Elliot H. Smith

The paper investigates network competition in the brain using electrophysiology and neuroimaging, finding temporally layered antagonism between default and task-related networks, with distinct patterns in the hippocampus.

The paper uses deep reinforcement learning to model risk-adaptive decision-making strategies and identifies low-dimensional neural dynamics associated with high-performing strategies in humans.

The paper investigates neural representations of time during decision-making under risk using human intracranial electro-physiology and a temporal convolution network to predict response timing.

This study examines how propofol affects cortical traveling waves in the human brain, finding changes in wave speed, direction, and spectral structure during anesthesia.

This study shows that human hippocampal neurons use polysemantic coding, where neurons represent multiple unrelated semantic features through high-dimensional superposition, enabling efficient contextualization of meaning.

The paper shows that semantic features in word meaning are encoded in the brain through geometric structures similar to those in language models.

This study shows that an asymmetric reinforcement learning model better explains human decision-making under risk than symmetric models.

This study shows that aperiodic exponents from intracranial EEG can differentiate depression symptom severity and correlate with specific brain regions and networks.

The paper investigates neural bursting activity in human prefrontal and temporal brain areas during visual working memory and finds that gamma and beta bursting correlates with memory performance and is coupled via a phase-burst code.

This study examines how theta burst stimulation of the basolateral amygdala modulates single-neuron activity in humans during a memory task, finding that ~30% of neurons show heterogeneous responses.

The paper investigates how eye movements influence neural activity, information coding, and network connectivity in the human hippocampus during natural visual processing.

This study examines how human neurons respond to single-pulse electrical stimulation, finding that most neurons show firing rate suppression, with differences based on cell type and stimulation distance.

This study uses human brain recordings to show that creative thinking is associated with distinct neural states in the default mode and dorsal attention networks.

This study shows that spreading depolarizations (SDs) are associated with seizure termination in both human and rodent models, with SDs reducing seizure duration and delaying subsequent events.

The paper identifies neural traveling waves evoked by single-pulse brain stimulation using intracranial recordings and shows they propagate with biologically plausible velocities.

The paper investigates how neuronal representations of reward and risk expectations differ between impulsive and less impulsive decision-makers during a risky choice task.

This study uses intracranial recordings to analyze how neural activity correlates with binary and graded pain responses during tonic thermal stimuli in humans.

The paper measures the spatial reach of neuronal coherence and spike-field coupling in human neocortex during cognitive tasks, finding a consistent 2-3 cm effective range for local communication.

The paper shows that interictal epileptiform discharges (IEDs) are bidirectional traveling waves that follow the same path and direction as ictal discharges, suggesting they originate outside the seizure focus.

The paper shows that pre-trial firing rate patterns in human dlPFC predict conflict resolution in cognitive tasks, with distinct but related patterns for different conflict types.

The paper develops a novel spike sorting method to analyze neuronal activity during human seizures, finding that recruited neurons show altered action potential waveforms compared to non-recruited tissue.

The paper investigates human hippocampal theta oscillations, finding distinct high (8-Hz) and low (3-Hz) frequencies associated with spatial navigation and non-spatial processes respectively.

The paper shows that conflict in the dorsal anterior cingulate cortex (dACC) amplifies task-relevant information across neurons, rather than relying on specific conflict-encoding neurons or coactivation of action plans.

This study examines how neurons in the human medial-temporal lobe represent spatial targets during navigation, finding that firing rates change based on target position and heading direction.

The paper analyzes 770 intracranial stimulation sessions to assess the risk of stimulation-induced seizures, finding 3-6% of sessions likely or possibly caused seizures with no adverse outcomes.

The paper develops a neural network model to simulate focal seizure dynamics, including initiation, propagation, termination, and progression, and identifies mechanisms underlying seizure patterns and synaptic plasticity.

This study examines how medically-induced loss of consciousness affects cortical microstates and neuronal ensembles in mice and humans using imaging and electrophysiological data.

The paper identifies trace cells in the human entorhinal cortex that remap their spatial fields to represent memory cues during cued recall.

The paper investigates how inhibitory control affects the spread of focal ictal activity in a rodent model, showing that localized inhibition defects can lead to both classical and epileptic network propagation.