Sex differences in the response to emotional distraction: an event-related fMRI investigation

Evidence has suggested that women have greater emotional reactivity than men. However, it is unclear whether these differences in basic emotional responses are also associated with differences in emotional distractibility, and what the neural mechanisms that implement differences in emotional distractibility between women and men are. Functional MRI recording was used in conjunction with a working memory (WM) task, with emotional distraction (angry faces) presented during the interval between the memoranda and the probes. First, we found an increased impact of emotional distraction among women in trials associated with high-confidence responses, in the context of overall similar WM performance in women and men. Second, women showed increased sensitivity to emotional distraction in brain areas associated with "hot" emotional processing, whereas men showed increased sensitivity in areas associated with "cold" executive processing, in the context of overall similar patterns of response to emotional distraction in women and men. Third, a sex-related dorsal-ventral hemispheric dissociation emerged in the lateral PFC related to coping with emotional distraction, with women showing a positive correlation with WM performance in left ventral PFC, and men showing similar effects in the right dorsal PFC. In addition to extending to men results that have previously been reported in women, by showing that both sexes engage mechanisms that are similar overall in response to emotional distraction, the present study identifies sex differences in both the response to and coping with emotional distraction. These results have implications for understanding sex differences in the susceptibility to affective disorders, in which basic emotional responses, emotional distractibility, and coping abilities are altered

ConnSearch: A framework for functional connectivity analysis designed for interpretability and effectiveness at limited sample sizes

Functional connectivity studies increasingly turn to machine learning methods, which typically involve fitting a connectome-wide classifier, then conducting post hoc interpretation analyses to identify the neural correlates that best predict a dependent variable. However, this traditional analytic paradigm suffers from two main limitations. First, even if classifiers are perfectly accurate, interpretation analyses may not identify all the patterns expressed by a dependent variable. Second, even if classifiers are generalizable, the patterns implicated via interpretation analyses may not replicate. In other words, this traditional approach can yield effective classifiers while falling short of most neuroscientists’ goals: pinpointing the neural correlates of dependent variables. We propose a new framework for multivariate analysis, ConnSearch, which involves dividing the connectome into components (e.g., groups of highly connected regions) and fitting an independent model for each component (e.g., a support vector machine or a correlation-based model). Conclusions about the link between a dependent variable and the brain are based on which components yield predictive models rather than on interpretation analysis. We used working memory data from the Human Connectome Project (N = 50–250) to compare ConnSearch with four existing connectome-wide classification/interpretation methods. For each approach, the models attempted to classify examples as being from the high-load or low-load conditions (binary labels). Relative to traditional methods, ConnSearch identified neural correlates that were more comprehensive, had greater consistency with the WM literature, and better replicated across datasets. Hence, ConnSearch is well-positioned to be an effective tool for functional connectivity research

Neural Correlates of Opposing Effects of Emotional Distraction on Working Memory and Episodic Memory: An Event-Related fMRI Investigation

A fundamental question in the emotional memory literature is why emotion enhances memory in some conditions but disrupts memory in other conditions. For example, separate studies have shown that emotional stimuli tend to be better remembered in long-term episodic memory (EM), whereas emotional distracters tend to impair working memory (WM) maintenance. The first goal of this study was to directly compare the neural correlates of EM enhancement (EME) and WM impairing (WMI) effects, and the second goal was to explore individual differences in these mechanisms. During event-related fMRI, participants maintained faces in WM while being distracted by emotional or neutral pictures presented during the delay period. EM for the distracting pictures was tested after scanning and was used to identify successful encoding activity for the picture distracters. The first goal yielded two findings: (1) Emotional pictures that disrupted face WM but enhanced subsequent EM were associated with increased amygdala and hippocampal activity (ventral system) coupled with reduced dorsolateral PFC activity (dorsal system); (2) Trials in which emotion enhanced EM without disrupting WM were associated with increased ventrolateral PFC activity. The ventral-dorsal switch can explain EME and WMI, while the ventrolateral PFC effect suggests a coping mechanism. The second goal yielded two additional findings: (3) Participants who were more susceptible to WMI showed greater amygdala increases and PFC reductions; (4) Amygdala activity increased and dlPFC activity decreased with measures of impulsivity. Taken together, the results clarify the mechanisms linking the enhancing and impairing effects of emotion on memory

Aging and Network Properties: Stability Over Time and Links with Learning during Working Memory Training

Growing evidence suggests that healthy aging affects the configuration of large-scale functional brain networks. This includes reducing network modularity and local efficiency. However, the stability of these effects over time and their potential role in learning remain poorly understood. The goal of the present study was to further clarify previously reported age effects on “resting-state” networks, to test their reliability over time, and to assess their relation to subsequent learning during training. Resting-state fMRI data from 23 young (YA) and 20 older adults (OA) were acquired in 2 sessions 2 weeks apart. Graph-theoretic analyses identified both consistencies in network structure and differences in module composition between YA and OA, suggesting topological changes and less stability of functional network configuration with aging. Brain-wide, OA showed lower modularity and local efficiency compared to YA, consistent with the idea of age-related functional dedifferentiation, and these effects were replicable over time. At the level of individual networks, OA consistently showed greater participation and lower local efficiency and within-network connectivity in the cingulo-opercular network, as well as lower intra-network connectivity in the default-mode network and greater participation of the somato-sensorimotor network, suggesting age-related differential effects at the level of specialized brain modules. Finally, brain-wide network properties showed associations, albeit limited, with learning rates, as assessed with 10 days of computerized working memory training administered after the resting-state sessions, suggesting that baseline network configuration may influence subsequent learning outcomes. Identification of neural mechanisms associated with learning-induced plasticity is important for further clarifying whether and how such changes predict the magnitude and maintenance of training gains, as well as the extent and limits of cognitive transfer in both younger and older adults

Age differences in functional network reconfiguration with working memory training

Demanding cognitive functions like working memory (WM) depend on functional brain networks being able to communicate efficiently while also maintaining some degree of modularity. Evidence suggests that aging can disrupt this balance between integration and modularity. In this study, we examined how cognitive training affects the integration and modularity of functional networks in older and younger adults. Twenty three younger and 23 older adults participated in 10- days of verbal WM training, leading to performance gains in both age groups. Older adults exhibited lower modularity overall and a greater decrement when switching from rest to task, compared to younger adults. Interestingly, younger but not older adults showed increased task- related modularity with training. Furthermore, whereas training increased efficiency within, and decreased participation of, the default- mode network for younger adults, it enhanced efficiency within a task- specific salience/sensorimotor network for older adults. Finally, training increased segregation of the default- mode from frontoparietal/salience and visual networks in younger adults, while it diffusely increased between- network connectivity in older adults. Thus, while younger adults increase network segregation with training, suggesting more automated processing, older adults persist in, and potentially amplify, a more integrated and costly global workspace, suggesting different age- related trajectories in functional network reorganization with WM training.We examined how working memory (WM) training affects the integration and modularity of functional networks in older and younger adults. Younger adults increase network segregation with training, suggesting more automated processing. Older adults persist in, and potentially amplify, a more integrated and costly global workspace, suggesting different age- related trajectories in functional network reorganization with WM training.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/167029/1/hbm25337.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/167029/2/hbm25337-sup-0001-supinfo.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/167029/3/hbm25337_am.pd

Tolerability and blinding of high-definition transcranial direct current stimulation among older adults at intensities of up to 4 mA per electrode

Background: Few studies have investigated tolerability, blinding, and double-blinding of High-Definition transcranial Direct Current Stimulation (HD-tDCS) at amplitudes above 2 milliamps (mA). Objective: We examined a) tolerability of HD-tDCS during stimulation sessions and b) blinding and double blinding of participants and study team members. Methods: Data from a mixed neurologic sample of 292 older adults were pooled from 3046 HD-tDCS sessions (2329 active; 717 sham). Per electrode amplitudes ranged from 1 mA to 4 mA with total currents up to 10 mA. Participants completed a standardized sensation (tolerability) questionnaire after each session. Participants and study team members stated whether the participant received active or sham stimulation at the end of various sessions. Data were collapsed into the presence/absence of a symptom due to low rates of positive responding and were analyzed for both differences and bioequivalency. Results: There were no safety-related adverse events. HD-tDCS was well tolerated with mostly no (“none”) or “mild” sensations reported across sessions, regardless of active or sham condition and in both stimulation naïve and experienced participants. There were no significant differences in side effects between active and sham, with some achieving bioequivalence. Tingling and itching were significantly more common after lower (<2 mA) than higher (≥3 mA) amplitude active sessions, while skin redness was significantly more common after higher amplitudes. Blinding was effective at the participant and study team levels. Conclusions: HD-tDCS was well tolerated with center electrode amplitudes up to 4 mA. The bimodal ramp-up/down format of the sham was effective for blinding. These results support higher scalp-based amplitudes that enable greater brain-based current intensities in older adults