Biology subjects

Glaser, J. I.

Publications and source records attributed to Glaser, J. I..

12 recordsLinked to original sources

bioRxiv2026

Multi-area activity in mouse motor cortex associated with one- and two-handed oromanual dexterity

Cortical dynamics during goal-directed dexterous hand movements are mainly understood from paradigms involving use of the contralateral hand. To study how movement-related activity changes when the ipsilateral or both hands are used, we exploited a natural form of rodent manual dexterity - food handling - that rodents can perform uni- or bimanually. We sampled kilohertz 3D kinematics as mice used either or both hands to manipulate food, while recording spiking activity in forelimb primary (fl-M1) and secondary (fl-M2) motor cortices, and in a lateral oral and manual (LOM) motor cortex area implicated in oromanual food handling. Unit- and population-level analyses showed that activity in fl-M1 and fl-M2 depended on both laterality (ipsi- vs contralateral) and "manuality" (uni- vs bimanual), with few differences between the two areas. By comparison, activity in LOM was largely laterality- and manuality-invariant. These results demonstrate how activity in multiple areas of mouse motor cortex varies as the same task is performed unimanually with either hand or bimanually with both. Our findings support a model in which fl-M1 and fl-M2 maintain separable information about both forelimbs for bimanual coordination, while LOM encodes ingestion-related forelimb parameters necessary for oromanual coordination.

neuroscience↗

bioRxiv2026

Flexible integration of corollary discharge and sensory feedback signals in somatosensory cortex

Motor control depends on the continuous integration of motor and sensory signals to maintain accurate estimates of body state, yet neural evidence for this integration remains elusive. Here, we investigated the interaction of motor corollary discharge and proprioceptive feedback signals in area 2 of monkey somatosensory cortex during voluntary and externally-perturbed reaching tasks. Though single neurons had mixed responses to corollary discharge and sensory feedback, we disentangled these signals at the population level to discover they occupy approximately orthogonal subspaces. Integrating information across these subspaces enabled accurate body state estimation prior to feedback arrival during voluntary movements. Moreover, the orthogonal population geometry of corollary discharge and sensory feedback enabled cancellation of movement-related signals to improve the decoding of external perturbations. Together, these results identified orthogonality as a population-level coding strategy for flexible integration of motor and sensory signals to support multiple distinct computations.

neuroscience↗

bioRxiv2025

Constraining inference of across-region interactions using neural activity perturbations

Functional interactions between brain regions are often inferred from multi-region models fit to neural activity recorded in behaving animals. Here, we show that inference of acrossregion interactions is hindered by the wide breadth of model fits consistent with naturally occurring neural activity. In contrast, models fit to activity that includes region-wide activity perturbations provide well-constrained estimates of across-region interactions; simulations suggest these estimates can be accurate.

neuroscience↗

bioRxiv2025

Active Dissociation of Intracortical Spiking and High Gamma Activity

Cortical high gamma activity (HGA) is used in many scientific investigations, yet its biophysical source is a matter of debate. Two leading hypotheses are that HGA predominantly represents summed postsynaptic potentials or-more commonly- predominantly represents summed local spikes. If the latter were true, the nearest neurons to an electrode should contribute most to HGA recorded on that electrode. We trained subjects to decouple local spiking from HGA on a single electrode using a brain-machine interface. Their ability to decouple them suggested that HGA is likely not simply generated by summed local spiking. Instead, HGA correlated with neuronal population co-firing of neurons that were widely distributed across millimeters. The neuronal spikes that contributed more to this co-firing also contributed more to, and preceded, spike-triggered HGA. These results suggest that HGA arises predominantly from summed postsynaptic potentials triggered by synchronous co-firing of widely distributed neurons.

neuroscience↗

bioRxiv2024

Identifying Interpretable Latent Factors with Sparse Component Analysis

In many neural populations, the computationally relevant signals are posited to be a set of latent factors - signals shared across many individual neurons. Understanding the relationship between neural activity and behavior requires the identification of factors that reflect distinct computational roles. Methods for identifying such factors typically require supervision, which can be suboptimal if one is unsure how (or whether) factors can be grouped into distinct, meaningful sets. Here, we introduce Sparse Component Analysis (SCA), an unsupervised method that identifies interpretable latent factors. SCA seeks factors that are sparse in time and occupy orthogonal dimensions. With these simple constraints, SCA facilitates surprisingly clear parcellations of neural activity across a range of behaviors. We applied SCA to motor cortex activity from reaching and cycling monkeys, single-trial imaging data from C. elegans, and activity from a multitask artificial network. SCA consistently identified sets of factors that were useful in describing network computations.

neuroscience↗

bioRxiv2021

Recording Temporal Signals with Minutes Resolution Using Enzymatic DNA Synthesis

Employing DNA as a high-density data storage medium has paved the way for next-generation digital storage and biosensing technologies. However, the multipart architecture of current DNA-based recording techniques renders them inherently slow and incapable of recording fluctuating signals with sub-hour frequencies. To address this limitation, we developed a simplified system employing a single enzyme, terminal deoxynucleotidyl transferase (TdT), to transduce environmental signals into DNA. TdT adds nucleotides to the 3 ends of single-stranded DNA (ssDNA) in a template-independent manner, selecting bases according to inherent preferences and environmental conditions. By characterizing TdT nucleotide selectivity under different conditions, we show that TdT can encode various physiologically relevant signals like Co2+, Ca2+, Zn2+ concentrations and temperature changes in vitro. Further, by considering the average rate of nucleotide incorporation, we show that the resulting ssDNA functions as a molecular ticker tape. With this method we accurately encode a temporal record of fluctuations in Co2+ concentration to within 1 minute over a 60-minute period. Finally, we engineer TdT to allosterically turn off in the presence of physiologically relevant concentration of calcium. We use this engineered TdT in concert with a reference TdT to develop a two-polymerase system capable of recording a single step change in Ca2+ signal to within 1 minute over a 60-minute period. This work expands the repertoire of DNA-based recording techniques by developing a novel DNA synthesis-based system that can record temporal environmental signals into DNA with minutes resolution.

synthetic biology↗

bioRxiv2021

Flexible neural control of motor units

Voluntary movement requires communication from cortex to the spinal cord, where a dedicated pool of motor units (MUs) activates each muscle. The canonical description of MU function rests upon two foundational tenets. First, cortex cannot control MUs independently but supplies each pool with a common drive. Second, MUs are recruited in a rigid fashion that largely accords with Hennemans size principle. While this paradigm has considerable empirical support, a direct test requires simultaneous observations of many MUs across diverse force profiles. We developed an isometric task that allowed stable MU recordings even during rapidly changing forces. MU activity patterns were surprisingly behavior-dependent. MU activity could not be accurately described as reflecting common drive, but could be captured by assuming multiple drives. Neuropixels probe recordings revealed that, consistent with the requirements of flexible control, the motor cortex population response displays a great many degrees of freedom. Neighboring cortical sites recruited different MUs. Thus, MU activity is flexibly controlled to meet task demands, and cortex may contribute to this ability.

neuroscience↗

bioRxiv2020

Recurrent Switching Dynamical Systems Models for Multiple Interacting Neural Populations

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 populations of neurons. To tackle this challenge, we develop recurrent switching linear dynamical systems models for multiple populations. Here, each high-dimensional neural population is represented by a unique set of latent variables, which evolve dynamically in time. Populations interact with each other through this low-dimensional space. We allow the nature of these interactions to change over time by using a discrete set of dynamical states. Additionally, we parameterize these discrete state transition rules to capture which neural populations are responsible for switching between interaction states. To fit the model, we use variational expectation-maximization with a structured mean-field approximation. After validating the model on simulations, we apply it to two different neural datasets: spiking activity from motor areas in a non-human primate, and calcium imaging from neurons in the nematode C. elegans. In both datasets, the model reveals behaviorally-relevant discrete states with unique inter-population interactions and different populations that predict transitioning between these states.

neuroscience↗

bioRxiv2019

Area 2 of primary somatosensory cortex encodes kinematics of the whole arm

AO_SCPLOWBSTRACTC_SCPLOWProprioception, the sense of body position, movement, and associated forces, remains poorly understood, despite its critical role in movement. Most studies of area 2, a proprioceptive area of somatosensory cortex, have simply compared neurons activities to the movement of the hand through space. By using motion tracking, we sought to elaborate this relationship by characterizing how area 2 activity relates to whole arm movements. We found that a whole-arm model, unlike classic models, successfully predicted how features of neural activity changed as monkeys reached to targets in two workspaces. However, when we then evaluated this whole-arm model across active and passive movements, we found that many neurons did not consistently represent the whole arm over both conditions. These results suggest that 1) neural activity in area 2 includes representation of the whole arm during reaching and 2) many of these neurons represented limb state differently during active and passive movements.

neuroscience↗

bioRxiv2019

Recording temporal data onto DNA with minutes resolution

Recording biological signals can be difficult in three-dimensional matrices, such as tissue. We present a DNA polymerase-based strategy that records temporal biosignals locally onto DNA to be read out later, which could obviate the need to extract information from tissue on the fly. We use a template-independent DNA polymerase, terminal deoxynucleotidyl transferase (TdT) that probabilistically adds dNTPs to single-stranded DNA (ssDNA) substrates without a template. We show that in vitro, the dNTP-incorporation preference of TdT changes with the presence of Co2+, Ca2+, Zn2+ and temperature. Extracting the signal profile over time is possible by examining the dNTP incorporation preference along the length of synthesized ssDNA strands like a molecular ticker tape. We call this TdT-based untemplated recording of temporal local environmental signals (TURTLES). We show that we can determine the time of Co2+ addition to within two minutes over a 60-minute period. Further, TURTLES has the capability to record multiple fluctuations. We can estimate the rise and fall of an input Co2+ pulse to within three minutes. TURTLES has at least 200-fold better temporal resolution than all previous DNA-based recording techniques.

synthetic biology↗

bioRxiv2018

From preliminary to definitive plans: two classes of neurons in frontal eye field

Prior to selecting an action, we often consider other possibilities. How does the brain represent these preliminary plans prior to action selection? Here, we investigated this question in the oculomotor system during self-guided search of natural scenes. We found two classes of neurons in the frontal eye field (FEF): 1) \"late selection neurons\" that represented the selected action plan not long before the upcoming saccade, and 2) \"early selection neurons\" that became predictive of the upcoming saccade much earlier, often before the previous saccade had even ended. Crucially, these early selection neurons did not only predict the upcoming saccade direction; they also reflected the probabilities of possible upcoming saccades, even when they did not end up being selected. Our results demonstrate that during naturalistic eye movements, separate populations of neurons code for preliminary and definitive plans.

neuroscience↗

bioRxiv2017

Population Coding Of Conditional Probability Distributions In Dorsal Premotor Cortex

Our bodies and the environment constrain our movements. For example, when our arm is fully outstretched, we cannot extend it further. More generally, the distribution of possible movements is conditioned on the state of our bodies in the environment, which is constantly changing. However, little is known about how the brain represents such distributions, and uses them in movement planning. Here, we recorded from dorsal premotor cortex (PMd) and primary motor cortex (M1) while monkeys reached to randomly placed targets. The hands position within the workspace created probability distributions of possible upcoming targets, which affected movement trajectories and latencies. PMd, but not M1, neurons had increased activity when the monkeys hand position made it likely the upcoming movement would be in the neurons preferred directions. Across the population, PMd activity represented probability distributions of individual upcoming reaches, which depended on rapidly changing information about the bodys state in the environment.

neuroscience↗