Biology subjects

Kahana, M. J.

Publications and source records attributed to Kahana, M. J..

At least 19 recordsLinked to original sources

bioRxiv2026

Spectral Correlates of Encoding Distinguish Good from Poor Learners

Individuals vary in their ability to encode and recall new experiences, yet neural markers of memory have rarely been linked to these trait-level differences. Subsequent memory effects (SMEs) identify patterns of neural activity during encoding that predict whether an item will later be remembered or forgotten. In scalp EEG, SMEs are typically characterized by increased theta and gamma power with decreased alpha, a profile that has been interpreted as a signature of effective encoding. Here, we tested whether SMEs reflect individual differences in mnemonic ability by analyzing over 1.3 million encoding events from a large free recall dataset. At the group level, alpha suppression and theta enhancement predicted successful encoding, while gamma did not predict subsequent memory after controlling for serial position. Across individuals, better learners showed reduced SMEs in all three frequency bands. The neural contrast that defines successful encoding was therefore most pronounced among the poorest learners. These findings suggest that high-performing individuals are less reliant on phasic spectral activity for successful encoding, and that SMEs capture stable individual differences in encoding efficiency. HighlightsO_LIEEG activity during learning differentiates better from poorer learners C_LIO_LIEEG markers of successful encoding also reflect stable learning ability C_LIO_LIHigher-performing individuals show attenuated theta-alpha-gamma signatures C_LIO_LIEEG dynamics track both transient states and trait-like ability differences C_LI

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bioRxiv2026

Structural and Functional Connectivity Predict the Effects of Direct Brain Stimulation on Memory

Intracranial stimulation can enhance episodic memory in humans; however, the behavioral effects vary substantially across individuals and stimulation sites. Here, we investigated whether the network embedding of a stimulation target, defined by MRI-based normative structural and functional connectivity, accounts for variability in stimulation-linked memory enhancement. We analyzed data from 50 adults with medically refractory epilepsy who underwent intracranial EEG monitoring and completed a verbal delayed free-recall task during stimulation of left temporal cortex sites across 61 sessions (39 closed-loop; 22 random). On average, closed-loop stimulation delivered during classifier-detected low-encoding states increased recall rates, whereas random stimulation produced no reliable benefit. Diffusion tractography from a normative database showed that sites yielding greater memory enhancement were characterized by stronger structural coupling to a distributed fronto-temporo-parietal network. Greater structure-function congruence with a normative verbal-encoding activation network predicted larger closed-loop memory benefit (Spearman {rho} = 0.58, P < 0.0001). Functional connectivity exhibited overlapping trends but did not yield robust regional associations after permutation correction. Multivariate Partial Least Squares Structural Equation Modeling further identified stimulation mode, baseline memory, and a structural profile factor as independent predictors of memory enhancement, with no independent contribution of functional connectivity. These findings indicate that reliable stimulation-driven memory improvement depends not only on the timing of stimulation, but also on whether the stimulated target is structurally embedded within an encoding-relevant network scaffold. Significance statementMemory enhancement through direct brain stimulation holds substantial clinical promise, yet inconsistent outcomes have limited its therapeutic translation. This study shows that the effectiveness of closed-loop brain stimulation for memory improvement is determined by the structural network architecture of the stimulation target. Sites more deeply embedded within white-matter pathways connecting a distributed verbal encoding network yield the greatest mnemonic benefits when stimulation is delivered adaptively during poor encoding states. These findings establish a principled, network-based rationale for precision-guided neuromodulation: optimizing both the targets structural embedding and the timing of stimulation delivery are necessary and complementary conditions for reliable, individualized memory enhancement.

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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.

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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

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bioRxiv2024

Phase reset dynamics of memory encoding

Human and animal studies implicate theta and alpha oscillations in memory function. We tested whether theta, alpha, and beta phase consistency predicts memory encoding dynamics in neurosurgical patients performing delayed free recall tasks with either unrelated (N=188) or categorized words (N=157). We observed widespread post-stimulus phase consistency (3- 21 Hz) and, crucially, identified distinct frequency-specific patterns predictive of successful encoding. Specifically, increased early-list item recall was significantly correlated across subjects with increased theta (3-7 Hz) phase consistency. Subsequent recall analyses, controlling for serial position, revealed distinct frequency signatures for successfully encoded items: theta (3-6 Hz) and alpha (9-14 Hz) for unrelated lists, and theta (3-6 Hz) and beta (14-19 Hz) for categorized lists. Regional analyses for unrelated lists highlighted the lateral temporal cortex for theta effects and the prefrontal cortex for both theta and alpha consistency. These findings provide novel evidence for the frequency-specific presence of increased phase consistency during episodic encoding, revealing its sensitivity to both item context and temporal position within a learning sequence. Significance StatementNeural oscillations are implicated in human memory encoding, but their precise roles are still being defined. Our study leverages large-scale intracranial EEG datasets from participants undergoing word recall experiments, and introduces analytical innovations for robustly quantifying phase consistency with differing numbers of recalled versus forgotten items. This methodology reveals that phase consistency across different frequency bands (theta, alpha, beta) predicts memory formation. We demonstrate a specific role for theta consistency in encoding early list items and show that the brain adaptively recruits different oscillatory patterns (alpha or beta alongside theta) depending on item context (unrelated vs. categorized lists). These findings advance our understanding of the frequency-specific neural mechanisms supporting human episodic memory, revealing how the brain adapts its encoding strategies based on informational structure.

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bioRxiv2024

Neural Context Reinstatement of Recurring Events

Episodic recollection involves retrieving context information bound to specific events. However, autobiographical memory largely comprises recurrent, similar experiences that become integrated into joint representations. In the current study, we extracted a neural signature of temporal context from scalp electroencephalography (EEG) to investigate whether recalling a recurring event accompanies the reinstatement of one or multiple instances of its occurrence. We asked 52 young adults to study and recall lists of words that included both once-presented and repeated items. Participants recalled repeated items in association with neighboring list items from each occurrence, but with stronger clustering around the repetitions initial occurrence. Furthermore, multivariate spectral EEG analyses revealed that neural activity from just prior to the recall of these words resembled patterns of activity observed near the items first occurrence, but not its second. Together, these results suggest that the initial occurrence of an event carries stronger temporal context associations than later repetitions. Research Transparency StatementThe authors report no conflicts of interest with respect to the authorship or publication of this article. This research was conducted with support from National Institutes of Health grant MH55687. The current study was not preregistered. Data are available upon reasonable request and with proper approval from the University of Pennsylvania research and ethics entities. Requests should be directed to Adam Broitman. Key EEG and behavioral data analysis scripts are available for download at https://github.com/awb99cu/repFRcode.Studymaterialsareavailablefordownloadathttps://memory.psych.upenn.edu/PEERS.

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bioRxiv2024

A preserved neural code for temporal order between memory formation and recall in the human medial temporal lobe

Temporal memory enables us to remember the temporal order of events happening in our life. The human medial temporal lobe (MTL) appears to contain neural representations supporting temporal memory formation, but the cellular mechanisms that preserve temporal order information for recall are largely unknown. Here, we examined whether human MTL neuronal activity represents the temporal position of events during memory formation and recall, using invasive single and multi-unit recordings in human epilepsy patients (n = 19). Participants freely navigated a virtual environment in order to explore and remember locations and temporal positions of objects. During each exploration period, they sequentially encountered two or three different objects, placed in different locations. This allowed us to examine single- and multi-unit neuronal firing rates (FR) as a function of the temporal position the objects were presented in. We found that a significant number of multi-units and single-units in various MTL regions including the hippocampus showed selectivity to the temporal position of objects during the exploration period. During recall, patients were asked to indicate which one of two objects from the same trial was found latter. Neural firing rates during recall showed a selectivity supporting recall of temporal positions. Interestingly, most of the selective single-units that stayed selective during encoding and recall preserved their temporal position preference. Our results thus suggest that neuronal activity in the human MTL contains a preserved neural code for temporal order in memory formation and recall.

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bioRxiv2024

EEG Biomarkers of Age-Related Memory Change

The current study investigates whether electroencephalographic (EEG) activity reflects age-related memory changes during encoding. We recorded scalp EEG in 151 young adults (aged 18-30) and 37 older adults (aged 60-85) as they memorized lists of words. Subjects studied the word lists either under full attention or while performing a secondary task that required them to make semantic judgments about each word. Although the secondary task reduced recall among all subjects, differences in recall performance between the age groups were smaller when participants performed a secondary task at encoding. Older adults also exhibited distinct neural subsequent memory effects, characterized by less negativity in the alpha frequencies compared to young adults. Multivariate classifiers trained on neural features successfully predicted subsequent memory at the trial level in both young and older adults, and captured the differential effects of task demands on memory performance between young and older adults. The findings indicate that neural biomarkers of successful memory vary with both cognitive aging and task demands. Public significanceThe current study investigates the EEG spectral biomarkers of memory encoding in young and older adults, and identifies key features of neural activity associated with age-related memory change. We further find that age-related memory differences are smaller when participants perform a semantic judgment task during encoding, and that multivariate classifiers trained on the EEG data predict these effects.

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bioRxiv2024

Synchronous theta networks characterize successful memory retrieval

Memory retrieval activates regions across the brain, including not only the hippocampus and medial temporal lobe (MTL), but also frontal, parietal, and lateral temporal cortical regions. What remains unclear, however, is how these regions communicate to organize retrieval-specific process-ing. Here, we elucidate the role of theta (3-8 Hz) synchronization, broadly implicated in memory function, during the spontaneous retrieval of episodic memories. Analyzing a dataset of 382 neurosurgical patients (213 male, 168 female, 1 unknown) implanted with intracranial electrodes who completed a free recall task, we find that synchronous networks of theta phase synchrony span the brain in the moments before spontaneous recall, in comparison to periods of deliberation and incorrect recalls. Hubs of the retrieval network, which systematically synchronize with other regions, appear throughout the prefrontal cortex and lateral and medial temporal lobes, as well as other areas. Theta synchrony increases appear more prominently for slow (3 Hz) theta than for fast (8 Hz) theta in the recall-deliberation contrast, but not in the encoding or recall-intrusion contrast, and theta power and synchrony positively correlate throughout the theta band. These results implicate diffuse brain-wide synchronization of theta rhythms, especially slow theta, in episodic memory retrieval. Significance StatementAnalyzing intracranial recordings from 382 subjects who completed an episodic free recall experi-ment, we study the brain-wide theta synchrony effects of memory retrieval. The literature has not previously described the whole-brain regional distribution of these effects nor studied them with respect to intrusions. We show that a whole-brain theta synchrony effect marks the recall accuracy contrast, that distributed synchronous hubs constitute a whole-brain retrieval network, and that theta synchrony in the successful encoding, successful retrieval, and recall accuracy contrasts corre-lates positively with theta power increases at a region. These findings advance our understanding of the role and localization of theta synchrony effects during human memory retrieval.

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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.

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bioRxiv2023

Optimizing learning via real-time neural decoding

BackgroundSpectral features of human electroencephalographic (EEG) recordings during learning predict subsequent recall variability. New methodCapitalizing on these fluctuating neural features, we develop a non-invasive closed-loop (NICL) system for real-time optimization of human learning. Participants play a virtual navigation and memory game; recording multi-session data across days allowed us to build participant-specific classification models of recall success. In subsequent closed-loop sessions, our platform manipulated the timing of memory encoding, selectively presenting items during periods of predicted good or poor memory function based on EEG features decoded in real time. ResultsWe observed greater memory modulation (difference between recall rates when presenting items during predicted good vs. poor learning periods) for participants with higher out-of-sample classification accuracy. Comparison with Existing MethodsThis study demonstrates greater-than-chance memory decoding from EEG recordings in a naturalistic virtual navigation task with greater real-world validity than basic word-list recall paradigms. Here we modulate memory by timing stimulus presentation based on noninvasive scalp EEG recordings, whereas prior closed-loop studies for memory improvement involved intracranial recordings and direct electrical stimulation. Other noninvasive studies have investigated the use of neurofeedback or remedial study for memory improvement. ConclusionsThese findings present a proof-of-concept for using non-invasive closed-loop technology to optimize human learning and memory through principled stimulus timing, but only in those participants for whom classifiers reliably predict out-of-sample memory function.

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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.

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bioRxiv2023

Replay as context-driven memory reactivation

During rest and sleep, sequential neural activation patterns corresponding to awake experience re-emerge, and this replay has been shown to benefit subsequent behavior and memory. Whereas some studies show that replay directly recapitulates recent experience, others demonstrate that replay systematically deviates from the temporal structure, the statistics, and even the content of recent experience. Given these disparate characteristics, what is the nature and purpose of replay? Here, we offer a theoretical framework in which replay reflects simple context-guided processes that facilitate memory. We suggest that during awake learning, the brain associates experiences with the contexts in which they are encoded, at encoding rates that vary according to the salience of each experience. During quiescence, replay emerges as the result of a cascade of autonomous bidirectional interactions between contexts and their associated experiences, which in turn facilitates memory consolidation. A computational model instantiating this proposal explains numerous replay phenomena, including findings that existing models fail to account for and observations that have been predominantly construed through the lens of reinforcement learning. Our theory provides a unified, mechanistic framework of how the brain initially encodes and subsequently replays experiences in the service of memory consolidation.

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bioRxiv2022

MTL neurons phase-lock to human hippocampal theta

Memory formation depends on neural activity across a network of regions, including the hippocampus and broader medial temporal lobe (MTL). Interactions between these regions have been studied indirectly using functional MRI, but the bases for inter-regional communication at a cellular level remain poorly understood. Here we evaluate the hypothesis that oscillatory currents in the hippocampus synchronize the firing of neurons both within and outside the hippocampus. We recorded extracellular spikes from 1,854 single- and multi-units simultaneously with hippocampal local field potentials (LFPs) in 28 neurosurgical patients who completed virtual navigation experiments. A majority of hippocampal neurons phase-locked to oscillations in the slow (2-4Hz) or fast (6-10Hz) theta bands, with a significant subset exhibiting nested slow theta x beta frequency (13-20Hz) phase-locking. Outside of the hippocampus, phase-locking to hippocampal oscillations occurred only at theta frequencies and primarily among neurons in the entorhinal cortex and amygdala. Extrahippocampal neurons phase-locked to hippocampal theta even when theta did not appear locally. These results indicate that spike-time synchronization with hippocampal theta is a defining feature of neuronal activity in the hippocampus and structurally-connected MTL regions. Theta phase-locking could mediate flexible communication with the hippocampus to influence the content and quality of memories.

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bioRxiv2022

Searching memory in time and space

We investigated memory encoding and retrieval during a quasi-naturalistic spatial-episodic memory task in which subjects delivered items to landmarks in a desktop virtual environment and later recalled the delivered items. Transition probabilities and latencies revealed the spatial and temporal organization of memory. As subjects gained experience with the town, their improved spatial knowledge led to more efficient navigation and increased spatial organization during recall. Subjects who exhibited stronger spatial organization exhibited weaker temporal organization. Scalp-recorded electroencephalographic (EEG) signals revealed spectral correlates of successful encoding and retrieval. Increased theta power (T +) and decreased alpha/beta power (A-) accompanied successful encoding, with the addition of increased gamma (G+) accompanying successful retrieval. Logistic-regression classifiers trained on spectral features reliably predicted mnemonic success in held-out sessions. Univariate and multivariate EEG analyses revealed a similar spectral T +A-G+ of successful memory. These findings extend behavioral and neural signatures of successful encoding and retrieval to a naturalistic task in which learning occurs within a spatiotemporal context.

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bioRxiv2022

Direct Brain Recordings Identify a Causal Subsequent-Memory Effect

Endogenous variation in brain state and stimulus-specific evoked activity can both contribute to successful encoding. Previous studies, however, have not clearly distinguished among these components. We address this question by analyzing intracranial EEG recorded from epilepsy patients as they studied and subsequently recalled lists of words. We first trained classifiers to predict recall of either single items or entire lists and found that both classifiers exhibited similar performance. We found that list-level classifier output--a biomarker of successful encoding--tracked item presentation and recall events, despite having no information about the trial structure. Across widespread brain regions, decreased low- and increased high-frequency activity (HFA) marked successful encoding of both items and lists. We found regional differences in the hippocampus and prefrontal cortex, where in the hippocampus HFA correlated more strongly with item recall, whereas in the prefrontal cortex HFA correlated more strongly with list performance. Despite subtle differences in item- and list-level features, the similarity in overall classification performance, spectral signatures of successful recall, and fluctuations of spectral activity across the encoding period argue for a shared endogenous process that causally impacts the brains ability to learn new information.

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bioRxiv2022

Human hippocampal ripples signal encoding of episodic memories

Recent human electrophysiology work has uncovered the presence of high frequency oscillatory events, termed ripples, during awake behavior. This prior work focuses on ripples in the medial temporal lobe (MTL) during memory retrieval. Few studies, however, investigate ripples during item encoding. Many studies have found neural activity during encoding that predicts later recall, termed subsequent memory effects (SMEs), but it is unclear if ripples during encoding also predict subsequent recall. Detecting ripples in 116 neurosurgical participants (n = 61 male) performing an episodic memory task, we find insignificant ripple SMEs in any MTL region, even as these regions exhibit robust high frequency activity (HFA) SMEs. Instead, hippocampal ripples increase during encoding of items leading to recall of temporally or semantically associated items, a phenomenon known as clustering. This subsequent clustering effect (SCE) arises specifically when hippocampal ripples occur during both encoding and retrieval, suggesting that ripples mediate the encoding and future reinstatement of episodic memories.

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bioRxiv2022

A neural code for spatiotemporal context

Time and space are principle organizing dimensions of human experience. Whereas separate lines of study have identified neural correlates of time and space, little is known about how these representations converge during self-guided experience. Here we asked how neurons in the human brain represent time and space concurrently. Subjects fitted with intracranial microelectrodes played a timed navigation game where they alternated between searching for and retrieving objects in a virtual environment. Significant proportions of both time- and place-selective neurons were present during navigation, and distinct time-selective neurons appeared during task-free delays absent movement. We find that temporal and spatial codes are dissociable, with time cells remapping between search and retrieval tasks while place cells maintained stable firing fields. Other neurons tracked the context unique to each task phase, independent of time or space. Together these neuronal classes comprise a biological basis for the cognitive map of spatiotemporal context.

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