Kamin's Blocking Effect: Neuronal Substrates
KAMIN'S BLOCKING EFFECT: NEURONAL SUBSTRATES
Blocking is a classical conditioning phenomenon that has profoundly influenced thinking about associative learning. This article will discuss the key characteristics of blocking and the role it may play in several mammalian brain systems in regulating particular types of learning.
Introduction and Significance
Classical or Pavlovian conditioning is an elementary form of associative learning—systematically described by a Russian physiologist Ivan Pavlov in the early twentieth century—that is considered an essential building block for complex learning. Typically, classical conditioning occurs when an initially neutral stimulus (conditional stimulus, CS) is paired in close temporal proximity (or contiguously) with a biologically significant stimulus (unconditional stimulus, US) that elicits an unlearned, reflexive behavior (unconditional response, UR). Through CS-US association formation, the animal acquires a behavior (conditional response, CR) to the CS that typically resembles the UR (but not always), precedes the US in onset time, and reaches a maximum magnitude at about the time of US onset.
Although the temporal arrangement between the CS and the US was thought to be the critical feature of classical conditioning, three separate studies in the late 1960s revealed that the informational, rather than temporal, relationship between the CS and US is the essential determinant of classical conditioning (Kamin, 1968; Rescorla, 1968; Wagner et al., 1968) and profoundly shaped subsequent thinking about associative learning. One of the three findings was the phenomenon of blocking, discovered by Leon Kamin. In a typical blocking experiment (see Table 1), one CS (denoted A) is first extensively paired with a US (A-US). Then a second CS (denoted B) undergoes compound conditioning with A and the same US (AB- US). Later, when B is tested, almost no (or very little) conditioning has accrued to B. However, if A was previously not (or weakly) conditioned with the US, then B (as well as A) accrues substantial associative strength during the compound conditioning phase. Thus, conditioning to B during the compound (AB-US) conditioning is inversely proportional to the magnitude of previous conditioning to A, and it is not B 's temporal relationship with the US that determines whether or not conditioning will develop to B.
It was originally suggested that if a US is already fully predicted by one stimulus and if the addition of a new stimulus provides no new significant information about the US, then the US will not activate or support the learning process responsible for establishing a new CS-US association (Kamin, 1968, 1969). Since its discovery, blocking has become the cornerstone of all modern learning theories (see Rescorla and Wagner, 1972; Mackintosh, 1975; Pearce and Hall 1980; Wagner, 1981; Sutton and Barto, 1990) and has been considered as an instance of cognitive processing in classical conditioning (Thompson et al., 1998).
Theoretical Aspects
Robert Rescorla and Allan Wagner (1972) proposed a simple learning equation based on "US processing" δV n = κ (λ - σV i) that elegantly describes the blocking effect; where κ is a learning constant; λ is the maximum associative strength conditionable with a given US; σV i is the sum of associative strengths between all CS elements present and the US; and δV n is the change in the associative strength of a particular CS on trial n. In essence, the associative strength between the CS-US is driven by "errors" between the expected US and the actual US. According to this equation, blocking occurs when the associative strength acquired by a CS (A) that was paired with a US (Phase I; A-US) reaches the λ value. Then, when a new CS (B) is introduced during the compound conditioning (Phase II; AB-US), stimulus A already fully predicts the US and has acquired all of its associative strength, because VA = λ. Hence, the stimulus B will not accrue any associative strength, because δVB = λ - (VA+VB) = 0 because VA = λ.
Other learning theories based on CS processing rather than US processing can also effectively accommodate blocking by postulating that the absence of surprising events on a trial (e.g., in the presence of a well-predicted reinforcer) reduces the associability (the ability to enter into new associations) of CSs present on that trial (Mackintosh, 1975; Pearce and Hall, 1980). In this view, blocking occurs because stimulus B rapidly loses associability because no surprising events occur after the compound CS presentation. Conditioning to B is blocked because its associability is reduced (rapidly to zero) and thus it does not enter into associations with the US, not because of any loss of effectiveness of the US as a reinforcer.
The US and CS processing theories, however, make somewhat different predictions regarding blocking; for example, whereas the Rescorla-Wagner model predicts one trial blocking, theories based on CS processing do not; conversely, CS-processing models can account for the disruption of blocking ("unblocking") when the magnitude of the reinforcer is decreased simultaneously with the addition of an element to the CS (Dickinson et al., 1976; Holland and Gallagher, 1993), a phenomenon that causes difficulty for the Rescorla-Wagner model.
Progress in identifying neural circuits subserving particular learning phenomena has yielded insight into the neural basis of this phenomenon. We will briefly discuss the involvement of the cerebellum, amygdala, midbrain dopamine neurons, and sept-ohippocampal systems in blocking.
Cerebellum and Eyeblink Conditioning
In eyeblink conditioning the animals learn to respond with eyelid closure to a CS (tone or light) that has been contingently paired with a US (e.g., airpuff to the eye). The anatomically rooted neural circuit underlying eyeblink conditioning (Kim and Thompson 1997) is remarkably similar to the US processing view of the Rescorla-Wagner model (see Figure 1).
Briefly, the CS pathway consists of excitatory mossy-fiber projections from the pontine nuclei to the cerebellum, whereas the US pathway consists of excitatory climbing-fiber projections from the inferior olive to the cerebellum. The cerebellum, in turn, sends monosynaptic γ -aminobutyric acid (GABA)-containing projections to the inferior olive. As GABA neurotransmitters generally exert inhibitory influences, it is conceivable that this cerebello-olivary pathway serves a negative feedback function and thus "gates" the inferior olive activity. Consistent with this view, neurons in the inferior olive show evoked neural activity to the airpuff US during the initial stage of CS-US training (before the animal exhibits any CRs), but not when the animals perform CRs during CS-US trials (Sears and Steinmetz, 1991; Hesslow and Ivarsson, 1996).
If the cerebello-olivary GABAergic projection serves a negative-feedback function in regulating the US information from reaching the cerebellum (where the CS-US association is thought to take place), then this can explain the blocking effect in eyeblink conditioning in the following manner: According to Figure 1, blocking will occur when a CS (e.g., auditory CSA) acquires sufficient associative strength to activate the cerebellum, which then inhibits the inferior olive (via the GABA-containing cerebello-olivary pathway) from US activation. Because the input representing the US can no longer reach the cerebellum, it cannot support conditioning to a new CS (e.g., visual CSB). Consistent with this view, a study found that pharmacological blockade of the cerebello-olivary activity (by infusing a GABA antagonist directly into the inferior olive) during the compound tone/light-airpuff conditioning—thereby disinhibiting inferior olive neurons—prevented blocking (Kim et al., 1998).
Amygdala and Fear Conditioning
Fear conditioning typically involves pairing a tone (or light) CS with a nociceptive shock US. After few CS-US pairings, the CS not only becomes capable of activating fear responses but also acquires the ability to inhibit/decrease sensitivity to nociceptive stimuli (e.g., foot shock) via a conditioned analgesic response (involving partly endogenous opioids) (Chance, 1980; MacLennan et al., 1980). Because the amygdala has been implicated as the locus of fear conditioning and sends projections to hypothalamus and brainstem nuclei that mediate various fear responses (LeDoux, 1997), some researchers believe that as fear conditioning proceeds, the ability of the nociceptive US to support fear conditioning diminishes as a function of the CS ability to elicit conditioned analgesia via the amygdala (see Figure 2). Consistent with this notion, systemic administration of the opioid antagonist naloxone during compound fear conditioning (phase II, blocking procedure) attenuated blocking (Fanselow and Bolles, 1979; Fanselow, 1998). It is possible that naloxone, by opposing the conditioned opioid analgesia response to the first CS, prevented the CS-associated decline in the nociceptive US's ability to support fear conditioning to the second CS (during compound conditioning). However, the locus of naloxone's effects on blocking is not known, and further research is necessary to determine whether the US-evoked responses in the amygdala decrease as a function of fear conditioning.
Striatum and Dopaminergic Midbrain Neurons
Other brain structures may employ a negative-feedback mechanism similar to that of the cerebellum to regulate the US or "reinforcing" input (Graybiel et al., 1994; Schultz et al., 1993). For example, some researchers report that many dopamine neurons in the substantia nigra (SN) and the ventral tegmental area (VTA) show phasic responses to the delivery of liquid reward in monkeys undergoing a spatial delayed-response task (Schultz et al., 1993). However, once learning is established (i.e., the animal learns that a light cue predicts the reward), the delivery of the reward no longer elicits phasic responses in dopaminergic neurons. Such negative-feedback circuits in the brain may well provide the neuronal instantiation of behavioral phenomena of blocking.
Indeed, when examined in a blocking paradigm, dopamine neurons did not fire in response to the blocked element of a compound stimulus but did fire to one element of a compound control stimulus (Waelti et al., 2001). These neurons seem to enable blocking phenomena in more complex forms of associative learning that involve appetitive stimuli and more complex motor responses and that depend on forebrain structures by conveying a "prediction error" signal that enables the formation of associations (Schultz and Dickinson, 2000). On a neural level, this system is analogous to that in the cerebellum (see Figure 1), replacing the inferior olive with the SN/VTA and the cerebellum with the basal ganglia and neocortex (which receive dopaminergic input from the SN/VTA). These findings are also consistent with reports of disrupted blocking after manipulations of the dopamine system (Crider et al., 1982, 1986).
Septohippocampal System
The hippocampus appears to play a role in the capacity to reduce the associability of a CS (Han, Gallagher, and Holland, 1995; Kaye and Pearce, 1987; Solomon and Moore, 1975; Honey and Good, 1993; Gallo and Cándido, 1995; Reilly, Harley, and Revusky, 1993); moreover, this function of the hippocampus appears to depend on the integrity of its cholinergic input (Baxter et al., 1997). Based on the view that the blocking effect results from variations in processing of the US, one would not expect the hippocampal damage to affect blocking, and some experiments have found just that (Garrud et al., 1984). In contrast, CS-processing theories of blocking propose that the associability of the added element of the compound CS is reduced because the reinforcer is already well predicted. On this view, damage to the hippocampus (or its cholinergic input) should eliminate this reduction in associability and, by extension, the blocking effect. In support of this view, several investigators have reported that lesions of the hippocampus reduced or eliminated blocking (Gallo and Cándido, 1995; Rickert et al., 1978; Rickert et al., 1981; Solomon 1977). These variations in the effectiveness of hippocampal system damage on blocking are consistent with the view that blocking has diverse origins (Holland, 1988) and may reflect different contributions of CS and US processing systems in different conditioning situations.
Experiments in an appetitive Pavlovian conditioning paradigm suggested that a blocking paradigm produces both CS-and US-processing mechanisms. Baxter et al. (1999) examined blocking in rats with selective removal of medial septal cholinergic neurons. These lesions remove hippocampal cholinergic input and impair reductions in CS associability in several different learning paradigms (Baxter et al., 1997). Although lesioned rats showed a normal blocking effect when tested in an extinction test with the added cue B, learning about B was facilitated relative to controls in subsequent savings tests, in which B alone was paired with reinforcement or served as a conditioned inhibitor. These findings suggested that although B did undergo a loss of associability as a consequence of the blocking procedure, this loss of associability was not necessary for blocking of learning about B to occur.
Conclusion
Functionally, blocking (or other similar processes) may play an important role in how animals process and attend to information in their environments. Because animals are constantly bombarded by numerous stimuli, it benefits them respond selectively to those stimuli that reliably predict biologically significant events. Other stimuli that provide no new useful information should be disregarded (or filtered), otherwise animals would be constantly forming unnecessary associations with various stimuli in their surroundings, thus inviting information overload. Indeed, malfunctioning selective attention mechanisms in the brain may contribute to psychopathological conditions such as schizophrenia (Bender et al., 2001). The behavioral phenomenon of blocking, which appears to use heuristic negative-feedback attentional processes, may circumvent such redundant learning.
See also:CONDITIONING, CELLULAR AND NETWORK SCHEMES FOR HIGHER-ORDER FEATURES OF; LEARNING THEORY: CURRENT STATUS; REINFORCEMENT OR REWARD IN LEARNING: CEREBELLUM; REINFORCEMENT OR REWARD IN LEARNING: STRIATUM
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Jeansok J.Kim
Mark G.Baxter