Tag Archives: brain

Algorithm brings whole-brain simulation within reach

An improvement to the Neural Simulation Tool (NEST) algorithm, the primary tool of the Human Brain Project, expanded the scope of brain neural data management (for simulations) from the current 1% of discrete neurons (about the number in the cerebellum) to 10%. The NEST algorithm can scale to store 100% of BCI-derived or simulated neural data within near-term reach as supercomputing capacity increases. The algorithm achieves its massive efficiency boost by eliminating the need to explicitly store as much data about each neuron’s state.

Abstract of Extremely Scalable Spiking Neuronal Network Simulation Code: From Laptops to Exascale Computers

State-of-the-art software tools for neuronal network simulations scale to the largest computing systems available today and enable investigations of large-scale networks of up to 10 % of the human cortex at a resolution of individual neurons and synapses. Due to an upper limit on the number of incoming connections of a single neuron, network connectivity becomes extremely sparse at this scale. To manage computational costs, simulation software ultimately targeting the brain scale needs to fully exploit this sparsity. Here we present a two-tier connection infrastructure and a framework for directed communication among compute nodes accounting for the sparsity of brain-scale networks. We demonstrate the feasibility of this approach by implementing the technology in the NEST simulation code and we investigate its performance in different scaling scenarios of typical network simulations. Our results show that the new data structures and communication scheme prepare the simulation kernel for post-petascale high-performance computing facilities without sacrificing performance in smaller systems.

Source: http://www.kurzweilai.net/new-algorithm-will-allow-for-simulating-neural-connections-of-entire-brain-on-future-exascale-supercomputers

Next discussion meeting Apr 2: Brain-Computer Interface, now and future

During our next discussion meeting, we’ll explore the status, future potential, and human implications of neuroprostheses–particularly brain-computer interfaces. If you are local to Albuquerque, check our Meetup announcement to join or RSVP. The announcement text follows.

Focal questions

What are neuroprostheses? How are they used now and what may the future hold for technology-enhanced sensation, motor control, communications, cognition, and other human processes?

Resources (please review before the meeting)

Primary resources
• New Brain-Computer Interface Technology (video, 18 m)
• Imagining the Future: The Transformation of Humanity (video, 19 m)
• The Berlin Brain-Computer Interface: Progress Beyond Communication and Control (research article, access with a free Frontiers account)
• The Elephant in the Mirror: Bridging the Brain’s Explanatory Gap of Consciousness (research article)

Other resources (recommend your own in the comments!)

• DARPA implant (planned) with up to 1 million neural connections (short article)

Extra Challenge: As you review the resources, think of possible implications from the perspectives of the other topics we’ve recently discussed:
• the dilemma of so much of human opinion and action deriving from non-conscious sources
• questions surrounding what it means to ‘be human’ and what values we place on our notions of humanness (e.g., individuality and social participation, privacy, ‘self-determination’ (or the illusion thereof), organic versus technologically enhanced cognition, etc.)

Does quantum mechanics play a role in consciousness

A 2017 BBC article concisely reviews essential concepts of quantum physics and summarizes the state of scientific speculation into the possible interactions of consciousness and quantum mechanics. Of interest are some specific, possibly testable, suggestions about chemical structures that could sustain nuclear spin entanglements in the brain for up to two days.

Sex differences in the gut-microbiome-brain axis


In recent years, the bidirectional communication between the gut microbiome and the brain has emerged as a factor that influences immunity, metabolism, neurodevelopment and behaviour. Cross-talk between the gut and brain begins early in life immediately following the transition from a sterile in utero environment to one that is exposed to a changing and complex microbial milieu over a lifetime. Once established, communication between the gut and brain integrates information from the autonomic and enteric nervous systems, neuroendocrine and neuroimmune signals, and peripheral immune and metabolic signals. Importantly, the composition and functional potential of the gut microbiome undergoes many transitions that parallel dynamic periods of brain development and maturation for which distinct sex differences have been identified. Here, we discuss the sexually dimorphic development, maturation and maintenance of the gut microbiome–brain axis, and the sex differences therein important in disease risk and resilience throughout the lifespan.


Giant neuron found encircling and intraconnecting mouse brain

A neuron that encircles the mouse brain emanates from the claustrum (an on/off switch for awareness) and has dense links with both brain hemispheres. Scientists including Francis Crick and Christoph Koch have speculated that the claustrum may play a role in enabling conscious thought.


https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1569501/ (Crick and Koch academic article)

We’ve frequently discussed how self-aware consciousness likely arises not from any single brain structure or signal, but from complex, recursive (reentrant), synchronized signaling among many structures organized into functional regions. (Did I get close to accurate there?) That a giant neuron provides another connection path among such regions can be taken to align with the reentrant signaling and coordination view of consciousness (ala Edelman and Tononi).

Computer metaphor not accurate for brain’s embodied cognition

It’s common for brain functions to be described in terms of digital computing, but this metaphor does not hold up in brain research. Unlike computers, in which hardware and software are separate, organic brains’ structures embody memories and brain functions. Form and function are entangled.

Rather than finding brains to work like computers, we are beginning to design computers–artificial intelligence systems–to work more like brains. 


Brain’s facial-recognition mechanism revealed

Caltech researchers have identified the brain mechanisms that enable primates to quickly identify specific faces. In a feat of efficiency, surprisingly few feature-recognition neurons are involved in a process that may be able to distinguish among billions of faces. Each neuron in the facial-recognition system specializes in noticing one feature, such as the width of the part in the observed person’s hair. If the person is bald or has no part, the part-width-recognizing neuron remains silent. A small number of such specialized-recognizer neurons feed their inputs to other layers (patches) that integrate a higher-level pattern (e.g., hair pattern), and these integrate at yet higher levels until there is a total face pattern. This process occurs nearly instantaneously and works regardless of the view angle (as long as some facial features are visible). Also, by cataloging which neurons perform which functions and then mapping these to a relatively small set of composite faces, researchers were able to tell which face a macaque (monkey) was looking at.

These findings seem to correlate closely with Ray Kurzweil’s (Google’s Chief Technology Officer) pattern-recognition theory of mind.

Scientific American article

BMCAI library file (site members only)

Mathematical field of topology reveals importance of ‘holes in brain’

New Scientist article: Applying the mathematical field of topology to brain science suggests gaps in densely connected brain regions serve essential cognitive functions. Newly discovered densely connected neural groups are characterized by a gap in the center, with one edge of the ring (cycle) being very thin. It’s speculated that this architecture evolved to enable the brain to better time and sequence the integration of information from different functional areas into a coherent pattern.

Aspects of the findings appear to support Edelman’s and Tononi’s (2000, p. 83) theory of neuronal group selection (TNGS, aka neural Darwinism).

Edelman, G.M. and Tononi, G. (2000). A Universe of Consciousness: How Matter Becomes Imagination. Basic Books.