The Real Science (Not Armchair Science) Of Consciousness

Among brain researchers there’s a truism that says the reason people underestimate how much unconscious processing goes on in your brain is because you’re not conscious of it. And while there is a lot of unconscious processing, the truism also points out a duality: your brain does both processing that leads to consciousness and processing that does not. As you’ll see below, this duality has opened up a scientific approach to studying consciousness.

Are Subjective Results Scientific?

Researcher checking fMRI images.
Checking fMRI images.

In science we’re used to empirical test results, measurements made in a way that are verifiable, a reading from a calibrated meter where that reading can be made again and again by different people. But what if all you have to go on is what a person says they are experiencing, a subjective observation? That doesn’t sound very scientific.

That lack of non-subjective evidence is a big part of what stalled scientific research into consciousness for many years. But consciousness is unique. While we have measuring tools for observing brain activity, how do you know whether that activity is contributing to a conscious experience or is unconscious? The only way is to ask the person whose brain you’re measuring. Are they conscious of an image being presented to them? If not, then it’s being processed unconsciously. You have to ask them, and their response is, naturally, subjective.

Skepticism about subjective results along with a lack of tools, held back scientific research into consciousness for many years. It was taboo to even use the C-word until the 1980s when researchers decided that subjective results were okay. Since then, here’s been a great deal of scientific research into consciousness and this then is a sampling of that research. And as you’ll see, it’s even saved a life or two.

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How To Telepathically Tell A Robot It Screwed Up

Training machines to effectively complete tasks is an ongoing area of research. This can be done in a variety of ways, from complex programming interfaces, to systems that understand commands in natural langauge. A team from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) wanted to see if it was possible for humans to communicate more directly when training a robot. Their system allows a user to correct a robot’s actions using only their brain.

The concept is simple – using an EEG cap to detect brainwaves, the system measures a special type of brain signals called “error-related potentials”. Simply noticing the robot making a mistake allows the robot to correct itself, and for a nice extra touch – blush in embarassment.

This interface allows for a very intuitive way of working with a robot – upon noticing a mistake, the robot is able to automatically stop or correct its behaviour. Currently the system is only capable of being used for very simple tasks – the video shows the robot sorting objects of two types into corresponding bins. The robot knows that if the human has detected an error, it must simply place the object in the other bin. Further research seeks to expand the possibilities of using this automatic brainwave feedback to train robots for more complex tasks. You can read the research paper here.

MIT’s CSAIL work on lots of exciting projects – their video microphone technology is truly astounding.

[Thanks to Adam Connor-Simmons for the tip!]

Hacklet 105 – More Mind And Brain Hacks

A mind is a terrible thing to waste – but an awesome thing to hack. We last visited brain hacks back in July of 2015. Things happen fast on Hackaday.io. Miss a couple of days, and you’ll miss a bunch of great new projects, including some awesome new biotech hacks. This week, we’re checking out some of the best new mind and brain hacks on Hackaday.io

We start with [Daniel Felipe Valencia V] and Brainmotic. Brainmotic is [Daniel’s] entry in the 2016 Hackaday Prize. Smart homes and the Internet of Things are huge buzzwords these days. [Daniel’s] project aims to meld this technology with electroencephalogram (EEG). Your mind will be able to control your home. This would be great for anyone, but it’s especially important for the handicapped. Brainmotic’s interface is using the open hardware OpenBCI as the brain interface. [Daniel’s] software and hardware will create a bridge between this interface and the user’s home.

 

biofeed1Next we have [Angeliki Beyko] with Serial / Wireless Brainwave Biofeedback. EEG used to be very expensive to implement. Things have gotten cheap enough that we now have brain controlled toys on the market. [Angeliki] is hacking these toys into useful biofeedback tools. These tools can be used to visualize, and even control the user’s state of mind. [Angeliki’s] weapon of choice is the MindFlex series of toys. With the help of a PunchThrouch LightBlue Bean she was able to get the EEG headsets talking on Bluetooth. A bit of fancy software on the PC side allows the brainwave signals relieved by the MindFlex to be interpreted as simple graphs. [Angeliki] even went on to create a Mind-Controlled Robotic Xylophone based on this project.

brainhelmetNext is [Stuart Longland] who hopes to protect brains with Improved Helmets. Traumatic Brain Injury (TBI) is in the spotlight of medical technology these days. As bad as it may be, TBI is just one of several types of head and neck injuries one may sustain when in a bicycle or motorcycle accident. Technology exists to reduce injury, and is included with some new helmets. Many of these technologies, such as MIPS, are patented. [Stuart] is working to create a more accurate model of the head within the helmet, and the brain within the skull. From this data he intends to create a license free protection system which can be used with new helmets as well as retrofitted to existing hardware.

mindwaveFinally we have [Tom Meehan], whose entry in the 2016 Hackaday Prize is Train Your Brain with Neurofeedback. [Tom] is hoping to improve quality of life for people suffering from Epilepsy, Autism, ADHD, and other conditions with the use of neurofeedback. Like [Angeliki ] up above, [Tom] is hacking hardware from NeuroSky. In this case it’s the MindWave headset. [Tom’s] current goal is to pull data from the TAGM1 board inside the MindWave. Once he obtains EEG data, a Java application running on the PC side will allow him to display users EEG information. This is a brand new project with updates coming quickly – so it’s definitely one to watch!

If you want more mind hacking goodness, check out our freshly updated brain hacking project list! Did I miss your project? Don’t be shy, just drop me a message on Hackaday.io. That’s it for this week’s Hacklet, As always, see you next week. Same hack time, same hack channel, bringing you the best of Hackaday.io!

Hacklet 56 – Brain Hacks

The brain is the most powerful – and least understood computer known to man. For these very reasons, working with the mind has long been an attraction for hackers, makers, and engineers. Everything from EEG to magnetic stimulus to actual implants have found their way into projects. This week’s Hacklet is about some of the best brain hacks on Hackaday.io!

teensy-bio[Paul Stoffregen], father of the Teensy, is hard at work on Biopotential Signal Library, his entry in the 2015 Hackaday Prize. [Paul] isn’t just hacking his own mind, he’s creating a library and reference design using the Teensy 3.1. This library will allow anyone to read electroencephalogram (EEG) signals without having to worry about line noise filtering, signal processing, and all the other details that make recording EEG signals hard. [Paul] is making this happen by having the Teensy’s cortex M4 processor perform interrupt driven acquisition and filtering in the background. This leaves the user’s Arduino sketch free to actually work with the data, rather than acquiring it. The initial hardware design will collect data from TI ADS129x chips, which are 24 bit ADCs with 4 or 8 simultaneous channels. [Paul] plans to add more chips to the library in the future.

 

bioxNext up is [Jae Choi] with Lucid Dream Communication Link. [Jae] hopes to create a link between the dream world and the real world. To do this, they are utilizing BioEXG, a device [Jae] designed to collect several types of biological signals. Data enters the system through several active probes. These probes use common pogo pins to make contact with the wearer’s skin. [Jae] says the active probes were able to read EEG signals even through their thick hair! Communication between dreams and the real world will be accomplished with eye movements. We haven’t heard from [Jae] in awhile – so we hope they aren’t caught in limbo!

bioloop[Qquuiinn] is working from a different angle to build bioloop, their entry in the 2015 Hackaday Prize. Rather than using EEG signals, [Qquuiinn] is going with Galvanic Skin Response (GSR). GSR is easy to measure compared to EEG signals. [Qquuiinn] is using an Arduino Pro Mini to perform all their signal acquisition and processing. This biofeedback signal has been used for decades by devices like polygraph “lie detector” machines. GSR values change as the sweat glands become active. It provides a window into a person’s psychological or physiological stress levels. [Qquuiinn] hopes bioloop will be useful both to individuals and to mental health professionals.

biomonitorFinally we have [Marcin Byczuk] with Biomonitor. Biomonitor can read both EEG and electrocardiogram (EKG) signals. Unlike the other projects on today’s Hacklet, Biomonitor is wireless. It uses a Bluetooth radio to transmit data to a nearby PC or smartphone. The main processor in Biomonitor is an 8 bit ATmega8L. Since the 8L isn’t up to a lot of signal processing, [Marcin] does much of his filtering the old fashioned way – in hardware. Carefully designed op-amp based active filters provide more than enough performance when measuring these types of signals. Biomonitor has already found it’s way into academia, being used in both the PalCom project, and brain-computer interface research.

If you want more brain hacking goodness, check out our brain hacking project list! Did I miss your project? Don’t be shy, just drop me a message on Hackaday.io. That’s it for this week’s Hacklet, As always, see you next week. Same hack time, same hack channel, bringing you the best of Hackaday.io!