Here at New York Times:
Scientists have puzzled out profoundly important insights about how the brain works, like the way the mammalian brain navigates and remembers places, work that won the 2014 Nobel Prize in Physiology or Medicine for a British-American and two Norwegians.
Yet the growing body of data — maps, atlases and so-called connectomes that show linkages between cells and regions of the brain — represents a paradox of progress, with the advances also highlighting great gaps in understanding.
Larry Abbott, at Columbia University, has helped develop theoretical models of how perception works in weakly electric fish.
So many large and small questions remain unanswered. How is information encoded and transferred from cell to cell or from network to network of cells? Science found a genetic code but there is no brain-wide neural code; no electrical or chemical alphabet exists that can be recombined to say “red” or “fear” or “wink” or “run.” And no one knows whether information is encoded differently in various parts of the brain. More.
Sounds like, as long as there is funding, they’ll never want for work.
Hat tip: Stephanie West Allen at Brains on Purpose
The big data challenges of connectomics
doi:10.1038/nn.3837
The structure of the nervous system is extraordinarily complicated because individual neurons are interconnected to hundreds or even thousands of other cells in networks that can extend over large volumes.
Mapping such networks at the level of synaptic connections, a field called connectomics, began in the 1970s with a the study of the small nervous system of a worm and has recently garnered general interest thanks to technical and computational advances that automate the collection of electron-microscopy data and offer the possibility of mapping even large mammalian brains.
However, modern connectomics produces ‘big data’, unprecedented quantities of digital information at unprecedented rates, and will require, as with genomics at the time, breakthrough algorithmic and computational solutions.
http://www.uncommondescent.com.....ent-529114
Focus on big data
doi:10.1038/nn.3856
The number of big data projects in neuroscience, such as the BRAIN initiative in the United States or the Human Brain Mapping initiative in Europe, has been increasing in recent years.
Will such big data efforts become the modus operandi in neuroscience, replacing smaller scale, hypothesis-driven science?
How much insight will be gained from such projects?
What are the best ways to go about conducting such projects and sharing the data that they produce?
http://www.nature.com/neuro/jo......3856.html
We ain’t seen nothing yet. 🙂
While many of us want to see the huge gaps in biological science shrinking ASAP, apparently some old-guard folks out there might prefer those gaps to remain. Why?
Hopefully that’s not the case in neuroscience. 🙂
That is the main problem facing the AI research community. The only way to design a truly intelligent machine is to copy what the brain does. Unfortunately, the brain is not giving away its secrets just for the asking. Even if we had a complete and accurate connectome of the brain, we would not be the better for it. It would still take researchers hundreds, if not thousands of years to figure out how it works.
True AI is indeed coming to the world and it is coming much sooner than most people expect. However, it will come from neither academia nor industry.
Holy Smokes! We had better get busy and figure all of this stuff out. We only have 10 to 15 years before the singularity begins.
Here is the latest from Elon Musk, the CEO of Tesla and CTO of SpaceX, the man who, not too long ago, declared that AI research is “like summoning the demon.” Now Musk is saying the threat is closer than we think (although I seriously doubt anybody has anything close to working like the brain). He posted a comment at Edge.org and immediately deleted it but not before others copied it.
The risk of something seriously dangerous happening is in the five year timeframe. 10 years at most.
Rather than making the bacterial flagellum the subject of debate on ID, isn’t the brain a far better example?
I guess the fact that we don’t understand it very well makes it difficult to write about clearly and use it as an example, but the flagellum is nothing compared to the brain!
Perhaps the fact that low life forms do not have a brain like ours is also a factor, but just how did organisms with little to no brain turn into humans?
How in the world do chemicals turn into consciousness?
How did the wiring to the brain coincide with the evolution of the new organs?
Where did the information come from for the software that controls the new bodily systems, organs, abilities, reflexes, etc.?
“I’m sure one day science will figure it all out some day”
This statement of belief represents the faith of atheists in science, their worldview, and their understanding of life.
There just are no guarantees! In this realm, we both need to have faith!
I don’t think these nobel winners did anything other then fool around with a road system. They didn’t figure anything out. jUst that stuff is moving around.
why not just say the encoding is simple memory operation.
not so simple but its just memory road system.
we are a hugh memory machine and not a brain with a memory partner.
encoding is just memorization at a molecular level.
why not just a simple idea of a soul meshed to a memory machine.?
no mystery.
Elon Musk:
as to:
The material brain does not, and can not ever, ‘perceive’ anything. The hard problem’ of consciousness proves this:
a bit more in-depth look at the ‘hard problem’ is here:
Moreover, Abbott’s very ‘tools’, computers and equations, prove that the ‘hard problem’ of consciousness will never be solved by computers and equations.
Alan Turing, who was at the forefront in inventing computers, infamously thought that his brain was merely a ‘Turing Machine’. This following poem humorously teases the ‘I’m merely a machine’ notion of Turing
Yet, in spite of Turing’s irrational belief that he was merely a machine, and although I don’t believe Turing ever actually admitted it, Alan Turing actually succeeded in extending Godel’s incompleteness theorem to material computers, and in doing so, thus undermining his own materialistic belief that he was merely a machine in the process. This point is illustrated in the following video and quote:
And since ‘“an infinite number of true mathematical theorems exist that cannot be proved from any finite system of axioms.”,,,
Then computers, and the notion that we are merely turing machines, by default, will never be able explain the mathematical intuition of humans. Godel himself put the situation like this:
In fact, 6 months ago this challenge was issued to materialists who believe they are merely a turing machine,
Of related note, deep mathematical insight that leads to a physical discovery is said to be guided by a sense of ‘mathematical beauty’:
Yet ‘beauty’ is an argument for theism, and is not an argujment for materialism:
Although the following article is somewhat technical, it is almost comical to read how every approach, in which the materialists tried to reduce the subjective sense of beauty to a mere material mechanism, was thwarted.
Why computers will never have genuine mathematical insight is summed up nicely by Dr. Berlinski in the following interview:
Of related note, the following paper gives the ‘secret’ away for mathematically defeating the infamous ‘Turing test’ in a fairly simple manner:
designed to serve specific functions. ?
Illuminating the Multifaceted Roles of Neurotransmission in Shaping Neuronal Circuitry
Across the nervous system, neurons form highly stereotypic patterns of synaptic connections that are designed to serve specific functions.
Mature wiring patterns are often attained upon the refinement of early, less precise connectivity.
Much work has led to the prevailing view that many developing circuits are sculpted by activity-dependent competition among converging afferents, which results in the elimination of unwanted synapses and the maintenance and strengthening of desired connections.
Studies of the vertebrate retina, however, have recently revealed that activity can play a role in shaping developing circuits without engaging competition among converging inputs that differ in their activity levels.
Such neurotransmission-mediated processes can produce stereotypic wiring patterns by promoting selective synapse formation rather than elimination. [how?]
We discuss how the influence of transmission may also be limited by circuit design and further highlight the importance of transmission beyond development in maintaining wiring specificity and synaptic organization of neural circuits.
DOI: http://dx.doi.org/10.1016/j.neuron.2014.08.029
#16 follow-up
Say what?
Beauty does not exist. its simply a awareness of accuracy. or symmetry.
so our perceiving of beauty is just perceiving accuracy.
I’m not sure its a case against materialism.
Mind, Powered
Neuroscientist Eric Leuthardt talks about the science and technology behind brain-computer interfaces.
http://www.youtube.com/watch?v=T3UxUVcgI-Y
Brain Region Mapping Using Global Metabolomics
DOI: http://dx.doi.org/10.1016/j.chembiol.2014.09.016
Historically, studies of brain metabolism have been based on targeted analyses of a limited number of metabolites.
Here we present an untargeted mass spectrometry-based metabolomic strategy that has successfully uncovered differences in a broad array of metabolites across anatomical regions of the mouse brain.
The NSG immunodeficient mouse model was chosen because of its ability to undergo humanization leading to numerous applications in oncology and infectious disease research.
Metabolic phenotyping by hydrophilic interaction liquid chromatography and nanostructure imaging mass spectrometry revealed both water-soluble and lipid metabolite patterns across brain regions.
Neurochemical differences in metabolic phenotypes were mainly defined by various phospholipids and several intriguing metabolites including carnosine, cholesterol sulfate, lipoamino acids, uric acid, and sialic acid, whose physiological roles in brain metabolism are poorly understood.
This study helps define regional homeostasis for the normal mouse brain to give context to the reaction to pathological events.
Rhythmic Rewiring
Circadian neurons in fruit flies form synapses with different, noncircadian brain regions depending on the time of day.
http://www.the-scientist.com//.....-Rewiring/
Brain Structure Rediscovered
First described in the late 19th century, then lost from the literature for more than 100 years, the vertical occipital fasciculus appears to be important in visual processing.
“There has to be some way for that dichotomy to merge,” Massachusetts General Hospital and Harvard Medical School’s Jeremy Schmahmann, who was not involved in the new research, told Discovery News, “and the [VOF] is one way for the ‘where’ and the ‘what’ streams in the visual modality to become a unified whole.”
The study also revealed that the VOF is myelinated differently than other regions of the brain, Yeatman noted. “We don’t know what it means yet, but [the myelination differences are] very consistent across every subject,” he told Discovery. “It opens up some new hypotheses, new directions to study: Why is this structure so different than the other neighboring pathways?”
http://www.the-scientist.com//.....iscovered/
Neuroprosthetics
Linking the human nervous system to computers is providing unprecedented control of artificial limbs and restoring lost sensory function.
http://www.the-scientist.com//.....osthetics/
Probing Starling Sleep
Birds may provide a new animal model for memory consolidation during sleep, according to research presented at the Society for Neuroscience meeting this week.
http://www.the-scientist.com//.....ing-Sleep/
Neurons Regenerate in Rat Spinal Cord
Researchers at the University of California, San Diego, demonstrate that neural progenitor cells grafted into injured rat spinal cords can grow long axons and connect to host neurons.
http://www.the-scientist.com//.....inal-Cord/
Maternal Inflammation Impacts Offspring
A mom’s stress could lead to changes in her offspring’s brains that can affect the physiology and behavior of the young, researchers report at the Society for Neuroscience annual meeting.
http://www.the-scientist.com//.....Offspring/
Unwinding the Mysteries of the Cellular Clock
http://www.biosciencetechnolog.....cation=top
Imagination, reality flow in opposite directions in the brain
As real as that daydream may seem, its path through your brain runs opposite reality.
“A really important problem in brain research is understanding how different parts of the brain are functionally connected. What areas are interacting? What is the direction of communication?” says Barry Van Veen, a UW-Madison professor of electrical and computer engineering. “We know that the brain does not function as a set of independent areas, but as a network of specialized areas that collaborate.”
“There seems to be a lot in our brains and animal brains that is directional, that neural signals move in a particular direction, then stop, and start somewhere else,” says. “I think this is really a new theme that had not been explored.”
http://medicalxpress.com/news/.....tml#ajTabs
Transiently Increasing cAMP Levels Selectively in Hippocampal Excitatory Neurons during Sleep Deprivation Prevents Memory Deficits Caused by Sleep Loss
doi: 10.1523/JNEUROSCI.2403-14.2014
The hippocampus is particularly sensitive to sleep loss. Although previous work has indicated that sleep deprivation impairs hippocampal cAMP signaling, it remains to be determined whether the cognitive deficits associated with sleep deprivation are caused by attenuated cAMP signaling in the hippocampus.
Further, it is unclear which cell types are responsible for the memory impairments associated with sleep deprivation.
Transgenic approaches lack the spatial resolution to manipulate specific signaling pathways selectively in the hippocampus, while pharmacological strategies are limited in terms of cell-type specificity.
Therefore, we used a pharmacogenetic approach based on a virus-mediated expression of a G?s-coupled Drosophila octopamine receptor selectively in mouse hippocampal excitatory neurons in vivo.
With this approach, a systemic injection with the receptor ligand octopamine leads to increased cAMP levels in this specific set of hippocampal neurons. We assessed whether transiently increasing cAMP levels during sleep deprivation prevents memory consolidation deficits associated with sleep loss in an object–location task.
Five hours of total sleep deprivation directly following training impaired the formation of object–location memories.
Transiently increasing cAMP levels in hippocampal neurons during the course of sleep deprivation prevented these memory consolidation deficits.
These findings demonstrate that attenuated cAMP signaling in hippocampal excitatory neurons is a critical component underlying the memory deficits in hippocampus-dependent learning tasks associated with sleep deprivation.
http://www.jneurosci.org/content/34/47/15715
Laminar activity in the hippocampus and entorhinal cortex related to novelty and episodic encoding
doi:10.1038/ncomms6547
The ability to form long-term memories for novel events depends on information processing within the hippocampus (HC) and entorhinal cortex (EC).
The HC–EC circuitry shows a quantitative segregation of anatomical directionality into different neuronal layers.
Whereas superficial EC layers mainly project to dentate gyrus (DG), CA3 and apical CA1 layers, HC output is primarily sent from pyramidal CA1 layers and subiculum to deep EC layers.
Here we utilize this directionality information by measuring encoding activity within HC/EC subregions with 7?T high resolution functional magnetic resonance imaging (fMRI).
Multivariate Bayes decoding within HC/EC subregions shows that processing of novel information most strongly engages the input structures (superficial EC and DG/CA2–3), whereas subsequent memory is more dependent on activation of output regions (deep EC and pyramidal CA1).
This suggests that while novelty processing is strongly related to HC–EC input pathways, the memory fate of a novel stimulus depends more on HC–EC output.
http://www.nature.com/ncomms/2.....s6547.html
#30 addendum
‘Bat-nav’ system enables three-dimensional maneuvers
Study reveals surprising neural code based on bagel-shaped coordinate system.
doi:10.1038/nature.2014.16475
The brains of bats have a neuronal ‘compass’ that enables them to navigate in three dimensions
http://www.nature.com/news/bat.....es-1.16475
Neuroscience: A three-dimensional neural compass
doi:10.1038/nature14076
The discovery that the neural navigation system of the mammalian brain acts in three dimensions sheds light on how mammals orient themselves in complex environments.
http://www.nature.com/nature/j.....e14076.pdf
Three-dimensional head-direction coding in the bat brain
doi:10.1038/nature14031
Navigation requires a sense of direction (‘compass’), which in mammals is thought to be provided by head-direction cells, neurons that discharge when the animal’s head points to a specific azimuth.
However, it remains unclear whether a three-dimensional (3D) compass exists in the brain.
Here we conducted neural recordings in bats, mammals well-adapted to 3D spatial behaviours, and found head-direction cells tuned to azimuth, pitch or roll, or to conjunctive combinations of 3D angles, in both crawling and flying bats.
Head-direction cells were organized along a functional–anatomical gradient in the presubiculum, transitioning from 2D to 3D representations.
In inverted bats, the azimuth-tuning of neurons shifted by 180°, suggesting that 3D head direction is represented in azimuth × pitch toroidal coordinates.
Consistent with our toroidal model, pitch-cell tuning was unimodal, circular, and continuous within the available 360° of pitch.
Taken together, these results demonstrate a 3D head-direction mechanism in mammals, which could support navigation in 3D space.
http://www.nature.com/nature/j.....affil-auth
Brain training with non-action video games enhances aspects of cognition
doi: 10.3389/fnagi.2014.00277
Age-related cognitive and brain declines can result in functional deterioration in many cognitive domains, dependency, and dementia.
A major goal of aging research is to investigate methods that help to maintain brain health, cognition, independent living and wellbeing in older adults.
This randomized controlled study investigated the effects of 20 1-h non-action video game training sessions with games selected from a commercially available package (Lumosity) on a series of age-declined cognitive functions and subjective wellbeing.
Two groups of healthy older adults participated in the study, the experimental group who received the training and the control group who attended three meetings with the research team along the study.
Groups were similar at baseline on demographics, vocabulary, global cognition, and depression status.
All participants were assessed individually before and after the intervention, or a similar period of time, using neuropsychological tests and laboratory tasks to investigate possible transfer effects.
The results showed significant improvements in the trained group, and no variation in the control group, in processing speed (choice reaction time), attention (reduction of distraction and increase of alertness), immediate and delayed visual recognition memory, as well as a trend to improve in Affection and Assertivity, two dimensions of the Wellbeing Scale.
Visuospatial working memory (WM) and executive control (shifting strategy) did not improve.
Overall, the current results support the idea that training healthy older adults with non-action video games will enhance some cognitive abilities but not others.
http://journal.frontiersin.org.....7/abstract
The title issue may have been addressed in this paper, but a number of ‘how’ and ‘why’ questions remain in the details. Work in progress. Just open the link and see how many ‘how’ and ‘why’ questions one could ask about every detail.
From a software development perspective, no procedural questions can be left unanswered.
A genuine layer 4 in motor cortex with prototypical synaptic circuit connectivity
DOI: http://dx.doi.org/10.7554/eLife.05422
The motor cortex (M1) is classically considered an agranular area, lacking a distinct layer 4 (L4).
Our findings therefore identify pyramidal neurons in M1 with the expected prototypical circuit properties of excitatory L4 neurons, and question the traditional assumption that motor cortex lacks this layer.
question the traditional assumption ?
What else is new? 🙂
More breakthrough discoveries about the brain:
https://www.youtube.com/embed/1qR2IsUnSrw
This raises new “why, how, when” questions.
‘Complex network theory and the brain’
http://rstb.royalsocietypublis.....3/20130520
More articles on this subject:
http://rstb.royalsocietypublis.....9/1653.toc
We ain’t seen nothing yet… can’t wait to see what is going to be revealed to these new technology.
“Across the diversity of cortical cell types, transcription factors formed a complex, layered regulatory code, suggesting a mechanism for the maintenance of adult cell type identity.”
http://www.uncommondescent.com.....ent-549467