Seminars

Academic bullying is a serious issue that affects all disciplines and people of all levels of experience. To create a truly safe, productive, and vibrant environment in academia requires coordinated and collaborative input as well as the action of a variety of stakeholders, including scholarly communities, funding agencies, and institutions. This talk will focus on a framework of integrated responding, in which stakeholders as responsible and response-able parties could proactively collaborate and coordinate to reduce the incidence and consequences of academic bullying while at the same time building constructive academic cultures. The outcome of such a framework would be to create novel entities and actions that accelerate successful responses to academic bullying.

In most animal species including humans, commissural axons connect neurons on the left and right side of the nervous system. In humans, abnormal axon midline crossing during development causes a whole range of neurological disorders ranging from congenital mirror movements, horizontal gaze palsy, scoliosis or binocular vision deficits. The mechanisms which guide axons across the CNS midline were thought to be evolutionary conserved but our recent results suggesting that they differ across vertebrates. I will discuss the evolution of visual projection laterality during vertebrate evolution. In most vertebrates, camera-style eyes contain retinal ganglion cell (RGC) neurons projecting to visual centers on both sides of the brain. However, in fish, RGCs are thought to only innervate the contralateral side. Using 3D imaging and tissue clearing we found that bilateral visual projections exist in non-teleost fishes. We also found that the developmental program specifying visual system laterality differs between fishes and mammals. We are currently using various strategies to discover genes controlling the development of visual projections. I will also present ongoing work using 3D imaging techniques to study the development of the visual system in human embryo.

GABAergic interneurons are chiefly responsible for controlling the activity of local circuits in the cortex. Chandelier cells (ChCs) are a type of GABAergic interneuron that control the output of hundreds of neighbouring pyramidal cells through axo-axonic synapses which target the axon initial segment (AIS). Despite their importance in modulating circuit activity, our knowledge of the development and function of axo-axonic synapses remains elusive. We have investigated the emergence and plasticity of axo-axonic synapses in layer 2/3 of the somatosensory cortex (S1) and found that ChCs follow what appear to be homeostatic rules when forming synapses with pyramidal neurons. We are currently implementing in vivo techniques to image the process of axo-axonic synapse formation during development and uncover the dynamics of synaptogenesis and pruning at the AIS. In addition, we are using an all-optical approach to both activate and measure the activity of chandelier cells and their postsynaptic partners in the primary visual cortex (V1) and somatosensory cortex (S1) in mice, also during development. We aim to provide a structural and functional description of the emergence and plasticity of a GABAergic synapse type in the cortex.

New tasks are often similar in structure to old ones. Animals that take advantage of such conserved or “abstract” task structures can master new tasks with minimal training. To understand the neural basis of this abstraction, we developed a novel behavioural paradigm for mice: the “ABCD” task, and recorded from their medial frontal neurons as they learned. Animals learned multiple tasks where they had to visit 4 rewarded locations on a spatial maze in sequence, which defined a sequence of four “task states” (ABCD). Tasks shared the same circular transition structure (… ABCDABCD …) but differed in the spatial arrangement of rewards. As well as improving across tasks, mice inferred that A followed D (i.e. completed the loop) on the very first trial of a new task. This “zero-shot inference” is only possible if animals had learned the abstract structure of the task. Across tasks, individual medial Frontal Cortex (mFC) neurons maintained their tuning to the phase of an animal’s trajectory between rewards but not their tuning to task states, even in the absence of spatial tuning. Intriguingly, groups of mFC neurons formed modules of coherently remapping neurons that maintained their tuning relationships across tasks. Such tuning relationships were expressed as replay/preplay during sleep, consistent with an internal organisation of activity into multiple, task-matched ring attractors. Remarkably, these modules were anchored to spatial locations: neurons were tuned to specific task space “distances” from a particular spatial location. These newly discovered “Spatially Anchored Task clocks” (SATs), suggest a novel algorithm for solving abstraction tasks. Using computational modelling, we show that SATs can perform zero-shot inference on new tasks in the absence of plasticity and guide optimal policy in the absence of continual planning. These findings provide novel insights into the Frontal mechanisms mediating abstraction and flexible behaviour.

The way we represent and perceive time has crucial implications for studying temporality in conscious experience. Contrasting positions posit that temporal information is separately abstracted out like any other perceptual property, or that time is represented through representations having temporal properties themselves. To add to this debate, we investigated alterations in felt time in conditions where only conscious visual experience is altered while a bistable figure remains physically unchanged. In this talk, I will discuss two studies that we have done in relation to answering this question. In study 1, we investigated whether perceptual switches in fixed intervals altered felt time. In three experiments we showed that a break in visual experience (via a perceptual switch) also leads to a break in felt time. In study 2, we are currently looking at figure-ground perception in ambigous displays. Here, in experiment 1 we show that differences in flicker frequencies on ambigous regions can induce figure-ground segregation. To see if a reverse complementarity exists for felt time, we ask participants to view ambigous regions as figure/ground and show that they have different temporal resolutions for the same region based on whether it is seen as figure or background. Overall, the two studies provide evidence for temporal mirroring and isomorphism in visual experience, arguing for a link between the timing of experience and time perception.

Quantifying the timing (duration and frequency) of brief visual events is vital to human perception, multisensory integration and action planning. For example, this allows us to follow and interact with the precise timing of speech and sports. Here we investigate how visual event timing is represented and transformed across the brain’s hierarchy: from sensory processing areas, through multisensory integration areas, to frontal action planning areas. We hypothesized that the dynamics of neural responses to sensory events in sensory processing areas allows derivation of event timing representations. This would allow higher-level processes such as multisensory integration and action planning to use sensory timing information, without the need for specialized central pacemakers or processes. Using 7T fMRI and neural model-based analyses, we found responses that monotonically increase in amplitude with visual event duration and frequency, becoming increasingly clear from primary visual cortex to lateral occipital visual field maps. Beginning in area MT/V5, we found a gradual transition from monotonic to tuned responses, with response amplitudes peaking at different event timings in different recording sites. While monotonic response components were limited to the retinotopic location of the visual stimulus, timing-tuned response components were independent of the recording sites' preferred visual field positions. These tuned responses formed a network of topographically organized timing maps in superior parietal, postcentral and frontal areas. From anterior to posterior timing maps, multiple events were increasingly integrated, response selectivity narrowed, and responses focused increasingly on the middle of the presented timing range. These results suggest that responses to event timing are transformed from the human brain’s sensory areas to the association cortices, with the event’s temporal properties being increasingly abstracted from the response dynamics and locations of early sensory processing. The resulting abstracted representation of event timing is then propagated through areas implicated in multisensory integration and action planning.

How do children learn to read in different countries? How do deficits in various components of the reading network affect learning outcomes? What are the consequences of such deficits in different languages? In this talk, I will present a full-blown developmentally plausible computational model of reading acquisition that has been implemented in English, French, Italian and German. The model can simulate individual learning trajectories and intervention outcomes on the basis of three component skills: orthography, phonology, and vocabulary. I will use the model to show how cross-language differences affect the learning-to-read process in different languages and to investigate to what extent similar deficits will produce similar or different manifestations of dyslexia in different languages.

Resting-state functional magnetic resonance imaging (MRI) has yielded seemingly disparate insights into large-scale organization of the human brain. The brain’s large-scale organization can be divided into two broad categories: zero-lag representations of functional connectivity structure and time-lag representations of traveling wave or propagation structure. In this study, we sought to unify observed phenomena across these two categories in the form of three low-frequency spatiotemporal patterns composed of a mixture of standing and traveling wave dynamics. We showed that a range of empirical phenomena, including functional connectivity gradients, the task-positive/task-negative anti-correlation pattern, the global signal, time-lag propagation patterns, the quasiperiodic pattern and the functional connectome network structure, are manifestations of these three spatiotemporal patterns. These patterns account for much of the global spatial structure that underlies functional connectivity analyses and unifies phenomena in resting-state functional MRI previously thought distinct.

Space is the universal donor for relations" (Gentner, 2014). This quote is the foundation of my talk. I will explore how and why visual representations and analogies are related, and why. I will also explore how considering the relation between analogy and spatial reasoning can shed light on why and how spatial thinking is correlated with learning in STEM fields. For example, I will consider children’s numbers sense and learning of the number line from the perspective of analogical reasoning.

On September 22, 2022 we will celebrate the 20th anniversary of The Picower Institute for Learning and Memory with an Exhibition Symposium — a day-long hybrid event highlighting "Two Decades of Discovery & Impact" since the launch of the Institute by a transformational gift from Barbara and Jeffry Picower. The symposium will feature a range of lay-friendly brain science talks from Picower Institute faculty and their alumni with opportunities to informally interact at lunch and at the reception that will follow the talks.

Epileptic seizures render the brain uniquely dependent on energy producing pathways. Studies in our laboratory have been focused on the role of redox processes and mitochondria in the context of abnormal neuronal excitability associated with epilepsy. We have shown that that status epilepticus (SE) alters mitochondrial and cellular redox status, energetics and function and conversely, that reactive oxygen species and resultant dysfunction can lead to chronic epilepsy. Oxidative stress and neuroinflammatory pathways have considerable crosstalk and targeting redox processes has recently been shown to control neuroinflammation and excitability. Understanding the role of metabolic and redox processes can enable the development of novel therapeutics to control epilepsy and/or its comorbidities.

The brain makes decisions by accumulating evidence until there is enough to stop and choose. Neural mechanisms of evidence accumulation are well established in association cortex, but the site and mechanism of termination is unknown. Here, we elucidate a mechanism for termination by neurons in the primate superior colliculus. We recorded simultaneously from neurons in lateral intraparietal cortex (LIP) and the superior colliculus (SC) while monkeys made perceptual decisions, reported by eye-movements. Single-trial analyses revealed distinct dynamics: LIP tracked the accumulation of evidence on each decision, and SC generated one burst at the end of the decision, occasionally preceded by smaller bursts. We hypothesized that the bursts manifest a threshold mechanism applied to LIP activity to terminate the decision. Focal inactivation of SC produced behavioral effects diagnostic of an impaired threshold sensor, requiring a stronger LIP signal to terminate a decision. The results reveal the transformation from deliberation to commitment.

Electrophysiological recordings during perceptual decision tasks in monkeys suggest that the degree of confidence in a decision is based on a simple neural signal produced by the neural decision process. Attractor neural networks provide an appropriate biophysical modeling framework, and account for the experimental results very well. However, it remains unclear whether attractor neural networks can account for confidence reports in humans. We present the results from an experiment in which participants are asked to perform an orientation discrimination task, followed by a confidence judgment. Here we show that an attractor neural network model quantitatively reproduces, for each participant, the relations between accuracy, response times and confidence. We show that the attractor neural network also accounts for confidence-specific sequential effects observed in the experiment (participants are faster on trials following high confidence trials), as well as non confidence-specific sequential effects. Remarkably, this is obtained as an inevitable outcome of the network dynamics, without any feedback specific to the previous decision (that would result in, e.g., a change in the model parameters before the onset of the next trial). Our results thus suggest that a metacognitive process such as confidence in one’s decision is linked to the intrinsically nonlinear dynamics of the decision-making neural network.

Chronic exercise is a powerful intervention that lowers the incidence of most age-related diseases while promoting healthy metabolism in humans. However, illness, injury or age prevent many humans from consistently exercising. Thus, identification of molecular targets that can mimic the benefits of exercise would be a valuable tool to improve health outcomes of humans with neurodegenerative or mitochondrial diseases, or those with enforced sedentary lifestyles. Using a novel exercise platform for Drosophila, we have identified octopaminergic neurons as a key subset of neurons that are critical for the exercise response, and shown that periodic daily stimulation of these neurons can induce a systemic exercise response in sedentary flies. Octopamine is released into circulation where it signals through various octopamine receptors in target tissues and induces gene expression changes similar to exercise. In particular, we have identified several key molecules that respond to octopamine in skeletal muscle, including the mTOR modulator Sestrin, the PGC-1α homolog Spargel, and the FNDC5/Irisin homolog Iditarod. We are currently testing these molecules as potential therapies for multiple diseases that reduce mobility, including the PolyQ disease SCA2 and the mitochondrial disease Barth syndrome.

A central goal in neuroscience is to understand how orchestrated computations in the brain arise from the properties of single neurons and networks of such neurons. Answering this question requires theoretical advances that shine light into the ‘black box’ of representations in neural circuits. In this talk, we will demonstrate theoretical approaches that help describe how cognitive and behavioral task implementations emerge from the structure in neural populations and from biologically plausible neural networks. First, we will introduce an analytic theory that connects geometric structures that arise from neural responses (i.e., neural manifolds) to the neural population’s efficiency in implementing a task. In particular, this theory describes a perceptron’s capacity for linearly classifying object categories based on the underlying neural manifolds’ structural properties. Next, we will describe how such methods can, in fact, open the ‘black box’ of distributed neuronal circuits in a range of experimental neural datasets. In particular, our method overcomes the limitations of traditional dimensionality reduction techniques, as it operates directly on the high-dimensional representations, rather than relying on low-dimensionality assumptions for visualization. Furthermore, this method allows for simultaneous multi-level analysis, by measuring geometric properties in neural population data, and estimating the amount of task information embedded in the same population. These geometric frameworks are general and can be used across different brain areas and task modalities, as demonstrated in the work of ours and others, ranging from the visual cortex to parietal cortex to hippocampus, and from calcium imaging to electrophysiology to fMRI datasets. Finally, we will discuss our recent efforts to fully extend this multi-level description of neural populations, by (1) investigating how single neuron properties shape the representation geometry in early sensory areas, and by (2) understanding how task-efficient neural manifolds emerge in biologically-constrained neural networks. By extending our mathematical toolkit for analyzing representations underlying complex neuronal networks, we hope to contribute to the long-term challenge of understanding the neuronal basis of tasks and behaviors.

PROGRAM: 16:00 - 16:30 Rebuild the Academy: Supporting academic mothers during COVID-19 and beyond with Robinson W. Fulweiler & Sarah W. Davies --- 16:30 - 17:00 Experiences with academia and family life by Siri Leknes (Norway-based) and Rachel Buckley (USA-based)--- 17:00 - 17:30 Questions and discussion