A functional anatomical study of associative learning in humans.

Molchan, Susan E.; Sunderland, Trey; McIntosh, Anthony R.; Herscovitch, Peter; Schreurs, Bernard G.

doi:10.1073/pnas.91.17.8122

Cited by 257 publications

(188 citation statements)

References 37 publications

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“…Miller et al (2003) found an acquisition-related fMRI signal decrease in bilateral lobule VI in rabbits. Previous positron emission tomography (PET) studies in humans showed both increases of regional cerebral blood flow (rCBF; Blaxton et al, 1996;Parker et al, 2012) and glucose metabolism (Logan and Grafton, 1995), as well as decreases of rCBF (Molchan et al, 1994;Schreurs et al, 1997Schreurs et al, , 2001Parker et al, 2012). Based on the present findings the assessment time during the course of learning is crucial.…”

Section: Discussionmentioning

confidence: 99%

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Cerebellar Cortex and Cerebellar Nuclei Are Concomitantly Activated during Eyeblink Conditioning: A 7T fMRI Study in Humans

Thürling

Kahl²,

Maderwald

et al. 2015

J. Neurosci.

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There are controversies whether learning of conditioned eyeblink responses primarily takes place within the cerebellar cortex, the interposed nuclei, or both. It has also been suggested that the cerebellar cortex may be important during early stages of learning, and that there is a shift to the cerebellar nuclei during later stages. As yet, human studies have provided little to resolve this question. In the present study, we established a setup that allows ultra-high-field 7T functional magnetic resonance imaging (fMRI) of the cerebellar cortex and interposed cerebellar nuclei simultaneously during delay eyeblink conditioning in humans. Event-related fMRI signals increased concomitantly in the cerebellar cortex and nuclei during early acquisition of conditioned eyeblink responses in 20 healthy human subjects. ANOVAs with repeated-measures showed significant effects of time across five blocks of 20 conditioning trials in the cortex and nuclei (p Ͻ 0.05, permutation corrected). Activations were most pronounced in, but not limited to, lobules VI and interposed nuclei. Increased activations were most prominent at the first time the maximum number of conditioned responses was achieved. Our data are consistent with a simultaneous and synergistic two-site model of learning during acquisition of classically conditioned eyeblinks. Because increased MRI signal reflects synaptic activity, concomitantly increased signals in the cerebellar nuclei and cortex are consistent with findings of learning related potentiation at the mossy fiber to nuclear cell synapse and mossy fiber to granule cell synapse. Activity related to the expression of conditioned responses, however, cannot be excluded.

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Section: Discussionmentioning

confidence: 99%

“…PET studies suggest that partly overlapping areas in the cerebellar cortex support acquisition and extinction in humans (Schreurs et al, 1997(Schreurs et al, , 2001Parker et al, 2012). Our findings agree with these observations.…”

Section: Discussionmentioning

confidence: 99%

Cerebellar Cortex and Cerebellar Nuclei Are Concomitantly Activated during Eyeblink Conditioning: A 7T fMRI Study in Humans

Thürling

Kahl²,

Maderwald

et al. 2015

J. Neurosci.

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“…Most-extensively studied in the primary auditory cortex, associative representational plasticity has been reported for cortical metabolism (Gonzalez-Lima & Scheich, 1986a), receptive field properties (Bakin & Weinberger, 1990;Blake, Strata, Churchland, & Merzenich, 2002;Edeline, Neuenschwander-el Massioui, & Dutrieux, 1990;Gao & Suga, 2000) and tonotopic maps (Rutkowski & Weinberger, 2005) in animals, as well as in studies of human brain imaging (Molchan, Sunderland, McIntosh, Herscovitch, & Schreurs, 1994;Morris, Friston, & Dolan, 1998;reviewed in Weinberger 1995reviewed in Weinberger , 2004aPalmer, Nelson, & Lindley, 1998;Rauschecker, 2003;Buonomano & Merzenich, 1998). Learning-related plasticity in A1 develops in a wide range of tasks, including habituation (Condon &Weinberger, 1991), classical reward (Kisley & Gerstein, 2001) and aversive (Bakin & Weinberger, 1990) conditioning, instrumental reward (Blake et al, 2002) and avoidance (Bakin, South, & Weinberger, 1996) learning, category learning (Ohl, Scheich, & Freeman, 2001), long-term training in perceptual discrimination learning (Recanzone, Schreiner, & Merzenich, 1993), working memory (Brechmann et al, 2007;Sakurai, 1994), reference memory (Sakurai, 1994) and motor planning (Villa, Tetko, Hyland, & Najem, 1999).…”

Section: Introductionmentioning

confidence: 99%

Learning strategy determines auditory cortical plasticity

Berlau

Weinberger

2008

Neurobiology of Learning and Memory

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Learning modifies the primary auditory cortex (A1) to emphasize the processing and representation of behaviorally relevant sounds. However, the factors that determine cortical plasticity are poorly understood. While the type and amount of learning are assumed to be important, the actual strategies used to solve learning problems might be critical. To investigate this possibility, we trained two groups of adult male Sprague-Dawley rats to bar-press (BP) for water contingent on the presence of a 5.0 kHz tone using two different strategies: BP during tone presence or BP from tone-onset until receiving an error signal after tone cessation. Both groups achieved the same high levels of correct performance and both groups revealed equivalent learning of absolute frequency during training. Post-training terminal "mapping" of A1 showed no change in representational area of the tone signal frequency but revealed other substantial cuespecific plasticity that developed only in the tone-onset-to-error strategy group. Threshold was decreased ~10 dB and tuning bandwidth was narrowed by ~0.7 octaves. As sound onsets have greater perceptual weighting and cortical discharge efficacy than continual sound presence, the induction of specific learning-induced cortical plasticity may depend on the use of learning strategies that best exploit cortical proclivities. The present results also suggest a general principle for the induction and storage of plasticity in learning, viz., that the representation of specific acquired information may be selected by neurons according to a match between behaviorally selected stimulus features and circuit/network response properties.

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“…Most research on auditory plasticity involved rodents, cats, or nonhuman primates, but some related evidence comes from human neuroimaging studies, with PET (8,9) or functional (f) MRI (10). Here, we used magnetoencephalography (MEG) (11,12) to address human auditory plasticity in an aversive classicalconditioning paradigm (1)(2)(3), focusing on the well-known, successive, auditory-evoked field components P1m, N1m, and P2m (13,14).…”

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confidence: 99%

Plasticity of human auditory-evoked fields induced by shock conditioning and contingency reversal

Kluge

Bauer

Leff

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

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We used magnetoencephalography (MEG) to assess plasticity of human auditory cortex induced by classical conditioning and contingency reversal. Participants listened to random sequences of high or low tones. A first baseline phase presented these without further associations. In phase 2, one of the frequencies (CS + ) was paired with shock on half its occurrences, whereas the other frequency (CS − ) was not. In phase 3, the contingency assigning CS + and CS − was reversed. Conditioned pupil dilation was observed in phase 2 but extinguished in phase 3. MEG revealed that, during phase-2 initial conditioning, the P1m, N1m, and P2m auditory components, measured from sensors over auditory temporal cortex, came to distinguish between CS + and CS − . After contingency reversal in phase 3, the later P2m component rapidly reversed its selectivity (unlike the pupil response) but the earlier P1m did not, whereas N1m showed some new learning but not reversal. These results confirm plasticity of human auditory responses due to classical conditioning, but go further in revealing distinct constraints on different levels of the auditory hierarchy. The later P2m component can reverse affiliation immediately in accord with an updated expectancy after contingency reversal, whereas the earlier auditory components cannot. These findings indicate distinct cognitive and emotional influences on auditory processing.

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A functional anatomical study of associative learning in humans.

Cited by 257 publications

References 37 publications

Cerebellar Cortex and Cerebellar Nuclei Are Concomitantly Activated during Eyeblink Conditioning: A 7T fMRI Study in Humans

Cerebellar Cortex and Cerebellar Nuclei Are Concomitantly Activated during Eyeblink Conditioning: A 7T fMRI Study in Humans

Learning strategy determines auditory cortical plasticity

Plasticity of human auditory-evoked fields induced by shock conditioning and contingency reversal

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