14 papers · ranked by Valyu relevance
Ethan M. Meyers
Neural decoding is a powerful method to analyze neural activity. However, the code needed to run a decoding analysis can be complex, which can present a barrier to using the method. In this paper we introduce a package that makes it easy to perform decoding analyses in the R programing language. We describe how the…
Joshua I. Glaser, Ari S. Benjamin, Raeed H. Chowdhury, Matthew G. Perich + 2 more
'Matthew G. Perich' 'Lee E. Miller' 'Konrad P. Kording'] Title: Abstract Despite rapid advances in machine learning tools, the majority of neural decoding approaches still use traditional methods. Modern machine learning tools, which are versatile and easy to use, have the potential to significantly improve decoding…
Benjamin I. Rapoport, Lorenzo Turicchia, Woradorn Wattanapanitch, Thomas J. Davidson + 2 more
'Thomas J. Davidson' 'Rahul Sarpeshkar' 'Michal Zochowski'] The ability to decode neural activity into meaningful control signals for prosthetic devices is critical to the development of clinically useful brain- machine interfaces (BMIs). Such systems require input from tens to hundreds of brain-implanted recording…
Vicente Botella-Soler, Stéphane Deny, Georg Martius, Olivier Marre + 2 more
Retina is a paradigmatic system for studying sensory encoding: the transformation of light into spiking activity of ganglion cells. The inverse problem, where stimulus is reconstructed from spikes, has received less attention, especially for complex stimuli that should be reconstructed “pixel-by-pixel”. We recorded…
Markus Frey, Sander Tanni, Catherine Perrodin, Alice O'Leary + 9 more
Rapid progress in technologies such as calcium imaging and electrophysiology has seen a dramatic increase in the size and extent of neural recordings. Even so, interpretation of this data requires considerable knowledge about the nature of the representation and often depends on manual operations. Decoding provides a…
Pooja Viswanathan, Anna M. Stein, Andreas Nieder, Uta Noppeney
Decision-making requires processing of sensory information, comparing the gathered evidence to make a judgment, and performing the action to communicate it. How neuronal representations transform during this cascade of representations remains a matter of debate. Here, we studied the succession of neuronal…
Célia Loriette, Julian L. Amengual, Suliann Ben Hamed
One of the major challenges in system neurosciences consists in developing techniques for estimating the cognitive information content in brain activity. This has an enormous potential in different domains spanning from clinical applications, cognitive enhancement to a better understanding of the neural bases of…
Yizhou Xie, Sadra Sadeh
Introduction Our brain is bombarded by a diverse range of visual stimuli, which are converted into corresponding neuronal responses and processed throughout the visual system. The neural activity patterns that result from these external stimuli vary depending on the object or scene being observed, but they also change…
Zach Mobille, Usama Bin Sikandar, Simon Sponberg, Hannah Choi
Convergent and divergent structures in the networks that make up biological brains are found across many species and brain regions at various spatial scales. Neurons in these networks fire action potentials, or “spikes”, whose precise timing is becoming increasingly appreciated as large sources of information about…
Min-Ki Kim, Jeong-woo Sohn, Bongsoo Lee, Sung-Phil Kim
Background Intracortical brain-machine interfaces (BMIs) harness movement information by sensing neuronal activities using chronic microelectrode implants to restore lost functions to patients with paralysis. However, neuronal signals often vary over time, even within a day, forcing one to rebuild a BMI every time they…
Jianing V. Shi, Jim Wielaard, R. Theodore Smith, Paul Sajda
Sparse coding has been posited as an efficient information processing strategy employed by sensory systems, particularly visual cortex. Substantial theoretical and experimental work has focused on the issue of sparse encoding, namely how the early visual system maps the scene into a sparse representation. In this paper…
Douglas L. Jones, Erik C. Johnson, Rama Ratnam
A neural code based on sequences of spikes can consume a significant portion of the brain's energy budget. Thus, energy considerations would dictate that spiking activity be kept as low as possible. However, a high spike-rate improves the coding and representation of signals in spike trains, particularly in sensory…
Ye Chen, Peter Beech, Ziwei Yin, Shanshan Jia + 4 more
'Zhaofei Yu' 'Jian K. Liu' 'Daniele Marinazzo'] Understanding the computational mechanisms that underlie the encoding and decoding of environmental stimuli is a crucial investigation in neuroscience. Central to this pursuit is the exploration of how the brain represents visual information across its hierarchical…
Merse E Gáspár, Pierre-Olivier Polack, Peyman Golshani, Máté Lengyel + 3 more
'Gergő Orbán' 'Nicole Rust' 'Joshua I Gold'] An important computational goal of the visual system is ‘representational untangling’ (RU): representing increasingly complex features of visual scenes in an easily decodable format. RU is typically assumed to be achieved in high-level visual cortices via several stages of…