Neurocognitive therapeutics: from concept to application in the treatment of negative attention bias

There is growing interest in the use of neuroimaging for the direct treatment of mental illness. Here, we present a new framework for such treatment, neurocognitive therapeutics. What distinguishes neurocognitive therapeutics from prior approaches is the use of precise brain-decoding techniques within a real-time feedback system, in order to adapt treatment online and tailor feedback to individuals’ needs. We report an initial feasibility study that uses this framework to alter negative attention bias in a small number of patients experiencing significant mood symptoms. The results are consistent with the promise of neurocognitive therapeutics to improve mood symptoms and alter brain networks mediating attentional control. Future work should focus on optimizing the approach, validating its effectiveness, and expanding the scope of targeted disorders

Attention and memory in real time

Information streams towards the brain at every moment. The nervous system is responsible for processing this information without substantial delays, in order to attend to important information and store memories for future use. Accordingly, for neuroscientists, I propose that it is not sufficient to be able to deduce what was happening in the brain, but we should also understand what is happening in the moment. Real-time neural analyses offer the opportunity to do so, by closing the loop between experimenter and participant. By tracking neural processes in real time, we can return rapid feedback to modify cognition, such as attention and memory. In Chapter 1, I used this approach to track and provide feedback about fluctuations of sustained attention in real time. When asked to sustain our attention to something, attention naturally fluctuates. I developed a paradigm to deliver real-time feedback about fluctuations of attention concurrent to task performance. Then, I observed how and whether this feedback modified cognitive abilities. This novel approach of closed-loop neurofeedback benefited attention performance and increased the neural discriminability of the attended information. In addition to providing feedback, real-time analyses can also be used to optimize experimental design and influence memory encoding. Information encoded when attention is lapsing is much less likely to be later remembered. In Chapter 2, by monitoring fluctuations of attention, the delivery of information was timed to be at the right or wrong moment, when attention was measured to be high or low. This manipulation affected later memory and contributed to our understanding of the tight link between attention and memory. Finally, after memories have already been encoded, their retrieval can also be manipulated. The retrieval of a memory is facilitated when it occurs in the same context as was present when the memory was initially encoded. In Chapter 3, I used real-time neurofeedback to guide participants closer or farther away from the original encoding context during retrieval, influencing what and how much they remembered. The work presented in this dissertation opens up several avenues to explore and perturb attentional and mnemonic processes and the neural mechanisms that support them

Recognition memory fluctuates with sustained attention regardless of task-relevance

Sustained attention fluctuates over time, affecting task-related processing and memory. However, it is less clear how attentional state affects processing and memory when images are accompanied by irrelevant visual information. We first quantify behavioral signatures of attentional state in an online sample (N1=92) and demonstrate that images presented in high attentional states are better remembered. Next, we test how sustained attention influences memory in two online samples (N2=188, N3=185) when task-irrelevant images are present. We show that high attention leads to better memory for both task-relevant and task-irrelevant images. This suggests that attentional state is not a selective spotlight, but rather affects processing broadly in a manner akin to a “floodlight.” Finally, we show that other components of attention such as selective attention contribute to the mnemonic fate of stimuli. Our findings highlight the necessity of considering and characterizing attention’s unique components and their effects on cognition

Forgetting from lapses of sustained attention

When performing any task for an extended period of time, attention fluctuates between good and bad states. These fluctuations affect performance in the moment, but may also have lasting consequences for what gets encoded into memory. Experiment 1 establishes this relationship between attentional states and memory, by showing that subsequent memory for an item was predicted by a response time index of sustained attention (average response time during the three trials prior to stimulus onset). Experiment 2 strengthens the causal interpretation of this predictive relationship by treating the sustained attention index as an independent variable to trigger the appearance of an encoding trial. Subsequent memory was better when items were triggered from good vs. bad attentional states. Together, these findings suggest that sustained attention can have downstream consequences for what we remember, and they highlight the inferential utility of adaptive experimental designs. By continuously monitoring attention, we can influence what will later be remembered

Predicting visual memory across images and within individuals

A repository of all the code, stimuli, and data with the submitted paper on "Predicting visual memory across images and within individuals"