Biology subjects

Aljishi, A.

Publications and source records attributed to Aljishi, A..

5 recordsLinked to original sources

bioRxiv2025

Beta bursts mediate amygdala gating of hippocampal emotional encoding

The amygdala and hippocampus are key structures in emotional processing, yet the transient neural dynamics coordinating their interaction remain poorly understood. We simultaneously recorded single-neuron activity and local field potentials from these regions in epilepsy patients performing an emotional image-rating task. Neurons in both areas exhibited firing rate changes predictive of subjective emotional valence. While conventional spectral analysis revealed no valence-specific patterns, beta bursts (13-30 Hz)--transient, high-power events-were uniquely modified by task features. In both regions, beta bursts were associated with increased gamma amplitude and enhanced phase coherence, with beta-gamma phase-amplitude coupling capturing emotion-related dynamics. Critically, amygdala beta bursts were associated with strong suppression of hippocampal firing, coinciding with interneuron activation, during negative valence/highest arousal processing, whereas hippocampal bursts showed no reciprocal influence. These findings suggest that beta bursts may represent a temporally precise neural correlate of emotional appraisal and a candidate mechanism for targeted neuromodulation in mood disorders.

neuroscience↗

bioRxiv2025

Experience reorganizes content-specific memory traces in macaques

Memory formation relies on the reorganization of neural activity patterns during experience that persist in subsequent sleep. How these processes promote learning while preserving established memories remains unclear. We recorded neural ensemble activity from hippocampal and associated regions in freely moving macaques as they recalled item sequences presented that day ("new"), one day prior ("recent"), or over two weeks prior ("old"). Cell assemblies biased for old sequences showed less drift, greater network connectivity, and stronger sleep reactivation than new-biased assemblies. Pairs of old and recent assemblies formed persistent task-to-sleep coupling ("metassemblies"), unlike new assembly pairs. In the hippocampus, the propensity for superficial and deep CA1 pyramidal cells to form integrated assemblies increased with memory age. These findings reveal rapid organization and stabilization of neural activity in the primate brain, suggesting potential mechanisms for balancing learning with memory linking and durability.

neuroscience↗

bioRxiv2025

Representation of visual sequences in the tuning and topology of neuronal activity in the human hippocampus

Time is a critical component of memory and yet how the hippocampus incorporates temporal information with the sensory contents of memories remains unclear. We hypothesized that the hippocampus can learn arbitrary sequences through rapid changes in the tuning and population geometry of individual neurons to mirror the sequence structure. We recorded single-unit activity from 134 neurons in the hippocampus of 17 patients with epilepsy while they viewed sequences of visual scenes that were presented repeatedly in the same order by looping from the end to start. As the sequence repeated, hippocampal neurons that were initially responsive to one scene in the sequence began responding to the other scenes proportional to their temporal proximity. The population vectors of spiking activity across recorded hippocampal neurons for each scene came to form a high-dimensional ring topology that encoded the circular structure of the sequence in a manner that preserved the serial order of the scenes. These effects were not observed when sequences were scrambled upon each repetition to destroy temporal structure, nor in brain regions outside of the hippocampus for both structured and random sequences. These findings suggest that temporal structure governs the representation of sensory stimuli in human hippocampal neurons.

neuroscience↗

bioRxiv2023

Statistical learning in epilepsy: Behavioral, anatomical, and causal mechanisms in the human brain

Statistical learning, the fundamental cognitive ability of humans to extract regularities across experiences over time, engages the medial temporal lobe in the healthy brain. This leads to the hypothesis that statistical learning may be impaired in epilepsy patients, and that this impairment could contribute to their varied memory deficits. In turn, epilepsy patients provide a platform to advance basic understanding of statistical learning by helping to evaluate the necessity of medial temporal lobe circuitry through disease and causal perturbations. We implemented behavioral testing, volumetric analysis of the medial temporal lobe substructures, and direct electrical brain stimulation to examine statistical learning across a cohort of 61 epilepsy patients and 28 healthy controls. Behavioral performance in a statistical learning task was negatively associated with seizure frequency, irrespective of where seizures originated in the brain. The volume of hippocampal subfields CA1 and CA2/3 correlated with statistical learning performance, suggesting a more specific role of the hippocampus. Indeed, transient direct electrical stimulation of the hippocampus disrupted statistical learning. Furthermore, the relationship between statistical learning and seizure frequency was selective: behavioral performance in an episodic memory task was impacted by structural lesions in the medial temporal lobe and by antiseizure medications, but not by seizure frequency. Overall, these results suggest that statistical learning may be hippocampally dependent and that this task could serve as a clinically useful behavioral assay of seizure frequency distinct from existing neuropsychological tests. Simple and short statistical learning tasks may thus provide patient-centered endpoints for evaluating the efficacy of novel treatments in epilepsy.

neuroscience↗

bioRxiv2023

Online abstraction during statistical learning revealed by neural entrainment from intracranial recordings

We encounter the same people, places, and objects in predictable sequences and configurations. These regularities are learned efficiently by humans via statistical learning. Importantly, statistical learning creates knowledge not only of specific regularities, but also of more abstract, generalizable regularities. However, prior evidence of such abstract learning comes from post-learning behavioral tests, leaving open the question of whether abstraction occurs online during initial exposure. We address this question by measuring neural entrainment during statistical learning with intracranial recordings. Neurosurgical patients viewed a stream of scene photographs with regularities at one of two levels: In the Exemplar-level Structured condition, the same photographs appeared repeatedly in pairs. In the Category-level Structured condition, the photographs were trial-unique but their categories were paired across repetitions. In a baseline Random condition, the same photographs repeated but in a scrambled order. We measured entrainment at the frequency of individual photographs, which was expected in all conditions, but critically also at half of that frequency -- the rate at which to-be-learned pairs appeared in the two structured conditions (but not the random condition). Neural entrainment to both exemplar and category pairs emerged within minutes throughout visual cortex and in frontal and temporal brain regions. Many electrode contacts were sensitive to only one level of structure, but a significant number encoded both exemplar and category regularities. These findings suggest that abstraction occurs spontaneously during statistical learning, providing insight into the brains unsupervised mechanisms for building flexible and robust knowledge that generalizes across input variation and conceptual hierarchies.

neuroscience↗