Biology subjects

Quraishi, I. H.

Publications and source records attributed to Quraishi, I. H..

6 recordsLinked to original sources

bioRxiv2023

Hippocampal Codes for Real-World Human Navigation

As animals move through the world, the hippocampus represents their location, direction, and speed. Parallel studies in humans have been mostly limited to virtual navigation because of physical constraints of suitable neural recording technologies. However, there are known differences between real-world and virtual navigation, leaving open the question of how the hippocampus supports real-world navigation in humans. Here we report evidence from ambulatory patients with chronic brain implants that the location, direction, and speed of humans walking along a linear track are represented in local field potentials from the hippocampus. We further show in a subset of patients who were tested twice after long delays that these representations can be reliable over time. These findings provide the first demonstration of multiple, stable neural codes for real-world navigation in the human hippocampus.

neuroscience↗

bioRxiv2023

Disease-causing Slack potassium channel mutations produce opposite effects on excitability of excitatory and inhibitory neurons

KCNT1 encodes the sodium-activated potassium channel Slack (KCNT1, KNa1.1), an important mediator of neuronal membrane excitability. Gain-of-function (GOF) mutations in humans lead cortical network hyperexcitability and seizures, as well as very severe intellectual disability. Using a mouse model of Slack GOF-associated epilepsy, we found that both excitatory and inhibitory neurons of the cerebral cortex have increased Na+-dependent K+ (KNa) currents and voltage-dependent sodium (NaV) currents. The characteristics of the increased KNa currents were, however, different in the two cell types such that the intrinsic excitability of excitatory neurons was enhanced but that of inhibitory neurons was suppressed. We further showed that the expression of NaV channel subunits, particularly that of NaV1.6, is upregulated and that the length of the axon initial segment (AIS) and of axonal NaV immunostaining is increased in both neuron types. We found that the proximity of the AIS to the soma is shorter in excitatory neurons than in inhibitory neurons of the mutant animals, potentially contributing to the different effects on membrane excitability. Our study on the coordinate regulation of KNa currents and the expression of NaV channels may provide a new avenue for understanding and treating epilepsies and other neurological disorders. In briefIn a genetic mouse model of Na+-activated K+ potassium channel gene Slack-related childhood epilepsy, Wu et al. show that a disease-causing gain-of-function (GOF) mutation R455H in Slack channel causes opposite effects on excitability of cortical excitatory and inhibitory neurons. In contrast to heterologous expression systems, they find that the increase in potassium current substantially alters the expression of sodium channel subunits, resulting in increased lengths of axonal initial segments. HighlightsGOF mutations in Slack potassium channel cause elevated outward K+currents and inward voltage-dependent Na+ (NaV) currents in cortical neurons Slack GOF does not alter the expression of Slack channel but upregulates the expression of NaV channel Slack GOF enhances the excitability of excitatory neurons but suppresses the firing of inhibitory interneurons Slack GOF alters the length of AIS in both excitatory and inhibitory neurons Proximity of AIS to the soma is different between excitatory neuron and inhibitory neuron

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↗

bioRxiv2022

Temporal dynamics of competition between statistical learning and episodic memory in intracranial recordings of human visual cortex

The function of long-term memory is not just to reminisce about the past, but also to make predictions that help us behave appropriately and efficiently in the future. This predictive function of memory provides a new perspective on the classic question from memory research of why we remember some things but not others. If prediction is a key outcome of memory, then the extent to which an item generates a prediction signifies that this information already exists in memory and need not be encoded. We tested this principle using human intracranial EEG as a time-resolved method to quantify prediction in visual cortex during a statistical learning task and link the strength of these predictions to subsequent episodic memory behavior. Epilepsy patients of both sexes viewed rapid streams of scenes, some of which contained regularities that allowed the category of the next scene to be predicted. We verified that statistical learning occurred using neural frequency tagging and measured category prediction with multivariate pattern analysis. Although neural prediction was robust overall, this was driven entirely by items that were subsequently forgotten. Such interference provides a mechanism by which prediction can regulate memory formation to prioritize encoding of information that could help learn new predictive relationships. Significance StatementWhen faced with a new experience, we are rarely at a loss for what to do. Rather, because many aspects of the world are stable over time, we rely upon past experiences to generate expectations that guide behavior. Here we show that these expectations during a new experience come at the expense of memory for that experience. From intracranial recordings of visual cortex, we decoded what humans expected to see next in a series of photographs based on patterns of neural activity. Photographs that generated strong neural expectations were more likely to be forgotten in a later behavioral memory test. Prioritizing the storage of experiences that currently lead to weak expectations could help improve these expectations in future encounters.

neuroscience↗

bioRxiv2021

A Biophysical Model of Nonquantal Transmission at the Vestibular Hair Cell-Calyx Synapse: KLV currents Modulate Fast Electrical and Slow K+ potentials in the Synaptic Cleft

Vestibular hair cells transmit information about head position and motion across synapses to primary afferent neurons. At some of these synapses, the afferent neuron envelopes the hair cell, forming an enlarged synaptic terminal called a calyx. The vestibular hair cell-calyx synapse supports a mysterious form of electrical transmission that does not involve gap junctions termed nonquantal transmission (NQT). The NQT mechanism is thought to involve the flow of ions from the pre-synaptic hair cell to the post-synaptic calyx through low-voltage-activated channels driven by changes in cleft [K+] as K+ exits the hair cell. However, this hypothesis has not been tested with a quantitative model and the possible role of an electrical potential in the cleft has remained speculative. Here we present a computational model that captures salient experimental observations of NQT and identifies overlooked features that corroborate the existence of an electrical potential ({phi}) in the synaptic cleft. We show that changes in cleft{phi} reduce transmission latency and illustrate the relative contributions of both cleft [K+] and{phi} to the gain and phase of NQT. We further demonstrate that the magnitude and speed of NQT depend on calyx morphology and that increasing calyx height reduces action potential latency in the calyx afferent. These predictions are consistent with the idea that the calyx evolved to enhance NQT and speed up vestibular signals that drive neural circuits controlling gaze, balance, and orientation. Significance StatementThe ability of the vestibular system to drive the fastest reflexes in the nervous system depends on rapid transmission of mechanosensory signals at vestibular hair cell synapses. In mammals and other amniotes, afferent neurons form unusually large calyx terminals on certain hair cells, and communication at these synapses includes nonquantal transmission (NQT), which avoids the synaptic delay of quantal transmission. We present a quantitative model that shows how NQT depends on the extent of the calyx covering the hair cell and attributes the short latency of NQT to changes in synaptic cleft electrical potential caused by current flowing through open potassium channels in the hair cell. This previously undescribed mechanism may act at other synapses.

neuroscience↗

bioRxiv2021

Remembering the pattern: A longitudinal case study on statistical learning in spatial navigation and memory consolidation

Distinct brain systems are thought to support statistical learning over different timescales. Regularities encountered during online perceptual experience can be acquired rapidly by the hippocampus. Further processing during offline consolidation can establish these regularities gradually in cortical regions, including the medial prefrontal cortex (mPFC). These mechanisms of statistical learning may be critical during spatial navigation, for which knowledge of the structure of an environment can facilitate future behavior. Rapid acquisition and prolonged retention of regularities have been investigated in isolation, but how they interact in the context of spatial navigation is unknown. We had the rare opportunity to study the brain systems underlying both rapid and gradual timescales of statistical learning using intracranial electroencephalography (iEEG) longitudinally in the same patient over a period of three weeks. As hypothesized, spatial patterns were represented in the hippocampus but not mPFC for up to one week after statistical learning and then represented in the mPFC but not hippocampus two and three weeks after statistical learning. Taken together, these findings clarify that the hippocampus may do the initial work of extracting regularities and transfer these integrated memories to cortex, rather than only storing individual experiences and leaving it up to cortex to extract regularities. HighlightsO_LICase study of an epilepsy patient tested longitudinally over three weeks. C_LIO_LIWe tracked time-dependent changes in neural representations of spatial patterns. C_LIO_LIRepresentations reconstructed from hippocampal activity reflected patterns learned within a week. C_LIO_LIRepresentations reconstructed from activity in the mPFC reflected patterns learned 2-3 weeks ago. C_LI

neuroscience↗