… M. Villafane-Delgado and S. Aviyente are with the Department of Electrical and Computer
Engineering, Michigan State University, East Lansing, MI, 48824 USA. e-mail: aviyente@egr.…

We present a 32-transmitter, 32-receiver dual-wavelength frequency-domain (FD) fNIRS
system comprised of commercially available avalanche photodiodes, laser drivers and laser …

Graph signal processing extends the notion of frequency from signals in the time domain to
signals defined on graphs. Graph signals arise in many applications including brain signals …

1. Abstract NeuVue is a software platform created for large-scale proofreading of machine
segmentation and neural circuit reconstruction in high-resolution electron microscopy …

Despite the progress in deep learning networks, efficient learning at the edge (enabling
adaptable, low-complexity machine learning solutions) remains a critical need for defense and …

Educating the workforce of tomorrow is an increasingly critical challenge for areas such as
data science, machine learning, and artificial intelligence. These core skills may revolutionize …

Advances in information technology are making it possible to collect increasingly massive
amounts of multidimensional, multi-modal neuroimaging data such as functional magnetic …

Collective motion among biological organisms such as insects, fish, and birds has motivated
considerable interest not only in biology but also in distributed robotic systems. In a robotic …

The spectrotemporal response function (STRF) model of neural encoding quantitatively
associates dynamic auditory neural (output) responses to a spectrogram-like representation of a …

The immense scale and complexity of neuronal electron microscopy (EM) datasets pose
significant challenges in data processing, validation, and interpretation, necessitating the …