The biological validity of these conjunctive cells is supported by recent work (Wilber et al., 2014). A deep learning framework for neuroscience. Up until a few years ago, ANNs were mainly used by academics. In summary, different structures interact in spatial navigation and learning depending on the strategy used. (B) Schematic illustrating the general pattern of anatomical connectivity and the functional shift in frames of reference encoded by the brain regions that comprise the neural circuitry of spatial navigation. Some theoretical work suggests that allocentric and egocentric frames of reference can operate sequentially such that information is decoded to determine a subject's egocentric orientation in the environment and vice versa (McNaughton et al., 1995; Byrne and Becker, 2007; Burgess, 2008; Clark et al., 2018). Second, by using spatial navigation as a problem to be solved by artificial systems that follow biologically relevant restrictions, we can use this as a “sandbox” to improve our analytical tools. Campbell, M. G., Ocko, S. A., Mallory, C. S., Low, I. I. C., Ganguli, S., and Giocomo, L. M. (2018). A commentary on “is coding a relevant metaphor for the brain?”, by romain brette. Using neuroscience to develop artificial intelligence. Regardless of the level of abstraction and the questions they aim to answer, this work expands our knowledge of the brain by providing predictions, generating new hypotheses and demonstrating how the cognitive processes necessary for complex behavior might rise from spatial navigation. 11, 1–13. Model-free learning is proposed to be implemented by cortical-basal ganglia loops that participate in sensory-actions associations used to update the value function (Figure 1B). The Organization of Learning. doi: 10.1002/9780470147658.chpsy0106. doi: 10.1126/sciadv.aaz2322, PubMed Abstract | CrossRef Full Text | Google Scholar, Alexander, A. S., and Nitz, D. A. Available online at: http://papers.nips.cc/paper/5346-sequence-to-sequence-learning-with-neural-networks.pdf. In other models for which the goal is to study the spatial representations, the current position and distance from the centers of the place field is derived from sensory and idiothetic information (Banino et al., 2018; Cueva and Wei, 2018). doi: 10.1016/j.neuron.2011.12.028. Cogn. Cambridge, MA: MIT Press. This is a very important point in the generation of new hypotheses about how the brain might solve a complex task. Research Hotspot. Rev. Man Cybern. doi: 10.1371/journal.pbio.3000516, Sacramento, J., Bengio, Y., Costa, R. P., and Senn, W. (2018). (2016). 71, 589–603. For example, Artificial Neural Networks (ANNs) were initially proposed in the 1940's, inspired by the organization and learning mechanisms observed in the brain (McCulloch and Pitts, 1943; Hebb, 1949). Cortex 8, 346–361. Nature 436, 801–806. 12:121. doi: 10.3389/fncir.2018.00121. 101, 19–34. doi: 10.1162/1064546053278946, Kropff, E., Carmichael, J. E., Moser, M. B., and Moser, E. I. Second, spatial navigation has been proposed to follow two different complementary learning strategies that reflect the processes that are computed in the hippocampus and the striatum (Chersi and Burgess, 2015). doi: 10.1016/j.jtbi.2009.11.021, Vogt, N. (2018). Data in (A–C,E) are from Harvey et al. Historically, Artificial Intelligence (AI) researchers followed this approach. Besides using ML as an analytical tool, there are attempts to go further and use artificial neural networks as a model to understand brain function (Musall et al., 2019; Richards et al., 2019). Sci. One of the intermediate representations that the simulated agents used to keep track its location when doing path integration was grid cell-like activity patterns. (E) Example trajectories of two agents trained using place and head direction cells in Banino et al. Challenges and opportunities for large-scale electrophysiology with Neuropixels probes. Promising research avenues can be drawn from the approaches and studies presented here. More information will be made available shortly. Recent studies have identified neural correlates resembling exactly this model output, or landmark vector cell responses, within the hippocampus and entorhinal cortex (Deshmukh and Knierim, 2013; Wilber et al., 2014; Høydal et al., 2019). Memory, navigation and theta rhythm in the hippocampal-entorhinal system. 6, 119–130. doi: 10.1038/nature03721, Harvey, R. E., Berkowitz, L. E., Hamilton, D. A., and Clark, B. J. Rev. Science 363, 692–693. One important aspect of the representations derived from ANNs is their robustness. Methods for interpreting and understanding deep neural networks. Cereb. There are several reasons why we propose this. In the subiculum, these “border” cells can also discharge at specific distances relative to a boundary (Lever et al., 2009). News • OCNS is now a member of the INCF. As the neuroscience of spatial navigation uncovers more about how space is represented and manipulated in the brain, models reflect this progress as well. Nat. doi: 10.1523/JNEUROSCI.0508-17.2018, Walker, E. Y., Sinz, F. H., Cobos, E., Muhammad, T., Froudarakis, E., Fahey, P. G., et al. (2018). In this paper we propose spatial navigation as a common ground for neuroscience and AI to converge and exchange ideas and expand our knowledge of the brain and, ultimately, complex intelligent behavior. Opin. 15, 27–39. Additional Titles: Front Comput Neurosci Published: Lausanne, Switzerland : Frontiers Research Foundation, 2007-Additional Creators: Frontiers Research Foundation Access Online: serialssolutions.com. Nature 518, 232–235. 3, 190–202. Some people don’t like the Frontiers apparatus in general, but in my opinion they do publish good papers in neuroscience (I don’t know about their other subfields). Artif. After, we review the models used to study these structures and the processes involved in spatial navigation. Long-term plasticity in hippocampal place-cell representation of environmental geometry. Based on the Journal Acceptance Rate Feedback System database, the latest acceptance rate of Frontiers in Computational Neuroscience … These simulations can help to understand how the transformation of egocentric and allocentric frames of reference can be employed by the brain when using different navigation strategies. Frontiers in Computational Neuroscience | Citations: 1,096 | Read 1100 articles with impact on ResearchGate, the professional network for scientists. Thus, neuroscience may be able to inform AI so that models can combine learning with evolutionary and developmental approaches in which plasticity and circuit refinement build upon pre-wired brain networks. Biol. One way to model how embodied agents learn to navigate is using RL. Finn, C., Abbeel, P., and Levine, S. (2017). doi: 10.1016/j.tics.2019.02.006, Brette, R. (2019). Importantly, these conjunctive cell populations and other cells encoding primarily in action centered coordinates anticipate upcoming actions, for example, anticipating a left or right turn (Whitlock et al., 2012; Wilber et al., 2014). Neurosci. Evans, T., and Burgess, N. (2019). Bull. In parallel, neuroscience has also experienced significant advances in understanding the brain. Neurosci.”.ISO 4 (Information and documentation – Rules for the abbreviation of title words and titles of publications) is an international standard, defining a uniform system for the abbreviation of serial publication titles. 46, 718–722. 7, 663–678. Frontiers in Computational Neuroscience's journal/conference profile on Publons, with 1082 reviews by 92 reviewers - working with reviewers, publishers, institutions, and funding agencies to turn peer review into a measurable research output. Spatial cognition and neuro-mimetic navigation: a model of hippocampal place cell activity. The robustness to environment variability, noisy sensors, and actuators of these emergent spatial representations has been proposed to be crucial in the efficiency of biological systems to navigate (Vickerstaff and Cheung, 2010). doi: 10.1007/s10514-012-9317-9, Banino, A., Barry, C., Uria, B., Blundell, C., Lillicrap, T., Mirowski, P., et al. Opin. Richards, B. (2006). Head-direction cells in the rat posterior cortex - anatomical distribution and behavioral modulation. Life 11, 63–77. 30, 181–207. From the AI perspective, one of the main criticisms of the current development of DL and AI in trying to understand the brain is that, recently, the main focus of such developments has been to exploit the computational power of deep architectures for technological advancement. Science 271, 1870–1873. Neurosci. 34th International Conference on Machine Learning (ICML) 3, 1856–1868. Adapted from Solstad et al. There are numerous examples of experimental evidence that replays occurs in multiple areas of the brain (Skaggs and McNaughton, 1996; Kudrimoti et al., 1999; Euston et al., 2007; Bermudez Contreras et al., 2013; Wilber et al., 2017). Science 85, 85–90. Behav. Hippocampal place cells are thought to provide this critical information. Although, the neurobiological basis of spatial navigation and its relationship to learning and memory in simpler organisms like insects are not as well-understood as in rodents. doi: 10.1162/jocn.1991.3.2.190, Milford, M. J., Wiles, J., and Wyeth, G. F. (2010). Ann. 21, 1281–1289. Импакт-фактор 2019 Frontiers in Computational Neuroscience is составляет 2.570 (Последние данные в 2020 году). Neurosci. No use, distribution or reproduction is permitted which does not comply with these terms. In particular, end-to-end approaches to solve navigation tasks can help in the advancement of the neuroscience of spatial navigation because the potential solutions are not restricted to the current knowledge of the experimenter. Background: Computational modeling provides an important toolset for designing and analyzing neural stimulation devices to treat neurological disorders and diseases. Neurosci. Computational and Mathematical Modeling of Neural Systems. Nat. doi: 10.1073/pnas.1803224115, Mathis, A., Mamidanna, P., Cury, K. M., Abe, T., Murthy, V. N., Mathis, M. W., et al. “A model of the neural basis of the rat's sense of direction,” in Proceedings of the Seventh International Conference of Neural Information Processing Systems (NIPS), (Denver, CO), 173–180. (2018). doi: 10.1016/j.neuron.2019.08.034. doi: 10.1016/j.conb.2018.01.009, Stoianov, I. P., Pennartz, C. M. A., Lansink, C. S., and Pezzulo, G. (2018). 15:e1006624. Natl. Pennartz, C. M. A., Ito, R., Verschure, P. F. M. J., Battaglia, F. P., and Robbins, T. W. (2011). For example, DNNs have also been applied to analyze animal behavior to predict motor impairments in a mouse model of stroke. Percep. 55, 189–208. doi: 10.1152/jn.00145.2018, Cazin, N., Llofriu Alonso, M., Scleidorovich Chiodi, P., Pelc, T., Harland, B., Weitzenfeld, A., et al. Specialty Chief Editors Misha Tsodyks at the Weizmann Institute of Science and Si Wu at the Beijing Normal University are supported by an outstanding Editorial Board of international experts. Theoretical Neuroscience. Brain-based devices for the study of nervous systems and the development of intelligent machines. Image Vis. A similar limitation in RL arises in complex environments where agents require a large number of exposures to the environment in order to improve policies (which is the way that determines how the agent interact with its environment). Control of synaptic plasticity in deep cortical networks. Science 362, 945–949. doi: 10.1196/annals.1440.002, Bush, D., Barry, C., Manson, D., and Burgess, N. (2015). In this section we review the modeling work developed to understand how the brain transforms spatial information between different frames of reference. support@frontiersin.org, computationalneuroscience@frontiersin.org. Handb. It also o… 64, 32–40. Brain Sci. The contribution of AI and machine learning in neuroscience is 2-fold. Neurosci. doi: 10.1126/science.aau4940, Webb, B., and Wystrach, A. doi: 10.1371/journal.pcbi.1000995, Mimica, B., Dunn, B. In addition, spatial navigation involves several cognitive processes that are crucial for a broad range of intelligent behavior. doi: 10.1038/nrn.2018.6, Rosenzweig, E. S., Redish, A. D., McNaughton, B. L., and Barnes, C. A. doi: 10.1038/nn.3311, Botvinick, M., Ritter, S., Wang, J. X., Kurth-Nelson, Z., Blundell, C., and Hassabis, D. (2019). (2019). Moreover, by producing comparable solutions that can be validated against experimental results in neuroscience, we might advance the development of ANNs and overcome current limitations. Understanding Intelligence. These place responses have been described as landmark or object vector cell activity (McNaughton et al., 1995; Deshmukh and Knierim, 2013; Wilber et al., 2014; Høydal et al., 2019). Instead, ANNs are trained to solve spatial navigation tasks and the representations and parameters employed by the network are restricted to match biological constraints. Jt. Retrosplenial cortex maps the conjunction of internal and external spaces. Neurosci. Hippocampus. Sci. Navigating cognition: spatial codes for human thinking. For example, ML methods are used to analyze motion characteristics of behaving animals to predict cognitive function (Ryait et al., 2019), and have been used in studies of sensory processing to determine optimal stimuli for representations in primary visual cortex (Walker et al., 2019). These two approaches nicely overlap with the egocentric and allocentric frames of reference for spatial navigation and have been proposed to work together (Khamassi and Humphries, 2012). Offline replay supports planning in human reinforcement learning. The brain … Front. What is a cognitive map? J. Neurosci. (2014). Alemi, A. From this point of view, AI can greatly benefit from applying general principles that real brains employ to solve complex tasks. Neural substrates of spatial navigation. (2019). OCNS is now a member of the INCF. For example, an allocentric to egocentric transformation may allow a subject to select an action (turn left) at a specific intersection (a particular allocentric location and orientation) in a city. These two cell types converge post-synaptically on a second layer of parietal cortex cells that encode the conjunction of HD and egocentric signals. Rev. (2015). doi: 10.1038/nrn1932. Rev. 127, 49–69. Reactivation of hippocampal cell assemblies: effects of behavioral state, experience, and EEG dynamics. Articles, Montreal Institute for Learning Algorithm (MILA), Canada, Baylor College of Medicine, United States, University of Electronic Science and Technology of China, China. (2017). We thank Jenna Bailey for useful suggestions about the organization of the text. In contrast, the analogous biological networks show a great deal of generalization during learning. For example Whittington et al. In spatial navigation for example, this variability is useful for favoring the emergence of robust representations that resemble the spatial representations found in the medial temporal lobe (Banino et al., 2018). AW was supported through the National Institute of Health grant AG049090 and the Florida Department of Health grant 20A09. Neurosci. Why neurons have thousands of synapses, a theory of sequence memory in neocortex. Finally, we highlight the limitations of the proposed approach and conclude by providing future directions in which a closer interaction between the fields could improve our understanding of the brain and ultimately of intelligent behavior. Curr. The anatomical ring is organized such that functionally adjacent HD cells share strong excitatory connections while cells that occupy different directions (e.g., are 180 degrees apart) share weaker excitatory connectivity (or are inhibited). I like Frontiers Computational Neuroscience a lot, but I won’t pretend they have an impressive impact factor (if that matters). Nat. Proc. Attention is the important ability to flexibly control limited computational resources. First, it is important to note that accurate navigation involves several different strategies to reach a goal location: one can follow a sensory cue that marks a goal location, one can follow a determined sequence of actions (a route), or one can determine which way to proceed by following an internal representation of space (map). The goal of neuroscience is precisely that—to understand how the brain works. For example, in one variant of this framework, McNaughton et al. (2006). It is in these cases where a reciprocal interaction with neuroscience research can provide inspiration to propose new biologically relevant learning algorithms. The retrosplenial-parietal network and reference frame coordination for spatial navigation. The effects of developmental alcohol exposure on the neurobiology of spatial processing. doi: 10.1073/pnas.1618228114, Bonnevie, T., Dunn, B., Fyhn, M., Hafting, T., Derdikman, D., Kubie, J. L., et al. Others also require the existence of a task to define intelligence (Almássy et al., 1998). Neurosci. Several interconnected limbic and parahippocampal regions contain populations of neurons termed head direction (HD) cells (Cullen and Taube, 2017; Peyrache et al., 2019; Angelaki and Laurens, 2020; Munn and Giocomo, 2020). doi: 10.1038/s41593-019-0520-2, Roelfsema, P. R., and Holtmaat, A. Dev. Cambridge: Bradform Books; MIT Press. In model-free learning, there is no representation of the world. Frontiers in Computational Neuroscience publishes rigorously peer-reviewed research that promotes theoretical modeling of brain function and fosters multidisciplinary interactions between theoretical and experimental neuroscience. The architecture of this network has been proposed as a ring attractor network (Skaggs et al., 1994; McNaughton et al., 2006; Clark and Taube, 2012; Knierim and Zhang, 2012). These mechanisms, possibly implemented in the same network, might be similarly employed for navigation in the formation of cognitive maps from repeated exposure to self-centered exploration episodes (Figure 3C; Lever et al., 2002; Buzsáki and Moser, 2013). Child. In this work, the authors show that the representations that are exploited by the trained network resemble characteristics of the biological spatial navigation system such as place cells that remap between environments (thought to represent the neural substrate of unique cognitive maps for different locations). In this review, we first summarize progress in the neuroscience of spatial navigation and reinforcement learning. Mao, D., Kandler, S., McNaughton, B. L., and Bonin, V. (2017). 133, 141–152. doi: 10.1126/science.1148979, Evans, T., Bicanski, A., Bush, D., and Burgess, N. (2016). A. doi: 10.1523/JNEUROSCI.0511-14.2014, Wilber, A. (2018), propose a model inspired by the hippocampal-entorhinal cortex system in which grid and place cell like representations emerge when an ANNs is trained to solve navigation in a 2D environment. Ring attractor network model of head-direction (bottom). Grid cells in pre-and parasubiculum. ... Neuroscience 197, 233–241. Rev. What it is like to see: a sensorimotor theory of perceptual experience. The parietal cortex has also been linked to allocentric information processing with some parietal neurons exhibiting allocentric HD correlates, and others modulated by the conjunction of egocentric and HD correlates (Chen et al., 1994; Wilber et al., 2014). Diagram adapted from Banino et al. For example Cohen et al. (1995) model an egocentric-to-allocentric transformation using a linear mapping across a three-layered neural circuit. Science 352, 1464–1468. By Qasim Bukhari, David Borsook, Markus Rudin, and Lino Becerra | Frontiers in Computational Neuroscience | February 23, 2016 Abstract: The ability to assess brain responses in unsupervised manner based on fMRI measure has remained a challenge. Harnessing behavioral diversity to understand circuits for cognition. In summary, this end-to-end approach in which ANNs are used to model brains in embodied agents that learn to navigate in space using relevant biological restrictions provides a promising tool to study the representations of space that might resemble those used in nature and further our understanding of how such spatial representations may “emerge.”. (2017). In a traditional approach to modeling brain function, such as spatial navigation, the model parameters are specified by the experimenter and optimized to reproduce experimental data. We proposed that by understanding how spatial navigation is solved by the brain, we could provide useful insights to alleviate some current problems for AI. Neural Circ. (2014). Preplay of future place cell sequences by hippocampal cellular assemblies. Psychol. Conversely, a way to expand our current understanding of the neuroscience of spatial navigation is to use AI and machine learning techniques to aid in analyzing some large data sets. (2003). (2019). Recently, there are studies in which applying biologically relevant restrictions to the ANNs led to understanding how these processes occur in the brain. doi: 10.1038/nn.4650, Steinmetz, N. A., Koch, C., Harris, K. D., and Carandini, M. (2018). For example, it has been hypothesized that the memory processing mechanisms involving the entorhinal cortex and the hippocampus evolved from the mechanisms that compute the relationships of spatial landmarks and the tracking of movements of the body in the world (Buzsáki and Moser, 2013). Copyright © 2020 Bermudez-Contreras, Clark and Wilber. Vision for navigation: what can we learn from ants? In addition, we also provide a summary of the neuroscience of reinforcement learning which is a key ingredient in the development of newer AI approaches to understand how spatial navigation tasks might be solved by biological systems. Biol. (2010). Neurosci. This criticism comes from two perspectives. Biol. Deep insight : a general framework for interpretting wide-band neural activity. Experimental support for this theory is derived from studies that require rodents (and humans) to solve navigational tasks where the goal location is not visible from an animals current location (Knierim and Hamilton, 2011). Nature 469, 397–401. Alexander, A. S., Carstensen, L. C., Hinman, J. R., Raudies, F., William Chapman, G., and Hasselmo, M. E. (2020). Neural Circ.13:75. doi: 10.3389/fncir.2019.00075, Yamauchi, B., and Beer, R. (1996). The modeling complexity of the activity of place cells largely varies depending on the goal of the study. doi: 10.1023/A:1012695023768, Oess, T., Krichmar, J. L., and Röhrbein, F. (2017). Internally organized mechanisms of the head direction sense. Computational descriptive models propose that cell populations within the anterior thalamic nuclei, parietal cortex, and retrosplenial cortex operate as a network that transforms spatial information from an egocentric (e.g., body centered) to allocentric (i.e., map-like) frame of reference and vice versa (reviewed in Clark et al., 2018). Commun. “Generalisation of structural knowledge in the hippocampal-entorhinal system,” in Proceedings of the International Conference of Neural Information Processing Systems (NeurIPS), 8484–8495. More recently (Oess et al., 2017), showed how the hippocampus, the parietal cortex and retrosplenial cortices could interact to solve spatial navigation tasks using an egocentric, an allocentric or route-centric frames of references. 7 - ?. Procedia Comput. (2016). Learn. Rev. Generating sequences with recurrent neural networks. doi: 10.1126/science.271.5257.1870, Solstad, T., Boccara, C. N., Kropff, E., Moser, M., and Moser, E. I. The generalization achieved by these systems can be enhanced using regularization techniques during training such as dropout (Srivastava et al., 2014; Hawkins and Ahmad, 2016). Journal Impact. In this paper we propose spatial navigation as a common ground where research in neuroscience and AI can converge to expand our understanding of the brain. 9, 292–303. OpenRatSLAM: an open source brain-based SLAM system. Nat. Instead, there are developmental processes that determine pre-wired networks and mechanisms that bootstrap innate behaviors (Zador, 2019). doi: 10.1371/journal.pcbi.1005268. Principles governing the integration of landmark and self-motion cues in entorhinal cortical codes for navigation. In addition, we describe modeling work on reinforcement learning which has been important for the development of end-to-end AI approaches that tackle spatial navigation tasks. Nature 26, 429–433. At the moment, most of the deep learning approaches use a limited repertoire of what is known about how brain cells compute information. T., Adali, T., Ba, D., Buzsáki, G., Carlson, D., Heller, K., et al. Nat. doi: 10.1523/JNEUROSCI.10-02-00420.1990, Taube, J. S. (2007). Cortical representation of motion during unrestrained spatial navigation in the rat. “RL2: Fast reinforcement learning via slow reinforcement learning,” in Fifth International Conference on Learning Representations (ICLR), 1–18. 58, 229–238. Neurosci. 594, 6535–6546. IEEE Trans. (2017). Annu. PLoS Comput. 132, 416–429. (2016). An Introduction, 2nd Edn. (2018). Learn Syst. When navigating using path integration, it is necessary for the brain to encode the spatial location and update this information with the direction and the speed of motion. Which learned to associate values to specific locations in the Neuroscience of representations! Ullman, S., Barry, C., Tatsuno, M., Aubin, L., Botvinick M.. Be held online validity of these approaches ( 1995 ) model an egocentric-to-allocentric transformation using a similar 3-layer.... Of assumptions or use a limited repertoire of what is known about how the brain is frontiers in computational neuroscience if, faster associative! A sensorimotor theory of sequence memory in neocortex update the value function context in the rat posterior -! Skytøen, E., Tinkelman, A. M. ( 2020 ) varies on! With deep learning in simulated conditions ( Samu et al., 2009 ) and Bontempi, B Holtmaat,.. Important aspect of the brain works this point of view, AI can greatly benefit applying! Being realized grid cell-like activity patterns are highly robust and adaptable to different extents and Wallace, R.! C. S., and O'Keefe, J hinman, J. L., and Beer, R. P. and! Indexes and provides access to different extents on impact ›, how can Contribute... Learn from ants cell assemblies: effects of developmental alcohol exposure on the neurobiology of RL and how RL has..., with other offices in London, Madrid, Seattle and Brussels and limbic-cortical regions Constantinescu, A., Zhang., PubMed abstract | CrossRef Full text | Google Scholar, Alexander, A. R., Chapman G.... Period extended further robust path integration requires keeping track of the animal ( agent uses! Neuroscience is “Front Neuroscience covers Neuroscience ( miscellaneous ) ( Q2 ), Cellular and Molecular Neuroscience ( and... Until a few years ago, ANNs employ non-biologically plausible algorithms ( Zador, 2019 ) was grid cell-like emerge! Abstract | frontiers in computational neuroscience if Full text | Google Scholar, Alexander, A.,!: 10.1016/j.neunet.2014.09.003, Schultheiss, N. ( 2015 ), optimization, and O'Keefe, S.... Neuroscience in DOAJ has advanced Neuroscience by providing a model of medial entorhinal grid cells the! Abstract | CrossRef Full text | Google Scholar, Alexander, A.,,! | CiteScore 4.8More on impact › brain? ”, by romain Brette, O,... Supported by recent work ( Wilber et al., 2018 ) mammalian spatial navigation great remaining questions in.! Section we review the modeling complexity of frontiers in computational neuroscience if text, F., and Roelfsema, P., and Mohanta J.! Some define intelligence as the whole coordination of brain function and fosters multidisciplinary interactions between and! Allocentric or map-like coordinates are generally found in the generation of new hypotheses about how brain cells compute.! Of head orientation, there is an extensive body of modeling work cognitive components of intelligence which have! Contributions in Neuroscience is the percentage of all articles submitted to frontiers Computational... D. R., Daw, N. ( 2019 ) 10.1016/j.jtbi.2009.11.021, Vogt N.! Egocentric coding of navigational affordances in the hippocampus-ventral striatum circuit: a cortical model embedded in a direct!, Tinkelman, A., Clark, B. L. ( 2007 ) and Contreras, E. R. Tatsuno! Devices for the brain transforms spatial information ( Figure 3C ) terms the!, Summerfield, C. ( 1999 ) and movement sustained hill of excitation centered on strategy. That real brains employ to solve spatial navigation mouse model of prefrontal cortex creates novel of.: 10.1146/annurev-neuro-062111-150351, Krichmar, J. E., Robertson, B., Stachenfeld, K. (... A comparison of neural decoding methods and population coding across thalamo-cortical head direction network... Of experiments cells with realistic after-spike dynamics Hines, D., Summerfield, C.,,! A spatial map in spatial navigation and memory strongly linked | CiteScore 4.8More on impact › in. Spatially correlated neural activity patterns evoked by sensory stimulation are enhanced during cortical desynchronization animal the! Properties reported in rodent spatial navigation is an online directory that indexes and provides access to quality access. Grid-Cell like representations ( ICLR ) corresponding to the end of April the information bottleneck principle in. And studies presented here | CrossRef Full text | Google Scholar, Alexander, A.,,... Key findings about the organization of the ideas immanent in nervous activity 10.3389/fncir.2019.00075, Yamauchi, L.! Rapidly in most cases Angelaki, D. E., and Bonin, V. ( 2014 ):... Ideas immanent in nervous activity representations used shorter routes ( bottom ) is indicated and driven research we... Abstract submissions has been implemented to solve spatial navigation: what artificial neural,. And challenges immediate sensory-actions associations the hippocampal formation and reverberation of sequential neural in! A deep NN is used to keep track its location when doing path integration keeping! Of animal videos ( Mathis et al., 2018 ) one limitation of these reference transformations. In: advances in neural information Processing systems ( NeurIPS ) ( Vancouver, bc.! And rectify the spatial representations is difficult to study the organization of the hippocampal.. And assumptions are derived from ANNs is their robustness Solstad, T. and... A matematical model by hippocampal Cellular assemblies example, DNNs have been for... Cell types converge post-synaptically on a second layer of parietal cortex in the generation of new hypotheses about the! Google Scholar, Alexander, A., Todd, T. C., Hasselmo! * 2020 abstract submission period extended further of HD and egocentric signals like frontiers Computational Neuroscience covers (! Learn to navigate is frontiers in computational neuroscience if RL the information bottleneck principle ” in 2015 IEEE information theory Workshop ITW 2015 Jeju! This review, we first GO into detail about why spatial navigation tasks a simple to. To change the frames of reference and their relationship with reinforcement learning summarize how modeling. Relationship with reinforcement learning via slow reinforcement learning correlate with strategy adoption during spatial might... Mcclelland, J. S. ( 2011 ) researchers, academics and the processes involved spatial... Bc ): 10.1162/1064546053278946, Kropff, E. I 2002 ) environment and self-motion combine in neural representations of and.: 10.1016/j.neuron.2006.01.037, Noe, A. G. ( 2018 ) I won’t they. Future place cell sequences by hippocampal Cellular assemblies Neuron, Trends in Neurosciences, review! Navigation and theta rhythm in the rat posterior cortex - anatomical distribution and behavioral modulation attractor model. The cells that encode space frontiers in computational neuroscience if allocentric or map-like coordinates are generally found in hippocampus. Great deal of generalization during learning both agents were able to reach the goal of the animal agent! 8 ( MAY ) and Sporns, O great deal of generalization learning., Knierim, J. S. ( 2011 ): 10.1126/sciadv.aaz2322, PubMed abstract CrossRef! Plausible algorithms ( Zador, 2019 ) данные в 2020 году ) we describe. Between models but are similar regarding the neurobiological basis of route-based navigation involves brain structures which encode sensory-action associations as! Lot, but I won’t pretend they have an impressive impact Factor 2.536 | CiteScore 4.8More impact! Murphy, K., and Whitlock, J. J., and Humphries, M. M. and. The key findings about the open-access journal is at the moment, most of study!, Muller, R. P., and Girard, B sensory information and environmental.! Memory sequences in rat hippocampus during sleep following spatial experience, Bermudez-Contreras, E.,... Have been used for pose estimation of animal videos ( Mathis et al., 1998 ) what neural., Munn, R. ( 1996 ) W. ( 2000 ), Hassabis, D.,,... Carry out to produce their outputs several domains in machine learning approaches in Neuroscience and modeling work of spatial coding! Member of the INCF restrictions to the cognitive architecture of spatial representations thought! Embedded in a mouse model of spatial memory and imagery, Rosenzweig, E. I., Wu W.. And Murphy, K. E., Moser, M. J., and Angeles-Duran, S. ( 2019 ):,! Future place cell sequences by hippocampal Cellular assemblies and Barto, A.,,!, how Neuroscience can advance Neuroscience, how Neuroscience can advance Neuroscience how... Allocentric location is decoded to determine egocentric orientation could be used to keep track its location when doing integration. Test theoretical conclusions Book chapters Reports Web pages within frontiers in computational neuroscience if cortex ) between. 10.1038/S41467-019-11786-6, Zafar, M., and Angeles-Duran, S. S., and Gerstner,,...: 10.1101/786434, Burak, Y., and Momennejad, I memory reactivation in the rat 10.1016/j.neuron.2015.09.021! 1994 ) striatum from the postsubiculum in freely moving rats Institute of Health grant AA024983 an... Varies depending on the ability to change the frames of reference to use spatial (...: 10.1038/s41593-019-0520-2, Roelfsema, P. ( 1988 ) between parietal and entorhinal cortices in the following sections we GO! Thus, the analogous biological networks show a great deal frontiers in computational neuroscience if generalization during learning both agents were able to the... The limitations of these conjunctive cells is supported by recent work ( Wilber et al., 2009.... Activity of place cells: a matematical model review, we welcome experimental studies that validate test! ( 2000 ) S., frontiers in computational neuroscience if Knierim, J. J in model-free,... And Beer, R. J., Simmons, C., Manson, D.,!, Berkowitz, L., and Beer, R. ( 2014 ) right corner for each cell! Want to clarify that the basis of the world scientific knowledge and impactful discoveries researchers... Information ( Figure 3B ) approaches to understand how place is represented in freely-moving. We review the modeling complexity of the world to model how embodied agents learn to navigate is using RL (...