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Neural Circuits in the Retina
• 126 million rods and cones converge to 1
million ganglion cells
• Higher convergence of rods than cones
– Average of 120 rods to one ganglion cell
– Average of 6 cones to one ganglion cell
– Cones in fovea have 1 to 1 relation to
ganglion cells
Focusing and Transduction
Light and the Eye
Windows
Why do we have Synapses?
• Economy
• Processing!
Convergence results in
poor acuity (the ability to
detect details). For the
rods, the RGC sends the
same message to the
brain in a and b. for the
cones (especially those in
the fovea) there is little
convergence. RGCs send
different messages to the
brain for a and b.
Lateral Inhibition of Neurons
• Experiments with eye of Limulus (Hartline, 1956)
– Ommatidia allow recordings from a single
receptor
– Light shown into a single receptor led to rapid
firing rate of nerve fiber
– Adding light into neighboring receptors led to
reduced firing rate of initial nerve fiber
Hartline’s Results
Lateral Inhibition and Lightness Perception
• Psychophysical results can be explained by
lateral inhibition
– The Hermann Grid: Seeing spots at an
intersection
– Mach Bands: Seeing borders more sharply
Hermann Grid
• People see an illusion of gray images in
intersections of white areas
• Signals from bipolar cells cause effect
– Receptors stimulated by dark areas inhibit
the response of neighboring cells receiving
input from white area
– The lateral inhibition causes a reduced
response which leads to the perception of
gray
Explanation of the
Herman Grid
Mach Bands
Figure 3.10 Circuit to explain the Mach band effect based on lateral inhibition. The circuit works like the
one for the Hermann grid in Figure 3.6, with each bipolar cell sending inhibition to its neighbors. If we know
the initial output of each receptor and the amount of lateral inhibition, we can calculate the final output of the
receptors. (See text for a description of the calculation.)
Simultaneous Contrast
Neural Circuits
• Groups of neurons connected by excitatory
and inhibitory synapses
• A linear circuit has no convergence and only
excitatory inputs
– Input into each receptor has no effect on
the output of neighboring circuits
– Each circuit can only indicate single spot of
stimulation
Linear Circuit
Neural Circuits - continued
• Convergent circuit with only excitatory
connections
– Input from each receptor summates into
the next neuron in the circuit
– Output from convergent system varies
based on input
– Output of circuit can indicate single input &
increases output as length of stimulus
increases
Circuit with convergence added.
Neural Circuits - continued
• Convergent circuit with excitatory and inhibitory
connections
– Inputs from receptors summate to determine
output of circuit
– Summation of inputs result in:
• Weak response for single inputs & long stimuli
• Maximum firing rate for medium length
stimulus
Receptive Fields
• Area of retina that
affects firing rate of a
given neuron in the
circuit
• Receptive fields are
determined by
monitoring single cell
responses
• Stimulus is presented
to retina and response
of cell is measured by
an electrode
Center-Surround Receptive Fields
• Excitatory and inhibitory effects are found in
receptive fields
• Center and surround areas of receptive fields
result in:
– Excitatory-center-inhibitory surround
– Inhibitory-center-excitatory surround
Response of a ganglion cell in the cat’s retina
Excel Assignment
• Use the MachHermann spreadsheet to
“program” ganglion cells that mimic the
mach band illusion and the Herman Grid
Illusion. Submit the file and be prepared to
explain how your model works.