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Article ; Online: Infer global, predict local: Quantity-relevance trade-off in protein fitness predictions from sequence data.

Posani, Lorenzo / Rizzato, Francesca / Monasson, Rémi / Cocco, Simona

2023 Volume 19, Issue 10, Page(s) e1011521

Abstract: Predicting the effects of mutations on protein function is an important issue in evolutionary biology and biomedical applications. Computational approaches, ranging from graphical models to deep-learning architectures, can capture the statistical ... ...

Abstract	Predicting the effects of mutations on protein function is an important issue in evolutionary biology and biomedical applications. Computational approaches, ranging from graphical models to deep-learning architectures, can capture the statistical properties of sequence data and predict the outcome of high-throughput mutagenesis experiments probing the fitness landscape around some wild-type protein. However, how the complexity of the models and the characteristics of the data combine to determine the predictive performance remains unclear. Here, based on a theoretical analysis of the prediction error, we propose descriptors of the sequence data, characterizing their quantity and relevance relative to the model. Our theoretical framework identifies a trade-off between these two quantities, and determines the optimal subset of data for the prediction task, showing that simple models can outperform complex ones when inferred from adequately-selected sequences. We also show how repeated subsampling of the sequence data is informative about how much epistasis in the fitness landscape is not captured by the computational model. Our approach is illustrated on several protein families, as well as on in silico solvable protein models.
MeSH term(s)	Proteins/genetics ; Mutagenesis ; Mutation ; Biological Evolution ; Computer Simulation ; Genetic Fitness/genetics ; Models, Genetic
Chemical Substances	Proteins
Language	English
Publishing date	2023-10-26
Publishing country	United States
Document type	Journal Article
ZDB-ID	2193340-6
ISSN	1553-7358 ; 1553-734X
ISSN (online)	1553-7358
ISSN	1553-734X
DOI	10.1371/journal.pcbi.1011521
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Tuned geometries of hippocampal representations meet the computational demands of social memory.

Boyle, Lara M / Posani, Lorenzo / Irfan, Sarah / Siegelbaum, Steven A / Fusi, Stefano

Neuron

2024 Volume 112, Issue 8, Page(s) 1358–1371.e9

Abstract: Social memory consists of two processes: the detection of familiar compared with novel conspecifics and the detailed recollection of past social episodes. We investigated the neural bases for these processes using calcium imaging of dorsal CA2 ... ...

Abstract	Social memory consists of two processes: the detection of familiar compared with novel conspecifics and the detailed recollection of past social episodes. We investigated the neural bases for these processes using calcium imaging of dorsal CA2 hippocampal pyramidal neurons, known to be important for social memory, during social/spatial encounters with novel conspecifics and familiar littermates. Whereas novel individuals were represented in a low-dimensional geometry that allows for generalization of social identity across different spatial locations and of location across different identities, littermates were represented in a higher-dimensional geometry that supports high-capacity memory storage. Moreover, familiarity was represented in an abstract format, independent of individual identity. The degree to which familiarity increased the dimensionality of CA2 representations for individual mice predicted their performance in a social novelty recognition memory test. Thus, by tuning the geometry of structured neural activity, CA2 is able to meet the demands of distinct social memory processes.
MeSH term(s)	Mice ; Animals ; Hippocampus/physiology ; Recognition, Psychology/physiology ; Memory/physiology ; Pyramidal Cells
Language	English
Publishing date	2024-02-20
Publishing country	United States
Document type	Journal Article
ZDB-ID	808167-0
ISSN	1097-4199 ; 0896-6273
ISSN (online)	1097-4199
ISSN	0896-6273
DOI	10.1016/j.neuron.2024.01.021
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Zs.A 2496: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (2.OG) ab Jg. 2022: Lesesaal (EG)
Zs.MG 92: Show issues

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Article: The representational geometry of emotional states in basolateral amygdala.

O'Neill, Pia-Kelsey / Posani, Lorenzo / Meszaros, Jozsef / Warren, Phebe / Schoonover, Carl E / Fink, Andrew J P / Fusi, Stefano / Salzman, C Daniel

bioRxiv : the preprint server for biology

2024

Abstract: Sensory stimuli associated with aversive outcomes cause multiple behavioral responses related to an animal's evolving emotional state, but neural mechanisms underlying these processes remain unclear. Here aversive stimuli were presented to mice, ... ...

Abstract	Sensory stimuli associated with aversive outcomes cause multiple behavioral responses related to an animal's evolving emotional state, but neural mechanisms underlying these processes remain unclear. Here aversive stimuli were presented to mice, eliciting two responses reflecting fear and flight to safety: tremble and ingress into a virtual burrow. Inactivation of basolateral amygdala (BLA) eliminated differential responses to aversive and neutral stimuli without eliminating responses themselves, suggesting BLA signals valence, not motor commands. However, two-photon imaging revealed that neurons typically exhibited mixed selectivity for stimulus identity, valence, tremble and/or ingress. Despite heterogeneous selectivity, BLA representational geometry was lower-dimensional when encoding valence, tremble and safety, enabling generalization of emotions across conditions. Further, tremble and valence coding directions were orthogonal, allowing linear readouts to specialize. Thus BLA representational geometry confers two computational properties that identify specialized neural circuits encoding variables describing emotional states: generalization across conditions, and readouts lacking interference from other readouts.
Language	English
Publishing date	2024-04-21
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.09.23.558668
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Article ; Online: Differential Relation between Neuronal and Behavioral Discrimination during Hippocampal Memory Encoding.

Allegra, Manuela / Posani, Lorenzo / Gómez-Ocádiz, Ruy / Schmidt-Hieber, Christoph

Neuron

2020 Volume 108, Issue 6, Page(s) 1103–1112.e6

Abstract: How are distinct memories formed and used for behavior? To relate neuronal and behavioral discrimination during memory formation, we use in vivo 2-photon ... ...

Abstract	How are distinct memories formed and used for behavior? To relate neuronal and behavioral discrimination during memory formation, we use in vivo 2-photon Ca
MeSH term(s)	Animals ; Calcium Signaling/physiology ; Dentate Gyrus/physiology ; Hippocampus/physiology ; Mice ; Neurons/physiology ; Patch-Clamp Techniques ; Photic Stimulation ; Spatial Memory/physiology
Language	English
Publishing date	2020-10-16
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	808167-0
ISSN	1097-4199 ; 0896-6273
ISSN (online)	1097-4199
ISSN	0896-6273
DOI	10.1016/j.neuron.2020.09.032
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Zs.A 2496: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (2.OG) ab Jg. 2022: Lesesaal (EG)
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Article ; Online: Integration and multiplexing of positional and contextual information by the hippocampal network.

Posani, Lorenzo / Cocco, Simona / Monasson, Rémi

PLoS computational biology

2018 Volume 14, Issue 8, Page(s) e1006320

Abstract: The hippocampus is known to store cognitive representations, or maps, that encode both positional and contextual information, critical for episodic memories and functional behavior. How path integration and contextual cues are dynamically combined and ... ...

Abstract	The hippocampus is known to store cognitive representations, or maps, that encode both positional and contextual information, critical for episodic memories and functional behavior. How path integration and contextual cues are dynamically combined and processed by the hippocampus to maintain these representations accurate over time remains unclear. To answer this question, we propose a two-way data analysis and modeling approach to CA3 multi-electrode recordings of a moving rat submitted to rapid changes of contextual (light) cues, triggering back-and-forth instabitilies between two cognitive representations ("teleportation" experiment of Jezek et al). We develop a dual neural activity decoder, capable of independently identifying the recalled cognitive map at high temporal resolution (comparable to theta cycle) and the position of the rodent given a map. Remarkably, position can be reconstructed at any time with an accuracy comparable to fixed-context periods, even during highly unstable periods. These findings provide evidence for the capability of the hippocampal neural activity to maintain an accurate encoding of spatial and contextual variables, while one of these variables undergoes rapid changes independently of the other. To explain this result we introduce an attractor neural network model for the hippocampal activity that process inputs from external cues and the path integrator. Our model allows us to make predictions on the frequency of the cognitive map instability, its duration, and the detailed nature of the place-cell population activity, which are validated by a further analysis of the data. Our work therefore sheds light on the mechanisms by which the hippocampal network achieves and updates multi-dimensional neural representations from various input streams.
MeSH term(s)	Action Potentials/physiology ; Animals ; CA3 Region, Hippocampal/physiology ; Cues ; Hippocampus/physiology ; Male ; Memory, Episodic ; Models, Neurological ; Nerve Net/physiology ; Neural Networks (Computer) ; Neurons/physiology ; Rats ; Space Perception/physiology ; Spatial Behavior/physiology
Language	English
Publishing date	2018-08-14
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2193340-6
ISSN	1553-7358 ; 1553-734X
ISSN (online)	1553-7358
ISSN	1553-734X
DOI	10.1371/journal.pcbi.1006320
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Article ; Online: A synaptic signal for novelty processing in the hippocampus.

Gómez-Ocádiz, Ruy / Trippa, Massimiliano / Zhang, Chun-Lei / Posani, Lorenzo / Cocco, Simona / Monasson, Rémi / Schmidt-Hieber, Christoph

Nature communications

2022 Volume 13, Issue 1, Page(s) 4122

Abstract: Episodic memory formation and recall are complementary processes that rely on opposing neuronal computations in the hippocampus. How this conflict is resolved in hippocampal circuits is unclear. To address this question, we obtained in vivo whole-cell ... ...

Abstract	Episodic memory formation and recall are complementary processes that rely on opposing neuronal computations in the hippocampus. How this conflict is resolved in hippocampal circuits is unclear. To address this question, we obtained in vivo whole-cell patch-clamp recordings from dentate gyrus granule cells in head-fixed mice trained to explore and distinguish between familiar and novel virtual environments. We find that granule cells consistently show a small transient depolarisation upon transition to a novel environment. This synaptic novelty signal is sensitive to local application of atropine, indicating that it depends on metabotropic acetylcholine receptors. A computational model suggests that the synaptic response to novelty may bias granule cell population activity, which can drive downstream attractor networks to a new state, favouring the switch from recall to new memory formation when faced with novelty. Such a novelty-driven switch may enable flexible encoding of new memories while preserving stable retrieval of familiar ones.
MeSH term(s)	Animals ; Dentate Gyrus/physiology ; Hippocampus/physiology ; Memory, Episodic ; Mental Recall/physiology ; Mice ; Neurons/physiology
Language	English
Publishing date	2022-07-15
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-022-31775-6
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Article ; Online: Adolescent thalamic inhibition leads to long-lasting impairments in prefrontal cortex function.

Benoit, Laura J / Holt, Emma S / Posani, Lorenzo / Fusi, Stefano / Harris, Alexander Z / Canetta, Sarah / Kellendonk, Christoph

Nature neuroscience

2022 Volume 25, Issue 6, Page(s) 714–725

Abstract: Impaired cortical maturation is a postulated mechanism in the etiology of neurodevelopmental disorders, including schizophrenia. In the sensory cortex, activity relayed by the thalamus during a postnatal sensitive period is essential for proper cortical ... ...

Abstract	Impaired cortical maturation is a postulated mechanism in the etiology of neurodevelopmental disorders, including schizophrenia. In the sensory cortex, activity relayed by the thalamus during a postnatal sensitive period is essential for proper cortical maturation. Whether thalamic activity also shapes prefrontal cortical maturation is unknown. We show that inhibiting the mediodorsal and midline thalamus in mice during adolescence leads to a long-lasting decrease in thalamo-prefrontal projection density and reduced excitatory drive to prefrontal neurons. It also caused prefrontal-dependent cognitive deficits during adulthood associated with disrupted prefrontal cross-correlations and task outcome encoding. Thalamic inhibition during adulthood had no long-lasting consequences. Exciting the thalamus in adulthood during a cognitive task rescued prefrontal cross-correlations, task outcome encoding and cognitive deficits. These data point to adolescence as a sensitive window of thalamocortical circuit maturation. Furthermore, by supporting prefrontal network activity, boosting thalamic activity provides a potential therapeutic strategy for rescuing cognitive deficits in neurodevelopmental disorders.
MeSH term(s)	Animals ; Inhibition, Psychological ; Mice ; Neural Pathways/physiology ; Neurons/physiology ; Prefrontal Cortex/physiology ; Schizophrenia ; Thalamus
Language	English
Publishing date	2022-05-19
Publishing country	United States
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, N.I.H., Extramural
ZDB-ID	1420596-8
ISSN	1546-1726 ; 1097-6256
ISSN (online)	1546-1726
ISSN	1097-6256
DOI	10.1038/s41593-022-01072-y
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Zs.A 4891: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (2.OG) ab Jg. 2022: Lesesaal (EG)
Zs.MG 67: Show issues

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Article ; Online: Functional connectivity models for decoding of spatial representations from hippocampal CA1 recordings.

Posani, Lorenzo / Cocco, Simona / Ježek, Karel / Monasson, Rémi

Journal of computational neuroscience

2017 Volume 43, Issue 1, Page(s) 17–33

Abstract: Hippocampus stores spatial representations, or maps, which are recalled each time a subject is placed in the corresponding environment. Across different environments of similar geometry, these representations show strong orthogonality in CA3 of ... ...

Abstract	Hippocampus stores spatial representations, or maps, which are recalled each time a subject is placed in the corresponding environment. Across different environments of similar geometry, these representations show strong orthogonality in CA3 of hippocampus, whereas in the CA1 subfield a considerable overlap between the maps can be seen. The lower orthogonality decreases reliability of various decoders developed in an attempt to identify which of the stored maps is active at the moment. Especially, the problem with decoding emerges with a need to analyze data at high temporal resolution. Here, we introduce a functional-connectivity-based decoder, which accounts for the pairwise correlations between the spiking activities of neurons in each map and does not require any positional information, i.e. any knowledge about place fields. We first show, on recordings of hippocampal activity in constant environmental conditions, that our decoder outperforms existing decoding methods in CA1. Our decoder is then applied to data from teleportation experiments, in which an instantaneous switch between the environment identity triggers a recall of the corresponding spatial representation . We test the sensitivity of our approach on the transition dynamics between the respective memory states (maps). We find that the rate of spontaneous state shifts (flickering) after a teleportation event is increased not only within the first few seconds as already reported, but this instability is sustained across much longer (> 1 min.) periods.
MeSH term(s)	CA1 Region, Hippocampal/physiology ; Hippocampus ; Humans ; Memory ; Models, Neurological ; Neurons/physiology ; Reproducibility of Results
Language	English
Publishing date	2017-05-08
Publishing country	United States
Document type	Journal Article
ZDB-ID	1230659-9
ISSN	1573-6873 ; 0929-5313
ISSN (online)	1573-6873
ISSN	0929-5313
DOI	10.1007/s10827-017-0645-9
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Book ; Online: The carbon footprint of a distributed cloud storage

Posani, Lorenzo / Paccoia, Alessio / Moschettini, Marco

2018

Abstract: The ICT (Information Communication Technologies) ecosystem is estimated to be responsible, as of today, for 10% of the total worldwide energy demand - equivalent to the combined energy production of Germany and Japan. Cloud storage, mainly operated ... ...

Abstract	The ICT (Information Communication Technologies) ecosystem is estimated to be responsible, as of today, for 10% of the total worldwide energy demand - equivalent to the combined energy production of Germany and Japan. Cloud storage, mainly operated through large and densely-packed data centers, constitutes a non-negligible part of it. However, since the cloud is a fast-inflating market and the energy-efficiency of data centers is mostly an insensitive issue for the collectivity, its carbon footprint shows no signs of slowing down. In this paper, we analyze a novel paradigm for cloud storage, implemented by Cubbit (www.cubbit.io), in which data are stored and distributed over a network of p2p-interacting ARM-based single-board devices. We compare Cubbit' distributed cloud to the traditional centralized solution in terms of environmental footprint and power-usage efficiency. We demonstrate how a distributed architecture is beneficial as regards impact reduction on both data transfers and data storage. Compared to the centralized cloud, the distributed architecture of Cubbit achieves a -87% reduction of the carbon footprint for data storage and a -50% reduction for data transfers, providing an example of how a radical paradigm shift can benefit both the final consumer and society as a whole.
Keywords	Computer Science - Distributed ; Parallel ; and Cluster Computing
Publishing date	2018-03-19
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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