Interference in memory for pitch-only and rhythm-only sequences

Abstract

In human memory, the ability to recognize a previously encountered stimulus often undergoes cumulative interference when the number of intervening items between its first and second presentation increases. Although this is a common effect in many domains, melodies composed in tuning systems familiar to participants (e.g., Western tonal music) do not seem to suffer such cumulative decrements in recognition performance. Interestingly, melodies in unfamiliar tuning systems do show cumulative decrements. This finding has been predicted by a novel Regenerative Multiple Representations (RMR) conjecture. The present study further explores this phenomenon and the conjecture by investigating pitch-only (isochronous rhythm) and rhythm-only (monotone pitch) sequences of melodies in an unfamiliar tuning system that previously showed cumulative disruptive effects. Experiment 1 replicated previous studies reporting significant interference effects from the number of intervening items when melodies use uncommon rhythms and are composed in an unfamiliar tuning system. Furthermore, as predicted by the RMR conjecture, when rhythmic information was neutralized (Experiment 2), the cumulative interference related to the number of intervening items was retained. This was also the case when the original pitch information of each melody was neutralized, leaving variation only in the rhythmic information (Experiment 3). Results are discussed in the context of the RMR conjecture: given converse results, the conjecture would have been falsified. However, it currently remains plausible and appears to be a useful tool for precise predictions about the link between prior experience, perception, and formation of new memories.

Keywords

interference memory music perception pitch recognition rhythm

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References

Baayen

R.H.

(2008). Analyzing linguistic data: A practical introduction to statistics using r. New York: Cambridge University Press.

Baayen

R.H.

Davidson

D.J.

Bates

D.M.

(2008). Mixed-effects modeling with crossed random effects for subjects and items. Journal of Memory and Language, 59, 390–412.

Bates

D.M.

Maechler

Bolker

Walker

(2013). Lme4: Linear mixed-effects models using eigen and s4. R package version, 1.

Berch

D.B.

(1976). Criterion change in continuous recognition memory: A sequential effect. Bulletin of the Psychonomic Society, 7, 309–312.

Brochard

Abecasis

Potter

Ragot

Drake

(2003). The “ticktock” of our internal clock direct brain evidence of subjective accents in isochronous sequences. Psychological Science, 14, 362–366.

Buchsbaum

B.R.

Padmanabhan

Berman

K.F.

(2011). The neural substrates of recognition memory for verbal information: Spanning the divide between short- and long-term memory. Journal of Cognitive Neuroscience, 23, 978–991.

Bui

D.C.

Maddox

G.B.

Zou

Hale

S.S.

(2014). Examining the lag effect under incidental encoding: Contributions of semantic priming and reminding. Quarterly Journal of Experimental Psychology, 67, 2134–2148.

Campeanu

Craik

F.I.M.

Backer

K.C.

Alain

(2014). Voice reinstatement modulates neural indices of continuous word recognition. Neuropsychologia, 62, 233–244.

Collier

G.L.

Logan

(2000). Modality differences in short-term memory for rhythms. Memory & Cognition, 28, 529–538.

10.

Deutsch

(1970). Tones and numbers: Specificity of interference in immediate memory. Science, 168, 1604–1605.

11.

Deutsch

(1975). The organization of short-term memory for a single acoustic attribute. In Deutsch

Deutsch

J. A.

(Eds.), Short-term memory (pp. 107–151). New York: Academic Press.

12.

Deutsch

(1986). Auditory pattern recognition. In Boff

K. R.

Kaufman

Thomas

J. P.

(Eds.), Handbook of perception and human performance (Vol. II, Cognitive Processes and Performance, pp. 32–1 - 32–49). New York: Wiley.

13.

Deutsch

J.A.

Deutsch

(1963). Attention – some theoretical considerations. Psychological Review, 70, 80–90.

14.

Donaldson

Murdock

B.B.

(1968). Criterion change in continuous recognition memory. Journal of Experimental Psychology, 76, 325–330.

15.

Dowling

W.J.

Kwak

Andrews

M.W.

(1995). The time course of recognition of novel melodies. Perception and Psychophysics, 57, 136–149.

16.

Gibson

J.J.

(1977). The theory of affordances. In Shaw

Bransford

(Eds.), Perceiving, acting, and knowing: Towards an ecological psychology (pp. 127–143). Hillsdale, NJ: Lawrence Erlabum Associates.

17.

Gibson

J.J.

(1978). The ecological approach to the visual perception of pictures. Leonardo, 11, 227–235.

18.

Hebert

Peretz

(1997). Recognition of music in long-term memory: Are melodic and temporal patterns equal partners? Memory and Cognition, 25, 518–533.

19.

Herff

S.A.

Olsen

K.N.

Dean

R.T.

(submitted). Resilent memories for melodies: The number of intervening melodies does not influence novel melody recognition.

20.

Herff

S.A.

Olsen

K.N.

Dean

R.T.

Prince

(submitted). Memory for melodies in unfamiliar tuning systems: Investigating effects of recency and number of intervening items.

21.

Hockley

W.E.

(1992). Item versus associative information - further comparisons of forgetting rates. Journal of Experimental Psychology: Learning Memory and Cognition, 18, 1321–1330.

22.

Judd

C.M.

Westfall

Kenny

D.A.

(2012). Treating stimuli as a random factor in social psychology: A new and comprehensive solution to a pervasive but largely ignored problem. Journal of Personality and Social Psychology, 103, 54–69.

23.

Kass

R.E.

Raftery

A.E.

(1995). Bayes factors. Journal of the American Statistical Association, 90, 773–795.

24.

Konkle

Brady

T.F.

Alvarez

G.A.

Oliva

(2010). Conceptual distinctiveness supports detailed visual long-term memory for real-world objects. Journal of Experimental Psychology: General, 139, 558–578.

25.

Krumhansl

C.L.

(1991). Music psychology – tonal structures in perception and memory. Annual Review of Psychology, 42, 277–303.

26.

Kruschke

J.K.

(2010). Doing bayesian data analysis: A tutorial introduction with R. San Diego: Academic Press.

27.

Kruschke

J.K.

(2013). Bayesian estimation supersedes the t test. Journal of Experimental Psychology: General, 142, 573–603.

28.

Margulis

E.H.

(2005). A model of melodic expectation. Music Perception Journal, 22, 663–714.

29.

Margulis

E.H.

(2012). Musical repetition detection across multiple exposures. Music Perception, 29, 377–385.

30.

Nathoo

F.S.

Masson

M.E.J.

(2016). Bayesian alternatives to null-hypothesis significance testing for repeated-measures designs. Journal of Mathematical Psychology, 144–157.

31.

Norman

D.A.

(2013). Models of human memory. New York: Elsevier.

32.

Oberauer

Lewandowsky

(2011). Modeling working memory: A computational implementation of the time-based resource-sharing theory. Psychonomic Bulletin & Review, 18, 10–45.

33.

Oberauer

Lewandowsky

Farrell

Jarrold

Greaves

(2012). Modeling working memory: An interference model of complex span. Psychonomic Bulletin & Review, 19, 779–819.

34.

Olson

G.M.

(1969). Learning and retention in a continuous recognition task. Journal of Experimental Psychology, 81, 381–384.

35.

Paivio

(1969). Mental imagery in associative learning and memory. Psychological Review, 76, 241–263.

36.

Pearce

M.T.

(2014). Idyom project. from https://code.soundsoftware.ac.uk/projects/idyom-project

37.

Poon

L.W.

Fozard

J.L.

(1980). Age and word-frequency effects in continuous recognition memory. Journals of Gerontology, 35, 77–86.

38.

R-Core-Team. (2013). R: A language and enviornment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Retrieved from http://www.R-project.org/

39.

Rakover

S.S.

Cahlon

(2001). Face recognition: Cognitive and computational processes (Vol. 31). Amsterdam: John Benjamins Publishing.

40.

Sadeh

Ozubko

J.D.

Winocur

Moscovitch

(2014). How we forget may depend on how we remember. Trends in Cognitive Sciences, 18, 26–36.

41.

Schaal

N.K.

Banissy

M.J.

Lange

(2015). The rhythm span task: Comparing memory capacity for musical rhythms in musicians and non-musicians. Journal of New Music Research, 44, 3–10.

42.

Schellenberg

E.G.

(1996). Expectancy in melody: Tests of the implication-realization model. Cognition, 58, 75–125.

43.

Schellenberg

E.G.

Habashi

(2015). Remembering the melody and timbre, forgetting the key and tempo. Memory and Cognition, 43, 1021–1031.

44.

Schneider

(1997). “Verschmelzung”, tonal fusion, and consonance: Carl Stumpf revisited. In Leman

(Ed.), Music, gestalt, and computing: Studies in cognitive and systematic musicology. New York: Springer.

45.

Shepard

R.N.

Teghtsoonian

(1961). Retention of information under conditions approaching a steady-state. Journal of Experimental Psychology, 62, 302–309.

46.

Snodgrass

J.G.

Corwin

(1988). Pragmatics of measuring recognition memory: Applications to dementia and amnesia. Journal of Experimental Psychology-General, 117, 34–50.

47.

White

B.W.

(1960). Recognition of distorted melodies. American Journal of Psychology, 73, 100–107.

48.

Wilks

S.S.

(1938). The large-sample distribution of the likelihood ratio for testing composite hypotheses. The Annals of Mathematical Statistics, 9, 60–62.

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