@article{21473, abstract = {Physical exercise acutely improves hippocampus-dependent memory. Whereas animal studies have offered cellular- and synaptic-level accounts of these effects, human neuroimaging studies show that exercise improves hippocampal-cortical connectivity at the macroscale level. However, the neurophysiological basis of exercise-induced effects on hippocampal-cortical circuits remains unknown. Experimental evidence supports the idea that hippocampal sharp wave-ripples (SWR) play a critical role in learning and memory. Coupling between SWRs in the hippocampus and neocortex may reflect modulations in inter-regional connectivity required by mnemonic processes. Here, we examine the hypothesis that exercise modulates hippocampal-cortical ripple dynamics in the human brain. We performed intracranial recordings in epilepsy patients undergoing pre-surgical evaluation, during awake resting state, before and after an exercise session. Exercise increased ripple rate in the hippocampus. Exercise also enhanced the coupling and phase-synchrony between cortical ripples in the limbic and the default mode (DM) cortical networks and hippocampal SWRs. Further, a higher heart rate during exercise, reflecting exercise intensity, was related to a subsequent increase in resting state ripples across specific cortical networks, including the DM network. These results offer the first direct evidence that a single exercise session elicits changes in ripple events, a well-established neurophysiological marker of mnemonic processing. The characterisation and anatomical distribution of the described modulation points to hippocampal ripples as a potential mechanism by which exercise elicits its reported short-term effects in cognition.}, author = {Cardenas, Araceli R. and Ramirez Villegas, Juan F and Kovach, Christopher K. and Gander, Phillip E. and Cole, Rachel C. and Grossbach, Andrew J. and Kawasaki, Hiroto and Greenlee, Jeremy D.W. and Howard, Matthew A. and Nourski, Kirill V. and Banks, Matthew I. and Voss, Michelle W.}, issn = {2632-1297}, journal = {Brain Communications}, number = {2}, publisher = {Oxford University Press}, title = {{Exercise enhances hippocampal-cortical ripple interactions in the human brain}}, doi = {10.1093/braincomms/fcag041}, volume = {8}, year = {2026}, } @misc{18991, abstract = {Research data for the article "Learning reshapes the hippocampal representation hierarchy" from Chiossi et al. (PNAS, 2025). The data includes hippocampal CA1 unit activity and behaviour tracking of 5 Long Evans rats during the learning of an associative memory task. Detailed information can be found in the 'readme.txt' file.}, author = {Chiossi, Heloisa}, keywords = {hippocampus, electrophysiology, behavior}, publisher = {Institute of Science and Technology Austria}, title = {{Research data for the publication "Learning reshapes the hippocampal representation hierarchy"}}, doi = {10.15479/AT:ISTA:18991}, year = {2025}, } @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}, } @phdthesis{20777, author = {Zivadinovic, Predrag}, issn = {2663-337X}, pages = {104}, publisher = {Institute of Science and Technology Austria}, title = {{Scale-free activity as a basis for spatial learning and memory in the brain}}, doi = {10.15479/AT-ISTA-20777}, year = {2025}, } @article{20664, abstract = {Conference travel contributes to the climate footprint of academic research. Here, we provide a quantitative estimate of the carbon emissions associated with conference attendance by analyzing travel data from participants of 10 international conferences in the field of magnetic resonance, namely EUROMAR, ENC and ICMRBS. We find that attending a EUROMAR conference produces, on average, more than 1 t CO2 eq.. For the analyzed conferences outside Europe, the corresponding value is about 2–3 times higher, on average, with intercontinental trips amounting to up to 5 t. We compare these conference-related emissions to other activities associated with research and show that conference travel is a substantial portion of the total climate footprint of a researcher in magnetic resonance. We explore several strategies to reduce these emissions, including the impact of selecting conference venues more strategically and the possibility of decentralized conferences. Through a detailed comparison of train versus air travel – accounting for both direct and infrastructure-related emissions – we demonstrate that train travel offers considerable carbon savings. These data may provide a basis for strategic choices of future conferences in the field and for individuals deciding on their conference attendance.}, author = {Kapoor, Lucky and Ruzickova, Natalia and Zivadinovic, Predrag and Leitner, Valentin and Sisak, Maria A and Mweka, Cecelia N and Dobbelaere, Jeroen A and Katsaros, Georgios and Schanda, Paul}, issn = {2699-0016}, journal = {Magnetic Resonance}, number = {2}, pages = {243--256}, publisher = {Copernicus Publications}, title = {{Quantifying the carbon footprint of conference travel: The case of NMR meetings}}, doi = {10.5194/mr-6-243-2025}, volume = {6}, year = {2025}, } @article{19506, abstract = {Hippocampal reactivation of waking neuronal assemblies in sleep is a key initial step of systems consolidation. Nevertheless, it is unclear whether reactivated assemblies are static or whether they reorganize gradually over prolonged sleep. We tracked reactivated CA1 assembly patterns over ∼20 h of sleep/rest periods and related them to assemblies seen before or after in a spatial learning paradigm using rats. We found that reactivated assembly patterns were gradually transformed and started to resemble those seen in the subsequent recall session. Periods of rapid eye movement (REM) sleep and non-REM (NREM) had antagonistic roles: whereas NREM accelerated the assembly drift, REM countered it. Moreover, only a subset of rate-changing pyramidal cells contributed to the drift, whereas stable-firing-rate cells maintained unaltered reactivation patterns. Our data suggest that prolonged sleep promotes the spontaneous reorganization of spatial assemblies, which can contribute to daily cognitive map changes or encoding new learning situations.}, author = {Bollmann, Lars and Baracskay, Peter and Stella, Federico and Csicsvari, Jozsef L}, issn = {1097-4199}, journal = {Neuron}, number = {9}, pages = {1446--1459.e6}, publisher = {Elsevier}, title = {{Sleep stages antagonistically modulate reactivation drift}}, doi = {10.1016/j.neuron.2025.02.025}, volume = {113}, year = {2025}, } @phdthesis{19456, abstract = {Making decisions requires flexibly adapting to changing environments, a process that depends on accurately interpreting current contingencies and integrating them with past experience. Two brain regions are particularly critical for this process, the medial prefrontal cortex (mPFC) and the hippocampus. Using contextual information from the hippocampus, the mPFC selects relevant cognitive frameworks and suppresses irrelevant ones to guide appropriate actions. Several studies have shown that some mPFC pyramidal neurons become spatially tuned when spatial information is required to guide goal-directed behavior. However, the role of prefrontal spatial representations in learning and decision making is not well understood. This work aims to characterize the role of mPFC spatial tuning in supporting a contextual association task. Rats were trained to learn two cue–location associations on a radial arm maze over multiple days, while we simultaneously recorded from dorsal CA1 of the hippocampus and the prelimbic area of the mPFC. We describe a subset of spatially tuned hippocampal and prefrontal pyramidal neurons that “flicker” between multiple spatial representations on different trials, suggesting dynamic, context-dependent coding. This flickering may provide a substrate for how the network reorganizes in response to task demands, likely by enabling the flexible evaluation of competing representations. }, author = {Cumpelik, Andrea D}, isbn = {978-3-99078-056-5}, issn = {2663-337X}, keywords = {neuroscience, decision making, learning, cognitive flexibility, medial prefrontal cortex, hippocampus, electrophysiology}, pages = {96}, publisher = {Institute of Science and Technology Austria}, title = {{The role of prefrontal spatial coding in supporting a contextual association task}}, doi = {10.15479/AT-ISTA-19456}, 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{17089, abstract = {How the coordination of neuronal spiking and brain rhythms between hippocampal subregions supports memory function remains elusive. We studied the interregional coordination of CA3 neuronal spiking with CA1 theta oscillations by recording electrophysiological signals along the proximodistal axis of the hippocampus in rats that were performing a high-memory-demand recognition memory task adapted from humans. We found that CA3 population spiking occurs preferentially at the peak of distal CA1 theta oscillations when memory was tested but only when previously encountered stimuli were presented. In addition, decoding analyses revealed that only population cell firing of proximal CA3 together with that of distal CA1 can predict performance at test in the present non-spatial task. Overall, our work demonstrates an important role for the synchronization of CA3 neuronal activity with CA1 theta oscillations during memory testing.}, author = {Ku, Shih Pi and Atucha, Erika and Alavi, Nico and Mulla-Osman, Halla and Kayumova, Rukhshona and Yoshida, Motoharu and Csicsvari, Jozsef L and Sauvage, Magdalena M.}, issn = {2211-1247}, journal = {Cell Reports}, number = {6}, publisher = {Elsevier}, title = {{Phase locking of hippocampal CA3 neurons to distal CA1 theta oscillations selectively predicts memory performance}}, doi = {10.1016/j.celrep.2024.114276}, volume = {43}, year = {2024}, } @phdthesis{17346, abstract = {Acquiring, retaining, and retrieving information over a wide range of timescales are crucial functions of the brain. The successful processing of memories affects many aspects of our lives and enables us and many other organisms to operate in a complex environment and to interact with it. In this context, the hippocampus and functionally connected brain areas, such as the prefrontal cortex, are central and have been subject to intensive research in the past decades. Storage of memories is believed to rely on distributed neural activity within these neural circuits. Additionally, neural memory traces of recent experience are reinstated during periods of rest or sleep. These reactivations are thought to play an outstanding role in the consolidation of memories and potentially facilitate the transfer of information from the hippocampus to cortical areas for long-term storage and integration into existing knowledge. However, there is growing evidence that memory-related neural representations in the hippocampus are not as stable as initially thought and that they change even in the absence of learning. It has been suggested that these changes reflect the accumulation of experience, but the influence of interspersed consolidation periods has not been considered. Previous studies have analyzed consolidation periods by detecting activity that strongly resembled neural activity during the acquisition of memory. Besides being often limited to only non-rapid eye movement (NREM) sleep, the used approaches were not capable of tracking changes in neural representations over extended temporal periods. More fluid representations do not only challenge our understanding of how information is stored, but they also affect the transfer of information between brain areas during the consolidation process. For this thesis, I investigated the evolution of memory-related activity during sleep periods expected to be involved in consolidation in the hippocampus and between the hippocampus and prefrontal cortex. I found that reactivated activity in the hippocampus gradually transformed during prolonged periods of sleep and inactivity. In the beginning, neural activity strongly resembled acquisition activity, whereas, with the progression of time, it became more similar to the subsequent recall activity. NREM periods drove this process, while rapid-eye movement (REM) periods showed a resetting effect. This reactivation drift was due to firing rate changes of a subset of cells and mirrored the representational changes from the acquisition to the recall. A stable subset of cells withstood the drift and maintained their activity. Therefore, my results indicate that memory-related representations undergo spontaneous modifications during consolidation periods and that these changes are predictive of representational drift. Furthermore, I found that the amount of change in the neural activity during subsequent sleep periods was biased by prior behavioral performance. Observed changes in the hippocampus and the prefrontal cortex were synchronized and increased after poor performance, highlighting a potential role in the exchange of information. Low-variance vii periods with distinct, more stable activity from a subset of cells significantly contributed to the heightened synchrony between both areas. Hence, interleaved phases of more stable neural activity could facilitate the information transfer between brain areas. In conclusion, my investigations underline the fluidity of memory-related representations and assign a prominent role to sleep reactivation periods in their evolution. In addition, I identified a potential mechanism of stable activity phases that might facilitate the synchronization across hippocampal-prefrontal activity despite ongoing changes. Reconciling and integrating findings from both spontaneous and behaviorally-related representational changes in functionally related brain areas will help to broaden our understanding of how knowledge is stored, maintained, updated, and transferred between brain areas.}, author = {Bollmann, Lars}, issn = {2663-337X}, keywords = {Memory, Hippocampus, Consolidation}, pages = {103}, publisher = {Institute of Science and Technology Austria}, title = {{Stability and change in the memory system during rest}}, doi = {10.15479/at:ista:17346}, year = {2024}, } @phdthesis{14821, abstract = {The hippocampus is central to memory formation, storage and retrieval over many timescales. Neurons in this brain area are highly selective to spatial position as well as to many other variables of the environment. It is believed that the selectivity patterns of hippocampal neurons reflect the structure of tasks an animal performs. However, especially at timescales longer than a few minutes or hours it is not fully known how these representations evolve, nor how they map to behaviour in the process. In this thesis, I monitored the evolution of hippocampal representations in a novel spatial-associative memory task for rats. Reward locations were associated with global sensory cues (i.e. context); animals had to remember the associations and dig for food in those locations only. I used in vivo electrophysiology to record the activity of the hippocampus dorsal CA1 neurons during the learning period of a few days. I report here a novel and simple method to classify behaviour performance to account for individual variability in learning speed and spurious performance unrelated to true task rule learning. Using this classification I was then able to investigate neural responses on different stages of learning matched across animals. On the first day of learning, I observed a fast formation of single-cell selectivity to task variables which remained stable over days. I also observed that reward tuning was not a single process but dependent on task-related cognitive load. At the population level, a linear decoding approach revealed a hierarchy in the representation of task variables that changed with learning. In the high-dimensional space of population activity, the representation of contexts was specific to each position in the maze, and could thus be better decoded if the position was known. The decoding of position did not improve with knowledge of other variables. As learning progressed, the hippocampal code underwent a reorganisation of high-variance directions in population activity, identified by principal component analysis. I found that dominant dimensions started carrying increasing amounts of information about task context specifically at those positions where it mattered for task performance. When I contrasted this with variables less relevant to task performance (e.g. movement direction), I did not observe differences in decoding quality over positions nor a reduction of dimensionality with learning. Overall, the largest changes in CA1 neural response with task learning happened in a matter of a few trials; over days, changes undetectable in single-cell statistics were responsible for re-structuring the hierarchy of neural representations at the population level; these changes were task-specific and reflected different stages of learning. This indicates that complex task learning may involve different magnitudes of response modulation in CA1, which happen at specific time scales linked to behaviour.}, author = {Chiossi, Heloisa}, issn = {2663-337X}, pages = {89}, publisher = {Institute of Science and Technology Austria}, title = {{Adaptive hierarchical representations in the hippocampus}}, doi = {10.15479/at:ista:14821}, 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{12862, abstract = {Despite the considerable progress of in vivo neural recording techniques, inferring the biophysical mechanisms underlying large scale coordination of brain activity from neural data remains challenging. One obstacle is the difficulty to link high dimensional functional connectivity measures to mechanistic models of network activity. We address this issue by investigating spike-field coupling (SFC) measurements, which quantify the synchronization between, on the one hand, the action potentials produced by neurons, and on the other hand mesoscopic “field” signals, reflecting subthreshold activities at possibly multiple recording sites. As the number of recording sites gets large, the amount of pairwise SFC measurements becomes overwhelmingly challenging to interpret. We develop Generalized Phase Locking Analysis (GPLA) as an interpretable dimensionality reduction of this multivariate SFC. GPLA describes the dominant coupling between field activity and neural ensembles across space and frequencies. We show that GPLA features are biophysically interpretable when used in conjunction with appropriate network models, such that we can identify the influence of underlying circuit properties on these features. We demonstrate the statistical benefits and interpretability of this approach in various computational models and Utah array recordings. The results suggest that GPLA, used jointly with biophysical modeling, can help uncover the contribution of recurrent microcircuits to the spatio-temporal dynamics observed in multi-channel experimental recordings.}, author = {Safavi, Shervin and Panagiotaropoulos, Theofanis I. and Kapoor, Vishal and Ramirez Villegas, Juan F and Logothetis, Nikos K. and Besserve, Michel}, issn = {1553-7358}, journal = {PLoS Computational Biology}, number = {4}, publisher = {Public Library of Science}, title = {{Uncovering the organization of neural circuits with Generalized Phase Locking Analysis}}, doi = {10.1371/journal.pcbi.1010983}, volume = {19}, 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}, } @article{11951, abstract = {The mammalian hippocampal formation (HF) plays a key role in several higher brain functions, such as spatial coding, learning and memory. Its simple circuit architecture is often viewed as a trisynaptic loop, processing input originating from the superficial layers of the entorhinal cortex (EC) and sending it back to its deeper layers. Here, we show that excitatory neurons in layer 6b of the mouse EC project to all sub-regions comprising the HF and receive input from the CA1, thalamus and claustrum. Furthermore, their output is characterized by unique slow-decaying excitatory postsynaptic currents capable of driving plateau-like potentials in their postsynaptic targets. Optogenetic inhibition of the EC-6b pathway affects spatial coding in CA1 pyramidal neurons, while cell ablation impairs not only acquisition of new spatial memories, but also degradation of previously acquired ones. Our results provide evidence of a functional role for cortical layer 6b neurons in the adult brain.}, author = {Ben Simon, Yoav and Käfer, Karola and Velicky, Philipp and Csicsvari, Jozsef L and Danzl, Johann G and Jonas, Peter M}, issn = {2041-1723}, journal = {Nature Communications}, keywords = {General Physics and Astronomy, General Biochemistry, Genetics and Molecular Biology, General Chemistry, Multidisciplinary}, publisher = {Springer Nature}, title = {{A direct excitatory projection from entorhinal layer 6b neurons to the hippocampus contributes to spatial coding and memory}}, doi = {10.1038/s41467-022-32559-8}, volume = {13}, year = {2022}, } @article{12149, abstract = {Editorial on the Research Topic}, author = {Gambino, Giuditta and Bhik-Ghanie, Rebecca and Giglia, Giuseppe and Puig, M. Victoria and Ramirez Villegas, Juan F and Zaldivar, Daniel}, issn = {1662-5110}, journal = {Frontiers in Neural Circuits}, keywords = {Cellular and Molecular Neuroscience, Cognitive Neuroscience, Sensory Systems, Neuroscience (miscellaneous)}, publisher = {Frontiers Media}, title = {{Editorial: Neuromodulatory ascending systems: Their influence at the microscopic and macroscopic levels}}, doi = {10.3389/fncir.2022.1028154}, volume = {16}, year = {2022}, } @article{10614, abstract = {The infiltration of immune cells into tissues underlies the establishment of tissue-resident macrophages and responses to infections and tumors. Yet the mechanisms immune cells utilize to negotiate tissue barriers in living organisms are not well understood, and a role for cortical actin has not been examined. Here, we find that the tissue invasion of Drosophila macrophages, also known as plasmatocytes or hemocytes, utilizes enhanced cortical F-actin levels stimulated by the Drosophila member of the fos proto oncogene transcription factor family (Dfos, Kayak). RNA sequencing analysis and live imaging show that Dfos enhances F-actin levels around the entire macrophage surface by increasing mRNA levels of the membrane spanning molecular scaffold tetraspanin TM4SF, and the actin cross-linking filamin Cheerio, which are themselves required for invasion. Both the filamin and the tetraspanin enhance the cortical activity of Rho1 and the formin Diaphanous and thus the assembly of cortical actin, which is a critical function since expressing a dominant active form of Diaphanous can rescue the Dfos macrophage invasion defect. In vivo imaging shows that Dfos enhances the efficiency of the initial phases of macrophage tissue entry. Genetic evidence argues that this Dfos-induced program in macrophages counteracts the constraint produced by the tension of surrounding tissues and buffers the properties of the macrophage nucleus from affecting tissue entry. We thus identify strengthening the cortical actin cytoskeleton through Dfos as a key process allowing efficient forward movement of an immune cell into surrounding tissues. }, author = {Belyaeva, Vera and Wachner, Stephanie and György, Attila and Emtenani, Shamsi and Gridchyn, Igor and Akhmanova, Maria and Linder, M and Roblek, Marko and Sibilia, M and Siekhaus, Daria E}, issn = {1545-7885}, journal = {PLoS Biology}, number = {1}, pages = {e3001494}, publisher = {Public Library of Science}, title = {{Fos regulates macrophage infiltration against surrounding tissue resistance by a cortical actin-based mechanism in Drosophila}}, doi = {10.1371/journal.pbio.3001494}, volume = {20}, year = {2022}, } @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}, }