Developmental changes in the processing of faces as revealed by EEG decoding

Rapidly and accurately processing information from faces is a critical human function that is known to improve with developmental age. Understanding the underlying drivers of this improvement remains a contentious question, with debate continuing as to the presence of early vs. late maturation of face-processing mechanisms. Recent behavioural evidence suggests an important ‘hallmark’ of expert face processing – the face inversion effect – is present in very young children, yet neural support for this remains unclear. To address this, we conducted a detailed investigation of the neural dynamics of face processing in children spanning a range of ages (6 – 11 years) and adults. Uniquely, we applied multivariate pattern analysis (MVPA) to the electroencephalogram signal (EEG) to test for the presence of a distinct neural profile associated with canonical upright faces when compared both to other objects (houses) and to inverted faces. Results revealed robust discrimination profiles, at the individual level, of differentiated neural activity associated with broad face categorization and further with its expert processing, as indexed by the face inversion effect, from the youngest ages tested. This result is consistent with an early functional maturation of broad face processing mechanisms. Yet, clear quantitative differences between the response profile of children and adults is suggestive of age-related refinement of this system with developing face and general expertise. Standard ERP analysis also provides some support for qualitative differences in the neural response to inverted faces in children in contrast to adults. This neural profile is in line with recent behavioural studies that have reported impressively expert early face abilities during childhood, while also providing novel evidence of the ongoing neural specialisation between child and adulthood

Orientation effects support specialist processing of upright unfamiliar faces in children and adults

It is considerably harder to generalize identity across different pictures of unfamiliar faces, compared with familiar faces. This finding hints strongly at qualitatively distinct processing of unfamiliar face stimuli—for which we have less expertise. Yet, the extent to which face selective versus generic visual processes drive outcomes during this task has yet to be determined. To explore the relative contributions of each, we contrasted performance on a version of the popular Telling Faces Together unfamiliar face matching task, implemented in both upright and inverted orientations. Furthermore, we included different age groups (132 British children ages 6 to 11 years [69.7% White], plus 37 British White adults) to investigate how participants’ experience with faces as a category influences their selective utilization of specialized processes for unfamiliar faces. Results revealed that unfamiliar face matching is highly orientation-selective. Accuracy was higher for upright compared with inverted faces from 6 years of age, which is consistent with selective utilization of specialized processes for upright versus inverted unfamiliar faces during this task. The effect of stimulus orientation did not interact significantly with age, and there was no graded increase in the magnitude of inversion effects observed across childhood. Still, a numerically larger inversion effect in adults compared to children provides a degree of support for developmental changes in these specialized face abilities with increasing age/experience. Differences in the pattern of errors across age groups are also consistent with a qualitative shift in unfamiliar face processing that occurs some time after 11 years of ag

Implementing an mHealth System for Substance Use Disorders in Primary Care: A Mixed Methods Study of Clinicians’ Initial Expectations and First Year Experiences

Millions of Americans need but don’t receive treatment for substance use, and evidence suggests that addiction-focused interventions on smart phones could support their recovery. There is little research on implementation of addiction-related interventions in primary care, particularly in Federally Qualified Health Centers (FQHCs) that provide primary care to underserved populations. We used mixed methods to examine three FQHCs’ implementation of Seva, a smart-phone app that offers patients online support/discussion, health-tracking, and tools for coping with cravings, and offers clinicians information about patients’ health tracking and relapses. We examined (a) clinicians\u27 initial perspectives about implementing Seva, and (b) the first year of implementation at Site 1

Face recognition ability is manifest in early dynamic decoding of face-orientation selectivity – evidence from multi-variate pattern analysis of the neural response

Although humans are considered to be face experts, there is a well-established reliable variation in the degree to which neurotypical individuals are able to learn and recognise faces. While many behavioural studies have characterised these differences, studies that seek to relate the neuronal response to standardised behavioural measures of ability remain relatively scarce, particularly so for the time-resolved approaches and the early response to face stimuli. In the present study we make use of a relatively recent methodological advance, multi-variate pattern analysis (MVPA), to decode the time course of the neural response to faces compared to other object categories (inverted faces, objects). Importantly, for the first time, we directly relate metrics of this decoding assessed at the individual level to gold-standard measures of behavioural face processing ability assessed in an independent task. Thirty-nine participants completed the behavioural Cambridge Face Memory Test (CFMT), then viewed images of faces and houses (presented upright and inverted) while their neural activity was measured via electroencephalography. Significant decoding of both face orientation and face category were observed in all individual participants. Decoding of face orientation, a marker of more advanced face processing, was earlier and stronger in participants with higher levels of face expertise, while decoding of face category information was earlier but not stronger for individuals with greater face expertise. Taken together these results provide a marker of significant differences in the early neuronal response to faces from around 100ms post stimulus as a function of behavioural expertise with faces

Implementing a Mobile Health System to Integrate the Treatment of Addiction Into Primary Care: A Hybrid Implementation-Effectiveness Study

Background: Despite the near ubiquity of mobile phones, little research has been conducted on the implementation of mobile health (mHealth) apps to treat patients in primary care. Although primary care clinicians routinely treat chronic conditions such as asthma and diabetes, they rarely treat addiction, a common chronic condition. Instead, addiction is most often treated in the US health care system, if it is treated at all, in a separate behavioral health system. mHealth could help integrate addiction treatment in primary care. Objective: The objective of this paper was to report the effects of implementing an mHealth system for addiction in primary care on both patients and clinicians. Methods: In this implementation research trial, an evidence-based mHealth system named Seva was introduced sequentially over 36 months to a maximum of 100 patients with substance use disorders (SUDs) in each of three federally qualified health centers (FQHCs; primary care clinics that serve patients regardless of their ability to pay). This paper reports on patient and clinician outcomes organized according to the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. Results: The outcomes according to the RE-AIM framework are as follows: Reach—Seva reached 8.31% (268/3226) of appropriate patients. Reach was limited by our ability to pay for phones and data plans for a maximum of 100 patients per clinic. Effectiveness—Patients who were given Seva had significant improvements in their risky drinking days (44% reduction, (0.7-1.25)/1.25, P=.04), illicit drug-use days (34% reduction, (2.14-3.22)/3.22, P=.01), quality of life, human immunodeficiency virus screening rates, and number of hospitalizations. Through Seva, patients also provided peer support to one another in ways that are novel in primary care settings. Adoption—Patients sustained high levels of Seva use—between 53% and 60% of the patients at the 3 sites accessed Seva during the last week of the 12-month implementation period. Among clinicians, use of the technology was less robust than use by patients, with only a handful of clinicians using Seva in each clinic and behavioral health providers making most referrals to Seva in 2 of the 3 clinics. Implementation—At 2 sites, implementation plans were realized successfully; they were delayed in the third. Maintenance—Use of Seva dropped when grant funding stopped paying for the mobile phones and data plans. Two of the 3 clinics wanted to maintain the use of Seva, but they struggled to find funding to support this. Conclusions: Implementing an mHealth system can improve care among primary care patients with SUDs, and patients using the system can support one another in their recovery. Among clinicians, however, implementation requires figuring out how information from the mHealth system will be used and making mHealth data available in the electronic health (eHealth) record. In addition, paying for an mHealth system remains a challenge

The effect of bundling medication-assisted treatment for opioid addiction with mHealth: study protocol for a randomized clinical trial

Completed SPIRIT figure. (PDF 103 kb

Effects of expectation on face perception and its association with expertise

Perceptual decisions are derived from the combination of priors and sensorial input. While priors are broadly understood to reflect experience/expertise developed over one’s lifetime, the role of perceptual expertise at the individual level has seldom been directly explored. Here, we manipulate probabilistic information associated with a high and low expertise category (faces and cars respectively), while assessing individual level of expertise with each category. 67 participants learned the probabilistic association between a color cue and each target category (face/car) in a behavioural categorization task. Neural activity (EEG) was then recorded in a similar paradigm in the same participants featuring the previously learned contingencies without the explicit task. Behaviourally, perception of the higher expertise category (faces) was modulated by expectation. Specifically, we observed facilitatory and interference effects when targets were correctly or incorrectly expected, which were also associated with independently measured individual levels of face expertise. Multivariate pattern analysis of the EEG signal revealed clear effects of expectation from 100 ms post stimulus, with significant decoding of the neural response to expected vs. not stimuli, when viewing identical images. Latency of peak decoding when participants saw faces was directly associated with individual level facilitation effects in the behavioural task. The current results not only provide time sensitive evidence of expectation effects on early perception but highlight the role of higher-level expertise on forming priors

Antibody 8ANC195 Reveals a Site of Broad Vulnerability on the HIV-1 Envelope Spike

Broadly neutralizing antibodies (bNAbs) to HIV-1 envelope glycoprotein (Env) can prevent infection in animal models. Characterized bNAb targets, although key to vaccine and therapeutic strategies, are currently limited. We defined a new site of vulnerability by solving structures of bNAb 8ANC195 complexed with monomeric gp120 by X-ray crystallography and trimeric Env by electron microscopy. The site includes portions of gp41 and N-linked glycans adjacent to the CD4-binding site on gp120, making 8ANC195 the first donor-derived anti-HIV-1 bNAb with an epitope spanning both Env subunits. Rather than penetrating the glycan shield by using a single variable-region CDR loop, 8ANC195 inserted its entire heavy-chain variable domain into a gap to form a large interface with gp120 glycans and regions of the gp120 inner domain not contacted by other bNAbs. By isolating additional 8ANC195 clonal variants, we identified a more potent variant, which may be valuable for therapeutic approaches using bNAb combinations with nonoverlapping epitopes

Implementing an mHealth system for substance use disorders in primary care: a mixed methods study of clinicians’ initial expectations and first year experiences

Background: Millions of Americans need but don’t receive treatment for substance use, and evidence suggests that addiction-focused interventions on smart phones could support their recovery. There is little research on implementation of addiction-related interventions in primary care, particularly in Federally Qualified Health Centers (FQHCs) that provide primary care to underserved populations. We used mixed methods to examine three FQHCs’ implementation of Seva, a smart-phone app that offers patients online support/discussion, health-tracking, and tools for coping with cravings, and offers clinicians information about patients’ health tracking and relapses. We examined (a) clinicians’ initial perspectives about implementing Seva, and (b) the first year of implementation at Site 1. Methods: Prior to staggered implementation at three FQHCs (Midwest city in WI vs. rural town in MT vs. metropolitan NY), interviews, meetings, and focus groups were conducted with 53 clinicians to identify core themes of initial expectations about implementation. One year into implementation at Site 1, clinicians there were re-interviewed. Their reports were supplemented by quantitative data on clinician and patient use of Seva. Results: Clinicians anticipated that Seva could help patients and make behavioral health appointments more efficient, but they were skeptical that physicians would engage with Seva (given high caseloads), and they were uncertain whether patients would use Seva. They were concerned about legal obligations for monitoring patients’ interactions online, including possible “cries for help” or inappropriate interactions. One year later at Site 1, behavioral health care providers, rather than physicians, had incorporated Seva into patient care, primarily by discussing it during appointments. Given workflow/load concerns, only a few key clinicians monitored health tracking/relapses and prompted outreach when needed; two researchers monitored the discussion board and alerted the clinic as needed. Clinician turnover/leave complicated this approach. Contrary to clinicians’ initial concerns, patients showed sustained, mutually supportive use of Seva, with few instances of misuse. Conclusions: Results suggest the value of (a) focusing implementation on behavioral health care providers rather than physicians, (b) assigning a few individuals (not necessarily clinicians) to monitor health tracking, relapses, and the discussion board, (c) anticipating turnover/leave and having designated replacements. Patients showed sustained, positive use of Seva. Trial registration: ClinicalTrials.gov (NCT01963234)