Connect with us

Health

Prefrontal and lateral entorhinal neurons co-dependently learn item–outcome rules

Prefrontal and lateral entorhinal neurons co-dependently learn item–outcome rules

 


  • Suzuki, W. A. Associative learning signals in the brain. Prog. Brain Res. 169, 305–320 (2008).

    PubMed 

    Google Scholar
     

  • Osada, T., Adachi, Y., Kimura, H. M. & Miyashita, Y. Towards understanding of the cortical network underlying associative memory. Phil. Trans. R. Soc. B 363, 2187–2199 (2008).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Ozawa, T. & Johansen, J. P. Learning rules for aversive associative memory formation. Curr. Opin. Neurobiol. 49, 148–157 (2018).

    CAS 
    PubMed 

    Google Scholar
     

  • Igarashi, K. M., Lee, J. Y. & Jun, H. Reconciling neuronal representations of schema, abstract task structure, and categorization under cognitive maps in the entorhinal–hippocampal–frontal circuits. Curr. Opin. Neurobiol. 77, 102641 (2022).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Squire, L. R. Memory and the hippocampus: a synthesis from findings with rats, monkeys, and humans. Psychol. Rev. 99, 195–231 (1992).

    CAS 
    PubMed 

    Google Scholar
     

  • Buzsaki, G. & Moser, E. I. Memory, navigation and theta rhythm in the hippocampal–entorhinal system. Nat. Neurosci. 16, 130–138 (2013).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Morris, R. G. in The Hippocampus Book (ed. P. Andersen, P.) 581–714 (Oxford Univ. Press, 2007).

  • Eichenbaum, H. On the integration of space, time, and memory. Neuron 95, 1007–1018 (2017).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • O’Keefe, J. & Nadel, L. The Hippocampus as a Cognitive Map (Oxford Univ. Press, 1978).

  • Moser, E. I., Moser, M. B. & Roudi, Y. Network mechanisms of grid cells. Phil. Trans. R. Soc. B 369, 20120511 (2014).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Price, J. L. An autoradiographic study of complementary laminar patterns of termination of afferent fibers to the olfactory cortex. J. Comp. Neurol. 150, 87–108 (1973).

    CAS 
    PubMed 

    Google Scholar
     

  • Burwell, R. D. The parahippocampal region: corticocortical connectivity. Ann. N. Y. Acad. Sci. 911, 25–42 (2000).

    ADS 
    CAS 
    PubMed 

    Google Scholar
     

  • Igarashi, K. M. et al. Parallel mitral and tufted cell pathways route distinct odor information to different targets in the olfactory cortex. J. Neurosci. 32, 7970–7985 (2012).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Young, B. J., Otto, T., Fox, G. D. & Eichenbaum, H. Memory representation within the parahippocampal region. J. Neurosci. 17, 5183–5195 (1997).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Deshmukh, S. S. & Knierim, J. J. Representation of non-spatial and spatial information in the lateral entorhinal cortex. Front. Behav. Neurosci. 5, 69 (2011).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Tsao, A., Moser, M. B. & Moser, E. I. Traces of experience in the lateral entorhinal cortex. Curr. Biol. 23, 399–405 (2013).

    CAS 
    PubMed 

    Google Scholar
     

  • Igarashi, K. M., Lu, L., Colgin, L. L., Moser, M. B. & Moser, E. I. Coordination of entorhinal–hippocampal ensemble activity during associative learning. Nature 510, 143–147 (2014).

    ADS 
    CAS 
    PubMed 

    Google Scholar
     

  • Lee, J. Y. et al. Dopamine facilitates associative memory encoding in the entorhinal cortex. Nature 598, 321–326 (2021).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Martin, C., Beshel, J. & Kay, L. M. An olfacto-hippocampal network is dynamically involved in odor-discrimination learning. J. Neurophysiol. 98, 2196–2205 (2007).

    PubMed 

    Google Scholar
     

  • Cohen, J. Y., Haesler, S., Vong, L., Lowell, B. B. & Uchida, N. Neuron-type-specific signals for reward and punishment in the ventral tegmental area. Nature 482, 85–88 (2012).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Luo, W. et al. Acquiring new memories in neocortex of hippocampal-lesioned mice. Nat. Commun. 13, 1601 (2022).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Insausti, R., Herrero, M. T. & Witter, M. P. Entorhinal cortex of the rat: cytoarchitectonic subdivisions and the origin and distribution of cortical efferents. Hippocampus 7, 146–183 (1997).

    CAS 
    PubMed 

    Google Scholar
     

  • Witter, M. P. & Amaral, D. G. in The Rat Nervous System 3rd edn (ed. Paxinos, G.) 635–704 (Elsevier, 2004).

  • Zingg, B. et al. Neural networks of the mouse neocortex. Cell 156, 1096–1111 (2014).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Jun, H. et al. Disrupted place cell remapping and impaired grid cells in a knockin model of Alzheimer’s disease. Neuron 107, 1095–1112.e6 (2020).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Issa, J. B., Radvansky, B. A., Xuan, F. & Dombeck, D. A. Lateral entorhinal cortex subpopulations represent experiential epochs surrounding reward. Nat. Neurosci. 27, 536–546 (2024).

    CAS 
    PubMed 

    Google Scholar
     

  • Mulder, A. B., Nordquist, R., Orgut, O. & Pennartz, C. M. Plasticity of neuronal firing in deep layers of the medial prefrontal cortex in rats engaged in operant conditioning. Prog. Brain Res. 126, 287–301 (2000).

    CAS 
    PubMed 

    Google Scholar
     

  • Rushworth, M. F., Noonan, M. P., Boorman, E. D., Walton, M. E. & Behrens, T. E. Frontal cortex and reward-guided learning and decision-making. Neuron 70, 1054–1069 (2011).

    CAS 
    PubMed 

    Google Scholar
     

  • Euston, D. R., Gruber, A. J. & McNaughton, B. L. The role of medial prefrontal cortex in memory and decision making. Neuron 76, 1057–1070 (2012).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Anastasiades, P. G. & Carter, A. G. Circuit organization of the rodent medial prefrontal cortex. Trends Neurosci. 44, 550–563 (2021).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Lillicrap, T. P., Santoro, A., Marris, L., Akerman, C. J. & Hinton, G. Backpropagation and the brain. Nat. Rev. Neurosci. 21, 335–346 (2020).

    CAS 
    PubMed 

    Google Scholar
     

  • Konishi, M. I., Igarashi, K. M. & Miura, K. Biologically plausible local synaptic learning rules robustly implement deep supervised learning. Front. Neurosci. 17, 1160899 (2023).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Hasegawa, I., Fukushima, T., Ihara, T. & Miyashita, Y. Callosal window between prefrontal cortices: cognitive interaction to retrieve long-term memory. Science 281, 814–818 (1998).

    ADS 
    CAS 
    PubMed 

    Google Scholar
     

  • Tomita, H., Ohbayashi, M., Nakahara, K., Hasegawa, I. & Miyashita, Y. Top-down signal from prefrontal cortex in executive control of memory retrieval. Nature 401, 699–703 (1999).

    ADS 
    CAS 
    PubMed 

    Google Scholar
     

  • Frankland, P. W. & Bontempi, B. The organization of recent and remote memories. Nat. Rev. Neurosci. 6, 119–130 (2005).

    CAS 
    PubMed 

    Google Scholar
     

  • Tse, D. et al. Schema-dependent gene activation and memory encoding in neocortex. Science 333, 891–895 (2011).

    ADS 
    CAS 
    PubMed 

    Google Scholar
     

  • Eichenbaum, H. Prefrontal–hippocampal interactions in episodic memory. Nat. Rev. Neurosci. 18, 547–558 (2017).

    CAS 
    PubMed 

    Google Scholar
     

  • Kitamura, T. et al. Engrams and circuits crucial for systems consolidation of a memory. Science 356, 73–78 (2017).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Tse, D. et al. Schemas and memory consolidation. Science 316, 76–82 (2007).

    ADS 
    CAS 
    PubMed 

    Google Scholar
     

  • Baraduc, P., Duhamel, J. R. & Wirth, S. Schema cells in the macaque hippocampus. Science 363, 635–639 (2019).

    ADS 
    CAS 
    PubMed 

    Google Scholar
     

  • Simons, J. S. & Spiers, H. J. Prefrontal and medial temporal lobe interactions in long-term memory. Nat. Rev. Neurosci. 4, 637–648 (2003).

    CAS 
    PubMed 

    Google Scholar
     

  • Ito, H. T. Prefrontal–hippocampal interactions for spatial navigation. Neurosci. Res. 129, 2–7 (2018).

    PubMed 

    Google Scholar
     

  • Spellman, T. et al. Hippocampal–prefrontal input supports spatial encoding in working memory. Nature 522, 309–314 (2015).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Place, R., Farovik, A., Brockmann, M. & Eichenbaum, H. Bidirectional prefrontal–hippocampal interactions support context-guided memory. Nat. Neurosci. 19, 992–994 (2016).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Ito, H. T., Zhang, S. J., Witter, M. P., Moser, E. I. & Moser, M. B. A prefrontal–thalamo–hippocampal circuit for goal-directed spatial coding. Nature https://doi.org/10.1038/nature14396 (2015).

  • Feierstein, C. E., Quirk, M. C., Uchida, N., Sosulski, D. L. & Mainen, Z. F. Representation of spatial goals in rat orbitofrontal cortex. Neuron 51, 495–507 (2006).

    CAS 
    PubMed 

    Google Scholar
     

  • Wang, P. Y. et al. Transient and persistent representations of odor value in prefrontal cortex. Neuron 108, 209–224.e6 (2020).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Basu, R. et al. The orbitofrontal cortex maps future navigational goals. Nature 599, 449–452 (2021).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Jun, H., Chavez, J., Bramian, A. & Igarashi, K. M. Protocol for remapping of place cells in disease mouse models. STAR Protoc. 2, 100759 (2021).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Kvitsiani, D. et al. Distinct behavioural and network correlates of two interneuron types in prefrontal cortex. Nature 20, 363–366 (2013).

    ADS 

    Google Scholar
     

  • Sources

    1/ https://Google.com/

    2/ https://www.nature.com/articles/s41586-024-07868-1

    The mention sources can contact us to remove/changing this article

    What Are The Main Benefits Of Comparing Car Insurance Quotes Online

    LOS ANGELES, CA / ACCESSWIRE / June 24, 2020, / Compare-autoinsurance.Org has launched a new blog post that presents the main benefits of comparing multiple car insurance quotes. For more info and free online quotes, please visit https://compare-autoinsurance.Org/the-advantages-of-comparing-prices-with-car-insurance-quotes-online/ The modern society has numerous technological advantages. One important advantage is the speed at which information is sent and received. With the help of the internet, the shopping habits of many persons have drastically changed. The car insurance industry hasn't remained untouched by these changes. On the internet, drivers can compare insurance prices and find out which sellers have the best offers. View photos The advantages of comparing online car insurance quotes are the following: Online quotes can be obtained from anywhere and at any time. Unlike physical insurance agencies, websites don't have a specific schedule and they are available at any time. Drivers that have busy working schedules, can compare quotes from anywhere and at any time, even at midnight. Multiple choices. Almost all insurance providers, no matter if they are well-known brands or just local insurers, have an online presence. Online quotes will allow policyholders the chance to discover multiple insurance companies and check their prices. Drivers are no longer required to get quotes from just a few known insurance companies. Also, local and regional insurers can provide lower insurance rates for the same services. Accurate insurance estimates. Online quotes can only be accurate if the customers provide accurate and real info about their car models and driving history. Lying about past driving incidents can make the price estimates to be lower, but when dealing with an insurance company lying to them is useless. Usually, insurance companies will do research about a potential customer before granting him coverage. Online quotes can be sorted easily. Although drivers are recommended to not choose a policy just based on its price, drivers can easily sort quotes by insurance price. Using brokerage websites will allow drivers to get quotes from multiple insurers, thus making the comparison faster and easier. For additional info, money-saving tips, and free car insurance quotes, visit https://compare-autoinsurance.Org/ Compare-autoinsurance.Org is an online provider of life, home, health, and auto insurance quotes. This website is unique because it does not simply stick to one kind of insurance provider, but brings the clients the best deals from many different online insurance carriers. In this way, clients have access to offers from multiple carriers all in one place: this website. On this site, customers have access to quotes for insurance plans from various agencies, such as local or nationwide agencies, brand names insurance companies, etc. "Online quotes can easily help drivers obtain better car insurance deals. All they have to do is to complete an online form with accurate and real info, then compare prices", said Russell Rabichev, Marketing Director of Internet Marketing Company. CONTACT: Company Name: Internet Marketing CompanyPerson for contact Name: Gurgu CPhone Number: (818) 359-3898Email: [email protected]: https://compare-autoinsurance.Org/ SOURCE: Compare-autoinsurance.Org View source version on accesswire.Com:https://www.Accesswire.Com/595055/What-Are-The-Main-Benefits-Of-Comparing-Car-Insurance-Quotes-Online View photos

    ExBUlletin

    to request, modification Contact us at Here or [email protected]