@article{19453, abstract = {A key feature of biological and artificial neural networks is the progressive refinement of their neural representations with experience. In neuroscience, this fact has inspired several recent studies in sensory and motor systems. However, less is known about how higher associational cortical areas, such as the hippocampus, modify representations throughout the learning of complex tasks. Here, we focus on associative learning, a process that requires forming a connection between the representations of different variables for appropriate behavioral response. We trained rats in a space-context associative task and monitored hippocampal neural activity throughout the entire learning period, over several days. This allowed us to assess changes in the representations of context, movement direction, and position, as well as their relationship to behavior. We identified a hierarchical representational structure in the encoding of these three task variables that was preserved throughout learning. Nevertheless, we also observed changes at the lower levels of the hierarchy where context was encoded. These changes were local in neural activity space and restricted to physical positions where context identification was necessary for correct decision-making, supporting better context decoding and contextual code compression. Our results demonstrate that the hippocampal code not only accommodates hierarchical relationships between different variables but also enables efficient learning through minimal changes in neural activity space. Beyond the hippocampus, our work reveals a representation learning mechanism that might be implemented in other biological and artificial networks performing similar tasks.}, author = {Chiossi, Heloisa and Nardin, Michele and Tkačik, Gašper and Csicsvari, Jozsef L}, issn = {1091-6490}, journal = {Proceedings of the National Academy of Sciences}, number = {11}, publisher = {National Academy of Sciences}, title = {{Learning reshapes the hippocampal representation hierarchy}}, doi = {10.1073/pnas.2417025122}, volume = {122}, year = {2025}, } @article{15381, abstract = {Cholecystokinin-expressing interneurons (CCKIs) are hypothesized to shape pyramidal cell-firing patterns and regulate network oscillations and related network state transitions. To directly probe their role in the CA1 region, we silenced their activity using optogenetic and chemogenetic tools in mice. Opto-tagged CCKIs revealed a heterogeneous population, and their optogenetic silencing triggered wide disinhibitory network changes affecting both pyramidal cells and other interneurons. CCKI silencing enhanced pyramidal cell burst firing and altered the temporal coding of place cells: theta phase precession was disrupted, whereas sequence reactivation was enhanced. Chemogenetic CCKI silencing did not alter the acquisition of spatial reference memories on the Morris water maze but enhanced the recall of contextual fear memories and enabled selective recall when similar environments were tested. This work suggests the key involvement of CCKIs in the control of place-cell temporal coding and the formation of contextual memories.}, author = {Rangel Guerrero, Dámaris K and Balueva, Kira and Barayeu, Uladzislau and Baracskay, Peter and Gridchyn, Igor and Nardin, Michele and Roth, Chiara N and Wulff, Peer and Csicsvari, Jozsef L}, issn = {1097-4199}, journal = {Neuron}, number = {12}, pages = {2045--2061.e10}, publisher = {Cell Press}, title = {{Hippocampal cholecystokinin-expressing interneurons regulate temporal coding and contextual learning}}, doi = {10.1016/j.neuron.2024.03.019}, volume = {112}, year = {2024}, } @article{14314, abstract = {The execution of cognitive functions requires coordinated circuit activity across different brain areas that involves the associated firing of neuronal assemblies. Here, we tested the circuit mechanism behind assembly interactions between the hippocampus and the medial prefrontal cortex (mPFC) of adult rats by recording neuronal populations during a rule-switching task. We identified functionally coupled CA1-mPFC cells that synchronized their activity beyond that expected from common spatial coding or oscillatory firing. When such cell pairs fired together, the mPFC cell strongly phase locked to CA1 theta oscillations and maintained consistent theta firing phases, independent of the theta timing of their CA1 counterpart. These functionally connected CA1-mPFC cells formed interconnected assemblies. While firing together with their CA1 assembly partners, mPFC cells fired along specific theta sequences. Our results suggest that upregulated theta oscillatory firing of mPFC cells can signal transient interactions with specific CA1 assemblies, thus enabling distributed computations.}, author = {Nardin, Michele and Käfer, Karola and Stella, Federico and Csicsvari, Jozsef L}, issn = {2211-1247}, journal = {Cell Reports}, number = {9}, publisher = {Elsevier}, title = {{Theta oscillations as a substrate for medial prefrontal-hippocampal assembly interactions}}, doi = {10.1016/j.celrep.2023.113015}, volume = {42}, year = {2023}, } @article{14656, abstract = {Although much is known about how single neurons in the hippocampus represent an animal's position, how circuit interactions contribute to spatial coding is less well understood. Using a novel statistical estimator and theoretical modeling, both developed in the framework of maximum entropy models, we reveal highly structured CA1 cell-cell interactions in male rats during open field exploration. The statistics of these interactions depend on whether the animal is in a familiar or novel environment. In both conditions the circuit interactions optimize the encoding of spatial information, but for regimes that differ in the informativeness of their spatial inputs. This structure facilitates linear decodability, making the information easy to read out by downstream circuits. Overall, our findings suggest that the efficient coding hypothesis is not only applicable to individual neuron properties in the sensory periphery, but also to neural interactions in the central brain.}, author = {Nardin, Michele and Csicsvari, Jozsef L and Tkačik, Gašper and Savin, Cristina}, issn = {1529-2401}, journal = {The Journal of Neuroscience}, number = {48}, pages = {8140--8156}, publisher = {Society for Neuroscience}, title = {{The structure of hippocampal CA1 interactions optimizes spatial coding across experience}}, doi = {10.1523/JNEUROSCI.0194-23.2023}, volume = {43}, year = {2023}, } @phdthesis{11932, abstract = {The ability to form and retrieve memories is central to survival. In mammals, the hippocampus is a brain region essential to the acquisition and consolidation of new memories. It is also involved in keeping track of one’s position in space and aids navigation. Although this space-memory has been a source of contradiction, evidence supports the view that the role of the hippocampus in navigation is memory, thanks to the formation of cognitive maps. First introduced by Tolman in 1948, cognitive maps are generally used to organize experiences in memory; however, the detailed mechanisms by which these maps are formed and stored are not yet agreed upon. Some influential theories describe this process as involving three fundamental steps: initial encoding by the hippocampus, interactions between the hippocampus and other cortical areas, and long-term extra-hippocampal consolidation. In this thesis, I will show how the investigation of cognitive maps of space helped to shed light on each of these three memory processes. The first study included in this thesis deals with the initial encoding of spatial memories in the hippocampus. Much is known about encoding at the level of single cells, but less about their co-activity or joint contribution to the encoding of novel spatial information. I will describe the structure of an interaction network that allows for efficient encoding of noisy spatial information during the first exploration of a novel environment. The second study describes the interactions between the hippocampus and the prefrontal cortex (PFC), two areas directly and indirectly connected. It is known that the PFC, in concert with the hippocampus, is involved in various processes, including memory storage and spatial navigation. Nonetheless, the detailed mechanisms by which PFC receives information from the hippocampus are not clear. I will show how a transient improvement in theta phase locking of PFC cells enables interactions of cell pairs across the two regions. The third study describes the learning of behaviorally-relevant spatial locations in the hippocampus and the medial entorhinal cortex. I will show how the accumulation of firing around goal locations, a correlate of learning, can shed light on the transition from short- to long-term spatial memories and the speed of consolidation in different brain areas. The studies included in this thesis represent the main scientific contributions of my Ph.D. They involve statistical analyses and models of neural responses of cells in different brain areas of rats executing spatial tasks. I will conclude the thesis by discussing the impact of the findings on principles of memory formation and retention, including the mechanisms, the speed, and the duration of these processes.}, author = {Nardin, Michele}, issn = {2663-337X}, pages = {136}, publisher = {Institute of Science and Technology Austria}, title = {{On the encoding, transfer, and consolidation of spatial memories}}, doi = {10.15479/at:ista:11932}, year = {2022}, } @article{10635, abstract = {The brain efficiently performs nonlinear computations through its intricate networks of spiking neurons, but how this is done remains elusive. While nonlinear computations can be implemented successfully in spiking neural networks, this requires supervised training and the resulting connectivity can be hard to interpret. In contrast, the required connectivity for any computation in the form of a linear dynamical system can be directly derived and understood with the spike coding network (SCN) framework. These networks also have biologically realistic activity patterns and are highly robust to cell death. Here we extend the SCN framework to directly implement any polynomial dynamical system, without the need for training. This results in networks requiring a mix of synapse types (fast, slow, and multiplicative), which we term multiplicative spike coding networks (mSCNs). Using mSCNs, we demonstrate how to directly derive the required connectivity for several nonlinear dynamical systems. We also show how to carry out higher-order polynomials with coupled networks that use only pair-wise multiplicative synapses, and provide expected numbers of connections for each synapse type. Overall, our work demonstrates a novel method for implementing nonlinear computations in spiking neural networks, while keeping the attractive features of standard SCNs (robustness, realistic activity patterns, and interpretable connectivity). Finally, we discuss the biological plausibility of our approach, and how the high accuracy and robustness of the approach may be of interest for neuromorphic computing.}, author = {Nardin, Michele and Phillips, James W. and Podlaski, William F. and Keemink, Sander W.}, issn = {2804-3871}, journal = {Peer Community Journal}, publisher = {Peer Community In}, title = {{Nonlinear computations in spiking neural networks through multiplicative synapses}}, doi = {10.24072/pcjournal.69}, volume = {1}, year = {2021}, } @unpublished{10080, abstract = {Hippocampal and neocortical neural activity is modulated by the position of the individual in space. While hippocampal neurons provide the basis for a spatial map, prefrontal cortical neurons generalize over environmental features. Whether these generalized representations result from a bidirectional interaction with, or are mainly derived from hippocampal spatial representations is not known. By examining simultaneously recorded hippocampal and medial prefrontal neurons, we observed that prefrontal spatial representations show a delayed coherence with hippocampal ones. We also identified subpopulations of cells in the hippocampus and medial prefrontal cortex that formed functional cross-area couplings; these resembled the optimal connections predicted by a probabilistic model of spatial information transfer and generalization. Moreover, cross-area couplings were strongest and had the shortest delay preceding spatial decision-making. Our results suggest that generalized spatial coding in the medial prefrontal cortex is inherited from spatial representations in the hippocampus, and that the routing of information can change dynamically with behavioral demands.}, author = {Nardin, Michele and Käfer, Karola and Csicsvari, Jozsef L}, booktitle = {bioRxiv}, publisher = {Cold Spring Harbor Laboratory}, title = {{The generalized spatial representation in the prefrontal cortex is inherited from the hippocampus}}, doi = {10.1101/2021.09.30.462269}, year = {2021}, } @unpublished{10077, abstract = {Although much is known about how single neurons in the hippocampus represent an animal’s position, how cell-cell interactions contribute to spatial coding remains poorly understood. Using a novel statistical estimator and theoretical modeling, both developed in the framework of maximum entropy models, we reveal highly structured cell-to-cell interactions whose statistics depend on familiar vs. novel environment. In both conditions the circuit interactions optimize the encoding of spatial information, but for regimes that differ in the signal-to-noise ratio of their spatial inputs. Moreover, the topology of the interactions facilitates linear decodability, making the information easy to read out by downstream circuits. These findings suggest that the efficient coding hypothesis is not applicable only to individual neuron properties in the sensory periphery, but also to neural interactions in the central brain.}, author = {Nardin, Michele and Csicsvari, Jozsef L and Tkačik, Gašper and Savin, Cristina}, booktitle = {bioRxiv}, publisher = {Cold Spring Harbor Laboratory}, title = {{The structure of hippocampal CA1 interactions optimizes spatial coding across experience}}, doi = {10.1101/2021.09.28.460602}, year = {2021}, } @article{7472, abstract = {Temporally organized reactivation of experiences during awake immobility periods is thought to underlie cognitive processes like planning and evaluation. While replay of trajectories is well established for the hippocampus, it is unclear whether the medial prefrontal cortex (mPFC) can reactivate sequential behavioral experiences in the awake state to support task execution. We simultaneously recorded from hippocampal and mPFC principal neurons in rats performing a mPFC-dependent rule-switching task on a plus maze. We found that mPFC neuronal activity encoded relative positions between the start and goal. During awake immobility periods, the mPFC replayed temporally organized sequences of these generalized positions, resembling entire spatial trajectories. The occurrence of mPFC trajectory replay positively correlated with rule-switching performance. However, hippocampal and mPFC trajectory replay occurred independently, indicating different functions. These results demonstrate that the mPFC can replay ordered activity patterns representing generalized locations and suggest that mPFC replay might have a role in flexible behavior.}, author = {Käfer, Karola and Nardin, Michele and Blahna, Karel and Csicsvari, Jozsef L}, issn = {0896-6273}, journal = {Neuron}, number = {1}, pages = {P154--165.e6}, publisher = {Elsevier}, title = {{Replay of behavioral sequences in the medial prefrontal cortex during rule switching}}, doi = {10.1016/j.neuron.2020.01.015}, volume = {106}, year = {2020}, } @misc{6062, abstract = {Open the files in Jupyter Notebook (reccomended https://www.anaconda.com/distribution/#download-section with Python 3.7).}, author = {Nardin, Michele}, publisher = {Institute of Science and Technology Austria}, title = {{Supplementary Code and Data for the paper "The Entorhinal Cognitive Map is Attracted to Goals"}}, doi = {10.15479/AT:ISTA:6062}, year = {2019}, } @article{6194, abstract = {Grid cells with their rigid hexagonal firing fields are thought to provide an invariant metric to the hippocampal cognitive map, yet environmental geometrical features have recently been shown to distort the grid structure. Given that the hippocampal role goes beyond space, we tested the influence of nonspatial information on the grid organization. We trained rats to daily learn three new reward locations on a cheeseboard maze while recording from the medial entorhinal cortex and the hippocampal CA1 region. Many grid fields moved toward goal location, leading to long-lasting deformations of the entorhinal map. Therefore, distortions in the grid structure contribute to goal representation during both learning and recall, which demonstrates that grid cells participate in mnemonic coding and do not merely provide a simple metric of space.}, author = {Boccara, Charlotte N. and Nardin, Michele and Stella, Federico and O'Neill, Joseph and Csicsvari, Jozsef L}, issn = {1095-9203}, journal = {Science}, number = {6434}, pages = {1443--1447}, publisher = {American Association for the Advancement of Science}, title = {{The entorhinal cognitive map is attracted to goals}}, doi = {10.1126/science.aav4837}, volume = {363}, year = {2019}, }