Frontal Networks for Learning and Executing Arbitrary Stimulus-Response Associations

Department of Psychology, University of California, Berkeley, Berkeley, California, United States
The Journal of Neuroscience : The Official Journal of the Society for Neuroscience (Impact Factor: 6.34). 04/2005; 25(10):2723-32. DOI: 10.1523/JNEUROSCI.3697-04.2005
Source: PubMed

ABSTRACT Flexible rule learning, a behavior with obvious adaptive value, is known to depend on an intact prefrontal cortex (PFC). One simple, yet powerful, form of such learning consists of forming arbitrary stimulus-response (S-R) associations. A variety of evidence from monkey and human studies suggests that the PFC plays an important role in both forming new S-R associations and in using learned rules to select the contextually appropriate response to a particular stimulus cue. Although monkey lesion studies more strongly implicate the ventrolateral PFC (vlPFC) in S-R learning, clinical data and neurophysiology studies have implicated both the vlPFC and the dorsolateral region (dlPFC) in associative rule learning. Previous human imaging studies of S-R learning tasks, however, have not demonstrated involvement of the dlPFC. This may be because of the design of previous imaging studies, which used few stimuli and used explicitly stated one-to-one S-R mapping rules that were usually practiced before scanning. Humans learn these rules very quickly, limiting the ability of imaging techniques to capture activity related to rule acquisition. To address these issues, we performed functional magnetic resonance imaging while subjects learned by trial and error to associate sets of abstract visual stimuli with arbitrary manual responses. Successful learning of this task required discernment of a categorical type of S-R rule in a block design expected to yield sustained rule representation. Our results show that distinct components of the dorsolateral, ventrolateral, and anterior PFC, lateral premotor cortex, supplementary motor area, and the striatum are involved in learning versus executing categorical S-R rules.

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Available from: Charlotte A Boettiger, Sep 28, 2015
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    • "Previous research suggests that functions discussed above might also apply to the right caudate nucleus. Specifically, it might have been involved in representing S–R rules (Toni and Passingham 1999; Passingham et al. 2000; Toni et al. 2001; Boettiger and D'Esposito 2005) and/or selecting (Schumacher et al. 2003; Gerardin et al. 2004; Wager et al. 2005; van Eimeren et al. 2006; Amiez et al. 2012) and reprogramming (Mars et al. 2007) the relevant response appropriate to the target. These possible functions would be relied on less during CON compared with INC trials. "
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    ABSTRACT: Unconscious visuomotor priming defined as the advantage in reaction time (RT) or accuracy for target shapes mapped to the same (congruent condition) when compared with a different (incongruent condition) motor response as a preceding subliminally presented prime shape has been shown to modulate activity within a visuomotor network comprised of parietal and frontal motor areas in previous functional magnetic resonance imaging (fMRI) studies. The present fMRI study investigated whether, in addition to changes in brain activity, unconscious visuomotor priming results in a modulation of functional connectivity profiles. Activity associated with congruent compared with incongruent trials was lower in the bilateral inferior and medial superior frontal gyri, in the inferior parietal lobules, and in the right caudate nucleus and adjacent portions of the thalamus. Functional connectivity increased under congruent relative to incongruent conditions between ventral visual stream areas (e.g., calcarine, fusiform, and lingual gyri), the precentral gyrus, the supplementary motor area, posterior parietal areas, the inferior frontal gyrus, and the caudate nucleus. Our findings suggest that an increase in coupling between visuomotor regions, reflecting higher efficiency of processing, is an important neural mechanism underlying unconscious visuomotor priming, in addition to changes in the magnitude of activation. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail:
    Cerebral Cortex 04/2015; DOI:10.1093/cercor/bhv070 · 8.67 Impact Factor
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    • "The neural generator of the pP was localized in the anterior Insula in a study combining fMRI and ERP data collected with the same task used in the present study (Di Russo et al., 2013b), and its function would be to trigger the response when enough information are accumulated. Other studies showed that insular activation indicates the stimulus-response (S-R) association to guide response selection (Boettiger and Dand’Esposito, 2005), and reflects both self and motor awareness (Berti et al., 2005). In the present study, we additionally adopted the subtraction method to better focus on the pP modulation on prefrontal sites: the main risk of this procedure is to compare different activities acting in the same period. "
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    ABSTRACT: The study investigates the neurocognitive stages involved in the speed-accuracy trade-off (SAT). Contrary to previous approach, we did not manipulate speed and accuracy instructions: participants were required to be fast and accurate in a go/no-go task, and we selected post-hoc the groups based on the subjects' spontaneous behavioral tendency. Based on the reaction times, we selected the fast and slow groups (Speed-groups), and based on the percentage of false alarms, we selected the accurate and inaccurate groups (Accuracy-groups). The two Speed-groups were accuracy-matched, and the two Accuracy-groups were speed-matched. High density electroencephalographic (EEG) and stimulus-locked analyses allowed us to observe group differences both before and after the stimulus onset. Long before the stimulus appearance, the two Speed-groups showed different amplitude of the Bereitschaftspotential (BP), reflecting the activity of the supplementary motor area (SMA); by contrast, the two Accuracy-groups showed different amplitude of the prefrontal negativity (pN), reflecting the activity of the right prefrontal cortex (rPFC). In addition, the post-stimulus event-related potential (ERP) components showed differences between groups: the P1 component was larger in accurate than inaccurate group; the N1 and N2 components were larger in the fast than slow group; the P3 component started earlier and was larger in the fast than slow group. The go minus no-go subtractive wave enhancing go-related processing revealed a differential prefrontal positivity (dpP) that peaked at about 330 ms; the latency and the amplitude of this peak were associated with the speed of the decision process and the efficiency of the stimulus-response mapping, respectively. Overall, data are consistent with the view that speed and accuracy are processed by two interacting but separate neurocognitive systems, with different features in both the anticipation and the response execution phases.
    Frontiers in Behavioral Neuroscience 07/2014; 8(251). DOI:10.3389/fnbeh.2014.00251 · 3.27 Impact Factor
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    • "In our experiment, we demonstrated that (i) DS does not mediate early feedback-based stimulus–response learning but is implicated in performing response decisions, and (ii) VS underlies stimulus–response association learning. Our findings challenge the claim that DS mediates stimulus–response learning via feedback (Balleine et al., 2009; Boettiger and D'Esposito, 2005; Brovelli et al., 2011; Brown and Stern, 2013; Foerde et al., 2013; Garrison et al., 2013; Hart et al., 2014), and recast it as a brain region mediating decision making, integrating with a growing literature supporting this view (Atallah et al., 2007; Grahn et al., 2008; Jessup and O'Doherty, 2011; MacDonald et al., 2014; McDonald and Hong, 2004; Postle and D'Esposito, 1999; Smittenaar et al., 2012). "
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    ABSTRACT: Cognitive deficits are recognized in Parkinson's disease. Understanding cognitive functions mediated by the striatum can clarify some of these impairments and inform treatment strategies. The dorsal striatum, a region impaired in Parkinson's disease, has been implicated in stimulus-response learning. However, most investigations combine acquisition of associations between stimuli, responses, or outcomes (i.e., learning) and expression of learning through response selection and decision enactment, confounding these separate processes. Using neuroimaging, we provide evidence that dorsal striatum does not mediate stimulus-response learning from feedback but rather underlies decision making once associations between stimuli and responses are learned. In the experiment, 11 males and 5 females (mean age 22) learned to associate abstract images to specific button-press responses through feedback in Session 1. In Session 2, they were asked to provide responses learned in Session 1. Feedback was omitted, precluding further feedback-based learning in this session. Using functional magnetic resonance imaging, dorsal striatum activation in healthy young participants was observed at the time of response selection and not during feedback, when greatest learning presumably occurs. Moreover, dorsal striatum activity increased across the duration of Session 1, peaking after most associations were well learned and was significant during Session 2 where no feedback was provided, and therefore no feedback-based learning occurred. Preferential ventral striatum activity occurred during feedback and was maximal early in Session 1. Taken together, the results suggest that the ventral striatum underlies learning associations between stimuli and responses via feedback whereas the dorsal striatum mediates enacting decisions.
    NeuroImage 07/2014; 101. DOI:10.1016/j.neuroimage.2014.07.013 · 6.36 Impact Factor
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