Neural Connections: Memory, Learning & Inheritance

  • Thread starter Thread starter ramollari
  • Start date Start date
  • Tags Tags
    Neural
Click For Summary

Discussion Overview

The discussion revolves around the nature of neural connections related to memory and learning, specifically addressing whether the values of synaptic weights are learned throughout life or inherited, and how these weights are initialized at birth. The conversation touches on theoretical and conceptual aspects of neuroscience, synaptic plasticity, and genetic influences on neural development.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • Some participants propose that learning involves adjusting the weights of synapses, which are influenced by experiences throughout life.
  • Others argue that certain neural connections may be genetically wired, as seen in animals like spiders, suggesting an inherited component to neural structure.
  • A participant discusses the initialization of synaptic weights at birth, suggesting that infants have fully connected but unmyelinated brains, with pruning and myelination occurring during early development.
  • There is mention of ongoing debates regarding the extent of inherited neural structures versus those developed through experience, with some asserting that most values are learned.
  • One participant introduces a model of synaptic plasticity, noting that neuronal outgrowths require specific signals to form lasting synapses, and that genetic factors play a role in guiding neuronal development.
  • Another participant acknowledges the influence of drugs and neurotransmitters on brain function, indicating a recognition of the complexity of neural interactions.
  • A participant identifies themselves as a modeler focused on network connections, emphasizing a distinction between software and hardware in the context of artificial intelligence.

Areas of Agreement / Disagreement

Participants express multiple competing views regarding the balance of learned versus inherited neural connections, and the initialization of synaptic weights at birth remains a topic of uncertainty. The discussion does not reach a consensus on these points.

Contextual Notes

Participants note limitations in their understanding of specific mechanisms, such as the exact processes of synaptic plasticity and the role of nutrition and genetic code in neural development. There are also references to ongoing debates in the field regarding these topics.

Who May Find This Useful

This discussion may be of interest to those studying neuroscience, psychology, artificial intelligence, or anyone curious about the interplay between genetics and learning in neural development.

ramollari
Messages
433
Reaction score
1
Research has shown that memory and learning is based on the values of weights that the neural synapses have. Learning involves the adjustment of the weights (strengths) of these synapses so that the reactions given to stimuli are adjusted as well.

But are all the correct values learned during one's life, or are they also inherited? How are the weights initialized when a baby is born?
 
Biology news on Phys.org
I am not an expert in neural connections, but I know that a spider has certain neural connections it has had genetically "wired" into its brain. A spider web is a very complicated structure, some strands are much thicker than others etc. But anyway it seems that the answer to your question is that everyone starts off with a similar but not identical neural connections. Inheritance of "intelligence" is obvious, we as humans pass on this ability to reason. However the approaches we take to reasoning can be learned and are obiviously very different then something essential like making a spider web, and so everyone starts off with almost the same chance.
 
Last edited:
"But are all the correct values learned during one's life, or are they also inherited? How are the weights initialized when a baby is born?" values?

synapses are all about inhibition/excitation/"all or none"firing ...the weight values that you speak of is a math model refereing to [1]number of connections between two neurons...which can be many [2] amount of myelination. If a neuron is myelinated(white coating) then conductance is faster down an axon.

AT birth it is said that an infants brain is FC-fully connected and unmyelinated
and during the first 5 years of life pruning/cell death occurs to excise unused or weak synapses and myelination for those of strong firing. Pruning stops at the age of about 5 and myelination i don't know if it stops but i read that its said to be about 15 to hone ones skills...but adults can learn so i don't know if that's do to the network setup but somethings got to change for them to learn. Also note that "terrible twos" is names as so because of the constant change at a young age and its really cool that if you damgage your visual system or audition at a young age that the other area can grow or adapt to handle some processes of the damage neural substrates.

SO
"But are all the correct values learned during one's life or inherited" the majority of them are learned or experienced...I can't quote on inheritance because its an ongoing debate...there may be some neural structures that are geneticallly wired but for the most its grown. Food is argued to influence the brain.

"How are the weights initialized when a baby is born?" should be requestioned to say how are they reconnected...and well this all starts when the brain is not even a brain.
But nutrition probably has a lot to do with it. Genetic Code also prolly says hook up these neurons to these for the time being.
 
What you're referring to (I think) is one model of how synaptic plasticity occurs (it's not the only one, and right now, it's still just a hypothetical model, not a known fact). I haven't looked into this in depth, though we've somewhat recently hired on someone who works in this field, so I've attended his seminars as well as those of other candidates working in that area. Anyway, my understanding is that neurons are spontaneously (? - there'd be some argument if it's spontaneous or directed) producing outgrowths (spines) all the time, but the right signals (again, vague here...complementary transmitters and receptors or surface adhesion molecules) have to be present for that outgrowth to form a bona fide synapse. If there is strong signalling at that synapse, it is reinforced and more likely to become long-lasting, but if it is only weak, or weaker than other nearby synapses, the neuronal outgrowth retracts.

Of course, during development, some of this has to be genetically determined. For example, neural adhesion molecules provide paths for neurons to follow as they migrate into their adult locations. There are developmental stages during which some molecules are turned on or off that help guide different stages of neuronal development.

Much of the "weighting" your talking about, as I've heard it, refers more to after the neurons are in position and there is juxtapositioning of axons and dendrites. Once the major structural components are in place, the neurite outgrowth is where most adult synaptic plasticity takes place.

While my area of research is not in learning/memory, I am interested in neuronal remodeling/synaptic plasticity in a different context. So, I'll likely return to this discussion later with a little better explanations. I'm just posting quickly while gulping down coffee before heading back into the lab, hence the rather vague, incomplete, and not fully thought out explanation above. (Okay, I'm just posting so you'll stick around to continue the discussion later. :biggrin:)
 
ah yes being a modeller i tend to forget the drugs/neurotransmitters influence on the brain.
 
neurocomp2003 said:
ah yes being a modeller i tend to forget the drugs/neurotransmitters influence on the brain.
:rolleyes: What exactly are you modeling then? :biggrin:
 
mmmmm the network connections =] the software not the hardware I'm a strong AI supporter
 

Similar threads

  • · Replies 1 ·
Replies
1
Views
3K
  • · Replies 16 ·
Replies
16
Views
4K
  • · Replies 8 ·
Replies
8
Views
5K
Replies
9
Views
5K
  • · Replies 8 ·
Replies
8
Views
5K
  • · Replies 43 ·
2
Replies
43
Views
8K
  • · Replies 0 ·
Replies
0
Views
2K
  • · Replies 2 ·
Replies
2
Views
4K
  • · Replies 2 ·
Replies
2
Views
5K
  • · Replies 4 ·
Replies
4
Views
5K