Publications by Mackenzie Mathis

Neuropeptides specify and reprogram division of labor in the leafcutter ant Atta cephalotes

Social insects offer powerful models to investigate mechanisms of elaborate individual behaviors comprising a cooperative community. Workers of the leafcutter ant genus Atta are extreme examples of behavioral segregation among phenotypically distinct worke ...

Elsevier BV2025

Ethological computational psychiatry: Challenges and opportunities

Mackenzie Mathis

Studying the intricacies of individual subjects' moods and cognitive processing over extended periods of time presents a formidable challenge in medicine. While much of systems neuroscience appropriately focuses on the link between neural circuit functions ...

Current Biology Ltd2024

Keypoint-MoSeq: parsing behavior by linking point tracking to pose dynamics

Mackenzie Mathis, Alexander Mathis, Shaokai Ye

Keypoint tracking algorithms can flexibly quantify animal movement from videos obtained in a wide variety of settings. However, it remains unclear how to parse continuous keypoint data into discrete actions. This challenge is particularly acute because key ...

2024

Decoding the brain: From neural representations to mechanistic models

Mackenzie Mathis, Alexander Mathis

A central principle in neuroscience is that neurons within the brain act in concert to produce perception, cognition, and adaptive behavior. Neurons are organized into specialized brain areas, dedicated to different functions to varying extents, and their ...

CELL PRESS2024

SuperAnimal pretrained pose estimation models for behavioral analysis

Tian Qiu, Maxime Michel André Vidal, Mackenzie Mathis, Alexander Mathis, Shaokai Ye, Jessy Lauer, Steffen Schneider

Quantification of behavior is critical in diverse applications from neuroscience, veterinary medicine to animal conservation. A common key step for behavioral analysis is first extracting relevant keypoints on animals, known as pose estimation. However, re ...

Nature Research2024

Data for Contrasting action and posture coding with hierarchical deep neural network models of proprioception

Mackenzie Mathis, Alexander Mathis, Matthias Bethge

############# Contrasting action and posture coding with hierarchical deep neural network models of proprioception, eLife 2023 ############# Authors: Kai J Sandbrink, Pranav Mamidanna, Claudio Michaelis, Matthias Bethge, Mackenzie W Mathis and Alexander ...

Zenodo2024

Dimensionality reduction of time-series data, and systems and devices that use the resultant embeddings

Mackenzie Mathis, Steffen Schneider

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for dimensionality reduction of time-series using contrastive learning. A method can include receiving multidimensional input time series data that includes ...

2023

Brain dynamics uncovered using a machine-learning algorithm

Mackenzie Mathis

CEBRA is a machine-learning method that can be used to compress time series in a way that reveals otherwise hidden structures in the variability of the data. It excels at processing behavioural and neural data recorded simultaneously, and it can decode act ...

NATURE PORTFOLIO2023

Reaching an understanding of cortico-medullary control of forelimb behaviors

Mackenzie Mathis, Thomas Trevelyan James Sainsbury

How the neocortex modulates hindbrain and spinal circuits is of fundamental interest for understanding mo-tor control and adaptive behaviors. New work from Yang, Kanodia, and Arber demonstrates that there is an exquisite anatomical organization and functio ...

CELL PRESS2023

NeuroAI: If grid cells are the answer, is path integration the question?

Mackenzie Mathis, Alexander Mathis, Markus Frey

Spatially modulated neurons known as grid cells are thought to play an important role in spatial cognition. A new study has found that units with grid-cell-like properties can emerge within artificial neural networks trained to path integrate, and develope ...

CELL PRESS2023

Rethinking pose estimation in crowds: overcoming the detection information bottleneck and ambiguity

Mackenzie Mathis, Alexander Mathis

Here we provide neural networks weights for the best models in our article "Rethinking pose estimation in crowds: overcoming the detection information-bottleneck and ambiguity", ICCV 2023. Each model has the naming convention "dataset"-"modeltype".pth. Th ...

Zenodo2023

A response to claims of emergent intelligence and sentience in a dish

Maria del Carmen Sandi Perez, Mackenzie Mathis

CELL PRESS2023

Learnable latent embeddings for joint behavioural and neural analysis

Mackenzie Mathis, Steffen Schneider, Jin Hwa Lee

Mapping behavioural actions to neural activity is a fundamental goal of neuroscience. As our ability to record large neural and behavioural data increases, there is growing interest in modelling neural dynamics during adaptive behaviours to probe neural re ...

NATURE PORTFOLIO2023

Contrasting action and posture coding with hierarchical deep neural network models of proprioception

Pranav Mamidanna, Mackenzie Mathis, Alexander Mathis, Kai Jappe Sandbrink, Matthias Bethge

Biological motor control is versatile, efficient, and depends on proprioceptive feedback. Muscles are flexible and undergo continuous changes, requiring distributed adaptive control mechanisms that continuously account for the body's state. The canonical r ...

eLIFE SCIENCES PUBL LTD2023

AmadeusGPT: a natural language interface for interactive animal behavioral analysis

Mackenzie Mathis, Alexander Mathis, Shaokai Ye, Jessy Lauer

The process of quantifying and analyzing animal behavior involves translating the naturally occurring descriptive language of their actions into machine-readable code. Yet, codifying behavior analysis is often challenging without deep understanding of anim ...

2023

Next-generation brain observatories

Shreya Saxena, Mackenzie Mathis

We propose centralized brain observatories for large-scale recordings of neural activity in mice and non-human primates coupled with cloud-based data analysis and sharing. Such observatories will advance reproducible systems neuroscience and democratize ac ...

CELL PRESS2022

The neocortical column as a universal template for perception and world-model learning

Mackenzie Mathis

Mackenzie Mathis highlights an essay by Vernon Mountcastle that shaped our understanding of the organization and function of the neocortex. ...

NATURE PORTFOLIO2022

Multi-animal pose estimation, identification and tracking with DeepLabCut

Tanmay Nath, Mackenzie Mathis, Alexander Mathis, Shaokai Ye, Jessy Lauer, Steffen Schneider

Estimating the pose of multiple animals is a challenging computer vision problem: frequent interactions cause occlusions and complicate the association of detected keypoints to the correct individuals, as well as having highly similar looking animals that ...

NATURE PORTFOLIO2022

Striatal dopamine explains novelty-induced behavioral dynamics and individual variability in threat prediction

Mackenzie Mathis, Alexander Mathis

Animals both explore and avoid novel objects in the environment, but the neural mechanisms that underlie these behaviors and their dynamics remain uncharacterized. Here, we used multi-point tracking (DeepLabCut) and behavioral segmentation (MoSeq) to chara ...

CELL PRESS2022

Perspectives in machine learning for wildlife conservation

Devis Tuia, Mackenzie Mathis, Alexander Mathis, Benjamin Alexander Kellenberger

Inexpensive and accessible sensors are accelerating data acquisition in animal ecology. These technologies hold great potential for large-scale ecological understanding, but are limited by current processing approaches which inefficiently distill data into ...

Nature Research2022