EEG source derived salience network coupling supports real-world attention switching.

While the brain mechanisms underlying selective attention have been studied in great detail in controlled laboratory settings, it is less clear how these processes function in the context of a real-world self-paced task. Here, we investigated engagement on a real-world computerized task equivalent to a standard academic test that consisted of solving high-school level problems in a self-paced manner. In this task, we used EEG-source derived estimates of effective coupling between brain sources to characterize the neural mechanisms underlying switches of sustained attention from the attentive on-task state to the distracted off-task state. Specifically, since the salience network has been implicated in sustained attention and attention switching, we conducted a hypothesis-driven analysis of effective coupling between the core nodes of the salience network, the anterior insula (AI) and the anterior cingulate cortex (ACC). As per our hypothesis, we found an increase in AI - > ACC effective coupling that occurs during the transitions of attention from on-task focused to off-task distracted state. This research may inform the development of future neural function-targeted brain-computer interfaces to enhance sustained attention.

Distinct neural activations correlate with maximization of reward magnitude versus frequency.

Choice selection strategies and decision-making are typically investigated using multiple-choice gambling paradigms that require participants to maximize expected value of rewards. However, research shows that performance in such paradigms suffers from individual biases towards the frequency of gains such that users often choose smaller frequent gains over larger rarely occurring gains, also referred to as melioration. To understand the basis of this subjective tradeoff, we used a simple 2-choice reward task paradigm in 186 healthy human adult subjects sampled across the adult lifespan. Cortical source reconstruction of simultaneously recorded electroencephalography suggested distinct neural correlates for maximizing reward magnitude versus frequency. We found that activations in the parahippocampal and entorhinal areas, which are typically linked to memory function, specifically correlated with maximization of reward magnitude. In contrast, maximization of reward frequency was correlated with activations in the lateral orbitofrontal cortices and operculum, typical areas involved in reward processing. These findings reveal distinct neural processes serving reward frequency versus magnitude maximization that can have clinical translational utility to optimize decision-making.

Mapping cognitive brain functions at scale.

A fundamental set of cognitive abilities enable humans to efficiently process goal-relevant information, suppress irrelevant distractions, maintain information in working memory, and act flexibly in different behavioral contexts. Yet, studies of human cognition and their underlying neural mechanisms usually evaluate these cognitive constructs in silos, instead of comprehensively in-tandem within the same individual. Here, we developed a scalable, mobile platform, "BrainE" (short for Brain Engagement), to rapidly assay several essential aspects of cognition simultaneous with wireless electroencephalography (EEG) recordings. Using BrainE, we rapidly assessed five aspects of cognition including (1) selective attention, (2) response inhibition, (3) working memory, (4) flanker interference and (5) emotion interference processing, in 102 healthy young adults. We evaluated stimulus encoding in all tasks using the EEG neural recordings, and isolated the cortical sources of the spectrotemporal EEG dynamics. Additionally, we used BrainE in a two-visit study in 24 young adults to investigate the reliability of the neuro-cognitive data as well as its plasticity to transcranial magnetic stimulation (TMS). We found that stimulus encoding on multiple cognitive tasks could be rapidly assessed, identifying common as well as distinct task processes in both sensory and cognitive control brain regions. Event related synchronization (ERS) in the theta (3-7 Hz) and alpha (8-12 Hz) frequencies as well as event related desynchronization (ERD) in the beta frequencies (13-30 Hz) were distinctly observed in each task. The observed ERS/ERD effects were overall anticorrelated. The two-visit study confirmed high test-retest reliability for both cognitive and neural data, and neural responses showed specific TMS protocol driven modulation. We also show that the global cognitive neural responses are sensitive to mental health symptom self-reports. This first study with the BrainE platform showcases its utility in studying neuro-cognitive dynamics in a rapid and scalable fashion.

Closed-loop digital meditation for neurocognitive and behavioral development in adolescents with childhood neglect.

Adverse childhood experiences are linked to poor attentive behaviors during adolescence, as well as increased risk for mental health disorders in adults. However, no study has yet tested targeted interventions to optimize neurocognitive processes in this population. Here, we investigated closed-loop digital interventions in a double-blind randomized controlled study in adolescents with childhood neglect, and evaluated the outcomes using multimodal assessments of neuroimaging, cognitive, behavioral, and academic evaluations. In the primary neuroimaging results, we demonstrate that a closed-loop digital meditation intervention can strengthen functional connectivity of the dorsal anterior cingulate cortex (dACC) in the cingulo-opercular network, which is critically developing during the adolescent period. Second, this intervention enhanced sustained attention and interference-resolution abilities, and also reduced behavioral hyperactivity at a 1-year follow-up. Superior academic performance was additionally observed in adolescents who underwent the digital meditation intervention. Finally, changes in dACC functional connectivity significantly correlated with improvements in sustained attention, hyperactivity, and academic performance. This first study demonstrates that closed-loop digital meditation practice can facilitate development of important aspects of neurocognition and real-life behaviors in adolescents with early childhood neglect.

Respiratory regulation & interactions with neuro-cognitive circuitry.

It is increasingly being recognized that active control of breathing - a key aspect of ancient Vedic meditative practices, can relieve stress and anxiety and improve cognition. However, the underlying mechanisms of respiratory modulation of neurophysiology are just beginning to be elucidated. Research shows that brainstem circuits involved in the motor control of respiration receive input from and can directly modulate activity in subcortical circuits, affecting emotion and arousal. Meanwhile, brain regions involved in the sensory aspects of respiration, such as the olfactory bulb, are like-wise linked with wide-spread brain oscillations; and perturbing olfactory bulb activity can significantly affect both mood and cognition. Thus, via both motor and sensory pathways, there are clear mechanisms by which brain activity is entrained to the respiratory cycle. Here, we review evidence gathered across multiple species demonstrating the links between respiration, entrainment of brain activity and functional relevance for affecting mood and cognition. We also discuss further linkages with cardiac rhythms, and the potential translational implications for biorhythm monitoring and regulation in neuropsychiatric disorders.

SimBSI: An open-source Simulink library for developing closed-loop brain signal interfaces in animals and humans.

OBJECTIVE: A promising application of BCI technology is in the development of personalized therapies that can target neural circuits linked to mental or physical disabilities. Typical BCIs, however, offer limited value due to simplistic designs and poor understanding of the conditions being treated. Building BCIs on more solid grounds may require the characterization of the brain dynamics supporting cognition and behavior at multiple scales, from single-cell and local field potential (LFP) recordings in animals to non-invasive electroencephalography (EEG) in humans. Despite recent efforts, a unifying software framework to support closed-loop studies in both animals and humans is still lacking. The objective of this paper is to develop such a unifying neurotechnological software framework. APPROACH: Here we develop the Simulink for Brain Signal Interfaces library (SimBSI). Simulink is a mature graphical programming environment within MATLAB that has gained traction for processing electrophysiological data. SimBSI adds to this ecosystem: 1) advanced human EEG source imaging, 2) cross-species multimodal data acquisition based on the Lab Streaming Layer library, and 3) a graphical experimental design platform. MAIN RESULTS: We use several examples to demonstrate the capabilities of the library, ranging from simple signal processing, to online EEG source imaging, cognitive task design, and closed-loop neuromodulation. We further demonstrate the simplicity of developing a sophisticated experimental environment for rodents within this environment. SIGNIFICANCE: With the SimBSI library we hope to aid BCI practitioners of dissimilar backgrounds in the development of, much needed, single and cross-species closed-loop neuroscientific experiments. These experiments may provide the necessary mechanistic data for BCIs to become effective therapeutic tools.

Influence of intertrial interval on basal and drug-induced impulsive action in the 5-choice serial reaction time task: Effects of d-amphetamine and (±)-2,5-dimethoxy-4-iodoamphetamine (DOI).

Impulsivity is a characteristic of a number of neuropsychiatric disorders such as attention-deficit/hyperactivity disorder. The 5-choice serial reaction time task (5-CSRTT) is a rodent paradigm extensively used to assess attention and impulsivity. Notably, 5-CSRTT studies do not typically account for the reduction in premature responding, the measure of impulsive action, occurring upon repeated exposure to test sessions with long or variable intertrial intervals (ITIs). This present 5-CSRTT study investigated the use of variable ITIs (5, 10 or 15s) across 15 test days (4 training days followed by 1 drug test day per week for three weeks) as previous experience had shown that 4 training days would be sufficient to induce consistent premature response levels in male C57BL/6J mice. Once a steady state was achieved, the effects of dextroamphetamine (AMPH) and (±)-2,5-dimethoxy-4-iodoamphetamine (DOI) were then assessed using a Latin-square design to determine whether pharmacological-induced impulsive actions depended on ITI length. Mice habituated to the variable ITI schedule after only 3days and showed consistently lower premature response levels until the end of the study. AMPH (p<0.05) and DOI (p<0.05) increased the percentage of premature responses at 15s ITI trials, while only DOI (p<0.05) increased impulsive action at 10s ITI trials. Additionally, DOI increased omission rates (p<0.001), mean correct latency (p<0.01), reward collection latency (p<0.001), and reduced the total attempted trials (p<0.001). In summary, we demonstrated that mice habituate to the variable ITI schedule, suggesting that using the variable ITI schedule during training allowed premature response rates to stabilize before commencing pharmacological testing. Moreover, in these habituated mice AMPH and DOI significantly enhanced impulsive action at the long ITI trials only. We propose that experimental design considerations can improve the sensitivity of the 5-CSRTT to detect pharmacologicallyinduced impulsive action.