Bold Signal
BOLD signal
A Network for Computing Value Equilibrium in the Human Medial Prefrontal Corte
Humans and other animals make decisions in order to satisfy their goals. However, it remains unknown how neural circuits compute which of multiple possible goals should be pursued (e.g., when balancing hunger and thirst) and how to combine these signals with estimates of available reward alternatives. Here, humans undergoing fMRI accumulated two distinct assets over a sequence of trials. Financial outcomes depended on the minimum cumulate of either asset, creating a need to maintain “value equilibrium” by redressing any imbalance among the assets. Blood-oxygen-level-dependent (BOLD) signals in the rostral anterior cingulate cortex (rACC) tracked the level of imbalance among goals, whereas the ventromedial prefrontal cortex (vmPFC) signaled the level of redress incurred by a choice rather than the overall amount received. These results suggest that a network of medial frontal brain regions compute a value signal that maintains value equilibrium among internal goals.
Race and the brain: Insights from the neural systems of emotion and decisions
Investigations of the neural systems mediating the processing of social groups defined by race, specifically Black and White race groups in American participants, reveals significant overlap with brain mechanisms involved in emotion. This talk will provide an overview of research on the neuroscience of race and emotion, focusing on implicit race attitudes. Implicit race attitudes are expressed without conscious effort and control, and contrast with explicit, conscious attitudes. In spite of sharp decline in the expression of explicit, negative attitudes towards outgroup race members over the last half century, negative implicit attitudes persist, even in the face of strong egalitarian goals and beliefs. Early research demonstrated that implicit, but not explicit, negative attitudes towards outgroup race members correlate with blood oxygenation level dependent (BOLD) signal in the amygdala – a region implicated in threat representations, as well as emotion’s influence on cognition. Building on this initial finding, we demonstrate how learning and decisions may be modulated by implicit race attitudes and involve neural systems mediating emotion, learning and choice. Finally, we discuss techniques that may diminish the unintentional expression of negative, implicit race attitudes.
Multitask performance humans and deep neural networks
Humans and other primates exhibit rich and versatile behaviour, switching nimbly between tasks as the environmental context requires. I will discuss the neural coding patterns that make this possible in humans and deep networks. First, using deep network simulations, I will characterise two distinct solutions to task acquisition (“lazy” and “rich” learning) which trade off learning speed for robustness, and depend on the initial weights scale and network sparsity. I will chart the predictions of these two schemes for a context-dependent decision-making task, showing that the rich solution is to project task representations onto orthogonal planes on a low-dimensional embedding space. Using behavioural testing and functional neuroimaging in humans, we observe BOLD signals in human prefrontal cortex whose dimensionality and neural geometry are consistent with the rich learning regime. Next, I will discuss the problem of continual learning, showing that behaviourally, humans (unlike vanilla neural networks) learn more effectively when conditions are blocked than interleaved. I will show how this counterintuitive pattern of behaviour can be recreated in neural networks by assuming that information is normalised and temporally clustered (via Hebbian learning) alongside supervised training. Together, this work offers a picture of how humans learn to partition knowledge in the service of structured behaviour, and offers a roadmap for building neural networks that adopt similar principles in the service of multitask learning. This is work with Andrew Saxe, Timo Flesch, David Nagy, and others.
Narrowband fMRI BOLD signal entropy predicts neonatal age
FENS Forum 2024
Somatosensory evoked BOLD signals with ultra-high temporal resolution
FENS Forum 2024