adding page right after watching ben goertzel‘s singularity doc and then teds neurosci of imagination video [and a slew of other docs.. about music and mind and instinct.. and forbidden cures and body.. and sicko ness of society and….].. and at same time as neural networks
Neuroscience is the scientific study of the nervous system. Traditionally, neuroscience is recognized as a branch of biology. However, it is
currently an interdisciplinary science that collaborates with other fields such as chemistry, cognitive science, computer science, engineering, linguistics, mathematics, medicine (including neurology), genetics, and allied disciplines including philosophy, physics, and psychology.
It also exerts influence on other fields, such as neuroeducation, neuroethics, and neurolaw.
The term neurobiology is often used interchangeably with the term neuroscience, although the former refers specifically to the biology of the nervous system, whereas the latter refers to the entire science of the nervous system, including elements of psychology as well as the purely physical sciences.
The scope of neuroscience has broadened to include different approaches used to study the molecular, cellular, developmental, structural, functional, evolutionary, computational, and medical aspects of the nervous system. The techniques used by neuroscientists have also expanded enormously, from molecular and cellular studies of individual nerve cells to imaging of sensory and motor tasks in the brain. Recent theoretical advances in neuroscience have also been aided by the study of neural networks.
Neural networks (also referred to as connectionist systems) are a computational approach which is based on a large collection of neural units loosely modeling the way a biological brain solves problems with large clusters of biological neurons connected by axons. Each neural unit is connected with many others, and links can be enforcing or inhibitory in their effect on the activation state of connected neural units. Each individual neural unit may have a summation function which combines the values of all its inputs together. There may be a threshold function or limiting function on each connection and on the unit itself such that it must surpass it before it can propagate to other neurons. These systems are self-learning and trained rather than explicitly programmed and excel in areas where the solution or feature detection is difficult to express in a traditional computer program.
The goal of the neural network is to solve problems in the same way that the human brain would, although several neural networks are much more abstract.
Neural networks and neuroscience
Theoretical and computational neuroscience is the field concerned with the theoretical analysis and the computational modeling of biological neural systems. Since neural systems are intimately related to cognitive processes and behavior, the field is closely related to cognitive and behavioral modeling.
The aim of the field is to create models of biological neural systems in order to understand how biological systems work. To gain this understanding, neuroscientists strive to make a link between observed biological processes (data), biologically plausible mechanisms for neural processing and learning (biological neural network models) and theory (statistical learning theory and information theory).
Types of models
Many models are used in the field, defined at different levels of abstraction and modeling different aspects of neural systems. They range from models of the short-term behavior of individual neurons (e.g.), models of how the dynamics of neural circuitry arise from interactions between individual neurons and finally to models of how behavior can arise from abstract neural modules that represent complete subsystems. These include models of the long-term, and short-term plasticity, of neural systems and their relations to learning and memory from the individual neuron to the system level.
Networks with memory
Integrating external memory components with artificial neural networks has a long history dating back to early research in distributed representations and self-organizing maps. E.g. in sparse distributed memory the patterns encoded by neural networks are used as memory addresses for content-addressable memory, with “neurons” essentially serving as address encoders and decoders.
More recently deep learning was shown to be useful in semantic hashing where a deep graphical model of the word-count vectors is obtained from a large set of documents. Documents are mapped to memory addresses in such a way that semantically similar documents are located at nearby addresses. Documents similar to a query document can then be found by simply accessing all the addresses that differ by only a few bits from the address of the query document.
Memory Networks is another extension to neural networks incorporating long-term memory which was developed by Facebook research. The long-term memory can be read and written to, with the goal of using it for prediction. These models have been applied in the context of question answering (QA) where the long-term memory effectively acts as a (dynamic) knowledge base, and the output is a textual response.
Neural Turing Machines developed by Google DeepMind extend the capabilities of deep neural networks by coupling them to external memory resources, which they can interact with by attentional processes. The combined system is analogous to a Turing Machine but is differentiable end-to-end, allowing it to be efficiently trained with gradient descent. Preliminary results demonstrate that Neural Turing Machines can infer simple algorithms such as copying, sorting, and associative recall from input and output examples.
Differentiable neural computers (DNC) are an extension of Neural Turing Machines, also from DeepMind. They have out-performed Neural turing machines, Long short-term memory systems and memory networks on sequence-processing tasks.
back to neuroscience
As a result of the increasing number of scientists who study the nervous system, several prominent neuroscience organizations have been formed to provide a forum to all neuroscientists and educators. For example, the International Brain Research Organization was founded in 1960, the International Society for Neurochemistry in 1963, the European Brain and Behaviour Society in 1968, and the Society for Neuroscience in 1969.
networked individualism et al
infographic of neuroplasticity
Just like the Universe, our brains might be programmed to maximise disorder – similar to the principle of entropy – and our consciousness could simply be a side effect.[..]
what if consciousness is a side effect of our brain moving towards a state of entropy?
Entropy is basically the term used to describe the progression of a system from order to disorder. Picture an egg: when it’s all perfectly separated into yolk and white, it has low entropy, but when you scramble it, it has high entropy – it’s the most disordered it can be.
the participants’ brains displayed higher entropy when in a fully conscious state.
This lead the researchers to argue that consciousness could simply be an “emergent property” of a system that’s trying to maximise information exchange.
i have this somewhere else to.. but can’t find it.. shared today by Jason on fb – living normally w 90% damage to brain
In the past, researchers have suggested that consciousness might be linked to various specific brain regions – such as the claustrum, a thin sheet of neurons running between major brain regions, or the visual cortex.
But if those hypotheses were correct, then the French man shouldn’t be conscious, with the majority of his brain damaged.
Cleeremans has instead come up with a hypothesis that’s based on the brain learning consciousness over and over again, rather than being born with it. Which means its location can be flexible and learnt by different brain regions.
“Consciousness is the brain’s non-conceptual theory about itself, gained through experience – that is learning, interacting with itself, the world, and with other people,” he explains.
He calls his hypothesis the ‘radical plasticity thesis‘, and it fits in pretty well with recent research that suggests the adult brain is more adaptable than we previously thought – and capable of taking on new roles in case of injury.
Cleeremans claims that the brain is continually and unconsciously learning to re-describe its own activity to itself, and these descriptions form the basis of conscious experience.”
According to Cleeremans, even though his remaining brain was only tiny, the neurons left over were able to still generate a theory about themselves, which means the man remained conscious of his actions
Update 3 Jan 2017: This man has a specific type of hydrocephalus known as chronic non-communicating hydrocephalus, which is where fluid slowly builds up in the brain. Rather than 90 percent of this man’s brain being missing, it’s more likely that it’s simply been compressed into the thin layer you can see in the images above. We’ve corrected the story to reflect this.
2015 (?) – Neuroscience Confirms Your Subconscious Shapes Your Reality
Time, for example, is supposed to be an objective measurement, but we experience it subjectively.
4 rituals that will make you happy based on neuroscience
1\ ask.. what am i grateful for (just the asking/seeking helps)
2\ label negative feelings
3\ make a decision (voluntary ness matters.. not 100% right ness)
4\ touch (touching someone you love actually reduces pain – handholding.. exp: 5 long hugs a day for 4 wks)
Will Hall (@willhall) tweeted at 6:40 PM on Tue, Jun 13, 2017:
A Traumatic Experience Can Reshape Your Microbiome https://t.co/Bla1cfx1IV via @thescienceofus