Alessandro Giuliano Treves

• Centonze, Martino Salomone; Treves, Alessandro Giuliano; Agliari, Elena & Barra, Adriano (2025). Analytical Methods for Continuous Attractor Neural Networks. Journal of statistical physics. ISSN 0022-4715. 192(5). doi: 10.1007/s10955-025-03447-4. Full text in Research Archive Show summary

  Pyramidal cells that emit spikes when the animal is at specific locations of the environment are known as place cells: these neurons are thought to provide an internal representation of space via cognitive maps. Here, we consider the Battaglia-Treves neural network model for cognitive map storage and reconstruction, instantiated with McCulloch & Pitts binary neurons. To quantify the information processing capabilities of these networks, we exploit spin-glass techniques, namely the interpolation method and the replica trick. In particular, in the low-storage regime (i.e., when the number of stored maps scales sub-linearly with the network size and the order parameters self-average around their means), by adapting the Hamilton-Jacobi PDE-approach, we obtain an exact phase diagram in the noise vs inhibition strength plane. In the high-storage regime, by adapting the standard interpolation based on stochastic stability, we find that—for mild inhibition and not too high noise—memorization and retrieval of an extensive number of spatial maps is possible. These results, holding under the replica-symmetry assumption, are recovered, for completeness, also by the replica method and they are corroborated by Monte Carlo simulations. Finally, by leveraging the integral representation of the model (in terms of a bipartite network equipped with highly-selective hidden units), we successfully test its robustness versus various distributions of place fields, including the log-normal distribution observed in recent experiments on bats navigating long tunnels. Additionally, we demonstrate that, by appropriately coupling these hidden units, the network can effectively orient itself even in dynamic environments.

• Rolls, Edmund & Treves, Alessandro Giuliano (2024). A theory of hippocampal function: New developments. Progress in Neurobiology. ISSN 0301-0082. doi: 10.1016/j.pneurobio.2024.102636. Full text in Research Archive
• Ryom, KwangIl; Basu, Anindita; Stendardi, Debora; Ciaramelli, Elisa & Treves, Alessandro Giuliano (2024). Taking time to compose thoughts with prefrontal schemata. Experimental Brain Research. ISSN 0014-4819. doi: 10.1007/s00221-024-06785-z. Full text in Research Archive
• Rajan, Kanaka; Treves, Alessandro Giuliano & Gaudenzi, Rocco (2024). Reflections on Simplicity and Complexity in Computational Neuroscience. Human Arenas. ISSN 2522-5790. doi: 10.1007/s42087-024-00423-4. Full text in Research Archive
• Schönsberg, Francesca; Monasson, Rémi & Treves, Alessandro Giuliano (2024). Continuous Quasi-Attractors dissolve with too much - or too little - variability. PNAS Nexus. 3(12), p. 1–12. doi: 10.1093/pnasnexus/pgae525. Full text in Research Archive Show summary

  Recent research involving bats flying in long tunnels has confirmed that hippocampal place cells can be active at multiple locations, with considerable variability in place field size and peak rate. With self-organizing recurrent networks, variability implies inhomogeneity in the synaptic weights, impeding the establishment of a continuous manifold of fixed points. Are continuous attractor neural networks still valid models for understanding spatial memory in the hippocampus, given such variability? Here, we ask what are the noise limits, in terms of an experimentally inspired parametrization of the irregularity of a single map, beyond which the notion of continuous attractor is no longer relevant. Through numerical simulations we show that (i) a continuous attractor can be approximated even when neural dynamics ultimately converge onto very few fixed points, since a quasi-attractive continuous manifold supports dynamically localized activity; (ii) excess irregularity in field size however disrupts the continuity of the manifold, while too little irregularity, with multiple fields, surprisingly prevents localized activity; and (iii) the boundaries in parameter space among these three regimes, extracted from simulations, are well matched by analytical estimates. These results lead to predict that there will be a maximum size of a 1D environment which can be retained in memory, and that the replay of spatial activity during sleep or quiet wakefulness will be for short segments of the environment.

• Padovani, P.; Giommi, P.; Falomo, R.; Oikonomou, Foteini; Petropoulou, M. & Glauch, T. [Show all 9 contributors for this article] (2022). The spectra of IceCube neutrino (SIN) candidate sources - II. Source characterization. Monthly notices of the Royal Astronomical Society. ISSN 0035-8711. 510(2), p. 2671–2688. doi: 10.1093/mnras/stab3630. Full text in Research Archive
• Spalla, Davide; Treves, Alessandro & Boccara, Charlotte (2022). Angular and linear speed cells in the parahippocampal circuits. Nature Communications. 13. doi: 10.1038/s41467-022-29583-z. Full text in Research Archive Show summary

  Abstract An essential role of the hippocampal region is to integrate information to compute and update representations. How this transpires is highly debated. Many theories hinge on the integration of self-motion signals and the existence of continuous attractor networks (CAN). CAN models hypothesise that neurons coding for navigational correlates – such as position and direction – receive inputs from cells conjunctively coding for position, direction, and self-motion. As yet, very little data exist on such conjunctive coding in the hippocampal region. Here, we report neurons coding for angular and linear velocity, uniformly distributed across the medial entorhinal cortex (MEC), the presubiculum and the parasubiculum, except for MEC layer II. Self-motion neurons often conjunctively encoded position and/or direction, yet lacked a structured organisation. These results offer insights as to how linear/angular speed – derivative in time of position/direction – may allow the updating of spatial representations, possibly uncovering a generalised algorithm to update any representation.

• Schönsberg, Francesca; Roudi, Yasser & Treves, Alessandro (2021). Efficiency of local learning rules in threshold-linear associative networks. Physical Review Letters. ISSN 0031-9007. 126(1), p. 1–5. doi: 10.1103/PhysRevLett.126.018301. Full text in Research Archive Show summary

  We derive the Gardner storage capacity for associative networks of threshold linear units, and show that with Hebbian learning they can operate closer to such Gardner bound than binary networks, and even surpass it. This is largely achieved through a sparsification of the retrieved patterns, which we analyze for theoretical and empirical distributions of activity. As reaching the optimal capacity via non-local learning rules like back-propagation requires slow and neurally implausible training procedures, our results indicate that one-shot self-organized Hebbian learning can be just as efficient.

• Ryom, Kwang Il; Boboeva, Vezha; Soldatkina, Oleksandra & Treves, Alessandro (2021). Latching dynamics as a basis for short-term recall. PLoS Computational Biology. ISSN 1553-734X. 17(9). doi: 10.1371/journal.pcbi.1008809. Full text in Research Archive Show summary

  We discuss simple models for the transient storage in short-term memory of cortical patterns of activity, all based on the notion that their recall exploits the natural tendency of the cortex to hop from state to state—latching dynamics. We show that in one such model, and in simple spatial memory tasks we have given to human subjects, short-term memory can be limited to similar low capacity by interference effects, in tasks terminated by errors, and can exhibit similar sublinear scaling, when errors are overlooked. The same mechanism can drive serial recall if combined with weak order-encoding plasticity. Finally, even when storing randomly correlated patterns of activity the network demonstrates correlation-driven latching waves, which are reflected at the outer extremes of pattern space.

• Fiedler, Judit; Leonibus, Elvira De & Treves, Alessandro (2021). Has the hippocampus really forgotten about space? Current Opinion in Neurobiology. ISSN 0959-4388. 71, p. 164–169. doi: 10.1016/j.conb.2021.11.009. Full text in Research Archive
• Kaya, Zeynep; Soltanipour, Mohammadreza & Treves, Alessandro (2020). Non-hexagonal neural dynamics in vowel space. AIMS Neuroscience. 7(3), p. 275–298. doi: 10.3934/NEUROSCIENCE.2020015. Full text in Research Archive
• Stella, Federico; Urdapilleta, Eugenio; Luo, Yifan & Treves, Alessandro (2019). Partial coherence and frustration in self-organizing spherical grids. Hippocampus. ISSN 1050-9631. doi: 10.1002/hipo.23144. Full text in Research Archive
• Naim, Michelangelo; Boboeva, Vezha; Kang, Chol Jun & Treves, Alessandro (2018). Reducing a cortical network to a Potts model yields storage capacity estimates. Journal of Statistical Mechanics: Theory and Experiment. 2018(4). doi: 10.1088/1742-5468/aab683. Full text in Research Archive
• Wernle, Tanja; Waaga, Torgeir; Mørreaunet, Maria; Treves, Alessandro; Moser, May-Britt & Moser, Edvard Ingjald (2018). Integration of grid maps in merged environments. Nature Neuroscience. ISSN 1097-6256. 21(1), p. 92–101. doi: 10.1038/s41593-017-0036-6. Full text in Research Archive Show summary

  Natural environments are represented by local maps of grid cells and place cells that are stitched together. The manner by which transitions between map fragments are generated is unknown. We recorded grid cells while rats were trained in two rectangular compartments, A and B (each 1 m × 2 m), separated by a wall. Once distinct grid maps were established in each environment, we removed the partition and allowed the rat to explore the merged environment (2 m × 2 m). The grid patterns were largely retained along the distal walls of the box. Nearer the former partition line, individual grid fields changed location, resulting almost immediately in local spatial periodicity and continuity between the two original maps. Grid cells belonging to the same grid module retained phase relationships during the transformation. Thus, when environments are merged, grid fields reorganize rapidly to establish spatial periodicity in the area where the environments meet.

• Boboeva, Vezha; Brasselet, Romain & Treves, Alessandro (2018). The capacity for correlated semantic memories in the cortex. Entropy. 20(11). doi: 10.3390/e20110824. Full text in Research Archive Show summary

  A statistical analysis of semantic memory should reflect the complex, multifactorial structure of the relations among its items. Still, a dominant paradigm in the study of semantic memory has been the idea that the mental representation of concepts is structured along a simple branching tree spanned by superordinate and subordinate categories. We propose a generative model of item representation with correlations that overcomes the limitations of a tree structure. The items are generated through “factors” that represent semantic features or real-world attributes. The correlation between items has its source in the extent to which items share such factors and the strength of such factors: if many factors are balanced, correlations are overall low; whereas if a few factors dominate, they become strong. Our model allows for correlations that are neither trivial nor hierarchical, but may reproduce the general spectrum of correlations present in a dataset of nouns. We find that such correlations reduce the storage capacity of a Potts network to a limited extent, so that the number of concepts that can be stored and retrieved in a large, human-scale cortical network may still be of order 107, as originally estimated without correlations. When this storage capacity is exceeded, however, retrieval fails completely only for balanced factors; above a critical degree of imbalance, a phase transition leads to a regime where the network still extracts considerable information about the cued item, even if not recovering its detailed representation: partial categorization seems to emerge spontaneously as a consequence of the dominance of particular factors, rather than being imposed ad hoc. We argue this to be a relevant model of semantic memory resilience in Tulving’s remember/know paradigms.

• Kang, Chol Jun; Naim, Michelangelo; Boboeva, Vezha & Treves, Alessandro (2017). Life on the edge: Latching dynamics in a Potts neural network. Entropy. 19(9). doi: 10.3390/e19090468. Full text in Research Archive Show summary

  We study latching dynamics in the adaptive Potts model network, through numerical simulations with randomly and also weakly correlated patterns, and we focus on comparing its slowly and fast adapting regimes. A measure, Q, is used to quantify the quality of latching in the phase space spanned by the number of Potts states S, the number of connections per Potts unit C and the number of stored memory patterns p. We find narrow regions, or bands in phase space, where distinct pattern retrieval and duration of latching combine to yield the highest values of Q. The bands are confined by the storage capacity curve, for large p, and by the onset of finite latching, for low p. Inside the band, in the slowly adapting regime, we observe complex structured dynamics, with transitions at high crossover between correlated memory patterns; while away from the band latching, transitions lose complexity in different ways: below, they are clear-cut but last such few steps as to span a transition matrix between states with few asymmetrical entries and limited entropy; while above, they tend to become random, with large entropy and bi-directional transition frequencies, but indistinguishable from noise. Extrapolating from the simulations, the band appears to scale almost quadratically in the p–S plane, and sublinearly in p–C. In the fast adapting regime, the band scales similarly, and it can be made even wider and more robust, but transitions between anti-correlated patterns dominate latching dynamics. This suggest that slow and fast adaptation have to be integrated in a scenario for viable latching in a cortical system. The results for the slowly adapting regime, obtained with randomly correlated patterns, remain valid also for the case with correlated patterns, with just a simple shift in phase space.

• Alme, Charlotte; Miao, Chenglin; Jezek, Karel; Treves, Alessandro; Moser, Edvard Ingjald & Moser, May-Britt (2014). Place cells in the hippocampus: Eleven maps for eleven rooms. Proceedings of the National Academy of Sciences of the United States of America (PNAS). ISSN 0027-8424. 111(52), p. 18428–18435. doi: 10.1073/pnas.1421056111. Full text in Research Archive Show summary

  The contribution of hippocampal circuits to high-capacity episodic memory is often attributed to the large number of orthogonal activity patterns that may be stored in these networks. Evidence for high-capacity storage in the hippocampus is missing, however. When animals are tested in pairs of environments, different combinations of place cells are recruited, consistent with the notion of independent representations. However, the extent to which representations remain independent across larger numbers of environments has not been determined. To investigate whether spatial firing patterns recur when animals are exposed to multiple environments, we tested rats in 11 recording boxes, each in a different room, allowing for 55 comparisons of place maps in each animal. In each environment, activity was recorded from neuronal ensembles in hippocampal area CA3, with an average of 30 active cells per animal. Representations were highly correlated between repeated tests in the same room but remained orthogonal across all combinations of different rooms, with minimal overlap in the active cell samples from each environment. A low proportion of cells had activity in many rooms but the firing locations of these cells were completely uncorrelated. Taken together, the results suggest that the number of independent spatial representations stored in hippocampal area CA3 is large, with minimal recurrence of spatial firing patterns across environments.

• Si, Bailu & Treves, Alessandro (2013). A Model for the Differentiation Between Grid and Conjunctive Units in Medial Entorhinal Cortex. Hippocampus. ISSN 1050-9631. 23(12), p. 1410–1424. doi: 10.1002/hipo.22194. Full text in Research Archive
• Cerasti, Erika & Treves, Alessandro (2013). The spatial representations acquired in CA3 by self-organizing recurrent connections. Frontiers in Cellular Neuroscience. 7. doi: 10.3389/fncel.2013.00112. Full text in Research Archive Show summary

  Neural computation models have hypothesized that the dentate gyrus (DG) drives the storage in the CA3 network of new memories including, e.g., in rodents, spatial memories. Can recurrent CA3 connections self-organize, during storage, and form what have been called continuous attractors, or charts-so that they express spatial information later, when aside from a partial cue the information may not be available in the inputs? We use a simplified mathematical network model to contrast the properties of spatial representations self-organized through simulated Hebbian plasticity with those of charts pre-wired in the synaptic matrix, a control case closer to the ideal notion of continuous attractors. Both models form granular quasi-attractors, characterized by drift, which approach continuous ones only in the limit of an infinitely large network. The two models are comparable in terms of precision, but not of accuracy: with self-organized connections, the metric of space remains distorted, ill-adequate for accurate path integration, even when scaled up to the real hippocampus. While prolonged self-organization makes charts somewhat more informative about position in the environment, some positional information is surprisingly present also about environments never learned, borrowed, as it were, from unrelated charts. In contrast, context discrimination decreases with more learning, as different charts tend to collapse onto each other. These observations challenge the feasibility of the idealized CA3 continuous chart concept, and are consistent with a CA3 specialization for episodic memory rather than path integration.

• Stella, Federico; Cerasti, Erika; Si, Bailu; Jezek, Karel & Treves, Alessandro (2012). Self-organization of multiple spatial and context memories in the hippocampus. Neuroscience and Biobehavioral Reviews. ISSN 0149-7634. 36(7), p. 1609–1625. doi: 10.1016/j.neubiorev.2011.12.002. Full text in Research Archive
• Si, Bailu; Kropff, Emilio & Treves, Alessandro (2012). Grid alignment in entorhinal cortex. Biological cybernetics. ISSN 0340-1200. 106(8-9), p. 483–506. doi: 10.1007/s00422-012-0513-7. Full text in Research Archive
• Rolls, ET & Treves, Alessandro (2011). The neuronal encoding of information in the brain. Progress in Neurobiology. ISSN 0301-0082. 95(3), p. 448–490. doi: 10.1016/j.pneurobio.2011.08.002. Full text in Research Archive
• Jezek, Karel; Henriksen, Espen Joakim; Treves, Alessandro; Moser, Edvard Ingjald & Moser, May-Britt (2011). Theta-paced flickering between place-cell maps in the hippocampus. Nature. ISSN 0028-0836. 478(7368), p. 246–U136. doi: 10.1038/nature10439. Full text in Research Archive
• Aleksic, J; Alvarez, EA; Antonelli, LA; Antoranz, P; Asensio, M & Backes, M [Show all 158 contributors for this article] (2011). OBSERVATIONS OF THE CRAB PULSAR BETWEEN 25 AND 100 GeV WITH THE MAGIC I TELESCOPE. The Astrophysical Journal (ApJ). ISSN 0004-637X. 742(1). doi: 10.1088/0004-637X/742/1/43. Full text in Research Archive
• Stella, F. & Treves, Alessandro (2011). Associative Memory Storage and Retrieval: Involvement of Theta Oscillations in Hippocampal Information Processing. Journal of Neural Plasticity. ISSN 0792-8483. doi: 10.1155/2011/683961. Full text in Research Archive
• Cerasti, E & Treves, Alessandro (2010). How Informative Are Spatial CA3 Representations Established by the Dentate Gyrus? PLoS Computational Biology. ISSN 1553-734X. 6(4). doi: 10.1371/journal.pcbi.1000759. Full text in Research Archive
• Si, Bailu & Treves, Alessandro (2009). The role of competitive learning in the generation of DG fields from EC inputs. Cognitive Neurodynamics. ISSN 1871-4080. 3(2), p. 177–187. doi: 10.1007/s11571-009-9079-z. Full text in Research Archive
• Roudi, Y & Treves, Alessandro (2008). Representing Where along with What information in a model of a cortical patch. PLoS Computational Biology. ISSN 1553-734X. 4. doi: 10.1371/journal.pcbi.1000012. Full text in Research Archive
• Treves, Alessandro; Tashiro, Ayumu; Witter, Menno & Moser, Edvard Ingjald (2008). What is the mammalian dentate gyrus good for? Neuroscience. ISSN 0306-4522. 154, p. 1155–1172. doi: 10.1016/j.neuroscience.2008.04.073. Full text in Research Archive
• Kropff, Emilio & Treves, Alessandro (2008). The Emergence of Grid Cells: Intelligent Design or Just Adaptation? Hippocampus. ISSN 1050-9631. 18(12), p. 1256–1269. doi: 10.1002/hipo.20520. Full text in Research Archive
• Fyhn, Marianne; Hafting, Torkel; Treves, Alessandro; Moser, May-Britt & Moser, Edvard Ingjald (2007). Hippocampal remapping and grid realignment in entorhinal cortex. Nature. ISSN 0028-0836. 446. doi: 10.1038/nature05601. Full text in Research Archive
• Lauro-Grotto, Rosapia; Ciaramelli, Elisa; Piccini, Carolina & Treves, Alessandro (2007). Differential impact of brain damage on the access mode to memory representations: an information theoretic approach. European Journal of Neuroscience. ISSN 0953-816X. 26. doi: 10.1111/j.1460-9568.2007.05881.x. Full text in Research Archive
• Papp, G; Witter, Menno & Treves, A (2007). The CA3 network as a memory store for spatial representations. Learning & memory (Cold Spring Harbor, N.Y.). ISSN 1072-0502. 14, p. 732–744. doi: 10.1101/lm.687407. Full text in Research Archive
• Roudi, Y & Treves, Alessandro (2006). Localized activity profiles and storage capacity of rate-based autoassociative networks. Physical Review E. Statistical, Nonlinear, and Soft Matter Physics. ISSN 1539-3755. 73. doi: 10.1103/PhysRevE.73.061904. Full text in Research Archive
• Ciaramelli, Elisa; Lauro-Grotto, Rosapia & Treves, Alessandro (2006). Dissociating episodic from semantic access mode by mutual information measures: Evidence from aging and Alzheimer's disease. Journal of Physiology - Paris. ISSN 0928-4257. 100, p. 142–153. Full text in Research Archive
• Treves, Alessandro (2005). Frontal latching networks: A possible neural basis for infinite recursion. Cognitive Neuropsychology. ISSN 0264-3294. 22. Full text in Research Archive
• Leutgeb, Jill Kristin; Leutgeb, Stefan; Treves, Alessandro; Meyer, R.; Barnes, Carol & McNaughton, Bruce [Show all 8 contributors for this article] (2005). Progressive transformation of hippocampal neuronal representations in "morphed" environments. Neuron. ISSN 0896-6273. 20, p. 345–358. Full text in Research Archive
• Leutgeb, Stefan; Leutgeb, Jill Kristin; Treves, Alessandro; Moser, May-Britt & Moser, Edvard Ingjald (2004). Distinct ensemble codes in hippocampal areas CA3 and CA1. Science. ISSN 0036-8075. 305, p. 1295–1298. Full text in Research Archive
• Treves, Alessandro (2004). Computational constraints between retrieving the past and predicting the future, and the CA3-CA1 differentiation. Hippocampus. ISSN 1050-9631. 14, p. 539–556. Full text in Research Archive
• Treves, Alessandro (2004). Neural phase transitions that made us mammals. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 3146, p. 55–70. Full text in Research Archive

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• Stella, Federico; Si, Bailu; Kropff, Emilio & Treves, Alessandro (2013). Grid maps for spaceflight, anyone? They are for free! Behavioral and Brain Sciences. ISSN 0140-525X. 36(5), p. 566–567. doi: 10.1017/S0140525X13000575. Full text in Research Archive
• Alme, Charlotte; Miao, Chenglin; Jezek, Karel; Treves, Alessandro; Moser, Edvard Ingjald & Moser, May-Britt (2013). Independent place-cell maps for 10 environments with overlapping properties. Full text in Research Archive Show summary

  The contribution of hippocampal circuits to high-capacity episodic memory is often attributed to the large number of orthogonal activity patterns that may be stored in these networks. When rodents explore an environment for the first time, a new combination of active place cells is recruited which appears different from maps of already familiar environments. The orthogonality of the representations is thought to minimize interference between memories for experiences with overlapping spatial elements and to allow large numbers of experiences to be stored in the same network. This view is challenged, however, by the recent observation that firing patterns in a novel environment correlate with activity patterns recorded in the resting state before the animal entered the environment for the first time (Dragoi and Tonegawa, 2011). Instead the presence of experience-independent firing sequences points to the hippocampus as a preconfigured network from which sequence information is recruited repeatedly across environments and experiences (McNaughton et al., 1996). To test this possibility, we measured the relatedness of hippocampal representations in 10 sequentially presented test rooms, allowing for 45 map comparisons - many more than in any previous work. Five new environments were presented on each of 2 consecutive days. A familiar room was presented at the beginning and the end of each experimental day to test for stability. On each trial, activity was recorded from large ensembles of neurons in hippocampal area CA3, with an average of approximately 30 active cells per trial. Population vectors were defined to correlate cell populations within and across all 11 rooms (novel and familiar). Representations were highly correlated between repeated tests in the same room but nearly orthogonal across all combinations of different rooms, indicating that unique representations were initially expressed in each environment, despite the similarity of the rooms. The results suggest that the mnemonic capacity of the hippocampal CA3 spatial-mapping network is large, with minimal recurrence of firing patterns across environments.

• Stella, F. & Treves, Alessandro (2012). CA1 contribution to mapping space in the hippocampus. Journal of Molecular Neuroscience. ISSN 0895-8696. 48, p. S113–S114. Full text in Research Archive
• Jezek, Karel; Treves, Alessandro; Moser, May-Britt & Moser, Edvard Ingjald (2010). Single theta cycle-based pattern completion in hippocampal CA3. Society for Neuroscience : Abstracts. Full text in Research Archive
• Jezek, Karel; Treves, Alessandro; Moser, May-Britt & Moser, Edvard Ingjald (2010). Single theta cycle-based pattern completion in hippocampal CA3. Full text in Research Archive
• Jezek, Karel; Colgin, Laura Lee; Treves, Alessandro; Moser, May-Britt & Moser, Edvard Ingjald (2009). EEG changes in hippocampus in response to transitions between CA3 attractor states. Full text in Research Archive
• Fyhn, Marianne; Hafting, Torkel; Treves, Alessandro; Moser, Edvard Ingjald & Moser, May-Britt (2006). Coherence in ensembles of entorhinal grid cells. Full text in Research Archive
• Hafting, Torkel; Fyhn, Marianne; Treves, Alessandro; Moser, Edvard Ingjald & Moser, May-Britt (2006). Coherent realignment of entorhinal grid cells coincides global remapping in the hippocampus. Full text in Research Archive
• Fyhn, Marianne; Hafting, T; Treves, Alessandro; Moser, May-Britt & Moser, Edvard Ingjald (2005). Preserved spatial and temporar firing structure in entorhinal grid cells during remapping in the hippocampus. Abstracts - Society for Neuroscience. ISSN 0190-5295. p. 198.6.–198.6.. Full text in Research Archive
• Leutgeb, Jill Kristin; Leutgeb, Stefan; Treves, Alessandro; Fyhn, Marianne; Meyer, R. & Barnes, Carol [Show all 9 contributors for this article] (2004). Pattern completion and pattern separation in CA3 during morphing of two enviroments. Society for Neuroscience : Abstracts. 30. Full text in Research Archive
• Papp, G.; Roudi, Y.; Leutgeb, Stefan; Leutgeb, Jill Kristin; Moser, May-Britt & Moser, Edvard Ingjald [Show all 7 contributors for this article] (2004). Computational significance of differentiating CA1 from CA3. Society for Neuroscience : Abstracts. 30. Full text in Research Archive
• Leutgeb, Stefan; Leutgeb, Jill Kristin; Treves, Alessandro; Moser, May-Britt & Moser, Edvard Ingjald (2004). Fast orthogonalixation of ensemble codes in CA3 but not CA1. Society for Neuroscience : Abstracts. 30. Full text in Research Archive
• Fyhn, Marianne; Fyhn, Torkel Hafting; Treves, Alessandro; Moser, May-Britt & Moser, Edvard Ingjald (2004). Pattern separation in hippocampus but not layers II and III of entorhinal cortex. Society for Neuroscience : Abstracts. 30. Full text in Research Archive
• Leutgeb, S; Kjelstrup, Kirsten Gjerstad; Treves, A; Moser, May-Britt & Moser, Edvard Ingjald (2003). DIFFERENTIAL REPRESENTATION OF CONTEXT IN HIPPOCAMPAL AREAS CA3 AND CA1. Full text in Research Archive

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