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Dr Josh Arnold
Dr

Josh Arnold

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Overview

Background

Joshua earned his undergraduate degree in Engineering (Software) from the University of Queensland. He began his research career developing social behaviours for a rat sized robot (the iRat) to facilitate interactions between the robot and real rats. Joshua completed his PhD in computational neuroscience under the mentorship of Prof. Janet Wiles. This work focused on the role of time in neural computation and in particular focused on how delays between neurons can be used as a functional learning rule. He then joined the Scott Lab at the Queensland Brain Institute where his work focuses on computational models of brain-wide calcium imaging data from the zebrafish model.

Availability

Dr Josh Arnold is:
Available for supervision

Qualifications

  • Bachelor (Honours) of Engineering, The University of Queensland
  • Doctor of Philosophy of Artificial Intelligence, The University of Queensland

Works

Search Professor Josh Arnold’s works on UQ eSpace

9 works between 2014 and 2025

1 - 9 of 9 works

2025

Journal Article

Generation of stable brain cell cultures from embryonic zebrafish to interrogate phenotypes in zebrafish mutants of neurodevelopmental disorders

Odierna, G. Lorenzo, Stednitz, Sarah, Pruitt, April, Arnold, Joshua, Hoffman, Ellen J. and Scott, Ethan K. (2025). Generation of stable brain cell cultures from embryonic zebrafish to interrogate phenotypes in zebrafish mutants of neurodevelopmental disorders. Journal of Neuroscience Methods, 418 110426, 110426-418. doi: 10.1016/j.jneumeth.2025.110426

Generation of stable brain cell cultures from embryonic zebrafish to interrogate phenotypes in zebrafish mutants of neurodevelopmental disorders

2025

Journal Article

Evidence for Auditory Stimulus‐Specific Adaptation But Not Deviance Detection in Larval Zebrafish Brains

Wilde, Maya, Poulsen, Rebecca E., Qin, Wei, Arnold, Joshua, Favre‐Bulle, Itia A., Mattingley, Jason B., Scott, Ethan K. and Stednitz, Sarah J. (2025). Evidence for Auditory Stimulus‐Specific Adaptation But Not Deviance Detection in Larval Zebrafish Brains. Journal of Comparative Neurology, 533 (4) e70046, 4. doi: 10.1002/cne.70046

Evidence for Auditory Stimulus‐Specific Adaptation But Not Deviance Detection in Larval Zebrafish Brains

2025

Journal Article

Brain-wide impacts of sedation on spontaneous activity and auditory processing in larval zebrafish

Favre-Bulle, Itia A., Muller, Eli, Lee, Conrad, Scholz, Leandro A., Arnold, Joshua, Munn, Brandon, Wainstein, Gabriel, Shine, James M. and Scott, Ethan K. (2025). Brain-wide impacts of sedation on spontaneous activity and auditory processing in larval zebrafish. The Journal of Neuroscience, 45 (15), e0204242025. doi: 10.1523/jneurosci.0204-24.2025

Brain-wide impacts of sedation on spontaneous activity and auditory processing in larval zebrafish

2022

Other Outputs

Conduction delay plasticity in spiking neurons for learning precise temporal structure in noisy and variable inputs

Arnold, Joshua (2022). Conduction delay plasticity in spiking neurons for learning precise temporal structure in noisy and variable inputs. PhD Thesis, School of Information Technology and Electrical Engineering, The University of Queensland. doi: 10.14264/92a2fe1

Conduction delay plasticity in spiking neurons for learning precise temporal structure in noisy and variable inputs

2021

Conference Publication

Conduction delay plasticity can robustly learn spatiotemporal patterns embedded in noise

Arnold, Joshua, Stratton, Peter and Wiles, Janet (2021). Conduction delay plasticity can robustly learn spatiotemporal patterns embedded in noise. 2021 International Joint Conference on Neural Networks (IJCNN), Shenzhen, China, 18-22 July 2021. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/IJCNN52387.2021.9533934

Conduction delay plasticity can robustly learn spatiotemporal patterns embedded in noise

2021

Conference Publication

Single neurons with delay-based learning can generalise between time-warped patterns

Arnold, Joshua, Stratton, Peter and Wiles, Janet (2021). Single neurons with delay-based learning can generalise between time-warped patterns. International Conference on Artificial Neural Networks, Bratislava, Slovakia, 14-17 September 2021. Cham, Switzerland: Springer International Publishing. doi: 10.1007/978-3-030-86380-7_11

Single neurons with delay-based learning can generalise between time-warped patterns

2018

Conference Publication

Building speech recognition systems for language documentation: the CoEDL Endangered Language Pipeline and Inference System (ELPIS)

Foley, Ben, Arnold, Josh, Coto-Solano, Rolando, Durantin, Gautier, Ellison, T. Mark, van Esch, Daan, Heath, Scott, Kratochvíl, František, Maxwell-Smith, Zara, Nash, David, Olsson, Ola, Richards, Mark, San, Nay, Stoakes, Hywel, Thieberger, Nick and Wiles, Janet (2018). Building speech recognition systems for language documentation: the CoEDL Endangered Language Pipeline and Inference System (ELPIS). SLTU 2018: 6th Workshop on Spoken Language Technologies for Under-resourced Languages, Gurugram, India, 29-31 August 2018. Baxias, France: International Speech Communication Association. doi: 10.21437/sltu.2018-43

Building speech recognition systems for language documentation: the CoEDL Endangered Language Pipeline and Inference System (ELPIS)

2018

Conference Publication

PiRat: an autonomous framework for studying social behaviour in rats and robots

Heath, Scott, Ramirez-Brinez, Carlos Andres, Arnold, Joshua, Olsson, Ola, Taufatofua, Jonathon, Pounds, Pauline, Wiles, Janet, Leonardis, Eric, Gygi, Emanuel, Leija, Estelita, Quinn, Laleh K. and Chiba, Andrea A. (2018). PiRat: an autonomous framework for studying social behaviour in rats and robots. 25th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, 1-5 October 2018. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/IROS.2018.8594060

PiRat: an autonomous framework for studying social behaviour in rats and robots

2014

Conference Publication

Event-based visual data sets for prediction tasks in spiking neural networks

Gibson, Tingting (Amy), Heath, Scott, Quinn, Robert P., Lee, Alexia H., Arnold, Joshua T., Sonti, Tharun S., Whalley, Andrew, Shannon, George P., Song, Brian T., Henderson, James A. and Wiles, Janet (2014). Event-based visual data sets for prediction tasks in spiking neural networks. 24th International Conference on Artificial Neural Networks, ICANN 2014, Hamburg, Germany, 15 - 19 September 2014. Heidelberg, Germany: Springer Verlag. doi: 10.1007/978-3-319-11179-7_80

Event-based visual data sets for prediction tasks in spiking neural networks

Supervision

Availability

Dr Josh Arnold is:
Available for supervision

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Media

Enquiries

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