Biology subjects

Parvizi, J.

Publications and source records attributed to Parvizi, J..

16 recordsLinked to original sources

bioRxiv2026

Intracranial electrophysiology reveals distinct neural representations of nociception and salience in the human brain

Neuroimaging studies have shown close overlap between neural representations of nociceptive stimuli and non-nociceptive, salient stimuli (such as low-probability sounds), leading to the proposal that nociception and salience share a common neural substrate in the human brain. Here we use high-resolution intracranial recordings from 13 neurosurgical patients (2,018 total electrodes) to show that neural representations of nociception and salience are anatomically and functionally distinct in the human brain. 77% of 107 electrodes that encoded nociceptive stimuli did not encode low-probability sounds ("nociceptive representations"), whereas 23% encoded both nociceptive and low-probability sounds ("salience representations"). Nociceptive representations were distinct from salience representations in terms of anatomical prevalence (posterior insula, inferior parietal, and perirolandic cortex vs. anterior insula, thalamus, and inferior frontal gyrus), timing (nociception preceded salience by 120 ms on a trial-by-trial basis), and function (intracranial electrical stimulation was more likely to cause sensory experience when applied near nociceptive representations, as compared to salience representations). These results provide strong evidence that nociception and salience have distinct neural substrates in the human brain, and that selective measurement of these distinct processes may help understand patient-to-patient variability in chronic pain and develop personalized brain stimulation treatments.

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bioRxiv2026

Diffusion MRI Tractography Predicts Electrophysiological Connectivity and Explains Spectral Signatures of Evoked Potentials in the Human Brain

White matter fiber bundles are the structural conduits of information flow in the human brain and thereby mediate the spatial trajectories and timings of the electrophysiological signaling. Here, we combined diffusion magnetic resonance imaging (dMRI) and stereoelectroencephalography (SEEG) recordings in neurosurgical patients to develop an integrated framework for predicting and interpreting causal electrophysiological connectivity patterns between pairs of brain regions. We used repeated single-pulse electrical stimulation in 40 participants implanted with a total of 5794 intracranial electrodes throughout the human brain, encompassing both cortical and multiple thalamic nuclei. A nonlinear, time-frequency manifold learning approach was used to define electrophysiological connectivity, which was then compared with subject-specific and atlas-based structural connectivity. Across 150,000 electrode pairs, we found that the presence of a structural connection predicted causal electrophysiological connectivity with a probability of ~0.95; and its absence predicted the lack of the direct electrophysiological connectivity with a probability of ~0.8. We also show evidence of indirect/polysynaptic pathways supported by both modalities and reported neural features from time-frequency decomposition that distinguished between direct and indirect signaling. We demonstrated that an early phase-locked broadband component (10-70 ms) marked direct structural pathways, whereas delayed and slower components reflected indirect propagation. Notably, we reported that thalamic involvement within an indirect pathway results in increased latency (> 200 ms) and enhanced late oscillatory behavior, despite increased conduction velocity measures along thalamo-cortical pathways. Therefore, our multimodal framework maps human brain connectivity, bridging structural architecture, causal electrophysiological dynamics, and network-level communication.

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bioRxiv2026

Distinct yet neighboring neural populations encode past, future, and surrounding speech context in the human temporal lobe

Context is critical for both human and artificial speech comprehension systems. While the role of preceding context in speech processing has been well documented, the neural mechanisms supporting the integration of subsequent input -- phonemes and words that occur in the future -- remain poorly understood. Here, we leverage advances in artificial speech systems to model the contribution of different sources of context on the neural encoding of speech in the human brain. For neural encoding, context-informed but not context-uninformed speech model embeddings explain unique variance in human neural activity beyond acoustics, including in early speech processing regions. In particular, model embeddings informed by past, future, and surrounding context explain activity in distinct intracranial electrodes. These electrodes are left-lateralised, and spatially intermixed in the temporal lobe. We find that beyond-word context is crucial for the representational quality of speech model embeddings, and in particular for the encoding of abstract linguistic information. Our finding that spatially neighboring yet distinct neural populations in the temporal lobe encode representations shaped by different contextual sources (past, future, and surrounding input) provides key insight into the neural circuitry that integrates multiple forms of contextual information. Furthermore, our results may inform the downstream use of self-supervised speech representations in language technology tasks, and in models of speech comprehension in the human brain.

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bioRxiv2026

Hippocampal patterns and associative memory: Distinct intracranial EEG temporal encoding patterns support memory

Episodic memory depends on neural representations encoded in the hippocampus. Experimental and computational evidence suggests that the hippocampus encodes pattern-separated representations that support later recall of episodic event elements. While extant data in humans predominantly focus on assaying the relationship between the similarity of spatial neural patterns at encoding and later memory performance, similarity of neural patterns in the temporal domain may also reveal encoding computations predictive of future memory. To examine how the similarity among temporal patterns of hippocampal activity during encoding relates to later episodic retrieval (associative cued recall and recognition memory), hippocampal activity was recorded from human participants (n=7) with implanted intracranial electrodes while they encoded arbitrary (A-B) paired-associates. Subsequent memory analyses first revealed that hippocampal high-frequency broadband power (HFB; 70-180Hz) was linked to a graded increase in memory strength; HFB power was greater during the encoding of pairs later correctly recalled relative to events later recognized and was lowest for events later forgotten. Second, and critically, subsequent memory analyses further revealed that more distinctive temporal patterns in the hippocampus during encoding -- indexed by the similarity of the HFB timeseries elicited by a given event to that elicited by other events -- were associated with superior subsequent memory performance. Finally, exploratory analyses revealed stimulus category effects on hippocampal HFB power during encoding and retrieval cuing. These results indicate that the temporal distinctiveness of hippocampal traces during encoding is important for subsequent retrieval of episodic event elements, consistent with theories that posit that pattern separation facilitates future remembering.

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bioRxiv2026

Divergent Electrophysiological Responses in the Human Hippocampus During Verbal Memory Processing

The profile of electrophysiological responses in the human hippocampus (HPC) during verbal memory processing has remained complex and unclear. Here, we studied 26 patients implanted with intracranial electrodes across 187 HPC sites (50% left, 2-18 per patient). During memory encoding and retrieval, a subset of HPC responsive sites demonstrated increased ripple events, along with elevated high-frequency (HFA >50 Hz), and low-frequency (LFA 1-8 Hz) activity. A nearly equal number of sites showed no changes in ripple rate but increased LFA power and a delayed response-locked decrease in HFA power. More importantly, both successful encoding as well as recognition of remembered words were strongly associated with the coordination of the timing of LFA and HFA increases across the two clusters of responsive HPC sites. Using direct cortical electrical stimulations, we confirmed overlapping, but partially distinct, cortical connections to the functionally distinct HPC clusters. Our findings suggest a mesoscale mosaic functional organization within the human HPC where adjacent sites with divergent electrophysiological responses may have specialized roles during verbal memory processing. More importantly, our findings suggest that successful human memory depends on the coordination of the timing of low and high frequency local fields generated across these functionally divergent neuronal population sites.

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bioRxiv2025

Distinct neural temporal architectures encode rapid social expressions and sustained internal mood states

Affective processing operates across multiple temporal scales, from rapid social signaling through facial expressions to sustained internal mood states, yet the neural computational principles governing these different timescales remain unclear. Understanding how the brain implements distinct temporal architectures for momentary versus persistent affective phenomena is important to comprehending emotional processing and developing objective biomarkers for psychiatric conditions. Here, we introduced a multimodal approach combining automated facial expression monitoring and continuous intracranial electroencephalography in 2,037 electrode contacts across 16 epilepsy patients, over multiple days. Of these, 15 and 12 patients met criteria for facial expression and for mood analysis, respectively. Among patients meeting criteria, we captured 1,396 naturalistic smiles, and 3,746 neutral expressions - separated by at least 10 seconds, alongside 336 periodic mood assessments. This paradigm revealed distinct behavioral and neural computational architectures. Aperiodic neural activity in the lateral temporal cortex (79.5% accuracy) encoded facial expressions with high cross-participant generalizability. Mood states, however, showed different encoding patterns. Facial expressions provided no consistent mood indicators across participants. Critically, low-gamma power dynamics in limbic regions encoded mood states in only a subset of individuals (5 of 12 participants) with expression-mood behavioral correlations, suggesting a distinct encoding phenotype. Cross-domain analysis confirmed computational independence: neural features optimized for facial expression decoding failed to predict sustained mood states, and vice versa. These findings suggest that multiple neural mechanisms may influence underlying affective processing, with variations in their contributions between individuals. The results provide a framework for understanding individual differences in neural mood representation and establish methodological approaches for objective measurement of naturalistic affective behaviors.

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bioRxiv2025

Human Mediodorsal Thalamus in Seizure Propagation

BackgroundHow different thalamic sites are recruited during seizure propagation remains poorly understood. Simultaneous recordings from multiple thalamic sites in patients with focal seizures provide a rare opportunity to investigate the spatiotemporal pattern of thalamic involvement during human epilepsy. ObjectiveTo characterize the recruitment patterns of mediodorsal (MD) thalamic subregion during seizures and their generalization to the contralateral hemisphere. MethodsWe analyzed 119 seizures from 23 patients (12 male, age range: 20-57y) undergoing multisite thalamic recordings. In accordance with current clinical standards, we determined the spatial and temporal features of thalamic seizure activity by visually reviewing intracranial EEG recordings from different seizure types in each individual patient. ResultsThe procedure of multisite thalamic recordings had no complications. In total, we captured seizures originating from temporal lobes (63%), orbitofrontal (11%), frontotemporal (8%), occipital (8%), lateral frontal (4%), parietal (3%), and cingulate (2%) regions. Seizures were focal (76% in 21 patients), focal-to-bilateral tonic-clonic (FBTC, 9% in nine patients), or only electrographic (15% in six patients). Thalamic engagement was seen in 100% of patients occurring typically early during seizure evolution (83% within 15 seconds of seizure onset). Majority of FBTC seizures (73%) had faster thalamic recruitment, often within the first 5 seconds. The pulvinar (PLV) subregion was the most common first-activated thalamic site, particularly in temporal lobe seizures. Although the MD was involved in most seizures (88.2%), it was rarely the initial or sole thalamic structure engaged and more often followed anterior (ANT) and/or PLV sites. Contralateral propagation occurred in 66% of seizures and was strongly linked to MD involvement: the ipsilateral and contralateral MDs were engaged in about 95% of these cases. When ipsilateral MD engagement was absent, contralateral spread of seizures was uncommon. In majority of seizures (60%) that generalized to the contralateral hemisphere, the ipsilateral MD was involved before or simultaneously with the contralateral cortical sites. Importantly, seizures that first activated the MD originated mainly from the medial temporal lobes, whereas those spreading primarily to the contralateral cortex were mostly neocortical in onset. ConclusionsThe thalamic MD subregion was often involved after the other thalamic sites, but the MD sites, along with the massa intermedia connecting the two thalami, were significantly involved when seizures spread to contralateral hemisphere. Our findings suggest that a single thalamic lead capturing both MD subregions may yield important clinical information about laterality, origin, and generalization of seizures.

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bioRxiv2025

Electrophysiological Brain Connectivity and Subjective States Evoked by Electrical Stimulation of the Human Mediodorsal Thalamus

Recent advances in human intracranial EEG (iEEG) have enabled new investigations into the role of the thalamus in human brain functions. In this study, we applied direct intracranial electrical stimulation (iES) to the mediodorsal (MD) subregion of the thalamus using both high-frequency (50 Hz, iESHF) and low-frequency (0.5 Hz, iESLF) procedures to examine its impact on conscious experience and causal brain connectivity in 30 patients with focal refractory epilepsy (128 electrode contacts; 4 {+/-} 1 MD sites per patient). iESHF of the MD elicited reportable changes in conscious experience in 11 of 12 patients (39 sites; 83 stimulations across 27 unique pairs) - predominantly in the visceral, emotional, or somatosensory domains and often described as unpleasant without any lateralization effect. Our connectivity analyses based on iESLF revealed that the cingulate and insular cortices produced stronger electrophysiological responses in the MD (inflow connectivity) than did the sites in the prefrontal cortex (PFC) within the same individuals. Moreover, MD stimulation showed its strongest outflow connectivity to the cingulate, insular, and PFC regions, all significantly stronger than to medial temporal lobe (MTL) structures. Notably, inflow from both MTL and insula sites to the MD were significantly stronger than their reverse directions, indicating clear asymmetry in connectivity. These findings provide direct evidence that stimulation of the human thalamus can modulate conscious experience. They also highlight the extensive bidirectional connectivity between the MD and cingulate and insular cortices along with asymmetric connectivity between the MD and MTL and insula sites in the human brain. SIGNIFICANCE STATEMENTOur findings provide a functional and causal map of the mediodorsal thalamus (MD) in the human brain. We provide direct evidence that stimulation of the human thalamus can modulate conscious experience. This study also holds clinical and translational value for identifying thalamic pathways involved in the propagation and generalization of seizures, especially seizures involving the medial temporal lobe, as well as for neuromodulation in epilepsy and other neuropsychiatric disorders, as MD stimulation may not be well-tolerated in human subjects.

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bioRxiv2024

Causal Cortical and Thalamic Connections in the Human Brain

The brains functional architecture is intricately shaped by causal connections between its cortical and subcortical structures. Here, we studied 27 participants with 4864 electrodes implanted across the anterior, mediodorsal, and pulvinar thalamic regions, and the cortex. Using data from electrical stimulation procedures and a data-driven approach informed by neurophysiological standards, we dissociated three unique spectral patterns generated by the perturbation of a given brain area. Among these, a novel waveform emerged, marked by delayed-onset slow oscillations in both ipsilateral and contralateral cortices following thalamic stimulations, suggesting a mechanism by which a thalamic site can influence bilateral cortical activity. Moreover, cortical stimulations evoked earlier signals in the thalamus than in other connected cortical areas suggesting that the thalamus receives a copy of signals before they are exchanged across the cortex. Our causal connectivity data can be used to inform biologically-inspired computational models of the functional architecture of the brain.

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bioRxiv2024

Naturalistic acute pain states decoded from neural and facial dynamics

Pain is a complex experience that remains largely unexplored in naturalistic contexts, hindering our understanding of its neurobehavioral representation in ecologically valid settings. To address this, we employed a multimodal, data-driven approach integrating intracranial electroencephalography, pain self-reports, and facial expression quantification to characterize the neural and behavioral correlates of naturalistic acute pain in twelve epilepsy patients undergoing continuous monitoring with neural and audiovisual recordings. High self-reported pain states were associated with elevated blood pressure, increased pain medication use, and distinct facial muscle activations. Using machine learning, we successfully decoded individual participants high versus low self-reported pain states from distributed neural activity patterns (mean AUC = 0.70), involving mesolimbic regions, striatum, and temporoparietal cortex. High self-reported pain states exhibited increased low-frequency activity in temporoparietal areas and decreased high-frequency activity in mesolimbic regions (hippocampus, cingulate, and orbitofrontal cortex) compared to low pain states. This neural pain representation remained stable for hours and was modulated by pain onset and relief. Objective facial expression changes also classified self-reported pain states, with results concordant with electrophysiological predictions. Importantly, we identified transient periods of momentary pain as a distinct naturalistic acute pain measure, which could be reliably differentiated from affect-neutral periods using intracranial and facial features, albeit with neural and facial patterns distinct from self-reported pain. These findings reveal reliable neurobehavioral markers of naturalistic acute pain across contexts and timescales, underscoring the potential for developing personalized pain interventions in real-world settings.

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bioRxiv2023

Spatiotemporal dynamics of successive activations across the human brain during simple arithmetic processing

Previous neuroimaging studies have offered unique insights about the spatial organization of activations and deactivations across the brain, however these were not powered to explore the exact timing of events at the subsecond scale combined with precise anatomical source information at the level of individual brains. As a result, we know little about the order of engagement across different brain regions during a given cognitive task. Using experimental arithmetic tasks as a prototype for human-unique symbolic processing, we recorded directly across 10,076 brain sites in 85 human subjects (52% female) using intracranial electroencephalography (iEEG). Our data revealed a remarkably distributed change of activity in almost half of the sampled sites. Notably, an orderly successive activation of a set of brain regions - anatomically consistent across subjects-was observed in individual brains. Furthermore, the temporal order of activations across these sites was replicable across subjects and trials. Moreover, the degree of functional connectivity between the sites decreased as a function of temporal distance between regions, suggesting that information is partially leaked or transformed along the processing chain. Furthermore, in each activated region, distinct neuronal populations with opposite activity patterns during target and control conditions were juxtaposed in an anatomically orderly manner. Our study complements the prior imaging studies by providing hitherto unknown information about the timing of events in the brain during arithmetic processing. Such findings can be a basis for developing mechanistic computational models of human-specific cognitive symbolic systems. Significance statementOur study elucidates the spatiotemporal dynamics and anatomical specificity of brain activations across >10,000 sites during arithmetic tasks, as captured by intracranial EEG. We discovered an orderly, successive activation of brain regions, consistent across individuals, and a decrease in functional connectivity as a function of temporal distance between regions. Our findings provide unprecedented insights into the sequence of cognitive processing and regional interactions, offering a novel perspective for enhancing computational models of cognitive symbolic systems.

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bioRxiv2023

Cross regional coordination of neural activity in the human brain during autobiographical self-referential processing

For the human mind to operate, populations of neurons across remote regions of the brain need to coordinate their activity in the subsecond temporal scale. To date, our knowledge of such fast interactions involving cortical and subcortical structures in large brains, such as the human brain, remains limited. Here, we used stereo-electroencephalography (sEEG) recordings across four brain regions that are known, from decades of work, to be important for autobiographical memory processing. Our recordings involved 31 human participants implanted with intracranial electrodes in the hippocampus (HPC), posteromedial cortex (PMC), and ventromedial, as well as orbital subregions of the prefrontal cortex (OFC). In 14 subjects, we also recorded simultaneously in the anterior thalamus (ANT) across various experimental conditions and with direct electrical stimulations. Our observations provide new lines of correlative and causal evidence about the spatiotemporal profile of oscillatory coordination of cortical and subcortical activity during self-referential memory-based processing.

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bioRxiv2022

Multisite Thalamic Recordings to Characterize Seizure Propagation in the Human Brain

Neuromodulation of the anterior nuclei of the thalamus (ANT) has shown to be efficacious in patients with refractory focal epilepsy, but it is not uniformly effective. One important uncertainty is to what extent thalamic subregions other than the ANT are recruited earlier and more prominently in the propagation of seizures in patients with presumed temporal lobe epilepsy (TLE). To address this unknown, we studied 11 patients with clinical manifestations of TLE planned to undergo invasive stereo-encephalography (sEEG) monitoring. We extended cortical electrodes to reach thalamic nuclear subdivisions in the anterior (ANT), middle (mediodorsal) and or posterior (pulvinar) sites. This multisite thalamic sampling was without any adverse events. Intracranial EEG (iEEG) recordings confirmed seizure-onset in medial temporal lobe, insula, orbitofrontal and temporal neocortical sites - highlighting the importance of iEEG for more accurate localization of seizure foci. Visual review of EEGs documented early and prominent involvement of specific thalamic sites. Seizures originating from the same brain origin produced a stereotyped thalamic EEG signature. Visual review of EEGs, validated with singlepulse corticothalamic evoked potentials, documented early and prominent involvement of thalamic sites that would have not been predicted given the anatomy of seizure onset zones. Pulvinar was involved earlier and more prominently than other sampled nuclear subgroups in 60% of patients, even though all patients had a presumed diagnosis of TLE prior to invasive monitoring. Our findings document the feasibility and safety of multisite sampling from the human thalamus and suggest that the anatomy of thalamic involvement may not be entirely predictable on the basis of clinical information or lobar localization of seizures. Future clinical trials can establish whether offering more personalized targets for thalamic neuromodulation will lead to greater meaningful improvements in outcome.

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bioRxiv2021

Dissociable oscillatory networks support gain and loss processing in human orbitofrontal cortex

Human neuroimaging and animal studies have linked neural activity in orbitofrontal cortex (OFC) to valuation of positive and negative outcomes. Additional evidence shows that neural oscillations, representing the coordinated activity of neuronal ensembles, support information processing in both animal and human prefrontal regions. However, the role of OFC neural oscillations in reward-processing in humans remains unknown, partly due to the difficulty of recording oscillatory neural activity from deep brain regions. Here, we examined the role of OFC neural oscillations (<30Hz) in reward processing by combining intracranial OFC recordings with a gambling task in which patients made economic decisions under uncertainty. Our results show that power in different oscillatory bands are associated with distinct components of reward evaluation. Specifically, we observed a double dissociation, with a selective theta band oscillation increase in response to monetary gains and a beta band increase in response to losses. These effects were interleaved across OFC in overlapping networks and were accompanied by increases in oscillatory coherence between OFC electrode sites in theta and beta band during gain and loss processing, respectively. These results provide evidence that gain and loss processing in human OFC are supported by distinct low-frequency oscillations in networks, and provide evidence that participating neuronal ensembles are organized functionally through oscillatory coherence, rather than local anatomical segregation.

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bioRxiv2018

Anticorrelated inter-network electrophysiological activity varies dynamically with attentional performance and behavioral states

The default mode network (DMN) is thought to exhibit infraslow anticorrelated activity with dorsal attention (DAN) and salience (SN) networks across various behavioral states. To investigate the dynamics of activity across these networks on a finer timescale, we used human intracranial electroencephalography with simultaneous recordings within core nodes of the three networks. During attentional task performance, the three sites showed dissociable profiles of high-frequency broadband activity. Anticorrelated infraslow fluctuations of this activity were found across networks during task performance but also intermittently emerged during rest and sleep in concert with the expression of task-like network-level topographic patterns. Critically, on a finer timescale, DAN and SN activations preceded DMN deactivations by hundreds of milliseconds. Moreover, greater lagged, but not zero-lag, anticorrelation between DAN and DMN activity was associated with better attentional performance. These findings have implications for interpreting antagonistic network relationships and confirm the behavioral importance of time-lagged inter-network interactions.

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bioRxiv2018

Fast temporal dynamics and causal relevance of face processing in the human temporal cortex

Recordings with a large number of intracranial electrodes in eight neurosurgical subjects offered a unique opportunity to examine the fast temporal dynamics of face processing simultaneously across a relatively large extent of the human temporal cortex (TC). Measuring the power of slow oscillatory bands of activity ({theta}, , {beta}, and {gamma}) as well as High-Frequency Broadband (HFB, 70-177 Hz) signal, we found that the HFB showed the strongest univariate and multivariate changes in response to face compared to non-face stimuli. Using the HFB signal as a surrogate marker for local cortical engagement, we identified recording sites with selective responses to faces that were anatomically consistent across subjects and responded with graded strength to human, mammal, bird, and marine animal faces. Importantly, the most face selective sites were located more posteriorly and responded earlier than those with less selective responses to faces. Using machine learning based methods, we demonstrated that a sparse model focusing on information from the human face selective sites performed as well as, or better than, anatomically distributed models of face processing when discriminating faces from non-faces stimuli. Lastly, we identified the posterior fusiform (pFUS) site as causally the most relevant node for inducing distortion of face perception by direct electrical stimulation. Our findings support the notion of face information being processed first in the most selective sites - that are anatomically discrete and localizable within individual brains and anatomically consistent across subjects - which is then distributed in time to less selective anterior temporal sites within a time window that is too fast to be detected by current neuroimaging methods. The new information about the fast spatio-temporal dynamics of face processing across multiple sites of the human brain provides a new common ground for unifying the seemingly contradictory modular and distributed models of face processing in the human brain.

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