Human Adult Neurogenesis: Evidence and Remaining Questions

Renewed discussion about whether or not adult neurogenesis exists in the human hippocampus, and the nature and strength of the supporting evidence, has been reignited by two prominently published reports with opposite conclusions. Here, we summarize the state of the field and argue that there is currently no reason to abandon the idea that adult-generated neurons make important functional contributions to neural plasticity and cognition across the human lifespan

Dimethyl fumarate in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

Dimethyl fumarate (DMF) inhibits inflammasome-mediated inflammation and has been proposed as a treatment for patients hospitalised with COVID-19. This randomised, controlled, open-label platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), is assessing multiple treatments in patients hospitalised for COVID-19 (NCT04381936, ISRCTN50189673). In this assessment of DMF performed at 27 UK hospitals, adults were randomly allocated (1:1) to either usual standard of care alone or usual standard of care plus DMF. The primary outcome was clinical status on day 5 measured on a seven-point ordinal scale. Secondary outcomes were time to sustained improvement in clinical status, time to discharge, day 5 peripheral blood oxygenation, day 5 C-reactive protein, and improvement in day 10 clinical status. Between 2 March 2021 and 18 November 2021, 713 patients were enroled in the DMF evaluation, of whom 356 were randomly allocated to receive usual care plus DMF, and 357 to usual care alone. 95% of patients received corticosteroids as part of routine care. There was no evidence of a beneficial effect of DMF on clinical status at day 5 (common odds ratio of unfavourable outcome 1.12; 95% CI 0.86-1.47; p = 0.40). There was no significant effect of DMF on any secondary outcome

Manipulating a "Cocaine Engram" in Mice

Experience with drugs of abuse (such as cocaine) produces powerful, long-lasting memories that may be important in the development and persistence of drug addiction. The neural mechanisms that mediate how and where these cocaine memories are encoded, consolidated and stored are unknown. Here we used conditioned place preference in mice to examine the precise neural circuits that support the memory of a cocaine-cue association (the “cocaine memory trace” or “cocaine engram”). We found that a small population of neurons (∼ 10%) in the lateral nucleus of amygdala (LA) were recruited at the time of cocaine-conditioning to become part of this cocaine engram. Neurons with increased levels of the transcription factor CREB were preferentially recruited or allocated to the cocaine engram. Ablating or silencing neurons overexpressing CREB (but not a similar number of random LA neurons) before testing disrupted the expression of a previously acquired cocaine memory, suggesting that neurons overexpressing CREB become a critical hub in what is likely a larger cocaine memory engram. Consistent with theories that coordinated postencoding reactivation of neurons within an engram or cell assembly is crucial for memory consolidation (Marr, 1971; Buzsaki, 1989; Wilson and McNaughton, 1994; McClelland et al., 1995; Girardeau et al., 2009; Dupret et al., 2010; Carr et al., 2011), we also found that post-training suppression, or nondiscriminate activation, of CREB overexpressing neurons impaired consolidation of the cocaine memory. These findings reveal mechanisms underlying how and where drug memories are encoded and stored in the brain and may also inform the development of treatments for drug addiction

Manipulating a "cocaine engram" in mice

Experience with drugs of abuse (such as cocaine) produces powerful, long-lasting memories that may be important in the development and persistence of drug addiction. The neural mechanisms that mediate how and where these cocaine memories are encoded, consolidated and stored are unknown. Here we used conditioned place preference in mice to examine the precise neural circuits that support the memory of a cocaine-cue association (the “cocaine memory trace” or “cocaine engram”). We found that a small population of neurons (∼ 10%) in the lateral nucleus of amygdala (LA) were recruited at the time of cocaine-conditioning to become part of this cocaine engram. Neurons with increased levels of the transcription factor CREB were preferentially recruited or allocated to the cocaine engram. Ablating or silencing neurons overexpressing CREB (but not a similar number of random LA neurons) before testing disrupted the expression of a previously acquired cocaine memory, suggesting that neurons overexpressing CREB become a critical hub in what is likely a larger cocaine memory engram. Consistent with theories that coordinated postencoding reactivation of neurons within an engram or cell assembly is crucial for memory consolidation (Marr, 1971; Buzsaki, 1989; Wilson and McNaughton, 1994; McClelland et al., 1995; Girardeau et al., 2009; Dupret et al., 2010; Carr et al., 2011), we also found that post-training suppression, or nondiscriminate activation, of CREB overexpressing neurons impaired consolidation of the cocaine memory. These findings reveal mechanisms underlying how and where drug memories are encoded and stored in the brain and may also inform the development of treatments for drug addiction

Melodic Grouping in Music Information Retrieval: New Methods and Applications

We introduce the MIR task of segmenting melodies into phrases, summarise the musicological and psychological background to the task and review existing computational methods before presenting a new model, IDyOM, for melodic segmentation based on statistical learning and information-dynamic analysis. The performance of the model is compared to several existing algorithms in predicting the annotated phrase boundaries in a large corpus of folk music. The results indicate that four algorithms produce acceptable results: one of these is the IDyOM model which performs much better than naive statistical models and approaches the performance of the best-performing rule-based models. Further slight performance improvement can be obtained by combining the output of the four algorithms in a hybrid model, although the performance of this model is moderate at best, leaving a great deal of room for improvement on this task