Inhibition failures and late errors in the antisaccade task: influence of cue delay

TAPAS: An Open-Source Software Package for Translational Neuromodeling and Computational Psychiatry

Psychiatry faces fundamental challenges with regard to mechanistically guided differential diagnosis, as well as prediction of clinical trajectories and treatment response of individual patients. This has motivated the genesis of two closely intertwined fields: (i) Translational Neuromodeling (TN), which develops "computational assays" for inferring patient-specific disease processes from neuroimaging, electrophysiological, and behavioral data; and (ii) Computational Psychiatry (CP), with the goal of incorporating computational assays into clinical decision making in everyday practice. In order to serve as objective and reliable tools for clinical routine, computational assays require end-to-end pipelines from raw data (input) to clinically useful information (output). While these are yet to be established in clinical practice, individual components of this general end-to-end pipeline are being developed and made openly available for community use. In this paper, we present the Translational Algorithms for Psychiatry-Advancing Science (TAPAS) software package, an open-source collection of building blocks for computational assays in psychiatry. Collectively, the tools in TAPAS presently cover several important aspects of the desired end-to-end pipeline, including: (i) tailored experimental designs and optimization of measurement strategy prior to data acquisition, (ii) quality control during data acquisition, and (iii) artifact correction, statistical inference, and clinical application after data acquisition. Here, we review the different tools within TAPAS and illustrate how these may help provide a deeper understanding of neural and cognitive mechanisms of disease, with the ultimate goal of establishing automatized pipelines for predictions about individual patients. We hope that the openly available tools in TAPAS will contribute to the further development of TN/CP and facilitate the translation of advances in computational neuroscience into clinically relevant computational assays.

Computational Dissociation of Dopaminergic and Cholinergic Effects on Action Selection and Inhibitory Control

BACKGROUND

Patients with schizophrenia make more errors than healthy subjects in the antisaccade task. In this paradigm, participants are required to inhibit a reflexive saccade to a target and to select the correct action (a saccade in the opposite direction). While the precise origin of this deficit is not clear, it has been connected to aberrant dopaminergic and cholinergic neuromodulation.

METHODS

To study the impact of dopamine and acetylcholine on inhibitory control and action selection, we administered two selective drugs (levodopa 200 mg/galantamine 8 mg) to healthy volunteers (N = 100) performing the antisaccade task. The computational model SERIA (stochastic early reaction, inhibition, and late action) was employed to separate the contribution of inhibitory control and action selection to empirical reaction times and error rates.

RESULTS

Modeling suggested that levodopa improved action selection (at the cost of increased reaction times) but did not have a significant effect on inhibitory control. By contrast, according to our model, galantamine affected inhibitory control in a dose-dependent fashion, reducing inhibition failures at low doses and increasing them at higher levels. These effects were sufficiently specific that the computational analysis allowed for identifying the drug administered to an individual with 70% accuracy.

CONCLUSIONS

Our results do not support the hypothesis that elevated tonic dopamine strongly impairs inhibitory control. Rather, levodopa improved the ability to select correct actions. However, inhibitory control was modulated by cholinergic drugs. This approach may provide a starting point for future computational assays that differentiate neuromodulatory abnormalities in heterogeneous diseases like schizophrenia.

Switch costs in inhibitory control and voluntary behaviour: A computational study of the antisaccade task

An integral aspect of human cognition is the ability to inhibit stimulus-driven, habitual responses, in favour of complex, voluntary actions. In addition, humans can also alternate between different tasks. This comes at the cost of degraded performance when compared to repeating the same task, a phenomenon called the "task-switch cost." While task switching and inhibitory control have been studied extensively, the interaction between them has received relatively little attention. Here, we used the SERIA model, a computational model of antisaccade behaviour, to draw a bridge between them. We investigated task switching in two versions of the mixed antisaccade task, in which participants are cued to saccade either in the same or in the opposite direction to a peripheral stimulus. SERIA revealed that stopping a habitual action leads to increased inhibitory control that persists onto the next trial, independently of the upcoming trial type. Moreover, switching between tasks induces slower and less accurate voluntary responses compared to repeat trials. However, this only occurs when participants lack the time to prepare the correct response. Altogether, SERIA demonstrates that there is a reconfiguration cost associated with switching between voluntary actions. In addition, the enhanced inhibition that follows antisaccade but not prosaccade trials explains asymmetric switch costs. In conclusion, SERIA offers a novel model of task switching that unifies previous theoretical accounts by distinguishing between inhibitory control and voluntary action generation and could help explain similar phenomena in paradigms beyond the antisaccade task.

Modeling Saccadic Action Selection: Cortical and Basal Ganglia Signals Coalesce in the Superior Colliculus

The distributed nature of information processing in the brain creates a complex variety of decision making behavior. Likewise, computational models of saccadic decision making behavior are numerous and diverse. Here we present a generative model of saccadic action selection in the context of competitive decision making in the superior colliculus (SC) in order to investigate how independent neural signals may converge to interact and guide saccade selection, and to test if systematic variations can better replicate the variability in responses that are part of normal human behavior. The model was tasked with performing pro- and anti-saccades in order to replicate specific attributes of healthy human saccade behavior. Participants (ages 18-39) were instructed to either look toward (pro-saccade, well-practiced automated response) or away from (anti-saccade, combination of inhibitory and voluntary responses) a peripheral visual stimulus. They generated express and regular latency saccades in the pro-saccade task. In the anti-saccade task, correct reaction times were longer and participants occasionally looked at the stimulus (direction error) at either express or regular latencies. To gain a better understanding of the underlying neural processes that lead to saccadic action selection and response inhibition, we implemented 8 inputs inspired by systems neuroscience. These inputs reflected known sensory, automated, voluntary, and inhibitory components of cortical and basal ganglia activity that coalesces in the intermediate layers of the SC (SCi). The model produced bimodal reaction time distributions, where express and regular latency saccades had distinct modes, for both correct pro-saccades and direction errors in the anti-saccade task. Importantly, express and regular latency direction errors resulted from interactions of different inputs in the model. Express latency direction errors were due to a lack of pre-emptive fixation and inhibitory activity, which aloud sensory and automated inputs to initiate a stimulus-driven saccade. Regular latency errors occurred when the automated motor signals were stronger than the voluntary motor signals. While previous models have emulated fewer aspects of these behavioral findings, the focus of the simulations here is on the interaction of a wide variety of physiologically-based information integration producing a richer set of natural behavioral variability.

Alpha Oscillations Modulate Preparatory Activity in Marmoset Area 8Ad

Cognitive control often requires suppression of prepotent stimulus-driven responses in favor of less potent alternatives. Suppression of prepotent saccades has been shown to require proactive inhibition in the frontoparietal saccade network. Electrophysiological evidence in macaque monkeys has revealed neural correlates of such inhibition in this network; however, the interlaminar instantiation of inhibitory processes remains poorly understood because these areas lie deep within sulci in macaques, rendering them inaccessible to laminar recordings. Here, we addressed this gap by exploiting the mostly lissencephalic cortex of the common marmoset (Callithrix jacchus). We inserted linear electrode arrays into areas 8Ad-the putative marmoset frontal eye field-and the lateral intraparietal area of two male marmosets and recorded neural activity during performance of a task comprised of alternating blocks of trials requiring a saccade either toward a large, high-luminance stimulus or the inhibition of this prepotent response in favor of a saccade toward a small, low-luminance stimulus. We observed prominent task-dependent activity in both alpha/gamma bands of the LFP and discharge rates of single neurons in area 8Ad during a prestimulus task epoch in which the animals had been instructed which of these two tasks to perform but before peripheral stimulus onset. These data are consistent with a model in which rhythmic alpha-band activity in deeper layers inhibits spiking in upper layers to support proactive inhibitory saccade control.SIGNIFICANCE STATEMENT Failures to inhibit automatic saccadic responses are a hallmark of many neuropsychiatric disorders, but how this process is implemented across the cortical layers in the frontoparietal saccade network remains unknown because many of the areas are inaccessible to laminar recordings in macaques. Here, we investigated laminar neural activity in marmoset monkeys, which have a smooth cortex. Monkeys were required either to generate or inhibit a prepotent saccade response. In area 8Ad, the putative frontal eye field in marmosets, rhythmic alpha-band activity (9-14 Hz) was higher in deeper layers and spiking activity was lower in upper layers when the animals were instructed to suppress a saccade toward a peripheral stimulus. Reduced alpha power during task preparation may be the underlying common neural basis of a saccade suppression deficit.