Mark D. Humphries

发表

Theory, Simulations, and Experiments Optimal Time Scale for Spike-Time Reliability:

Mark D. Humphries, Louisa J. Steinberg, Jose L. Peña, 2015 .

A pulsed neural network model of bursting in the basal ganglia

Mark D. Humphries, Kevin N. Gurney, K. Gurney, 2001, Neural Networks.

A means to an end: Validating models by fitting experimental data

Mark D. Humphries, Kevin N. Gurney, 2007, Neurocomputing.

Signatures of optimal inference during learning in rat prefrontal cortex

Mark D. Humphries, Abhinav Singh, Adrien Peyrache, 2015 .

Prediction of Choice from Competing Mechanosensory and Choice-Memory Cues During Active Tactile Decision Making

Mark D. Humphries, Dario Campagner, Rasmus S. Petersen, 2018 .

Population-wide distributions of neural activity during perceptual decision-making

Mark D. Humphries, Christian K. Machens, Adrien Wohrer, 2013, Progress in neurobiology.

A robot model of the basal ganglia: Behavior and intrinsic processing

Mark D. Humphries, Peter Redgrave, Tony J. Prescott, 2006, Neural Networks.

User Manual for the Spiking Neuron Basal Ganglia Model

Mark D. Humphries, 2006 .

Dopamine-modulated dynamic cell assemblies generated by the GABAergic striatal microcircuit

Mark D. Humphries, Kevin N. Gurney, Ric Wood, 2009, Neural Networks.

How Degrading Networks Can Increase Cognitive Functions

Mark D. Humphries, Kevin N. Gurney, Christian Beste, 2012, ICANN.

BRAHMS: Novel middleware for integrated systems computation

Mark D. Humphries, Tony J. Prescott, Kevin N. Gurney, 2010, Adv. Eng. Informatics.

The Robot Basal Ganglia

Mark D. Humphries, Tony J. Prescott, Fernando Montes-Gonzalez, 2002 .

Basal Ganglia: Mechanisms for Action Selection

Mark D. Humphries, 2014, Encyclopedia of Computational Neuroscience.

Passive Dendrites Enable Single Neurons to Compute Linearly Non-separable Functions

Boris S. Gutkin, Mark D. Humphries, Romain D. Cazé, 2013, PLoS Comput. Biol..

Technical Integration of Hippocampus, Basal Ganglia and Physical Models for Spatial Navigation

Mark D. Humphries, Tony J. Prescott, Tamás Kiss, 2008, Front. Neuroinform..

Frontiers in Computational Neuroscience

Mark D. Humphries, Nathan F. Lepora, Kevin N. Gurney, 2022 .

Spectral estimation for detecting low-dimensional structure in networks using arbitrary null models

Mark D. Humphries, Abhinav Singh, Mat Evans, 2019, PloS one.

Dendrites enhance both single neuron and network computation

Mark D. Humphries, Romain D. Cazé, Boris Gutkin, 2014 .

The dual-route hypothesis: evaluating a neurocomputational model of fear conditioning in rats

Tom Ziemke, Mark D. Humphries, Robert Lowe, 2009, Connect. Sci..

Evidence for a probabilistic, brain-distributed, recursive mechanism for decision-making

Mark D. Humphries, Kevin Gurney, Javier A Caballero, 2016, bioRxiv.

Spiking and saturating dendrites differentially expand single neuron computation capacity

Boris S. Gutkin, Mark D. Humphries, Romain D. Cazé, 2012, NIPS.

The Interaction of Recurrent Axon Collateral Networks in the Basal Ganglia

Mark D. Humphries, Tony J. Prescott, Kevin N. Gurney, 2003, ICANN.

Is There an Integrative Center in the Vertebrate Brain-Stem? A Robotic Evaluation of a Model of the Reticular Formation Viewed as an Action Selection Device

Mark D. Humphries, Tony J. Prescott, Kevin N. Gurney, 2005, Adapt. Behav..

Task learning reveals signatures of sample-based internal 1 models in rodent prefrontal cortex

Mark D. Humphries, Abhinav Singh, Adrien Peyrache, 2016 .

Solution Methods for a New Class of Simple Model Neurons

Mark D. Humphries, Kevin N. Gurney, 2007, Neural Computation.

Modular Deconstruction Reveals the Dynamical and Physical Building Blocks of a Locomotion Motor Program

Mark D. Humphries, William N. Frost, Angela M. Bruno, 2015, Neuron.

Finding communities in sparse networks

Mark D. Humphries, Abhinav Singh, M. Humphries, 2015, Scientific Reports.

Distributed Action Selection by a Brainstem Neural Substrate: An Embodied Evaluation

Mark D. Humphries, Tony J. Prescott, T. Prescott, 2006, SAB.

Spectral rejection for testing hypotheses of structure in networks pdf

Mark D. Humphries, Abhinav Singh, Mat Evans, 2019, ArXiv.

A Probabilistic, Distributed, Recursive Mechanism for Decision-making in the Brain

Mark D. Humphries, Kevin Gurney, Javier A. Caballero, 2018 .

A probabilistic, distributed, recursive mechanism for decision-making in the brain

Mark D. Humphries, Kevin N. Gurney, Javier A. Caballero, 2018, PLoS Comput. Biol..

Dynamical networks: finding, measuring, and tracking neural population activity using network theory

Mark D. Humphries, 2017 .

Transient and steady-state selection in the striatal microcircuit

Mark D. Humphries, Kevin N. Gurney, Christian Beste, 2014, Front. Comput. Neurosci..

Author response: A spiral attractor network drives rhythmic locomotion

Mark D. Humphries, William N. Frost, Angela M. Bruno, 2017 .

Reconstructing the Three-Dimensional GABAergic Microcircuit of the Striatum

Mark D. Humphries, Kevin N. Gurney, Ric Wood, 2010, PLoS Comput. Biol..

On the use of calcium deconvolution algorithms in practical contexts

Mark D. Humphries, Mathew H. Evans, Rasmus S. Petersen, 2019, bioRxiv.

Making decisions in the dark basement of the brain: A look back at the GPR model of action selection and the basal ganglia

Mark D. Humphries, Kevin N. Gurney, K. Gurney, 2021, Biological Cybernetics.

Who dominates who in the dark basements of the brain?

Mark D. Humphries, Tony J. Prescott, 2007, Behavioral and Brain Sciences.

Medial prefrontal cortex population activity is plastic irrespective of learning

Mark D. Humphries, Adrien Peyrache, Abhinav Singh, 2018 .

Early hypersynchrony in juvenile PINK1−/− motor cortex is rescued by antidromic stimulation

Mark D. Humphries, Romain Carron, F. Michel, 2014, Front. Syst. Neurosci..

Independent population coding of the past and the present in prefrontal cortex during learning

Mark D. Humphries, Silvia Maggi, M. Humphries, 2019 .