Interacting neural ensembles in orbitofrontal cortex for social and feeding behaviour

Nature
Categorically distinct basic drives can exert potent influences on each other; such interactions are likely to have important adaptive consequences and can become maladaptive.

Systemic AAV vectors for targeted gene delivery

Nature Protocols
Multicolor labeling of cardiac muscle with systemic AAVs. Three fluorescent proteins (mTurquoise2, mNeonGreen, and mRuby2) were separately packaged into AAV-PHP.S and systemically codelivered to a wild-type mouse at 3.3 × 1011vector genomes (vg) per virus (1 × 1012 vg total).
preprint

Machine learning in resting-state fMRI analysis

arXiv
Here, we present an overview of various unsupervised and supervised machine learning applications to rs-fMRI. We present a methodical taxonomy of machine learning methods in resting-state fMRI.

Circuit Models of Low-Dimensional Shared Variability in Cortical Networks

Neuron
Trial-to-trial variability is a reflection of the circuitry and cellular physiology that make up a neuronal network. A pervasive yet puzzling feature of cortical circuits is that despite their complex wiring, population-wide shared spiking variability is low dimensional.
preprint

Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels

arXiv
We present a theoretically grounded set of noise-robust loss functions that can be seen as a generalization of mean absolute error and categorical cross entropy.

Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels

32nd Conference on Neural Information Processing Systems (NeurIPS 2018)
As we show in this paper, mean absolute error (MAE) can perform poorly with deep neural networks and challenging datasets. Here, we present a theoretically grounded set of noise-robust loss functions that can be seen as a generalization of MAE and categorical cross entropy.

An adaptive excitation source for multiphoton imaging

Conference on Lasers and Electro-Optics, OSA Technical Digest (online)
We demonstrate an adaptive femtosecond laser source that improves the imaging speed by >10 times for multiphoton imaging of brain activity in awake mouse, achieving 30 frames/s, 734×734 µm field-of-view (FOV) at 700 µm depth.
preprint

Predicting response to motor therapy in chronic stroke patients using Machine Learning

bioRxiv
The first main objective of this study was to use machine learning methods to predict a chronic stroke individual’s motor function improvement after 6 weeks of intervention using pre-intervention demographic, clinical, neurophysiological and imaging data.

Interferometric spatial frequency modulation imaging

Optics Letters
Interferometric spatial frequency modulation for imaging (I-SPIFI) is demonstrated for the first time, to our knowledge. Significantly, this imaging modality can be seamlessly combined with nonlinear SPIFI imaging and operates through single-element detection.