COSYNE 2022 ePosters

Decisions are often guided by detecting subtle signals in a dynamic sensory environment. Although the brain must track such decision-relevant signals, how they are represented and transformed by neural activity across the sensorimotor axis remains poorly understood. Here, we recorded neural activity with Neuropixels…

Sensory features are encoded in topographically mapped neuronal populations in the brain. Their fine structure layout is not readily accessible due to their dense wiring and extended volume. To reveal their wiring logic, we combine genetic multicolor labeling of neural cells and large-volume micrometer scale imaging…

Neurons spike spontaneously in many experimental settings. Such firing patterns are often characterized by prolonged periods of silence followed by an unknown trigger of spontaneous activity that propagates throughout the slice. These were dubbed `neural avalanches' as they resemble avalanches in which accumulated…

Log-linear 1/f spectral densities are widely observed in the brain - across multiple species and at many levels of abstraction. However, the intrinsic relationship between the structural attributes of the brain and 1/f biorhythms remains largely unclear. Here, we explore a novel theoretical and generative framework,…

The striatum and prefrontal cortex (PFC) play critical roles in reinforcement learning (RL). The striatum implements a model-free RL algorithm by driving synaptic plasticity modulated by dopaminergic prediction errors. The PFC, in turn, is thought to implement a model-based algorithm through its neuronal dynamics. The…

Brain networks possess many non-random features that might present a key to the computational effectiveness and robustness of the nervous system. Information-transmission pathways in neuronal structure, especially in complex connectomes, seem to favor specific recurrent motifs. For intrinsically directional and…

Motor activity including locomotion and other movement types influence neuronal activity in many brain areas across animal species, including worms, flies, and mice. Yet the origin of these neural representations of ongoing behavior remain elusive. We posit that in extreme cases, activity could arise from two opposite…

Animals use their vision to detect objects in their environment and thereby guide their behavior. In particular, flying insects show behavioral responses to small moving visual objects, but neural circuits underlying such visuomotor reflexes are not clearly understood. We identified a neural pathway underlying small…

In recent years, advances in the fields of computational ethology and neuroscience have enabled detailed modeling of animal behavior and its neural underpinnings. However, these advances have yet to produce normative models of neuromotor control that generate the full diversity of animal behavior. Using recently…

How do we learn about experiences while being removed from the experience itself? One solution involves offline learning via reactivations. Sensory reactivation involves the recurrence of a pattern of neural activity during sleep or quiet waking that previously occurred during a sensory experience. Historically,…

Children learn to build a visual representation of the world from unsupervised exploration and we hypothesize that a key part of this learning ability is the use of self-generated navigational information as a similarity label to drive a learning objective for self-supervised learning. The goal of this work is to…

Sharp-wave ripples (SWR) are high frequency events recorded in the local field potential (LFP) of the hippocampus of rodents and humans. During SWR, the sequential firing of ensembles of neurons act to reactivate memory traces of previously encoded experience. SWR-related interventions can influence…

Understanding the activity of single neurons in relation to features in the environment is the first step in many neuroscience studies. We propose a method using algorithm unrolling, an emerging technique in interpretable deep learning, to deconvolve single-trial neuronal activity into interpretable components.…

When an agent is trained on a complex episodic task, different task parts may be learned at different rates. How do we determine which part of the task challenged the agent the most? Since reward is provided usually only at the end of each trial, it cannot be used to infer within-trial learning trends. Behavioral…

During prolonged periods of stress, animals switch from active to passive coping strategies to manage effort expenditure. These normally adaptive behavioral state transitions become maladaptive in disorders such as depression. Such behavioral state transitions occur as animals continually evaluate the fruitfulness or…

The 3D morphology of cortical neurons is highly complex with widely varying shapes and has long been used to classify neurons into cell types. Classification based on morphology has classically been done by either laborious expert analysis through visual inspection or by computing a set of predefined features that…

Columnar organization is the hallmark of mature visual cortex in primates and carnivores, and is often assumed to be unique to those areas. Such an organization is already evident in the developing visual cortex (V1) well before eye-opening, where correlated modular spontaneous activity predicts future sensory-evoked…

Neurons in primary Visual Cortex (V1) have a receptive field (RF) or "center", the region in visual space in which appropriate stimuli drive the neuron to fire. Stimuli surrounding the RF modulate these responses, a phenomenon known as contextual modulation. Here we consider 3 types of contextual modulation: i)…

We trained five rats to perform a complex auditory-guided task in a large environment (diameter 160 cm) with twelve nose-poke ports. To obtain rewards, rats had to position themselves at specific locations indicated by sounds. Despite the nontrivial task, rats reached high success rates within two 70-minute sessions.…

The brain learns an internal model of the world by making predictions about upcoming inputs and comparing its predictions with actual incoming sensory information. Prediction errors are essential for learning an accurate internal representation of the world because they indicate where the internal representation needs…

For visual perception to be unaffected by viewing conditions, animals must adapt their sensitivity to changing visual statistics, such as mean illumination. Consistently, photoreceptors in many species control their luminance gain and encode relative changes in luminance [1,2], termed contrast. However, this early…

Neurons in the brain communicate through action potentials (spikes) that are transmitted through chemical synapses. Throughout the last decades, the question how networks of spiking neurons represent and process information has remained an important challenge. Some progress has resulted from a recent family of…

Transcriptomics has revealed the exquisite diversity of cortical inhibitory neurons, but it is not known whether these fine molecular subtypes have correspondingly diverse activity patterns in the living brain. Here, we show that inhibitory subtypes in primary visual cortex (V1) have diverse correlates with brain…

The computational principles driving the transformation of sound information throughout the auditory system remains an intense subject of research. Here, we used large-scale samples of neuronal activity from the auditory cortex, thalamus and inferior colliculus in mice and from a detailed cochlea model to identify key…