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Introduction: Diagnostic classification systems and guidelines posit distinguishing patterns of impairment in Alzheimer's (AD) and vascular dementia (VaD). In our study, we aim to identify which diagnostic instruments distinguish them. Methods: We searched PubMed and PsychInfo for empirical studies published until December 2020, which investigated differences in cognitive, behavioral, psychiatric, and functional measures in patients older than 64years and reported information on VaD subtype, age, education, dementia severity, and proportion of women. We systematically reviewed these studies and conducted Bayesian hierarchical metaregressions to quantify the evidence for differences using the Bayes factor (BF). The risk of bias was assessed using the Newcastle-Ottawa-Scale and funnel plots. Results: We identified 122 studies with 17,850 AD and 5,247 VaD patients. Methodological limitations of the included studies are low comparability of patient groups and an untransparent patient selection process. In the digit span backward task, AD patients were nine times more probable (BF = 9.38) to outperform VaD patients (βg = 0.33, 95% ETI = 0.12, 0.52). In the phonemic fluency task, AD patients outperformed subcortical VaD (sVaD) patients (βg = 0.51, 95% ETI = 0.22, 0.77, BF = 42.36). VaD patients, in contrast, outperformed AD patients in verbal (βg = -0.61, 95% ETI = -0.97, -0.26, BF = 22.71) and visual (βg = -0.85, 95% ETI = -1.29, -0.32, BF = 13.67) delayed recall. We found the greatest difference in verbal memory, showing that sVaD patients outperform AD patients (βg = -0.64, 95% ETI = -0.88, -0.36, BF = 72.97). Finally, AD patients performed worse than sVaD patients in recognition memory tasks (βg = -0.76, 95% ETI = -1.26, -0.26, BF = 11.50). Conclusion: Our findings show inferior performance of AD in episodic memory and superior performance in working memory. We found little support for other differences proposed by diagnostic systems and diagnostic guidelines. The utility of cognitive, behavioral, psychiatric, and functional measures in differential diagnosis is limited and should be complemented by other information. Finally, we identify research areas and avenues, which could significantly improve the diagnostic value of cognitive measures. [ABSTRACT FROM AUTHOR]

Objective: Elevated cortisol levels have been frequently reported in Alzheimer's disease (AD) and linked to brain atrophy, especially of the hippocampus. Besides, high cortisol levels have been shown to impair memory performance and increase the risk of developing AD in healthy individuals. We investigated the associations between serum cortisol levels, hippocampal volume, gray matter volume and memory performance in healthy aging and AD. Methods: In our cross-sectional study, we analyzed the relationships between morning serum cortisol levels, verbal memory performance, hippocampal volume, and whole-brain voxel-wise gray matter volume in an independent sample of 29 healthy seniors (HS) and 29 patients along the spectrum of biomarker-based AD. Results: Cortisol levels were significantly elevated in patients with AD as compared to HS, and higher cortisol levels were correlated with worse memory performance in AD. Furthermore, higher cortisol levels were significantly associated with smaller left hippocampal volumes in HS and indirectly negatively correlated to memory function through hippocampal volume. Higher cortisol levels were further related to lower gray matter volume in the hippocampus and temporal and parietal areas in the left hemisphere in both groups. The strength of this association was similar in HS and AD. Conclusion: In AD, cortisol levels are elevated and associated with worse memory performance. Furthermore, in healthy seniors, higher cortisol levels show a detrimental relationship with brain regions typically affected by AD. Thus, increased cortisol levels seem to be indirectly linked to worse memory function even in otherwise healthy individuals. Cortisol may therefore not only serve as a biomarker of increased risk for AD, but maybe even more importantly, as an early target for preventive and therapeutic interventions. [ABSTRACT FROM AUTHOR]

Aging is associated with memory decline and progressive disabilities in the activities of daily living. These deficits have a significant impact on the quality of life of the aging population and lead to a tremendous burden on societies and health care systems. Understanding the mechanisms underlying aging-related memory decline is likely to inform the development of compensatory strategies promoting independence in old age. Research on aging-related memory decline has mainly focused on encoding and retrieval. However, some findings suggest that memory deficits may at least partly be due to impaired consolidation. To date, it remains elusive whether aging-related memory decline results from defective consolidation. This study examined age effects on consolidation-related neural mechanisms and their susceptibility to interference using functional magnetic resonance imaging data from 13 younger (20–30 years, 8 female) and 16 older (49–75 years, 5 female) healthy participants. fMRI was performed before and during a memory paradigm comprised of encoding, consolidation, and retrieval phases. Consolidation was variously challenged: (1) control (no manipulation), (2) interference (repeated stimulus presentation with interfering information), and (3) reminder condition (repeated presentation without interfering information). We analyzed the fractional amplitude of low-frequency fluctuations (fALFF) to compare brain activity changes from pre- to post-encoding rest. In the control condition, fALFF was decreased in the left supramarginal gyrus, right middle temporal gyrus, and left precuneus but increased in parts of the occipital and inferior temporal cortex. Connectivity analyses between fALFF-derived seeds and network ROIs revealed an aging-related decrease in the efficiency of functional connectivity (FC) within the ventral stream network and between salience, default mode, and central executive networks during consolidation. Moreover, our results indicate increased interference susceptibility in older individuals with dynamics between salience and default mode networks as a neurophysiological correlate. Conclusively, aging-related memory decline is partly caused by inefficient consolidation. Memory consolidation requires a complex interplay between large-scale brain networks, which qualitatively decreases with age. [ABSTRACT FROM AUTHOR]

Background: Early and severe neuronal loss in the cholinergic basal forebrain is observed in Alzheimer's disease (AD). To date, cholinomimetics play a central role in the symptomatic treatment of AD dementia. Although basic research indicates that a cholinergic deficit is present in AD before dementia, the efficacy of cholinomimetics in mild cognitive impairment (MCI) remains controversial. Predictors of cholinergic impairment could guide individualized therapy.Objective: To investigate if the extent of the cholinergic deficit, measured using positron emission tomography (PET) and the tracer 11C-N-methyl-4-piperidyl acetate (MP4A), could be predicted from the volume of cholinergic basal forebrain nuclei in non-demented AD patients.Methods: Seventeen patients with a high likelihood of MCI due to AD and 18 age-matched cognitively healthy adults underwent MRI-scanning. Basal forebrain volume was assessed using voxel-based morphometry and a cytoarchitectonic atlas of cholinergic nuclei. Cortical acetylcholinesterase (AChE) activity was measured using MP4A-PET.Results: Cortical AChE activity and nucleus basalis of Meynert (Ch4 area) volume were significantly decreased in MCI. The extent of the cholinergic deficit varied considerably across patients. Greater volumes of anterior basal forebrain nuclei (Ch1/2 area) and younger age (Spearman's rho (17)  = -0.596, 95% -CI [-0.905, -0.119] and 0.593, 95% -CI [0.092, 0.863])) were associated with a greater cholinergic deficit.Conclusion: Data suggest that less atrophy of the Ch1/2 area and younger age are associated with a more significant cholinergic deficit in MCI due to AD. Further investigations are warranted to determine if the individual response to cholinomimetics can be inferred from these measures. [ABSTRACT FROM AUTHOR]

Background: To date, it remains unclear how amyloid plaques and neurofibrillary tangles are related to neural activation and, consequently, cognition in Alzheimer's disease (AD). Recent findings indicate that tau accumulation may drive hippocampal hyperactivity in cognitively normal aging, but it remains to be elucidated how tau accumulation is related to neural activation in AD.Objective: To determine whether the association between tau accumulation and hippocampal hyperactivation persists in mild cognitive impairment (MCI) and mild dementia or if the two measures dissociate with disease progression, we investigated the relationship between local tau deposits and memory-related neural activation in MCI and mild dementia due to AD.Methods: Fifteen patients with MCI or mild dementia due to AD underwent a neuropsychological assessment and performed an item memory task during functional magnetic resonance imaging. Cerebral tau accumulation was assessed using positron emission tomography and [18F]-AV-1451.Results: Entorhinal, but not global tau accumulation, was highly correlated with hippocampal activation due to visual item memory encoding and predicted memory loss over time. Neural activation in the posterior cingulate cortex and the fusiform gyrus was not significantly correlated with tau accumulation.Conclusion: These findings extend previous observations in cognitively normal aging, demonstrating that entorhinal tau continues to be closely associated with hippocampal hyperactivity and memory performance in MCI and mild dementia due to AD. Furthermore, data suggest that this association is strongest in medial temporal lobe structures. In summary, our data provide novel insights into the relationship of tau accumulation to neural activation and memory in AD. [ABSTRACT FROM AUTHOR]

Objective : In subjects with mild cognitive impairment (MCI), interference during memory consolidation may further degrade subsequent recall of newly learned information. We investigated whether spatial and object memory are differentially susceptible to interference. Method : Thirty-nine healthy young subjects, 39 healthy older subjects, and 12 subjects suffering from MCI encoded objects and their spatial position on a 4-by-5 grid. Encoding was followed by either: (i) a pause; (ii) an interference task immediately following encoding; or (iii) an interference task following encoding after a 6-min delay. Type of interference (no, early, delayed) was applied in different sessions and order was counterbalanced. Twelve minutes after encoding, subjects saw objects previously presented or new ones. Subjects indicated whether they recognized the object, and if so, the objects' position during encoding. Results : Interference during consolidation provoked a negative effect on spatial memory in young more than older controls. In MCI, object but not spatial memory was affected by interference. Furthermore, a shift from fine- to coarse-grained spatial representation was observed in MCI. No differential effect of early vs. late interference (EI vs. LI) in either of the groups was detected. Conclusions : Data show that consolidation in healthy aging and MCI differs from consolidation in young controls. Data suggest differential processes underlying object and spatial memory and that these are differentially affected by aging and MCI. [ABSTRACT FROM AUTHOR]

The diagnosis of Alzheimer's disease (AD), especially in the early stage, is still not very reliable and the development of new diagnosis tools is desirable. A diagnosis based on functional magnetic resonance imaging (fMRI) is a suitable candidate, since fMRI is non-invasive, readily available, and indirectly measures synaptic dysfunction, which can be observed even at the earliest stages of AD. However, the results of previous attempts to analyze graph properties of resting state fMRI data are contradictory, presumably caused by methodological differences in graph construction. This comprises two steps: clustering the voxels of the functional image to define the nodes of the graph, and calculating the graph's edge weights based on a functional connectivity measure of the average cluster activities. A variety of methods are available for each step, but the robustness of results to method choice, and the suitability of the methods to support a diagnostic tool, are largely unknown. To address this issue, we employ a range of commonly and rarely used clustering and edge definition methods and analyze their graph theoretic measures (graph weight, shortest path length, clustering coefficient, and weighted degree distribution and modularity) on a small data set of 26 healthy controls, 16 subjects with mild cognitive impairment (MCI) and 14 with Alzheimer's disease. We examine the results with respect to statistical significance of the mean difference in graph properties, the sensitivity of the results to model and parameter choices, and relative diagnostic power based on both a statistical model and support vector machines. We find that different combinations of graph construction techniques yield contradicting, but statistically significant, relations of graph properties between health conditions, explaining the discrepancy across previous studies, but casting doubt on such analyses as a method to gain insight into disease effects. The production of significant differences in mean graph properties turns out not to be a good predictor of future diagnostic capacity. Highest predictive power, expressed by largest negative surprise values, are achieved for both atlas-driven and data-driven clustering (Ward clustering), as long as graphs are small and clusters large, in combination with edge definitions based on correlations and mutual information transfer. [ABSTRACT FROM AUTHOR]

In early Alzheimer's disease, which initially presents with progressive loss of short-term memory, neurodegeneration especially affects cholinergic neurons of the basal forebrain. Pharmacotherapy of Alzheimer's disease therefore often targets the cholinergic system. In contrast, cholinergic pharmacotherapy of mild cognitive impairment is debated since its efficacy to date remains controversial. We here investigated the relationship between cholinergic treatment effects and the integrity of the cholinergic system in mild cognitive impairment due to Alzheimer's disease. Fourteen patients with high likelihood of mild cognitive impairment due to Alzheimer's disease and 16 age-matched cognitively normal adults performed an episodic memory task during functional magnetic resonance imaging under three conditions: (i) without pharmacotherapy; (ii) with placebo; and (iii) with a single dose of rivastigmine (3 mg). Cortical acetylcholinesterase activity was measured using PET with the tracer 11C-N-methyl-4-piperidyl acetate (MP4A). Cortical acetylcholinesterase activity was significantly decreased in patients relative to controls, especially in the lateral temporal lobes. Without pharmacotherapy, mild cognitive impairment was associated with less memory-related neural activation in the fusiform gyrus and impaired deactivation in the posterior cingulate cortex, relative to controls. These differences were attenuated under cholinergic stimulation with rivastigmine: patients showed increased neural activation in the right fusiform gyrus but enhanced deactivation of the posterior cingulate cortex under rivastigmine, compared to placebo. Conversely, controls showed reduced activation of the fusiform gyrus and reduced deactivation of the posterior cingulate under rivastigmine, compared to placebo. In both groups, the change in neural activation in response to rivastigmine was negatively associated with local acetylcholinesterase activity. At the behavioural level, an analysis of covariance revealed a significant group × treatment interaction in episodic memory performance when accounting for hippocampal grey matter atrophy and function. Our results indicate that rivastigmine differentially affects memory-related neural activity in patients with mild cognitive impairment and cognitively normal, age-matched adults, depending on acetylcholinesterase activity as a marker for the integrity of the cortical cholinergic system. Furthermore, hippocampal integrity showed an independent association with the response of memory performance to acetylcholinesterase inhibition. [ABSTRACT FROM AUTHOR]

See Whitwell (doi:10.1093/brain/awy001) for a scientific commentary on this article.A stereotypical anatomical propagation of tau pathology has been described in Alzheimer's disease. According to recent concepts (network degeneration hypothesis), this propagation is thought to be indicative of misfolded tau proteins possibly spreading along functional networks. If true, tau pathology accumulation should correlate in functionally connected brain regions. Therefore, we examined whether independent components could be identified in the distribution pattern of in vivo tau pathology and whether these components correspond with specific functional connectivity networks. Twenty-two 18F-AV-1451 PET scans of patients with amnestic Alzheimer's disease (mean age = 66.00 ± 7.22 years, 14 males/eight females) were spatially normalized, intensity standardized to the cerebellum, and z-transformed using the mean and deviation image of a healthy control sample to assess Alzheimer's disease-related tau pathology. First, to detect distinct tau pathology networks, the deviation maps were subjected to an independent component analysis. Second, to investigate if regions of high tau burden are associated with functional connectivity networks, we extracted the region with the maximum z-value in each of the generated tau pathology networks and used them as seeds in a subsequent resting-state functional MRI analysis, conducted in a group of healthy adults (n = 26) who were part of the 1000 Functional Connectomes Project. Third, to examine if tau pathology co-localizes with functional connectivity networks, we quantified the spatial overlap between the seed-based networks and the corresponding tau pathology network by calculating the Dice similarity coefficient. Additionally, we assessed if the tau-dependent seed-based networks correspond with known functional resting-state networks. Finally, we examined the relevance of the identified components in regard to the neuropathological Braak stages. We identified 10 independently coherent tau pathology networks with the majority showing a symmetrical bi-hemispheric expansion and coinciding with highly functionally connected brain regions such as the precuneus and cingulate cortex. A fair-to-moderate overlap was observed between the tau pathology networks and corresponding seed-based networks (Dice range: 0.13-0.57), which in turn resembled known resting-state networks, particularly the default mode network (Dice range: 0.42-0.56). Moreover, greater tau burden in the tau pathology networks was associated with more advanced Braak stages. Using the data-driven approach of an independent component analysis, we observed a set of independently coherent tau pathology networks in Alzheimer's disease, which were associated with disease progression and coincided with functional networks previously reported to be impaired in Alzheimer's disease. Together, our results provide novel information regarding the impact of tau pathology networks on the mechanistic pathway of Alzheimer's disease. [ABSTRACT FROM AUTHOR]

Neurodegenerative brain changes can affect the functional connectivity strength between nodes of the default-mode network (DMN), which may underlie changes in cognitive performance. It remains unclear how the functional connectivity strength of DMN nodes differs from healthy to pathological aging and whether these changes are cognitively relevant. We used resting-state functional magnetic resonance imaging to investigate the functional connectivity strength across five DMN nodes in 25 healthy controls (HC), 28 subjective cognitive decline (SCD) participants, and 25 prodromal Alzheimer's disease (AD) patients. After identifying the ventral medial prefrontal cortex (vmPFC), posterior cingulate cortex (PCC), retrosplenial cortex (RSC), inferior parietal lobule, and the hippocampus we investigated the functional strength between DMN nodes using temporal network modeling. Functional coupling of the vmPFC and PCC in prodromal AD patients was disrupted. This vmPFC-PCC coupling correlated positively with memory performance in prodromal AD. Furthermore, the hippocampus de-coupled from posterior DMN nodes in SCD and prodromal AD patients. There was no coupling between the hippocampus and the anterior DMN. Additional mediation analyses indicated that the RSC enables communication between the hippocampus and DMN regions in HC but none of the other two groups. These results suggest an anterior-posterior disconnection and a hippocampal de-coupling from posterior DMN nodes with disease progression. Hippocampal de-coupling already occurring in SCD may provide valuable information for the development of a functional biomarker. [ABSTRACT FROM AUTHOR]

The clinical heterogeneity of Alzheimer's disease is not reflected in the rather diffuse cortical deposition of amyloid-β. We assessed the relationship between clinical symptoms, in vivo tau pathology, amyloid distribution, and hypometabolism in variants of Alzheimer's disease using novel multimodal PET imaging techniques. Tau pathology was primarily observed in brain regions related to clinical symptoms and overlapped with areas of hypometabolism. In contrast, amyloid-β deposition was diffusely distributed over the entire cortex. Tau PET imaging may thus serve as a valuable biomarker for the localization of neuronal injury in vivo and may help to validate atypical subtypes of Alzheimer's disease. [ABSTRACT FROM AUTHOR]

In a multimodal PET imaging approach, we determined the differential contribution of neurofibrillary tangles (measured with [18F] AV-1451) and beta-amyloid burden (measured with [11C]PiB) on degree of neurodegeneration (i.e., glucose metabolism measured with [18F] FDG- PET) in patients with Alzheimer's disease. Across brain regions, we observed an interactive effect of beta-amyloid burden and tau deposition on glucose metabolism which was most pronounced in the parietal lobe. Elevated beta-amyloid burden was associated with a stronger influence of tau accumulation on glucose metabolism. Our data provide the first in vivo insights into the differential contribution of A β and tau to neurodegeneration in Alzheimer's disease. [ABSTRACT FROM AUTHOR]

Background: Episodic memory decline characterizes "normal" aging but is also a core symptom of Alzheimer's disease. Therefore, considerable efforts have been undertaken to study this memory domain and its neural substrates. Recent studies have mainly focused on encoding‐ and retrieval‐ related processes. However, some findings suggest that episodic memory deficits are at least in part due to impaired consolidation processes. Methods: We investigated age effects on consolidation‐related functional network changes and their vulnerability to cognitive interference, using fMRI data of 13 young (20–30 years) and 16 senior (49–75 years) participants. FMRI scanning was performed prior to and during a spatial memory paradigm, consisting of encoding, consolidation, and retrieval phases. To ensure that the observed connectivity changes were due to consolidation processes, the consolidation phase was manipulated over two sessions: (1) no manipulation and (2) repeated stimulus‐presentation with interfering spatial context information. Results: We compared the fractional amplitude of low‐frequency fluctuations (fALFF) to analyze spontaneous brain activity changes from pre‐ to post‐encoding rest. In the control condition, fALFF decreased within left supramarginal gyrus (SMG), right middle temporal gyrus (MTL), and left precuneus (Pc), whereas, fALFF increased within parts of the occipital and inferior temporal cortex. To evaluate the integration in large‐scale brain networks, connectivity analyses between the fALFF‐derived seeds and network ROIs were performed. We observed significant coupling between consolidation‐related brain regions and large‐scale brain networks during consolidation, with connectivity between the SMG and large parts of the memory network modulated by aging. There was also a disruptive effect of interference on connectivity between the Pc and parts of the salience network. Of particular importance for successful consolidation, however, is the connectivity between parts of the occipital lobe, the inferior and middle temporal gyrus. Connectivity within this network, which corresponds to the ventral visual stream, may predict subsequent memory performance. The predictive value appears to be higher in young than in seniors. Conclusion: Our results support the assumption that age‐related memory decline is at least partly caused by impaired consolidation processes. We showed that consolidation requires a complex interplay between large‐scale brain networks, which is partially disrupted by aging and thus becomes insufficient. [ABSTRACT FROM AUTHOR]

Data is inconsistent concerning the question whether cognitive-physical training (CPT) yields stronger cognitive gains than cognitive training (CT). Effects of additional counseling, neurobiological mechanisms, and predictors have scarcely been studied. Healthy older adults were trained with CT (n = 20), CPT (n = 25), or CPT with counseling (CPT+C; n = 23). Cognition, physical fitness, BDNF, IGF-1, and VEGF were assessed at pre- and post-test. No interaction effects were found except for one effect showing that CPT+C led to stronger gains in verbal fluency than CPT (p = 0.03). However, this superiority could not be assigned to additional physical training gains. Low baseline cognitive performance and BDNF, not carrying apoE4, gains in physical fitness and the moderation of gains in physical fitness × gains in BDNF predicted training success. Although all types of interventions seem successful to enhance cognition, our data do not support the hypotheses that CPT shows superior CT gains compared to CT or that CPT+C adds merit to CPT. However, as CPT leads to additional gains in physical fitness which in turn is known to have positive impact on cognition in the long-term, CPT seems more beneficial. Training success can partly be predicted by neuropsychological, neurobiological, and genetic parameters. [ABSTRACT FROM AUTHOR]

Memory encoding and retrieval problems are inherent to aging. To date, however, the effect of aging upon the neural correlates of forming memory traces remains poorly understood. Resting-state fMRI connectivity can be used to investigate initial consolidation. We compared within and between network connectivity differences between healthy young and older participants before encoding, after encoding and before retrieval by means of resting-state fMRI. Alterations over time in the between-network connectivity analyses correlated with retrieval performance, whereas within-network connectivity did not: a higher level of negative coupling or competition between the default mode and the executive networks during the after encoding condition was associated with increased retrieval performance in the older adults, but not in the young group. Data suggest that the effective formation of memory traces depends on an age-dependent, dynamic reorganization of the interaction between multiple, large-scale functional networks. Our findings demonstrate that a cross-network based approach can further the understanding of the neural underpinnings of aging-associated memory decline. [ABSTRACT FROM AUTHOR]

The cerebral cholinergic system is centrally involved in memory formation. Studies in rodents suggest that cholinergic stimulation may facilitate encoding of new information but may interfere with retrieval. We investigated the effect of cholinergic stimulation on encoding and retrieval of episodic memory in humans. We also tested whether the putative benefit of cholinergic stimulation on memory function depends on individual baseline performance. Since such effects were expected to be greatest in an older population resulting from an age-related degeneration of the cholinergic system, we recruited 22 healthy older subjects (51- 68 years) for an event-related functional magnetic resonance imaging experiment. In two separate scanning sessions, subjects encoded and retrieved items and their spatial context under cholinergic stimulation or placebo with the acetylcholine-esterase inhibitor physostigmine or saline being administered intravenously in a double-blind cross-over design. Baseline performance was recorded at a separate occasion without scanning. Cholinergic stimulation enhanced neural activity for successful versus unsuccessful spatial context encoding in the right hippocampus but reduced activity for successful versus unsuccessful spatial context retrieval in the right amygdala. These data may bridge the gap between rodent and human studies by showing that also in man cholinergic stimulation enhances encoding but interferes with retrieval on a neural level. Furthermore, baseline performance negatively correlated with the effect of cholinergic stimulation. Thus, participants who were worse at baseline benefited more from cholinergic stimulation than those who had better baseline values, indicating that a cholinergic deficit contributes to the memory decline even in healthy older subjects. [ABSTRACT FROM AUTHOR]

An emerging theme in the neuroscience of emotion is the question of how acute stress shapes, and distorts, social-emotional behavior. The prevailing neurocircuitry models of social-emotional behavior emphasize the central role of the amygdala. Acute stress leads to increased central levels of norepinephrine (NE) and cortisol (CORT), and evidence suggests that these endogenous neuromodulators synergistically influence amygdala responses to social-emotional stimuli. We therefore hypothesized that amygdala responses to emotional facial expressions would be susceptible to pharmacologically induced increases in central NE and CORT levels. To specifically test this hypothesis, we measured amygdala activation to emotional faces using functional magnetic resonance imaging in 62 healthy subjects under four pharmacological conditions: (1) single oral dose of placebo, (2) 4mg of the selective NE-reuptake inhibitor reboxetine (RBX), (3) 30mg of hydrocortisone, or (4) both drugs in combination. We found that a decrease in amygdala activation to positive facial emotion was coupled with an increase in amygdala activation to negative facial emotion in the RBX-CORT combined challenge condition. In conclusion, a pharmacologically induced elevation of central NE and CORT levels in healthy subjects created a negative response bias in the amygdala that did not exist at baseline. Our results implicate a causative role of NE-CORT interactions in the emergence of a negative bias of cognitive and emotional functions which is germane in stress-related affective spectrum disorders. [ABSTRACT FROM AUTHOR]

To elucidate the mechanism of action of the anticonvulsant gabapentin (GBP), we compared its effects on K+-evoked [3H]-noradrenaline ([3H]-NA) release from rat hippocampal and human neocortical slices with those of the KATP channel opener pinacidil and the Na+ channel blockers phenytoin, carbamazepine and lamotrigine. Rat hippocampal and human neocortical slices were loaded with [3H]-NA and superfused. [3H]-NA release was evoked by increasing the extracellular [K+] from 3 to 15 mM. GBP decreased [3H]-NA release from rat hippocampal with a pIC50 of 5.59 and a maximum inhibition of 44%. Concentration-dependent inhibition was also seen in human neocortical slices (39% inhibition with 100 µM GBP). These inhibitory effects were antagonized by the KATP channel antagonist glibenclamide, yielding a pA2 of 7.50 in the rat. The KATP channel opener pinacidil (10 µM), like GBP, decreased [3H]-NA release from rat hippocampal slices by 27% and this effect was also antagonized by glibenclamide. In human neocortical slices the inhibition by pinacidil (10 µM) was 31%. Although phenytoin (10 µM), carbamazepine (100 µM) and lamotrigine (10 µM) also decreased [3H]-NA release (by 25%, 57% and 22%, respectively), glibenclamide did not antagonize the effects of these classical Na+ channel blockers. These findings suggest that GBP inhibits K+-evoked [3H]-NA release through activation of KATP channels. To establish whether the KATP channels under investigation were located on noradrenergic nerve terminals or on other neuronal elements, the effects of GBP were compared in the absence and in the presence of tetrodotoxin (TTX 0.32 µM) throughout superfusion. Since the functional elimination of the perikarya of interneurons by TTX reduced the inhibitory effect of GBP, the KATP channels mediating the effect of GBP may be located on nerve terminals, probably on both noradrenergic and glutamatergic nerve endings. [ABSTRACT FROM AUTHOR]

Table of contents A1 Functional advantages of cell-type heterogeneity in neural circuits Tatyana O. Sharpee A2 Mesoscopic modeling of propagating waves in visual cortex Alain Destexhe A3 Dynamics and biomarkers of mental disorders Mitsuo Kawato F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons Vladislav Sekulić, Frances K. Skinner F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks. Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi O3 Modeling auditory stream segregation, build-up and bistability James Rankin, Pamela Osborn Popp, John Rinzel O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields Alejandro Tabas, André Rupp, Emili Balaguer-Ballester O5 A simple model of retinal response to multi-electrode stimulation Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer O7 Input-location dependent gain modulation in cerebellar nucleus neurons Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Nielsen, Volker Steuber O8 Analytic solution of cable energy function for cortical axons and dendrites Huiwen Ju, Jiao Yu, Michael L. Hines, Liang Chen, Yuguo Yu O9 C. elegans interactome: interactive visualization of Caenorhabditis elegans worm neuronal network Jimin Kim, Will Leahy, Eli Shlizerman O10 Is the model any good? Objective criteria for computational neuroscience model selection Justas Birgiolas, Richard C. Gerkin, Sharon M. Crook O11 Cooperation and competition of gamma oscillation mechanisms Atthaphon Viriyopase, Raoul-Martin Memmesheimer, Stan Gielen O12 A discrete structure of the brain waves Yuri Dabaghian, Justin DeVito, Luca Perotti O13 Direction-specific silencing of the Drosophila gaze stabilization system Anmo J. Kim, Lisa M. Fenk, Cheng Lyu, Gaby Maimon O14 What does the fruit fly think about values? A model of olfactory associative learning Chang Zhao, Yves Widmer, Simon Sprecher,Walter Senn O15 Effects of ionic diffusion on power spectra of local field potentials (LFP) Geir Halnes, Tuomo Mäki-Marttunen, Daniel Keller, Klas H. Pettersen,Ole A. Andreassen, Gaute T. Einevoll O16 Large-scale cortical models towards understanding relationship between brain structure abnormalities and cognitive deficits Yasunori Yamada O17 Spatial coarse-graining the brain: origin of minicolumns Moira L. Steyn-Ross, D. Alistair Steyn-Ross O18 Modeling large-scale cortical networks with laminar structure Jorge F. Mejias, John D. Murray, Henry Kennedy, Xiao-Jing Wang O19 Information filtering by partial synchronous spikes in a neural population Alexandra Kruscha, Jan Grewe, Jan Benda, Benjamin Lindner O20 Decoding context-dependent olfactory valence in Drosophila Laurent Badel, Kazumi Ohta, Yoshiko Tsuchimoto, Hokto Kazama P1 Neural network as a scale-free network: the role of a hub B. Kahng P2 Hemodynamic responses to emotions and decisions using near-infrared spectroscopy optical imaging Nicoladie D. Tam P3 Phase space analysis of hemodynamic responses to intentional movement directions using functional near-infrared spectroscopy (fNIRS) optical imaging technique Nicoladie D.Tam, Luca Pollonini, George Zouridakis P4 Modeling jamming avoidance of weakly electric fish Jaehyun Soh, DaeEun Kim P5 Synergy and redundancy of retinal ganglion cells in prediction Minsu Yoo, S. E. Palmer P6 A neural field model with a third dimension representing cortical depth Viviana Culmone, Ingo Bojak P7 Network analysis of a probabilistic connectivity model of the Xenopus tadpole spinal cord Andrea Ferrario, Robert Merrison-Hort, Roman Borisyuk P8 The recognition dynamics in the brain Chang Sub Kim P9 Multivariate spike train analysis using a positive definite kernel Taro Tezuka P10 Synchronization of burst periods may govern slow brain dynamics during general anesthesia Pangyu Joo P11 The ionic basis of heterogeneity affects stochastic synchrony Young-Ah Rho, Shawn D. Burton, G. Bard Ermentrout, Jaeseung Jeong, Nathaniel N. Urban P12 Circular statistics of noise in spike trains with a periodic component Petr Marsalek P14 Representations of directions in EEG-BCI using Gaussian readouts Hoon-Hee Kim, Seok-hyun Moon, Do-won Lee, Sung-beom Lee, Ji-yong Lee, Jaeseung Jeong P15 Action selection and reinforcement learning in basal ganglia during reaching movements Yaroslav I. Molkov, Khaldoun Hamade, Wondimu Teka, William H. Barnett, Taegyo Kim, Sergey Markin, Ilya A. Rybak P17 Axon guidance: modeling axonal growth in T-Junction assay Csaba Forro, Harald Dermutz, László Demkó, János Vörös P19 Transient cell assembly networks encode persistent spatial memories Yuri Dabaghian, Andrey Babichev P20 Theory of population coupling and applications to describe high order correlations in large populations of interacting neurons Haiping Huang P21 Design of biologically-realistic simulations for motor control Sergio Verduzco-Flores P22 Towards understanding the functional impact of the behavioural variability of neurons Filipa Dos Santos, Peter Andras P23 Different oscillatory dynamics underlying gamma entrainment deficits in schizophrenia Christoph Metzner, Achim Schweikard, Bartosz Zurowski P24 Memory recall and spike frequency adaptation James P. Roach, Leonard M. Sander, Michal R. Zochowski P25 Stability of neural networks and memory consolidation preferentially occur near criticality Quinton M. Skilling, Nicolette Ognjanovski, Sara J. Aton, Michal Zochowski P26 Stochastic Oscillation in Self-Organized Critical States of Small Systems: Sensitive Resting State in Neural Systems Sheng-Jun Wang, Guang Ouyang, Jing Guang, Mingsha Zhang, K. Y. Michael Wong, Changsong Zhou P27 Neurofield: a C++ library for fast simulation of 2D neural field models Peter A. Robinson, Paula Sanz-Leon, Peter M. Drysdale, Felix Fung, Romesh G. Abeysuriya, Chris J. Rennie, Xuelong Zhao P28 Action-based grounding: Beyond encoding/decoding in neural code Yoonsuck Choe, Huei-Fang Yang P29 Neural computation in a dynamical system with multiple time scales Yuanyuan Mi, Xiaohan Lin, Si Wu P30 Maximum entropy models for 3D layouts of orientation selectivity Joscha Liedtke, Manuel Schottdorf, Fred Wolf P31 A behavioral assay for probing computations underlying curiosity in rodents Yoriko Yamamura, Jeffery R. Wickens P32 Using statistical sampling to balance error function contributions to optimization of conductance-based models Timothy Rumbell, Julia Ramsey, Amy Reyes, Danel Draguljić, Patrick R. Hof, Jennifer Luebke, Christina M. Weaver P33 Exploration and implementation of a self-growing and self-organizing neuron network building algorithm Hu He, Xu Yang, Hailin Ma, Zhiheng Xu, Yuzhe Wang P34 Disrupted resting state brain network in obese subjects: a data-driven graph theory analysis Kwangyeol Baek, Laurel S. Morris, Prantik Kundu, Valerie Voon P35 Dynamics of cooperative excitatory and inhibitory plasticity Everton J. Agnes, Tim P. Vogels P36 Frequency-dependent oscillatory signal gating in feed-forward networks of integrate-and-fire neurons William F. Podlaski, Tim P. Vogels P37 Phenomenological neural model for adaptation of neurons in area IT Martin Giese, Pradeep Kuravi, Rufin Vogels P38 ICGenealogy: towards a common topology of neuronal ion channel function and genealogy in model and experiment Alexander Seeholzer, William Podlaski, Rajnish Ranjan, Tim Vogels P39 Temporal input discrimination from the interaction between dynamic synapses and neural subthreshold oscillations Joaquin J. Torres, Fabiano Baroni, Roberto Latorre, Pablo Varona P40 Different roles for transient and sustained activity during active visual processing Bart Gips, Eric Lowet, Mark J. Roberts, Peter de Weerd, Ole Jensen, Jan van der Eerden P41 Scale-free functional networks of 2D Ising model are highly robust against structural defects: neuroscience implications Abdorreza Goodarzinick, Mohammad D. Niry, Alireza Valizadeh P42 High frequency neuron can facilitate propagation of signal in neural networks Aref Pariz, Shervin S. Parsi, Alireza Valizadeh P43 Investigating the effect of Alzheimer’s disease related amyloidopathy on gamma oscillations in the CA1 region of the hippocampus Julia M. Warburton, Lucia Marucci, Francesco Tamagnini, Jon Brown, Krasimira Tsaneva-Atanasova P44 Long-tailed distributions of inhibitory and excitatory weights in a balanced network with eSTDP and iSTDP Florence I. Kleberg, Jochen Triesch P45 Simulation of EMG recording from hand muscle due to TMS of motor cortex Bahar Moezzi, Nicolangelo Iannella, Natalie Schaworonkow, Lukas Plogmacher, Mitchell R. Goldsworthy, Brenton Hordacre, Mark D. McDonnell, Michael C. Ridding, Jochen Triesch P46 Structure and dynamics of axon network formed in primary cell culture Martin Zapotocky, Daniel Smit, Coralie Fouquet, Alain Trembleau P47 Efficient signal processing and sampling in random networks that generate variability Sakyasingha Dasgupta, Isao Nishikawa, Kazuyuki Aihara, Taro Toyoizumi P48 Modeling the effect of riluzole on bursting in respiratory neural networks Daniel T. Robb, Nick Mellen, Natalia Toporikova P49 Mapping relaxation training using effective connectivity analysis Rongxiang Tang, Yi-Yuan Tang P50 Modeling neuron oscillation of implicit sequence learning Guangsheng Liang, Seth A. Kiser, James H. Howard, Jr., Yi-Yuan Tang P51 The role of cerebellar short-term synaptic plasticity in the pathology and medication of downbeat nystagmus Julia Goncharenko, Neil Davey, Maria Schilstra, Volker Steuber P52 Nonlinear response of noisy neurons Sergej O. Voronenko, Benjamin Lindner P53 Behavioral embedding suggests multiple chaotic dimensions underlie C. elegans locomotion Tosif Ahamed, Greg Stephens P54 Fast and scalable spike sorting for large and dense multi-electrodes recordings Pierre Yger, Baptiste Lefebvre, Giulia Lia Beatrice Spampinato, Elric Esposito, Marcel Stimberg et Olivier Marre P55 Sufficient sampling rates for fast hand motion tracking Hansol Choi, Min-Ho Song P56 Linear readout of object manifolds SueYeon Chung, Dan D. Lee, Haim Sompolinsky P57 Differentiating models of intrinsic bursting and rhythm generation of the respiratory pre-Bötzinger complex using phase response curves Ryan S. Phillips, Jeffrey Smith P58 The effect of inhibitory cell network interactions during theta rhythms on extracellular field potentials in CA1 hippocampus Alexandra Pierri Chatzikalymniou, Katie Ferguson, Frances K. Skinner P59 Expansion recoding through sparse sampling in the cerebellar input layer speeds learning N. Alex Cayco Gajic, Claudia Clopath, R. Angus Silver P60 A set of curated cortical models at multiple scales on Open Source Brain Padraig Gleeson, Boris Marin, Sadra Sadeh, Adrian Quintana, Matteo Cantarelli, Salvador Dura-Bernal, William W. Lytton, Andrew Davison, R. Angus Silver P61 A synaptic story of dynamical information encoding in neural adaptation Luozheng Li, Wenhao Zhang, Yuanyuan Mi, Dahui Wang, Si Wu P62 Physical modeling of rule-observant rodent behavior Youngjo Song, Sol Park, Ilhwan Choi, Jaeseung Jeong, Hee-sup Shin P64 Predictive coding in area V4 and prefrontal cortex explains dynamic discrimination of partially occluded shapes Hannah Choi, Anitha Pasupathy, Eric Shea-Brown P65 Stability of FORCE learning on spiking and rate-based networks Dongsung Huh, Terrence J. Sejnowski P66 Stabilising STDP in striatal neurons for reliable fast state recognition in noisy environments Simon M. Vogt, Arvind Kumar, Robert Schmidt P67 Electrodiffusion in one- and two-compartment neuron models for characterizing cellular effects of electrical stimulation Stephen Van Wert, Steven J. Schiff P68 STDP improves speech recognition capabilities in spiking recurrent circuits parameterized via differential evolution Markov Chain Monte Carlo Richard Veale, Matthias Scheutz P69 Bidirectional transformation between dominant cortical neural activities and phase difference distributions Sang Wan Lee P70 Maturation of sensory networks through homeostatic structural plasticity Júlia Gallinaro, Stefan Rotter P71 Corticothalamic dynamics: structure, number of solutions and stability of steady-state solutions in the space of synaptic couplings Paula Sanz-Leon, Peter A. Robinson P72 Optogenetic versus electrical stimulation of the parkinsonian basal ganglia. Computational study Leonid L. Rubchinsky, Chung Ching Cheung, Shivakeshavan Ratnadurai-Giridharan P73 Exact spike-timing distribution reveals higher-order interactions of neurons Safura Rashid Shomali, Majid Nili Ahmadabadi, Hideaki Shimazaki, S. Nader Rasuli P74 Neural mechanism of visual perceptual learning using a multi-layered neural network Xiaochen Zhao, Malte J. Rasch P75 Inferring collective spiking dynamics from mostly unobserved systems Jens Wilting, Viola Priesemann P76 How to infer distributions in the brain from subsampled observations Anna Levina, Viola Priesemann P77 Influences of embedding and estimation strategies on the inferred memory of single spiking neurons Lucas Rudelt, Joseph T. Lizier, Viola Priesemann P78 A nearest-neighbours based estimator for transfer entropy between spike trains Joseph T. Lizier, Richard E. Spinney, Mikail Rubinov, Michael Wibral, Viola Priesemann P79 Active learning of psychometric functions with multinomial logistic models Ji Hyun Bak, Jonathan Pillow P81 Inferring low-dimensional network dynamics with variational latent Gaussian process Yuan Zaho, Il Memming Park P82 Computational investigation of energy landscapes in the resting state subcortical brain network Jiyoung Kang, Hae-Jeong Park P83 Local repulsive interaction between retinal ganglion cells can generate a consistent spatial periodicity of orientation map Jaeson Jang, Se-Bum Paik P84 Phase duration of bistable perception reveals intrinsic time scale of perceptual decision under noisy condition Woochul Choi, Se-Bum Paik P85 Feedforward convergence between retina and primary visual cortex can determine the structure of orientation map Changju Lee, Jaeson Jang, Se-Bum Paik P86 Computational method classifying neural network activity patterns for imaging data Min Song, Hyeonsu Lee, Se-Bum Paik P87 Symmetry of spike-timing-dependent-plasticity kernels regulates volatility of memory Youngjin Park, Woochul Choi, Se-Bum Paik P88 Effects of time-periodic coupling strength on the first-spike latency dynamics of a scale-free network of stochastic Hodgkin-Huxley neurons Ergin Yilmaz, Veli Baysal, Mahmut Ozer P89 Spectral properties of spiking responses in V1 and V4 change within the trial and are highly relevant for behavioral performance Veronika Koren, Klaus Obermayer P90 Methods for building accurate models of individual neurons Daniel Saska, Thomas Nowotny P91 A full size mathematical model of the early olfactory system of honeybees Ho Ka Chan, Alan Diamond, Thomas Nowotny P92 Stimulation-induced tuning of ongoing oscillations in spiking neural networks Christoph S. Herrmann, Micah M. Murray, Silvio Ionta, Axel Hutt, Jérémie Lefebvre P93 Decision-specific sequences of neural activity in balanced random networks driven by structured sensory input Philipp Weidel, Renato Duarte, Abigail Morrison P94 Modulation of tuning induced by abrupt reduction of SST cell activity Jung H. Lee, Ramakrishnan Iyer, Stefan Mihalas P95 The functional role of VIP cell activation during locomotion Jung H. Lee, Ramakrishnan Iyer, Christof Koch, Stefan Mihalas P96 Stochastic inference with spiking neural networks Mihai A. Petrovici, Luziwei Leng, Oliver Breitwieser, David Stöckel, Ilja Bytschok, Roman Martel, Johannes Bill, Johannes Schemmel, Karlheinz Meier P97 Modeling orientation-selective electrical stimulation with retinal prostheses Timothy B. Esler, Anthony N. Burkitt, David B. Grayden, Robert R. Kerr, Bahman Tahayori, Hamish Meffin P98 Ion channel noise can explain firing correlation in auditory nerves Bahar Moezzi, Nicolangelo Iannella, Mark D. McDonnell P99 Limits of temporal encoding of thalamocortical inputs in a neocortical microcircuit Max Nolte, Michael W. Reimann, Eilif Muller, Henry Markram P100 On the representation of arm reaching movements: a computational model Antonio Parziale, Rosa Senatore, Angelo Marcelli P101 A computational model for investigating the role of cerebellum in acquisition and retention of motor behavior Rosa Senatore, Antonio Parziale, Angelo Marcelli P102 The emergence of semantic categories from a large-scale brain network of semantic knowledge K. Skiker, M. Maouene P103 Multiscale modeling of M1 multitarget pharmacotherapy for dystonia Samuel A. Neymotin, Salvador Dura-Bernal, Alexandra Seidenstein, Peter Lakatos, Terence D. Sanger, William W. Lytton P104 Effect of network size on computational capacity Salvador Dura-Bernal, Rosemary J. Menzies, Campbell McLauchlan, Sacha J. van Albada, David J. Kedziora, Samuel Neymotin, William W. Lytton, Cliff C. Kerr P105 NetPyNE: a Python package for NEURON to facilitate development and parallel simulation of biological neuronal networks Salvador Dura-Bernal, Benjamin A. Suter, Samuel A. Neymotin, Cliff C. Kerr, Adrian Quintana, Padraig Gleeson, Gordon M. G. Shepherd, William W. Lytton P107 Inter-areal and inter-regional inhomogeneity in co-axial anisotropy of Cortical Point Spread in human visual areas Juhyoung Ryu, Sang-Hun Lee P108 Two bayesian quanta of uncertainty explain the temporal dynamics of cortical activity in the non-sensory areas during bistable perception Joonwon Lee, Sang-Hun Lee P109 Optimal and suboptimal integration of sensory and value information in perceptual decision making Hyang Jung Lee, Sang-Hun Lee P110 A Bayesian algorithm for phoneme Perception and its neural implementation Daeseob Lim, Sang-Hun Lee P111 Complexity of EEG signals is reduced during unconsciousness induced by ketamine and propofol Jisung Wang, Heonsoo Lee P112 Self-organized criticality of neural avalanche in a neural model on complex networks Nam Jung, Le Anh Quang, Seung Eun Maeng, Tae Ho Lee, Jae Woo Lee P113 Dynamic alterations in connection topology of the hippocampal network during ictal-like epileptiform activity in an in vitro rat model Chang-hyun Park, Sora Ahn, Jangsup Moon, Yun Seo Choi, Juhee Kim, Sang Beom Jun, Seungjun Lee, Hyang Woon Lee P114 Computational model to replicate seizure suppression effect by electrical stimulation Sora Ahn, Sumin Jo, Eunji Jun, Suin Yu, Hyang Woon Lee, Sang Beom Jun, Seungjun Lee P115 Identifying excitatory and inhibitory synapses in neuronal networks from spike trains using sorted local transfer entropy Felix Goetze, Pik-Yin Lai P116 Neural network model for obstacle avoidance based on neuromorphic computational model of boundary vector cell and head direction cell Seonghyun Kim, Jeehyun Kwag P117 Dynamic gating of spike pattern propagation by Hebbian and anti-Hebbian spike timing-dependent plasticity in excitatory feedforward network model Hyun Jae Jang, Jeehyun Kwag P118 Inferring characteristics of input correlations of cells exhibiting up-down state transitions in the rat striatum Marko Filipović, Ramon Reig, Ad Aertsen, Gilad Silberberg, Arvind Kumar P119 Graph properties of the functional connected brain under the influence of Alzheimer’s disease Claudia Bachmann, Simone Buttler, Heidi Jacobs, Kim Dillen, Gereon R. Fink, Juraj Kukolja, Abigail Morrison P120 Learning sparse representations in the olfactory bulb Daniel Kepple, Hamza Giaffar, Dima Rinberg, Steven Shea, Alex Koulakov P121 Functional classification of homologous basal-ganglia networks Jyotika Bahuguna,Tom Tetzlaff, Abigail Morrison, Arvind Kumar, Jeanette Hellgren Kotaleski P122 Short term memory based on multistability Tim Kunze, Andre Peterson, Thomas Knösche P123 A physiologically plausible, computationally efficient model and simulation software for mammalian motor units Minjung Kim, Hojeong Kim P125 Decoding laser-induced somatosensory information from EEG Ji Sung Park, Ji Won Yeon, Sung-Phil Kim P126 Phase synchronization of alpha activity for EEG-based personal authentication Jae-Hwan Kang, Chungho Lee, Sung-Phil Kim P129 Investigating phase-lags in sEEG data using spatially distributed time delays in a large-scale brain network model Andreas Spiegler, Spase Petkoski, Matias J. Palva, Viktor K. Jirsa P130 Epileptic seizures in the unfolding of a codimension-3 singularity Maria L. Saggio, Silvan F. Siep, Andreas Spiegler, William C. Stacey, Christophe Bernard, Viktor K. Jirsa P131 Incremental dimensional exploratory reasoning under multi-dimensional environment Oh-hyeon Choung, Yong Jeong P132 A low-cost model of eye movements and memory in personal visual cognition Yong-il Lee, Jaeseung Jeong P133 Complex network analysis of structural connectome of autism spectrum disorder patients Su Hyun Kim, Mir Jeong, Jaeseung Jeong P134 Cognitive motives and the neural correlates underlying human social information transmission, gossip Jeungmin Lee, Jaehyung Kwon, Jerald D. Kralik, Jaeseung Jeong P135 EEG hyperscanning detects neural oscillation for the social interaction during the economic decision-making Jaehwan Jahng, Dong-Uk Hwang, Jaeseung Jeong P136 Detecting purchase decision based on hyperfrontality of the EEG Jae-Hyung Kwon, Sang-Min Park, Jaeseung Jeong P137 Vulnerability-based critical neurons, synapses, and pathways in the Caenorhabditis elegans connectome Seongkyun Kim, Hyoungkyu Kim, Jerald D. Kralik, Jaeseung Jeong P138 Motif analysis reveals functionally asymmetrical neurons in C. elegans Pyeong Soo Kim, Seongkyun Kim, Hyoungkyu Kim, Jaeseung Jeong P139 Computational approach to preference-based serial decision dynamics: do temporal discounting and working memory affect it? Sangsup Yoon, Jaehyung Kwon, Sewoong Lim, Jaeseung Jeong P141 Social stress induced neural network reconfiguration affects decision making and learning in zebrafish Choongseok Park, Thomas Miller, Katie Clements, Sungwoo Ahn, Eoon Hye Ji, Fadi A. Issa P142 Descriptive, generative, and hybrid approaches for neural connectivity inference from neural activity data JeongHun Baek, Shigeyuki Oba, Junichiro Yoshimoto, Kenji Doya, Shin Ishii P145 Divergent-convergent synaptic connectivities accelerate coding in multilayered sensory systems Thiago S. Mosqueiro, Martin F. Strube-Bloss, Brian Smith, Ramon Huerta P146 Swinging networks Michal Hadrava, Jaroslav Hlinka P147 Inferring dynamically relevant motifs from oscillatory stimuli: challenges, pitfalls, and solutions Hannah Bos, Moritz Helias P148 Spatiotemporal mapping of brain network dynamics during cognitive tasks using magnetoencephalography and deep learning Charles M. Welzig, Zachary J. Harper P149 Multiscale complexity analysis for the segmentation of MRI images Won Sup Kim, In-Seob Shin, Hyeon-Man Baek, Seung Kee Han P150 A neuro-computational model of emotional attention René Richter, Julien Vitay, Frederick Beuth, Fred H. Hamker P151 Multi-site delayed feedback stimulation in parkinsonian networks Kelly Toppin, Yixin Guo P152 Bistability in Hodgkin–Huxley-type equations Tatiana Kameneva, Hamish Meffin, Anthony N. Burkitt, David B. Grayden P153 Phase changes in postsynaptic spiking due to synaptic connectivity and short term plasticity: mathematical analysis of frequency dependency Mark D. McDonnell, Bruce P. Graham P154 Quantifying resilience patterns in brain networks: the importance of directionality Penelope J. Kale, Leonardo L. Gollo P155 Dynamics of rate-model networks with separate excitatory and inhibitory populations Merav Stern, L. F. Abbott P156 A model for multi-stable dynamics in action recognition modulated by integration of silhouette and shading cues Leonid A. Fedorov, Martin A. Giese P157 Spiking model for the interaction between action recognition and action execution Mohammad Hovaidi Ardestani, Martin Giese P158 Surprise-modulated belief update: how to learn within changing environments? Mohammad Javad Faraji, Kerstin Preuschoff, Wulfram Gerstner P159 A fast, stochastic and adaptive model of auditory nerve responses to cochlear implant stimulation Margriet J. van Gendt, Jeroen J. Briaire, Randy K. Kalkman, Johan H. M. Frijns P160 Quantitative comparison of graph theoretical measures of simulated and empirical functional brain networks Won Hee Lee, Sophia Frangou P161 Determining discriminative properties of fMRI signals in schizophrenia using highly comparative time-series analysis Ben D. Fulcher, Patricia H. P. Tran, Alex Fornito P162 Emergence of narrowband LFP oscillations from completely asynchronous activity during seizures and high-frequency oscillations Stephen V. Gliske, William C. Stacey, Eugene Lim, Katherine A. Holman, Christian G. Fink P163 Neuronal diversity in structure and function: cross-validation of anatomical and physiological classification of retinal ganglion cells in the mouse Jinseop S. Kim, Shang Mu, Kevin L. Briggman, H. Sebastian Seung, the EyeWirers P164 Analysis and modelling of transient firing rate changes in area MT in response to rapid stimulus feature changes Detlef Wegener, Lisa Bohnenkamp, Udo A. Ernst P165 Step-wise model fitting accounting for high-resolution spatial measurements: construction of a layer V pyramidal cell model with reduced morphology Tuomo Mäki-Marttunen, Geir Halnes, Anna Devor, Christoph Metzner, Anders M. Dale, Ole A. Andreassen, Gaute T. Einevoll P166 Contributions of schizophrenia-associated genes to neuron firing and cardiac pacemaking: a polygenic modeling approach Tuomo Mäki-Marttunen, Glenn T. Lines, Andy Edwards, Aslak Tveito, Anders M. Dale, Gaute T. Einevoll, Ole A. 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Karoly, Dean R. Freestone, Daniel Soundry, Levin Kuhlmann, Liam Paninski, Mark Cook P179 Data-driven neural models part I: state and parameter estimation Dean R. Freestone, Philippa J. Karoly, Daniel Soundry, Levin Kuhlmann, Mark Cook P180 Spectral and spatial information processing in human auditory streaming Jaejin Lee, Yonatan I. Fishman, Yale E. Cohen P181 A tuning curve for the global effects of local perturbations in neural activity: Mapping the systems-level susceptibility of the brain Leonardo L. Gollo, James A. Roberts, Luca Cocchi P182 Diverse homeostatic responses to visual deprivation mediated by neural ensembles Yann Sweeney, Claudia Clopath P183 Opto-EEG: a novel method for investigating functional connectome in mouse brain based on optogenetics and high density electroencephalography Soohyun Lee, Woo-Sung Jung, Jee Hyun Choi P184 Biphasic responses of frontal gamma network to repetitive sleep deprivation during REM sleep Bowon Kim, Youngsoo Kim, Eunjin Hwang, Jee Hyun Choi P185 Brain-state correlate and cortical connectivity for frontal gamma oscillations in top-down fashion assessed by auditory steady-state response Younginha Jung, Eunjin Hwang, Yoon-Kyu Song, Jee Hyun Choi P186 Neural field model of localized orientation selective activation in V1 James Rankin, Frédéric Chavane P187 An oscillatory network model of Head direction and Grid cells using locomotor inputs Karthik Soman, Vignesh Muralidharan, V. Srinivasa Chakravarthy P188 A computational model of hippocampus inspired by the functional architecture of basal ganglia Karthik Soman, Vignesh Muralidharan, V. Srinivasa Chakravarthy P189 A computational architecture to model the microanatomy of the striatum and its functional properties Sabyasachi Shivkumar, Vignesh Muralidharan, V. Srinivasa Chakravarthy P190 A scalable cortico-basal ganglia model to understand the neural dynamics of targeted reaching Vignesh Muralidharan, Alekhya Mandali, B. Pragathi Priyadharsini, Hima Mehta, V. Srinivasa Chakravarthy P191 Emergence of radial orientation selectivity from synaptic plasticity Catherine E. Davey, David B. Grayden, Anthony N. Burkitt P192 How do hidden units shape effective connections between neurons? Braden A. W. Brinkman, Tyler Kekona, Fred Rieke, Eric Shea-Brown, Michael Buice P193 Characterization of neural firing in the presence of astrocyte-synapse signaling Maurizio De Pittà, Hugues Berry, Nicolas Brunel P194 Metastability of spatiotemporal patterns in a large-scale network model of brain dynamics James A. Roberts, Leonardo L. Gollo, Michael Breakspear P195 Comparison of three methods to quantify detection and discrimination capacity estimated from neural population recordings Gary Marsat, Jordan Drew, Phillip D. Chapman, Kevin C. Daly, Samual P. Bradley P196 Quantifying the constraints for independent evoked and spontaneous NMDA receptor mediated synaptic transmission at individual synapses Sat Byul Seo, Jianzhong Su, Ege T. Kavalali, Justin Blackwell P199 Gamma oscillation via adaptive exponential integrate-and-fire neurons LieJune Shiau, Laure Buhry, Kanishka Basnayake P200 Visual face representations during memory retrieval compared to perception Sue-Hyun Lee, Brandon A. Levy, Chris I. Baker P201 Top-down modulation of sequential activity within packets modeled using avalanche dynamics Timothée Leleu, Kazuyuki Aihara Q28 An auto-encoder network realizes sparse features under the influence of desynchronized vascular dynamics Ryan T. Philips, Karishma Chhabria, V. Srinivasa Chakravarthy

Background: In the last years, several voxel‐wise data‐driven metrics gained attention to study resting‐state connectivity in healthy aging and various pathological states. More recently, a new measure assessing the interaction between the commonly used metrics has been proposed and made widely available via the DPABI toolbox: the so‐called concordance index (CI). This index reflects the coupling of different metrics. The value of this new measure in Alzheimer's disease (AD) research is yet unclear. Method: Healthy young controls (YC, n=26), healthy senior controls (SC, n=29), and patients diagnosed with AD (n=35) underwent 3T resting‐state fMRI. First, the fractional amplitude of low frequency fluctuations (fALFF), regional homogeneity (ReHo), and degree centrality (DC) were calculated. Next, the CI among these measures was determined for each time window and each brain voxel across time by using Kendall's W. Differences in the CI between groups were examined on a whole brain, voxel‐wise, and network‐level using masks of seven of the most prominent intrinsic brain networks, with age, sex, head motion and gray matter volume as covariates. Result: The whole‐brain CI was significantly lower in AD patients as compared to YC and SC, which is in line with results from analyzing the single metrics. Reductions of the CI in AD was consistently observed in all networks investigated except for the limbic network. In SC compared to YC, no network‐level CI differences were detectable. On the voxel level, AD patients compared to SC showed lower CI in the right middle temporal gyrus, and SC compared to YC revealed lower CI in the left middle frontal gyrus. Analyzing the single metrics for their own, we observed a lower fALFF in the right angular gyrus in AD compared to SC, but no differences were detected for ReHo and DC. Conclusion: The newly proposed CI based on resting‐state connectivity may serve as a more sensitive imaging marker in AD than single metrics. The data suggest that this index distinguishes well between neurodegeneration and healthy aging. [ABSTRACT FROM AUTHOR]

Background: To date, it remains unclear how the hallmark pathological changes of Alzheimer's disease (AD), amyloid plaques, and neurofibrillary tangles, affect neuronal activity and, consequently, cognition. In cognitively normal aging, it appears that tau accumulation may drive hippocampal hyperactivity, however, studies investigating this association in AD are sparse. Method: Patients with mild cognitive impairment (MCI) or mild dementia due to AD (n = 15) underwent positron emission tomography with the tracer [18F]‐AV‐1451, which binds to tau accumulation, and performed a visual item memory task during functional magnetic resonance imaging. Result: Entorhinal tau accumulation was highly correlated with memory‐related hippocampal activation. Greater tau accumulation and hippocampal activation were negatively correlated with memory performance. Neural activation in other task‐related structures was not correlated with local or global tau accumulation. Conclusion: Similar to observations in cognitively healthy aging, entorhinal tau accumulation is closely associated with hippocampal hyperactivity and impaired memory performance in MCI and mild dementia. Interestingly, this association is specific for medial temporal lobe structures. [ABSTRACT FROM AUTHOR]