Associative learning in humans — conditioning of sensory-evoked brain activity

Skrandies, Wolfgang; Jedynak, A.

doi:10.1016/s0166-4328(99)00096-0

Cited by 24 publications

(17 citation statements)

References 30 publications

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“…Pizzagalli et al (2003), for example, showed that fearful faces associated with an aversive outcome modulated early exogenous visual ERP components such as N1. They cited a number of other studies, such as that by Baas et al (2002), demonstrating aversive conditioning effects on early ERP components as well as studies demonstrating effects on later components such as P3 instead (e.g., Skrandies and Jedynak 2000). They interpreted the results from these studies, especially those revealing early effects, as ".…”

Section: Discussionmentioning

confidence: 99%

Irritancy Expectancy Alters Odor Perception: Evidence From Olfactory Event-Related Potential Research

Bulsing

Smeets

Gemeinhardt³

et al. 2010

Journal of Neurophysiology

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Bulsing PJ, Smeets MAM, Gemeinhardt C, Laverman M, Schuster B, Van den Hout MA, Hummel T. Irritancy expectancy alters odor perception: evidence from olfactory event-related potential research. J Neurophysiol 104: 2749 -2756, 2010. First published September 15, 2010 doi:10.1152/jn.00754.2009. The aim of the present research was to investigate the influences of cognition on temporal processing of olfactory information in a health-relevant context. We investigated whether expecting an odor to cause adverse health effects alters perception of that odor. An irritation-free odor (Study 1: H 2 S; Study 2: phenyl ethyl alcohol [PEA]) was presented after which participants expected to experience either adverse sensory irritation (caused by intranasal CO 2 presentation) in one condition or no adverse effects in another condition, depending on a previously presented visual cue. Olfactory event-related potentials (OERPs) were measured to assess effects of expectations on the temporal course of olfactory processing. When participants expected irritancy after perceiving the odor of H 2 S, N1 and P3 peak amplitude and N1 latency were increased and shortened, respectively, suggesting more intense and faster processing of the odor as well as effects on salience and anticipation of sensory irritation. When the odor was PEA, only the N1 amplitude was increased. These results, obtained with OERP, provide converging evidence for comparable conclusions regarding the influence of cognition on odor perception reached with functional magnetic resonance imaging. Furthermore, the results suggest that a priori hedonic valence of an odor affects how susceptible the olfactory percept is to modulation via expectations.

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Section: Discussionmentioning

confidence: 99%

Irritancy Expectancy Alters Odor Perception: Evidence From Olfactory Event-Related Potential Research

Bulsing

Smeets

Gemeinhardt³

et al. 2010

Journal of Neurophysiology

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“…The EEG was recorded from 30 electrodes covering the whole scalp (see Fig. 4); the bandpass was from 0.16 to 70 Hz, and a sampling rate of 500 Hz was employed; for further methodological details we refer to [18].…”

Section: An Application Of Wavelet Coherence To Experimental Datamentioning

confidence: 99%

Conventional and Wavelet Coherence Applied to Sensory–Evoked Electrical Brain Activity

Klein¹,

Sauer²,

Jedynak

et al. 2006

IEEE Trans. Biomed. Eng.

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Abstract-The use of coherence is a well-established standard approach for the analysis of biomedical signals. Being entirely based on frequency analysis, i.e., on spectral properties of the signal, it is not possible to obtain any information about the temporal structure of coherence which is useful in the study of brain dynamics, for example. Extending the concept of coherence as a measure of linear dependence between realizations of a random process to the wavelet transform, this paper introduces a new approach to coherence analysis which allows to monitor time-dependent changes in the coherence between electroenecphalographic (EEG) channels. Specifically, we analyzed multichannel EEG data of 26 subjects obtained in an experiment on associative learning, and compare the results of Fourier coherence and wavelet coherence, showing that wavelet coherence detects features that were inaccessible by application of Fourier coherence.

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“…To achieve this goal, we used associative learning (Mackintosh, 1975(Mackintosh, , 1983Mitchell, De Houwer, & Lovibond, 2009;Skrandies & Jedynak, 2000) to charge meaningless stimuli with a negative or positive value by systematically pairing them with a specific behavioral outcome, namely monetary loss or reward. By counterbalancing the pairing between specific stimulus groups and specific behavioral outcomes, we carefully controlled for the contribution of lowlevel properties and thus were able to isolate the influence of motivation on early sensory processing.…”

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confidence: 99%