Valencia, Gabriela Ojeda

Abstract Human visual cortex comprises three interacting streams, but anatomy and correlated activity cannot determine the direction or reliability of interareal influence. Characterizing directional interactions among these streams can reveal the architecture through which activity can propagate across the visual system. Here, we used single-pulse electrical stimulation during intracranial EEG recordings in 17 patients to map directed causal influences among 22 atlas-defined visual cortical areas. The resulting effective connectivity matrix revealed a selective and asymmetric architecture of interareal influence. Feedforward influences from early visual areas to the dorsal, lateral, and ventral streams were more reliable and more prevalent than feedback influences. Cross-stream interactions favored temporal-to-parietal over parietal-to-temporal influence, with higher response reliability and a greater proportion of significant responses among sampled connections. Network-level profiles were consistent with source-like organization in early visual areas and the ventral stream, and integrator-like organization in the dorsal and lateral streams. Independent visual-task data collected in three of the same patients illustrated how stimulation-derived connectivity may relate to functional responses across connected visual regions. These findings reveal a directional architecture for activity propagation across the human visual cortex and provide empirical constraints for biologically grounded models of visual processing.

Objective The effects of deep brain stimulation (DBS) manifest across multiple timescales, spanning seconds to months, and involve direct electrical effects, neuroplasticity, and network reorganization. In epilepsy, the delayed impact of DBS on seizures presents challenges for optimization. Single‐pulse stimulation and resulting brain stimulation evoked potentials (BSEPs) provide a means to assess effective connectivity and network excitability. This study integrates BSEPs and short trials of DBS during stereoelectroencephalography (sEEG) to map seizure network engagement, modulate network dynamics, and monitor excitability and interictal abnormalities for biomarker informed neuromodulation. Methods Ten individuals with drug resistant epilepsy undergoing clinical sEEG were enrolled in this retrospective cohort study of epilepsy neuromodulation biomarkers. Each patient underwent a trial of high frequency (145Hz) thalamic DBS. BSEPs were acquired before and after DBS trials. Baseline BSEP amplitude assessed seizure network engagement, and modulation of amplitude (pre vs post DBS) assessed change in network excitability. Interictal epileptiform discharges were tracked by an automated classifier. Results Baseline BSEPs delineated distinct patterns of network engagement between thalamic subfields with maximal frontotemporal engagement achieved with stimulation of the anterior nucleus of the thalamus‐ventral anterior nucleus junction. DBS delivered for >1.5 hours reduced BSEP amplitudes compared to baseline, and the degree of modulation correlated with baseline connectivity strength. Shorter DBS trials did not induce reliable BSEP amplitude suppression, but did immediately suppress interictal epileptiform discharge rates in well‐connected seizure networks. Interpretation BSEPs and trials of DBS during sEEG provide novel network biomarkers to evaluate the modulation of large‐scale networks across multiple timescales, advancing biomarker informed neuromodulation. ANN NEUROL 2026;99:748–760

Abstract Electrical stimulation is increasingly used to modulate brain networks for clinical purposes. The basic unit of neurostimulation, a single electrical pulse, can travel through white matter to influence connected neuronal populations. However, the mechanisms by which it influences connected populations is not well understood: stimulation may excite, inhibit, or add noise to neuronal population activity. In this study, we investigated how single pulses modulate the neuronal processing of images in a well-controlled visual paradigm. In two human subjects implanted with iEEG electrodes for clinical purposes, single pulses were delivered to electrodes in white matter tracts connected to measurement electrodes in visual cortex. Images appeared on-screen at 0, 100, or 200 ms after each pulse. Using finite impulse response modeling, we decomposed the broadband and evoked potential responses into separate components induced by electrical stimulation and by visual processing. Single pulses induced transient broadband increases followed by suppression, but they did not modulate the visual broadband responses (i.e., stimulation response was additive to visual response). In contrast, single pulses elicited prominent brain stimulation evoked potentials and they modulated the visual evoked potentials. Specifically, visual evoked potentials were larger when stimulation occurred closer to visual onset. This indicates that a single electrical pulse can increase the strength or synchrony of visual inputs. Overall, these findings suggest that the effects of electrical stimulation in the visual system are two-fold: stimulation induces additive effects on broadband power, possibly by adding noise, and it interacts with synchronous visual inputs to amplify them.

Abstract Deep brain stimulation (DBS) is a targeted manipulation of brain circuitry to treat neurological and neuropsychiatric conditions. Optimal DBS lead placement is essential for treatment efficacy. Current targeting practice is based on preoperative and intraoperative brain imaging, intraoperative electrophysiology, and stimulation mapping. Electrophysiological mapping using extracellular microelectrode recordings aids in identifying functional subdomains, anatomical boundaries, and disease-correlated physiology. The shape of single-unit action potentials may differ due to different biophysical properties between cell-types and brain regions. Here, we describe a technique to parameterize the structure and duration of sorted spike units using a novel algorithmic approach based on canonical response parameterization, and illustrate how it may be used on DBS microelectrode recordings. Isolated spike shapes are parameterized then compared using a spike similarity metric and grouped by hierarchical clustering. When spike morphology is associated with anatomy, we find regional clustering in the human globus pallidus. This method is widely applicable for spike removal and single-unit characterization and could be integrated into intraoperative array-based technologies to enhance targeting and clinical outcomes in DBS lead placement. Author summary We developed a new algorithmic approach to capture the structure of single neuron electrophysiology from microelectrode recordings during deep brain stimulation surgery. This method has broad applications for spike characterization, clustering, removal from the background field potential, and comparison across recording sites. Using this technique, we illustrate regional clustering of spike morphologies in the human globus pallidus.

We studied movement-associated spectral changes in human motor thalamus and observed focal increases in broadband power with movement. This biomarker may be used as a tool for intraoperative functional mapping, DBS targeting, and closed-loop device control.