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Much of sensory neuroscience focuses on presenting stimuli that are chosen by the experimenter because they are parametric and easy to sample and are thought to be behaviorally relevant to the organism. However, it is not generally known what the relevant features are in complex, natural scenes. This work focuses on…
While sleeping, many vertebrate groups alternate between at least two sleep stages: rapid eye movement (REM) and slow wave sleep (SWS), in part characterized by wake-like and synchronous brain activity respectively. Sleep stage alternation has been implicated in learning and memory function experimentally1, and has…
Stimuli trigger a pattern of activity across neurons in cortex, whose firing rates define a stimulus's representation in a high-dimensional vector space. Learning a visuomotor task can affect the responses of visual cortical neurons, but how and why training modifies population-level representations is unclear. One…
Distinguishing near and far visual cues is an essential computation that animals must carry out to guide behavior using vision. When animals move, self-motion creates motion parallax — an important but poorly understood source of depth information — whereby the speed of optic flow generated by self-motion depends on…
The functional visual hierarchy has been widely studied in primates but was only recently revealed in mice. It is thus unclear whether different areas along the mouse visual hierarchy also represent distinct levels of visual abstraction. To address this question, we carefully designed a visual stimulus set consisting…
Cognitive maps are hypothesized memory systems that organize sensory experience into knowledge that can be used flexibly in novel scenarios, such as finding new routes during navigation. Evidence for this hypothesis has been largely limited to experiments with fully observable sensory information. However, to serve as…
Humans are capable of generalising local pairwise relations to transitively infer global relationships between items, states or events. Recent research has shown that asymmetric learning, where beliefs about only the winners (or losers) of local comparisons are updated, is well-suited to allow human and artificial…
Birdsong is an important model for vocal learning and sequential motor behavior. Similarly to human language, songs, notably those of Bengalese finches and canaries, exhibit higher-order sequence structure, meaning that the statistics of one syllable may depend on a number of previous syllables. However, this number…
To learn a new task and predict accurately on new stimuli, the brain must extract patterns from limited observations. The learning rule and initial synaptic weights determine how well a network will generalize on new data. Here, we investigate how initial synaptic variability and representation learning affect the…
When foraging in dynamic and uncertain environments, animals can benefit from basing their decisions on smart inferences about hidden properties of the world. Typical theoretical approaches for understanding the strategies that animals use in such settings combine Bayesian inference and value iteration to derive…
Parkinson's disease (PD), characterized by the absence of dopamine in the striatum[1], is caused by the death of the substantia nigra pars compacta dopamine (SNcDA) neurons in the mid-brain. The cause of this cell loss is attributed to irreparable damage due to a dysregulation cascade originating from excess cytosolic…
Recent work [Yamins 2014, Bashivan 2019, Bao 2020] has shown that the initial responses of individual neurons in the ventral stream of visual cortex can be predicted with high accuracy by deep neural networks trained on challenging visual classification problems. Similar results have been obtained for voxels of…
Understanding how the brain builds maps of novel environments on behavioral timescales (seconds-minutes) is a fundamental question for neuroscience. Theoretical works posit a Hebbian plasticity mechanism for integrating novel landmarks [1]. Drosophila have been shown to use such a mechanism to integrate novel…
Network models are often designed to capture selective aspects of cortical circuits. On one end, mechanistic models such as balanced spiking networks resemble activity regimes observed in data, but are often limited to simple computations. On the other end, functional models like trained deep networks can show…
How does intrinsic network structure shape spontaneous coordinated neural dynamics? Previous work has shown that overlapping tectal neuronal assemblies can be circuit mechanisms for robust visual detection [1]. To better understand how these assemblies give rise to emergent dynamics, we use single-photon calcium…
Precise movement execution often relies on adequately planning the upcoming action, a process that is largely mediated by the dorsal premotor (PMd) and primary motor (M1) cortices. Due to their anatomical and functional similarities, PMd and M1 are commonly assumed to contain similar planning- related information.…
Mounting evidence suggests that the prefrontal cortex encodes environmental uncertainty for value-based decision-making. However, how uncertainty influences goal-seeking at the neural level remains elusive. We used human fMRI data collected with a two-stage Markov decision task to investigate the neural embeddings of…
Learning in neural circuits manifests via slow changes in activity driving behaviour changes. Uncovering how the coordination of plasticity mechanisms found in the brain leads to such changes is a difficult problem, chiefly because we do not have access to the synaptic parameters underlying neural computation.…
Understanding the basis of shared, across trial fluctuations in neural activity in mammalian cortex is critical to uncovering the nature of information processing in the brain. This correlated variability has often been related to the structure of cortical connectivity since variability not accounted for by signal…
An important goal of the nervous system is to integrate sensory cues with an animal’s current behavior state to generate a suitable motor response. However, the underlying neuronal mechanism behind how neural circuits integrate sensory and behavior signals remains unknown. To answer this question, we performed a…
To make decisions in a dynamic world, animals adjust their behavior in response to environmental feedback. To understand how this flexibility is achieved, we seek to understand how the nervous system learns from choice outcomes. Theories proposed that norepinephrine (NE) neurons in the locus coeruleus (LC) modulate…
To navigate, we must continuously estimate the direction we are headed in, and we must use this information to guide our path toward our goal (Schöne, 2014). Direction estimation is accomplished by ring attractor networks in the head direction system (Knierim et al., 2012, Hulse et al., 2020). However, we do not…
Cortical activity is characterized by state-specific dynamics arising from the interplay between connectivity, cellular diversity, and intrinsic properties. During non-Rapid Eye Movement (NREM) sleep, cortical population activity alternates between periods of neuronal firing (“UP” states) and neuronal silence (“DOWN”…
Flexible navigation requires animals to form accurate and persistent internal representations of continuous spatial variables. Such representations—e.g., those carried by head direction (HD), grid, and place cells—can guide behavior even in the absence of localizing sensory cues. Theories of mammalian HD cells propose…