Biology subjects

Miska, N. J.

Publications and source records attributed to Miska, N. J..

6 recordsLinked to original sources

bioRxiv2024

Interactive data exploration websites for large-scale electrophysiology

Methodological advances in neuroscience have enabled the collection of massive datasets which demand innovative approaches for scientific communication. Existing platforms for data storage lack intuitive tools for data exploration, limiting our ability to interact effectively with these brain-wide datasets. We introduce two public websites: (Data and Atlas) developed for the International Brain Laboratory which provide access to millions of behavioral trials and hundreds of thousands of individual neurons. These interfaces allow users to discover both the raw and processed brain-wide data released by the IBL at the scale of the whole brain, individual sessions, trials, and neurons. By hosting these data interfaces as websites they are available cross-platform with no installation. By releasing each sites code as a modular open-source framework, other researchers can easily develop their own web interfaces and explore their own data. As neuroscience datasets continue to expand, customizable web interfaces offer a glimpse into a future of streamlined data exploration and act as blueprints for future tools.

neuroscience↗

bioRxiv2023

Dissecting the Complexities of Learning With Infinite Hidden Markov Models

Learning to exploit the contingencies of a complex experiment is not an easy task for animals. Individuals learn in an idiosyncratic manner, revising their approaches multiple times as they are shaped, or shape themselves, and potentially end up with different strategies. Their long-run learning curves are therefore a tantalizing target for the sort of individualized quantitative characterizations that sophisticated modelling can provide. However, any such model requires a flexible and extensible structure which can capture radically new behaviours as well as slow changes in existing ones. To this end, we suggest a dynamic input-output infinite hidden semi-Markov model, whose latent states are associated with specific components of behaviour. This model includes an infinite number of potential states and so has the capacity to describe substantially new behaviours by unearthing extra states; while dynamics in the model allow it to capture more modest adaptations to existing behaviours. We individually fit the model to data collected from more than 100 mice as they learned a contrast detection task over tens of sessions and around fifteen thousand trials each. Despite large individual differences, we found that most animals progressed through three major stages of learning, the transitions between which were marked by distinct additions to task understanding. We furthermore showed that marked changes in behaviour are much more likely to occur at the very beginning of sessions, i.e. after a period of rest, and that response biases in earlier stages are not predictive of biases later on in this task.

animal behavior and cognition↗

bioRxiv2023

A Brain-Wide Map of Neural Activity during Complex Behaviour

A key challenge in neuroscience is understanding how neurons in hundreds of interconnected brain regions integrate sensory inputs with prior expectations to initiate movements and thereby make decisions. It is difficult to meet this challenge if different laboratories apply different analyses to different recordings in different regions during different behaviours. Here, we report a comprehensive set of recordings from 621733 neurons across 139 mice in 12 labs performing a decision-making task with sensory, motor, and cognitive components, obtained with 699 Neuropixels probe insertions covering 279 brain areas in the left forebrain and midbrain and the right hindbrain and cerebellum. We provide an initial appraisal of this brain-wide map, assessing how neural activity encoded key task variables. Representations of visual stimuli appeared transiently in classical visual areas after stimulus onset and then spread to ramp-like activity in a collection of mid- and hindbrain regions that also encoded choices. Neural responses correlated with motor action almost everywhere in the brain. Responses to reward delivery and consumption versus negative feedback were also widespread. This publicly available dataset represents an unprecedented resource for understanding how computations distributed across and within brain areas drive behaviour.

neuroscience↗

bioRxiv2023

Brain-wide representations of prior information in mouse decision-making

The neural representations of prior information about the state of the world are poorly understood. To investigate them, we examined brain-wide Neuropixels recordings and widefield calcium imaging collected by the International Brain Laboratory. Mice were trained to indicate the location of a visual grating stimulus, which appeared on the left or right with prior probability alternating between 0.2 and 0.8 in blocks of variable length. We found that mice estimate this prior probability and thereby improve their decision accuracy. Furthermore, we report that this subjective prior is encoded in at least 20% to 30% of brain regions which, remarkably, span all levels of processing, from early sensory areas (LGd, VISp) to motor regions (MOs, MOp, GRN) and high level cortical regions (ACAd, ORBvl). This widespread representation of the prior is consistent with a neural model of Bayesian inference involving loops between areas, as opposed to a model in which the prior is incorporated only in decision-making areas. This study offers the first brain-wide perspective on prior encoding at cellular resolution, underscoring the importance of using large scale recordings on a single standardized task.

neuroscience↗

bioRxiv2018

Autism-associated Shank3 is essential for homeostatic plasticity and neuronal circuit stability

Mutations in Shank3 are strongly associated with autism spectrum disorders and circuit disfunction, but a unified view of how Shank3 loss disrupts circuit function and excitability is lacking. Stabilizing, homeostatic forms of synaptic and intrinsic plasticity are critical for preventing circuit hyper- or hypo-excitability, leading us to ask whether Shank3 loss perturbs circuits by disrupting homeostatic plasticity. We show that Shank3 loss abolishes synaptic and intrinsic homeostatic plasticity, which can be rescued by lithium(Li), a drug with therapeutic potential in human Shankopathies. Further, Shank3 loss in vivo severely compromises the ability of visual cortical circuits to recover from perturbations to sensory drive. Our findings suggest that the loss of homeostatic compensation is a critical endophenotype that can explain a range of circuit disfunctions in Shankopathies.

neuroscience↗

bioRxiv2018

Sensory Deprivation Independently Regulates Neocortical Feedforward and Feedback Excitation-Inhibition Ratio

Brief (2-3d) monocular deprivation (MD) during the critical period induces a profound loss of responsiveness within layer 4 of primary visual cortex (V1). This has largely been ascribed to long-term depression (LTD) at thalamocortical synapses onto pyramidal neurons, while a contribution from intracortical inhibition has been controversial. Here we used optogenetics to probe feedforward thalamocortical and feedback intracortical excitation-inhibition (E-I) ratios following brief MD. While thalamocortical inputs onto pyramidal neurons were depressed, there was stronger depression onto PV+ interneurons, which shifted the thalamocortical-evoked E-I ratio toward excitation. In contrast, feedback intracortical E-I ratio was shifted toward inhibition, and a computational model of layer 4 demonstrated that these opposing shifts produced an overall suppression of layer 4 excitability. Thus, feedforward and feedback E-I ratios onto the same postsynaptic target can be independently regulated by visual experience, and enhanced feedback inhibition is the primary driving force behind loss of visual responsiveness.

neuroscience↗