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Neural probes are in vivo invasive devices that combine electrophysiology and optogenetics to gain insight into how the brain operates, down to the single neuron and its network activity. Their integration of stimulation sites and sensors…

Two major initiatives to accelerate research in the brain sciences have focused attention on developing a new generation of scientific instruments for neuroscience. These instruments will be used to record static (structural) and dynamic…

Neurons and Cognition · Quantitative Biology 2013-07-30 Thomas Dean , Biafra Ahanonu , Mainak Chowdhury , Anjali Datta , Andre Esteva , Daniel Eth , Nobie Redmon , Oleg Rumyantsev , Ysis Tarter

A major open challenge in neuroscience is the ability to measure and perturb neural activity in vivo from well-defined neural sub-populations at cellular resolution anywhere in the brain. However, limitations posed by scattering and…

Biological Physics · Physics 2017-11-10 Shay Ohayon , Antonio Miguel Caravaca-Aguirre , Rafael Piestun , James J. DiCarlo

Progress in neuroscience constantly relies on the development of new techniques to investigate the complex dynamics of neuronal networks. An ongoing challenge is to achieve minimally-invasive and high-resolution observations of neuronal…

Miniaturized microscopes (miniscopes) have opened a new frontier in animal behavior studies, enabling real-time imaging of neuron activity while leaving animals largely unconstrained. Canonical designs typically use Gradient-Index (GRIN)…

Recent years have seen dramatic progress in the development of techniques for measuring the activity and connectivity of large populations of neurons in the brain. However, as these techniques grow ever more powerful---allowing us to even…

Neurons and Cognition · Quantitative Biology 2017-10-20 Thomas Dean

The brain is a powerful tool used to achieve amazing feats. There have been several significant advances in neuroscience and artificial brain research in the past two decades. This article is a review of such advances, ranging from the…

Artificial Intelligence · Computer Science 2016-05-16 Gabriel Makdah

Neuroscientists today can measure activity from more neurons than ever before, and are facing the challenge of connecting these brain-wide neural recordings to computation and behavior. Here, we first describe emerging tools and…

Neurons and Cognition · Quantitative Biology 2022-01-10 Anne E. Urai , Brent Doiron , Andrew M. Leifer , Anne K. Churchland

Visual object recognition -- the behavioral ability to rapidly and accurately categorize many visually encountered objects -- is core to primate cognition. This behavioral capability is algorithmically impressive because of the myriad…

Neurons and Cognition · Quantitative Biology 2023-12-12 Kohitij Kar , James J DiCarlo

The story of information processing is a story of great success. Todays' microprocessors are devices of unprecedented complexity and MOSFET transistors are considered as the most widely produced artifact in the history of mankind. The…

Emerging Technologies · Computer Science 2020-05-20 Dawid Przyczyna , Piotr Zawal , Tomasz Mazur , Pier Luigi Gentili , Konrad Szaciłowski

We present the case for developing the tardigrade (Hypsibius exemplaris) into a model organism for systems neuroscience. These microscopic, transparent animals (~300-500 microns) are among the smallest known to possess both limbs (eight)…

Neurons and Cognition · Quantitative Biology 2025-01-14 Ana M. Lyons , Saul Kato

We pose that microscopy offers an ideal real-world experimental environment for the development and deployment of active Bayesian and reinforcement learning methods. Indeed, the tremendous progress achieved by machine learning (ML) and…

Disordered Systems and Neural Networks · Physics 2022-10-14 Sergei V. Kalinin , Rama Vasudevan , Yongtao Liu , Ayana Ghosh , Kevin Roccapriore , Maxim Ziatdinov

Current magnetic resonance imaging (MRI) requires the subject to remain stationary to limit motion artifacts and avoid unwanted field-induced brain stimulation. However, imaging during large-scale motion could enable studies in which motion…

Flying insects are capable of vision-based navigation in cluttered environments, reliably avoiding obstacles through fast and agile maneuvers, while being very efficient in the processing of visual stimuli. Meanwhile, autonomous micro air…

Robotics · Computer Science 2020-08-18 J. J. Hagenaars , F. Paredes-Vallés , S. M. Bohté , G. C. H. E. de Croon

The need for high-throughput, precise, and meaningful methods for measuring behavior has been amplified by our recent successes in measuring and manipulating neural circuitry. The largest challenges associated with moving in this direction,…

Biological Physics · Physics 2017-12-18 Gordon J. Berman

Recent developments in experimental neuroscience make it possible to simultaneously record the activity of thousands of neurons. However, the development of analysis approaches for such large-scale neural recordings have been slower than…

Neurons and Cognition · Quantitative Biology 2022-10-18 Rufus Mitchell-Heggs , Seigfred Prado , Giuseppe P. Gava , Mary Ann Go , Simon R. Schultz

Neuromorphic control is receiving growing attention due to the multifaceted advantages it brings over more classical control approaches, including: sparse and on-demand sensing, information transmission, and actuation; energy-efficient…

Systems and Control · Electrical Eng. & Systems 2025-06-13 Taisia Medvedeva , Alessio Franci , Fernando Castaños

Neuropixels probes, initially developed for use in small animal models, have transformed basic neuroscience by enabling high-density, single-cell resolution recordings across multiple brain regions simultaneously. The recent development of…

Cognitive neuroscience is enjoying rapid increase in extensive public brain-imaging datasets. It opens the door to large-scale statistical models. Finding a unified perspective for all available data calls for scalable and automated…

Machine Learning · Statistics 2019-05-16 Arthur Mensch , Julien Mairal , Danilo Bzdok , Bertrand Thirion , Gaël Varoquaux

Traditional mathematical approaches to studying analytically the dynamics of neural networks rely on the mean-field approximation, which is rigorously applicable only to networks of infinite size. However, all existing real biological…

Neurons and Cognition · Quantitative Biology 2019-04-30 Diego Fasoli , Stefano Panzeri