Biology subjects

Diamanti, E. M.

Publications and source records attributed to Diamanti, E. M..

5 recordsLinked to original sources

bioRxiv2024

TWINKLE: An open-source two-photon microscope for teaching and research

Many laboratories use two-photon microscopy through commercial suppliers, or homemade designs of considerable complexity. The integrated nature of these systems complicates customization, troubleshooting, and training on the principles of two-photon microscopy. Here, we present "Twinkle": a microscope for Two-photon Imaging in Neuroscience, and Kit for Learning and Education. It is a fully open, high performing and easy-to-set-up microscope that can effectively be used for both education and research. The instrument features a > 1 mm field of view, using a modern objective with 3 mm working distance and 2 inch diameter optics combined with GaAsP photomultiplier tubes to maximize the fluorescence signal. We document our experiences using this system as a teaching tool in several two week long workshops, exemplify scientific use cases, and conclude with a broader note on the place of our work in the growing space of open scientific instrumentation.

neuroscience↗

bioRxiv2022

Modeling communication and switching nonlinear dynamics in multi-region neural activity

Understanding how multiple brain regions interact to produce behavior is a major challenge in systems neuroscience, with many regions causally implicated in common tasks such as sensory processing and decision making. However, a precise description of interactions between regions remains an open problem. Moreover, neural dynamics are nonlinear, non-stationary, and can vary dramatically across sessions, days, and animals. Here, we propose multi-region, switching dynamical systems (MR-SDS), a probabilistic model of multiple latent interacting systems that evolve with switching nonlinear dynamics and communication between regions. MR-SDS includes directed interactions between brain regions, allowing for estimation of state-dependent communication signals, and accounts for sensory inputs effects, history effects, and heterogeneity across days and animals. We show that our model accurately recovers latent trajectories, vector fields underlying switching nonlinear dynamics, and cross-region communication profiles in two simulations. We then apply our method to two large-scale, multi-region neural datasets involving mouse decision making. The first includes hundreds of neurons per region, recorded simultaneously at single-cell-resolution across 3 distant cortical regions. The second is a mesoscale widefield dataset of 8 adjacent cortical regions imaged across both hemispheres. On these multi-region datasets, our model outperforms existing piece-wise linear multi-region models and reveals multiple distinct dynamical states and a rich set of cross-region communication profiles.

neuroscience↗

bioRxiv2019

Spatial encoding in the visual pathway arises in cortex and depends on active navigation

During navigation, the visual responses of neurons in primary visual cortex (V1) are modulated by the animals spatial position. Here we show that this spatial modulation is similarly present across multiple higher visual areas but largely absent in the main thalamic pathway into V1. Similar to hippocampus, spatial modulation in visual cortex strengthens with experience and requires engagement in active behavior. Active navigation in a familiar environment, therefore, determines spatial modulation of visual signals starting in the cortex.

neuroscience↗

bioRxiv2019

Modulation of visual cortex by hippocampal signals

Neurons in primary visual cortex (V1) are influenced by the animals position in the environment and encode positions that correlate with those encoded by hippocampus (CA1). Might V1s encoding of spatial positions be inherited from hippocampal regions? If so, it should depend on non-visual factors that affect the encoding of position in hippocampus, such as the physical distance traveled and the phase of theta oscillations. We recorded V1 and CA1 neurons while mice ran through a virtual corridor and confirmed these predictions. Spatial representations in V1 and CA1 were correlated even in the absence of visual cues. Moreover, similar to CA1 place cells, the spatial responses of V1 neurons were influenced by the physical distance traveled and the phase of hippocampal theta oscillations. These results reveal a modulation of cortical sensory processing by non-sensory estimates of position that might originate in hippocampal regions.

neuroscience↗

bioRxiv2017

Coherent representations of subjective spatial position in primary visual cortex and hippocampus

A major role of vision is to guide navigation, and navigation is strongly driven by vision1-4. Indeed, the brains visual and navigational systems are known to interact5, 6, and signals related to position in the environment have been suggested to appear as early as in visual cortex6, 7. To establish the nature of these signals we recorded in primary visual cortex (V1) and in the CA1 region of the hippocampus while mice traversed a corridor in virtual reality. The corridor contained identical visual landmarks in two positions, so that a purely visual neuron would respond similarly in those positions. Most V1 neurons, however, responded solely or more strongly to the landmarks in one position. This modulation of visual responses by spatial location was not explained by factors such as running speed. To assess whether the modulation is related to navigational signals and to the animals subjective estimate of position, we trained the mice to lick for a water reward upon reaching a reward zone in the corridor. Neuronal populations in both CA1 and V1 encoded the animals position along the corridor, and the errors in their representations were correlated. Moreover, both representations reflected the animals subjective estimate of position, inferred from the animals licks, better than its actual position. Indeed, when animals licked in a given location - whether correct or incorrect - neural populations in both V1 and CA1 placed the animal in the reward zone. We conclude that visual responses in V1 are tightly controlled by navigational signals, which are coherent with those encoded in hippocampus, and reflect the animals subjective position in the environment. The presence of such navigational signals as early as in a primary sensory area suggests that these signals permeate sensory processing in the cortex.

neuroscience↗