Biology subjects

Donato, F.

Publications and source records attributed to Donato, F..

8 recordsLinked to original sources

bioRxiv2026

Associative memory formation reshapes the learning trajectory of a novel cognitive map

Learning never occurs on a blank slate, as each experience an animal encounters in its daily life is encoded by circuits already shaped by previous ones. During such experiences, the hippocampus builds place-cell-based cognitive maps of the environments explored, and encodes ensemble-based memories for associations among events that occur within them. These spatial and mnemonic representations draw on neurons embedded within the same network. However, whether forming an associative memory of an experience unfolding in one context changes how the same hippocampal network maps a different one is unknown. Here, we longitudinally imaged CA3 neurons as mice familiarized with one environment, encoded either an associative fear memory or a context-only memory in a different environment, and then explored a novel one. Across separate experiences, neuronal recruitment into cognitive maps and memory ensembles followed structured, partially orthogonal allocation rules that were consistent across fear and neutral memories, with ensemble membership and place-cell identity showing no reciprocal enrichment. Fear memory encoding left the properties of the familiar map unchanged, while altering those of the novel one. From first exposure, the novel map already recruited a familiar-like fraction of place cells and supported spatial decoding with near-familiar precision, and its population activity occupied a latent subspace that aligned with the familiar map while remaining context-specific. Yet this novel map failed to undergo the experience-dependent refinement of decoding precision and across-day latent alignment that normally accompanies familiarization, even though place cells continued to gain spatial information and to remap. Associative memory encoding therefore shifts CA3 into a distinct representational regime, decoupling the immediate precision of a new cognitive map from the experience-dependent refinement of its context-specific population embedding.

neuroscience↗

bioRxiv2026

Equivalent volitional learning emerges through circuit-specific population dynamics in motor cortex and hippocampus

Learning operates across different brain circuits to associate population activity patterns with desired outcomes, and to enable volitional reactivation of those patterns to control behavior. These circuits differ profoundly in their architecture and dynamical regimes, yet which features of learning are shared across them and which arise from circuit-specific implementations remains unknown. Here, we use a brain-computer interface (BCI) to train mice to modulate the activity of selected neuronal ensembles toward configurations that trigger reward delivery. By making reward delivery contingent directly on population activity, we impose an identical associative learning problem on two circuits with distinct dynamical regimes: the primary motor cortex (M1) and the hippocampal area CA3. Mice acquired robust volitional control in both regions, and learning produced a set of shared signatures across circuits, including modulation of reward-controlling neurons, network-level sparsification, and greater exploration of reward-related activity patterns. These signatures were underpinned by distinct population dynamics: M1 activity flowed continuously through reward-associated states, whereas CA3 activity traced approach-and-return dynamics around them. Recurrent network models endowed with distinct minimal connectivity constraints chosen to reflect the dominant dynamical regime associated with each region captured key features of these shared signatures and region-specific dynamics, indicating that local architectural constraints are sufficient to account for the distinct implementations of learning. These findings indicate that equivalent learning outcomes arise from divergent dynamical implementations across architecturally distinct circuits. This principled degeneracy reveals that learning is not a single canonical solution, but is implemented through multiple circuit-specific mechanisms shaped by local network architecture.

neuroscience↗

bioRxiv2025

The Reinstatement of a Forgotten Infantile Memory

Infantile memories present a striking paradox: while early-life experiences are typically forgotten, reflecting the phenomenon of infantile amnesia, traumatic events from infancy can profoundly shape adult cognition and behavior. How do memories that are seemingly inaccessible persistently influence cognitive processes and behaviors throughout life? Rodent studies have demonstrated that forgotten infantile memories remain encoded as latent "infantile memory engrams" (iEngrams) within neuronal circuits, capable of memory reinstatement under artificial experimental conditions. Still, the network mechanisms underpinning the natural reinstatement of a forgotten infantile memory are unknown. Here, we show that infantile memories, though physiologically irretrievable in adults, remain stored within hippocampal circuits and their engrams contribute to hippocampal network dynamics. Crucially, reinstating these memories requires a carefully orchestrated network process. An initial contextual reminder primes the hippocampal network to increase activity of the iEngram during a subsequent aversive reminder, which tags iEngram neurons for offline reactivation. This reactivation facilitates the integration of previously latent infantile memories with novel neuronal ensembles, reinstating behavior consistent with the original memory. These findings critically advance our understanding of the neuronal mechanisms underlying physiological memory encoding, retrieval, and reinstatement across development. Furthermore, they delineate the temporal boundaries and underlying physiological substrate of the process by which a latent representation becomes associated with a novel neuronal substrate, suggesting potential interventions to prevent the maladaptive reinstatement of traumatic infantile memories.

neuroscience↗

bioRxiv2024

NMDA receptor activation drives early synapse formation in vivo

The rules governing neural circuit formation in mammalian central nervous systems are poorly understood. NMDA receptors are involved in synaptic plasticity mechanisms in mature neurons, but their contribution to circuit formation and dendritic maturation remains controversial. Using pharmacological and genetic interventions to disrupt NMDA receptor signaling in hippocampal CA1 pyramidal neurons in vitro and in vivo, we identify an early critical window for a synapse-specific function in wiring Schaffer collateral connections and dendritic arborization. Through in vivo imaging, we show that NMDA receptors are frequently activated during early development and elicit minute-long calcium transients, which immediately precede the emergence of filopodia. These results demonstrate that NMDA receptors drive synapto- and dendritogenesis during development, challenging the view that these processes are primarily mediated by molecular cues.

neuroscience↗

bioRxiv2023

Divergent Recruitment of Developmentally-Defined Neuronal Ensembles Supports Memory Dynamics

Memories are dynamic constructs whose properties change with time and experience. The biological mechanisms underpinning these dynamics remain elusive, particularly concerning how shifts in the composition of memory-encoding neuronal ensembles influence a memory properties evolution over time. By leveraging a developmental approach to target distinct subpopulations of principal neurons, we show that memory encoding results in the concurrent establishment of multiple memory traces in the mouse hippocampus. Two of these traces are instantiated in subpopulations of early- and late-born neurons and follow distinct reactivation trajectories post-encoding. Notably, the divergent recruitment of these subpopulations underpins memory ensembles gradual reorganization, and modulates memory persistence and plasticity across multiple learning episodes. Thus, our findings reveal profound and intricate relationships between ensemble dynamics and memories progression over time.

neuroscience↗

bioRxiv2022

Minute-scale oscillatory sequences in medial entorhinal cortex

The medial entorhinal cortex (MEC) hosts many of the brains circuit elements for spatial navigation and episodic memory, operations that require neural activity to be organized across long durations of experience1. While location is known to be encoded by a plethora of spatially tuned cell types in this brain region2-6, little is known about how the activity of entorhinal cells is tied together over time. Among the brains most powerful mechanisms for neural coordination are network oscillations, which dynamically synchronize neural activity across circuit elements7-10. In MEC, theta and gamma oscillations provide temporal structure to the neural population activity at subsecond time scales1,11-13. It remains an open question, however, whether similarly powerful coordination occurs in MEC at behavioural time scales, in the second-to-minute regime. Here we show that MEC activity can be organized into a minute-scale oscillation that entrains nearly the entire cell population, with periods ranging from 10 to 100 seconds. Throughout this ultraslow oscillation, neural activity progresses in periodic and stereotyped sequences. This activity was elicited while mice ran at free pace on a rotating wheel in darkness, with no change in its location or running direction and no scheduled rewards. The oscillation sometimes advanced uninterruptedly for tens of minutes, transcending epochs of locomotion and immobility. Similar oscillatory sequences were not observed in neighboring parasubiculum or in visual cortex. The ultraslow oscillation of activity sequences in MEC may have the potential to couple its neurons and circuits across extended time scales and to serve as a scaffold for processes that unfold at behavioural time scales, such as navigation and episodic memory formation.

neuroscience↗

bioRxiv2021

All-viral tracing of monosynaptic inputs to single birthdate-defined neurons in the intact brain

Neuronal firing patterns are the result of inputs converging onto single cells. Identifying these inputs, anatomically and functionally, is essential to understand how neurons integrate information. Single-cell electroporation of helper genes and subsequent local injection of recombinant rabies viruses enable precise mapping of inputs to individual cells in superficial layers of the intact cortex. However, access to neurons in deeper structures requires more invasive procedures, including removal of overlying tissue. We have developed a method that through a combination of virus injections allows us to target [≤]4 hippocampal cells 48% of the time and a single cell 16% of the time in wildtype mice without the use of electroporation or tissue aspiration. We identify local and distant monosynaptic inputs that can be functionally characterised in vivo. By expanding the toolbox for monosynaptic circuit tracing, this method will help further our understanding of neuronal integration at the level of single cells.

neuroscience↗

bioRxiv2021

Functional network topography of the medial entorhinal cortex

The medial entorhinal cortex (MEC) creates a map of local space, based on the firing patterns of grid, head direction (HD), border, and object-vector (OV) cells. How these cell types are organized anatomically is debated. In-depth analysis of this question requires collection of precise anatomical and activity data across large populations of neurons during unrestrained behavior, which neither electrophysiological nor previous imaging methods fully afford. Here we examined the topographic arrangement of spatially modulated neurons in MEC and adjacent parasubiculum using miniaturized, portable two-photon microscopes, which allow mice to roam freely in open fields. Grid cells exhibited low levels of co-occurrence with OV cells and clustered anatomically, while border, HD and OV cells tended to intermingle. These data suggest that grid-cell networks might be largely distinct from those of border, HD and OV cells and that grid cells exhibit strong coupling among themselves but weaker links to other cell types. Highlights- Grid and object vector cells show low levels of regional co-occurrence - Grid cells exhibit the strongest tendency to cluster among all spatial cell types - Grid cells stay separate from border, head direction and object vector cells - The territories of grid, head direction and border cells remain stable over weeks

neuroscience↗