458 Semantic Memory and Priming
mutual associates in a free-association task at a much higher
frequency than was observed. This analysis does not prove
that the primes and targets were not directly related, and the
conclusion is limited to one model of priming (viz., the com-
pound-cue model conjoined with SAM). The contribution
exists in demonstrating that a particular model would have
difficulty accounting for both the mediated priming and the
free-association results. As another example of this approach,
Livesay and Burgess (1998) used HAL (discussed in the sec-
tion on models of semantic memory) to compute semantic
distances between the 2-step mediated primes and targets de-
veloped by Balota and Lorch (1986) and subsequently used
by McNamara and Altarriba (1988). Average semantic dis-
tance was higherbetween mediated primes and targets than
between unrelated primes and targets. In addition, they found
no relation between the magnitude of mediated priming and
lexical co-occurrence frequency, contradicting predictions of
McKoon and Ratcliff (1992). These results lead us to con-
clude that mediated priming remains a challenge to many
models of semantic priming.
Effects of Lag
Lag refers to the number of items that intervene between the
prime and the target. The standard priming paradigm uses a
lag of zero; the target immediately follows the prime. Many
studies have examined priming at lags of one, two, and even
greater. The early literature on lag effects was ambiguous
(e.g., Masson, 1991). Subsequent investigations indicated
that priming occurred across a lag of one but not two (e.g.,
Joordens & Besner, 1992; McNamara, 1992b), although
Masson (1995) did not obtain lag-1 priming in naming.
Recent experiments indicate that semantic priming may
occur over lags much greater than one or two items. For
theoretical reasons (discussed in the section on models of
semantic priming), S. Becker and Joordens (S. Becker et al.,
1997; Joordens & Becker, 1997) hypothesized that semantic
priming could be obtained at long lags if the primes and the
targets were strongly semantically related and the task en-
gaged semantic processing to a high degree. They con-
structed prime-target pairs that were semantically similar
(e.g.,pontoon-raft, tulip-rose) and used several methods to
increase the semantic processing of target words. S. Becker
et al. (1997) used an animacy decision task in which partic-
ipants were required to decide whether each word referred
to a living or a nonliving entity; Joordens and Becker
(1997) used a lexical decision task in which nonwords were
very word-like (e.g., brane). Semantic priming was ob-
tained in these experiments at lags of 4, 8, and even as high
as 21.5.
Priming at long lags is predicted by learning models, but it
is a serious problem for all other models of priming. In prin-
ciple, spreading activation models could explain such prim-
ing by making the decay of activation very slow, but this
assumption would be inconsistent with other findings sug-
gesting that activation decays quickly. Moreover, slow decay
would probably leave so much residual activation in memory
that basic semantic priming effects could no longer be pre-
dicted. Compound-cue models would need cues of between
23 and 24 items to explain priming at a lag of 21.5 (prime +
intervening items + target). Cues of this size strain credibility.
Proximity models explain priming across intervening items
by assuming that the semantic pattern of the prime is not
completely replaced by semantic patterns of intervening
items (e.g., Masson, 1995; Plaut & Booth, 2000). This mech-
anism almost certainly will not work with lags greater than
one or two items.
There are several reasons to question these findings, how-
ever. First, the results are unstable. Joordens and Becker
(1997) obtained lag-8 priming in two experiments but did not
obtain it in another two experiments. Second, and more im-
portant, the priming observed in these studies has peculiar
properties. Priming either did not decay with lag or decayed
rapidly with lag, and yet priming at the shortest lag did not
differ in these situations. For example, in their second exper-
iment, Joordens and Becker varied lag over the values 0, 1, 2,
4, and 8. One condition was designed to produce long-term
semantic priming and used a lexical decision task with diffi-
cult nonwords (e.g., brane). This condition yielded 45 ms of
priming at lag 0, and there was no evidence of decay across
lags; for example, priming was 41 ms at lag 8. Another con-
dition was designed not to produce long-term semantic prim-
ing and used a lexical decision task with easier nonwords
(e.g.,brene). This condition yielded 27 ms of priming at lag
0, which quickly decayed to nonsignificant levels. The 18-ms
difference in priming at lag 0 for these two conditions did not
approach statistical significance. This pattern of results is dif-
ficult to explain even in the learning model. Why should
priming of comparable initial magnitude decay slowly in one
case but quickly in another?
Joordens and Becker (1997) proposed several explanations
of these results that relied on dual mechanisms, but none was
compelling. Their preferred model incorporated a quickly de-
caying associative priming mechanism with a long-term
learning mechanism. Priming in the easy nonword condition
would be attributed to the associative mechanism alone,
whereas priming in the difficult nonword condition would be
attributed to the combined effects of both mechanisms. Even
this model, however, is not consistent with their findings, as it
still predicts some decline in priming with lag: At lag 0, both