Biology subjects

Tiganj, Z.

Publications and source records attributed to Tiganj, Z..

8 recordsLinked to original sources

bioRxiv2026

Boundary Vector Cells Encode a Future-Biased Spectrum of Positions in the Rat

Spatial tuning is a hallmark property of neural firing in the hippocampal formation. Yet, that tuning is often less well correlated with the instantaneous current position of an animal than it is with an integrated version of the past or future state of the animal. Whether that encoding is biased towards past or future states and the extent to which it shows fixed versus multi-scale encoding varies across circuits and cell types. The temporal encoding properties of boundary vector cells of the subiculum are not well established. To address this here, we re-analyzed recordings of BVCs described previously by Lever et al. (2009) with multiple approaches. In the first, we asked if adding a temporal offset between the rat position and the spiking of a BVC increased the apparent spatial tuning in the firing rate map. We found that aligning BVC spiking with future states maximized the rate map spatial tuning. These results were mirrored in a second analysis that, instead of optimizing rate map spatial tuning, optimized how well the firing rate map predicted the BVC spiking. The second analysis also allowed us to ask whether that encoding is focused on a particular temporal horizon or whether the encoding captures behavior at multiple scales. To this end, for a given recording, we asked "How much time-integration of the behavioral state is the observed spiking most consistent with?" We observed a wide spectrum of time-constants of integration across cells, indicating that BVCs form a multiscale encoding of future states. The distribution of both offsets and integration rates observed across BVCs did not differ significantly from other, non-BVC, subiculum neurons. Taken together, these findings indicate that BVCs, along with other subiculum neurons, form a multi-scale encoding of future states.

neuroscience↗

bioRxiv2025

Intrinsic persistent firing in CA1 encodes elapsed time across behaviorally relevant scales

The ability to encode and maintain temporal relationships is crucial for learning, predicting, and forming episodic memories. While hippocampal time cells and entorhinal temporal context cells are well-established in vivo, it remains unclear whether single neurons can sustain representations of elapsed time over multi-second intervals, independent of synaptic drive. Here, using whole-cell patchclamp recordings in rat hippocampal CA1 slices under synaptic blockade, we show that following a brief current pulse, many neurons exhibit exponentially decaying firing rates with a broad distribution of time constants extending to tens of seconds. This indicates that single neurons possess intrinsic mechanisms capable of covering behaviorally relevant temporal scales. These results highlight that single neurons can encode temporal information over more than an order of magnitude, providing a potential cellular substrate for temporal coding in the brain.

neuroscience↗

bioRxiv2025

Path integration impairments reveal early cognitive changes in Subjective Cognitive Decline

Path integration, the ability to track ones position using self-motion cues, is critically dependent on the grid cell network in the entorhinal cortex, a region vulnerable to early Alzheimers disease pathology. In this study, we examined path integration performance in individuals with subjective cognitive decline (SCD), a group at increased risk for Alzheimers disease, and healthy controls using an immersive virtual reality task. We developed a Bayesian computational model to decompose path integration errors into distinct components. SCD participants exhibited significantly higher path integration error, primarily driven by increased memory leak, while other modelling-derived error sources, such as velocity gain, sensory and reporting noise, remained comparable across groups. Our findings suggest that path integration deficits, specifically memory leak, may serve as an early marker of neurodegeneration in SCD and highlight the potential of self-motion-based navigation tasks for detecting pre-symptomatic Alzheimers disease-related cognitive changes. TeaserVirtual reality, modelling, and plasma biomarkers reveal path integration deficits in pre-symptomatic Alzheimers vs normal aging.

neuroscience↗

bioRxiv2025

rTCT: Rodent Triangle Completion Task to facilitate translational study of path integration

Path integration is navigation in the absence of environmental landmarks and is a primary cognitive mechanism underlying spatial memory. Path integration performance is primarily assessed in humans using the Triangle Completion Task (TCT). In humans, TCT has shown promise for the early diagnosis of Alzheimers disease. In rodents, however, path integration is assessed using a wide variety of tasks but none of which currently provide a homologue for the TCT. As rodents are routinely used as preclinical models, homologous path integration tasks that result in comparable performance metrics between species are important. In the present study we developed and tested a novel rodent version of the triangle completion task to enhance cross species comparability of path integration performance. Rats were able to comprehend and perform the task. A group of Alzheimers disease model rats (TgF344-AD) exhibited similar path integration performance to their wild-type littermates; however, analysis of behavioural structure suggests use of differing behavioural strategies. This work establishes a novel rodent homologue of the triangle completion task, facilitating enhanced reverse translational study of human path integration.

neuroscience↗

bioRxiv2019

Conjunctive representation of what and when in monkey hippocampus and lateral prefrontal cortex during an associative memory task

Adaptive memory requires the organism to form associations that bridge between events separated in time. Many studies show interactions between hippocampus (HPC) and prefrontal cortex (PFC) during formation of such associations. We analyze neural recording from monkey HPC and PFC during a memory task that requires the monkey to associate stimuli separated by about a second in time. After the first stimulus was presented, large numbers of units in both HPC and PFC fired in sequence. Many units fired only when a particular stimulus was presented at a particular time in the past. These results indicate that both HPC and PFC maintain a temporal record of events that could be used to form associations across time. This temporal record of the past is a key component of the temporal coding hypothesis, a hypothesis in psychology that memory not only encodes what happened, but when it happened.

neuroscience↗

bioRxiv2019

A temporal record of the past with a spectrum of time constants in the monkey entorhinal cortex

Episodic memory is believed to be intimately related to our experience of the passage of time. Indeed, neurons in the hippocampus and other brain regions critical to episodic memory code for the passage of time at a range of time scales. The origin of this temporal signal, however, remains unclear. Here, we examined temporal responses in the entorhinal cortex of macaque monkeys as they viewed complex images. Many neurons in the entorhinal cortex were responsive to image onset, showing large deviations from baseline firing shortly after image onset but relaxing back to baseline at different rates. This range of relaxation rates allowed for the time since image onset to be decoded on the scale of seconds. Further, these neurons carried information about image content, suggesting that neurons in the entorhinal cortex carry information not only about when an event took place but also the identity of that event. Taken together, these findings suggest that the primate entorhinal cortex uses a spectrum of time constants to construct a temporal record of the past in support of episodic memory.

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bioRxiv2018

A Neural Microcircuit Model for a Scalable Scale-invariant Representation of Time

Scale-invariant timing has been observed in a wide range of behavioral experiments. The firing properties of recently described time cells provide a possible neural substrate for scale-invariant behavior. Earlier neural circuit models do not produce scale-invariant neural sequences. In this paper we present a biologically detailed network model based on an earlier mathematical algorithm. The simulations incorporate exponentially decaying persistent firing maintained by the calcium-activated nonspecific (CAN) cationic current and a network structure given by the inverse Laplace transform to generate time cells with scale-invariant firing rates. This model provides the first biologically detailed neural circuit for generating scale-invariant time cells. The circuit that implements the inverse Laplace transform merely consists of off-center/on-surround receptive fields. Critically, rescaling temporal sequences can be accomplished simply via cortical gain control (changing the slope of the f-I curve).

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bioRxiv2017

Compressed timeline of recent experience in monkey lPFC

Cognitive theories suggest that working memory maintains not only the identity of recently-presented stimuli but also a sense of the elapsed time since the stimuli presentation. Previous studies of the neural underpinnings of working memory have focused on sustained firing, which can account for maintenance of the stimulus identity, but not for representation of the elapsed time. We analyzed single-unit recordings from the macaque lateral prefrontal cortex (lPFC) during performance of a delayed-match-to-category task. The sample stimulus triggered a consistent sequence of neurons, each neuron in the sequence firing during a circumscribed period of time. The sequences initiated by different sample stimuli were distinct but overlapping, with the degree of overlap reflecting the visual similarity of the stimuli that caused the sequences. These sequences of neurons encoded both stimulus identity and the elapsed time. The temporal code became less precise as the sample stimulus receded into the past. These findings suggest that working memory is maintained as a compressed timeline, consistent with longstanding cognitive theories of human memory.

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