorded are haemodynamic (blood flow) changes which are slow (on the order of 5–6 seconds) this is not so important; even a ‘standard’ 10Hz rate is still massively over-sampling the haemodynamic signal, so I’m not sure what extra (useful) information a 200Hz sampling rate would give you. The paper doesn’t seem to have any information about spatial resolution or penetration depth; arguably the more important characteristics of the system.
The data presented at the Psych Symposium was also… kinda weird. You can see the results in this press release, but the key slide was this one:
This seems to show patterns of functional connectivity for five days before, and five days after, a ketamine dosing session, in a single subject (actually the Kernel company founder, Bryan Johnson). It wasn’t clear how they actually derived these connectivity maps, and what they really mean. There seems to be a strong asymmetry in them, with one (pink) hub in the left frontal lobe which has a strong connection to lots of other areas. As I said, kinda weird.
Also, in the image below, they seem to have derived network plots which include relatively deep-brain structures, with the nodes extending down to at least the level of the thalamus/striatum and some nodes on the medial surfaces of the cortical hemispheres. This seems… odd, given the strong limits on penetration depth of all previous fNIRS systems. Unless the Kernel team have made a real game-changing breakthrough in the technology, this seems unlikely.
Clearly the Kernel team have made a highly-advanced device which can potentially make a real contribution to neuroimaging research. These developments in wearable brain imaging devices like Kernel Flow (and the recent OPM-MEG innovations) can potentially mean that we can do neuroimaging outside the confines of an MRI or PET scanner; or even leave the laboratory behind and acquire functional brain data out in the ‘real’ world. This is definitely an exciting prospect, however I think it remains to be seen whether the portability/ease of use are truly useful innovations, and outweigh the strong limitations on the quality and kinds of data that can be acquired from such devices based on fNIRS technology. I’m very much looking forward to seeing more data and formal write-ups from the Kernel Flow device and what kinds of data it can actually provide.
