Integrating incremental learning and episodic memory models of the hippocampal region.

By integrating previous computational models of corticohippocampal function, the authors develop and test a unified theory of the neural substrates of familiarity, recollection, and classical conditioning. This approach integrates models from 2 traditions of hippocampal modeling, those of episodic memory and incremental learning, by drawing on an earlier mathematical model of conditioning, SOP (A. Wagner, 1981). The model describes how a familiarity signal may arise from parahippocampal cortices, giving a novel explanation for the finding that the neural response to a stimulus in these regions decreases with increasing stimulus familiarity. Recollection is ascribed to the hippocampus proper. It is shown how the properties of episodic representations in the neocortex, parahippocampal gyrus, and hippocampus proper may explain phenomena in classical conditioning. The model reproduces the effects of hippocampal, septal, and broad hippocampal region lesions on contextual modulation of classical conditioning, blocking, learned irrelevance, and latent inhibition

Reminiscence bump in memory for public events

People tend to recall more personal events from adolescence and early adulthood than from other lifetime periods. Most evidence suggests that differential encoding causes this reminiscence bump. However, the question why personal events are encoded better in those periods is still unanswered. To shed more light on this discussion, we examined memory for public events. Since it is often impossible to ascertain that queried events are equally difficult, we circumvented the issue of equivalence by calculating deviation scores for each trial. We found that participants more frequently answered questions correctly about events that occurred in the period in which they were between 10 and 25 years old. Furthermore, we found that the reminiscence bump was more pronounced for cued recall than for recognition. We argue that these results support the biological account that events are stored better, because the memory system is working more efficiently during adolescence and early adulthood. These results do not falsify the other accounts for differential encoding, because they are not mutually exclusive. People speak of autobiographical memory when they are referring to the memories they have of their own life experiences (Robinson, 1986). Autobiographical memory does not only consist of personal memories that are remembered vividly, but also of autobiographical facts (Brewer, 1986). Some researchers have examined the contents of autobiographical memories (e.g., Fitzgerald, 1988; Niedźwieńska, 2003; Robinson, 1976), whereas other researchers have focused on the temporal distribution of memories of personal events across the lifespan (e.g., Janssen, Chessa, &amp

Clinical Value of Longitudinal Serum Neurofilament Light Chain in Prodromal Genetic Frontotemporal Dementia

BACKGROUND AND OBJECTIVES: Elevated serum neurofilament light chain (NfL) is used to identify carriers of genetic frontotemporal dementia (FTD) pathogenic variants approaching prodromal conversion. Yet, the magnitude and timeline of NfL increase are still unclear. Here, we investigated the predictive and early diagnostic value of longitudinal serum NfL for the prodromal conversion in genetic FTD. METHODS: In a longitudinal observational cohort study of genetic FTD pathogenic variant carriers, we examined the diagnostic accuracy and conversion risk associated with cross-sectional and longitudinal NfL. Time periods relative to prodromal conversion (&gt;3, 3-1.5, 1.5-0 years before; 0-1.5 years after) were compared with values of participants who did not convert. Next, we modeled longitudinal NfL and MRI volume trajectories to determine their timeline.RESULTS: We included 21 participants who converted (5 chromosome 9 open-reading frame 72 [C9orf72], 10 progranulin [GRN], 5 microtubule-associated protein tau [MAPT], and 1 TAR DNA-binding protein [TARDBP]) and 61 who did not (20 C9orf72, 30 GRN, and 11 MAPT). Participants who converted had higher NfL levels at all examined periods before prodromal conversion (median values 14.0-18.2 pg/mL; betas = 0.4-0.7, standard error [SE] = 0.1, p &lt; 0.046) than those who did not (6.5 pg/mL) and showed further increase 0-1.5 years after conversion (28.4 pg/mL; beta = 1.0, SE = 0.1, p &lt; 0.001). Annualized longitudinal NfL change was only significantly higher in participants who converted (vs. participants who did not) 0-1.5 years after conversion (beta = 1.2, SE = 0.3, p = 0.001). Diagnostic accuracy of cross-sectional NfL for prodromal conversion (vs. nonconversion) was good-to-excellent at time periods before conversion (area under the curve range: 0.72-0.92), improved 0-1.5 years after conversion (0.94-0.97), and outperformed annualized longitudinal change (0.76-0.84). NfL increase in participants who converted occurred earlier than frontotemporal MRI volume change and differed by genetic group and clinical phenotypes. Higher NfL corresponded to increased conversion risk (hazard ratio: cross-sectional = 6.7 [95% CI 3.3-13.7]; longitudinal = 13.0 [95% CI 4.0-42.8]; p &lt; 0.001), but conversion-free follow-up time varied greatly across participants. DISCUSSION: NfL increase discriminates individuals who convert to prodromal FTD from those who do not, preceding significant frontotemporal MRI volume loss. However, NfL alone is limited in predicting the exact timing of prodromal conversion. NfL levels also vary depending on underlying variant-carrying genes and clinical phenotypes. These findings help to guide participant recruitment for clinical trials targeting prodromal genetic FTD.</p

Longitudinal cognitive biomarkers predicting symptom onset in presymptomatic frontotemporal dementia

Introduction: We performed 4-year follow-up neuropsychological assessment to investigate cognitive decline and the prognostic abilities from presymptomatic to symptomatic familial frontotemporal dementia (FTD). Methods: Presymptomatic MAPT (n = 15) and GRN mutation carriers (n = 31), and healthy controls (n = 39) underwent neuropsychological assessment every 2 years. Eight mutation carriers (5 MAPT, 3 GRN) became symptomatic. We investigated cognitive decline with multilevel regression modeling; the prognostic performance was assessed with ROC analyses and stepwise logistic regression. Results: MAPT converters declined on language, attention, executive function, social cognition, and memory, and GRN converters declined on attention and executive function (p < 0.05). Cognitive decline in ScreeLing phonology (p = 0.046) and letter fluency (p = 0.046) were predictive for conversion to non-fluent variant PPA, and decline on categorical fluency (p = 0.025) for an underlying MAPT mutation. Discussion: Using longitudinal neuropsychological assessment, we detected a mutation-specific pattern of cognitive decline, potentially suggesting prognostic value of neuropsychological trajectories in conversion to symptomatic FTD

Modelling the cascade of biomarker changes in GRN-related frontotemporal dementia

OBJECTIVE: Progranulin-related frontotemporal dementia (FTD-GRN) is a fast progressive disease. Modelling the cascade of multimodal biomarker changes aids in understanding the aetiology of this disease and enables monitoring of individual mutation carriers. In this cross-sectional study, we estimated the temporal cascade of biomarker changes for FTD-GRN, in a data-driven way. METHODS: We included 56 presymptomatic and 35 symptomatic GRN mutation carriers, and 35 healthy non-carriers. Selected biomarkers were neurofilament light chain (NfL), grey matter volume, white matter microstructure and cognitive domains. We used discriminative event-based modelling to infer the cascade of biomarker changes in FTD-GRN and estimated individual disease severity through cross-validation. We derived the biomarker cascades in non-fluent variant primary progressive aphasia (nfvPPA) and behavioural variant FTD (bvFTD) to understand the differences between these phenotypes. RESULTS: Language functioning and NfL were the earliest abnormal biomarkers in FTD-GRN. White matter tracts were affected before grey matter volume, and the left hemisphere degenerated before the right. Based on individual disease severities, presymptomatic carriers could be delineated from symptomatic carriers with a sensitivity of 100% and specificity of 96.1%. The estimated disease severity strongly correlated with functional severity in nfvPPA, but not in bvFTD. In addition, the biomarker cascade in bvFTD showed more uncertainty than nfvPPA. CONCLUSION: Degeneration of axons and language deficits are indicated to be the earliest biomarkers in FTD-GRN, with bvFTD being more heterogeneous in disease progression than nfvPPA. Our data-driven model could help identify presymptomatic GRN mutation carriers at risk of conversion to the clinical stage

Correction to: Cognitive profiles discriminate between genetic variants of behavioral frontotemporal dementia

The original version of this article unfortunately contained a mistake. The presentation of Table 1 was incorrect. The original article has been corrected. The corrected Table 1 is given below. (Table presented.)

Cognitive profiles discriminate between genetic variants of behavioral frontotemporal dementia

Introduction: Trials to test disease-modifying treatments for frontotemporal dementia are eagerly awaited and sensitive instruments to assess potential treatment effects are increasingly urgent, yet lacking thus far. We aimed to identify gene-specific instruments assessing clinical onset and disease progression by comparing cognitive functioning between bvFTD patients across genetic mutations. Methods: We examined differences in 7 cognitive domains between bvFTD patients with GRN (n = 20), MAPT (n = 29) or C9orf72 (n = 31) mutations, and non-carriers (n = 24), and describe

Correction to: Cognitive profiles discriminate between genetic variants of behavioral frontotemporal dementia

The original version of this article unfortunately contained a mistake. The presentation of Table 1 was incorrect. The original article has been corrected. The corrected Table 1 is given below. (Table presented.)

A Modular Network Architecture Resolving Memory Interference through Inhibition

International audienceIn real learning paradigms like pavlovian conditioning, several modes of learning are associated, including generalization from cues and integration of specific cases in context. Associative memories have been shown to be interesting neuronal models to learn quickly specific cases but they are hardly used in realistic applications because of their limited storage capacities resulting in interferences when too many examples are considered. Inspired by biological considerations, we propose a modular model of associative memory including mechanisms to manipulate properly multimodal inputs and to detect and manage interferences. This paper reports experiments that demonstrate the good behavior of the model in a wide series of simulations and discusses its impact both in machine learning and in biological modeling