Biology subjects

Gross, R. E.

Publications and source records attributed to Gross, R. E..

At least 19 recordsLinked to original sources

bioRxiv2025

Neural components underlying successful free recall are specific to episodic memory

AbstractEpisodic memory depends upon activity distributed across the brain. However, the activity underlying memory has largely been examined within single tasks in isolation. Thus it is unclear to what extent prior findings reflect task-general rather than memory-specific cognitive processes. Here we address this question using data from 371 patients recorded intracranially who performed a free recall task with encoding and retrieval phases alongside an arithmetic distractor phase. We ask whether neural decoders fit to predict behavior from one phase transfer to the others. Encoding-retrieval transfer exceeds both arithmetic-encoding and arithmetic-retrieval transfer and therefore cannot be explained solely by processes supporting arithmetic. We further detect transfer between arithmetic and retrieval but not between arithmetic and encoding. The brain-behavioral relations observed in these tasks thus do not merely reflect a single task-general factor of activity. We propose cross-task decoding as a method for identifying the neural factor structure underlying distinct cognitive processes.

neuroscience↗

bioRxiv2025

MuFIX - Enabling Combinations of Concurrent Optogenetics and Lock-in Amplification Fiber Photometry via Removal of Optogenetic Stimulation Crosstalk

Simultaneous fiber photometry and optogenetics is a powerful emerging technique for precisely studying the interactions of neuronal brain networks. However, spectral overlap between photometry and optogenetic components has severely limited the application of an all-optical approach. Due to spectral overlap, light from optogenetic stimulation saturates the photosensor and occludes photometry fluorescence, which is especially problematic in physically smaller model organism brains like mice. Here, we demonstrate the Multi-Frequency Interpolation X- talk removal algorithm (MuFIX, or {micro}FIX) for recovering crosstalk-contaminated photometry responses recorded with lock-in amplification. {micro}FIX exploits multi-frequency lock-in amplification by modeling the remaining uncontaminated data to interpolate across crosstalk- affected segments (R2 [~] 1.0); we found that this approach accurately recovers the original photometry response after demodulation (Pearsons r [~] 1.0). When applied to crosstalk- contaminated data, {micro}FIX recovered a photometry response closely resembling the dynamics of non-crosstalk photometry recorded simultaneously. Upon further verification using simulated and empirical data, we demonstrated that {micro}FIX reproduces any signal that underwent simulated crosstalk contamination (r [~] 1.0). We believe adopting {micro}FIX will enable experimental designs using simultaneous fiber photometry and optogenetics that were previously not feasible due to crosstalk.

neuroscience↗

bioRxiv2025

A wireless, 60-channel, AI-enabled neurostimulation platform

ObjectiveClosed-loop neuromodulatory therapies require devices that can both decode ongoing brain states and deliver multi-site stimulation. MethodsWe describe the Smart Neurostimulation System (SNS), a cranially mounted implant with 60 configurable recording/stimulation channels, inductive power, and onboard spectral-feature classification. In three freely-moving sheep we streamed local-field potentials and conducted two parameter sweep experiments. ResultsCross-validated movement classifiers achieved an average AUC > 0.95. Increasing stimulation amplitude and frequency produced post-stimulation elevations in -band (8-12 Hz) and{gamma} -band (78-82 Hz) power at most target locations. ConclusionThe SNS unifies high-density sensing, real-time brain state decoding, and programmable closed-loop stimulation in a single device, demonstrating behavioral-state prediction and parameter-dependent neuromodulation in vivo. SignificanceThese findings establish a preclinical foundation for biomarker-guided stimulation targeting distributed cortical networks underlying memory and cognition. HighlightsO_LIWireless 60-channel implant enables simultaneous sensing and stimulation C_LIO_LIvine study demonstrates reliable classification of movement and stimulation-related modulation of spectral activity C_LIO_LIThe SNS represents a platform for biomarker-guided neuromodulation therapies C_LI

neuroscience↗

bioRxiv2025

Post-Ictal Gamma Oscillations Predict Hippocampal Structural Integrity in Mesial Temporal Lobe Epilepsy

The underlying histopathology and epileptic network of patients with mesial temporal lobe epilepsy (mTLE) are difficult to ascertain. Here, we report a novel electrical activity following seizure termination, termed post-ictal gamma oscillations (PIGOs), recorded in mice with intrahippocampal kainic acid injection and a patient with mTLE. PIGOs are characterized by a spectral shift of increased power in gamma frequencies relative to decreased power in other frequencies, generating a gamma peak. PIGOs are accompanied by increased intracellular calcium levels among parvalbumin-positive interneurons and a direct current shift. Only a subgroup of animals in the study had PIGOs. These animals had less pronounced hippocampal sclerosis (HS) than those without PIGOs. To illustrate the translational potential of these findings, we analyzed data from two patients with unilateral mTLE, one with PIGOs and the other without. The patient with PIGOs had symmetrical hippocampi on neuroimaging, whereas the other exhibited overly decreased interictal glucose uptake in left hippocampus, suggesting left-sided HS. After receiving laser ablation of mesial temporal regions, the patient with PIGOs became seizure-free, whereas the other did not. Our results suggest that PIGOs may serve as a biomarker for a milder form of HS in patients with mTLE and for predicting treatment outcomes.

neuroscience↗

bioRxiv2024

Organellular imaging in vivo reveals a depletion of endoplasmic reticular calcium during post-ictal cortical spreading depolarization

AO_SCPLOWBSTRACTC_SCPLOWDuring cortical spreading depolarization (CSD), neurons exhibit a dramatic increase in cytosolic calcium, which may be integral to CSD-mediated seizure termination. This calcium increase greatly exceeds that during seizures, suggesting the calcium source may not be solely extracellular. Thus, we sought to determine if the endoplasmic reticulum (ER), the largest intracellular calcium store, is involved. We developed a two-photon calcium imaging paradigm to simultaneously record the cytosol and ER during seizures in awake mice. Paired with direct current recording, we reveal that CSD can manifest as a slow post-ictal cytosolic calcium wave with a concomitant depletion of ER calcium that is spatiotemporally consistent with a calcium-induced calcium release. Importantly, we observed both naturally occurring and electrically induced CSD suppressed post-ictal epileptiform activity. Collectively, this work links ER dynamics to CSD, which serves as an innate process for seizure suppression and a potential mechanism underlying therapeutic electrical stimulation for epilepsy.

neuroscience↗

bioRxiv2024

Exercise Evokes Retained Motor Performance without Neuroprotection in a Mouse Model of Parkinson's Disease

Exercise has been extensively studied in Parkinsons Disease, with a particular focus on the potential for neuroprotection that has been demonstrated in animal models. While this preclinical work has provided insight into the underlying molecular mechanisms, it has not addressed the neurophysiological changes during exercise. Here, first, we tested for neuroprotective effects of adaptive wheel running exercise in the 6-hydroxydopamine mouse model of Parkinsons disease, assessing for dopaminergic cell preservation. Finding none, despite running performance that equaled the pre-parkinsonian state, we probed the neurophysiology of running exercise as a transient state of high motor function amidst an unameliorated Parkinsonian lesion. Exercise was associated with characteristic, excitatory changes in the dopamine-depleted substantia nigra, which could be suppressed along with running itself by dopamine receptor blockade. Going forward, the functional state evoked by exercise merits further study, as it has parallels in human disease and may represent an optimal physiologic target for neuromodulation.

neuroscience↗

bioRxiv2024

Refining Brain Stimulation Therapies: An Active Learning Approach to Personalization

Brain stimulation holds promise for treating brain disorders, but personalizing therapy remains challenging. Effective treatment requires establishing a functional link between stimulation parameters and brain response, yet traditional methods like random sampling (RS) are inefficient and costly. To overcome this, we developed an active learning (AL) framework that identifies optimal relationships between stimulation parameters and brain response with fewer experiments. We validated this framework through three experiments: (1) in silico modeling with synthetic data from a Parkinsons disease model, (2) in silico modeling with real data from a non-human primate, and (3) in vivo modeling with a real-time rat optogenetic stimulation experiment. In each experiment, we compared AL models to RS models, using various query strategies and stimulation parameters (amplitude, frequency, pulse width). AL models consistently outperformed RS models, achieving lower error on unseen test data in silico (p<0.0056, N=1,000) and in vivo (p=0.0036, N=20). This approach represents a significant advancement in brain stimulation, potentially improving both research and clinical applications by making them more efficient and effective. Our findings suggest that AL can substantially reduce the cost and time required for developing personalized brain stimulation therapies, paving the way for more effective and accessible treatments for brain disorders.

neuroscience↗

bioRxiv2024

SAFE-OPT: A Bayesian optimization algorithm for learning optimal deep brain stimulation parameters with safety constraints

To treat neurological and psychiatric diseases with deep brain stimulation, a trained clinician must select parameters for each patient by monitoring their symptoms and side-effects in a months-long trial-and-error process, delaying optimal clinical outcomes. Bayesian optimization has been proposed as an efficient method to quickly and automatically search for optimal parameters. However, conventional Bayesian optimization does not account for patient safety and could trigger unwanted or dangerous side-effects. In this study we develop SAFE-OPT, a Bayesian optimization algorithm designed to learn subject-specific safety constraints to avoid potentially harmful stimulation settings during optimization. We prototype and validate SAFE-OPT using a rodent multielectrode stimulation paradigm which causes subject-specific performance deficits in a spatial memory task. We first use data from an initial cohort of subjects to build a simulation where we design the best SAFE-OPT configuration for safe and accurate searching in silico. We then deploy both SAFE-OPT and conventional Bayesian optimization in new subjects in vivo, showing that SAFE-OPT can find an optimally high stimulation amplitude that does not harm task performance with comparable sample efficiency to Bayesian optimization and without selecting amplitude values that exceed the subjects safety threshold. The incorporation of safety constraints will provide a key step for adopting Bayesian optimization in real-world applications of deep brain stimulation.

bioengineering↗

bioRxiv2023

Study-Phase Reinstatement: Encoding Spontaneous Thoughts as Memories

Can the brain improve the retrievability of an experience after it has occurred? Systems consolidation theory proposes that item-specific cortical reactivation during post-encoding rest periods facilitates the formation of stable memory representations, a prediction supported by neural evidence in humans and animals. Such reactivation may also occur on shorter time scales, offering a potential account of classic list memory phenomena but lacking in support from neural data. Leveraging the high-temporal specificity of intracranial electroencephalography (iEEG), we investigate spontaneous reactivation of previously experienced items during brief intervals between individual encoding events. Across two large-scale free recall experiments, we show that reactivation during these periods, measured by spectral iEEG similarity, predicts subsequent recall. In a third experiment, we show that the same methodology can identify post-encoding reactivation that correlates with subsequent memory, consistent with previous results. Thus, spontaneous study-phase reinstatement reliably predicts memory behavior, linking psychological accounts to neural mechanisms and providing evidence for rapid consolidation processes during encoding.

neuroscience↗

bioRxiv2023

Seizure event detection using intravital two-photon calcium imaging data

SignificanceGenetic cellular calcium imaging has emerged as a powerful tool to investigate how different types of neurons interact at the microcircuit level to produce seizure activity, with newfound potential to understand epilepsy. Although many methods exist to measure seizure-related activity in traditional electrophysiology, few yet exist for calcium imaging. AimTo demonstrate an automated algorithmic framework to detect seizure-related events using calcium imaging - including the detection of pre-ictal spike events, propagation of the seizure wavefront, and terminal spreading waves for both population-level activity and that of individual cells. ApproachWe developed an algorithm for precise recruitment detection of population and individual cells during seizure-associated events, which broadly leverages averaged population activity and high-magnitude slope features to detect single-cell pre-ictal spike and seizure recruitment. We applied this method to data recorded using awake in vivo two-photon calcium imaging during pentylenetetrazol induced seizures in mice. ResultsWe demonstrate that our detected recruitment times are concordant with visually identified labels provided by an expert reviewer and are sufficiently accurate to model the spatiotemporal progression of seizure-associated traveling waves. ConclusionsOur algorithm enables accurate cell recruitment detection and will serve as a useful tool for researchers investigating seizure dynamics using calcium imaging.

neuroscience↗

bioRxiv2023

Functional and anatomical connectivity predict brain stimulation's mnemonic effects

Closed-loop direct brain stimulation is a promising tool for modulating neural activity and behavior. However, it remains unclear how to optimally target stimulation to modulate brain activity in particular brain networks that underlie particular cognitive functions. Here, we test the hypothesis that stimulations behavioral and physiological effects depend on the stimulation targets anatomical and functional network properties. We delivered closed-loop stimulation as 47 neurosurgical patients studied and recalled word lists. Multivariate classifiers, trained to predict momentary lapses in memory function, triggered stimulation of the lateral temporal cortex (LTC) during the study phase of the task. We found that LTC stimulation specifically improved memory when delivered to targets near white matter pathways. Memory improvement was largest for targets near white matter that also showed high functional connectivity to the brains memory network. These targets also reduced low-frequency activity in this network, an established marker of successful memory encoding. These data reveal how anatomical and functional networks mediate stimulations behavioral and physiological effects, provide further evidence that closed-loop LTC stimulation can improve episodic memory, and suggest a method for optimizing neuromodulation through improved stimulation targeting.

neuroscience↗

bioRxiv2023

The Entrainment of the Substantia Nigra During Temporal Lobe Seizures is Dependent on the Seizure Onset Pattern

Temporal lobe (TL) epilepsy is the most common form of drug-resistant epilepsy. A major focus of human and animal studies on TLE network has been the limbic circuit and the structures composing the temporal lobe. However, there is also evidence suggesting an active role of the basal ganglia in the propagation and control of temporal lobe seizures. Evidence suggests that the network involved in temporal lobe seizure may depend on their onset and offset pattern but studies on the relationship between the patterns and extralimbic activity are limited. Here, we characterize the involvement of the substantia nigra (SN) and somatosensory cortex (SI) during temporal lobe seizures induced in two nonhuman primates (NHP). The seizure onset and offset patterns were manually classified and spectral power and coherence were calculated. We then analyzed the three first and last seconds of the seizure as well as 3-second segments of recorded in pre-ictal and post-ictal periods and compared the changes based on the seizure onset and offset patterns. Our results demonstrated an involvement of the SN and SI dependent on the seizure onset and offset pattern. We found that seizures with both low amplitude fast activity (LAF) and high amplitude slow activity (HAS) onset patterns were associated with an increase in activity of the SN while the change in activity was limited to LAF seizures in the SI. However, the increase of HPC/SI coherence was similar for both type of onset, while the increase in HPC/SN coherence was specific to the farther-spreading LAF onset pattern. As for the role of the SN in seizure cessation, we observed that the coherence between the HPC/SN was reduced during burst suppression (BS) compared to other termination phases. Additionally, we found that this coherence returned to normal levels after the seizure ended, with no significant difference in post-ictal periods among the three types of seizure offsets. This result suggests that the SN might be involved differently in the termination of the BS seizure pattern. This study constitutes the first demonstration of temporal lobe seizures entraining the SN in the primate brain. Moreover, these findings provide evidence that this entrainment is dependent on the seizure onset pattern and support the hypothesis that the SN might play a role in the maintenance and termination of some specific temporal lobe seizure.

neuroscience↗

bioRxiv2023

Adaptive Bayesian Optimization for State-Dependent Brain Stimulation

Brain stimulation has become an important treatment option for a variety of neurological and psychiatric diseases. A key challenge in improving brain stimulation is selecting the optimal set of stimulation parameters for each patient, as parameter spaces are too large for brute-force search and their induced effects can exhibit complex subject-specific behavior. To achieve greatest effectiveness, stimulation parameters may additionally need to be adjusted based on an underlying neural state, which may be unknown, unmeasurable, or challenging to quantify a priori. In this study, we first develop a simulation of a state-dependent brain stimulation experiment using rodent optogenetic stimulation data. We then use this simulation to demonstrate and evaluate two implementations of an adaptive Bayesian optimization algorithm that can model a dynamically changing response to stimulation parameters without requiring knowledge of the underlying neural state. We show that, while standard Bayesian optimization converges and overfits to a single optimal set of stimulation parameters, adaptive Bayesian optimization can continue to update and explore as the neural state is changing and can provide more accurate optimal parameter estimation when the optimal stimulation parameters shift. These results suggest that learning algorithms such as adaptive Bayesian optimization can successfully find optimal state-dependent stimulation parameters, even when brain sensing and decoding technologies are insufficient to track the relevant neural state.

neuroscience↗

bioRxiv2022

Chronic activation of dopaminergic neurons via bioluminescence-optogenetics provides neuroprotection in a rodent model of Parkinson's disease

Previous studies in human patients and rodent models of Parkinsons disease (PD) have established neuroprotection of dopaminergic (DA) neurons in substantia nigra pars compacta (SNC) by physical exercise, but the precise origin of this neuroprotective effect has yet to be elucidated. In this study, we tested a hypothesis that enhanced activity of DA neurons in SNC results in neuroprotection using the unilateral 6-hydroxydopamine (6-OHDA) injection model in mice. To increase activity of DA neurons chronically and specifically, we injected an adeno-associated viral vector carrying a step-function luminopsin (SFL) - a fusion protein of light-emitting Gaussia luciferase and light-sensing step-function channelrhodopsin 2 - into SNC ipsilateral to 6-OHDA using the pan-neuronal human synapsin I promoter or the Cre-lox system in transgenic mice expressing the recombinase under control of the tyrosine hydroxylase (TH) promoter. Upon application of SFL substrate, coelenterazine (CTZ), the luciferase moiety of luminopsin emits bioluminescence which in turn activate the opsin moiety. Daily injection of CTZ for 4 weeks ameliorated a stereotypical behavior, namely ipsiversive rotations, induced by unilateral 6-OHDA. In addition, postmortem immunohistochemistry against TH revealed less severe neurodegeneration of DA neurons compared to vehicle-injected control animals. Furthermore, when mice were pretreated with ANA-12, a selective antagonist for tropomyosin receptor kinase B (TrkB), the behavioral improvement and neuroprotective effect were diminished. These results suggest that increased neuronal activity of DA neurons provides neuroprotection against 6-OHDA injury and alleviates its symptoms through the brain-derived neurotrophic factor-TrkB pathway.

neuroscience↗

bioRxiv2022

Irregular optogenetic stimulation waveforms can induce naturalistic patterns of hippocampal spectral activity

IntroductionBrain stimulation is a fundamental and effective therapy for neurological diseases including Parkinsons disease, essential tremor, and epilepsy. One key challenge in delivering effective brain stimulation is identifying the stimulation parameters, such as the amplitude, frequency, contact configuration, and pulse width, that induce an optimal change in symptoms, behavior, or neural activity. Most clinical and translational studies use constant-frequency pulses of stimulation, but stimulation with irregular pulse patterns or non-pulsatile waveforms might induce unique changes in neural activity that could enable better therapeutic responses. Here, we comprehensively evaluate several optogenetic stimulation waveforms, report their differing effects on hippocampal spectral activity, and compare these induced effects to activity recorded during natural behavior. MethodsSprague-Dawley rats were prepared for pan-neuronal excitatory optogenetic stimulation of the medial septum (hSyn-ChR2) and 16-channel microelectrode recording in CA1 and CA3 layers of the hippocampus. We performed grid and random sampling of the parameters comprising several stimulation waveforms, including standard pulse, nested pulse, sinusoid, double sinusoid, and Poisson pulse waveforms. ResultsWe comprehensively report the effects of changing stimulation parameters in these parameter spaces on two key biomarkers of hippocampal function, theta (4-10 Hz) and gamma (32-50 Hz) power. Similarly, robust excitation of hippocampal gamma power was observed across all waveforms, whereas no set of stimulation parameters was sufficient to consistently increase power in the theta band beyond baseline levels of activity (despite the prominent role of the medial septum in pacing hippocampal theta oscillations). Using a manifold learning algorithm to compare high-dimensional neural activity, we show that irregular stimulation patterns produce differing effects with respect to multi-band patterns of activity and can induce activity patterns that more closely resemble activity recorded during natural behavior than conventional parameters. ConclusionOur counter-intuitive findings - that stimulation of the medial septum ubiquitously does not increase hippocampal theta power, and that different waveforms have similar effects on single power bands - contradict recent trends in brain stimulation research, necessitating greater caution and fewer mechanistic assumptions as to how a given stimulation target or waveform will modulate a neurophysiological biomarker of disease. We also reveal that irregular stimulation patterns can have biomimetic utility, promoting their exploration in medical applications where inducing a particular activity pattern can have therapeutic benefit. Last, we demonstrate a scalable data-driven analysis strategy that can make the discovery of such physiologically informed temporal stimulation patterns more empirically tractable in translational settings.

neuroscience↗

bioRxiv2022

Decoding Depression During Subcallosal Cingulate Deep Brain Stimulation

AO_SCPLOWBSTRACTC_SCPLOWDeep brain stimulation of subcallosal cingulate white matter (SCCwm-DBS) alleviates symptoms of treatment resistant depression (TRD) over months of therapy. Readouts of depression symptom severity derived from neural recordings are needed for more systematic study and improvement of the therapy. In this study, we measured local field potentials (LFP) multiple times a day alongside seven months of therapy using the Activa PC+S in six patients treated with SCCwm-DBS. We found significant changes in oscillatory power between early and late therapy after accounting for stimulation-related distortions, particularly within the {beta} band. We then used a decoder strategy to identify oscillatory activity that tracked with depression measurements over seven months, with asymmetric{delta} and {beta} oscillations contributing to a statistically significant prediction of 10% of the measured depression signal. Simulating its use in clinical decision-making, we demonstrated that the DR-SCC yield clinically meaningful information that can augment other measures of depression state. Ultimately, this DR-SCC provides a data-driven first-step towards objectively tracking chronic recovery after antidepressant DBS implantation and developing adaptive DBS strategies in the presence of active stimulation.

neuroscience↗

bioRxiv2021

Kinetic Monitoring Of Neuronal Stress Response To Proteostasis Dysfunction

Proteostasis dysfunction and activation of the unfolded protein response (UPR) are characteristic of all major neurodegenerative diseases. Nevertheless, although the UPR and proteostasis dysfunction has been studied in great detail in model organisms like yeast and mammalian cell lines, it has not yet been examined in neurons. In this study, we applied a viral vector-mediated expression of a reporter protein based on a UPR transcription factor, ATF4, and time-lapse fluorescent microscopy to elucidate how mouse primary neurons respond to pharmacological and genetic perturbations to neuronal proteostasis. In in vitro models of endoplasmic reticulum (ER) stress and proteasome inhibition, we used the ATF4 reporter to reveal the time course of the neuronal stress response relative to neurite degeneration and asynchronous cell death. We showed how potential neurodegenerative disease co-factors, ER stress and mutant -synuclein overexpression, impacted neuronal stress response and overall cellular health. This work therefore introduces a viral vector-based reporter that yields a quantifiable readout suitable for non-cell destructive kinetic monitoring of proteostasis dysfunction in neurons by harnessing ATF4 signaling as part of the UPR activation.

cell biology↗

bioRxiv2020

Distinct cortical systems reinstate the content and context of episodic memories

Episodic recall depends upon the reinstatement of cortical activity present during the formation of a memory. We identified dissociable cortical networks via functional connectivity that uniquely reinstated semantic content and temporal context of previously studied stimuli during free recall. Network-specific reinstatement predicted the temporal and semantic organization of recall sequences, demonstrating how specialized cortical systems enable the human brain to target specific memories.

neuroscience↗