Biology subjects

Battaglia, F.

Publications and source records attributed to Battaglia, F..

10 recordsLinked to original sources

bioRxiv2026

The emergence of a novel CA1 spatial map requires direct entorhinal input

The hippocampus and its main input, the entorhinal cortex, are essential for memory formation, yet how they interact to do so remains unresolved. Hippocampal CA1 pyramidal neurons exhibit spatial receptive fields which reorganize unpredictably upon exposure to a novel environment, a process called remapping, considered a model of memory formation. CA1 neurons integrate both hippocampal and direct entorhinal inputs, but their relative contributions to spatial coding are unclear. Here we combined population recordings of CA1 neurons with optogenetic silencing of their direct entorhinal input. While this manipulation did not impact spatial firing in a familiar environment, it impaired remapping in a novel environment, resulting in the emergence of a stable hybrid map combining features of both environments. This shows the direct entorhinal pathway plays a specific role in CA1 novelty detection, enabling the plasticity necessary to drive the reorganisation of spatial firing patterns, preventing interference between memories in different contexts.

neuroscience↗

bioRxiv2024

The DREAM implant: A Lightweight, Modular and Cost-Effective Implant System for Chronic Electrophysiology in Head-fixed and Freely Behaving Mice

Chronic electrophysiological recordings in rodents have significantly improved our understanding of neuronal dynamics and their behavioral relevance. However, current methods for chronically implanting probes present steep trade-offs between cost, ease of use, size, adaptability and long-term stability. SUMMARYIntroducing a lightweight, cost-effective probe implant system for chronic electrophysiology in rodents, optimized for ease of use, probe recovery, experimental versatility and compatibility with behavior. This protocol introduces a novel chronic probe implant system for mice called the DREAM (Dynamic, Recoverable, Economical, Adaptable and Modular), designed to overcome the trade-offs associated with currently available options. The system provides a lightweight, modular and cost-effective solution with standardized hardware elements that can be combined and implanted in straightforward steps and explanted safely for recovery and multiple re-use of probes, significantly reducing experimental costs. The DREAM implant system integrates three hardware modules: (1) a microdrive that can carry all standard silicon probes, allowing experimenters to adjust recording depth across a travel distance of up to 7mm; (2) a 3D-printable, open-source design for a wearable Faraday cage covered in copper mesh for electrical shielding, impact protection and connector placement, and (3) a miniaturized head-fixation system for improved animal welfare and ease of use. The corresponding surgery protocol was optimized for speed (total duration: 2 hours), probe safety and animal welfare. The resulting implants had minimal impact on animals behavioral repertoire, were easily applicable in freely moving and head-fixed contexts and delivered clearly identifiable spike waveforms and healthy neuronal responses for weeks of data collection post-implant. Infections and other surgery complications were extremely rare. As such, the DREAM implant system is a versatile, cost-effective solution for chronic electrophysiology in mice, enhancing animal well-being, and enabling more ethologically sound experiments. Its design simplifies experimental procedures across various research needs, increasing accessibility of chronic electrophysiology in rodents to a wide range of research labs.

neuroscience↗

bioRxiv2023

Differential population coding of natural movies through spike counts and temporal sequences

Information in the nervous system is encoded by the spiking patterns of large populations of neurons. The analysis of such high-dimensional data is typically restricted to simple, arbitrarily defined features like spike rates, which discards information in the temporal structure of spike trains. Here, we use a recently developed method called SpikeShip based on optimal transport theory, which captures information from all of the relative spike-timing relations among neurons. We compared spike-rate and spike-timing codes in neural ensembles from six visual areas during natural video presentations. Temporal spiking sequences conveyed substantially more information about natural movies than population spike-rate vectors, especially for larger number of neurons. As previously, shown, population rate vectors exhibited substantial drift across repetitions and between blocks. Conversely, encoding through temporal sequences was stable over time, and did not show representational drift both within and between blocks. These findings reveal a purely spike-based neural code that is based on relative spike timing relations in neural ensembles alone.

neuroscience↗

bioRxiv2022

Hippocampal ripples coincide with ''up-state'' and cortical spindles in Retrosplenial Cortex

During NREM sleep hippocampal Sharp-wave ripples (SWR) events are thought to stabilize memory traces for long-term storage in downstream neocortical structures. Within the neocortex, Default Mode Network (DMN) areas interact preferentially with the hippocampus purportedly to consolidate those traces. Transient bouts of slow oscillations and sleep spindles in DMN areas are often observed around SWRs, suggesting that these two activities are related and that their interplay possibly contributes to memory consolidation. To investigate how SWRs interact with the DMN and spindles, we combined cortical wide-field voltage imaging, ECoG, and hippocampal LFP recordings in anesthetized and sleeping mice. Here we show that, during SWR, "up-states" and spindles reliably co-occur in a cortical subnetwork centered around the Retrosplenial cortex. Furthermore, Retrosplenial transient activations and spindles predict Slow Gamma oscillations in CA1 during SWRs. Together, our results suggest that Retrosplenial-hippocampal interaction may be a central source of information exchange between cortex and hippocampus.

neuroscience↗

bioRxiv2022

State Dependent Coupling of Hippocampal Oscillations

Oscillations occurring simultaneously in a given area represent a physiological unit of brain states. They allow for temporal segmentation of spikes and support distinct behaviors. To establish how multiple oscillatory components co-varies simultaneously and influence neuronal firing during sleep and wakefulness, we describe a multi-variate analytical framework for constructing the state space of hippocampal oscillations. Examining the co-occurrence patterns of oscillations on the state space, across species, uncovered the presence of network constraints and distinct set of cross-frequency interactions during wakefulness as compared to sleep. We demonstrated how the state space can be used as a canvas to map the neural firing and found that distinct neurons during navigation were tuned to different set of simultaneously occurring oscillations during sleep. This multivariate analytical framework provides a window to move beyond classical bivariate pipelines, for investigating oscillations and neuronal firing, thereby allowing to factor-in the complexity of oscillation-population interactions.

neuroscience↗

bioRxiv2022

Hippocampal gamma and sharp wave/ripples mediate bidirectional interactions with cortical networks during sleep

Hippocampus-neocortex interactions during sleep are critical for memory processes: hippocampally-initiated replay contributes to memory consolidation in the neocortex and hippocampal sharp wave/ripples are linked to generalized increases in neocortical cell activity and DOWN-UP state transitions. Yet, the spatial and temporal patterns of this exchange are unknown. With voltage imaging, electrocorticography, and laminarly-resolved hippocampal potentials, we characterized cortico-hippocampal interactions during anesthesia and NREM sleep. We observed neocortical activation transients spanning multiple spatial scales hinting at a quasi-critical regime. Transients were organized in a small number of functional networks matching known anatomical connectivity. A network overlapping with the default mode network and centered on retrosplenial cortex was the most associated with the hippocampus. Interestingly, hippocampal slow gamma was the oscillation that best correlated with this neocortical network, outpacing ripples. In fact, neocortical activity predicted hippocampal slow gamma and followed ripples, suggesting that consolidation processes rely on bi-directional exchanges between hippocampus and neocortex.

neuroscience↗

bioRxiv2019

An incremental training method with automated, extendible T-maze for training spatial behavioral tasks in rodents

We present a training procedure and a T-maze equipped with sensors and automated feeders for training spatial behavioral tasks in rodents. The maze can be transformed from an enclosed box to a maze of variable dimensions. The modularity of the protocol and setup makes it highly flexible and suitable for training a wide variety of spatial tasks, and facilitates incremental training stages of increasing maze size for more efficient learning. The apparatus, in its software and hardware, is able to adapt to animal performance, adjusting task challenges and difficulty.\n\nTwo different methods of automatic behavioral scoring are evaluated against manual methods. Sensors embedded in the maze provide information regarding the order of reward locations visited and the time between the activation of the cue via the nose-poke and the activation of the reward location sensors. The distributions of these reaction times differ between correct and incorrect trials, providing an index of behavior and motivation. The automated maze system allows the trainer to operate and monitor the task away from the experimental set-up, minimizing human interference and improving the reproducibility of the experiment. We show that our method succeeds in training a binary forced-choice task in rats.

animal behavior and cognition↗

bioRxiv2018

The Hex-Maze: A previous knowledge task for mice

New information is rarely learned in isolation, instead most of what we experience can be incorporated into or uses previous knowledge networks in some form. However, most rodent laboratory tasks assume the animal to be naive with no previous experience influencing the results. Previous knowledge in form of a schema can facilitate knowledge acquisition and accelerate systems consolidation: memories become more rapidly hippocampal independent and instead rely more on the prefrontal cortex. Here, we developed a new spatial navigation task where food locations are learned in a large, gangway maze - the HexMaze. Analysing performance across sessions as well as on specific trials, we can show simple memory effects as well as multiple effects of previous knowledge accelerating both online learning and performance increases over offline periods. Importantly, we are the first to show that schema build-up is dependent on how much time passes, not how often the animal is trained.

animal behavior and cognition↗

bioRxiv2018

Why not record from every channel with a CMOS scanning probe?

It is an uninformative truism to state that the brain operates at multiple spatial and temporal scales, each with each own set of emergent phenomena. More worthy of attention is the point that our current understanding of it cannot clearly indicate which of these phenomenological scales are the significant contributors to the brains function and primary output (i.e. behaviour). Apart from the sheer complexity of the problem, a major contributing factor to this state of affairs is the lack of instrumentation that can simultaneously address these multiple scales without causing function altering damages to the underlying tissue. One important facet of this problem is that standard neural recording devices normally require one output connection per electrode. This limits the number of electrodes that can fit along the thin shafts of implantable probes generating a limiting balance between density and spread. Sharing a single output connection between multiple electrodes relaxes this constraint and permits designs of ultra-high density probes. Here we report the design and in-vivo validation of such a device, a complementary metal-oxide-semiconductor (CMOS) scanning probe with 1344 electrodes; the outcome of the European research project NeuroSeeker. We show that this design targets both local and global spatial scales by allowing the simultaneous recording of more than 1000 neurons spanning 7 functional regions with a single shaft. The neurons show similar recording longevity and signal to noise ratio to passive probes of comparable size and no adverse effects in awake or anesthetized animals. Addressing the data management of this device we also present novel visualization and monitoring methods. Using the probe with freely moving animals we show how accessing a number of cortical and subcortical brain regions offers a novel perspective on how the brain operates around salient behavioural events. Finally, we compare this probe with lower density, non CMOS designs (which have to adhere to the one electrode per output line rule). We show that an increase in density results in capturing neural firing patterns, undetectable by lower density devices, which correlate to self-similar structures inherent in complex naturalistic behaviour. To help design electrode configurations for future, even higher density, CMOS probes, recordings from many different brain regions were obtained with an ultra-dense passive probe.

neuroscience↗

bioRxiv2017

The Object Space Task for mice and rats

Declarative memory encompasses representations of specific events as well as knowledge extracted by accumulation over multiple episodes. To investigate how these different sorts of memories are created, we developed a new behavioral task in rodents. The task consists of three distinct conditions (stable, overlapping, random). Rodents are exposed to multiple sample trials, in which they explore objects in specific spatial arrangements. In the stable condition, the locations are constant during all sample trials; in the test trial, one objects location is changed. In the random condition, object locations are presented in the sample phase without a specific spatial pattern. In the overlapping condition, one location is shared (overlapping) between all trials while the other location changes during sample trials. We show that in the overlapping condition, instead of only remembering the last sample trial, rodents form a cumulative memory of the sample trials.\n\nHere we could show that both mice and rats can accumulate information across multiple trials and express a long-term abstracted memory.

animal behavior and cognition↗