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Related papers: Physical Principles for Scalable Neural Recording

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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

Understanding the mechanical behavior of brain tissue is crucial for advancing both fundamental neuroscience and clinical applications. Yet, accurately measuring these properties remains challenging due to the brain unique mechanical…

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

A central issue in neural recording is that of distinguishing the activities of many neurons. Here, we develop a framework, based on Fisher information, to quantify how separable a neuron's activity is from the activities of nearby neurons.…

The brain is immensely complex, with diverse components and dynamic interactions building upon one another to orchestrate a wide range of functions and behaviors. Understanding patterns of these complex interactions and how they are…

Neurons and Cognition · Quantitative Biology 2024-08-06 Suman Kulkarni , Dani S. Bassett

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

The mammalian brain is a densely interconnected network that consists of millions to billions of neurons. Decoding how information is represented and processed by this neural circuitry requires the ability to capture and manipulate the…

Biological Physics · Physics 2018-05-10 Siegfried Weisenburger , Alipasha Vaziri

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

Neural activity fluctuates over a wide range of timescales within and across brain areas. Experimental observations suggest that diverse neural timescales reflect information in dynamic environments. However, how timescales are defined and…

Neurons and Cognition · Quantitative Biology 2026-01-21 Roxana Zeraati , Anna Levina , Jakob H. Macke , Richard Gao

Scaling data and artificial neural networks has transformed AI, driving breakthroughs in language and vision. Whether similar principles apply to modeling brain activity remains unclear. Here we leveraged a dataset of 3.1 million neurons…

From 1/f noise to neuronal avalanches, evidence of scaling in brain activity has been increasingly linked to tuning to or near criticality. The concept of scaling is intimately related to the renormalization group (RG), in essence providing…

Neurons and Cognition · Quantitative Biology 2026-03-17 Irem Topal , Anna Poggialini , Marco Dal Maschio , Daniele De Martino , Oren Shriki , Fabrizio Lombardi

A central challenge in the computational modeling of neural dynamics is the trade-off between accuracy and simplicity. At the level of individual neurons, nonlinear dynamics are both experimentally established and essential for neuronal…

The brain is in a state of perpetual reverberant neural activity, even in the absence of specific tasks or stimuli. Shedding light on the origin and functional significance of such a dynamical state is essential to understanding how the…

Statistical Mechanics · Physics 2022-07-08 Guillermo B. Morales , Serena Di Santo , Miguel A. Munoz

Accurate and robust recording and decoding from the central nervous system (CNS) is essential for advances in human-machine interfacing. However, technologies used to directly measure CNS activity are limited by their resolution,…

Neurons and Cognition · Quantitative Biology 2025-09-19 Jaime Ibáñez , Blanka Zicher , Etienne Burdet , Stuart N. Baker , Carsten Mehring , Dario Farina

The brain is a highly complex organ consisting of a myriad of subsystems that flexibly interact and adapt over time and context to enable perception, cognition, and behavior. Understanding the multi-scale nature of the brain, i.e., how…

Neurons and Cognition · Quantitative Biology 2025-01-17 Adam S. Charles

The continuous integration of experimental data into coherent models of the brain is an increasing challenge of modern neuroscience. Such models provide a bridge between structure and activity, and identify the mechanisms giving rise to…

Neurons and Cognition · Quantitative Biology 2017-03-03 Jannis Schuecker , Maximilian Schmidt , Sacha J. van Albada , Markus Diesmann , Moritz Helias

A technology for recording electrical activity of large neuron populations at arbitrary depth in brain tissues with less than cell spatial and millisecond temporal resolutions was the most craving dream of neuroscientists and a long pursued…

Biological Physics · Physics 2013-09-02 Roman V. Beletskiy

Head-mounted miniaturized microscopes, commonly known as miniscopes, have undergone rapid development and seen widespread adoption over the past two decades, enabling the imaging of neural activity in freely-behaving animals such as…

Neurons and Cognition · Quantitative Biology 2026-03-13 Weijian Zong , Weijian Yang

To understand Working of Human Brain measurements related to the brain function are required. These measurements should be possibly non-invasive. Brain should be disturbed as less as possible during the measurement. Integration of various…

Emerging Technologies · Computer Science 2015-06-16 Revati Shriram , M. Sundhararajan , Nivedita Daimiwal

We consider the information transmission problem in neurons and its possible implications for learning in neural networks. Our approach is based on recent developments in statistical physics and complexity science. Combining sensory…

Neurons and Cognition · Quantitative Biology 2025-09-30 Siddharth Kackar
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