Biology subjects

Qasim, S. E.

Publications and source records attributed to Qasim, S. E..

12 recordsLinked to original sources

bioRxiv2026

Single neurons in the human substantia nigra encode social learning signals

Humans are remarkable at adapting to changing norms, yet we know little about how the human brain encodes these social signals at the single neuron level. Here, we recorded the activity of single neurons in the substantia nigra and globus pallidus in neurosurgical participants as they played an iterative ultimatum game versus human and computer avatars. Using computational modeling of behavior, we found that putative dopaminergic units in the substantia nigra tracked the valence of norm prediction errors, with greater encoding during gameplay with human versus computer avatars. Analogous analyses in the globus pallidus, a nucleus adjacent to the substantia nigra, found no significant effect. Our results identify a novel role for the substantia nigra in encoding social learning signals.

neuroscience↗

bioRxiv2026

Hippocampal-cingulate dynamics in the human brain link reinforcement-learning and memory

Reinforcement learning (RL) models describe how reward computations shape our choices, but whether the same computations also shape memory in the human brain is unclear. To address this question, we combined multi-areal intracranial recordings with computational modeling of reward and memory in neurosurgical patients. Patients played a gambling task in which decisions yielded monetary rewards tied to trial-unique images, followed immediately by a recognition test for those images. Model-derived positive reward prediction errors (RPEs) predicted later memory for each image. During feedback, multivariate high-frequency activity revealed the spatiotemporal evolution of RPE representations across distributed prefrontal cortex. During subsequent recognition, however, only anterior cingulate cortex (ACC) transiently reinstated RPE representations, and successful recognition specifically associated with hippocampal reinstatement of these ACC representations. Hippocampal-cingulate theta synchrony scaled with RPE during recognition, alongside hippocampal theta decoding of upcoming memory choices. Thus, the RL computations that guide decision-making also shape memory through hippocampal-cingulate circuit dynamics in the human brain.

neuroscience↗

bioRxiv2026

Human single-neuron recordings reveal population coding of attentional dynamics during naturalistic movie viewing

Our eyes move constantly. Where they land is shaped by internal cognitive state, making eye movements a rare, non-invasive window onto that state. However, how moment-to-moment eye-movements map onto human neural population activity during naturalistic viewing remains poorly characterized. We analyzed a public intracranial dataset in which 14 neurosurgical patients watched an eight-minute movie during simultaneous eye-tracking and neuronal activity recording. Single-neuron activity from 814 neurons across anterior cingulate cortex, pre-supplementary motor area, amygdala, hippocampus, and ventromedial prefrontal cortex was pooled into a single distributed population and related to a joint eye-movement state comprising pupil size, saccade rate and fixation duration. Using a cross-validated, multivariate analysis of population activity we found group-level coupling between the neural population and the joint eye-movement state (mean held-out canonical r = 0.145; one-sample t-test p = 0.0003; 9 of 14 subjects individually significant). The coupling was carried principally by saccade dynamics (r = 0.141) and pupil size (r = 0.094), with fixation duration contributing only marginally (r = 0.041). At the single-neuron level the picture differed: more neurons were eye-coupled than expected by chance, yet so weakly that almost none survived correction for multiple comparisons. Read out jointly, the same weakly coupled cells cohered into one reliable population dimension, and no single region's removal significantly reduced it. This pattern is more consistent with a distributed, redundant organization than with a small set of strongly coupled cells. In summary, eye-tracking offers a non-invasive window onto population-level neural states in humans.

neuroscience↗

bioRxiv2026

Coordinated human prefrontal dynamics sustain task-state representations during learning

Making decisions in complex, real-world environments is challenging. Biologically plausible strategies like reinforcement learning (RL) require attention toward reward-predictive stimuli to define task states, yet how attention and decision processes coordinate in the human brain remains unclear. We hypothesized this arises through interactions between orbitofrontal (OFC) value-based mechanisms and lateral prefrontal (LPFC) attention filtering. To test this, we combined behavioral modeling with local field potential (LFP) and single-unit recordings in 22 subjects performing a multidimensional RL task. Reward expectations were encoded in OFC and LPFC, as reflected in high-frequency LFP and OFC single-unit spiking, but modulated by attention only in LPFC. Theta LFPs encoded reward expectations and indexed attention-dependent LPFC-OFC coordination, with value-related coupling emerging pre-choice in high-attention subjects and post-choice in low-attention subjects. These findings show that prefrontal circuits dynamically coordinate to encode attention-weighted value signals, shaping state representations and providing a tractable solution to learning in complex environments.

neuroscience↗

bioRxiv2025

Evaluating Place Cell Detection Methods in Ratsand Humans: Implications for Cross-Species Spatial Coding

Place cells, first identified in the rat hippocampus as neurons that fire selectively at specific locations, are central to investigations of the neural underpinnings of spatial navigation. With recent work with human patients, identifying and characterizing place cells across species has become increasingly important for understanding the extent to which decades of rodent research generalize to humans and uncovering principles of spatial cognition. One challenge, however, is that detection methods differ: rodent studies often rely on spatial information (SI), whereas human studies employ analysis of variance (ANOVA) - based approaches. These methodological differences may affect the identified place cell population, which complicates how their properties are interpreted and cross-species comparisons. To address this, we systematically applied multiple detection pipelines to human and rat datasets, supported by simulations that vary place-field properties. Our analyses and simulations demonstrate that spatial information and ANOVA-based approaches are responsive to distinct place field properties: spatial information primarily reflects the contrast between peak and average firing rates, while ANOVA emphasizes consistency across trials. Across species, rodent place cells revealed a broad spectrum of spatial tuning, including strongly tuned neurons with high spatial information (SI) and high ANOVA values. In contrast, human place cells lacked this strongly tuned population and exhibited a narrower distribution of tuning scores, concentrated at the lower end of both spatial tuning metrics. Despite these differences, both species had an overlapping population of neurons with weaker yet consistent spatial tuning, which may support important functional roles such as generalization and mixed selectivity. Together, our study provides a roadmap showing how spatial tuning metrics shape place cell detection and interpretation, while underscoring the functional importance of weaker-tuned neurons in cross-species comparisons. Author SummaryPlace cells are neurons that become active in specific locations, and they play a critical role in how the brain supports navigation and memory. Place cells were first discovered in rats and later observed in humans, however, there has been a lack of direct comparisons between species using comparable approaches. Part of the difficulty doing so is that studies of rodent and human place cells have often relied on different analysis methods, making it difficult to determine if and how place-cell properties differ between species. To address this, in this study, we set out to understand how differences in place cell detection methods affect the identified place cell populations and interpretations of spatial coding across species. To do so, we compared the most prevalent detection methods used in rodent and human research side by side, applying them to datasets from both species and to simulations. We found that different methods emphasize different features of spatial responses, which changes which neurons are identified as place cells. Across species, rat recordings revealed a wide range of spatial responses, from neurons with sharply localized activity to those with broader but reliable patterns. Human recordings, by contrast, were more concentrated at weaker but consistent levels of tuning. Importantly, these weaker but consistent responses reflect an overlapping population of neurons found in both species, which may serve similar functional roles in supporting flexible spatial memory and generalization. By separating methodological effects from biological differences, we lay the groundwork for future cross-species studies for spatial coding. Materials Descriptions and Availability StatementsO_ST_ABSProject RepositoryC_ST_ABSThis project is openly available through an online project repository, which includes all the code used for data pre-processing and analysis. Project Repository: https://github.com/HSUPipeline/PlaceCellMethods DatasetThis project uses electrophysiological data collected from neurosurgical patients, as well as an open-access dataset of rat recordings from CRCNS.org: http://dx.doi.org/10.6080/K09G5JRZ The human data were collected as part of a previously published study and will be made available prior to publication [1]. A custom simulation framework was developed to evaluate place cell detection methods across species and will be released as part of the open-source SpikeTools repository prior to publication. SoftwareAll code used and developed for this project was written in the Python programming language. The code is openly available, licensed for reuse, and deposited in the project repository. Management of the dataset was conducted using the Human Single Unit (HSU) Pipeline: https://github.com/HSUPipeline Analyses of the single-neuron data were performed using the open-source SpikeTools toolbox: https://github.com/spiketools/spiketools Literature searches and related resources were organized using LISC, an open-source Python module for literature analysis. https://github.com/HSUPipeline/Literature

neuroscience↗

bioRxiv2024

Human Substantia Nigra Neurons Encode Reward Expectations

Dopamine (DA) signals originating from substantia nigra (SN) neurons are centrally involved in the regulation of motor and reward processing. DA signals behaviorally relevant events where reward outcomes differ from expectations (reward prediction errors, RPEs). RPEs play a crucial role in learning optimal courses of action and in determining response vigor when an agent expects rewards. Nevertheless, how reward expectations, crucial for RPE calculations, are conveyed to and represented in the dopaminergic system is not fully understood, especially in the human brain where the activity of DA neurons is difficult to study. One possibility, suggested by evidence from animal models, is that DA neurons explicitly encode reward expectations. Alternatively, they may receive RPE information directly from upstream brain regions. To address whether SN neuron activity directly reflects reward expectation information, we directly examined the encoding of reward expectation signals in human putative DA neurons by performing single-unit recordings from the SN of patients undergoing neurosurgery. Patients played a two-armed bandit decision- making task in which they attempted to maximize reward. We show that neuronal firing rates (FR) of putative DA neurons during the reward expectation period explicitly encode reward expectations. First, activity in these neurons was modulated by previous trial outcomes, such that FR were greater after positive outcomes than after neutral or negative outcome trials. Second, this increase in FR was associated with shorter reaction times, consistent with an invigorating effect of DA neuron activity during expectation. These results suggest that human DA neurons explicitly encode reward expectations, providing a neurophysiological substrate for a signal critical for reward learning.

neuroscience↗

bioRxiv2023

Neurons in the human entorhinal cortex map abstract emotion space

When animals move through space, neurons in their entorhinal cortex activate periodically at multiple locations to form a map of the spatial environment. These grid cells may also map non-physical, conceptual spaces to support various other complex behaviors. Here, using intracranial recordings in neurosurgical patients performing an emotional memory task, we find that neurons in the human medial temporal lobe activate in a grid-like pattern across a two-dimensional feature space characterized by emotional valence and arousal. These neurons were different from cells tuned solely to valence or arousal, were preferentially located in the entorhinal cortex, and exhibited theta-phase locking. Our observation of grid-like neuronal activity during emotional processing in humans supports the idea that the neural structure of cognitive maps generalizes beyond spatial navigation.

neuroscience↗

bioRxiv2021

Neuronal activity in the human amygdala and hippocampus enhances emotional memory encoding

Emotional events comprise our strongest and most valuable memories, yet it is unknown how the brain prioritizes emotional information for storage. Here, we examined the neural basis of this prioritization using direct brain recording, deep brain stimulation, and psychometric assessment, with human subjects performing an episodic memory task in which they showed improved performance for emotional stimuli. During the task, high-frequency activity (HFA), a correlate of neuronal spiking activity, increased in both the hippocampus and amygdala when subjects successfully encoded emotionally arousing stimuli. Applying inhibitory electrical stimulation to these regions decreased HFA and specifically reversed the enhancement of memory for emotional stimuli, indicating that neuronal activity in the amygdalohippocampal circuit has a direct role in prioritizing emotional memories. Finally, we found abnormal patterns of amygdalohippocampal HFA in depressed individuals which correlated with a bias for negative memories in these subjects. Going forward, targeted modulation that upregulates neuronal excitation in the amygdalohippocampal circuit may have a causal and translational role in modulating emotional memory.

neuroscience↗

bioRxiv2020

Phase precession in the human hippocampus and entorhinal cortex

Knowing where we are, where we have been, and where we are going is critical to many behaviors, including navigation and memory. One potential neuronal mechanism underlying this ability is phase precession, in which spatially tuned neurons represent sequences of positions by activating at progressively earlier phases of local network theta (~5-10 Hz) oscillations. Phase precession may be a general neural pattern for representing sequential events for learning and memory. However, phase precession has never been observed in humans. By recording human single-neuron activity during spatial navigation, we show that spatially tuned neurons in the human hippocampus and entorhinal cortex exhibit phase precession. Furthermore, beyond the neural representation of locations, we show evidence for phase precession related to specific goal-states. Our findings thus extend theta phase precession to humans and suggest that this phenomenon has a broad functional role for the neural representation of both spatial and non-spatial information.

neuroscience↗

bioRxiv2019

Single-neuron representations of spatial memory targets in humans

The hippocampus and surrounding medial-temporal-lobe (MTL) structures are critical for both memory and spatial navigation, but we do not fully understand the neuronal representations used to support these behaviors. Much research has examined how the MTL neurally represents spatial information, such as with \"place cells\" that represent the current location or \"head-direction cells\" that code for the current heading. In addition to behaviors that require an animal to attend to the current spatial location, navigating to remote destinations is a common part of daily life. To examine the neural basis of these behaviors we recorded single-neuron activity from neurosurgical patients playing Treasure Hunt, a virtual-reality spatial-memory task. By analyzing how the activity of these neurons related to behavior in Treasure Hunt, we found that the firing rates of many MTL neurons during navigation significantly changed depending on the position of the current spatial target. In addition, we observed neurons whose firing rates during navigation were tuned to specific heading directions in the environment, and others whose activity changed depending on the timing within the trial. By showing that neurons in our task represent remote locations rather than the subjects own position, our results suggest that the human MTL can represent remote spatial information according to task demands.

neuroscience↗

bioRxiv2018

Single neurons in the human entorhinal cortex remap to distinguish individual spatial memories

The entorhinal cortex (EC) is known to play a key role in both memory and spatial navigation. Despite this overlap in spatial and mnemonic circuits, it is unknown how spatially responsive neurons contribute to our ability to represent and distinguish past experiences. Recording from medial temporal lobe (MTL) neurons in subjects performing cued recall of object-location memories in a virtual-reality environment, we identified \"trace cells\" in the EC that remap their spatial fields to locations subjects were cued to recall on each trial. In addition to shifting its firing field according to the memory cue, this neuronal activity exhibited a firing rate predictive of the cued memorys content. Critically, this memory-specific neuronal activity re-emerged when subjects were cued for recall without entering the environment, indicating that trace-cell memory representations generalized beyond navigation. These findings suggest a general mechanism for memory retrieval via trace-cell activity and remapping in the EC.

neuroscience↗

bioRxiv2017

Phase-tuned neuronal firing encodes human contextual representations for navigational goals

We previously demonstrated that the phase of oscillations modulates neural activity representing categorical information using human intracranial recordings and high-frequency activity from local field potentials (Watrous et al., 2015b). We extend these findings here using human single-neuron recordings during a navigation task. We identify neurons in the medial temporal lobe with firing-rate modulations for specific navigational goals, as well as for navigational planning and goal arrival. Going beyond this work, using a novel oscillation detection algorithm, we identify phase-locked neural firing that encodes information about a persons prospective navigational goal in the absence of firing rate changes. These results provide evidence for navigational planning and contextual accounts of human MTL function at the single-neuron level. More generally, our findings identify phase-coded neuronal firing as a component of the human neural code.

neuroscience↗