Decreased Alertness Reconfigures Cognitive Control Networks

Humans' remarkable capacity to flexibly adapt their behavior based on rapid situational changes is termed cognitive control. Intuitively, cognitive control is thought to be affected by the state of alertness; for example, when drowsy, we feel less capable of adequately implementing effortful cognitive tasks. Although scientific investigations have focused on the effects of sleep deprivation and circadian time, little is known about how natural daily fluctuations in alertness in the regular awake state affect cognitive control. Here we combined a conflict task in the auditory domain with EEG neurodynamics to test how neural and behavioral markers of conflict processing are affected by fluctuations in alertness. Using a novel computational method, we segregated alert and drowsy trials from two testing sessions and observed that, although participants (both sexes) were generally sluggish, the typical conflict effect reflected in slower responses to conflicting information compared with nonconflicting information, as well as the moderating effect of previous conflict (conflict adaptation), were still intact. However, the typical neural markers of cognitive control—local midfrontal theta-band power changes—that participants show during full alertness were no longer noticeable when alertness decreased. Instead, when drowsy, we found an increase in long-range information sharing (connectivity) between brain regions in the same frequency band. These results show the resilience of the human cognitive control system when affected by internal fluctuations of alertness and suggest that there are neural compensatory mechanisms at play in response to physiological pressure during diminished alertness

Physiological and subjective experience data

This dataset contains two files. The first contains physiological measurements of each experimental session and on three points in time during a session. Specifically, heart rate and blood pressure were measured 1) before ingestion of the first pill, 2) ~4hrs after ingestion of the first pill (right before onset of 1st behavioral task), and 3) ~7hrs after ingestion of the first pill (at the end of the experimental session). The other file contains data from the Visual Analogue Scale, in which several subjective states are recorded. This questionaire was filled in at the same time as the physiological measurements (thus 3 times per experimental session.</p

Behavioral data

This dataset contains the raw behavioral data of the spatial attention task. The zip-file containts .csv files for each participant and experimental session. Each file shows parameters (columns) for each trial (rows), including direction of the cue ('cue'), location of the target stimulus ('location'), orientation of the target stimulus ('orientation').</p

Raw EEG data

This folder contains all the raw EEG data. Filenames have the following structure: {subjectID}_{session}_attend.raw.fif.  For example for the first, subject and session the filename is: 01_0_attend.raw.fif </p

Pupil data

This dataset contains the pupil data that was used to establish effects of atomoxetine and donepezil on pupil size prior to the onset of the first behavioral experiment (when levels of both atomoxetine and donepezil were assumed to peak in blood levels). Note that task order was counter-balanced between participants. The first task of each participant is named in the .edf file containing the pupil data. From the start of the recording participants saw an instruction text for 5s, followed by three periods (15s each) in which the monitor background was first dark (RGB=(0,0,0)), then bright (RGB=(0,0,0)), and then dark again (RGB=(0,0,0)). One can use these timings to extract raw pupil data during these time-windows to extract minimal and maximal pupil size during each drug condition.</p

Cognitive and Ocular Factors Jointly Determine Pupil Responses under Equiluminance

Changes in pupil diameter can reflect high-level cognitive signals that depend on central neuromodulatory mechanisms. However, brain mechanisms that adjust pupil size are also exquisitely sensitive to changes in luminance and other events that would be considered a nuisance in cognitive experiments recording pupil size. We implemented a simple auditory experiment involving no changes in visual stimulation. Using finite impulse-response fitting we found pupil responses triggered by different types of events. Among these are pupil responses to auditory events and associated surprise: cognitive effects. However, these cognitive responses were overshadowed by pupil responses associated with blinks and eye movements, both inevitable nuisance factors that lead to changes in effective lumi- nance. Of note, these latter pupil responses were not recording artifacts caused by blinks and eye movements, but endogenous pupil responses that occurred in the wake of these events. Furthermore, we identified slow (tonic) changes in pupil size that differentially influ- enced faster (phasic) pupil responses. Fitting all pupil responses using gamma functions, we provide accurate characterisations of cognitive and non-cognitive response shapes, and quantify each response's dependence on tonic pupil size. These results allow us to cre- ate a set of recommendations for pupil size analysis in cognitive neuroscience, which we have implemented in freely available software

Coincidence gamma-gamma spectroscopy system for instrumental neutron activation analysis

A flexible facility for ¿–¿ coincidence spectroscopy with two HPGe detectors based on NIM spectrometric modules in connection with VME or CAMAC data acquisition systems is described. First results of its application for Coincidence Instrumental Neutron Activation Analysis (CINAA) are presented

Coincidence gamma-gamma spectroscopy system for instrumental neutron activation analysis

A flexible facility for ¿–¿ coincidence spectroscopy with two HPGe detectors based on NIM spectrometric modules in connection with VME or CAMAC data acquisition systems is described. First results of its application for Coincidence Instrumental Neutron Activation Analysis (CINAA) are presented