Biology subjects

Herzfeld, D. J.

Publications and source records attributed to Herzfeld, D. J..

8 recordsLinked to original sources

bioRxiv2025

Neural circuit mechanisms to transform cerebellar population dynamics for motor control in monkeys

We identify the input-output transformations performed by the cerebellar circuit and isolate the circuit properties that implement them. Extracellular recordings exploited new technology for neuron-type identification in part of the cerebellar cortex that is causal for an oculomotor behavior whose neural substrate is well-understood in monkeys. Data demonstrate how multiple classes of interneurons in the cerebellar circuit cooperate to transform incoming mossy fiber responses into Purkinje cell outputs. Computer models suggest that temporal decomposition in the granule cell layer enables flexible reconstruction of transformed output dynamics, regulated by cerebellar plasticity, to convert eye position-like inputs into predominantly velocity-driven Purkinje cell outputs. Convergence of mossy fiber inputs with diverse direction preferences would increase input layer dimensionality and enable learning of highly flexible direction tuning. The neural circuit mechanisms suggested by our data outline a cerebellar operating principle that enables flexible input-output transformations and could generalize across cerebellar and other brain areas.

neuroscience↗

bioRxiv2025

Strategies to decipher neuron identity from extracellular recordings in the cerebellum of behaving non-human primates

Identification of neuron type is critical to understand computation in neural circuits through extracellular recordings in awake, behaving animal subjects. Yet, modern recording probes have limited power to resolve neuron type. Here, we leverage the well-characterized architecture of the cerebellar circuit to perform expert identification of neuron type from extracellular recordings in behaving non-human primates. Using deep-learning classifiers we evaluate the information contained in readily accessible extracellular features for neuron identification. Waveform, discharge statistics, anatomical layer, and functional interactions each can inform neuron labels for a sizable fraction of cerebellar units. Together, as inputs to a deep-learning classifier, the features perform even better. Our tools and methodologies, validated during smooth pursuit eye movements in the cerebellar floccular complex of awake behaving monkeys, can guide expert identification of neuron type during cerebellar-dependent tasks in behaving animals across species. They lay the groundwork for characterization of information processing in the cerebellar cortex. Impact statementTo understand how the brain performs computations in the service of behavior, we develop methods to link neuron type to functional activity within well-characterized neural circuits. Here, we show how features derived from extracellular recordings provide complementary information to disambiguate neuron identity in the cerebellar cortex.

neuroscience↗

bioRxiv2024

A deep-learning strategy to identify cell types across species from high-density extracellular recordings

High-density probes allow electrophysiological recordings from many neurons simultaneously across entire brain circuits but dont reveal cell type. Here, we develop a strategy to identify cell types from extracellular recordings in awake animals, revealing the computational roles of neurons with distinct functional, molecular, and anatomical properties. We combine optogenetic activation and pharmacology using the cerebellum as a testbed to generate a curated ground-truth library of electrophysiological properties for Purkinje cells, molecular layer interneurons, Golgi cells, and mossy fibers. We train a semi-supervised deep-learning classifier that predicts cell types with greater than 95% accuracy based on waveform, discharge statistics, and layer of the recorded neuron. The classifiers predictions agree with expert classification on recordings using different probes, in different laboratories, from functionally distinct cerebellar regions, and across animal species. Our classifier extends the power of modern dynamical systems analyses by revealing the unique contributions of simultaneously-recorded cell types during behavior.

neuroscience↗

bioRxiv2023

Rate versus synchrony codes for cerebellar control of motor behavior

Control of movement requires the coordination of multiple brain areas, each containing populations of neurons that receive inputs, process these inputs via recurrent dynamics, and then relay the processed information to downstream populations. Information transmission between neural populations could occur through either coordinated changes in firing rates or the precise transmission of spike timing. We investigate the nature of the code for transmission of signals to downstream areas from a part of the cerebellar cortex that is crucial for the accurate execution of a quantifiable motor behavior. Simultaneous recordings from Purkinje cell pairs in the cerebellar flocculus of rhesus macaques revealed how these cells coordinate their activity to drive smooth pursuit eye movements. Purkinje cells show millisecond-scale coordination of spikes (synchrony), but the level of synchrony is small and likely insufficient to impact the firing of downstream neurons in the vestibular nucleus. Further, analysis of previous metrics for assaying Purkinje cell synchrony demonstrates that these metrics conflate changes in firing rate and neuron-neuron covariance. We conclude that the output of the cerebellar cortex uses primarily a rate code rather than synchrony code to drive activity of downstream neurons and thus control motor behavior. Impact statementInformation transmission in the brain can occur via changes in firing rate or via the precise timing of spikes. Simultaneous recordings from pairs of Purkinje cells in the floccular complex reveals that information transmission out of the cerebellar cortex relies almost exclusively on changes in firing rates rather than millisecond-scale coordination of spike timing across the Purkinje cell population.

neuroscience↗

bioRxiv2021

Evaluation and resolution of many challenges of neural spike-sorting: a new sorter

We evaluate existing spike sorters and present a new one that resolves many sorting challenges. The new sorter, called "full binary pursuit" or FBP, comprises multiple steps. First, it thresholds and clusters to identify the waveforms of all unique neurons in the recording. Second, it uses greedy binary pursuit to optimally recognize the spike events in the original voltages. Third, it resolves spike events that are described more accurately as the superposition of spikes from two other neurons. Fourth, it resolves situations where the recorded neurons drift in amplitude or across electrode contacts during a long recording session. Comparison with other sorters on real and simulated ground-truth datasets reveals many of the failure modes of spike sorters. We suggest a set of post-sorting analyses that can improve the veracity of neural recordings by minimizing the intrusion of those failure modes into analysis and interpretation of neural data.

neuroscience↗

bioRxiv2019

Behavioral training of marmosets and electrophysiological recording from the cerebellum

The common marmoset (Callithrix Jacchus) is a promising new model for study of neurophysiological basis of behavior in primates. Like other primates, it relies on saccadic eye movements to monitor and explore its environment. Previous reports have demonstrated some success in training marmosets to produce goal-directed actions in the laboratory. However, the number of trials per session has been relatively small, thus limiting the utility of marmosets as a model for behavioral and neurophysiological studies. Here, we report the results of a series of new behavioral training and neurophysiological protocols aimed at increasing the number of trials per session while recording from the cerebellum. To improve the training efficacy, we designed a precisely calibrated food regulation regime that motivated the subjects to perform saccade tasks, resulting in about a thousand reward-driven trials on a daily basis. We then developed a multi-channel recording system that used imaging to target a desired region of the cerebellum, allowing for simultaneous isolation of multiple Purkinje cells in the vermis. In this report, we describe (1) the design and surgical implantation of a CT guided, subject specific head-post, (2) the design of a CT and MRI guided alignment tool for trajectory guidance of electrodes mounted on an absolute encoder microdrive, (3) development of a protocol for behavioral training of subjects, and (4) simultaneous recordings from pairs of Purkinje cells during a saccade task.\n\nNew and NoteworthyMarmosets present the opportunity to investigate genetically based neurological disease in primates; in particular, diseases that affect social behaviors, vocal communication, and eye movements. All of these behaviors depend on the integrity of the cerebellum. Here, we present training methods that better motivate the subjects, allowing for improved performance, and also present electrophysiological techniques that precisely target the subjects cerebellum, allowing for simultaneous isolation of multiple Purkinje cells.\n\nIn our parks, are there any trees more elegant and luxurious than the Purkinje cell from the cerebellum? Santiago Ramon y Cajal

neuroscience↗

bioRxiv2019

Reward prediction error modulates saccade vigor

Movements toward rewarding stimuli exhibit greater vigor, i.e., increased velocity and reduced reaction-times. This invigoration may be due to release of dopamine before movement onset. Dopamine release is strongly modulated by reward prediction error (RPE). Here, we generated an RPE event in the milliseconds before movement onset and tested whether there was a causal relationship between RPE and vigor. Human subjects made saccades toward an image. During the execution of their primary saccade, we probabilistically changed the position and content of the image. This led to a secondary saccade following completion of the primary saccade. We focused on properties of this secondary saccade. On some trials, the content of the secondary image was more valuable than the first image, resulting in a +RPE event that preceded the secondary saccade. On other trials, this content was less valuable, resulting in a -RPE event. We found that reaction-time and velocity of the secondary saccade were affected in an orderly fashion by the magnitude and direction of the preceding RPE event: the most vigorous saccades followed the largest +RPE, whereas the least vigorous saccades followed the largest -RPE. Presence of the secondary saccade indicated that the primary saccade had experienced a movement error, inducing trial-to-trial adaptation: the subsequent primary saccade was changed in the direction of the movement error in the previous trial. However, motor learning from error was not affected by the RPE event. Therefore, reward prediction error, and not reward per se, modulated vigor of saccades. Author summaryDoes dopamine release before onset of a movement modulate vigor of the ensuing movement? To test this hypothesis, we relied on the fact that RPE is a strong modulator of dopamine. Our innovation was a task in which an RPE event occurred precisely before onset of a movement. We probabilistically produced a combination of large or small, negative or positive RPE events before onset of a saccade, and observed that the vigor of the saccade that followed carried a robust signature of the preceding RPE event: high vigor saccades followed +RPE events, while low vigor saccades followed -RPE events. This suggests that control of vigor is partly through release of dopamine in the moments before onset of the movement.

neuroscience↗

bioRxiv2018

Impact of Human Behavioral Papers at Journal of Neuroscience

A recent policy change at Journal of Neuroscience (JN) has significantly increased editorial \"desk rejections\", reducing the number of papers that are considered for publication. Survey results from 130 scientists suggested that the new policy may have had a particularly large impact on studies that focused on human behavioral techniques. To quantify the effects of the new policy, we gathered data on all papers ever published in JN (~35,000), as well as all papers that had cited the JN papers (~2.7 million papers). We found that the recent change in editorial policy had disproportionately affected rejection rates of human behavioral papers: since 2015, the number of human behavioral papers as a proportion of all papers published in JN has seen a 30% decline. While there has been a long-term declining trend in the journals impact factor, we found that this declining impact factor was shared by both human behavioral papers as well as other papers in the journal. This suggested that whatever may have been the source of the declining impact factor at JN, this source was affecting the various areas of research equally. That is, it was unlikely that papers in any one field were responsible for the declining impact factor number at JN. Indeed, when impact was measured over the long-term, we found that the average human behavioral paper at JN consistently outperformed other papers, generating a significantly higher number of citations per year at 5 and 10 years post publication.

scientific communication and education↗