Biology subjects

Maravall, M.

Publications and source records attributed to Maravall, M..

6 recordsLinked to original sources

bioRxiv2022

Sensory adaptation in the barrel cortex during active sensation in the awake, behaving mouse

Sensory adaptation (SA) is a prominent aspect of how neurons in anaesthetised animals respond to sensory signals, ubiquitous across species and modalities. However, SA depends on the activation state of the brain and it has been doubted whether SA is expressed in behaving animals. Here, we addressed this question by training mice to detect an object using their whiskers and recording neuronal activity from barrel cortex whilst simultaneously imaging the whiskers in 3D. We found that neuronal responses decreased during the course of whisker-object touch sequences but that this was due to two factors. First, a motor effect, whereby, during a sequence of touches, later touches were mechanically weaker than early ones. Second, a sensory encoding effect, whereby neuronal tuning to touch became progressively less sensitive during the course of a touch sequence. The sensory encoding effect was whisker-specific. These results show that SA does occur during active whisker sensing and suggest that SA is fundamental to sensation during natural behaviour.

neuroscience↗

bioRxiv2020

Learning a tactile sequence induces selectivity to action decisions and outcomes in the mouse somatosensory cortex

Sequential temporal ordering and patterning are key features of natural signals used by the brain to decode stimuli and perceive them as sensory objects. To explore how cortical neuronal activity underpins sequence recognition, we developed a task in which mice distinguished between tactile words constructed from distinct vibrations delivered to the whiskers, assembled in different orders. Animals licked to report the presence of the target sequence. Mice could respond to the earliest possible cues allowing discrimination, effectively solving the task as a detection of change problem, but enhanced their performance when deliberating for longer. Optogenetic inactivation showed that both primary somatosensory barrel cortex (S1bf) and secondary somatosensory cortex were necessary for sequence recognition. Two-photon imaging of calcium activity in S1bf layer 2/3 revealed that, in well-trained animals, neurons had heterogeneous selectivity to multiple task variables including not just sensory input but also the animals action decision and the trial outcome (presence or absence of a predicted reward). A large proportion of neurons were activated preceding goal-directed licking, thus reflecting the animals learnt response to the target sequence rather than the sequence itself; these neurons were found in S1bf as soon as mice learned to associate the rewarded sequence with licking. In contrast, learning evoked smaller changes in sensory responses: neurons responding to stimulus features were already found in naive mice, and training did not generate neurons with enhanced temporal integration or categorical responses. Therefore, in S1bf sequence learning results in neurons whose activity reflects the learnt association between the target sequence and licking, rather than a refined representation of sensory features.

neuroscience↗

bioRxiv2019

Divergent excitation two photon microscopy for 3D random access mesoscale imaging at single cell resolution

ABSTACTIn neuroscience, diffraction limited two-photon (2P) microscopy is a cornerstone technique that permits minimally invasive optical monitoring of neuronal activity. However, most conventional 2P microscopes impose significant constraints on the size of the imaging field-of-view and the specific shape of the effective excitation volume, thus limiting the scope of biological questions that can be addressed and the information obtainable. Here, employing divergent beam optics (DBO), we present an ultra-low-cost, easily implemented and flexible solution to address these limitations, offering a several-fold expanded three-dimensional field of view that also maintains single-cell resolution. We show that this implementation increases both the space-bandwidth product and effective excitation power, and allows for straight-forward tailoring of the point-spread-function. Moreover, rapid laser-focus control via an electrically tunable lens now allows near-simultaneous imaging of remote regions separated in three dimensions and permits the bending of imaging planes to follow natural curvatures in biological structures. Crucially, our core design is readily implemented (and reversed) within a matter of hours, and fully compatible with a wide range of existing 2P customizations, making it highly suitable as a base platform for further development. We demonstrate the application of our system for imaging neuronal activity in a variety of examples in mice, zebrafish and fruit flies.

neuroscience↗

bioRxiv2018

Heterogeneous progenitor cell behaviors underlie the assembly of neocortical cytoarchitecture

The cerebral cortex contains multiple hierarchically organized areas with distinctive cytoarchitectonical patterns, but the cellular mechanisms underlying the emergence of this diversity remain unclear. Here, we have quantitatively investigated the neuronal output of individual progenitor cells in the ventricular zone of the developing mouse neocortex using a combination of methods that together circumvent the biases and limitations of individual approaches. We found that individual cortical progenitor cells show a high degree of stochasticity and generate pyramidal cell lineages that adopt a wide range of laminar configurations. Mathematical modelling these lineage data suggests that a small number of progenitor cell populations, each generating pyramidal cells following different stochastic developmental programs, suffice to generate the heterogenous complement of pyramidal cell lineages that collectively build the complex cytoarchitecture of the neocortex.

neuroscience↗

bioRxiv2018

Spikeling: a low-cost hardware implementation of a spiking neuron for neuroscience teaching and outreach.

Understanding of how neurons encode and compute information is fundamental to our study of the brain, but opportunities for hands-on experience with neurophysiological techniques on live neurons are scarce in science education. Here, we present Spikeling, an open source {pound}25 in silico implementation of a spiking neuron that mimics a wide range of neuronal behaviours for classroom education and public neuroscience outreach. Spikeling is based on an Arduino microcontroller running the computationally efficient Izhikevich model of a spiking neuron. The microcontroller is connected to input ports that simulate synaptic excitation or inhibition, dials controlling current injection and noise levels, a photodiode that makes Spikeling light-sensitive and an LED and speaker that allows spikes to be seen and heard. Output ports provide access to variables such as membrane potential for recording in experiments or digital signals that can be used to excite other connected Spikelings. These features allow for the intuitive exploration of the function of neurons and networks. We also report our experience of using Spikeling as a teaching tool for undergraduate and graduate neuroscience education in Nigeria and the UK.

scientific communication and education↗

bioRxiv2017

Learning And Recognition Of Tactile Temporal Sequences By Mice And Humans

The world around us is replete with stimuli that unfold over time. When we hear an auditory stream like music or speech or scan a texture with our fingertip, physical features in the stimulus are concatenated in a particular order, and this temporal patterning is critical to interpreting the stimulus. To explore the capacity of mice and humans to learn tactile sequences, we developed a task in which subjects had to recognise a continuous modulated noise sequence delivered to whiskers or fingertips, defined by its temporal patterning over hundreds of milliseconds. GO and NO-GO sequences differed only in that the order of their constituent noise modulation segments was temporally scrambled. Both mice and humans efficiently performed tactile sequence learning. Mouse performance relied mainly on detecting relative changes in noise amplitude over time, whereas humans appeared to have access to more cues, including the duration of noise modulation segments.

neuroscience↗