Biology subjects

Jayaprakash, B.

Publications and source records attributed to Jayaprakash, B..

7 recordsLinked to original sources

bioRxiv2026

Retrieval uncertainty drives rapid consolidation of confabulated memories in retrosplenial cortex

Learning to make associations in the absence of direct reinforcement, based on previous memories of reward or punishment, is an evolutionary trait quintessential for survival. Little is known about if such higher order associations (HOA) can lead to fabrication of new memories for unreal events. We probed if uncertainty during retrieval of old memory representations can trigger such confabulation. Using chemogenetics, in vivo imaging, and behavior we show that uncertainty in memory perception can not only transfer conditioning to hitherto unexperienced novel context but also can get rapidly consolidated. We find while acquisition of HOA require dorsal-CA1 parvalbumin interneuron activity in intact hippocampus, retrieval requires retrosplenial cortex (RSc). We develop an automated Large-scale Brainwide Correlated Activity Mapping (LaBCAM) method to identify functional connectivity changes across different brain regions in such scenarios. LaBCAM finds that only uncertain remote retrieval engages canonical fear circuitry while regular retrieval does not. Longitudinal imaging of dendritic spines in RSc, a region involved in detection and context-dependent conflict resolution, reveals differential reorganization of spines during acquisition and rapid systems consolidation of HOA. Interestingly, we find HOA is implicated early in AD mice model (APP/PS1) and also in aged animals.

neuroscience↗

bioRxiv2025

Tracking instances of task evoked oxygen influxes using a novel sensitive BLE enabled wearable fNIRS device identifies mPFC role in spatial memory.

Real-world neuroimaging requires true portability and sensitivity to detect signals from neuronal activity. Conventional methods such as MRI, EEG, or PET are constrained by their size and instrumentation complexity. Near Infra-Red (NIR) based optical methods have the potential for sensitive detection with a smaller footprint. Despite rapid advances in NIR detection there is no known device that is implementable using off-the-shelf integrated microprocessors and possesses the above desired characteristics along with proven sensitivity to detect task evoked responses. Here, we present a Bluetooth Low Energy (BLE)-enabled, high-sensitivity wearable functional near-infrared spectroscopy (fNIRS) device designed for untethered cortical hemodynamic monitoring during naturalistic cognitive tasks. Our fully integrated optical sensing device merges optical data acquisition and wireless transmission into a compact, cable-free platform with a very small footprint. This enables continuous multi-channel recording without placing any constraint on the subjects movement. We validate our device for reliable detection of task-evoked oxy- and deoxy-hemoglobin dynamics in the forearm, primary motor cortex, primary visual cortex, and prefrontal cortex. Subsequently, we capture real-time forebrain activity during a screen-based learning and memory task, revealing robust goal-specific hemodynamic responses. We formulate a method to identify the instances of peak neuronal activity and follow the "task Evoked Instances of Differential Oxygen influx(tEIDO)" as the subject is engaged in a task. These results highlight the potential of our proposed fNIRS device as a mobile neuroimaging solution for next-generation brain-computer interfaces and real-world cognitive monitoring. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=79 SRC="FIGDIR/small/690628v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@1f55855org.highwire.dtl.DTLVardef@7a67b8org.highwire.dtl.DTLVardef@2f6146org.highwire.dtl.DTLVardef@9b6e0c_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2024

Explicitly Acquired Interrelations Among Mental Schema Reduces Cognitive Load and Facilitates Emergence of Novel Responses in Mice and Artificial Neural Networks.

Mammalian brain has evolved to infer from past experiences and elicit context relevant novel behavioural responses hitherto unexpressed by the animal. However, little is known about how prior knowledge influences the emergence of such responses. Remarkably, the brain not only arrives at these responses through logical inferences based on previous leanings, but also acquire new related information, without causing catastrophic interference. Mental schemas have often been proposed as the framework for this phenomenon. In this study, using mice as a model animal, we show that schematic networks not only enhance the cognitive load handling capacity (CLHC) and prevent catastrophic interference, but also facilitate the generation of novel, contextually relevant responses. Interestingly, when the animals were trained in a paradigm that did not invoke the pre-formed mental schema, we observed neither an enhancement to CLHC nor a generation of novel context relevant responses. Based on the principles of mental schemas discovered in our animal experiments, we developed a biologically plausible artificial neural network (ANN) that avoids catastrophic interference and captures the learning properties observed in our experiments. The custom architecture of this ANN enables it to generate responses similar to those of animals in novel scenarios. Significance StatementLittle is known about the role of mental schemas in preventing memory interference--a process in which overlapping or similar memories hinder the acquisition and retention of related information. In this study, we demonstrate that mental schemas enhance cognitive load handling capacity and improve the ability to solve novel but related problems. Using mice as a model, we show that the mere existence of a mental schema is not enough for improved cognitive load handling; instead, the relationship between existing and new information must be explicitly established during the learning process. Based on these findings, we developed a minimalistic artificial neural network (ANN) that effectively mimics this behaviour. These insights pave the way for developing more efficient learning and teaching strategies.

neuroscience↗

bioRxiv2023

SRF-deficient astrocytes provide neuroprotection in mouse models of excitotoxicity and neurodegeneration

Reactive astrogliosis is a common pathological hallmark of central nervous system (CNS) injury, infection, and neurodegeneration, where reactive astrocytes can be protective or detrimental to normal brain functions. Currently, the mechanisms regulating neuroprotective astrocytes and the extent of neuroprotection are poorly understood. Here, we report that conditional deletion of serum response factor (SRF) in adult astrocytes causes reactive-like hypertrophic astrocytes throughout the mouse brain. These SrfGFAP-ERCKO astrocytes do not affect neuron survival, synapse numbers, synaptic plasticity or learning and memory. However, the brains of Srf knockout mice exhibited neuroprotection against kainic-acid induced excitotoxic cell death. Relevant to human neurodegenerative diseases, SrfGFAP-ERCKO astrocytes abrogate nigral dopaminergic neuron death and reduce {beta}-amyloid plaques in mouse models of Parkinsons and Alzheimers disease, respectively. Taken together, these findings establish SRF as a key molecular switch for the generation of reactive astrocytes with neuroprotective functions that attenuate neuronal injury in the setting of neurodegenerative diseases.

neuroscience↗

bioRxiv2021

Novel measures of Morris water maze performance that use vector field maps to assess accuracy, uncertainty, and intention of navigational searches

Most commonly used behavioural measures for testing learning and memory in the Morris water maze (MWM) involve comparisons of an animals residence time in different quadrants of the pool. Such measures are limited in their ability to test different aspects of the animals performance. Here, we describe novel measures of performance in the MWM that use vector fields to capture the motion of mice as well as their search pattern in the maze. Using these vector fields, we develop quantitative measures of performance that are intuitive and more sensitive than classical measures. First, we describe search patterns in terms of vector field properties and use these properties to define three metrics of spatial memory namely Spatial Accuracy, Uncertainty and, Intensity of Search. We demonstrate the usefulness of these measures using four different data sets including comparisons between different strains of mice, an analysis of two mouse models of Noonan syndrome (Ptpn11 D61G and Ptpn11 N308D/+), and a study of goal reversal training. Importantly, besides highlighting novel aspects of performance in this widely used spatial task, our measures were able to uncover previously undetected differences, including in an animal model of Noonan syndrome, which we rescued with the mitogen activated protein kinase kinase (MEK) inhibitor SL327. Thus, our results show that our approach breaks down performance in the Morris water maze into sensitive measurable independent components that highlight differences in spatial learning and memory in the MWM that were undetected by conventional measures.

animal behavior and cognition↗

bioRxiv2021

Implicitly Learned Higher Order Associations Differentiates Recent and Remote Retrieval of Temporal Order Memory

Memory of an ordered sequence of distinct events requires encoding the temporal order as well as the intervals that separates these events. In this study, using order place association task where the animal learns to associate the location of the food pellet to the order of entry into the event arena, we probe the nature of temporal order memory in mice. In our task, individual trials, become distinct events, as the animal is trained to form unique association between entry order and a correct location. The inter-trial intervals (> 30 mins) are chosen deliberately to minimise the working memory contributions. We develop this paradigm initially using 4 order place associates and later extend it to 5 paired associates. Our results show that animals not only acquire these explicit (entry order to place) associations but also higher order associations that can only be inferred implicitly from the temporal order of these events. As an indicator of such higher order learning during the probe trail the mice exhibit predominantly prospective errors that declines proportionally with temporal distance. On the other hand, prior to acquiring the sequence the retrospective errors are dominant. Additionally, we also tested the nature of such acquisitions when temporal order CS is presented along with flavour as a compound stimulus comprising of order and flavour both simultaneously being paired with location. Results from these experiments indicate that the animal learns both order-place and flavour-place associations. Comparing with pure order place training, we find that the additional flavour in compound training did not interfere with the ability of the animals to acquire the order place associations. When tested remotely, pure order place associations could be retrieved only after a reminder training. Further higher order associations representing the temporal relationship between the events is markedly absent in the remote time.

animal behavior and cognition↗

bioRxiv2020

Immediate early gene expression dynamics in vivo segregates neuronal ensemble of multiple memories.

Immediate early genes (IEGs) are widely used as a marker for neuronal plasticity. Here, we model the dynamics of IEG expression as a consecutive, irreversible first order reaction with a limiting substrate. We show that such a model, together with two-photon in vivo imaging of IEG expression, can be used to identify distinct neuronal subsets representing multiple memories. We image retrosplenial cortex (RSc) of cFOS-GFP transgenic mice to follow the dynamics of cellular changes resulting from both seizure and contextual fear conditioning behaviour. The analytical expression allowed us to segregate the neurons based on their temporal response to one specific behavioural event, thereby improving the sensitivity of detecting plasticity related neurons. This enables us to establish representation of context in RSc at the cellular scale following memory acquisition. Thus, we obtain a general method which distinguishes neurons that took part in multiple temporally separated events, by measuring fluorescence from individual neurons in live mice. SummaryIdentifying neuronal ensemble associated with different memories is vital in modern neuroscience. Meenakshi et al model and use the temporal expression dynamics of IEGs rather than thresholded intensities of the probes to identify the neurons encoding different memory in vivo. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=94 SRC="FIGDIR/small/423270v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@1d6c197org.highwire.dtl.DTLVardef@3fca7aorg.highwire.dtl.DTLVardef@64615org.highwire.dtl.DTLVardef@1e30dbc_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗