Transcript Chapter 3

Chapter 3:
Neural Processing and
Perception
Neural Processing and Perception
• Neural processing is the interaction of signals
in many neurons.
Figure 3-1 p54
Lateral Inhibition and Perception
• Experiments with eye of Limulus
– Ommatidia allow recordings from a single
receptor.
– Light shown into a single receptor leads to
rapid firing rate of nerve fiber.
– Adding light into neighboring receptors
leads to reduced firing rate of initial nerve
fiber.
Figure 3-2 p54
Figure 3-3 p55
Lateral Inhibition and Lightness
Perception
• Three lightness perception phenomena
explained by lateral inhibition
– The Hermann Grid: Seeing spots at an
intersection
– Mach Bands: Seeing borders more sharply
– Simultaneous Contrast: Seeing areas of
different brightness due to adjacent areas
Hermann Grid
• People see an illusion of gray images in
intersections of white areas.
• Signals from bipolar cells cause effect
– Receptors responding to white corridors
send inhibiting signals to receptor at the
intersection
– The lateral inhibition causes a reduced
response which leads to the perception of
gray.
Figure 3-4 p55
Figure 3-5 p55
Figure 3-6 p56
Figure 3-7 p56
Figure 3-8 p56
Mach Bands
• People see an illusion of enhanced lightness
and darkness at borders of light and dark
areas.
– Actual physical intensities indicate that this
is not in the stimulus itself.
– Receptors responding to low intensity
(dark) area have smallest output.
– Receptors responding to high intensity
(light) area have largest output.
Figure 3-9 p57
Figure 3-13 p58
Figure 3-14 p58
Figure 3-15 p59
A Display That Can’t Be Explained by
Lateral Inhibition
• White’s Illusion
– People see light and dark rectangles even
though lateral inhibition would result in the
opposite effect.
Figure 3-16 p59
Processing From Retina to Visual
Cortex and Beyond
• Area of receptors that affects firing rate of a
given neuron in the circuit
• Receptive fields are determined by
monitoring single cell responses.
• Research example for vision
– Stimulus is presented to retina and
response of cell is measured by an
electrode.
Figure 3-19 p60
Figure 3-20 p61
Figure 3-21 p61
Figure 3-22 p62
Figure 3-23 p62
Ganglion Cell Output
• Small Spot Stimuli
Spontaneous Activity
Uniform Illumination
Spike Record
Lateral Inhibition
• More natural Stimuli
• How does GC output vary?
10 spikes/sec
Lateral Inhibition
• Enhances edges
• De-emphasize broad unchanging surfaces
• Early processing is already “modifying” the
scene
10 spikes/sec
Hubel and Wiesel’s Rational for
Studying Receptive Fields
• Signals from the retina travel through the
optic nerve to the
– Lateral geniculate nucleus (LGN)
– Primary visual receiving area in the
occipital lobe (the striate cortex or area V1)
– And then through two pathways to the
temporal lobe and the parietal lobe
– Finally arriving at the frontal lobe
Figure 3-24 p63
Figure 3-25 p63
Hubel and Wiesel’s Rational for
Studying Receptive Fields - continued
• LGN cells have center-surround receptive
fields.
• Major function of LGN is to regulate neural
information from the retina to the visual
cortex.
– Signals are received from the retina, the
cortex, the brain stem, and the thalamus.
– Signals are organized by eye, receptor
type, and type of environmental
information.
Hubel and Wiesel’s Rational for
Studying Receptive Fields - continued
• 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
Figure 3-26 p64
Receptive Fields of Neurons in the
Visual Cortex
• Neurons that fire to specific features of a
stimulus
• Pathway away from retina shows neurons
that fire to more complex stimuli
• Cells that are feature detectors:
– Simple cortical cell
– Orientation tuning curve
– Complex cortical cell
– End-stopped cortical cell
Figure 3-27 p65
Figure 3-28 p65
Table 3-1 p66
Selective Adaptation
• Neurons tuned to specific stimuli fatigue
when exposure is long.
• Fatigue or adaptation to stimulus causes
– Neural firing rate to decrease
– Neuron to fire less when stimulus
immediately presented again
• Selective means that only those neurons that
respond to the specific stimulus adapt.
Figure 3-30 p67
Selective Adaptation - continued
• Measure sensitivity to range of one stimulus
characteristic
• Adapt to that characteristic by extended
exposure
• Re-measure the sensitivity to range of the
stimulus characteristic
Figure 3-31 p67
Figure 3-32 p67
Selective Adaptation - continued
• Measure contrast threshold by decreasing
intensity of grating until person can just see it.
• Calculate the contrast sensitivity by taking
1/threshold.
• If threshold is low, person has high contrast
sensitivity.
Figure 3-33 p68
Selective Rearing
• Animals are reared in environments that contain only
certain types of stimuli
– Neurons that respond to these stimuli will become
more predominate due to neural plasticity.
– Blakemore and Cooper (1970) showed this by
rearing kittens in tubes with either horizontal for
vertical lines.
– Both behavioral and neural responses showed the
development of neurons for the environmental
stimuli.
Figure 3-34 p69
Higher Level Neurons
• Inferotemporal (IT) cortex
• Prosopagnosia
• Fusiform face area
Figure 3-35 p69
Figure 3-36 p70
The Sensory Code
• Sensory code - representation of perceived
objects through neural firing
– Specificity coding - specific neurons
responding to specific stimuli
• Leads to the “grandmother cell”
hypothesis
• Recent research shows cells in the
hippocampus that respond to concepts
such as Halle Berry.
The Sensory Code continued
– Problems with specificity coding:
• Too many different stimuli to assign
specific neurons
• Most neurons respond to a number of
different stimuli.
• Distributed coding - pattern of firing across
many neurons codes specific objects
– Large number of stimuli can be coded by a
few neurons.
Figure 3-37 p70
Sensory Code The Sensory Code continued
• How many neurons are needed for an object
in distributed coding?
– Sparse coding - only a relatively small
number of neurons are necessary
• This theory can be viewed as a midpoint
between specificity and distributed
coding.
Figure 3-38 p71
Figure 3-39 p71
Figure 3-40 p72
The Mind-body Problem
• How do physiological processes become
transformed into perceptual experience?
– Easy problem of consciousness
• Neural correlate of consciousness
(NCC) - how physiological responses
correlate with experience
– Hard problem of consciousness
• How do physiological responses cause
experience?
Figure 3-41 p73