Behavioral and Neural bases of Subcomponents of the Attentional Blink

Abstract

Attention enables us to select relevant stimuli for enhanced sensory processing and decision-making. Yet, our ability to pay attention is severely capacity limited. This limitation is clearly revealed when we seek to perform multiple tasks simultaneously or to tackle multiple goals in rapid succession. A prime example of this capacity limitation is the phenomenon of the attentional blink1. When multiple targets are presented sequentially – in a rapid serial visual stream – individuals are often unable to accurately detect and identify the second target (T2), presented in close temporal proximity (200-500 ms) to the first target. Past studies1–3 on the attentional blink (AB) have predominantly considered it a monolithic phenomenon. However, recent findings suggest that attention operates through distinct, dissociable components: one that enhances perceptual sensitivity (sensory prioritization) and another that influences decision-making processes (decisional prioritization)4–7. Notably, all prior the attentional blink investigations, to the best of our knowledge, have utilized simple detection or identification tasks alongside psychophysical models. These methodologies cannot reliably distinguish between these two crucial components4–7. As a result, which specific attentional component – sensitivity or bias – is compromised during the attentional blink is not known. Moreover, does the attentional blink impair the ability to detect T2’s presence or discriminating T2’s features, or both? Furthermore, do the neural mechanisms underlying these detection or discrimination deficits induced by the attentional blink operate through common or distinct pathways?

In this thesis, I report four studies, each of which addresses one of these key questions. In the first study, I investigated the behavioral bases of the attentional blink dissecting it into its components and subcomponents. In particular, I addressed which specific attentional component – sensitivity or bias – and which specific subcomponent – detection or discrimination – gets impaired during the attentional blink. I addressed this question with a multialternative task and novel signal detection model, which decouples sensitivity from bias effects. I found that the attentional blink impairs specifically one component of attention – sensitivity – while leaving the other component – bias – unaffected . Moreover, this impairment affected not only detection but also discrimination of T2 features. This dissection enabled us to study the neural underpinnings of these deficits and to identify whether these are common or dissociable. [1]

In my second study, building upon the behavioral findings, I sought to elucidate the electrophysiological correlates underlying the two subcomponents (detection and discrimination deficits) of the attentional blink. I employed whole-brain EEG to record participants' electrophysiological activity during an attentional blink task designed to dissociate T2 detection and discrimination. The results revealed distinct neural markers for the sensitivity deficits associated with the attentional blink, mapped onto the separate subcomponents. Specifically, amplitudes of the parietooccipital N2p and P3 event-related potential components were modulated by target detection deficits, whereas long-range high-beta band (20-30 Hz) coherence between frontoparietal electrodes emerged as a neural marker for target discrimination deficits. [1]

In my third study, I delved deeper into the pharmacological underpinnings of the attentional blink's subcomponents (detection and discrimination deficits) by focusing on the right posterior parietal cortex (rPPC). This anatomical region has been strongly implicated in the attentional blink through local inhibitory mechanisms8–12. The study aimed to elucidate the rPPC's specific role in mediating each subcomponent. I employed a combined approach of model-based psychophysics and magnetic resonance spectroscopy (MRS). The findings revealed a selective correlation between the levels of the inhibitory neurotransmitter, gamma-aminobutyric acid (GABA) in the rPPC and detection, but not discrimination, deficits induced by the attentional blink. Moreover, I demonstrate, for the first time, that such an association persists, even after controlling for overall task difficulty, an aspect overlooked in many previous studies of attention. [2]

In my fourth study, I explored the structural underpinnings of the attentional blink's induced detection and discrimination deficits. By combining multi-alternative behavioral tasks with diffusion magnetic resonance imaging (dMRI), I aimed to differentiate the structural correlates of these subcomponents. I focused my investigation on the right posterior parietal cortex (rPPC), examining both its gray matter microstructural properties and white matter fiber connectivity. I show that local microstructural markers within the inferior parietal lobule (IPL), particularly fractional anisotropy (FA), robustly predicts GABA level modulation and behavioral detection deficits. Conversely, global connectivity measures between the inferior lobule (IPL) and multiple cortical regions predicts discrimination deficits. [3]

In conclusion, this thesis presents a novel multi-alternative task and a powerful model to dissect the attentional blink into distinct subcomponents – detection and discrimination deficits. This framework proved instrumental in our subsequent studies investigating the neural mechanisms behind these subcomponents. Converging evidence from three distinct modalities – electrophysiology, pharmacology, and structural neuroimaging –show that the neural substrates underlying these deficits are dissociable. Local markers, such as parietal event-related potentials (ERPs), GABAergic activity in the right posterior parietal cortex (rPPC), and rPPC microstructural properties, were primarily associated with detection deficits. Conversely, global markers reflecting long-range synchronization or white matter fiber connectivity emerged as neural markers of discrimination deficits.

These findings hold significant implications for various research fields. Researchers in systems, cognitive, and computational neuroscience, particularly those investigating the neural mechanisms of attention and working memory, may find our model and findings relevant. Additionally, our work may inform clinical researchers studying attention deficit disorders (ADD/ADHD): understanding the neural mechanisms underlying attention deficits may pave the way for developing rational therapeutic strategies for managing and treating these disorders.

Bibliography: [1] Halder S., Raya D.V., & Sridharan D (2024). Distinct neural bases of subcomponents of the attentional blink, eLife (reviewed preprint and one round of revision submitted). https://doi.org/10.7554/eLife.97098.1 [2] Halder S and Sridharan D. (2024) Parietal inhibition selectively mediates the detection subcomponent of the attentional blink (In review, Nature Communication). [3] Halder S., Chandrasekhar D. & Sridharan D. (2024) Connectivity correlates of detection of and discrimination bottlenecks underlying the attentional blink. (In preparation).