Abstract Despite rapid advances in machine learning tools, the majority of neural decoding approaches still use traditional methods. Modern which are versatile and easy to use, have potential significantly improve performance. This tutorial describes how effectively apply these algorithms for typical problems. We provide descriptions, best practices, code applying common methods, including networks gradient boosting. also detailed comparisons performance various methods at task spiking...

Simultaneously measuring the activities of all neurons in a mammalian brain at millisecond resolution is challenge beyond limits existing techniques neuroscience. Entirely new approaches may be required, motivating an analysis fundamental physical constraints on problem. We outline principles governing activity mapping using optical, electrical,magnetic resonance, and molecular modalities neural recording. Focusing mouse brain, we analyze scalability each method, concentrating limitations...

A fundamental challenge for the nervous system is to encode signals spanning many orders of magnitude with neurons limited bandwidth. To meet this challenge, perceptual systems use gain control. However, whether motor uses an analogous mechanism essentially unknown. Neuromodulators, such as serotonin, are prime candidates control during force production. Serotonergic project diffusely pools, and, therefore, production by one muscle should change others. Here we present behavioral and...

Whether one is delicately placing a contact lens on the surface of eye or lifting heavy weight from floor, motor system must produce wide range forces under different dynamical loads. How does cortex, with neurons that have limited activity range, function effectively these widely varying conditions? In this study, we explored interaction in primary cortex (M1) and muscles (electromyograms, EMGs) two male rhesus monkeys for wrist movements made during three tasks requiring loads forces....

Proprioception, the sense of body position, movement, and associated forces, remains poorly understood, despite its critical role in movement. Most studies area 2, a proprioceptive somatosensory cortex, have simply compared neurons' activities to movement hand through space. Using motion tracking, we sought elaborate this relationship by characterizing how 2 activity relates whole arm movements. We found that whole-arm model, unlike classic models, successfully predicted features neural...

Our bodies and the environment constrain our movements. For example, when arm is fully outstretched, we cannot extend it further. More generally, distribution of possible movements conditioned on state in environment, which constantly changing. However, little known about how brain represents such distributions, uses them movement planning. Here, record from dorsal premotor cortex (PMd) primary motor (M1) while monkeys reach to randomly placed targets. The hand's position within workspace...

Decoding behavior, perception or cognitive state directly from neural signals is critical for brain-computer interface research and an important tool systems neuroscience. In the last decade, deep learning has become state-of-the-art method in many machine tasks ranging speech recognition to image segmentation. The success of networks other domains led a new wave applications this article, we review approaches decoding. We describe architectures used extracting useful features recording...

When a saccade is expected to result in reward, both neural activity oculomotor areas and the itself (e.g., its vigor latency) are altered (compared with when no reward expected). As such, it unclear whether correlations of indicate representation beyond movement representation; modulated may simply represent differences motor output due reward. Here, distinguish between these possibilities, we trained monkeys perform natural scene search task while recorded from frontal eye field (FEF)....

Abstract Brain-machine interfaces (BMIs) have advanced greatly in decoding speech signals originating from the motor cortices. Primarily, these BMIs target individuals with intact cortices but who are paralyzed by disrupted connections between frontal and their articulators due to brainstem stroke or neuron diseases such as amyotrophic lateral sclerosis. A few studies shown some information outside cortices, parietal temporal lobes, that also may be useful for BMIs. The ability use lobes...

Adoption of innovations, whether new ideas, technologies, or products, is crucially important to knowledge societies. The landmark studies adoption dealt with innovations having great societal impact (such as antibiotics hybrid crops) but where determining the utility innovation was straightforward fewer side effects greater yield). Recent large-scale were conducted within heterogeneous populations and focused on products little impact. Here, we focus a case practical significance: by small...

Abstract Modern recording techniques can generate large-scale measurements of multiple neural populations over extended time periods. However, it remains a challenge to model non-stationary interactions between high-dimensional neurons. To tackle this challenge, we develop recurrent switching linear dynamical systems models for populations. Here, each population is represented by unique set latent variables, which evolve dynamically in time. Populations interact with other through...

Employing DNA as a high-density data storage medium has paved the way for next-generation digital and biosensing technologies. However, multipart architecture of current DNA-based recording techniques renders them inherently slow incapable fluctuating signals with subhour frequencies. To address this limitation, we developed simplified system employing single enzyme, terminal deoxynucleotidyl transferase (TdT), to transduce environmental into DNA. TdT adds nucleotides 3′-ends single-stranded...

Abstract In many neural populations, the computationally relevant signals are posited to be a set of ‘latent factors’ – shared across individual neurons. Understanding relationship between activity and behavior requires identification factors that reflect distinct computational roles. Methods for identifying such typically require supervision, which can suboptimal if one is unsure how (or whether) grouped into distinct, meaningful sets. Here, we introduce Sparse Component Analysis (SCA), an...

When we search for visual objects, the features of those objects bias our attention across landscape (feature-based attention). The brain uses these top-down cues to select eye movement targets (spatial selection). frontal field (FEF) is a prefrontal region implicated in selecting movements and thought reflect feature-based spatial selection. Here, study how FEF facilitates selection complex natural scenes. We ask whether neurons facilitate by representing search-relevant or they are...

Despite rapid advances in machine learning tools, the majority of neural decoding approaches still use traditional methods. Modern which are versatile and easy to use, have potential significantly improve performance. This tutorial describes how effectively apply these algorithms for typical problems. We provide descriptions, best practices, code applying common methods, including networks gradient boosting. also detailed comparisons performance various methods at task spiking activity motor...

A molecular device that records time-varying signals would enable new approaches in neuroscience. We have recently proposed such a device, termed "molecular ticker tape", which an engineered DNA polymerase (DNAP) writes into the form of nucleotide misincorporation patterns. Here, we define theoretical framework quantifying expected capabilities tapes as function experimental parameters. present decoding algorithm for estimating time-dependent input signals, and DNAP kinetic parameters,...

While attentional effects in visual selection tasks have traditionally been assigned "top-down" or "bottom-up" origins, more recently it has proposed that there are three major factors affecting selection: (1) physical salience, (2) current goals and (3) history. Here, we look further into history by investigating Priming of Pop-out (POP) the Distractor Preview Effect (DPE), two inter-trial demonstrate influence recent on search performance. Using Ratcliff diffusion model, model observed...

Summary Voluntary movement requires communication from cortex to the spinal cord, where a dedicated pool of motor units (MUs) activates each muscle. The canonical description MU function rests upon two foundational tenets. First, cannot control MUs independently but supplies with common drive. Second, are recruited in rigid fashion that largely accords Henneman’s size principle. While this paradigm has considerable empirical support, direct test simultaneous observations many across diverse...

There is a strong emphasis on developing novel neuroscience technologies, in particular recording from more neurons. has thus been increasing discussion about how to analyze the resulting big datasets. What received less attention that over last 30 years, papers have progressively integrated approaches, such as electrophysiology, anatomy, and genetics. As such, there little combine this multimodal data. Here, we describe growth of discuss needed analysis advancements make sense

Current high-resolution imaging techniques require an intact sample that preserves spatial relationships. We here present a novel approach, "puzzle imaging," allows spatially scrambled sample. This technique takes many disordered samples, and then pieces them back together using local properties embedded within the show puzzle can efficiently produce images dimensionality reduction algorithms. demonstrate theoretical capabilities of in three biological scenarios, showing (1) relatively...

Abstract Our bodies and the environment constrain our movements. For example, when arm is fully outstretched, we cannot extend it further. More generally, distribution of possible movements conditioned on state in environment, which constantly changing. However, little known about how brain represents such distributions, uses them movement planning. Here, recorded from dorsal premotor cortex (PMd) primary motor (M1) while monkeys reached to randomly placed targets. The hand’s position within...

To record from a given neuron, recording technology must be able to separate the activity of that neuron its neighbors. Here, we develop Fisher information based framework determine conditions under which this is feasible for technology. This combines measurable point spread functions with noise distributions produce theoretical bounds on precision can localize neural activities. If there suffi□cient uniquely activities, then will, an theoretic perspective, these neurons. We (1) describe...