J. Krichmar

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Evolutionary robotics: The biology, intelligence, and technology of self-organizing machines

Jeffrey L. Krichmar, J. Krichmar, 2001, Complex..

Thermodynamic Computing pdf

Christof Teuscher, James P. Crutchfield, Seth Lloyd, 2019, ArXiv.

Principles Underlying the Construction of Brain-Based Devices

G. Edelman, J. Krichmar, 2006 .

Neuromodulatory Systems and Their Interactions: A Review of Models, Theories, and Experiments

Michael C. Avery, J. Krichmar, 2017, Front. Neural Circuits.

Machine Psychology : Autonomous Behavior , Perceptual Categorization and Conditioning in a Brain-based Device

W. M. Keck, G. Edelman, J. Krichmar, 2002 .

Visual binding through reentrant connectivity and dynamic synchronization in a brain-based device.

G. Edelman, A. Seth, J. Krichmar, 2004, Cerebral cortex.

Title An efficient automated parameter tuning framework for spiking neural networks

Kristofor D. Carlson, J. Krichmar, N. Dutt, 2014 .

Spatiotemporal processing of whisker input supports texture discrimination by a brain-based device

G. Edelman, A. Seth, J. Krichmar, 2004 .

A cerebellar model for predictive motor control tested in a brain-based device.

Gerald M Edelman, Jeffrey L McKinstry, Jeffrey L Krichmar, 2006, Proceedings of the National Academy of Sciences of the United States of America.

Experience-Dependent Perceptual Categorization in a Behaving Real-World Device

G. Edelman, O. Sporns, J. Krichmar, 2000 .

Retrospective and prospective responses arising in a modeled hippocampus during maze navigation by a brain-based device

G. Edelman, J. Gally, J. Krichmar, 2007, Proceedings of the National Academy of Sciences.

Spatial navigation and causal analysis in a brain-based device modeling cortical-hippocampal interactions

Jeffrey L. Krichmar, Anil K. Seth, Jason Fleischer, 2007, Neuroinformatics.

Attention-Based Structural-Plasticity

Praveen K. Pilly, Nicholas A. Ketz, J. Krichmar, 2019, 1903.06070.

NEUROROBOTICS: NEUROBIOLOGICALLY INSPIRED ROBOTS

J. Krichmar, 2016 .

Design principles for biologically inspired cognitive robotics

J. Krichmar, 2012, BICA 2012.

Sensory integration and remapping in a model of the medial temporal lobe during maze navigation by a brain-based device.

J. Krichmar, Jason Fleischer, 2007, Journal of integrative neuroscience.

Visual response properties of MSTd emerge from a sparse population code

J. Krichmar, N. Dutt, M. Beyeler, 2017, 1702.06665.

Neuromodulation and time-dependent plasticity in a model of foraging behavior

J. Krichmar, 2008, 2008 7th IEEE International Conference on Development and Learning.

Investigation of Biases and Compensatory Strategies Using a Probabilistic Variant of the Wisconsin Card Sorting Test

Alexis B. Craig, Matthew E. Phillips, J. Krichmar, 2016, Front. Psychol..

Title Learning touch preferences with a tactile robot using dopamine modulated STDP in a model of insular cortex Permalink

Liam D. Bucci, J. Krichmar, Ting-Shuo Chou, 2015 .

Effects of dendritic morphology on CA3 pyramidal cell electrophysiology: a simulation study

Stuart D. Washington, G. Ascoli, J. Krichmar, 2002, Brain Research.

A Proposal for a Decade of the Mind Initiative

Giulio Tononi, Gordon M Shepherd, James S Albus, 2007, Science.

UC Irvine UC Irvine Previously Published Works Title An efficient automated parameter tuning framework for spiking neural networks

Kristofor D. Carlson, J. Krichmar, N. Dutt, 2014 .

Effects of β-Catenin on Dendritic Morphology and Simulated Firing Patterns in Cultured Hippocampal Neurons

G. Ascoli, J. Krichmar, David Velasquez, 2006, The Biological Bulletin.

Merced Proceedings of the Annual Meeting of the Cognitive Science Society Title Modeling individual differences in socioeconomic game playing Permalink

Derrik E. Asher, M. Lee, J. Krichmar, 2012 .

Models of Neuromodulation

Michael C. Avery, J. Krichmar, 2017 .

A model of proactive and reactive cognitive control with anterior cingulate cortex and the neuromodulatory system

Suhas E. Chelian, Matthias D. Ziegler, R. O’Reilly, 2014, BICA 2014.

pathway and its influence on attention and learning Learning to ignore : A modeling study of a decremental cholinergic

A. Chiba, J. Krichmar, D. Nitz, 2014 .

Visual Data Mining of Brain CellsJ

G. Ascoli, J. Krichmar, urgen Symanzik, 1999 .

Adaptive Robot Path Planning Using a Spiking Neuron Algorithm With Axonal Delays

Jeffrey L. Krichmar, Nicolas Oros, Tiffany Hwu, 2018, IEEE Transactions on Cognitive and Developmental Systems.

Neuromorphic and Brain-Based Robots Trends and Perspectives

J. Krichmar, H. Wagatsuma, 2010 .

Design Principles for Neurorobotics

J. Krichmar, Tiffany Hwu, 2022, Frontiers in Neurorobotics.

A Theoretical Framework for Inference Learning

Beren Millidge, J. Krichmar, E. Neftci, 2022, NeurIPS.

computer interaction with simulated adapting agents − Social contracts and human

Derrik E. Asher, Alexis B. Craig, A. Brewer, 2013 .

Effects of beta-catenin on dendritic morphology and simulated firing patterns in cultured hippocampal neurons.

G. Ascoli, J. Krichmar, David Velasquez, 2006, The Biological bulletin.

Generation, description and storage of dendritic morphology data.

G A Ascoli, J L Krichmar, S J Nasuto, 2001, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

CARLsim 6: An Open Source Library for Large-Scale, Biologically Detailed Spiking Neural Network Simulation

Eric O. Scott, J. Krichmar, N. Dutt, 2022, 2022 International Joint Conference on Neural Networks (IJCNN).

Dynamic Reliability Management in Neuromorphic Computing

Nagarajan Kandasamy, Nikil D. Dutt, Francky Catthoor, 2021, ACM J. Emerg. Technol. Comput. Syst..

Enabling Resource-Aware Mapping of Spiking Neural Networks via Spatial Decomposition

Nagarajan Kandasamy, Francky Catthoor, Nikil Dutt, 2021, IEEE Embedded Systems Letters.

Linking global top-down views to first-person views in the brain

Elizabeth R. Chrastil, J. Krichmar, D. Nitz, 2022, Proceedings of the National Academy of Sciences of the United States of America.

Sparse Representations for Object- and Ego-Motion Estimations in Dynamic Scenes

Jeffrey L. Krichmar, Charless C. Fowlkes, Charless Fowlkes, 2020, IEEE Transactions on Neural Networks and Learning Systems.

Neural correlates of sparse coding and dimensionality reduction

Nikil Dutt, Michael Beyeler, Kristofor D. Carlson, 2019, PLoS Comput. Biol..

Making BREAD: Biomimetic Strategies for Artificial Intelligence Now and in the Future

Jeffrey L. Krichmar, William M. Severa, William Severa, 2018, Front. Neurosci..

3D Visual Response Properties of MSTd Emerge from an Efficient, Sparse Population Code

Nikil Dutt, Michael Beyeler, Jeffrey L Krichmar, 2016, The Journal of Neuroscience.

Neuromorphic and Brain-Based Robots: Neuromorphic robots: biologically and neurally inspired designs

Jeffrey L. Krichmar, Hiroaki Wagatsuma, J. Krichmar, 2011 .

A self-driving robot using deep convolutional neural networks on neuromorphic hardware

Jeffrey L. Krichmar, Nicolas Oros, Tiffany Hwu, 2016, 2017 International Joint Conference on Neural Networks (IJCNN).

Large-Scale Spiking Neural Networks using Neuromorphic Hardware Compatible Models

Nikil D. Dutt, Jeffrey L. Krichmar, Philippe Coussy, 2015, ACM J. Emerg. Technol. Comput. Syst..

Categorization and decision-making in a neurobiologically plausible spiking network using a STDP-like learning rule

Nikil D. Dutt, Jeffrey L. Krichmar, Michael Beyeler, 2013, Neural Networks.

Investigation of autistic traits through strategic decision-making in games with adaptive agents

Jeffrey L. Krichmar, Alexis B. Craig, J. Krichmar, 2017, Scientific Reports.

CARLsim 3: A user-friendly and highly optimized library for the creation of neurobiologically detailed spiking neural networks

Nikil D. Dutt, Jeffrey L. Krichmar, Ting-Shuo Chou, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

GPGPU accelerated simulation and parameter tuning for neuromorphic applications

Nikil D. Dutt, Jeffrey L. Krichmar, Michael Beyeler, 2014, 2014 19th Asia and South Pacific Design Automation Conference (ASP-DAC).

Endurance-Aware Mapping of Spiking Neural Networks to Neuromorphic Hardware

Nagarajan Kandasamy, Francky Catthoor, Nikil Dutt, 2021, IEEE Transactions on Parallel and Distributed Systems.

Mapping Spiking Neural Networks to Neuromorphic Hardware

Nikil D. Dutt, Giacomo Indiveri, Jeffrey L. Krichmar, 2019, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

CARLsim 4: An Open Source Library for Large Scale, Biologically Detailed Spiking Neural Network Simulation using Heterogeneous Clusters

Nikil D. Dutt, Jeffrey L. Krichmar, Ting-Shuo Chou, 2018, 2018 International Joint Conference on Neural Networks (IJCNN).

A Neurobiological Schema Model for Contextual Awareness in Robotics

Jeffrey L. Krichmar, Hirak J. Kashyap, Tiffany Hwu, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

Neurorobots as a Means Toward Neuroethology and Explainable AI

Jeffrey L. Krichmar, Xinyun Zou, Kexin Chen, 2020, Frontiers in Neurorobotics.

Sparse coding and dimensionality reduction in cortex

Nikil Dutt, Jeffrey L. Krichmar, Kristofor D. Carlson, 2017, bioRxiv.

Neuromodulated attention and goal-driven perception in uncertain domains

Soheil Kolouri, Xinyun Zou, Praveen K. Pilly, 2020, Neural Networks.

Brain-Based Devices for the Study of Nervous Systems and the Development of Intelligent Machines

Jeffrey L. Krichmar, Gerald M. Edelman, G. Edelman, 2005, Artificial Life.

A Recurrent Neural Network Based Model of Predictive Smooth Pursuit Eye Movement in Primates

Nikil D. Dutt, Jeffrey L. Krichmar, Emre Neftci, 2018, 2018 International Joint Conference on Neural Networks (IJCNN).

Interactions between the neuromodulatory systems and the amygdala: exploratory survey using the Allen Mouse Brain Atlas

Jeffrey L. Krichmar, Andrew Zaldivar, J. Krichmar, 2012, Brain Structure and Function.

Biological underpinnings for lifelong learning machines

Praveen K. Pilly, Nicholas A. Ketz, J. Clune, 2022, Nature Machine Intelligence.

A neurorobotic platform to test the influence of neuromodulatory signaling on anxious and curious behavior

Jeffrey L. Krichmar, J. Krichmar, 2013, Front. Neurorobot..

A neurally controlled robot competes and cooperates with humans in Segway soccer

Jeffrey L. Krichmar, Jason Fleischer, Botond Szatmáry, 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

A GPU-accelerated cortical neural network model for visually guided robot navigation

Nikil D. Dutt, Jeffrey L. Krichmar, Michael Beyeler, 2015, Neural Networks.

Mechanisms underlying the basal forebrain enhancement of top‐down and bottom‐up attention

Nikil Dutt, Michael C. Avery, Jeffrey L Krichmar, 2014, The European journal of neuroscience.

Learning to ignore: A modeling study of a decremental cholinergic pathway and its influence on attention and learning

Nicolas Oros, Jeffrey L Krichmar, Douglas A Nitz, 2014, Learning & memory.

Spiking neuron model of basal forebrain enhancement of visual attention

Nikil D. Dutt, Jeffrey L. Krichmar, Michael C. Avery, 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

Embodied models of delayed neural responses: Spatiotemporal categorization and predictive motor control in brain based devices

Jeffrey L. Krichmar, Anil K. Seth, Gerald M. Edelman, 2008, Neural Networks.

Active Sensing of Visual and Tactile Stimuli by Brain-based Devices

Jeffrey L. Krichmar, Anil K. Seth, Gerald M. Edelman, 2004, Int. J. Robotics Autom..

Texture discrimination by an autonomous mobile brain-based device with whiskers

Jeffrey L. Krichmar, Anil K. Seth, Gerald M. Edelman, 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

Improper activation of D1 and D2 receptors leads to excess noise in prefrontal cortex

Jeffrey L. Krichmar, Michael C. Avery, J. Krichmar, 2015, Front. Comput. Neurosci..

A large-scale neural network model of the influence of neuromodulatory levels on working memory and behavior

Nikil D. Dutt, Jeffrey L. Krichmar, Michael C. Avery, 2013, Front. Comput. Neurosci..

Modeling Uncertainty-Seeking Behavior Mediated by Cholinergic Influence on Dopamine

Jeffrey L. Krichmar, Marwen Belkaid, J. Krichmar, 2019, bioRxiv.

Merging information in the entorhinal cortex: what can we learn from robotics experiments and modeling?

Philippe Gaussier, Mathias Quoy, Francesca Sargolini, 2019, Journal of Experimental Biology.

Visual binding, reentry, and neuronal synchrony ina physically situated brain-based device

Jeffrey L. Krichmar, Anil K. Seth, Gerald M. Edelman, 2003 .

A Computational Model for Spatial Navigation Based on Reference Frames in the Hippocampus, Retrosplenial Cortex, and Posterior Parietal Cortex

Jeffrey L. Krichmar, Florian Röhrbein, Timo Oess, 2017, Front. Neurorobot..

A Model of Cerebellar Saccadic Motor Learning Using Qualitative Reasoning

Lawrence Hunter, Jeffrey L. Krichmar, Giorgio A. Ascoli, 1997, IWANN.

The Importance of Lateral Connections in the Parietal Cortex for Generating Motor Plans

Jeffrey L. Krichmar, Derrik E. Asher, Nicolas Oros, 2015, PloS one.

Top-Down Executive Control Drives Reticular-Thalamic Inhibition and Relays Cortical Information in a Large-Scale Neurocognitive Model

Jeffrey L. Krichmar, Michael C. Avery, Rajan Bhattacharyya, 2013, FLAIRS.

Effect of neuromodulation on performance in game playing: A modeling study

Jeffrey L. Krichmar, Andrew Zaldivar, Derrik E. Asher, 2010, 2010 IEEE 9th International Conference on Development and Learning.

Efficient simulation of large-scale Spiking Neural Networks using CUDA graphics processors

Nikil D. Dutt, Alexander V. Veidenbaum, Alexandru Nicolau, 2009, 2009 International Joint Conference on Neural Networks.

Efficient Spiking Neural Network Model of Pattern Motion Selectivity in Visual Cortex

Nikil D. Dutt, Jeffrey L. Krichmar, Michael Beyeler, 2014, Neuroinformatics.

Oculomotor impairment during chronic partial sleep deprivation

J. Krichmar, T. Balkin, D. Thorne, 2003, Clinical Neurophysiology.

A configurable simulation environment for the efficient simulation of large-scale spiking neural networks on graphics processors

Nikil D. Dutt, Alexander V. Veidenbaum, Alexandru Nicolau, 2009, Neural Networks.

Unsupervised Heart-rate Estimation in Wearables With Liquid States and A Probabilistic Readout

Nikil D. Dutt, Chris Van Hoof, Francky Catthoor, 2017, Neural Networks.

Evolving Simple Models of Diverse Intrinsic Dynamics in Hippocampal Neuron Types

Jeffrey L. Krichmar, Kenneth A. De Jong, Giorgio A. Ascoli, 2018, Front. Neuroinform..

Towards reverse engineering the brain: Modeling abstractions and simulation frameworks

Nikil D. Dutt, Jeffrey L. Krichmar, Jayram Moorkanikara Nageswaran, 2010, 2010 18th IEEE/IFIP International Conference on VLSI and System-on-Chip.

The Neuromodulatory System: A Framework for Survival and Adaptive Behavior in a Challenging World

Jeffrey L. Krichmar, J. Krichmar, 2008, Adapt. Behav..

Deep Reinforcement Learning With Modulated Hebbian Plus Q-Network Architecture

Jeffrey L. Krichmar, Soheil Kolouri, Andrea Soltoggio, 2019, IEEE Transactions on Neural Networks and Learning Systems.

Learning touch preferences with a tactile robot using dopamine modulated STDP in a model of insular cortex

Jeffrey L. Krichmar, Ting-Shuo Chou, Liam D. Bucci, 2015, Front. Neurorobot..

A neural model of schemas and memory encoding

Jeffrey L. Krichmar, Tiffany Hwu, J. Krichmar, 2019, Biological Cybernetics.

A Neurobiologically Inspired Plan Towards Cognitive Machines

Jeffrey L. Krichmar, J. Krichmar, 2019, AAAI Spring Symposium: Towards Conscious AI Systems.

A Neural Model of Schemas and Memory Consolidation

Jeffrey L. Krichmar, Tiffany Hwu, J. Krichmar, 2018, bioRxiv.

Evolution of biologically plausible neural networks performing a visually guided reaching task

Jeffrey L. Krichmar, Derrik E. Asher, Nicolas Oros, 2014, GECCO.

An efficient automated parameter tuning framework for spiking neural networks

Nikil Dutt, Jeffrey L. Krichmar, Jayram Moorkanikara Nageswaran, 2014, Front. Neurosci..

Design space exploration and parameter tuning for neuromorphic applications

Nikil D. Dutt, Jeffrey L. Krichmar, Jayram Moorkanikara Nageswaran, 2013, 2013 International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS).

Biologically plausible models of homeostasis and STDP: Stability and learning in spiking neural networks

Nikil D. Dutt, Jeffrey L. Krichmar, Kristofor D. Carlson, 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).

Characterizing functional hippocampal pathways in a brain-based device as it solves a spatial memory task.

Gerald M Edelman, Jeffrey L Krichmar, Douglas A Nitz, 2005, Proceedings of the National Academy of Sciences of the United States of America.

Policy Distillation with Selective Input Gradient Regularization for Efficient Interpretability

J. Krichmar, Xinyun Zou, E. Neftci, 2022, ArXiv.

Domain Adaptation In Reinforcement Learning Via Latent Unified State Representation pdf

Jeffrey L. Krichmar, Takashi Nagata, Emre Neftci, 2021, AAAI.

Advantage of prediction and mental imagery for goal-directed behaviour in agents and robots

Jeffrey L. Krichmar, Todd Hylton, Xinyun Zou, 2019, Cogn. Comput. Syst..

Simulation of How Neuromodulation Influences Cooperative Behavior

Jeffrey L. Krichmar, Andrew Zaldivar, Derrik E. Asher, 2010, SAB.

NeuroXplorer 1.0: An Extensible Framework for Architectural Exploration with Spiking Neural Networks

Nagarajan Kandasamy, Francky Catthoor, Nikil Dutt, 2021, ICONS.

Enabling Resource-Aware Mapping of Spiking Neural Networks via Spatial Decomposition pdf

Nagarajan Kandasamy, Francky Catthoor, Nikil Dutt, 2020, IEEE Embedded Systems Letters.

Visual Data Mining of Brain Cells

Jürgen Symanzik, Giorgio A. Ascoli, Jeffrey L. Krichmar, 2002 .

A biologically inspired action selection algorithm based on principles of neuromodulation

Jeffrey L. Krichmar, J. Krichmar, 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

Oculomotor responses during partial and total sleep deprivation.

Gregory Belenky, Elizabeth Alicandri, Jeffrey L Krichmar, 2005, Aviation, space, and environmental medicine.

Design Principles and Constraints Underlying the Construction of Brain-Based Devices

Jeffrey L. Krichmar, Gerald M. Edelman, G. Edelman, 2007, ICONIP.

Robust Resting-State Dynamics in a Large-Scale Spiking Neural Network Model of Area CA3 in the Mouse Hippocampus

Sarojini M. Attili, G. Ascoli, J. Krichmar, 2022, Cognitive Computation.

An Efficient Simulation Environment for Modeling Large-Scale Cortical Processing

Nikil D. Dutt, Jeffrey L. Krichmar, Jayram Moorkanikara Nageswaran, 2011, Front. Neuroinform..

Guest Editorial: Biologically Inspired Human-Robot Interactions - Developing More Natural Ways to Communicate with our Machines

Hava T. Siegelmann, Frederick C. Harris, Jeffrey L. Krichmar, 2012, IEEE Trans. Auton. Ment. Dev..

Interactions between the neuromodulatory systems and the amygdala: exploratory survey using the Allen Mouse Brain Atlas

J. Krichmar, Andrew Zaldivar, 2012, Brain Structure and Function.

Neuromorphic modeling abstractions and simulation of large-scale cortical networks

Nikil D. Dutt, Jeffrey L. Krichmar, Jayram Moorkanikara Nageswaran, 2011, 2011 IEEE/ACM International Conference on Computer-Aided Design (ICCAD).

Neuromodulation, attention and localization using a novel Android™ robotic platform

Jeffrey L. Krichmar, Nicolas Oros, J. Krichmar, 2012, 2012 IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL).

Smartphone Based Robotics : Powerful , Flexible and Inexpensive Robots for Hobbyists , Educators , Students and Researchers

Jeffrey L. Krichmar, Nicolas Oros, J. Krichmar, 2013 .

A dynamic, embodied paradigm to investigate the role of serotonin in decision-making

Jeffrey L. Krichmar, Andrew Zaldivar, Derrik E. Asher, 2013, Front. Integr. Neurosci..

Achieving efficient interpretability of reinforcement learning via policy distillation and selective input gradient regularization

J. Krichmar, Xinyun Zou, E. Neftci, 2023, Neural Networks.

Computer generation and quantitative morphometric analysis of virtual neurons

Jeffrey L. Krichmar, Slawomir J. Nasuto, Ruggero Scorcioni, 2001, Anatomy and Embryology.

L-neuron: A modeling tool for the efficient generation and parsimonious description of dendritic morphology

Jeffrey L. Krichmar, Giorgio A. Ascoli, G. Ascoli, 2000, Neurocomputing.

Reciprocity and Retaliation in Social Games With Adaptive Agents

Jeffrey L. Krichmar, Andrew Zaldivar, Derrik E. Asher, 2012, IEEE Transactions on Autonomous Mental Development.

Neural and Synaptic Array Transceiver: A Brain-Inspired Computing Framework for Embedded Learning

Gert Cauwenberghs, Nikil D. Dutt, Jeffrey L. Krichmar, 2017, Front. Neurosci..

Simulation of cholinergic and noradrenergic modulation of behavior in uncertain environments

Jeffrey L. Krichmar, Michael C. Avery, Douglas A. Nitz, 2012, Front. Comput. Neurosci..

Path planning using a spiking neuron algorithm with axonal delays

Jeffrey L. Krichmar, J. Krichmar, 2016, 2016 IEEE Congress on Evolutionary Computation (CEC).

Understanding and Improving Optimization in Predictive Coding Networks

J. Krichmar, E. Neftci, Nick Alonso, 2023, AAAI.

Neuromorphic and Brain-Based Robots: Biomimetic robots as scientific models: a view from the whisker tip

Tony J. Prescott, Ag Pipe, M Pearson, 2011 .

PyCARL: A PyNN Interface for Hardware-Software Co-Simulation of Spiking Neural Network

J. Krichmar, N. Dutt, F. Catthoor, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

A configurable simulation environment for the efficient simulation of large-scale spiking neural networks on graphics processors

J. Krichmar, A. Nicolau, N. Dutt, 2009, Neural Networks.

Conjunctive Coding in an Evolved Spiking Model of Retrosplenial Cortex

Jeffrey L Krichmar, Emily L Rounds, Emily L. Rounds, 2018, Behavioral neuroscience.

A Sparse Quantized Hopfield Network for Online-Continual Memory

J. Krichmar, Nick Alonso, 2023, ArXiv.

Machine psychology: autonomous behavior, perceptual categorization and conditioning in a brain-based device.

G. Edelman, J. Krichmar, 2002, Cerebral cortex.

Neurorobotic models in neuroscience and neuroinformatics

Olaf Sporns, Jeffrey L. Krichmar, Anil K. Seth, 2007, Neuroinformatics.

Metacognitive Mechanisms for Novelty Processing: Lessons for AI

Rajesh P. N. Rao, J. Krichmar, Scott Sinclair Grigsby, 2021 .

Social contracts and human–computer interaction with simulated adapting agents

Jeffrey L. Krichmar, Derrik E. Asher, Nicolas Oros, 2013, Adapt. Behav..

Editorial: Explainable Artificial Intelligence and Neuroscience: Cross-Disciplinary Perspectives

Jeffrey L. Krichmar, Huajin Tang, James Leland Olds, 2021, Frontiers in Neurorobotics.

Machine Psychology: Autonomous Behavior, Perceptual Categorization and Conditioning in a Brain-based Device

W. M. Keck, G. Edelman, J. Krichmar, 2002 .

Selective Memory Replay Improves Exploration in a Spiking Wavefront Planner

J. Krichmar, Robert Bain, Harrison C. Espino, 2023, 2023 International Joint Conference on Neural Networks (IJCNN).

Spatial navigation and causal analysis in a brain-based device modeling cortical-hippocampal interactions

G. Edelman, J. Krichmar, D. Nitz, 2007, Neuroinformatics.

Learning to ignore: A modeling study of a decremental cholinergic pathway and its influence on attention and learning

A. Chiba, J. Krichmar, D. Nitz, 2014, Learning & memory.

Visual response properties of MSTd emerge from a sparse population code

J. Krichmar, N. Dutt, M. Beyeler, 2017, 1702.06665.

A configurable simulation environment for the efficient simulation of large-scale spiking neural networks on graphics processors

J. Krichmar, N. Dutt, A. Veidenbaum, 2009, Neural Networks.

The Cognitive Anteater Robotics Laboratory (CARL) at the University of California, Irvine

Jeffrey L. Krichmar, J. Krichmar, 2013, IEEE Intell. Informatics Bull..

Neurobiologically Inspired Robotics: Enhanced Autonomy through Neuromorphic Cognition

Minoru Asada, Jeffrey L. Krichmar, Jörg Conradt, 2015, Neural Networks.

Value and reward based learning in neurorobots

Jeffrey L. Krichmar, Florian Röhrbein, J. Krichmar, 2013, Front. Neurorobot..

Neuromodulation as a robot controller

Jeffrey L. Krichmar, Brian R. Cox, J. Krichmar, 2009, IEEE Robotics & Automation Magazine.

Brain-based devices: intelligent systems based on principles of the nervous system

Jeffrey L. Krichmar, Gerald M. Edelman, G. Edelman, 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

Neurobiologically Inspired Self-Monitoring Systems

Jeffrey L. Krichmar, Andrea A. Chiba, A. Chiba, 2020, Proceedings of the IEEE.

as a Robot Controller Neuromodulation as a Robot Controller A Brain-Inspired Strategy for Controlling Autonomous Robots

Jeffrey L. Krichmar, Brian R. Cox, J. Krichmar, 2009 .

Adapting to Environment Changes Through Neuromodulation of Reinforcement Learning

Praveen K. Pilly, Nicholas A. Ketz, J. Krichmar, 2022, Simulation of Adaptive Behavior.

Neurorobotics—A Thriving Community and a Promising Pathway Toward Intelligent Cognitive Robots

Jeffrey L. Krichmar, J. Krichmar, 2018, Front. Neurorobot..

A sparse quantized hopfield network for online-continual memory

J. Krichmar, Nick Alonso, 2023, Nature communications.

Embodied models of delayed neural responses: Spatiotemporal categorization and predictive motor control in brain based devices

G. Edelman, A. Seth, J. Krichmar, 2008, Neural Networks.