Groups of humans are often able to find ways to cooperate with one another in complex, temporally extended social dilemmas. Models based on behavioral economics are only able to explain this phenomenon for unrealistic stateless matrix games. Recently, multi-agent reinforcement learning has been applied to generalize social dilemma problems to temporally and spatially extended Markov games. However, this has not yet generated an agent that learns to cooperate in social dilemmas as humans do. A key insight is that many, but not all, human individuals have inequity averse social preferences. This promotes a particular resolution of the matrix game social dilemma wherein inequity-averse individuals are personally pro-social and punish defectors. Here we extend this idea to Markov games and show that it promotes cooperation in several types of sequential social dilemma, via a profitable interaction with policy learnability. In particular, we find that inequity aversion improves temporal credit assignment for the important class of intertemporal social dilemmas. These results help explain how large-scale cooperation may emerge and persist.

With increased rates of smartphone theft over the past decade, mobile authentication systems that operate on a continual basis are a necessity to meet increasing demands for user privacy, device usage, and authentication accuracy. Rather than forcing end users to continually self-authenticate via password pins or through other means on a time-interval basis [2-7], a system that continuously authenticates users provides a more frictionless relationship between a user's device and its physical security. Such a system, if effectively operating on a low-powered, unobtrusive, and secure basis, would make it viable for most consumer mobile devices. In this paper, we build upon our work in [1] to provide a novel authentication scheme that meets these requirements for a commonly adopted system. Our system, iSentinel, hopes to provide an unobtrusive, low-powered solution for detecting and responding to common theft scenarios by continuously authenticating mobile devices in use cases such as walking, texting, and driving.

Neurotechnologies in clinical applications can image the brain noninvasively, but they typically require surgical insertion to stimulate it. Although an increasingly popular alternative is to use noninvasive stimulation to enhance nervous system functions, questions about its effectiveness and ethical use remain unanswered.

There has been growing interest in transcranial direct current stimulation (tDCS), a non-invasive technique purported to modulate neural activity via weak, externally applied electric fields. Although some promising preliminary data have been reported for applications ranging from stroke rehabilitation to cognitive enhancement, little is known about how tDCS affects the human brain, and some studies have concluded that it may have no effect at all. Here, we describe a macaque model of tDCS that allows us to simultaneously examine the effects of tDCS on brain activity and behavior. We find that applying tDCS to right prefrontal cortex improves monkeys' performance on an associative learning task. While firing rates do not change within the targeted area, tDCS does induce large low-frequency oscillations in the underlying tissue. These oscillations alter functional connectivity, both locally and between distant brain areas, and these long-range changes correlate with tDCS's effects on behavior. Together, these results are consistent with the idea that tDCS leads to widespread changes in brain activity and suggest that it may be a valuable method for cheaply and non-invasively altering functional connectivity in humans.

Finding the balance between security, privacy, and usability for mobile authentication has been an active area of research for the past several years. Many researchers have taken advantage of the availability of multiple sensors on mobile devices and have used these data to train classifiers to authenticate users. For example, implicit authentication algorithms have been developed based on behavior patterns identified from a combination of sensors including location, co-location, application usage, biometric measurements, continuity of interaction between the user and the phone, and possession of the phone [1,2,3,4,5]. Furthermore, the onboard sensors of mobile devices have previously been used to identify users based on touch [6] and fusions of touch and speech inputs [7]. However, a system utilizing low-power onboard electronics for anomaly detection and user classification is lacking. Here, we report on the performance of two subsystems tested in a controlled use scenario to classify and authenticate users of a mobile device. The overall system utilizes two subsystems for anomaly detection and user classification: (1) a neuromorphic chip for continuous, low-power, online monitoring and classification, and (2) an early warning system (EWS) algorithm for longer duration time-series behavioral and biometric classification.

Skill acquisition requires distributed learning both within (online) and across (offline) days to consolidate experiences into newly learned abilities. In particular, piloting an aircraft requires skills developed from extensive training and practice. Here, we tested the hypothesis that transcranial direct current stimulation (tDCS) can modulate neuronal function to improve skill learning and performance during flight simulator training of aircraft landing procedures. Thirty-two right-handed participants consented to participate in four consecutive daily sessions of flight simulation training and received sham or anodal high-definition-tDCS to the right dorsolateral prefrontal cortex (DLPFC) or left motor cortex (M1) in a randomized, double-blind experiment. Continuous electroencephalography (EEG) and functional near infrared spectroscopy (fNIRS) were collected during flight simulation, n-back working memory, and resting-state assessments. tDCS of the right DLPFC increased midline-frontal theta-band activity in flight and n-back working memory training, confirming tDCS-related modulation of brain processes involved in executive function. This modulation corresponded to a significantly different online and offline learning rates for working memory accuracy and decreased inter-subject behavioral variability in flight and n-back tasks in the DLPFC stimulation group. Additionally, tDCS of left M1 increased parietal alpha power during flight tasks and tDCS to the right DLPFC increased midline frontal theta-band power during n-back and flight tasks. These results demonstrate a modulation of group variance in skill acquisition through an increasing in learned skill consistency in cognitive and real-world tasks with tDCS. Further, tDCS performance improvements corresponded to changes in electrophysiological and blood-oxygenation activity of the DLPFC and motor cortices, providing a stronger link between modulated neuronal function and behavior.

La presente invention concerne un systeme destine au reglage automatique de neurostimulation. Le systeme commande la stimulation de regions neuronales specifiques par l'intermediaire d'un dispositif neuronal positionne sur un sujet humain, tout en realisant simultanement des enregistrements a partir du dispositif neuronal a l'aide d'un systeme cible d'electrodes de stimulation et de types distincts d'electrodes d'enregistrement du dispositif neuronal. La stimulation des regions neuronales specifiques est ajustee en temps reel sur la base des enregistrements provenant du dispositif neuronal.

The Wisconsin Card Sorting Test (WCST) evaluates a subject’s ability to shift to a new pattern of behavior in response to the presentation of unexpected negative feedback. The present study introduces a novel version of the traditional WCST by integrating a probabilistic component into its traditional rule shifting to add uncertainty to the task, as well as the option to forage for information during any particular trial. These changes transformed a task that is trivial for neurotypical individuals into a challenging environment useful for evaluating biases and compensatory strategizing. Sixty subjects performed the probabilistic WCST at four uncertainty levels to determine the effect of uncertainty on subject performance and strategy. Results revealed that increasing the level of uncertainty during a run of trials correlated with a reduction in rational strategizing in favor of both random choice and information foraging, evoking biases and suboptimal strategies such as satisfaction of search, negativity bias, and probability matching.

The blood-oxygen-level-dependent (BOLD) signal measured in functional magnetic resonance imaging (fMRI) experiments is generally regarded as sluggish and poorly suited for probing neural function at the rapid timescales involved in sentence comprehension. However, recent studies have shown the value of acquiring data with very short repetition times (TRs), not merely in terms of improvements in contrast to noise ratio (CNR) through averaging, but also in terms of additional fine-grained temporal information. Using multiband-accelerated fMRI, we achieved whole-brain scans at 3-mm resolution with a TR of just 500ms at both 3T and 7T field strengths. By taking advantage of word timing information, we found that word decoding accuracy across two separate sets of scan sessions improved significantly, with better overall performance at 7T than at 3T. The effect of TR was also investigated; we found that substantial word timing information can be extracted using fast TRs, with diminishing benefits beyond TRs of 1000ms.

We have created a high-fidelity model of 9 regions of the brain involved in making sense of complex and uncertain situations. Sense making is a proactive form of situation awareness requiring sifting through information of various types to form hypotheses about evolving situations. The MINDS model (Mirroring Intelligence in a Neural Description of Sensemaking) reveals the neural principles and cognitive tradeoffs that explain weaknesses in human reasoning and decision-making.

A growing body of evidence suggests that trans-cranial neurostimulation can enhance key cognitive faculties associated with human performance across a wide range of domains including enhanced executive functions, perception and attention, motor performance, and memory enhancement [1-6]. However, multiple studies have found that changing the neurostimulation parameters can cause drastically different neural responses. Trans-cranial direct current stimulation (tDCS) enhances or suppresses the activation of neurons depending on the polarity of the electric field within the neural tissue. Alternating current stimulation (tACS) induces oscillatory patterns of neural activity that vary with amplitude, frequency, and phase, and random noise stimulation (tRNS) can promote neural plasticity [7-11].

Change detection, and which information to attend to, are key research problems relevant to understanding adaptive behavior. Rational analyses of change detection have been developed in optimal foraging theory (McNamara and Houston, 1987, Stephens, 1987) and psychology (Gallistel, Krishan, Liu, Miller, & Latham, 2014). Information foraging models (Pirolli, 2007) have been developed to predict the optimal choice of information, and when to terminate collecting additional information. Optimal performance depend crucially on changing behavior when the world changes. For example, intelligence analysts track the dynamically changing strategies of adversaries and must choose information to weigh the utility of alternate actions regarding these agents. Neurobiologically-plausible descriptions of these behaviors have thus far been fragmentary (cf., Hayden, Pearson, & Platt, 2011). Here, behavioral and mechanistic differences in belief updating about an agent’s strategy, and information foraging choices were investigated in a variant of the patch foraging task. Human subjects typically displayed non-normative updating and information foraging decisions which influenced future belief updating and foraging behaviors. To explore the biological basis of these behaviors, a neural model which forages, processes, and updates the beliefs of competing hypotheses was created. Strategy updating and information foraging behaviors were modeled in the temporal and prefrontal cortices consistent with theories of human cognitive processing during adversarial game play. The neural model reproduced human behaviors observed in foraging, belief updating, and change detection. These results highlight the importance of updating strategy, foraging, and fatigue behaviors and provide a simulation framework for future studies to investigate other high-level cognitive behaviors.

The thalamus is a critical brain structure involved in gating and regulating the flow of sensory and cortical information. The reticular nucleus of the thalamus (TRN) sends inhibitory projections to the thalamic relay nuclei instead of projecting to the cortex as the other thalamic nuclei do. These inhibitory projections endow the TRN with the functionality to modulate and control cortical information flowing through the thalamus. Yet, the functional roles of the TRN and thalamus in high-level cognitive processing, such as spatial reasoning and decisionmaking, remains poorly understood. Neurocognitive models offer a framework to explore the high-level cognitive functions of the thalamus and TRN. Here, we investigate the functional roles of the thalamus and TRN in high-level cognitive tasks using a large-scale neurocognitive model called ICArUS-MINDS. Our results demonstrate distributed and parallel top-down executive control of semantic and spatial cortical information. Specifically, we observed reticular-thalamic inhibitory gating of spatial and semantic information through top-down task switching control during reasoning, decision making and recall. Thalamic-gating was critical for orchestrating processing sequences of taskdependent switches between cortical sources and targets. These results are an important first step in simulating and understanding the functional roles and behaviors of the thalamic brain system in high-level cognitive processing.

Respiration produces rhythmic activity in the entire olfactory system, driving neurons in the olfactory epithelium, olfactory bulb (OB), and cortex. The rhythmic nature of this activity is believed to be a critical component of sensory processing. OB projection neurons, mitral and tufted cells exhibit both spiking and subthreshold membrane potential oscillations rhythmically coupled to respiration. However, the network and synaptic mechanisms that produce respiration-coupled activity, and the effects of respiration on lateral inhibition, a major component of sensory processing in OB circuits, are not known. Is respiration-coupled activity in mitral and tufted cells produced by sensory synaptic inputs from nasal airflow alone, cortico-bulbar feedback, or intrinsic membrane properties of the projection neurons? Does respiration facilitate or modulate the activity of inhibitory lateral circuits in the OB? Here, in vivo intracellular recordings from identified mitral and tufted cells in anesthetized rats demonstrate that nasal airflow provides excitatory synaptic inputs to both cell types and drives respiration-coupled spiking. Lateral inhibition, inhibitory postsynaptic potentials evoked by intrabulbar microstimulation, was modulated by respiration. In individual mitral and tufted cells, inhibition was larger at specific respiratory phases. However, lateral inhibition was not uniformly larger during a particular respiratory phase in either cell type. Removing nasal airflow abolished respiration-coupled spiking in both cell types and nearly eliminated spiking in mitral, but not tufted, cells. In the absence of nasal airflow, lateral inhibition was weaker in mitral cells and less modulated in tufted cells. Thus, respiration drives distinct network activities that functionally modulate sensory processing in the OB.

Using a longitudinal study design, two strains of Alzheimer's disease (AD) model mice, one expressing β-amyloid plaques and one expressing Tau protein-associated neurofibrillary tangles were assessed for olfactory and visuospatial learning and memory and their performance compared to that of age-matched controls. No significant difference between AD and control mice was found in the initial set of olfactory tasks performed at 6 months of age whereas both strains of AD mice performed significantly poorer than the controls in visuospatial learning at this age. Subsequent tests performed on the same individual animals at 7, 8, 9, 11, 13, 15, and 18 months of age also failed to find systematic differences in olfactory performance between AD and control mice. In contrast, the AD mice performed consistently poorer than the controls in visuospatial re-learning tests performed at these ages. With most olfactory tasks, both AD and control mice displayed a marked decrease in performance between testing at 15 and 18 months of age. These results show that the two strains of AD model mice do not display an olfactory impairment in a time course consistent with human AD, but are impaired in visuospatial capabilities. The marked age-related changes observed with the olfactory tasks in both AD and control mice suggest that the observed lack of an AD-related olfactory impairment is not due to an insensitivity of the tests employed. Rather, they suggest that the olfactory system of the two AD mouse model strains may be surprisingly robust against AD-typical neuropathologies.

Lateral connections in the olfactory bulb were previously thought to be organized for center-surround inhibition. However, recent anatomical and physiological studies showed sparse and distributed interactions of inhibitory granule cells (GCs) which tended to be organized in columnar clusters. Little is known about how these distributed clusters are interconnected. In this study, we use transsynaptic tracing viruses bearing green or red fluorescent proteins to further elucidate mitral- and tufted-to-GC connectivity. Separate sites in the glomerular layer were injected with each virus. Columns with labeling from both viruses after transsynaptic spread show sparse red or green GCs which tended to be segregated. However, there was a higher incidence of co-labeled cells than chance would predict. Similar segregation of labeling is observed from dual injections into olfactory cortex. Collectively, these results suggest that neighboring mitral and tufted cells receive inhibitory inputs from segregated subsets of GCs, enabling inhibition of a center by specific and discontinuous lateral elements.