Biology subjects

Buch, V. P.

Publications and source records attributed to Buch, V. P..

9 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.

neuroscience↗

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.

neuroscience↗

bioRxiv2026

Adolescent development accelerates responses to input in human neocortical neurons

Through childhood and adolescence, profound changes to the physiology of individual neurons accompany large-scale network changes in the mammalian neocortex. These physiological changes are well understood in rodent models but far less is known in the human neocortex. Here we combine patch-clamp electrophysiology and single-cell sequencing (Patch-Seq) in neurosurgically-resected pediatric human brain slices and age-matched mouse brain slices to elucidate the unique developmental trajectory of human neurons. We find that human Layer 2/3 pyramidal neurons show distinctive postnatal changes in neuronal physiology that align with the more directed, feedforward network architecture of human neocortex relative to the mouse. Human-specific changes to spike train dynamics include faster spike latencies and selective acceleration of early spiking. By applying linear modeling to our Patch-Seq data, we identify genes that predict physiological variation across single cells. This unbiased approach unexpectedly identifies BK-type calcium-activated potassium channels as key drivers of human postnatal changes in spike train dynamics between childhood and adolescence. We further test this pathway through pharmacology and computational modeling. Together, our results reveal novel mechanisms of postnatal maturation in human neocortical neurons and demonstrate a new application of Patch-Seq to uncover gene-physiology relationships at single-cell resolution.

neuroscience↗

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.

neuroscience↗

bioRxiv2025

Salient auditory stimuli evoke spatially segregated phasic and sustained neural responses in the human brain

Salient sensory stimuli are known to evoke neural activations across distributed brain regions. However, the temporal dynamics of these responses over sub-second timescales remain poorly understood, in part due to limitations in the temporal resolution of non-invasive neuroimaging methods. We examined the spatiotemporal dynamics of neural activations evoked by salient sensory stimuli (rare sounds) using 1,194 widely distributed intracranial electrodes in 5 neurosurgical patients. Salient stimuli preferentially activated 263 of 1,194 electrodes (22%), with responses segregating into two largely distinct spatiotemporal patterns: (1) phasic activation in sensorimotor regions, and (2) sustained activation within the salience network. Cross-correlation analysis revealed that phasic sensorimotor activation preceded sustained salience network activation on a trial-by-trial basis. These findings support an updated view of salience processing in the human brain, revealing that salient stimuli evoke two sequential stages of neural activation--phasic sensorimotor responses followed by sustained salience network activity--rather than simultaneous widespread activation.

neuroscience↗

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.

neuroscience↗

bioRxiv2025

ConvNeXt-Driven Detection of Alzheimers Disease: A Benchmark Study on Expert-Annotated AlzaSet MRI Dataset Across Anatomical Planes

Alzheimers disease (AD) is a leading worldwide cause of cognitive impairment, necessitating accurate, inexpensive diagnostic tools to enable early recognition. In this study, we present a robust deep learning approach for AD classification based on structural MRI scans, ConvNeXt, an emergent convolutional architecture inspired by vision transformers. We further present AlzaSet, a novel, expertly labeled clinical dataset with axial, coronal, and sagittal perspectives from AD and cognitively normal control subjects. Three ConvNeXt sizes (Tiny, Small, Base) were compared and benchmarked against existing state-of-the-art CNN models (VGG16, VGG19, InceptionV3, DenseNet1 21). ConvNeXt-Base consistently outperformed the other models on coronal slices with accuracy of 98.37% and an AUC of 0.992. Coronal views were determined to be most diagnostically informative, with emphasis on visualization of the medial temporal lobe. Moreover, comparison with recent ensemble-based techniques showed that superior performance with comparable computational efficiency. These results indicate that ConvNeXt-capable models applied to clinically curated data sets have strong potential to provide scalable, real-time AD screening in diverse settings, including both high-resource and resource-constrained settings.

neuroscience↗

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.

neuroscience↗

bioRxiv2022

"Primed to Perform:" Dynamic white matter graph communicability may drive metastable network representations of enhanced preparatory cognitive control

Spontaneous neural activity has become increasingly linked to behavioral and cognitive output. A specific cognitive control mode, proactive control, uses prior information to plan and prepare the brain to be particularly sensitive to incoming goal-directed stimuli. Little is known about specific proactive mechanisms implemented via preparatory patterns of spontaneous neural activity, that may enable dynamically enhanced cognitive performance. In this study, humans implanted with intracranial electrodes performed a simple cognitive task. For each subject, pre-trial spectral power and communicability-based features from both grey and white matter nodes were extracted to identify preparatory control states that were "primed to perform". The anatomical structure and topology of these states across subjects demonstrated a critical role for white matter communicability in decoding and intrinsically controlling preparatory network activity. Our results provide novel insights for putative cognitive network control and may be studied to develop prosthetic approaches for individuals with cognitive deficits.

neuroscience↗