Cognition seminars

Microglia are the immune cells of the brain, and play increasingly appreciated roles in synapse formation, brain plasticity, and cognition. A growing appreciation that the immune system involved in diseases like schizophrenia, epilepsy, and neurodegenerative diseases has led to renewed interest in how microglia regulate synaptic connectivity. Our group previously identified the IL-1 family cytokine Interleukin-33 (IL-33) as a novel regulator of microglial activation and function. I will discuss a mechanism by which microglia regulate synaptic plasticity and long-term memories by engulfing brain extracellular matrix (ECM) proteins. These studies raise the question of how these pathways may be altered or could be modified in the context of disease.

John O’Keefe is a Professor of Cognitive Neuroscience at UCL and he received the Nobel Prize in Physiology or Medicine in 2014 for his “discoveries of cells that constitute a positioning system in the brain". His revolutionary research on hippocampal place cells provided deeper insight into the neural processes underlying the sense of space. His lab in Sainsbury Wellcome Centre applies a wide range of methods to facilitate our understanding of the role of the entorhinal cortex and hippocampus in spatial memory and the neural mechanisms underlying short-term memories in the amygdala.

My lab seeks to understand how the mammalian brain performs the computations that underlie cognitive functions, including decision-making, short-term memory, and spatial navigation, at the level of the building blocks of the nervous system, cell types and neural populations organized into circuits. We have developed methods to measure, manipulate, and analyze neural circuits across various spatial and temporal scales, including technology for virtual reality, optical imaging, optogenetics, intracellular electrophysiology, molecular sensors, and computational modeling. I will present recent work that uses large scale calcium imaging to reveal the functional organization of the mouse posterior cortex for flexible decision-making during spatial navigation in virtual reality. I will also discuss work that uses optogenetics and calcium imaging during a variety of decision-making tasks to highlight how cognitive experience and context greatly alter the cortical circuits necessary for navigation decisions.

Face matching tests have traditionally been developed to assess human face perception in the neurotypical range, but methods that underlie their development often make it difficult for these measures to be applied in atypical populations (developmental prosopagnosics, super recognizers) due to unadjusted difficulty. We have recently presented the development of the Oxford Face Matching Test, a measure that bases individual item-difficulty on algorithmically derived similarity of presented stimuli. The measure seems useful as it can be given online or in-laboratory, has good discriminability and high test-retest reliability in the neurotypical groups. In addition, it has good validity in separating atypical groups at either of the spectrum ends. In this talk, I examine the stability of the OFMT and other traditionally used measures in atypical groups. On top of the theoretical significance of determining whether reliability of tests is equivalent in atypical population, this is an important question because of the practical concerns of retesting the same participants across different lab groups. Theoretical and practical implications for further test development and data sharing are discussed.

fMRI results have shown that the supplementary motor area (SMA) and the basal ganglia, most often discussed in their roles in generating action, are engaged by beat-based timing even in the absence of movement. Some have argued that the motor system is “recruited” by beat-based timing tasks due to the presence of motor-like timescales, but a deeper understanding of the roles of these motor structures is lacking. Reviewing a body of motor neurophysiology literature and drawing on the “active inference” framework, I argue that we can see the motor and timing functions of these brain areas as examples of dynamic sub-second prediction informed by sensory event timing. I hypothesize that in both cases, sub-second dynamics in SMA predict the progress of a temporal process outside the brain, and direct pathway activation in basal ganglia selects temporal and sensory predictions for the upcoming interval -- the only difference is that in motor processes, these predictions are made manifest through motor effectors. If we can unify our understanding of beat-based timing and motor control, we can draw on the substantial motor neuroscience literature to make conceptual leaps forward in the study of predictive timing and musical rhythm.

Medium-spiny neurons (MSNs) in the striatum are required for interval timing, or the estimation of the time over several seconds via a motor response. We and others have shown that striatal MSNs can encode the duration of temporal intervals via time-dependent ramping activity, progressive monotonic changes in firing rate preceding behaviorally salient points in time. Here, we investigated how timing-related activity within striatal ensembles changes with experience. We leveraged a rodent-optimized interval timing task in which mice ‘switch’ response ports after an amount of time has passed without reward. We report three main results. First, we found that the proportion of MSNs exhibiting time-dependent modulations of firing rate increased after 10 days of task overtraining. Second, temporal decoding by MSN ensembles increased with experience and was largely driven by time-related ramping activity. Finally, we found that time-related ramping activity generalized across both correct and error trials. These results enhance our understanding of striatal temporal processing by demonstrating that time-dependent activity within MSN ensembles evolves with experience and is dissociable from motor- and reward-related processes.

The risks of in utero and early exposure to environmental contaminants, such as heavy metals and persistent organic pollutants, on child neurodevelopment is now established, however our understanding of how these contaminants alter the human brain is very limited. To address this issue, more effort must be made to integrate brain imaging tools with epidemiological studies. In this seminar, I will be presenting EEG and MRI data collected in birth-cohort studies where impairments of cognitive and sensory functions were observed in association with prenatal exposure to mercury, lead, PCB or organophosphate insecticides. Results obtained in children and adolescents suggest that each pollutant might affect different levels of brain processing and that frontal regions are particularly vulnerable.

The eyes send a continuous stream of about two million nerve fibers to the brain, but only a fraction of this information is stored as visual memories. This talk will detail three neurocomputational models that attempt an understanding how the visual system makes on-the-fly decisions about how to encode that information. First, the STST family of models (Bowman & Wyble 2007; Wyble, Potter, Bowman & Nieuwenstein 2011) proposes mechanisms for temporal segmentation of continuous input. The conclusion of this work is that the visual system has mechanisms for rapidly creating brief episodes of attention that highlight important moments in time, and also separates each episode from temporally adjacent neighbors to benefit learning. Next, the RAGNAROC model (Wyble et al. 2019) describes a decision process for determining the spatial focus (or foci) of attention in a spatiotopic field and the neural mechanisms that provide enhancement of targets and suppression of highly distracting information. This work highlights the importance of integrating behavioral and electrophysiological data to provide empirical constraints on a neurally plausible model of spatial attention. The model also highlights how a neural circuit can make decisions in a continuous space, rather than among discrete alternatives. Finally, the binding pool (Swan & Wyble 2014; Hedayati, O’Donnell, Wyble in Prep) provides a mechanism for selectively encoding specific attributes (i.e. color, shape, category) of a visual object to be stored in a consolidated memory representation. The binding pool is akin to a holographic memory system that layers representations of select latent representations corresponding to different attributes of a given object. Moreover, it can bind features into distinct objects by linking them to token placeholders. Future work looks toward combining these models into a coherent framework for understanding the full measure of on-the-fly attentional mechanisms and how they improve learning.

According to the concreteness fading approach, instruction should start with concrete representations and progress stepwise to representations that are more idealized. Various researchers have suggested that concreteness fading is a broadly applicable instructional approach. In this talk, we conceptually analyze examples of concreteness fading in mathematics and various science domains. In this analysis, we draw on theories of analogical and relational reasoning and on the literature about learning with multiple representations. Furthermore, we report on an experimental study in which we employed concreteness fading in advanced physics education. The results of the conceptual analysis and the experimental study indicate that concreteness fading may not be as generalizable as has been suggested. The reasons for this limited generalizability are twofold. First, the types of representations and the relations between them differ across different domains. Second, the instructional goals between domains and the subsequent roles of the representations vary.

My research focuses, broadly speaking, on how emotions impact decision making. Specifically, I am interested in affective biases, a phenomenon known to be important in depression. Using a rodent decision-making task, combined with computational modelling I have investigated how different antidepressant and pro-depressant manipulations that are known to alter mood in humans alter judgement bias, and provided insight into the decision processes that underlie these behaviours. I will also highlight how the combination of behaviour and modelling can provide a truly translation approach, enabling comparison and interpretation of the same cognitive processes between animal and human research.

Classical models of perceptual decision-making assume that animals use a single, consistent strategy to integrate sensory evidence and form decisions during an experiment. In this talk, I aim to convince you that this common view is incorrect. I will show results from applying a latent variable framework, the “GLM-HMM”, to hundreds of thousands of trials of mouse choice data. Our analysis reveals that mice don’t lapse. Instead, mice switch back and forth between engaged and disengaged behavior within a single session, and each mode of behavior lasts tens to hundreds of trials.

In many societal problems, individuals exhibit a conflict between keeping resources (e.g., money, time or attention) to themselves or sharing them with another individual or group. The reasons motivating decisions in favor of others welfare can thereby vary from purely altruistic to completely strategic. Be it the stranger making an effort returning a lost valet to its rightful owner or a co-worker pitching in her fair share in a joint project. Actions like that create an environment that makes living together a pleasant experience. Hence, understanding how decisions determining the welfare of oneself and others are made is important for facilitating this behavior by building institutions that maximize the rate of cooperation in a society. To shed new light on such decision making processes I will present recent evidence from a set of process tracing experiments utilizing eye-tracking and economic games. Experiments will focus on the role of social preferences in the choice construction process and will identify mechanisms (i.e., search and processing depth, information weighting, and ignorance) through which they guide choice behavior. I will in particular focus on the differences and commonalitiesbetween strategic and altruistic decisions. Specifically, investigating to which extent people direct attention towards certain components of the decision situation in a context-dependent manner.

Recent advances in deep learning have produced models that far outstrip human performance in a number of domains. However, where machine learning approaches still fall far short of human-level performance is in the capacity to transfer knowledge across domains. While a human learner will happily apply knowledge acquired in one domain (e.g., mathematics) to a different domain (e.g., cooking; a vinaigrette is really just a ratio between edible fat and acid), machine learning models still struggle profoundly at such tasks. I will present a case that human intelligence might be (at least partially) usefully characterised by our ability to transfer knowledge widely, and a framework that we have developed for learning representations that support such transfer. The model is compared to current machine learning approaches.

The talk will give a tour of Guided Search 6.0 (GS6), the latest evolution of Guided Search. Part 1 describes The Mechanics of Search. Because we cannot recognize more than a few items at a time, selective attention is used to prioritize items for processing. Selective attention to an item allows its features to be bound together into a representation that can be matched to a target template in memory or rejected as a distractor. The binding and recognition of an attended object is modeled as a diffusion process taking > 150 msec/item. Since selection occurs more frequently than that, it follows that multiple items are undergoing recognition at the same time, though asynchronously, making GS6 a hybrid serial and parallel model. If a target is not found, search terminates when an accumulating quitting signal reaches a threshold. Part 2 elaborates on the five sources of Guidance that are combined into a spatial “priority map” to guide the deployment of attention (hence “guided search”). These are (1) top-down and (2) bottom-up feature guidance, (3) prior history (e.g. priming), (4) reward, and (5) scene syntax and semantics. In GS6, the priority map is a dynamic attentional landscape that evolves over the course of search. In part, this is because the visual field is inhomogeneous. Part 3: That inhomogeneity imposes spatial constraints on search that described by three types of “functional visual field” (FVFs): (1) a resolution FVF, (2) an FVF governing exploratory eye movements, and (3) an FVF governing covert deployments of attention. Finally, in Part 4, we will consider that the internal representation of the search target, the “search template” is really two templates: a guiding template and a target template. Put these pieces together and you have GS6.

Classic economists proposed that economic choices rely on the computation and comparison of subjective values. This hypothesis continues to inform economic theory and experimental research, but behavioral measures are ultimately not sufficient to prove the proposal. Consistent with the hypothesis, when agents make choices, neurons in the orbitofrontal cortex (OFC) encode the subjective value of offered and chosen goods. Moreover, neuronal activity in this area suggests the formation of a decision. However, it is unclear whether these neural processes are causally related to choices. More generally, the evidence linking choices to value signals in the brain remains correlational. In my talk, I will present recent results showing that neuronal activity in OFC are causal to economic choices.

Praying mantises are the only insects known to have stereo vision. We used a comparative approach to determine how the mechanisms underlying stereopsis in mantises differ from those underlying primate stereo vision. By testing mantises with virtual 3D targets we showed that mantis stereopsis enables prey capture in complex scenes but the mechanisms underlying it differ from those underlying primate stereopsis. My talk will further discuss how stereopsis combines with second-order motion perception to enable the detection of camouflaged prey by mantises. The talk will highlight the benefits of a comparative approach towards understanding visual cognition.