final neural circuits: networks

emergent property

networks of neurons can do things that individual neurons cannot

divergence

An incoming fiber triggers responses in ever-increasing numbers of neurons farther and farther along in the circuit. They are amplifying circuits that can occur along single or several pathways.

convergence

The pool receives inputs from several presynaptic neurons, and the circuit has a funneling or concentrating effect, allowing for spatio-temporal summation at the target neuron.

serial processing

refers to the sequential flow of information through a system, where one operation is completed before the next one begins. The neurons relay signals in a linear fashion from one neuron to the next.

parallel processing

the simultaneous transmission of information through multiple pathways or the concurrent activation of multiple neural elements.

reverberation

Also known as oscillating are incoming signal travels through a chain of neurons, each of which makes collateral synapses with neurons in a previous part of the pathway. They are involved in the control of rhythmic activities such as sleep-wake cycle, breahing, and certain motor activities (walking).

feedforward excitation

allows one neuron to relay information to its neighbor. long chains of these can be used to propagate information through the nervous system.

feedfoward inhibition

a presynaptic cell excites an inhibitory interneuron and that inhibitory interneuron then inhibits the next follower cell. this is a way of shitting down or limiting excitation in a downstream neuron in a neural circuits.

lateral inhibition

A presynaptic cell excites inhibitory interneurons, and they inhibit neighboring cells in the network. This type of circuit can be used in the sensory system to provide edge enhancement.

feedback/recurrent inhibition

a presynaptic cell connects to a postsynaptic cell, and the postsynaptic cell, in turn, connects to an interneuron, which then inhibits the presynaptic cell. This can limit excitation.

feedback/recurrent excitation

A presynaptic neuron excites a postsynaptic neuron, and that postsynaptic neuron excites the presynaptic neuron. This type of circuit can serve a switch-like function because once the presynaptic cell is activated, that activation could be perpetuated.

disinhibition

Inhibitory neurons suppress the activity of other inhibitory neurons, leading to the excitation or activation of downstream neurons. This allows for the selective amplification of an excitatory pathway.

what causes the hermann grid and the mmach bands?

These are optical illusions that are caused by lateral inhibition.

How does lateral inhibition affect sensory perception>

it disables the spreading of action potentials from excited neurons to neighboring neurons in the lateral direction. this contrast allows for increased sensory perception.

What is a reflex arc?

a neural pathway that controls a reflex action. In higher animals, most sensory neurons do not pass directly into the brain but synapse in the spinal cord.

How does the synapse being in the spinal cord beneficial for higher animals?

It allows reflex actions to occur relatively quickly by activating spinal motor neurons without the delay of routing signals throughout the brain, although the brain will receive sensory input while the reflex is carried out.

Patellar reflex

its initiated when the patellar dendon is tapped below the knee. the tap initiates an action potential in a specialized structure known as a muscle spindle located within the quadriceps.

What does the sensory input from quadriceps activate?

local interneurons that release the inhibitory neurotransmitter glycine onto motor neurons of antagonist muscles. blocking. the innervation of anagonistic (hamstring) muscles.

vestibulo-ocular reflex

a reflex where activation of the vestibular system causes eye movement. the reflex functions to stabilize images on the retinas during head movement by producing eye movements in the direction opposite to head movement.

how does your head know it is moving?

The stereocilia of the hair cells bend depending on the movement of fluid within the semicircular canals. if your head turns one direction, the fluid moves in the other and vice versa.

central pattern generators

neuronal circuits that produce rhythmic patterns of neural motor output activity without sensory or other inputs carrying timing information

neuromechanical tuning

Well-predicted movements, CPG-generated phase durations, and muscle forces closely match those required by the evolving biomechanical events, minimizing the sensory corrections required.

law of Neural Habit

when two elementry brain processes have been active together or in immediate succession, one of them, re-occurring, tends to propagate its excitement into the other.

hebbian theory

its concerned about how neurons and networks of neurons might connect themselves into a cell assembly to become engrams.

Hebbs learning rule

sets conditions that when met, the strength of synaptic transmission is enhanced.

Hebbian synapes

it provides an algorithm to update the weights of the connections. It provides a simplistic physiology-based model to mimic the activity-dependent features of synaptic plasticity.

What triggers long term potentiation (LTP)?

the activation of presynaptic and postsynaptic firing producing a large increase in postsynaptic calcium.

When does long term depression (LTD)?

when the strength and/or timing of presynaptic and postsynaptic firing limits the amount of calcium entry.

What induces LTP?

if a presyncaptic spike triggers glutamate release before there is a postsynaptic spike, that delay allows for the postsynaptic spike to open NMDA channels, allowing a large influx of calcium.

when is LTD triggered?

when the postsynaptic cell fires before the presynaptic cell releases glutamate, and then the amount of postsynaptic depolarization is less and there is less calcium influx.

perceptron

a type of artificial neural network and algorithms that can act as a binary or linear classifier.

What is MLNN?

a network of multiple artificial neurons over multiple “hidden” layers, although in practice there are many different connectivity and rule configurations.

what is the advantage of MLNN over the perceptron?

By connecting the artificial neurons in this network through non-linear activation functions, we can create complex, non-linear decision boundaries that allow us to tackle problems where the different classes are not linearly separable.