Biology subjects

Fried, I.

Publications and source records attributed to Fried, I..

At least 19 recordsLinked to original sources

bioRxiv2025

Reading specific memories from human neurons before and after sleep

The ability to retrieve a single episode encountered just once is a hallmark of human intelligence and episodic memory[1]. Yet, decoding a specific memory from neuronal activity in the human brain remains a formidable challenge. Here, we develop a transformer neural network model[2, 3] trained on neuronal spikes from intracranial microelectrodes recorded during a single viewing of an audiovisual episode. Combining spikes throughout the brain via cross-channel attention[4], capable of discovering neural patterns spread across brain regions and timescales, individual participant models predict vocalization of specific concepts such as persons or places during out-of-distribution memory recall. Brain regions differentially contribute to memory decoding before and after sleep. Models trained using only medial temporal lobe (MTL) spikes significantly decode concepts before but not after sleep, while models trained using only frontal cortex (FC) spikes decode concepts after but not before sleep, with better FC decoding relating to increased non-REM sleep. These findings suggest a system-wide distribution of information across neural populations that transforms over wake/sleep cycles[5]. Such decoding of internally generated memories suggests a path towards brain-computer interfaces to treat episodic memory disorders through enhancement or muting of specific memories.

neuroscience↗

bioRxiv2024

Modality-Specific and Amodal Language Processing by Single Neurons

According to psycholinguistic theories, during language processing, spoken and written words are first encoded along independent phonological and orthographic dimensions, then enter into modality-independent syntactic and semantic codes. Non-invasive brain imaging has isolated several cortical regions putatively associated with those processing stages, but lacks the resolution to identify the corresponding neural codes. Here, we describe the firing responses of over 1000 neurons, and mesoscale field potentials from over 1400 microwires and 1500 iEEG contacts in 21 awake neurosurgical patients with implanted electrodes during written and spoken sentence comprehension. Using forward modeling of temporal receptive fields, we determined which sensory or abstract dimensions are encoded. We observed a double dissociation between superior temporal neurons sensitive to phonemes and phonological features and previously unreported ventral occipito-temporal neurons sensitive to letters and orthographic features. We also discovered novel neurons, primarily located in middle temporal and inferior frontal areas, which are modality-independent and show responsiveness to higher linguistic features. Overall, these findings show how language processing can be linked to neural dynamics, across multiple brain regions at various resolutions and down to the level of single neurons.

neuroscience↗

bioRxiv2024

Human neural dynamics of real-world and imagined navigation

The ability to form episodic memories and later imagine them is integral to the human experience, influencing our recollection of the past and our ability to envision the future. While research on spatial navigation in rodents suggests the involvement of the medial temporal lobe (MTL), especially the hippocampus, in these cognitive functions, it is uncertain if these insights apply to the human MTL, especially regarding imagination and the reliving of events. Importantly, by involving human participants, imaginations can be explicitly instructed and their mental experiences verbally reported. In this study, we investigated the role of hippocampal theta oscillations in both real-world and imagined navigation, leveraging motion capture and intracranial electroencephalographic recordings from individuals with chronically implanted MTL electrodes who could move freely. Our results revealed intermittent theta dynamics, particularly within the hippocampus, which encoded spatial geometry and partitioned navigational routes into linear segments during real-world navigation. During imagined navigation, theta dynamics exhibited similar, repetitive patterns despite the absence of external environmental cues. Furthermore, a computational model, generalizing from real-world to imagined navigation, successfully reconstructed participants imagined positions using neural data. These findings offer unique insights into the neural mechanisms underlying human navigation and imagination, with implications for understanding episodic memory formation and retrieval in real-world settings.

neuroscience↗

bioRxiv2023

A visual paired associate learning (vPAL) paradigm to study memory consolidation during sleep

The hippocampus helps transform an experience into an enduring memory by associating its multiple aspects. Sleep improves the consolidation of the newly formed associations, leading to stable long-term memory. Most research on human declarative memory and its consolidation during sleep uses word-pair associations requiring exhaustive learning. Here we present the visual paired association learning (vPAL) paradigm, in which participants learn new associations between images of celebrities and animals. vPAL associations are based on a one-shot exposure that resembles learning in natural conditions. We tested if vPAL can reveal a role for sleep in memory consolidation by assessing the specificity of memory recognition, and the cued recall performance, before and after sleep. We found that a daytime nap improved the stability of recognition memory and discrimination abilities compared to identical intervals of wakefulness. By contrast, cued recall of associations did not exhibit significant sleep-dependent effects. High-density EEG during naps further revealed an association between sleep spindle density and stability of recognition memory. Thus, the vPAL paradigm opens new avenues for future research on sleep and memory consolidation across ages and heterogeneous populations in health and disease.

neuroscience↗

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.

neuroscience↗

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.

neuroscience↗

bioRxiv2022

Periodic Time Cells in Human Entorhinal Cortex

Grid cells in the entorhinal cortex demonstrate spatially periodic firing patterns, which are thought to provide a map of space on behaviorally relevant length scales. It is unknown, however, whether such periodicity exists for behaviorally relevant time scales in the human brain. Here we investigated neuronal firing during a temporally continuous uninterrupted experience by presenting fourteen neurosurgical patients with an audiovisual video while recording single neuron activity from multiple brain regions. We report on a set of units that modulate their activity in a strikingly periodic manner across different timescales--from seconds to many minutes. These cells were most prevalent in the entorhinal cortex. Time within the video could be decoded from their population activity. Furthermore, these cells remapped their dominant periodicity to shorter timescales during a subsequent recognition memory task. When the audiovisual sequence was presented at two different speeds (regular and faster), a significant percentage of these temporally periodic cells (TPCs) maintained their timescales, suggesting a degree of invariance with respect to the narrative content. The temporal periodicity of TPCs may complement the spatial periodicity of grid cells Whether these cells provide scalable spatiotemporal metrics for encoding and retrieval of human experience warrants future investigations.

neuroscience↗

bioRxiv2022

A wearable platform for closed-loop stimulation and recording of single- neuron and local field potential activity in freely-moving humans

Advances in technologies that can record and stimulate deep-brain activity in humans have led to impactful discoveries within the field of neuroscience and contributed to the development of novel therapies for neurological and psychiatric disorders. Further progress, however, has been hindered by device limitations in that recording of single-neuron activity during freely-moving behaviors in humans has not been possible. Additionally, implantable neurostimulation devices, currently approved for human use, have limited stimulation programmability and lack full-duplex bi-directional capability. Here, we developed a wearable bi-directional closed-loop neuromodulation system (Neuro-stack) and used it to record single-neuron and local field potential activity during stationary and ambulatory behavior in humans. Together with a highly flexible and customizable stimulation capability, the Neuro-stack provides an opportunity to investigate the neurophysiological basis of disease, develop improved responsive neuromodulation therapies, explore brain function during naturalistic behaviors in humans, and consequently, bridge decades of neuroscientific findings across species.

neuroscience↗

bioRxiv2021

Decoding of human identity by computer vision and neuronal vision

Extracting meaning from a dynamic and variable flow of incoming information is a major goal of both natural and artificial intelligence. Computer vision (CV) guided by deep learning (DL) has made significant strides in recognizing a specific identity despite highly variable attributes1,2. This is the same challenge faced by the nervous system and partially addressed by the concept cells--neurons exhibiting selective firing in response to specific persons/places, described in the human medial temporal lobe (MTL)3-6. Yet, access to neurons representing a particular concept is limited due to these neurons sparse coding. It is conceivable, however, that the information required for such decoding is present in relatively small neuronal populations. To evaluate how well neuronal populations encode identity information in natural settings, we recorded neuronal activity from multiple brain regions of nine neurosurgical epilepsy patients implanted with depth electrodes, while the subjects watched an episode of the TV series "24". We implemented DL models that used the time-varying population neural data as inputs and decoded the visual presence of the main characters in each frame. Before training and testing the DL models, we devised a minimally supervised CV algorithm (with comparable performance against manually-labelled data7) to detect and label all the important characters in each frame. This methodology allowed us to compare "computer vision" with "neuronal vision"--footprints associated with each character present in the activity of a subset of neurons--and identify the brain regions that contributed to this decoding process. We then tested the DL models during a recognition memory task following movie viewing where subjects were asked to recognize clip segments from the presented episode. DL model activations were not only modulated by the presence of the corresponding characters but also by participants subjective memory of whether they had seen the clip segment, and by the associative strengths of the characters in the narrative plot. The described approach can offer novel ways to probe the representation of concepts in time-evolving dynamic behavioral tasks. Further, the results suggest that the information required to robustly decode concepts is present in the population activity of only tens of neurons even in brain regions beyond MTL.

neuroscience↗

bioRxiv2021

Impaired top-down auditory processing despite extensive single-neuron responses during human sleep

Sleep in all species is universally defined as a reversible, homeostatically-regulated state of a reduced behavioral responsiveness, with a high arousal threshold in response to external sensory stimulation1. However, it remains unclear whether sleep mainly gates motor output or affects responses along sensory pathways, and whether sleep primarily modulates specific aspects of the sensory response such as feedforward vs. feedback signaling2-7. Here, we simultaneously recorded polysomnography, iEEG, microwire LFPs, and neuronal spiking activity during wakefulness and sleep in 13 epilepsy patients implanted with clinical depth electrodes, while presenting auditory stimuli (e.g. click-trains, words, music). The results revealed robust spiking and induced LFP high-gamma (80-200Hz) power responses during both NREM and REM sleep across the lateral temporal lobe. The magnitude of the responses was only moderately attenuated in sleep, most notably for late responses beyond the early auditory cortex. Nonetheless, sleep responses maintained their tight locking with soundwave envelopes and their information content was only minimally affected. In contrast, a decrease in LFP alpha-beta (10-30Hz) power responses was prevalent in wakefulness but significantly disrupted in sleep. Entrainment to 40 Hz click-trains was comparable across REM sleep and wakefulness, but reduced in NREM sleep. In conclusion, our results establish the presence of extensive and robust auditory responses during sleep while LFP alpha-beta power decrease, likely reflecting top-down processes8-10, is deficient. More broadly, our findings suggest that feedback signalling is key to conscious sensory processing11-13.

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↗

bioRxiv2020

Improving cell-specific drug connectivity mapping with collaborative filtering

MotivationDrug repositioning allows expedited discovery of new applications for existing compounds, but re-screening vast compound libraries is often prohibitively expensive. "Connectivity mapping" is a process that links drugs to diseases by identifying compounds whose impact on expression in a collection of cells reverses the diseases impact on expression in disease-relevant tissues. The high throughput LINCS project has expanded the universe of compounds and cell types for which data are available, but even with this effort, many potentially clinically useful combinations are missing. To evaluate the possibility of repurposing drugs this way despite missing data, we compared collaborative filtering with either neighborhood-based or SVD imputation methods to two naive approaches via cross-validation. ResultsMethods were evaluated for their ability to predict drug connectivity despite missing data. Predictions improved when cell type was taken into account. Neighborhood-based collaborative filtering was the most successful method, with the best improvements in non-immortalized primary cells. We also explored which classes of compounds are most and least reliant on cell type for accurate imputation, and we identified connections between related compounds even when many were not measured in the relevant cells. We conclude that even for cells in which drug responses have not been fully characterized, it is possible to identify unassayed drugs that reverse in those cells the expression signatures observed in disease. Contactdonna.slonim@tufts.edu

bioinformatics↗

bioRxiv2020

Single neurons throughout human memory regions phase-lock to hippocampal theta

Functional interactions between the hippocampus and cortex are critical for episodic memory. Neural oscillations are believed to coordinate these interactions, and in rodents, prefrontal neurons phase-lock to hippocampal theta oscillations during memory-guided behavior. We assessed inter-regional phase-locking to hippocampal oscillations in humans by recording 1,233 cortical and amygdala neurons and simultaneous hippocampal local field potentials in 18 neurosurgical patients. We identified 362 neurons (29.4%) from multiple regions that phase-locked to rhythmic hippocampal activity, predominantly at theta (2-8Hz) frequencies. Compared to baseline spiking, strong theta phase-locking coincided with regionally-specific increases in hippocampal theta power, local and hippocampal high frequency activity, and cross-frequency power correlations between the hippocampus and a phase-locked neurons local region. These results reveal that spike-time synchrony with hippocampal theta is a defining feature of cortico-hippocampal functional connections in humans. We propose that theta phase-locking could mediate flexible inter-regional communication to shape the content and quality of episodic memories.

neuroscience↗

bioRxiv2020

Wireless Programmable Recording and Stimulation of Deep Brain Activity in Freely Moving Humans

Current implantable devices that allow for recording and stimulation of brain activity in humans are not inherently designed for research and thus lack programmable control and integration with wearable sensors. We developed a platform that enables wireless and programmable intracranial electroencephalographic recording and deep brain stimulation integrated with wearable technologies. This methodology, when used in freely moving humans with implanted neural devices, can provide an ecologically valid environment conducive to elucidating the neural mechanisms underlying naturalistic behaviors and developing viable therapies for neurologic and psychiatric disorders.

neuroscience↗

bioRxiv2019

Modulation of human intracranial theta oscillations during freely moving spatial navigation and memory

How the human brain supports accurate navigation of a learned environment has been an active topic of research for nearly a century1-5. In rodents, the theta rhythm within the medial temporal lobe (MTL) has been proposed as a neural basis for fragmenting incoming information and temporally organizing experiences and is thus widely implicated in spatial and episodic memory6. In addition, high-frequency theta (~8Hz) is associated with navigation, and loss of theta results in spatial memory deficits in rats 7. Recently, high-frequency theta oscillations during ambulatory movement have been identified in humans8,9, though their relationship to spatial memory remains unexplored. Here, we were able to record MTL activity during spatial memory and navigation in freely moving humans immersed in a room-scale virtual reality (VR) environment. Naturalistic movements were captured using motion tracking combined with wireless VR in participants implanted with an intracranial electroencephalographic (iEEG) recording system for the treatment of epilepsy. We found that prevalence of theta oscillations across brain sites during both learning and recall of spatial locations during ambulatory navigation is critically linked to memory performance. This finding supports the reinstatement hypothesis of episodic memory--thought to underlie our ability to recreate a prior experience10-12--and suggests that theta prevalence within the MTL may act as a potential representational state for memory reinstatement during spatial navigation. Additionally, we found that theta power is hexadirectionally modulated13-15 as a function of the direction of physical movement, most prominently after learning has occurred. This effect bears a resemblance to the rodent grid cell system16 and suggests an analog in human navigation. Taken together, our results provide the first characterization of neural oscillations in the human MTL during ambulatory spatial memory tasks and provide a platform for future investigations of neural mechanisms underlying freely moving navigation in humans.

neuroscience↗

bioRxiv2019

Single-cell activity in human STG during perception of phonemes is organized according to manner of articulation

A long-standing controversy persists in psycholinguistic research regarding the way phonemes are coded in human auditory cortex during speech perception. Whereas the motor theory of speech perception suggests that phonemes are organized in terms of common articulatory gestures that generate them, auditory theories argue that phonetic processing is organized based on common spectro-temporal patterns in phoneme waveforms. Here, we recorded spiking activity in the superior temporal gyrus (STG) from six neurosurgical patients who performed a listening task with phoneme stimuli. Using a Naive-Bayes model, we show that single-cell responses to phonemes are governed by articulatory features that have acoustic correlates (manner-of-articulation) and organized according to sonority, with two main clusters for sonorants and obstruents. We further find that neural similarity (i.e. the similarity of evoked spiking activity between pairs of phonemes), is comparable to the perceptual similarity (i.e. how much the pair of phonemes sound similar) based on perceptual confusion assessed behaviorally in healthy subjects. Thus phonemes that were perceptually similar, also had similar neural responses. Our findings establish that phonemes are encoded according to manner-of-articulation, supporting the auditory theories of perception, and that the perceptual representation of phonemes can be reflected by the activity of single neurons in STG.

neuroscience↗

bioRxiv2018

Anesthesia-induced loss of consciousness disrupts auditory responses beyond primary cortex

Despite its ubiquitous use in medicine, and extensive knowledge of its molecular and cellular effects, how anesthesia induces loss of consciousness (LOC) and affects sensory processing remains poorly understood. Specifically, it is unclear whether anesthesia primarily disrupts thalamocortical relay or intercortical signaling. Here we recorded intracranial EEG (iEEG), local field potentials (LFPs), and single-unit activity in patients during wakefulness and light anesthesia. Propofol infusion was gradually increased while auditory stimuli were presented and patients responded to a target stimulus until they became unresponsive. We found widespread iEEG responses in association cortices during wakefulness, which were attenuated and restricted to auditory regions upon LOC. Neuronal spiking and LFP responses in primary auditory cortex (PAC) persisted after LOC, while responses in higher-order auditory regions were variable, with neuronal spiking largely attenuated. Gamma power induced by word stimuli increased after LOC while its frequency profile slowed, thus differing from local spiking activity. In summary, anesthesia-induced LOC disrupts auditory processing in association cortices while relatively sparing responses in PAC, opening new avenues for future research into mechanisms of LOC and the design of anesthetic monitoring devices.

neuroscience↗

bioRxiv2017

A Multi-Species Functional Embedding Integrating Sequence and Network Structure

A key challenge to transferring knowledge between species is that different species have fundamentally different genetic architectures. Initial computational approaches to transfer knowledge across species have relied on measures of heredity such as genetic homology, but these approaches suffer from limitations. First, only a small subset of genes have homologs, limiting the amount of knowledge that can be transferred, and second, genes change or repurpose functions, complicating the transfer of knowledge. Many approaches address this problem by expanding the notion of homology by leveraging high-throughput genomic and proteomic measurements, such as through network alignment.\n\nIn this work, we take a new approach to transferring knowledge across species by expanding the notion of homology through explicit measures of functional similarity between proteins in different species. Specifically, our kernel-based method, HO_SCPLOWANDLC_SCPLOW (Homology Assessment across Networks using Diffusion and Landmarks), integrates sequence and network structure to create a functional embedding in which proteins from different species are embedded in the same vector space. We show that inner products in this space capture functional similarity across species, and the vectors themselves are useful for a variety of cross species tasks. We perform the first whole-genome method for predicting phenologs, generating many that were previously identified, but also predicting new phenologs supported from the biological literature. We also demonstrate the HO_SCPLOWANDLC_SCPLOW-embedding captures pairwise gene function, in that gene pairs with synthetic lethal interactions are co-located in HO_SCPLOWANDLC_SCPLOW-space both within and across species. Software for the HO_SCPLOWANDLC_SCPLOW algorithm is available at http://github.com/lrgr/HANDL.

bioinformatics↗