| scholarly article | Q13442814 |
| P8978 | DBLP publication ID | journals/cin/HerdKKHHO13 |
| P356 | DOI | 10.1155/2013/149329 |
| P932 | PMC publication ID | 3722785 |
| P698 | PubMed publication ID | 23935605 |
| P5875 | ResearchGate publication ID | 255736357 |
| P50 | author | Randall C. O'Reilly | Q7291520 |
| Tsung-Ren Huang | Q59701314 | ||
| P2093 | author name string | Thomas E Hazy | |
| Seth A Herd | |||
| Kai A Krueger | |||
| Trenton E Kriete | |||
| P2860 | cites work | Clever animals and killjoy explanations in comparative psychology | Q50674720 |
| Computational models for the combination of advice and individual learning. | Q51939718 | ||
| Solving the credit assignment problem: explicit and implicit learning of action sequences with probabilistic outcomes. | Q51988427 | ||
| A neural substrate of prediction and reward | Q27860851 | ||
| PVLV: The Primary Value and Learned Value Pavlovian Learning Algorithm | Q28058176 | ||
| Specific impairments of planning | Q28260771 | ||
| A model of perceptual classification in children and adults | Q28284819 | ||
| Bilinearity, rules, and prefrontal cortex | Q28757307 | ||
| Parallel Organization of Functionally Segregated Circuits Linking Basal Ganglia and Cortex | Q29391304 | ||
| The role of the basal ganglia in habit formation | Q29619829 | ||
| The prefrontal cortex and cognitive control | Q34185482 | ||
| Effort-based cost-benefit valuation and the human brain | Q34194322 | ||
| Re-evaluating the role of the orbitofrontal cortex in reward and reinforcement. | Q34225763 | ||
| An integrated theory of the mind | Q34358520 | ||
| Dynamic dopamine modulation in the basal ganglia: a neurocomputational account of cognitive deficits in medicated and nonmedicated Parkinsonism | Q34392452 | ||
| How instructed knowledge modulates the neural systems of reward learning | Q34471653 | ||
| Making working memory work: a computational model of learning in the prefrontal cortex and basal ganglia. | Q34479655 | ||
| Actor-critic models of the basal ganglia: new anatomical and computational perspectives | Q34951552 | ||
| Reward, motivation, and reinforcement learning | Q34970684 | ||
| Tracking the emergence of conceptual knowledge during human decision making | Q35004964 | ||
| Neural mechanisms of acquired phasic dopamine responses in learning | Q35014907 | ||
| Modulation of the feedback-related negativity by instruction and experience | Q35571364 | ||
| Reward, memory and substance abuse: functional neuronal circuits in the nucleus accumbens. | Q35690512 | ||
| From an executive network to executive control: a computational model of the n-back task. | Q35716765 | ||
| Contextual encoding by ensembles of medial prefrontal cortex neurons. | Q35882354 | ||
| Banishing the homunculus: making working memory work | Q36339058 | ||
| Anatomy of a decision: striato-orbitofrontal interactions in reinforcement learning, decision making, and reversal | Q36459408 | ||
| The short-latency dopamine signal: a role in discovering novel actions? | Q36657815 | ||
| Recurrent Processing during Object Recognition | Q36729871 | ||
| Orbitofrontal cortex and its contribution to decision-making | Q36785109 | ||
| Role of the lateral prefrontal cortex in executive behavioral control | Q37056965 | ||
| Task set and prefrontal cortex | Q37193036 | ||
| Behavioural evidence for mental time travel in nonhuman animals | Q37644796 | ||
| Computational models of cognitive control | Q37698799 | ||
| Decision making and reward in frontal cortex: complementary evidence from neurophysiological and neuropsychological studies. | Q37870914 | ||
| Towards an executive without a homunculus: computational models of the prefrontal cortex/basal ganglia system | Q39605574 | ||
| Phasic nucleus accumbens dopamine release encodes effort- and delay-related costs. | Q39875248 | ||
| Instructional control of reinforcement learning: a behavioral and neurocomputational investigation | Q42038378 | ||
| Task rules, working memory, and fluid intelligence | Q42573924 | ||
| By carrot or by stick: cognitive reinforcement learning in parkinsonism | Q45140702 | ||
| Mapping the network for planning: a correlational PET activation study with the Tower of London task | Q48101173 | ||
| The Tower of London: the impact of instructions, cueing, and learning on planning abilities | Q48171297 | ||
| Temporal difference models and reward-related learning in the human brain | Q48323612 | ||
| Hypothalamic neuron involvement in integration of reward, aversion, and cue signals | Q48324670 | ||
| Categorization of behavioural sequences in the prefrontal cortex | Q48331115 | ||
| Frontostriatal system in planning complexity: a parametric functional magnetic resonance version of Tower of London task. | Q48383724 | ||
| Interactions between frontal cortex and basal ganglia in working memory: a computational model. | Q48432343 | ||
| Successful verbal encoding into episodic memory engages the posterior hippocampus: a parametrically analyzed functional magnetic resonance imaging study. | Q48519649 | ||
| Tuning in to the temporal dynamics of brain activation using functional magnetic resonance imaging (fMRI). | Q48660881 | ||
| Reactivity of limbic neurons of the monkey to appetitive and aversive signals. | Q48834286 | ||
| The role of the striatum and hippocampus in planning: a PET activation study in Parkinson's disease. | Q48891136 | ||
| P275 | copyright license | Creative Commons Attribution 3.0 Unported | Q14947546 |
| P6216 | copyright status | copyrighted | Q50423863 |
| P921 | main subject | cognitive neuroscience | Q1138951 |
| P304 | page(s) | 149329 | |
| P577 | publication date | 2013-07-08 | |
| P1433 | published in | Computational Intelligence and Neuroscience | Q15766432 |
| P1476 | title | Strategic cognitive sequencing: a computational cognitive neuroscience approach | |
| P478 | volume | 2013 |
| Q40726604 | The parietal cortex in sensemaking: the dissociation of multiple types of spatial information |
| Q28595812 | Toward an Integration of Deep Learning and Neuroscience |
| Q41009513 | Towards neuro-inspired symbolic models of cognition: linking neural dynamics to behaviors through asynchronous communications |
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