Boston Center for Memory

We present baseline characteristics of TRAILBLAZER-ALZ 2 (NCT04437511), a global phase 3 study designed to assess the treatment effects of donanemab on disease progression in individuals with early symptomatic AD.

Aging and exercise have opposing effects on mnemonic discrimination task performance, which putatively taxes pattern separation mechanisms reliant on the dentate gyrus (DG) subfield of the hippocampus. In young adults, increasing cardiorespiratory fitness (CRF) has been shown to improve mnemonic discrimination task performance and increase left anterior DG/CA3 volume. It is unknown how these variables interact in cognitive aging, yet this knowledge is critical, given the established effects of aging on hippocampal plasticity. To investigate these relationships, 65 older adults (aged 55–85 years) completed a submaximal treadmill test to estimate CRF, a mnemonic discrimination task, and a high‐resolution MRI scan to determine hippocampal subfield volumes. Our older adult sample demonstrated the lowest task accuracy in the condition with the greatest stimuli similarity and left DG/CA3 body volume significantly predicted accuracy in this condition. Our results did not provide support for relationships between CRF and task accuracy or CRF and DG/CA3 volume as evidenced in studies of young adults. Instead, CRF predicted bilateral subiculum volume in older adult women, not men. Altogether, these findings provide further support for a role of the DG in behavioral pattern separation in humans and suggest that CRF may have differential effects on hippocampal subfield integrity in older adult men and women. ClinicalTrials.gov identifiers: (a) Neuroimaging Study of Exercise and Memory Function, NCT02057354; (b) The Entorhinal Cortex and Aerobic Exercise in Aging, NCT02775760; (c) Physical Activity and Cognition Study, NCT02773121.

We describe an amnestic pattern of cognitive impairment in a patient with brain sagging syndrome (BSS) due to a dural diverticulum and its reversibility after treatment.

Scale-invariant timing has been observed in a wide range of behavioral experiments. The firing properties of recently described time cells provide a possible neural substrate for scale-invariant behavior. Earlier neural circuit models do not produce scale-invariant neural sequences. In this article, we present a biologically detailed network model based on an earlier mathematical algorithm. The simulations incorporate exponentially decaying persistent firing maintained by the calcium-activated nonspecific (CAN) cationic current and a network structure given by the inverse Laplace transform to generate time cells with scale-invariant firing rates. This model provides the first biologically detailed neural circuit for generating scale-invariant time cells. The circuit that implements the inverse Laplace transform merely consists of off-center/on-surround receptive fields. Critically, rescaling temporal sequences can be accomplished simply via cortical gain control (changing the slope of the f-I curve).

Journal Article Automated Serial Section Large-field Transmission-Mode Scanning Electron Microscopy (tSEM) for Volume Analysis of Hippocampus Ultrastructure Get access John M Mendenhall, John M Mendenhall Center for Learning and Memory Search for other works by this author on: Oxford Academic Google Scholar Masaaki Kuwajima, Masaaki Kuwajima Center for Learning and Memory Search for other works by this author on: Oxford Academic Google Scholar Kristen M Harris Kristen M Harris Center for Learning and MemoryDepartment of Neuroscience, University of Texas, Austin USA Search for other works by this author on: Oxford Academic Google Scholar Microscopy and Microanalysis, Volume 23, Issue S1, 1 July 2017, Pages 562–563, https://doi.org/10.1017/S143192761700349X Published: 04 August 2017

Visual attentional capacity is severely limited, but humans excel in familiar visual contexts, in part because long-term memories guide efficient deployment of attention. To investigate the neural substrates that support memory-guided visual attention, we performed a set of functional MRI experiments that contrast long-term, memory-guided visuospatial attention with stimulus-guided visuospatial attention in a change detection task. Whereas the dorsal attention network was activated for both forms of attention, the cognitive control network(CCN) was preferentially activated during memory-guided attention. Three posterior nodes in the CCN, posterior precuneus, posterior callosal sulcus/mid-cingulate, and lateral intraparietal sulcus exhibited the greatest specificity for memory-guided attention. These 3 regions exhibit functional connectivity at rest, and we propose that they form a subnetwork within the broader CCN. Based on the task activation patterns, we conclude that the nodes of this subnetwork are preferentially recruited for long-term memory guidance of visuospatial attention.