When a sea hare learns about touches to parts of its body, its sensory neurons detect those touches the same way every time. Repeated touches change how strong the connections are between sensory neurons and motor neurons, but they do not change how the sensory receptors react to a touch—the amount of neural firing generated by sensory neurons with each touch is stable throughout habituation. Habituation occurs when a sea hare learns to ignore touches to its siphon. Perceptual learning, in contrast, involves increases in the ability to make distinctions between similar inputs. In perceptual learning, an individual learns to recognize stimulus differences that were not noticed before, and sensory neurons may change how they respond to events over time.
Unlike sea hares, which have only very simple neural circuits, your ability to distinguish different kinds of touches depends heavily on neurons within your somatosensory cortex. Sensory receptors in your skin send signals that pass up your spinal cord, through your thalamus, and into your somatosensory cortex (intro-duced in Chapter 2 and shown in Figure 2.7). Do you remember from Chapter 2 how the motor cortex contains a map of different regions of the body that it con-trols? It was called a homunculus. Somatosensory cortex has a similar homunculus that maps parts of the body receiving touch messages (Figure 3.12). So, whenever you touch something with your index finger, a specific set of neurons within your somatosensory cortex becomes active, and you perceive not only that your finger has contacted something, but what the surface that you have touched is like.
As described in Chapter 2, one of the most important jobs of the cerebral cortex is to process information about stimuli, and this includes distinguish-ing the features of perceived stimuli. Sensory cortices are especially important for making such distinctions, and the somatosensory cortex is an example.
Sensory cortices are areas of the cerebral cortex that process visual stimuli, auditory stimuli, somatosensory (touch) stimuli, and so on. Within each of these brain regions, individual neurons respond to different stimulus features.
For example, some neurons in your auditory cortex will fire strongly when you hear a high-pitched note, and others will fire strongly when you hear a low-pitched note.
The range of stimuli that cause a particular cortical neuron to fire is called the neuron’s receptive field. Figure 3.13 shows the receptive field for one neuron in the auditory cortex of a guinea pig that was measured using single-cell record-ing techniques. This neuron fired when the guinea pig heard tones pitched between 0.7 and 3 kilohertz (kHz); this range of pitches is the neuron’s recep-tive field. The neuron fired most when the guinea pig heard tones pitched near 0.9 kHz. Neuroscientists would say that this cortical neuron is tuned to 0.9 kHz, meaning that this pitch causes the most firing. In somatosensory cortex, the receptive field of a neuron is defined as the patch of skin or other tissue that when stimulated causes the neuron to fire. In general, the more neurons that are tuned to a particular type, source, or strength of stimulus (or any other feature of a stimulus), the better the organism will be able to make fine distinctions related to that stimulus. So, for example, in the body map shown in Figure 3.12, the region sensitive to touches on the thumb is larger than the region sensitive to touches on the neck; a larger region in the cortex means more neurons, with
Primary somatosensory cortex (S1)
Genitals Toes Foot Leg Hip Trunk Head Neck
ryma SorimPatosensory Cortex (S1)
Intra-abdominal Pharynx Tongue Jaw Gums Teeth
Lips Upper lip
Lower lip Face
Nose Eye
Thumb Fingers
Hands Forearm
Elbow Arm Figure 3.12 The homunculus
corresponding to human somatosensory cortex Different regions of somatosensory cortex respond most strongly to touches of specific body parts. These regions are orga-nized such that body parts close together activate adjacent regions of somatosensory cortex.
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103the result that the skin on the thumb is able to make finer distinctions than the skin on the neck is.
The spatial organization (body map) of somatosensory cortex shown in Figure 3.12 reflects the fact that neurons with similar receptive fields are often found clustered together in sensory cortices. In like manner, visual and auditory cortices also contain clusters of similarly tuned neurons. When these clusters are organized in predictable ways, the pattern of cortical organization is described as a topographic map, which simply means that cortical neurons that are physi-cally close together are tuned to similar stimulus features. In topographic maps, neighboring cortical neurons have overlapping receptive fields. For example, if you collected recordings across the surface of a guinea pig’s auditory cortex, you would find that adjacent neurons respond to gradually increasing or decreasing sound frequencies—neurons tuned to 0.9 kHz will be surrounded by neurons tuned to 0.8, 0.9, or 1.0 kHz. If you sat at a piano and played the keys one at a time from left to right up the keyboard, activity in your auditory cortex would gradually shift in a pattern that corresponds to the movement of your hand across the keyboard.
For most of the history of neuroscience, it was thought that neurons in sen-sory cortices responded to sensations in ways that were directly analogous to how piano strings respond to the pressing of piano keys. It was thought that every time a specific set of sensory receptors detected a stimulus, a particular set of cortical neurons became active. You may recall from Chapter 1 that René Descartes proposed that sensations cause this type of reflexive chain reaction.
Neuroscientists were surprised to discover that in fact the receptive fields of neu-rons in sensory cortices change during early development and also after various injuries and as a result of repeated experiences. In other words, the topographic maps in your sensory cortices right now are not the same ones that were in your brain 10 years ago (although they are quite similar). The capacity for cortical receptive fields and cortical spatial organization to change as a result of experi-ence is called cortical plasticity.
If what you perceive depends on how neurons in your sensory cortices are tuned and if the tuning of your sensory cortices changes over time, then what does this suggest about your perception? It suggests that your perception may also change over time—which is exactly what studies of perceptual learning show. The clearest evidence that repeated experiences can change perception by changing sensory cortices comes not from learning studies, however, but from studies of perceptual development.
140 120 100 80 60 40 20 0 –20 Neuronal response (in spikes per second)
Tone frequency (in kilohertz) 1.0
0.1 10 100
Receptive field
Best frequency
Figure 3.13 Receptive field of a neuron in the auditory cortex of a guinea pig Receptive fields are identified by measuring the amount of neural activity produced in response to different stimuli—
in this case, to sounds ranging from 0.1 to 100 kilohertz (kHz). This neuron responds most to 0.9 kHz, but it also responds to a narrow range of similarly pitched sounds, and this range constitutes the neuron’s receptive field.
(Adapted from Weinberger, 2004.)
©Marion Wear/istockphoto
Studies with opossums have revealed that the development of cortical structure and function depends on repeated experiences.
Plasticity during Development
Normally, as young organisms develop, their ability to perceive differences in visual stimuli increases. Neurophysiological studies of neurons within the visual cortex of kittens show that their tuning becomes more selective over time and that topographic maps within visual cortex become more organized. If, however, a kitten’s eye is sewn shut during development or if vision in an infant’s eye is occluded by a cataract for several years, then even if vision in that eye is later restored, the acuity of that eye will be permanently degraded. Similarly, if young animals are experimentally deprived of vision in one eye, their cortical neurons will show less tuning to that eye than is seen in animals that grew up with both eyes functional. These findings suggest that normal development of visual corti-cal maps in mammals requires neural activity from both eyes. In other words, repeated visual experiences shape the organization of visual cortex during devel-opment, which in turn determines an organism’s perception of the visual world (Morishita & Hensch, 2008).
If perceptual experiences change how sensory cortices respond to stimuli, what happens if stimulation from both eyes is cut off, such as when a person is born blind or loses his sight soon after birth? Neuroimaging studies show that the areas of visual cortex that normally respond to visual stimuli in sighted peo-ple will, in blind peopeo-ple, respond to sounds and tactile stimulation. For exampeo-ple, activity in the visual cortex is seen to increase in blind individuals during Braille reading and other tactile tasks but decreases in sighted individuals performing these same tasks (Lewis, Saenz, & Fine, 2010; Sadato et al., 1998).
Cortical plasticity produced by early blindness has recently been studied experimentally in developing opossums (Kahn & Krubitzer, 2002; Karlen, Kahn,
& Krubitzer, 2006). Researchers blinded half of the animals at birth and then, when the animals reached adulthood, exposed both the blinded and sighted opossums to visual, auditory, and somatosensory inputs to measure between-group differences in cortical structure and receptive fields. Sighted opossums possessed distinct cortical regions that each were tuned exclusively either to visual, auditory, or somatosensory inputs. At the same time, receptive fields in other regions of the cortex were multimodal, meaning that neurons in those areas responded to inputs from more than one sensory modality—for example, visual and audi-tory stimuli. A different pattern was seen in opossums that had grown up blind. The cortical areas that were tuned exclusively to visual stimuli in sighted opossums had shrunk, and within those areas, some neurons now responded to auditory or somatosensory stimuli or both. In addi-tion, the auditory and somatosensory areas of the cortex had increased beyond normal size. Most striking of all, the blinded opossums possessed a new cortical region with unique anatomical and physiological characteristics that didn’t exist in any sighted opossum’s brain.
Clearly, developmental experiences can have a huge effect on how neurons within sensory cortices respond to stimuli, influencing both the perception of sensory events and the development of responses to perceived events. In the case of opossums that developed without sight, the absence of vision radically changed the sensory experiences to which cortical neurons were exposed, and the opossums’ brains changed accordingly. In all animals, not just those that have been blinded (or similarly injured) at birth, experience modifies sensory cortical maps. Your own cortical maps changed drastically during your infancy, and they will continue to change throughout your life, although you won’t perceive that this is happening. In the Clinical Perspectives section, we describe how percep-tual learning during development makes it possible for individuals to overcome sensory deficits such as blindness and deafness using new technologies.
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105Hebbian Learning
You have now read about some of the evidence that neurons in sensory cortices change with experience, but what is the mechanism of this change? Several ideas have been proposed, but the most influential was suggested by psychologist Donald Hebb. In one of the most often quoted passages in neuroscience, Hebb wrote: “When an axon of cell A is near enough to excite a cell B and repeatedly or persistently takes part in firing it, some growth process or metabolic change takes place such that A’s efficiency, as one of the cells firing B, is increased”
(Hebb, 1949). A shorthand version of this “rule” that neuroscientists often use is neurons that fire together, wire together. One form of synaptic plasticity that seems to follow this rule is long-term potentiation (LTP), which, as you’ll recall from Chapter 2, is thought to underlie many changes that occur in the brain during learning. Learning that involves strengthening connections between cells that work together (typically neurons) is called Hebbian learning.
Figure 3.14 shows a simple model of Hebbian learning. Eight hypothetical cortical neurons are shown, each with weak connections to surrounding neurons (Figure 3.14a). Now let’s assume that some sensory stimulus evokes activation in a subset of these neurons that are tuned to features of this stimulus (solid circles in Figure 3.14a). As those neurons become active, they produce outputs that are transmitted to other nearby neurons. According to Hebb’s rule—neurons that fire together, wire together—the connections between coactive neurons are strength-ened as a result. Repeated coactivity of the same subset of neurons, in response to the same stimulus, has a cumulative effect, resulting in the strong connections (heavy lines) shown in Figure 3.14b. Thus, repeated exposure to a stimulus can strengthen connections within a distinctive subset of cortical neurons, and this subset can then provide an increasingly reliable basis for identifying the stimulus that is activating them. Hebbian learning provides a possible neural mechanism for the representational processes proposed in comparator models and differentia-tion theories of perceptual learning, described previously. Changing the connec-tions between cortical neurons creates a pattern that makes a repeated stimulus more likely to be recognized and distinguished from other stimuli.
Hebbian learning can also explain how repeated exposures facilitate recogni-tion (the priming effect). Suppose that once connecrecogni-tions have been established between cortical neurons, the organism encounters an incomplete version of a familiar stimulus (Figure 3.14c). Only some of the subset of neurons that rep-resents that familiar stimulus are activated at first (solid circles in Figure 3.14c), but the connections already established through repeated experiences will pro-duce outputs that complete the familiar pattern, reconstructing Figure 3.14b.
This kind of pattern completion may correspond to retrieval in the word-stem completion task described above. Priming might then be explained as a strengthening of existing connections between cortical neurons that lasts only as long as the priming effect. Similarly, recognition of distorted versions of a famil-iar stimulus, such as might occur when a blue jay perceives a camouflaged moth,
Figure 3.14 A simple model of Hebbian learning Circles correspond to cortical neurons, and lines denote connections between them. (a) Stimulus inputs activate a subset of the neurons (solid circles). (b) Connections between coactive neurons are strengthened (heavy lines). (c) After connections between coactive neurons have been established, an incomplete version of a familiar stimulus may activate just some of the neurons (solid circles) in the subset that represents the stimulus. Activation flows along the strengthened con-nections and ultimately retrieves the complete stimulus, resulting in the representation shown in (b).
(a) (b) (c)
could also be facilitated by stored patterns encoded as connections between neurons that on a previous occasion were simultaneously active when moths were perceived. Thus, just as experiments with sea hares have provided a way to evaluate and extend the dual process theory of habituation, studies of cortical plasticity can potentially provide relevant information for assessing the adequacy of behavior-based models of perceptual learning and object recognition.
Cortical Changes in Adults after Exposure
During development, the arrival of inputs from different receptors determines how cortical neurons become tuned, as well as the proportion of available neu-rons that respond to a particular class of input. Someone born without vision is likely to have proportionately more neurons available to respond to tactile stimuli, and someone born deaf typically will come to have larger cortical regions sensitive to visual stimuli. Granted, these are extreme cases of depriving a brain of a particular class of input. What might happen in more subtle cases—
for example, in a person who chooses to listen only to rap music, or to classical music, or to country music? Might the topographic map in the auditory cortex reflect the kinds of songs the person listens to the most? Is cortical plasticity only present during early development? How much exposure is required for the cortical neurons to become retuned?
Recent neuroimaging studies suggest that it is relatively easy to retune neu-rons within the sensory cortices of adults and that it can be done in less than a day. For example, simply touching a person’s fingertip repeatedly with tiny pins was shown to improve the person’s ability to distinguish subtle differences in the pins’ positions. Initially, people were able to discriminate two simultaneous touches on the tip of their index finger, as long as the touches were spaced at least 1.1 mm apart (Figure 3.15a). After receiving 2 hours of exposure consisting of repeated simultaneous stimulation of two closely spaced points (0.25–3 mm apart) on the tip of their right index finger, participants’ ability to discriminate touches improved (Dinse, Ragert, Pleger, Schwenkreis, & Tegenthoff, 2003;
Hodzic, Veit, Karim, Erb, & Godde, 2004; Pilz, Veit, Braun, & Godde, 2004).
Like the experiment with squiggles described earlier (Figure 3.4), this study shows that humans can learn to make fine distinctions through mere repeated exposures. What’s going on in the brain when this happens? Before repeated expo-sures, fMRI difference images showed that touching the right index finger resulted in localized activation within the somatosensory cortex (Figure 3.15b). After this finger was stimulated repeatedly for 2 hours, subsequent instances of stimulation activated a larger region of the somatosensory cortex than was observed before exposure (Figure 3.15c; Hodzic et al., 2004). Repeated touching of the fingertip led to both perceptual learning and cortical reorganization. In this case, the reor-ganization showed up in fMRI images as an increase in the size of the region of somatosensory cortex that was selectively activated during stimulation of the tip of the right index finger; thus, perceptual learning was associated with an increase in the number of cortical neurons tuned to touches of the fingertip.
This same phenomenon has also been examined using magnetoencephalo-graphic (MEG) recordings of neural activity in somatosensory cortex. MEGs are similar to EEGs in that both reflect the activity of groups of neurons (unlike fMRI, which only measures blood oxygenation in the brain). The main differ-ence between MEGs and EEGs is that MEGs measure small changes in mag-netic fields rather than changes in electrical fields. MEG recordings showed that l arger changes in somatosensory-cortex activity in response to tactile stimulation predicted larger improvements in discrimination abilities (Godde, Ehrhardt, &
Braun, 2003). Together, these neuroimaging, neurophysiological, and behavioral
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1071.4 1.3 1.2 1.1 1.0 0.9 0.8 Threshold distance
(in millimeters)
After exposure Before
exposure
One day later Left IF
Right IF
Figure 3.15 Cortical reorganization in humans after exposure (a) Participants improved their ability to distinguish two separate touch points on their right index finger (Right IF) after 2 hours of passive exposure to stimulation of closely spaced points on that finger. (b) fMRI showing cortical activation patterns in somatosensory cortex during tactile stimulation of the right index finger before exposure. (c) After 2 hours of stimulation to the right index finger, activation in the left hemisphere (where the right finger is represented) has increased.
(a)
(b) (c)
results suggest that perceptual learning and cortical changes occur in parallel and that both can occur after repeated exposures to inconsequential stimuli.
Given that perceptual learning after mere exposure is associated with corti-cal changes, might discrimination training also lead to similar kinds of corticorti-cal change? Several experiments have found that discrimination training does lead to
Given that perceptual learning after mere exposure is associated with corti-cal changes, might discrimination training also lead to similar kinds of corticorti-cal change? Several experiments have found that discrimination training does lead to