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Looking at an image and seeing that something just isn’t quite right is always an intriguing experience. From past experience, we expect to see one thing, but often upon immediate observation we see something else quite different. Optical illusions demonstrate to us directly that reality is created by our perceptions of the environment and these perceptions are processed in our brain. So, maybe reality is just all in our heads?

“Reality is merely an illusion, albeit a very persistent one” – Albert Einstein
(a popular misquotation extracted from “For us believing physicists, the distinction between past, present and future is only a stubborn illusion.”  Einstein: His Life and Universe by Walter Isaacson (2008), p. 540)

Classic examples of optical illusions include the floor tiling at the Basilica of St. John Lateran in Rome and the “flashing” grid illusion first reported by Ludimar Hermann in 1870. The twentieth century artist M. C. Escher took the phenomena to an artistic level and created some of the most popular and aesthetically interesting illusions, and many more optical illusions may be viewed with an image search.

Rotating Snakes illusion, Copyright A.Kitaoka 2003

In 2003, Akiyoshi Kitaoka, a professor of psychology at the Ritsumeikan University in Kyoto, Japan, designed a new visual phenomenon called the peripheral drift illusion, or “Rotating Snakes” (read the original report, PDF). In this design, an apparent motion of the image is seen in the observer’s peripheral vision. The effect is strongest when the image contains clearly graduating sections of repetitive diminishing or increasing brightness and these sections follow fragmented or curved edges. A variety of examples of the design can be previewed on Kitoaka’s website of Rotating Snakes.

This visual phenomena has fascinated scientists with the challenge to explain how our brains process this image. It was not until quite recently that an answer may have been experimentally discovered (“Microsaccades and Blinks Trigger Illusory Rotation in the “Rotating Snakes” Illusion”, Otero-Millan, et al. The Journal of Neuroscience, 25 April 2012, 32(17): 6043-6051; doi: 10.1523/​JNEUROSCI.5823-11.2012, Read the abstract). Researchers from the Laboratory of Visual Neuroscience at the Barrow Neurological Institute in Arizona, lead by  Dr. Susana Martinez-Conde, presented “Rotating Snake” images to participants while recording their eye motion with high-resolution. Previously, it had been presumed that the eyes were drifting during observation to create the apparent motion. However, they instead found that when the observers acknowledged motion in the images, their eyes were undergoing small rapid movements called microsaccades. These mini-eye movements represent small jumps in a person’s gaze position that help to refresh the input on retinal receptors during the intentional fixation on an image (“Toward a model of microsaccade generation: The case of microsaccadic inhibition” Rolfs, et al. Journal of Vision, August 6, 2008 vol. 8 no. 11 article 5 doi: 10.1167/8.11.5, Read the full-text PDF).

It is quite amazing to gaze at an image that you consciously know is static, yet you unquestionably see an apparent animation. Your understanding of reality conflicts directly with your observation of reality. For a quick personal experiment to see if I could control this reality distortion, I was able to temporarily pause the motion with a very focused attempt to stare only at one corner of the Rotating Snake image. As I let my focus shift just bit, the rotation immediately re-appeared. It is only a guess as to whether I was inhibiting the microsaccades of my eyes, or if I was positioning the image in some “peripheral blind spot” where the retinal receptors taking input from the eye motions couldn’t receive the input. Nevertheless, I do still feel quite grounded in reality; however, I am reminded to maintain an appreciation of questioning what I directly perceive around me as my brain will continue to work in ways that is beyond my conscious control.


A few days before the birth of our second child, Andrew Thomas Dearing, I wrote about a little project where I wanted to attempt to identify the onset of his brain’s consciousness… or, at least identify the vague concept that I seem to have of what consciousness really is.

As is clear from my lack of published articles over the past five months, I had decided to take a little break from my writing and reading about the current developments in neurotechnology to focus on the newborn and our first child, Elizabeth Noelle, who is now three years old. I am excited and anxious to work myself back into the great world of neurotechnology, and don’t be surprised if my experiences with my family make their way into future articles.

The original question still remains open, however: At five months old, is Andrew conscious? He is certainly a bright young man, eating well, laughing, reacting, and learning how to move about and function in his environment. He giggles when you play with him and he can’t keep his attention away from his intriguing big sister when she is in the room… even if it is time to eat!

But, is he conscious?

Frankly, I don’t think so … at least in that vague, ill-defined sense that I seem to have of what is consciousness. This sense is so vague I don’t think that I can even put it into words at this moment.

So, how am I supposed to identify something that I apparently don’t even know what it is? My only hope is that I do still recall “sensing” the general onset of consciousness with my daughter. It was not necessarily a particular instant in time, but really just a gut connection that there seemed to be “something more” behind her gaze. It’s this very special “something more” that I am still looking out for in Andrew.

And just because he doesn’t seem to have it yet–at five months old–doesn’t mean he isn’t progressing very well and proving to me every day that is his an awesome kid (hey, I’m a proud Daddy, if that’s OK). I just think that the level of consciousness that we vaguely attribute to the defining characteristic of being human is a threshold experience… a phase transition, of sorts, that the brain completes only after a certain level of complexity has been achieved in a developing brain.

In lieu of my continued speculation on the matter, I will defer to an interesting article that addresses this very issue. Recently published in the Boston Globe, writer Jonah Leher discusses the current ideas on what might be going on inside your baby’s brain. It is surprising, actually, and discusses the notion that the infant brain is incredibly over-active and functions in a sort of hyperconscious way that may provide significant advantages to the seemingly helpless baby–helping it to figure out how to deal with its environment as quickly as possible. And, it also provides us hyperfocused and slow-moving adults an idea toward triggering our sluggish brains to temporarily regress to be more open and creative… just like a baby.

“Inside the baby mind” :: The Boston Globe :: April 26, 2009 [ READ ]


New experimental evidence for how human brains form “memories” and later access them via the neural network has been reported by researchers lead by Dr. Itzhak Fried from the UCLA Medical Center.

By directly recording neuronal activity through implanted electrodes in a group of epilepsy patients at the hospital, data was first taken while the patients watched scenes in familiar video clips. The group was then later asked to freely recall any of the videos while neuron recordings continued.

Although single (or very small collections) of neurons were being directly recorded, it was determined that they were not acting alone while accessing the “stored memory.” Rather, the recall process was part of a much larger network, possibly comprised of hundreds of thousands of neuron nodes. In addition, the work provides a bit of experimental confirmation of the previously theoretical notion that “memory recall” involves the same neurons that are active during “memory formation.”

This understanding is vital for the development of neural devices because it is becoming even more evident that large, interconnected networks of neurons are required to create create memories and any form of human “thought.” If we want to create technologies that will directly integrate into human neural networks, there must be a full understanding of not just the structure of the network, but also how the network can re-use the same neurons (or, network nodes) with possibly different patterns of activity to perform multiple brain functions or represent different “thoughts” of the mind.

“How memories are made, and recalled” :: :: September 8, 2008 :: [ READ ]


The 100 billion neurons in your head have interconnected into a vastly complex network, and these connections can change and evolve as you “think” and “learn.” Exactly how this network architecture is developed and even how individual connections are selected is not yet clear.

Image from

However, researchers from the Max Planck Institute for Neurobiology have experimentally verified that neurons have an even more efficient method for quickly selecting “good” connections from “maybe-not-so-good” connections, even before the critical synapse–the chemical controller that regulates communication between neurons–is fully developed.

The discovery shows that as an extension of a neuron (either a dendrite or axon) comes into contact with another neuron, a flood of calcium ions exchanges with the pair of cells and if certain thresholds are reached, then the growing connection will stick around long enough for a synapse to form; otherwise, it will retract and wiggle about growing into another direction.

The biological growth technique is observed to be quite efficient with “decision-making” for forming connections, in particular because synapse development can take much longer to complete. Even though the following article loosely suggests that this network connection technique “enables thinking,” it’s not necessarily the case that each time we have a “thought” that we are actually making a new, physical connection. Neural “learning” likely requires an evolution in the network structure, but our notion of “thinking” is likely related more to the patterns of electrical behavior in the existing network.

This work is also quite important for the future development of neurotechnological devices. For a pure neuron device to connect directly with a human brain, it will be required to have neurons living on the implanted device to grow extensions and interconnect directly with the subject brain… so, an understanding of how these connections develop and select one another will be absolutely vital for successful devices.

So, check out the following articles, and we’ll be following the important developments.

“Efficient technique enables thinking” :: :: August 19, 2008 :: [ READ ]

“A Role for Local Calcium Signaling in Rapid Synaptic Partner Selection by Dendritic Filopodia,”Christian Lohmann and Tobias BonhoefferNeuron, Vol 59, 253-260, 31 July 2008 [ READ ABSTRACT ]


This is an update to a previous Neuron News posting reviewing a new whole brain imaging technique–called Diffusion Spectrum Imaging–that tracks the flow of water molecules through axons to map neural interconnectivity. The research group has completed the imaging on a marmoset monkey, and the full three-dimensional animation of the result is now presented online.

The map was produced from a 24-hour scan of a dissected brain with a spatial resolution of 400 microns. View the animation and look closely at all of the intricate fiber pathways and interesting network patterns that are present. The level of complexity is not close to that of a human, but the system is certainly complex enough to begin the work on detailing the network to further understand brain function.

To be clear, each visualized pathway in the map does not represent a single axonal strand. However, it corresponds to hundreds of thousands of fibers that are all networked in approximately the same direction. So, this imaging technique does not resolve the network down to each individual connection, but an averaged view of large groups of connections.

“The Brain Unmasked” :: Technology Review by MIT :: August 6, 2008 :: [ READ ]

Slide show of Monkey Brain Scanned with DSI [ VIEW ]
Video Animation of 3D Results [ VIEW ]


The brain is a network. It is not just a lump of neurons. It’s function and capabilities are entirely based on its structural characteristics as a network.

For neurotechnologies to be ultimately successful, a deep understanding of brain function will be required … in other words, to connect into the brain we must understand the brain. And, this understanding requires a complete realization of the network structure that develops from a lump of neurons.

Recently published in PLoS Biology, is exciting research using a new method of brain imaging called diffusion imaging. This method uses magnetic resonance to monitor the movement of water molecules along the neuronal axons that are interconnected throughout the brain. This level of detail of a network map in a living brain has never been achieved before, and this initial work is just a first draft of low-resolution mapping.

Already in these low-res maps, intricate and even familiar structure is being discovered … network structure that is also seen in other forms of complex networks, including the Internet. The main discovery is of a primary node that is super-connected to many other nodes located in the posterior medial and parietal cerebral cortex; i.e., the back of the head.

This is extremely critical work and very exciting. Remember, it’s all about the network structure. This author is currently reviewing the published article, and will be updating Neuron News will an additional review soon.

“First Detailed Map of the Human Cortex” :: MIT Technology Review :: July 7, 2008 :: [ READ ]

Read the PLoS Synopsis
“From Structure to Function: Mapping the Connection Matrix of the Human Brain”
Gross L
PLoS Biology Vol. 6, No. 7, e164 doi:10.1371/journal.pbio.0060164

Mapping the Structural Core of Human Cerebral Cortex
Hagmann P, Cammoun L, Gigandet X, Meuli R, Honey CJ, et al.
PLoS Biology Vol. 6, No. 7, e159 doi:10.1371/journal.pbio.0060159