Seminars

We want to understand how the visual system detects and tracks salient stimuli in the environment to initiate and guide specific behaviors (i.e., visual neuroethology). Predator avoidance and prey capture are central selection pressures of animal evolution. Mice use vision to detect aerial predators and hunt insects. I will discuss studies from my group that identify specific circuits and pathways in the early visual system (i.e., the retina and its subcortical targets) mediating predator avoidance and prey capture in mice. Our results highlight the importance of subcellular visual processing in the retina and the alignment of viewing strategies with region- and cell-type-specific retinal ganglion cell projection patterns to the brain.

In many learning and decision scenarios, especially sequential settings like mazes or games, it is easy to state an objective function but difficult to compute it, for instance because this can require enumerating many possible future trajectories. This, in turn, motivates a variety of more tractable approximations which then raise resource-rationality questions about whether and when an efficient agent should invest time or resources in computing decision variables more accurately. Previous work has used a simple all-or-nothing version of this reasoning as a framework to explain many phenomena of automaticity, habits, and compulsion in humans and animals. Here, I present a more finegrained theoretical analysis of deliberation, which attempts to address not just whether to deliberate vs. act, but which of many possible actions and trajectories to consider. Empirically, I first motivate and compare this account to nonlocal representations of spatial trajectories in the rodent place cell system, which are thought to be involved in planning. I also consider its implications, in humans, for variation over time and situations in subjective feelings of mental effort, boredom, and cognitive fatigue. Finally, I present results from a new study using magnetoencephalography in humans to measure subjective consideration of possible trajectories during a sequential learning task, and study its relationship to rational prioritization and to choice behavior.

Distinct synapses influence one another when they undergo changes, with unclear consequences for neuronal dynamics and function. Here we show that synapses can interact such that excitatory currents are naturally normalised and balanced by inhibitory inputs. This happens when classical spike-timing dependent synaptic plasticity rules are extended by additional mechanisms that incorporate the influence of neighbouring synaptic currents and regulate the amplitude of efficacy changes accordingly. The resulting control of excitatory plasticity by inhibitory activation, and vice versa, gives rise to quick and long-lasting memories as seen experimentally in receptive field plasticity paradigms. In models with additional dendritic structure, we observe experimentally reported clustering of co-active synapses that depends on initial connectivity and morphology. Finally, in recurrent neural networks, rich and stable dynamics with high input sensitivity emerge, providing transient activity that resembles recordings from the motor cortex. Our model provides a general framework for codependent plasticity that frames individual synaptic modifications in the context of population-wide changes, allowing us to connect micro-level physiology with behavioural phenomena.

Regulation of information flow in the brain is critical for many forms of behavior. In the process of sensory based decision-making, decisions about future actions are held in memory until enacted, making them potentially vulnerable to distracting sensory input. Therefore, gating of information flow from sensory to motor areas could protect memory from interference during decision-making, but the underlying network mechanisms are not understood. I will present our recent experimental and modeling work describing how information flow from the sensory cortex can be gated by state-dependent frontal cortex dynamics during decision-making in mice. Our results show that communication between brain regions can be regulated via attractor dynamics, which control the degree of commitment to an action, and reveal a novel mechanism of gating of neural information.

Dravet syndrome (DS) is a neurodevelopmental disorder caused by heterozygous loss-of-function of the gene SCN1A encoding the voltage-gated sodium channel subunit Nav1.1, and is defined by treatment-resistant epilepsy, intellectual impairment, and sudden death. However, disease mechanisms remain unclear, as previously-identified deficiency in action potential generation of Nav1.1-expressing parvalbumin-positive fast-spiking GABAergic interneurons (PV-INs) in DS (Scn1a+/-) mice normalizes during development. We used a novel approach that facilitated the assessment of PV-IN function at both early (post-natal day (P) 16-21) and late (P35-56) time points in the same mice. We confirmed that PV-IN spike generation was impaired at P16-21 in all mice (those deceased from SUDEP by P35 and those surviving to P35-56). However, unitary synaptic transmission assessed in PV-IN:principal cell paired recordings was severely dysfunctional selectively in mice recorded at P16-21 that did not survive to P35. Spike generation in surviving mice had normalized by P35-56; yet we again identified abnormalities in synaptic transmission in surviving mice. We propose that early dysfunction of PV-IN spike propagation drives epilepsy severity and risk of sudden death, while persistent dysfunction of spike propagation contributes to chronic DS pathology.

Classic studies show that in many species – from leech and cricket to primate – responses of neural populations can be quite successfully read out using a measure neural population activity termed the population vector. However, despite its successes, detailed analyses have shown that the standard population vector discards substantial amounts of information contained in the responses of a neural population, and so is unlikely to accurately describe how signal communication between parts of the nervous system. I will describe recent theoretical results showing how to modify the population vector expression in order to read out neural responses without information loss, ideally. These results make it possible to quantify the contribution of weakly tuned neurons to perception. I will also discuss numerical methods that can be used to minimize information loss when reading out responses of large neural populations. Presented in the van Vreeswijk Theoretical Neuroscience Seminar series (formerly WWTNS) on 2021-03-03. Recording duration: 00:45:35.

Microorganisms can swim in a variety of environments, interacting with chemicals and other proteins in the fluid. In this talk, we will highlight recent computational methods and results for swimming efficiency and hydrodynamic interactions of swimmers in different fluid environments. Sperm are modeled via a centerline representation where forces are solved for using elastic rod theory. The method of regularized Stokeslets is used to solve the fluid-structure interaction where emergent swimming speeds can be compared to asymptotic analysis. In the case of fluids with extra proteins or cells that may act as friction, swimming speeds may be enhanced, and attraction may not occur. We will also highlight how parameter estimation techniques can be utilized to infer fluid and/or swimmer properties.

The anterior insular cortex (AIC) has been implicated in addictive behaviour, including the loss of control over drug intake, craving and the propensity to relapse. Evidence suggests that the influence of the AIC on drug-related behaviours is complex as in rats exposed to extended access to cocaine self-administration, the AIC was shown to exert a state-dependent, bidirectional influence on the development and expression of loss of control over drug intake, facilitating the latter but impairing the former. However, it is unclear whether this influence of the AIC is confined to stimulant drugs that have marked peripheral sympathomimetic and anxiogenic effects or whether it extends to other addictive drugs, such as opiates, that lack overt acute aversive peripheral effects. We investigated in outbred rats the effects of bilateral excitotoxic lesions of AIC induced both prior to or after long-term exposure to extended access heroin self-administration, on the development and maintenance of escalated heroin intake and the subsequent vulnerability to relapse following abstinence. Compared to sham surgeries, pre-exposure AIC lesions had no effect on the development of loss of control over heroin intake, but lesions made after a history of escalated heroin intake potentiated escalation and also enhanced responding at relapse. These data show that the AIC inhibits or limits the loss of control over heroin intake and propensity to relapse, in marked contrast to its influence on the loss of control over cocaine intake.

Jonathan Whitlock is an associate professor of neuroscience at the Kavli Institute for Systems Neuroscience in Trondheim, Norway. His group combines high-density single-unit recordings with silicone probes and sub-millimeter 3D tracking to study the cortical representation of pose and movement in freely behaving rats. The lecture will introduce his group’s work on neural tuning to pose and movement parietal and motor areas, and will include more recent findings from primary visual, auditory and somatosensory areas

Rigidity is the ability of a system to resist imposed stresses before ultimately undergoing failure. However, disordered materials often contain both rigid and floppy subregions that complicate the utility of taking system-wide averages. I will talk about 3 frameworks capable of connecting the internal structure of disordered materials to their rigidity and/or failure under loading, and describe how my collaborators and I have applied these frameworks to laboratory data on laser-cut lattices and idealized granular materials. These are, in order of increasing physics content: (1) centrality within an adjacency matrix describing its connectivity, (2) Maxwell constraint counting on the full network of frictional contact forces, and (3) the vibrational modes of a synthetic dynamical matrix (Hessian). The first two rely primarily on topology, and the second two contrast the utility of considering interparticle forces (Coulomb failure) vs. the energy landscape. All three methods, while successfully elucidating the origins of rigidity and brittle vs. ductile failure, also provide interesting counterpoints regarding how much information is enough to make predictions.

Concerns about the impact of social media use on adolescent well-being and mental health are common. While the amount of research in this area has increased rapidly over the last 5 years, most outputs are still marred by a multitude of limitations. These shortcomings have left our understanding of social media effects severely limited, holding back both scientific discovery and policy interventions. This talk discusses how developmental, cognitive and neuroscientific approaches might provide a new and improved way of studying social media effects. It will detail new studies in support of this idea, and raise potential avenues for collaborative work across the Cambridge Neuroscience community. As the digital world now (re)shapes what it means for us to live, communicate and develop, only an interdisciplinary approach will allow us to truly understand its impacts.

PIEZO ion channels detect force in cellular membranes. They are expressed in a wide variety of mammalian tissues, including the vasculature, lymphatic system, and the nervous system. We have found that PIEZO2 in sensory neurons is required for the mechanical senses of touch and proprioception, but our understanding of internal organ sensing, interoception, is far behind. I will describe our findings on the role of PIEZO ion channels in the lesser-known interoceptive senses in multiple organ systems.