Latent brain state dynamics distinguish behavioral variability, impaired decision-making, and inattention

Abstract

Children with Attention Deficit Hyperactivity Disorder (ADHD) have prominent deficits in sustained attention that manifest as elevated intra-individual response variability and poor decision-making. Influential neurocognitive models have linked attentional fluctuations to aberrant brain dynamics, but these models have not been tested with computationally rigorous procedures. Here we use a Research Domain Criteria approach, drift-diffusion modeling of behavior, and a novel Bayesian Switching Dynamic System unsupervised learning algorithm, with ultrafast temporal resolution (490 ms) whole-brain task-fMRI data, to investigate latent brain state dynamics of salience, frontoparietal, and default mode networks and their relation to response variability, latent decision-making processes, and inattention. Our analyses revealed that occurrence of a task-optimal latent brain state predicted decreased intra-individual response variability and increased evidence accumulation related to decision-making. In contrast, occurrence and dwell time of a non-optimal latent brain state predicted inattention symptoms and furthermore, in a categorical analysis, distinguished children with ADHD from controls. Importantly, functional connectivity between salience and frontoparietal networks predicted rate of evidence accumulation to a decision threshold, whereas functional connectivity between salience and default mode networks predicted inattention. Taken together, our computational modeling reveals dissociable latent brain state features underlying response variability, impaired decision-making, and inattentional symptoms common to ADHD. Our findings provide novel insights into the neurobiology of attention deficits in children.

Fig. 1. Task paradigm, behavior and latent brain states.

A Illustration of the choice response event-related fMRI task. B Children with ADHD have significantly larger RT standard deviation (Std) and tau than TD children, whereas TD children have significantly higher information accumulation speed (v) than children with ADHD. C RT tau is negatively correlated with information accumulation speed (v) (r = −0.34, p = 0.01). D Regions of interest (ROIs) include key nodes in the salience (SN), frontal-parietal (FPN) and default mode networks (DMN). E Schematic illustration of the BSDS model. F Temporal evolution of latent brain states in the choice response task. Each row represents one subject, each column represent one data point (fMRI volume). G Dynamic changes in posterior probability of latent brain states during the choice response task (averaged across participants).

Fig. 2. Occupancy rate of latent brain state in relation to IIRV.

A The occupancy rate (OR) of latent brain state S1 is negatively correlated with RT std. B OR of latent brain state S1 is negatively correlated with RT tau. C OR of latent brain state S2 is positively correlated with RT std. D OR of latent brain state S2 is positively correlated with RT tau.

Fig. 3. Occupancy rate of latent brain state in relation to deicsion-making and inattention.

A The Occupancy rate of latent brain state S1 is positively correlated with evidence accumulation speed (v). B The Occupancy rate and mean lifetime of latent brain state S2 predict inattention scores.

Fig. 4. Functional connectivity of latent brain state and its relation to decision-making.

A Latent brain states S1 and B S2 were characterized by their distinct functional connectivity. C Link-by-link analysis showed that strong connectivity within and between key nodes in SN and FPN in S1 than S2 (p < 0.001, FDR corrected). D Multivariate functional connectivity patterns in S1 accurately predict drift rate (v) of the DDM during the simple choice response task (r = 0.41, p = 0.002).

Fig. 5. Functional connectivity of PCC-AI in relation to inattention.

A Inattention scores were associated with functional connectivity between PCC and lAI, and B PCC and rAI in latent brain S2 (ps < 0.05, FDR corrected).