Harnessing behavioral diversity to understand circuits for cognition
暂无分享,去创建一个
[1] Xiao-Jing Wang,et al. Task representations in neural networks trained to perform many cognitive tasks , 2019, Nature Neuroscience.
[2] Kevin R Coffey,et al. DeepSqueak: a deep learning-based system for detection and analysis of ultrasonic vocalizations , 2019, Neuropsychopharmacology.
[3] Hansem Sohn,et al. Bayesian Computation through Cortical Latent Dynamics , 2018, Neuron.
[4] Ji Hyun Bak,et al. Efficient inference for time-varying behavior during learning , 2018, NeurIPS.
[5] T. Fukai,et al. Neuronal stability in medial frontal cortex sets individual variability in decision-making , 2018, Nature Neuroscience.
[6] Carlos D. Brody,et al. From predictive models to cognitive models: An analysis of rat behavior in the two-armed bandit task , 2018, bioRxiv.
[7] Christopher Summerfield,et al. Comparing continual task learning in minds and machines , 2018, Proceedings of the National Academy of Sciences.
[8] Kevin M. Cury,et al. DeepLabCut: markerless pose estimation of user-defined body parts with deep learning , 2018, Nature Neuroscience.
[9] F. Helmchen,et al. Behavioral Strategy Determines Frontal or Posterior Location of Short-Term Memory in Neocortex , 2018, Neuron.
[10] David M. Schneider,et al. A cortical filter that learns to suppress the acoustic consequences of movement , 2018, Nature.
[11] Kathryn Bonnen,et al. Beyond Trial-Based Paradigms: Continuous Behavior, Ongoing Neural Activity, and Natural Stimuli , 2018, The Journal of Neuroscience.
[12] David Sussillo,et al. Computation through Cortical Dynamics , 2018, Neuron.
[13] Scott W. Linderman,et al. The Striatum Organizes 3D Behavior via Moment-to-Moment Action Selection , 2018, Cell.
[14] Mikhail Kislin,et al. Fast animal pose estimation using deep neural networks , 2018, Nature Methods.
[15] Razvan Pascanu,et al. Vector-based navigation using grid-like representations in artificial agents , 2018, Nature.
[16] Matthew T. Kaufman,et al. Movement-related activity dominates cortex during sensory-guided decision making , 2018, bioRxiv.
[17] Joel Z. Leibo,et al. Prefrontal cortex as a meta-reinforcement learning system , 2018, bioRxiv.
[18] Kenneth D. Harris,et al. Effects of Arousal on Mouse Sensory Cortex Depend on Modality , 2018, Cell reports.
[19] Xiao-Jing Wang,et al. A dataset and architecture for visual reasoning with a working memory , 2018, ECCV.
[20] Stephen M Fleming,et al. Neural mediators of changes of mind about perceptual decisions , 2018, Nature Neuroscience.
[21] Xue-Xin Wei,et al. Emergence of grid-like representations by training recurrent neural networks to perform spatial localization , 2018, ICLR.
[22] Devika Narain,et al. Flexible Sensorimotor Computations through Rapid Reconfiguration of Cortical Dynamics , 2018, Neuron.
[23] Anne E. Urai,et al. Choice history biases subsequent evidence accumulation , 2018, bioRxiv.
[24] P. Faure,et al. Social interactions impact on the dopaminergic system and drive individuality , 2017, bioRxiv.
[25] Devika Narain,et al. Flexible timing by temporal scaling of cortical responses , 2017, Nature Neuroscience.
[26] Surya Ganguli,et al. A theory of multineuronal dimensionality, dynamics and measurement , 2017, bioRxiv.
[27] D. Hassabis,et al. Neuroscience-Inspired Artificial Intelligence , 2017, Neuron.
[28] Il Memming Park,et al. Functional dissection of signal and noise in MT and LIP during decision-making , 2017, Nature Neuroscience.
[29] Anne E. Urai,et al. Pupil-linked arousal is driven by decision uncertainty and alters serial choice bias , 2017, Nature Communications.
[30] Adam Kepecs,et al. Midbrain Dopamine Neurons Signal Belief in Choice Accuracy during a Perceptual Decision , 2017, Current Biology.
[31] M. A. MacIver,et al. Neuroscience Needs Behavior: Correcting a Reductionist Bias , 2017, Neuron.
[32] Kenneth D. Harris,et al. High-Yield Methods for Accurate Two-Alternative Visual Psychophysics in Head-Fixed Mice , 2016, bioRxiv.
[33] Jan Drugowitsch,et al. Computational Precision of Mental Inference as Critical Source of Human Choice Suboptimality , 2016, Neuron.
[34] D. McCormick,et al. Pupil fluctuations track rapid changes in adrenergic and cholinergic activity in cortex , 2016, Nature Communications.
[35] Ari S. Morcos,et al. History-dependent variability in population dynamics during evidence accumulation in cortex , 2016, Nature Neuroscience.
[36] Robert P. Bonin,et al. Hypothalamic CRH neurons orchestrate complex behaviours after stress , 2016, Nature Communications.
[37] Christopher D. Harvey,et al. Recurrent Network Models of Sequence Generation and Memory , 2016, Neuron.
[38] Roozbeh Kiani,et al. Neural Mechanisms of Post-error Adjustments of Decision Policy in Parietal Cortex , 2016, Neuron.
[39] Ryan P. Adams,et al. Mapping Sub-Second Structure in Mouse Behavior , 2015, Neuron.
[40] Jessica A. Cardin,et al. Waking State: Rapid Variations Modulate Neural and Behavioral Responses , 2015, Neuron.
[41] Stephen V. David,et al. Cortical Membrane Potential Signature of Optimal States for Sensory Signal Detection , 2015, Neuron.
[42] Martin Gruebele,et al. The Behavioral Space of Zebrafish Locomotion and Its Neural Network Analog , 2015, PloS one.
[43] Matthew T. Kaufman,et al. A neural network that finds a naturalistic solution for the production of muscle activity , 2015, Nature Neuroscience.
[44] N. Parga,et al. Dynamic Control of Response Criterion in Premotor Cortex during Perceptual Detection under Temporal Uncertainty , 2015, Neuron.
[45] Mark M Churchland,et al. Vacillation, indecision and hesitation in moment-by-moment decoding of monkey motor cortex , 2015, eLife.
[46] Surya Ganguli,et al. On simplicity and complexity in the brave new world of large-scale neuroscience , 2015, Current Opinion in Neurobiology.
[47] Shane Legg,et al. Human-level control through deep reinforcement learning , 2015, Nature.
[48] Bingni W. Brunton,et al. Distinct relationships of parietal and prefrontal cortices to evidence accumulation , 2014, Nature.
[49] Martin Vinck,et al. Arousal and Locomotion Make Distinct Contributions to Cortical Activity Patterns and Visual Encoding , 2014, Neuron.
[50] Ian H. Stevenson,et al. Saliency and saccade encoding in the frontal eye field during natural scene search. , 2014, Cerebral cortex.
[51] George H. Denfield,et al. Pupil Fluctuations Track Fast Switching of Cortical States during Quiet Wakefulness , 2014, Neuron.
[52] David J. Anderson,et al. Toward a Science of Computational Ethology , 2014, Neuron.
[53] A. Koulakov,et al. Orbitofrontal Cortex Is Required for Optimal Waiting Based on Decision Confidence , 2014, Neuron.
[54] Joseph J. Paton,et al. Big behavioral data: psychology, ethology and the foundations of neuroscience , 2014, Nature Neuroscience.
[55] M. Stryker,et al. A Cortical Circuit for Gain Control by Behavioral State , 2014, Cell.
[56] William Bialek,et al. Mapping the stereotyped behaviour of freely moving fruit flies , 2013, Journal of The Royal Society Interface.
[57] W. Newsome,et al. Context-dependent computation by recurrent dynamics in prefrontal cortex , 2013, Nature.
[58] P. Golshani,et al. Cellular mechanisms of brain-state-dependent gain modulation in visual cortex , 2013, Nature Neuroscience.
[59] David Raposo,et al. Dynamic weighting of multisensory stimuli shapes decision-making in rats and humans. , 2013, Journal of vision.
[60] Bingni W. Brunton,et al. Rats and Humans Can Optimally Accumulate Evidence for Decision-Making , 2013, Science.
[61] Markus Knaden,et al. A Conserved Dedicated Olfactory Circuit for Detecting Harmful Microbes in Drosophila , 2012, Cell.
[62] David Raposo,et al. Multisensory Decision-Making in Rats and Humans , 2012, The Journal of Neuroscience.
[63] E. Nestler,et al. Neurobiology of resilience , 2011, Nature Neuroscience.
[64] Christopher R Fetsch,et al. Neural correlates of reliability-based cue weighting during multisensory integration , 2011, Nature Neuroscience.
[65] Jeffrey C. Erlich,et al. A Cortical Substrate for Memory-Guided Orienting in the Rat , 2011, Neuron.
[66] M. Stryker,et al. Modulation of Visual Responses by Behavioral State in Mouse Visual Cortex , 2010, Neuron.
[67] Allan V. Kalueff,et al. Understanding behavioral and physiological phenotypes of stress and anxiety in zebrafish , 2009, Behavioural Brain Research.
[68] J. Maunsell,et al. Attention improves performance primarily by reducing interneuronal correlations , 2009, Nature Neuroscience.
[69] Marcelo A. Wood,et al. Automated scoring of fear-related behavior using EthoVision software , 2009, Journal of Neuroscience Methods.
[70] Greg J. Stephens,et al. Dimensionality and Dynamics in the Behavior of C. elegans , 2007, PLoS Comput. Biol..
[71] Justin L. Vincent,et al. Intrinsic Fluctuations within Cortical Systems Account for Intertrial Variability in Human Behavior , 2007, Neuron.
[72] J. Gold,et al. The neural basis of decision making. , 2007, Annual review of neuroscience.
[73] J. O'Doherty,et al. Model‐Based fMRI and Its Application to Reward Learning and Decision Making , 2007, Annals of the New York Academy of Sciences.
[74] David J. Freedman,et al. Experience-dependent representation of visual categories in parietal cortex , 2006, Nature.
[75] C. Petersen,et al. Correlating whisker behavior with membrane potential in barrel cortex of awake mice , 2006, Nature Neuroscience.
[76] G. Buzsáki,et al. Neuronal Oscillations in Cortical Networks , 2004, Science.
[77] Z. Mainen,et al. Speed and accuracy of olfactory discrimination in the rat , 2003, Nature Neuroscience.
[78] M. Shadlen,et al. Response of Neurons in the Lateral Intraparietal Area during a Combined Visual Discrimination Reaction Time Task , 2002, The Journal of Neuroscience.
[79] M. Nader,et al. Social dominance in monkeys: dopamine D2 receptors and cocaine self-administration , 2002, Nature Neuroscience.
[80] E. Fetz. Movement control: Are movement parameters recognizably coded in the activity of single neurons? , 1992 .
[81] A. Doupe,et al. Song-selective auditory circuits in the vocal control system of the zebra finch. , 1991, Proceedings of the National Academy of Sciences of the United States of America.
[82] Richard A. Andersen,et al. A back-propagation programmed network that simulates response properties of a subset of posterior parietal neurons , 1988, Nature.
[83] E. Hess,et al. Pupil Size in Relation to Mental Activity during Simple Problem-Solving , 1964, Science.
[84] E. Hess,et al. Pupil Size as Related to Interest Value of Visual Stimuli , 1960, Science.