Granule cells perform frequency-dependent pattern separation in a computational model of the dentate gyrus.

Mnemonic discrimination (MD) may be dependent on oscillatory perforant path input frequencies to the hippocampus in a "U"-shaped fashion, where some studies show that slow and fast input frequencies support MD, while other studies show that intermediate frequencies disrupt MD. We hypothesize that pattern separation (PS) underlies frequency-dependent MD performance. We aim to study, in a computational model of the hippocampal dentate gyrus (DG), the network and cellular mechanisms governing this putative "U"-shaped PS relationship. We implemented a biophysical model of the DG that produces the hypothesized "U"-shaped input frequency-PS relationship, and its associated oscillatory electrophysiological signatures. We subsequently evaluated the network's PS ability using an adapted spatiotemporal task. We undertook systematic lesion studies to identify the network-level mechanisms driving the "U"-shaped input frequency-PS relationship. A minimal circuit of a single granule cell (GC) stimulated with oscillatory inputs was also used to study potential cellular-level mechanisms. Lesioning synapses onto GCs did not impact the "U"-shaped input frequency-PS relationship. Furthermore, GC inhibition limits PS performance for fast frequency inputs, while enhancing PS for slow frequency inputs. GC interspike interval was found to be input frequency dependent in a "U"-shaped fashion, paralleling frequency-dependent PS observed at the network level. Additionally, GCs showed an attenuated firing response for fast frequency inputs. We conclude that independent of network-level inhibition, GCs may intrinsically be capable of producing a "U"-shaped input frequency-PS relationship. GCs may preferentially decorrelate slow and fast inputs via spike timing reorganization and high frequency filtering.

Pathologies of precision: A Bayesian account of goals, habits, and episodic foresight in addiction.

The brain is thought to implement two decision-making systems: a goal-directed system in which decisions are made through planning on the basis of action-outcome relationships, and a habitual system in which behaviour reflects stimulus-response associations. A prominent theory of addiction sees it as arising due to an extreme dominance of habit over goal-directed action. The balance between these systems is thought to be arbitrated by the relative precision of their separate predictions of reward. In this paper, we argue that various factors in addiction create hyper-precise reward predictions in the habitual system and hypo-precise reward predictions in the goal-directed system, shifting the balance of behavioural control in favour of habit. Based on this, we offer a theoretical account of the utility of episodic future thinking in addiction, interpreting it as increasing the precision of reward estimates in the goal-directed system, thereby enhancing the control of this system over behaviour.

Dynamic task-linked switching between brain networks - A tri-network perspective.

The highly influential tri-network model proposed by Menon integrates 3 key intrinsic brain networks - the central executive network (CEN), the salience network (SN), and the default mode network (DMN), into a single cohesive model underlying normal behaviour and cognition. A large body of evidence suggests that abnormal intra- and inter- network connectivity between these three networks underlies the various behavioural and cognitive dysfunctions observed in patients with neuropsychiatric conditions such as PTSD and depression. An important prediction of the tri-network model is that the DMN and CEN networks are anti-correlated under the control of the SN, such that if a task engages one of the two, the SN inhibits the activation of the other. To date most of the evidence surrounding the functions of these three core networks comes from either resting state analyses or in the context of a single task with respect to rest. Few studies have investigated multiple tasks simultaneously or characterized the dynamics of task switching. Hence, a careful investigation of the temporal dynamics of network activity during task switching is warranted. To accomplish this we collected fMRI data from 14 participants that dynamically switched between a 2-back working memory task and an autobiographical memory retrieval task, designed to activate the CEN, DMN and the SN. The fMRI data were used to 1. identify nodes and sub-networks within the three major networks involved in task-linked dynamic network switching, 2. characterize the temporal pattern of activation of these nodes and sub-networks, and finally 3. investigate the causal influence that these nodes and sub-networks exerted on each other. Using a combination of multivariate neuroimaging analyses, timecourse analyses and multivariate Granger causality measures to study the tri-network dynamics, the current study found that the SN co-activates with the task-relevant network, providing a mechanistic insight into SN-mediated network selection in the context of explicit tasks. Our findings also indicate active involvement of the posterior insula and some medial temporal nodes in task-linked functions of the SN and DMN, warranting their inclusion as network nodes in future studies of the tri-network model. These results add to the growing body of evidence showing the complex interplay of CEN, DMN and SN nodes and sub-networks required for adequate task-switching, characterizing a normative pattern of task-linked network dynamics within the context of Menon's tri-network model.

Visual perspective as a two-dimensional construct in episodic future thought.

Visual perspective (first-person vs. third-person) is a salient characteristic of memory and mental imagery with important cognitive and behavioural consequences. Most work on visual perspective treats it as a unidimensional construct. However, third-person perspective can have opposite effects on emotion and motivation, sometimes intensifying these and other times acting as a distancing mechanism, as in PTSD. For this reason among others, we propose that visual perspective in memory and mental imagery is best understood as varying along two dimensions: first, the degree to which first-person perspective predominates in the episodic imagery, and second, the degree to which the self is visually salient from a third-person perspective. We show that, in episodic future thinking, these are anticorrelated but non-redundant. These results further our basic understanding of the potent but divergent effects visual perspective has on emotion and motivation, both in everyday life and in psychiatric conditions.

Capturing the Forest but Missing the Trees: Microstates Inadequate for Characterizing Shorter-Scale EEG Dynamics.

The brain is known to be active even when not performing any overt cognitive tasks, and often it engages in involuntary mind wandering. This resting state has been extensively characterized in terms of fMRI-derived brain networks. However, an alternate method has recently gained popularity: EEG microstate analysis. Proponents of microstates postulate that the brain discontinuously switches between four quasi-stable states defined by specific EEG scalp topologies at peaks in the global field potential (GFP). These microstates are thought to be "atoms of thought," involved with visual, auditory, salience, and attention processing. However, this method makes some major assumptions by excluding EEG data outside the GFP peaks and then clustering the EEG scalp topologies at the GFP peaks, assuming that only one microstate is active at any given time. This study explores the evidence surrounding these assumptions by studying the temporal dynamics of microstates and its clustering space using tools from dynamical systems analysis, fractal, and chaos theory to highlight the shortcomings in microstate analysis. The results show evidence of complex and chaotic EEG dynamics outside the GFP peaks, which is being missed by microstate analysis. Furthermore, the winner-takes-all approach of only one microstate being active at a time is found to be inadequate since the dynamic EEG scalp topology does not always resemble that of the assigned microstate, and there is competition among the different microstate classes. Finally, clustering space analysis shows that the four microstates do not cluster into four distinct and separable clusters. Taken collectively, these results show that the discontinuous description of EEG microstates is inadequate when looking at nonstationary short-scale EEG dynamics.

The Effects of Physical Exercise and Cognitive Training on Memory and Neurotrophic Factors.

This study examined the combined effect of physical exercise and cognitive training on memory and neurotrophic factors in healthy, young adults. Ninety-five participants completed 6 weeks of exercise training, combined exercise and cognitive training, or no training (control). Both the exercise and combined training groups improved performance on a high-interference memory task, whereas the control group did not. In contrast, neither training group improved on general recognition performance, suggesting that exercise training selectively increases high-interference memory that may be linked to hippocampal function. Individuals who experienced greater fitness improvements from the exercise training (i.e., high responders to exercise) also had greater increases in the serum neurotrophic factors brain-derived neurotrophic factor and insulin-like growth factor-1. These high responders to exercise also had better high-interference memory performance as a result of the combined exercise and cognitive training compared with exercise alone, suggesting that potential synergistic effects might depend on the availability of neurotrophic factors. These findings are especially important, as memory benefits accrued from a relatively short intervention in high-functioning young adults.

Toward an Open-Ended BCI: A User-Centered Coadaptive Design.

Brain-computer interfaces (BCIs) allow users to control a device by interpreting their brain activity. For simplicity, these devices are designed to be operated by purposefully modulating specific predetermined neurophysiological signals, such as the sensorimotor rhythm. However, the ability to modulate a given neurophysiological signal is highly variable across individuals, contributing to the inconsistent performance of BCIs for different users. These differences suggest that individuals who experience poor BCI performance with one class of brain signals might have good results with another. In order to take advantage of individual abilities as they relate to BCI control, we need to move beyond the current approaches. In this letter, we explore a new BCI design aimed at a more individualized and user-focused experience, which we call open-ended BCI. Individual users were given the freedom to discover their own mental strategies as opposed to being trained to modulate a given brain signal. They then underwent multiple coadaptive training sessions with the BCI. Our first open-ended BCI performed similarly to comparable BCIs while accommodating a wider variety of mental strategies without a priori knowledge of the specific brain signals any individual might use. Post hoc analysis revealed individual differences in terms of which sensory modality yielded optimal performance. We found a large and significant effect of individual differences in background training and expertise, such as in musical training, on BCI performance. Future research should be focused on finding more generalized solutions to user training and brain state decoding methods to fully utilize the abilities of different individuals in an open-ended BCI. Accounting for each individual's areas of expertise could have important implications on BCI training and BCI application design.

A pilot study examining the impact of lithium treatment and responsiveness on mnemonic discrimination in bipolar disorder.

INTRODUCTION: Mnemonic discrimination (MD), the ability to discriminate new stimuli from similar memories, putatively involves dentate gyrus pattern separation. Since lithium may normalize dentate gyrus functioning in lithium-responsive bipolar disorder (BD), we hypothesized that lithium treatment would be associated with better MD in lithium-responsive BD patients. METHODS: BD patients (N = 69; NResponders = 16 [23 %]) performed the Continuous Visual Memory Test (CVMT), which requires discriminating between novel and previously seen images. Before testing, all patients had prophylactic lithium responsiveness assessed over ≥1 year of therapy (with the Alda Score), although only thirty-eight patients were actively prescribed lithium at time of testing (55 %; 12/16 responders, 26/53 nonresponders). We then used computational modelling to extract patient-specific MD indices. Linear models were used to test how (A) lithium treatment, (B) lithium responsiveness via the continuous Alda score, and (C) their interaction, affected MD. RESULTS: Superior MD performance was associated with lithium treatment exclusively in lithium-responsive patients (Lithium x AldaScore ß = 0.257 [SE 0.078], p = 0.002). Consistent with prior literature, increased age was associated with worse MD (ß = -0.03 [SE 0.01], p = 0.005). LIMITATIONS: Secondary pilot analysis of retrospectively collected data in a cross-sectional design limits generalizability. CONCLUSION: Our study is the first to examine MD performance in BD. Lithium is associated with better MD performance only in lithium responders, potentially due to lithium's effects on dentate gyrus granule cell excitability. Our results may influence the development of behavioural probes for dentate gyrus neuronal hyperexcitability in BD.

Altered Resting-State functional connectivity in the anterior and posterior hippocampus in Post-traumatic stress disorder: The central role of the anterior hippocampus.

BACKGROUND: Post-traumatic stress disorder can be viewed as a memory disorder, with trauma-related flashbacks being a core symptom. Given the central role of the hippocampus in autobiographical memory, surprisingly, there is mixed evidence concerning altered hippocampal functional connectivity in PTSD. We shed light on this discrepancy by considering the distinct roles of the anterior versus posterior hippocampus and examine how this distinction may map onto whole-brain resting-state functional connectivity patterns among those with and without PTSD. METHODS: We first assessed whole-brain between-group differences in the functional connectivity profiles of the anterior and posterior hippocampus within a publicly available data set of resting-state fMRI data from 31 male Vietnam war veterans diagnosed with PTSD (mean age = 67.6 years, sd = 2.3) and 29 age-matched combat-exposed male controls (age = 69.1 years, sd = 3.5). Next, the connectivity patterns of each subject within the PTSD group were correlated with their PTSD symptom scores. Finally, the between-group differences in whole-brain functional connectivity profiles discovered for the anterior and posterior hippocampal seeds were used to prescribe post-hoc ROIs, which were then used to perform ROI-to-ROI functional connectivity and graph-theoretic analyses. RESULTS: The PTSD group showed increased functional connectivity of the anterior hippocampus with affective brain regions (anterior/posterior insula, orbitofrontal cortex, temporal pole) and decreased functional connectivity of the anterior/posterior hippocampus with regions involved in processing bodily self-consciousness (supramarginal gyrus). Notably, decreased anterior hippocampus connectivity with the posterior cingulate cortex/precuneus was associated with increased PTSD symptom severity. The left anterior hippocampus also emerged as a central locus of abnormal functional connectivity, with graph-theoretic measures suggestive of a more central hub-like role for this region in those with PTSD compared to trauma-exposed controls. CONCLUSIONS: Our results highlight that the anterior hippocampus plays a critical role in the neurocircuitry underlying PTSD and underscore the importance of the differential roles of hippocampal sub-regions in serving as biomarkers of PTSD. Future studies should investigate whether the differential patterns of functional connectivity stemming from hippocampal sub-regions is observed in PTSD populations other than older war veterans.

The Impact of Aerobic Exercise on Mood Symptoms in Trauma-Exposed Young Adults: A Pilot Study.

Introduction: Physical activity has beneficial effects on mood in both healthy and clinical populations. Emerging literature suggests that physical activity may benefit psychological symptoms, such as depressive mood, in those with post-traumatic stress disorder (PTSD). It is estimated that 76% of Canadians have experienced a traumatic event during their lifetime (Van Ameringen et al., 2008). Thus, there is a large proportion of the population that does not meet criteria for PTSD but may still suffer from trauma-related symptoms such as depression and require support for their mental health. The current pilot study aimed to evaluate the impact of an aerobic exercise intervention on mood symptoms in trauma-exposed young adults. Methods: Twenty-five low active young adults with subclinical trauma symptoms but no current or past diagnosis of PTSD were recruited. Participants were randomly assigned to participate in an 8-week exercise intervention group or a waitlist control group. Mood symptoms were assessed before and after the intervention. In addition, measures of aerobic fitness, trauma symptoms, emotion regulation, and trait mindfulness were assessed at both time points. Results: The exercise intervention was effective at inducing the expected improvements in aerobic fitness. Overall, the exercise group had a significantly greater decrease in mood symptoms across the intervention compared to the waitlist control group. Conclusion: The current pilot study is the first to evaluate the impact of aerobic exercise on mood in trauma-exposed young adults. An 8-week intervention significantly reduced mood symptoms in exercisers relative to waitlist controls. Our results are consistent with previous research indicating that physical activity reduced depressive symptoms in those with PTSD (Rosenbaum et al., 2015b). Importantly, we extend these findings to individuals with subclinical or undiagnosed PTSD symptoms, where exercise may be an effective intervention to improve mood and manage or prevent further decline in mental health in those at risk of developing PTSD.

A critical evaluation of dynamical systems models of bipolar disorder.

Bipolar disorder (BD) is a mood disorder involving recurring (hypo)manic and depressive episodes. The inherently temporal nature of BD has inspired its conceptualization using dynamical systems theory, which is a mathematical framework for understanding systems that evolve over time. In this paper, we provide a critical review of the dynamical systems models of BD. Owing to the heterogeneity of methodological and experimental designs in computational modeling, we designed a structured approach that parallels the appraisal of animal models by their face, predictive, and construct validity. This tool, the validity appraisal guide for computational models (VAG-CM), is not an absolute measure of validity, but rather a guide for a more objective appraisal of models in this review. We identified 26 studies published before November 18, 2021 that proposed generative dynamical systems models of time-varying signals in BD. Two raters independently applied the VAG-CM to the included studies, obtaining a mean Cohen's κ of 0.55 (95% CI [0.45, 0.64]) prior to establishing consensus ratings. Consensus VAG-CM ratings revealed three model/study clusters: data-driven models with face validity, theory-driven models with predictive validity, and theory-driven models lacking all forms of validity. We conclude that future modeling studies should employ a hybrid approach that first operationalizes BD features of interest using empirical data to achieve face validity, followed by explanations of those features using generative models with components that are homologous to physiological or psychological systems involved in BD, to achieve construct validity. Such models would be best developed alongside long-term prospective cohort studies involving a collection of multimodal time-series data. We also encourage future studies to extend, modify, and evaluate the VAG-CM approach for a wider breadth of computational modeling studies and psychiatric disorders.

Combined Aerobic Exercise and Neurofeedback Lead to Improved Task-Relevant Intrinsic Network Synchrony.

Lifestyle interventions such as exercise and mindfulness training have the potential to ameliorate mental health symptoms and restore dysregulated intrinsic connectivity network (ICN) dynamics, seen in many psychopathologies. Multiple lifestyle interventions, in combination, may interact synergistically for enhanced benefits. While the impacts of lifestyle interventions on subjective measures of mood are well-documented, their impacts on ICN dynamics are not well-established. In this study, we assessed the validity of EEG-derived measures of ICN dynamics as potential markers of mood disorders, by tracking ICN dynamics and mood symptoms through the course of a longitudinal exercise intervention. Specifically, we investigated the separate and combined effects of aerobic exercise and mindfulness-like neurofeedback training on task-linked ICN dynamics of the default mode network (DMN), central executive network (CEN), and salience network (SN). Participants were assigned pseudo-randomly into four experimental conditions-Control, Running, Neurofeedback, and Combined, performing the corresponding intervention for 16 sessions across 8 weeks. Intervention-linked changes in ICN dynamics were studied using EEG-based neuroimaging scans before and after the 8-week intervention, during which participants performed multiple blocks of autobiographical memory recall (AM) and working memory (WM) trials, designed to activate the DMN and CEN, respectively, and to activate the SN in conjunction with the task-appropriate network. The EEG-based features for classification of the three core networks had been identified in our prior research from simultaneously recorded EEG and fMRI during the same AM and WM tasks. We categorized participants as "responders" or "non-responders" based on whether the exercise intervention increased their aerobic capacity (VO2-max) (Running/Combined group), and/or neurofeedback increased the percentage time spent in the calm mindfulness state (Neurofeedback/Combined group). In responders, compared to each intervention alone, the combined exercise-neurofeedback intervention resulted in a more healthy CEN-SN synchrony pattern. Interestingly, non-responders to neurofeedback exhibited a maladaptive pattern of persistent, task-inappropriate DMN-SN synchrony which we speculate could be linked to depressive rumination. Furthermore, the CEN-SN synchrony at baseline predicted NFB response with up to 80% accuracy, demonstrating the potential utility of such network-based biomarkers in personalizing intervention plans.

Can homeostatic plasticity in deafferented primary auditory cortex lead to travelling waves of excitation?

Travelling waves of activity in neural circuits have been proposed as a mechanism underlying a variety of neurological disorders, including epileptic seizures, migraine auras and brain injury. The highly influential Wilson-Cowan cortical model describes the dynamics of a network of excitatory and inhibitory neurons. The Wilson-Cowan equations predict travelling waves of activity in rate-based models that have sufficiently reduced levels of lateral inhibition. Travelling waves of excitation may play a role in functional changes in the auditory cortex after hearing loss. We propose that down-regulation of lateral inhibition may be induced in deafferented cortex via homeostatic plasticity mechanisms. We use the Wilson-Cowan equations to construct a spiking model of the primary auditory cortex that includes a novel, mathematically formalized description of homeostatic plasticity. In our model, the homeostatic mechanisms respond to hearing loss by reducing inhibition and increasing excitation, producing conditions under which travelling waves of excitation can emerge. However, our model predicts that the presence of spontaneous activity prevents the development of long-range travelling waves of excitation. Rather, our simulations show short-duration excitatory waves that cancel each other out. We also describe changes in spontaneous firing, synchrony and tuning after simulated hearing loss. With the exception of shifts in characteristic frequency, changes after hearing loss were qualitatively the same as empirical findings. Finally, we discuss possible applications to tinnitus, the perception of sound without an external stimulus.

Peer victimization, depressive symptoms, and high salivary cortisol predict poorer memory in children.

The predictive relations of peer victimization, depressive symptoms, and salivary cortisol on memory in 168 children aged 12 at Time 1 (T1) were examined using a longitudinal design in which data were collected on four occasions over a 2-year period. Results indicated that: (1) peer victimization, depressive symptoms, and evening cortisol were stable over time, (2) peer victimization and elevated symptoms of depression were concurrently linked at each time, (3) T1 peer victimization predicted elevated symptoms of depression at T2 which in turn predicted lower cortisol levels at T3, and (4) controlling for earlier associations, T3 peer victimization, depressive symptoms, and higher morning and evening cortisol levels uniquely predicted memory deficits at T4. The links between elevated cortisol, symptoms of depression, and poor memory are consistent with published research on depressed adults and extend the findings to children exposed to peer victimization. These findings highlight that peer abuse is harmful and may impact children's long-term mental health and memory functioning.

Computational models of millisecond level duration tuning in neural circuits.

Discrimination of stimulus duration on the order of milliseconds has been observed in behavioral and neurophysiological studies across a variety of species and taxa. Several studies conducted in mammals have found neurons in the auditory midbrain (inferior colliculus) that are selective for signal duration. Duration selectivity in these cells arises from an interaction of excitatory and inhibitory events occurring at particular latencies from stimulus onset and offset. As previously shown in barn owls, coincidence of delayed, excitatory events can be used by the CNS to respond selectively to specific stimuli in auditory space. This study formulates several computational models of duration tuning that combine existing conceptual models with observed physiological responses in the auditory brainstem and midbrain to evaluate the plausibility of the proposed neural mechanisms. The computational models are able to reproduce a wide range of in vivo responses including best duration tuning, duration-selective response classes, spike counts, first-spike latencies, level tolerance to changes in signal amplitude, and neuropharmacological effects of applying inhibitory neurotransmitter antagonists to duration-tuned neurons. A unified model of duration tuning is proposed that enhances classic models of duration tuning, emphasizes similarities across the models, and simplifies our understanding of duration tuning across species and sensory modalities.

Recovery of High Interference Memory in Spite of Lingering Cognitive Deficits in a Longitudinal Pilot Study of Hospitalized Depressed Patients.

BACKGROUND: Major depressive disorder has deleterious impacts on mood, cognition, and many functions of daily life. Even after remission of mood symptoms, patients frequently report persistent cognitive deficits. By contrast, the neurogenic theory of depression posits that recovery from depression is dependent upon a restoration of neurogenesis. The present study was designed to test this prediction by assessing performance in MDD in-patients on a broad battery of cognitive tasks including the Mnemonic Similarity Task, a high interference memory test that is a putative correlate of neurogenesis. We predicted that remitted patients should exhibit recovery of function on this task, even though they may show residual deficits on other cognitive tasks. METHODS: 18 hospitalized patients diagnosed with MDD and 22 healthy control participants matched for age, sex, and education completed a battery of mood and cognitive tests at two time points. Patients completed their baseline assessments when first admitted to hospital and repeated the same assessments upon remission, typically 4-5 weeks later and just prior to their release from hospital. Control participants were tested at baseline and 4-5 weeks later on the same assessment battery, which included the BDI-II, BAI, Cohen's PSS, Mnemonic Similarity Task, and several sub-tests adapted from the CANTAB. RESULTS: At baseline, MDD patients were impaired relative to controls on the MST and many other cognitive tasks. Upon remission, patients' MST scores did not differ from those of healthy controls, although patients were still impaired on Pattern Recognition Memory, Spatial Recognition Memory, Delayed Matching to Sample and Paired Associates Learning relative to healthy control participants. CONCLUSION: The lingering memory deficits observed in remitted patients with MDD observed here are broadly consistent with findings in the literature. Importantly, however, remitted patients showed recovery of cognitive function on the Mnemonic Similarity Task. This is the first study that we are aware of to report recovery of function on a high interference, putatively neurogenesis-dependent memory test in a longitudinal sample of hospitalized MDD patients from admission to remission. Our findings are consistent with the neurogenic theory of depression, which posits that a restoration of neurogenesis is linked to recovery from depression.

Using Deep Learning Algorithms to Grade Hydronephrosis Severity: Toward a Clinical Adjunct.

Grading hydronephrosis severity relies on subjective interpretation of renal ultrasound images. Deep learning is a data-driven algorithmic approach to classifying data, including images, presenting a promising option for grading hydronephrosis. The current study explored the potential of deep convolutional neural networks (CNN), a type of deep learning algorithm, to grade hydronephrosis ultrasound images according to the 5-point Society for Fetal Urology (SFU) classification system, and discusses its potential applications in developing decision and teaching aids for clinical practice. We developed a five-layer CNN to grade 2,420 sagittal hydronephrosis ultrasound images [191 SFU 0 (8%), 407 SFU I (17%), 666 SFU II (28%), 833 SFU III (34%), and 323 SFU IV (13%)], from 673 patients ranging from 0 to 116.29 months old (M age = 16.53, SD = 17.80). Five-way (all grades) and two-way classification problems [i.e., II vs. III, and low (0-II) vs. high (III-IV)] were explored. The CNN classified 94% (95% CI, 93-95%) of the images correctly or within one grade of the provided label in the five-way classification problem. Fifty-one percent of these images (95% CI, 49-53%) were correctly predicted, with an average weighted F1 score of 0.49 (95% CI, 0.47-0.51). The CNN achieved an average accuracy of 78% (95% CI, 75-82%) with an average weighted F1 of 0.78 (95% CI, 0.74-0.82) when classifying low vs. high grades, and an average accuracy of 71% (95% CI, 68-74%) with an average weighted F1 score of 0.71 (95% CI, 0.68-0.75) when discriminating between grades II vs. III. Our model performs well above chance level, and classifies almost all images either correctly or within one grade of the provided label. We have demonstrated the applicability of a CNN approach to hydronephrosis ultrasound image classification. Further investigation into a deep learning-based clinical adjunct for hydronephrosis is warranted.

Impact of a structured, group-based running programme on clinical, cognitive and social function in youth and adults with complex mood disorders: a 12-week pilot study.

BACKGROUND: Individuals with mood disorders often report lingering health-related quality of life (HRQOL) and social and cognitive impairments even after mood symptoms have improved. Exercise programmes improve mood symptoms in patients, but whether exercise improves functional outcomes in patients with difficult-to-treat mood disorders remains unknown. DESIGN: We evaluated the impact of a 12-week structured running programme on cognitive, social and quality-of-life outcomes in participants with difficult-to-treat mood disorders. METHODS: In a prospective, open-label study, patients referred to the St Joseph's Healthcare Hamilton Team Unbreakable running programme for youth and adults with mood disorders completed a comprehensive assessment battery before and after the 12-week exercise intervention. RESULTS: We collected preintervention and postintervention data from 18 participants who improved on the general health, vitality, role of emotions, social functioning and mental health (all p≤0.01) HRQOL subscales. Performance improved on cognitive tests that assessed working memory and processing speed (p≤0.04); there were no improvements in complex executive functioning tasks. Regression analyses indicated that younger age, shorter illness duration and reduced bodily pain predicted social and cognitive outcomes. CONCLUSION: Participation in a group-based, structured running programme was associated with improved HRQOL and social and cognitive function.

A model of hippocampal neurogenesis in memory and mood disorders.

The mounting evidence for neurogenesis in the adult hippocampus has fundamentally challenged the traditional view of brain development. The intense search for clues as to the functional significance of the new neurons has uncovered a surprising connection between neurogenesis and depression. In animal models of depression, neurogenesis is reduced, whereas many treatments for depression promote neurogenesis. We speculate on why the hippocampus, traditionally viewed as a memory structure, might be involved in mood disorders, and what specific role the new neurons might have in the pathogenesis of and recovery from depression. The proposed role of neurogenesis in contextual-memory formation predicts a specific pattern of cognitive deficits in depression and has important implications for treatment of this highly prevalent and debilitating disorder.

A neural network model of hippocampal-striatal-prefrontal interactions in contextual conditioning.

The hippocampus is thought to be critical for encoding contextually bound memories and setting the context for ongoing behavior. However, the mechanisms by which the hippocampal-cortical system controls behavior are poorly understood. We propose a computational model in which the hippocampus exerts contextual control over motivated behavior by gating prefrontal cortex inputs to the nucleus accumbens. The model integrates the episodic memory functions of the hippocampus, the prefrontal role in representing the motivational stimuli and cognitive control, and the role of striatal regions in conditioned learning within a single theoretical framework. Simulation results are consistent with the hypothesis that hippocampal-prefrontal interactions may act as the neural substrate that allows contextual cues to override conditioned responses at the level of the nucleus accumbens. Prefrontal and hippocampal input overrides the predominant CS-US association if the context is inconsistent, and promotes flexible selection of previously learned associations and behaviors. Simulated transection of the fornix, effectively eliminating hippocampal and prefrontal influence over the nucleus accumbens, abolishes normal contextual modulation of behavior. The model is consistent with a wide range of empirical data.