Patients with affective and non-affective psychoses show impairments in both the identification and discrimination of facial affect, which can significantly reduce their quality of life. The aim of this commentary is to present the strengths and weaknesses of the available instruments for a more careful evaluation of different stages of emotion processing in clinical and experimental studies on patients with non-affective and affective psychoses.

We reviewed the existing literature to identify different tests used to assess the ability to recognise (e.g. Ekman 60-Faces Test, Facial Emotion Identification Test and Penn Emotion Recognition Test) and to discriminate emotions (e.g. Face Emotion Discrimination Test and Emotion Differentiation Task).

The current literature revealed that few studies combine instruments to differentiate between different levels of emotion processing disorders. The lack of comprehensive instruments that integrate emotion recognition and discrimination assessments prevents a full understanding of patients’ conditions.

This commentary underlines the need for a detailed evaluation of emotion processing ability in patients with non-affective and affective psychoses, to characterise the disorder at early phases from the onset of the disease and to design rehabilitation treatments.

Understanding the factors contributing to optimal cognitive function throughout the aging process is essential to better understand successful cognitive aging. Processing speed is an age sensitive cognitive domain that usually declines early in the aging process; however, this cognitive skill is essential for other cognitive tasks and everyday functioning. Evaluating brain network interactions in cognitively healthy older adults can help us understand how brain characteristics variations affect cognitive functioning. Functional connections among groups of brain areas give insight into the brain’s organization, and the cognitive effects of aging may relate to this large-scale organization. To follow-up on our prior work, we sought to replicate our findings regarding network segregation’s relationship with processing speed. In order to address possible influences of node location or network membership we replicated the analysis across 4 different node sets.

Data were acquired as part of a multi-center study of 85+ cognitively normal individuals, the McKnight Brain Aging Registry (MBAR). For this analysis, we included 146 community-dwelling, cognitively unimpaired older adults, ages 85-99, who had undergone structural and BOLD resting state MRI scans and a battery of neuropsychological tests. Exploratory factor analysis identified the processing speed factor of interest. We preprocessed BOLD scans using fmriprep, Ciftify, and XCPEngine algorithms. We used 4 different sets of connectivity-based parcellation: 1)MBAR data used to define nodes and Power (2011) atlas used to determine node network membership, 2) Younger adults data used to define nodes (Chan 2014) and Power (2011) atlas used to determine node network membership, 3) Older adults data from a different study (Han 2018) used to define nodes and Power (2011) atlas used to determine node network membership, and 4) MBAR data used to define nodes and MBAR data based community detection used to determine node network membership.

Segregation (balance of within-network and between-network connections) was measured within the association system and three wellcharacterized networks: Default Mode Network (DMN), Cingulo-Opercular Network (CON), and Fronto-Parietal Network (FPN). Correlation between processing speed and association system and networks was performed for all 4 node sets.

We replicated prior work and found the segregation of both the cortical association system, the segregation of FPN and DMN had a consistent relationship with processing speed across all node sets (association system range of correlations: r=.294 to .342, FPN: r=.254 to .272, DMN: r=.263 to .273). Additionally, compared to parcellations created with older adults, the parcellation created based on younger individuals showed attenuated and less robust findings as those with older adults (association system r=.263, FPN r=.255, DMN r=.263).

This study shows that network segregation of the oldest-old brain is closely linked with processing speed and this relationship is replicable across different node sets created with varied datasets. This work adds to the growing body of knowledge about age-related dedifferentiation by demonstrating replicability and consistency of the finding that as essential cognitive skill, processing speed, is associated with differentiated functional networks even in very old individuals experiencing successful cognitive aging.

Adaptive decision-making is necessary to sustain functional independence. Maladaptive decisions are among the most prevalent features of psychological and neurological disorders. One crucial aspect of decision-making involves arbitrating between exploring new avenues with risky but potentially lucrative outcomes or exploiting prior knowledge and endorsing predictable outcomes. Balancing this dichotomy creates a behavioral tension that shapes all decisions and is termed the exploration-exploitation trade-off. This trade-off has been linked to reward and affective drives and associated neural circuitry as well as neuropsychological dysfunction. However, the neural mechanisms underlying the exploration-exploitation trade-off are still uncertain, due to the scarcity of literature and the heterogeneity of paradigms. This study aimed to systematically quantify and disambiguate neuroanatomical correlates of the exploration-exploitation tradeoff in a normative adult sample. These findings provide a necessary starting point for future investigations of this fundamental aspect of decision-making across clinical populations, with potential implications for assessment and intervention.

We used the effect-location method of meta-analysis to analyze data from 10 functional neuroimaging studies investigating the exploration-exploitation tradeoff in non-clinical samples. We analyzed the location and frequency of significant neural activations across studies for both explorative and exploitative decisions and characterized them as core and non-core regions. Core activations were defined as those reported in over 50% of studies. Secondary and tertiary activations were defined as those reported in 40% and 30% of studies, respectively. The present review was conducted in accordance with the guidelines of the 2009 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement.

The results revealed that explorative and exploitative choice behaviours differed markedly with respect to associated patterns of task-related brain activity. Exploration was associated with activity in brain regions implicated in externally directed, goal-based attentional processing and reward-related uncertainty, mainly tapping bilateral parietal and frontal circuitry, with relatively high consistency across studies. A core explorative network was revealed, consisting of activity in the frontal polar cortex, the dorsal anterior cingulate cortex, the bilateral medial frontal gyrus, the bilateral precuneus, and the bilateral intraparietal sulcus. Secondary and tertiary regions were also detected, including the bilateral anterior insula, the left precentral gyrus, the bilateral superior frontal gyrus, the right inferior frontal gyrus, the left supplementary motor area, the bilateral superior parietal lobule, and the bilateral thalamus. Exploitation was associated with brain regions implicated in internally directed processes including reward valuation, motivation, and memory. Core exploitative activations included the ventromedial prefrontal cortex, the bilateral anterior cingulate cortex, and the bilateral orbitofrontal cortex. Secondary and tertiary activations included the bilateral hippocampus, the left middle temporal gyrus, the bilateral angular gyrus, the left posterior cingulate cortex, the left superior frontal gyrus, and the bilateral superior temporal gyrus.

The exploration-exploitation trade-off provides a novel paradigmatic approach to study adaptive and maladaptive decision-making behaviour in humans. Our findings support the neural dichotomization of exploration and exploitation and illuminate potential neural networks underlying this fundamental feature of decision-making. Understanding these mechanistic networks opens a new avenue of inquiry into decision-making deficits in clinical populations, including neurodegenerative, neurodevelopmental, and neuropsychiatric syndromes.

When asked to imagine future events, individuals with PTSD provide narratives with limited event-specific details, suggesting an impairment in event elaboration. Here we examined whether future thinking in PTSD is also associated with an impairment in the initial stage of event construction, by using a future-event fluency task that makes no demands on event elaboration (MacLeod, A. K., & Salaminiou, E. (2001). Reduced positive future-thinking in depression: Cognitive and affective factors. Cognition & Emotion, 15(1), 99–107).

Thirty-five veterans (6 female, 29 male; aged 27–51), assigned on the basis of structured diagnostic interviews to PTSD-only (n = 15), PTSD + depression (n = 9), or psychopathology-free control groups (n = 11), were asked to generate, in one minute, as many events as possible that they expected to happen in the future, across four conditions that varied in valence (positive, negative) and temporal framework (1 month, 10 years). Two independent raters classified each event generated as being specific (i.e., a unique, time-limited event), generic (i.e., ongoing or recurring events), or a repetition.

Results of linear mixed modeling carried out on the number of specific events generated showed that diagnostic group and event valence contributed significantly to the overall model fit. All participants generated more positive than negative events (β = 1.014, SE = 0.330, t(105) = 3.07 p = 0.003), and both PTSD groups generated fewer specific events than controls (PTSD-only (β = -2.203, SE = 0.744, t(35) = -2.96, p = 0.005); PTSD + depression (β = -1.859, SE = 0.842, t(35) = -2.21, p = 0.034). Adding the interaction between group and valence did not improve the model fit, suggesting that the PTSD groups were not differentially impaired in the generation of positive and negative events. When including scores on an emotionally neutral phonemic fluency task (FAS) as a covariate to account for verbal fluency, the PTSD-only group still generated significantly fewer events than the controls (β = -1.667, SE = 0.733, t(34) = -2.27, p = 0.030). After adjusting for FAS, the group effect was marginal for the PTSD + depression group (β = -1.600, SE = 0.801, t(34) = -2.00, p = 0.054).

These results suggest that the impairment in future thinking in PTSD concerns not only the elaboration of future events but also the processes involved in initial event specification, such as those involved in the search and selection of a specific event. Moreover, these findings highlight a distinction between the future thinking abnormalities in PTSD, characterized by reduced generation of both positive and negative future events, compared to depression, which has been associated with reduced generation of positive future events only (MacLeod & Salaminiou, 2001).

Research shows intrusions in memory tests can predict cognitive impairment in abnormal aging. However, there still is a need for additional research regarding the association of intrusions in verbal fluency tasks and clinical diagnosis of mild cognitive impairment, and dementia. The aim of this research is to determine if there is an association between intrusion totals in verbal fluency tasks and diagnosis, longitudinally (across 3 years), if there are significant differences between category and phonemic fluency tasks in intrusion total scores, and if progression from cognitively normal (CN) to mild cognitive impairment (MCI) or dementia and from MCI to dementia can be indicated through differences in intrusion scores.

Participants were recruited from the Memory Disorders Center at Wien Center for Alzheimer’s Disease and Memory Disorders at Mount Sinai Medical Center in Miami, Florida to take part in the ongoing 1Florida Alzheimer’s Disease Research Center (ADRC) project. At baseline, participants had an average of 15 years of education (M = 15.00, SD = 3.65), were an average of 72.24 years old (M = 72.24, SD = 7.99), and were 62.93% female. At baseline (Visit/ year 1), there were 88 CN, 229 MCI, and 58 dementia participants. Participants were asked to complete Categorical and Phonemic verbal fluency tasks in which correct words said and intrusions were collected. Intrusion totals were quantified as the sum of intrusions within each subsection of the tasks (i.e., fruits, vegetables, and animals for the category; F, L, A, S for phonemic). Intrusion totals and correct words were analyzed across diagnostic groups and progressor vs. non-progressor groups.

Results indicated that intrusions are significantly associated with diagnosis in Phonemic fluency tasks, however, this was not the case for Category fluency tasks. Higher phonemic fluency task intrusions were associated with more severe cognitive decline. In progressor versus non-progressor groups there were no significant differences in intrusion totals. Lower correct scores for category and phonemic fluency tasks were found to be significantly associated with increased severity of diagnosis. Lower correct scores also significantly predicted progressor classification.

These findings suggest possible association of higher intrusion errors in verbal fluency tasks with more severe cognitive decline. Although these indications were significant, further research exploring intrusions and cognitive diagnosis are still needed.

Aging is associated with changes in cortical excitability which may affect motor learning and cognitive function via selective modulation of gamma aminobutyric acid (GABA). Previous studies using magnetic resonance spectroscopy (MRS) to measure GABA in older adults found that increased baseline GABA levels in the sensorimotor cortex (M1S1) were associated with better motor performance. GABA levels in M1S1 have tended to decrease during the execution of a repeated motor sequence. The dynamic change in GABA density in M1S1 in older adults is currently unknown and represents a critical gap in our understanding of how it could impact motor learning and cognitive performance. As such, the purpose of the current study is to quantify changes in cortical GABA during motor learning in the aging brain and examine those changes in relation to motor and cognitive performance. We hypothesize that older adults with greater dynamic range in M1S1 GABA levels will display more efficient motor learning and increased cognitive scores.

We report on a total of 18 healthy older adults aged 64 to 80 years (M = 70.44, SD = 4.99, 12 females). Using MRS at 3T, we measured changes in GABA concentration in M1S1 at rest, during an eight or 12 finger-movement motor entrainment task, and during a recall task. Gannett was used for GABA quantification relative to water. Change in GABA was calculated by subtracting Rest1 GABA from Recall1 GABA. In a separate session, participants completed a battery of cognitive assessments. We computed linear regressions to examine the relationship between dynamic GABA change, recall accuracy of the motor task and cognitive performance.

In relation to motor performance, we found that both greater baseline (Rest1) GABA levels and greater dynamic change in GABA significantly predicted better recall accuracy on the motor task. For cognitive performance, we found that greater dynamic change in GABA significantly predicted better performance on Word Reading in the Stroop Color and Word Test and Delayed Recall in the Hopkins Verbal Learning Test (HVLT). No additional significant relationships were found for the remaining cognitive assessments.

Older adults who were able to accurately perform the task had a greater dynamic change in GABA and increased baseline GABA levels. These adults with greater dynamic change also had better cognitive performance on HVLT Delay and Stroop Word Reading. This modulation of GABA associated with better performance could be related to changes in neuroplasticity. Although these results are in the preliminary stages, they point to a greater understanding of aging related changes in motor and cognitive performance. We’ll continue to explore the relationship between sensory motor performance and changes in GABA concentration as a potential predictor for cognitive performance and future rehabilitation.

In the United States, Alzheimer’s disease (AD) is the most common cause of dementia and the seventh leading cause of death. Exercise has demonstrated health benefits in older adults and reduces the risk of developing AD. Exploring underlying biological mechanisms of exercise could aid in identifying therapeutic targets to prevent AD progression, especially for high-risk individuals such as those with Mild Cognitive Impairment (MCI). Many studies of dementia focus on memory; however, executive function and processing speed are also vulnerable to the neuropathology that causes AD. This exploratory study aimed to identify potential mechanisms by which physical activity can facilitate change in cognitive functioning in older adults. This was accomplished by investigating correlations between changes in neurology-related plasma proteins and changes in measures of executive function and processing speed after participation in a water-based exercise intervention.

The sample included 20 older adults with amnestic MCI, ages 55-82 years (mean 68.15 ±7.75). Participants were predominately male (90%), White (70%), and non-Hispanic (85%), with more than high school education (95%). Participants engaged in supervised high-intensity water-based exercise three times per week for six months. Neuropsychological assessments and blood samples were assessed at baseline and after completion of the exercise intervention. Cognitive measures included: the Digit Span subtests from the Wechsler Adult Intelligence Scale, 4th Edition, Trail-Making Test (TMT), Stroop Color Word Test (SCWT), and the Symbol Digit Modalities Test (SDMT). Plasma protein levels were analyzed using the Olink Target 96 Neurology assay (Uppsala, Sweden), selected a priori for the established markers linked to neurobiological processes and diseases. Changes in cognitive measures and protein levels were assessed using paired-sample t-tests, and Pearson’s correlations were calculated for significant findings.

Participants’ cognitive performance significantly improved on the SCWT color trial (t = -2.19, p = 0.042) and SDMT (t = -2.17, p = .043). Significant decreases in plasma proteins levels were found for GDNF family receptor alpha-1 ([GFRA1]: t =2.05, p = 0.055), neuroblastoma suppressor tumorigenicity-1 ([NBL1]: t = 2.13, p= .046), and neuropilin-2 ([NRP2]: t = 2.61 p= 0.017). Correlational analyses showed reductions in NBL1 were significantly associated with changes in both SDMT (r = -.61, p = 0.006) and the color trial of SCWT (r = .48, p = .038), and NRP2 was significantly associated with improvement on the SDMT (r = -.46, p = 0.045). GFRA1 was not significantly associated with change on any cognitive measure.

In a sample of older adults with MCI, participation in high-intensity water-based exercise led to significant improvements in cognitive function as well as changes in neurological plasma proteome. Improved outcomes in processing speed, attention, visuospatial scanning, and working memory were associated with changes in specific plasma protein concentrations. This highlights potential activity-dependent neurobiological mechanisms that may underlie the cognitive benefits derived from physical activity. Future studies should explore these findings in Randomized Control Trials with a comparative condition and larger sample size.