3D Brain Model

Decoding inner speech from the brain,
non-invasively

The Parker Jones Neural Processing Lab (PNPL; pronounced 'pineapple') is the newest group within the Oxford Robotics Institute, established through generous funding from the UK Research and Innovation's Medical Research Council (MRC). We are interested in brains, computers, language, and robotics – all core areas of natural and artificial intelligence. As such, our work spans foundational neuroscience, machine learning methods development, and systems applications such as Brain Computer Interfaces (BCIs).

PNPL LogoOxford Robotics InstituteUniversity of Oxford
Announcement

Join the LibriBrain Competition

Advance the field of non-invasive brain-computer interfaces by participating in our open competition using the largest single-subject MEG dataset for speech decoding.

Enter Competition →
Open until September 30th (Phase 2)
50+
Hours of MEG Data
$10,000+
Prize money
pip install pnpl
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Latest Insights

Explore our latest research and discoveries in neural processing and brain-computer interfaces

Phoneme ClassificationLinguistics

Language-Inspired Approaches to Phoneme Classification

Linguistics-inspired strategies for leveraging phonetic features in LibriBrain MEG data, covering feature taxonomies, diphthong handling, and feature-to-phoneme conversion pipelines.

Teyun Kwon, SungJun Cho, Gereon Elvers, Francesco Mantegna, Oiwi Parker Jones
Sep 22, 202524 min read
Read More
NeuroscienceSpeech Detection

Brain-Inspired Approaches to Speech Detection

Neuroscience-informed approaches to speech detection for the LibriBrain competition, including STG sensor analysis, spatial and temporal strategies, and architectural recommendations.

Francesco Mantegna, Gereon Elvers, Oiwi Parker Jones
Jul 10, 202521 min read
Read More
Speech DetectionReference Model

The Speech Detection Task and the Reference Model

Exploring the Speech Detection task and the reference model architecture used in the LibriBrain competition, including insights into our 'Start Simple' approach and future research directions.

Gilad Landau, Gereon Elvers, Miran Özdogan, Oiwi Parker Jones
Jul 7, 20256 min read
Read More
Brain-Computer InterfacesMEG

Building a Collaborative Foundation for Non-Invasive Speech BCIs: The 2025 PNPL Competition

Exploring the motivation behind the 2025 PNPL Competition and how we're building towards non-invasive speech brain-computer interfaces through deep MEG datasets and collaborative research.

Gereon Elvers, Gilad Landau, Dulhan Jayalath, Francesco Mantegna, Oiwi Parker Jones
Jan 20, 20257 min read
Read More
Phoneme ClassificationLinguistics

Language-Inspired Approaches to Phoneme Classification

Linguistics-inspired strategies for leveraging phonetic features in LibriBrain MEG data, covering feature taxonomies, diphthong handling, and feature-to-phoneme conversion pipelines.

Teyun Kwon, SungJun Cho, Gereon Elvers, Francesco Mantegna, Oiwi Parker Jones
Sep 22, 202524 min read
Read More
NeuroscienceSpeech Detection

Brain-Inspired Approaches to Speech Detection

Neuroscience-informed approaches to speech detection for the LibriBrain competition, including STG sensor analysis, spatial and temporal strategies, and architectural recommendations.

Francesco Mantegna, Gereon Elvers, Oiwi Parker Jones
Jul 10, 202521 min read
Read More
Speech DetectionReference Model

The Speech Detection Task and the Reference Model

Exploring the Speech Detection task and the reference model architecture used in the LibriBrain competition, including insights into our 'Start Simple' approach and future research directions.

Gilad Landau, Gereon Elvers, Miran Özdogan, Oiwi Parker Jones
Jul 7, 20256 min read
Read More
Brain-Computer InterfacesMEG

Building a Collaborative Foundation for Non-Invasive Speech BCIs: The 2025 PNPL Competition

Exploring the motivation behind the 2025 PNPL Competition and how we're building towards non-invasive speech brain-computer interfaces through deep MEG datasets and collaborative research.

Gereon Elvers, Gilad Landau, Dulhan Jayalath, Francesco Mantegna, Oiwi Parker Jones
Jan 20, 20257 min read
Read More
Phoneme ClassificationLinguistics

Language-Inspired Approaches to Phoneme Classification

Linguistics-inspired strategies for leveraging phonetic features in LibriBrain MEG data, covering feature taxonomies, diphthong handling, and feature-to-phoneme conversion pipelines.

Teyun Kwon, SungJun Cho, Gereon Elvers, Francesco Mantegna, Oiwi Parker Jones
Sep 22, 202524 min read
Read More
NeuroscienceSpeech Detection

Brain-Inspired Approaches to Speech Detection

Neuroscience-informed approaches to speech detection for the LibriBrain competition, including STG sensor analysis, spatial and temporal strategies, and architectural recommendations.

Francesco Mantegna, Gereon Elvers, Oiwi Parker Jones
Jul 10, 202521 min read
Read More
Speech DetectionReference Model

The Speech Detection Task and the Reference Model

Exploring the Speech Detection task and the reference model architecture used in the LibriBrain competition, including insights into our 'Start Simple' approach and future research directions.

Gilad Landau, Gereon Elvers, Miran Özdogan, Oiwi Parker Jones
Jul 7, 20256 min read
Read More
Brain-Computer InterfacesMEG

Building a Collaborative Foundation for Non-Invasive Speech BCIs: The 2025 PNPL Competition

Exploring the motivation behind the 2025 PNPL Competition and how we're building towards non-invasive speech brain-computer interfaces through deep MEG datasets and collaborative research.

Gereon Elvers, Gilad Landau, Dulhan Jayalath, Francesco Mantegna, Oiwi Parker Jones
Jan 20, 20257 min read
Read More
Our work

Recent Publications

Take a look at some of our recent work in the field of neural signal processing and brain-computer interfaces.

Featured

The 2025 PNPL competition: Speech detection and phoneme classification in the LibriBrain dataset

Gilad Landau, Miran Özdogan, Gereon Elvers, Francesco Mantegna, Pratik Somaiya, Dulhan Jayalath, Luisa Kurth, Teyun Kwon, Brendan Shillingford, Greg Farquhar, Minqi Jiang, Karim Jerbi, Hamza Abdelhedi, Yorguin Mantilla Ramos, Caglar Gulcehre, Mark Woolrich, Natalie Voets, Oiwi Parker Jones
NeurIPS 2025 Competition Track (2025)arXiv

tl;dr: Competition framework for advancing speech decoding from non-invasive brain data using the LibriBrain dataset. Cite this for the LibriBrain competition.

Featured

LibriBrain: Over 50 Hours of Within-Subject MEG to Improve Speech Decoding Methods at Scale

Miran Özdogan, Gilad Landau, Gereon Elvers, Dulhan Jayalath, Pratik Somaiya, Francesco Mantegna, Mark Woolrich, Oiwi Parker Jones
arXiv preprint (2025)arXiv

tl;dr: The largest single-subject MEG dataset to date for speech decoding, with over 50 hours of recordings. Cite this for the LibriBrain dataset.

Featured

Unlocking Non-Invasive Brain-to-Text

Dulhan Jayalath, Gilad Landau, Oiwi Parker Jones
arXiv preprint (2025)arXiv

tl;dr: Advances in non-invasive brain-to-text technology with LLM-based rescoring and predictive in-filling approaches.

Featured

The Brain's Bitter Lesson: Scaling Speech Decoding With Self-Supervised Learning

Dulhan Jayalath, Gilad Landau, Brendan Shillingford, Mark Woolrich, Oiwi Parker Jones
ICML 2025 (2025)arXiv

tl;dr: Breakthrough in scaling speech decoding models across subjects using self-supervised learning techniques.

Who we are

Meet the group

A multidisciplinary team of researchers, engineers, and students advancing the frontiers of neural processing and brain-computer interfaces.

Oiwi Parker JonesOiwi Parker Jones wearing sunglasses

Oiwi Parker Jones

Principal Investigator

Oiwi leads the Parker Jones Neural Processing Lab (PNPL) at the University of Oxford. His aim is to build bridges between deep learning and the brain, for example by accelerating the development of Brain Computer Interfaces (BCIs), but also by developing deep learning methods for interpreting brain data and leveraging principles of systems neuroscience to inform machine learning. Oiwi completed a DPhil focused on Natural Language Processing (NLP) for low-resource languages. He further trained as a postdoc in Imaging Neuroscience at UCL and Oxford, and in Applied Artificial Intelligence at the ORI. He was previously a lecturer in Medicine at St Peter's College, Oxford, and is currently Hugh Price Fellow in Computer Science at Jesus College, Oxford.

Research Interests

Neural DecodingBrain-Computer InterfacesDeep LearningComputational Neuroscience
Francesco MantegnaFrancesco Mantegna wearing sunglasses

Francesco Mantegna

Postdoctoral Research Fellow

Francesco joined PNPL as a Postdoc in 2024 after receiving his PhD in Cognitive Psychology and Neuroscience from NYU under the supervision of David Poeppel. His interests include Brain Computer Interfaces (BCIs), Neurotechnology, and Speech Neuroprosthetics.

Research Interests

Brain Computer InterfacesNeurotechnologySpeech NeuroprostheticsCognitive Psychology
Pratik SomaiyaPratik Somaiya wearing sunglasses

Pratik Somaiya

Software Engineer

Pratik joined the Oxford Robotics Institute (ORI) in May 2023 as a Robotics Software Engineer. Before that, he pursued an MSc by Research in Robotics at the Lincoln Centre for Autonomous Systems Research (L-CAS), University of Lincoln, UK. Prior to his Master's, he was a Research Assistant at L-CAS working in agri-robotics. Pratik also spent several years in the industry before joining L-CAS. During that time, he worked on developing robots for warehouse material handling and consumer robots such as vacuum cleaning robots.

Research Interests

Robotics Software EngineeringAgri-roboticsWarehouse AutomationConsumer Robotics
Dulhan JayalathDulhan Jayalath wearing sunglasses

Dulhan Jayalath

DPhil/PhD Student

Dulhan is a DPhil student in the Autonomous Intelligent Machines and Systems (AIMS) CDT. At PNPL, his work focuses on leveraging deep learning to find efficient representations of brain signals for downstream tasks (e.g. phoneme recognition from heard speech brain data). Prior to joining PNPL, he worked on multi-agent RL and reasoning with graph neural networks at the University of Cambridge. Before this, he completed his BSc in Computer Science at the University of Southampton, where he researched computer vision systems for visual navigation. He has worked on large language models at Speechmatics and developing assembly-level machine learning kernels for new hardware at Arm.

Research Interests

Deep LearningBrain Signal ProcessingMulti-agent RLComputer Vision
Gilad D. LandauGilad D. Landau wearing sunglasses

Gilad D. Landau

DPhil/PhD Student

Gilad is a D.Phil student currently working on decoding semantic content from the brain with AI. He is motivated by the prospect of merging brains with AI to deepen our understanding of both. His academic background is in Philosophy of Cognitive Science, where he applied a multi-disciplinary approach to explore how brains process representations. Prior to joining PNPL he worked as an applied AI researcher, developing industry-first AI systems in several domains and modalities.

Research Interests

Semantic DecodingPhilosophy of Cognitive ScienceApplied AINeural Representations
Luisa KurthLuisa Kurth wearing sunglasses

Luisa Kurth

DPhil/PhD Student

My motivation is to help improving people's lives through AI. Currently, I am mostly interested in the challenges of advancing machine learning for medical image analysis. The CDT in AIMS offers the perfect platform for this journey and I'm excited to connect with anyone sharing my interest. I hold a Bachelor's degree in Psychology from the University of Mannheim and a Master's degree from the University of Oxford's Internet Institute. During my time at Oxford, I participated in cutting-edge research on the societal and ethical aspects of AI. This experience fueled my fascination for machine learning, leading me to pursue a second Master's degree at the University of Tübingen, where I focused on the foundations of deep learning, large language models and explainable AI. Along the way, I've conducted brain research at the Max-Planck-Institute and worked as a policy researcher at the OECD. Outside of research, I enjoy reading, socializing with friends, and visiting art galleries.

Research Interests

Medical Image AnalysisDeep LearningExplainable AIAI Ethics
Miran ÖzdoganMiran Özdogan wearing sunglasses

Miran Özdogan

DPhil/PhD Student

Miran's work in PNPL has recently focused on the role of sequence models, such as state space models (e.g. S4 and Mamba) for BCIs. He is also working to establish new benchmarks and standards for neural decoding, in order to quantify and accelerate progress in the field.

Research Interests

State Space ModelsBrain Computer InterfacesNeural DecodingBenchmarking
John KwonJohn Kwon wearing sunglasses

John Kwon

DPhil/PhD Student

John is a DPhil student as part of the EPSRC Centre for Doctoral Training in Autonomous Intelligent Machines and Systems. He joined Michaelmas Term 2024.

Research Interests

LLMsScaling laws
SungJun ChoSungJun Cho wearing sunglasses

SungJun Cho

DPhil/PhD Student

SungJun is a Neuroscience DPhil student, co-supervised with Mark Woolrich at OHBA/OxCIN/Psychiatry. He joined Michaelmas Term 2024.

Research Interests

Probabilistic dynamic models/DyNeMo/DyNeSteFoundation modelsTokenisation
Gereon ElversGereon Elvers wearing sunglasses

Gereon Elvers

Visiting Master's Student

Gereon is a Master's student from TU Munich. After initially joining PNPL remotely, he is currently visiting the lab in-person for six months. Besides working on the LibriBrain competition, he is working on the first practical applications of non-invasive speech decoding.

Research Interests

Word DetectionPNPL Competition

Get in Touch

Potential doctoral candidates are encouraged to apply both to the Department of Engineering Science and to the AIMS programme.

Potential collaborators are encouraged to reach out directly to the PI, Oiwi Parker Jones.