Integrating Spatial Working Memory and Remote Memory: Interactions between the Medial Prefrontal Cortex and Hippocampus

In recent years, two separate research streams have focused on information sharing between the medial prefrontal cortex (mPFC) and hippocampus (HC). Research into spatial working memory has shown that successful execution of many types of behaviors requires synchronous activity in the theta range between the mPFC and HC, whereas studies of memory consolidation have shown that shifts in area dependency may be temporally modulated. While the nature of information that is being communicated is still unclear, spatial working memory and remote memory recall is reliant on interactions between these two areas. This review will present recent evidence that shows that these two processes are not as separate as they first appeared. We will also present a novel conceptualization of the nature of the medial prefrontal representation and how this might help explain this area’s role in spatial working memory and remote memory recall

Compacton Solutions in a Class of Generalized Fifth Order Korteweg-de Vries Equations

We study a class of generalized fifth order Korteweg-de Vries (KdV) equations which are derivable from a Lagrangian L(p,m,n,l) which has variable powers of the first and second derivatives of the field with powers given by the parameters p,m,n,l. The resulting field equation has solitary wave solutions of both the usual (non-compact) and compact variety ("compactons"). For the particular case that p=m=n+l, the solitary wave solutions have compact support and the feature that their width is independent of the amplitude. We discuss the Hamiltonian structure of these theories and find that mass, momentum, and energy are conserved. We find in general that these are not completely integrable systems. Numerical simulations show that an arbitrary compact initial wave packet whose width is wider than that of a compacton breaks up into several compactons all having the same width. The scattering of two compactons is almost elastic, with the left over wake eventually turning into compacton-anticompacton pairs. When there are two different compacton solutions for a single set of parameters the wider solution is stable, and this solution is a minimum of the Hamiltonian.Comment: 13 pages (8 embedded figures), RevTeX (plus macro), uses eps

Continuous Theta Rhythm During Spatial Working Memory Task in Rodent Models of Streptozotocin-induced Type 2 Diabetes

Alzheimer’s disease is a neurodegenerative disorder altering memory loss thought to be due to neuropathological symptoms such as the buildup of beta amyloid plaques (Ab) and neurofibrillary tangles (NFT). The etiology of Alzheimer’s is still unknown; however, potential risk factors such as diabetes may lead to its development. The most common form of diabetes is type 2 diabetes known for persistent insulin resistance leading to a state of hyperglycemia. Insulin resistance has been shown to affect cognitive abilities such as learning, memory and also alters synaptic plasticity. Neural connections between the hippocampus (HC) and anterior cingulate cortex (ACC) are known to be very important for learning and memory and are highly plastic, making them an intriguing target that could be altered by hyperglycemia. We hypothesize that hyperglycemic rodents will exhibit spatial memory deficits that may be associated with cognitively linked interactions between the HC and ACC. Minimal doses of streptozotocin (STZ), which is toxic to insulin producing beta cells, were given for 9-10 weeks. Using a spatial working memory task known as delayed alternation we found significant differences between control and experimental rats in working memory accuracy. This task places strong working memory demands on subjects which may be compromised by a hyperglycemic state. We measured EEG recordings from the HC and ACC during task performance and found that hyperglycemic rats had nearly continuous theta rhythm during the 30-minute session. Control rats however, displayed normal transitions between theta and lower frequency delta. Neural connectivity may be altered due to a change in frequency activity between the HC and ACC due to diabetes which is a risk factor in the development of AD impairments. These results show that hyperglycemia leads to changes along the circuit critical for learning and memory

Decoding The Neural Circuitry of Reward Behavior

Classical conditioning demonstrates that rewards can be used to train behavior by pairing a stimulus, known as a prompt, with reinforced behavior. At a neuronal level, this association strengthens the connections between the neurons involved, making communication easier the next time. Enhanced communication is identified with learning, allowing an organism to anticipate a reward with a prompt so that it can perform the desired behavior to successfully obtain the reward (Noonan et al., 2011). In this study, we created a computational model to represent a neural circuit with synaptic plasticity during reward, no-reward and anticipation states. Our results confirmed our hypothesis that the model would be able to differentiate between reward and no-reward stimuli and subsequently anticipate the likelihood of reward and no-reward states on ensuing trials

Construction and Assembly of a Hyperdrive Recording Implant

The ability to record neural activity from multiple brain areas is crucial for the understanding of how different areas of the brain function or interact. This poster will cover instructions on how to construct and assemble a hyperdrive recording implant that bilaterally targets the ACC and the hippocampus. Intriguingly, the design of the hyperdrive recording implant is flexible and can be constructed to target other brain areas. The implant consists of 32 twisted bundles of tetrodes with a total of 128 individual recording wires which are controlled by movable ‘drivers’ (Gray et al., 1995; McNaughton et al., 1983). All 128 recording wires are then connected to an electrode interface board that takes information from the brain and transfers it to online available open-source acquisition software platform running. Using this implant with targeted tetrodes, we are able to look at the neuronal waveforms of individual neurons or the population-level responses in specific brain areas

The Western Africa Ebola Virus Disease Epidemic Exhibits Both Global Exponential and Local Polynomial Growth Rates

Background: While many infectious disease epidemics are initially characterized by an exponential growth in time, we show that district-level Ebola virus disease (EVD) outbreaks in West Africa follow slower polynomial-based growth kinetics over several generations of the disease. Methods: We analyzed epidemic growth patterns at three different spatial scales (regional, national, and subnational) of the Ebola virus disease epidemic in Guinea, Sierra Leone and Liberia by compiling publicly available weekly time series of reported EVD case numbers from the patient database available from the World Health Organization website for the period 05-Jan to 17-Dec 2014. Results: We found significant differences in the growth patterns of EVD cases at the scale of the country, district, and other subnational administrative divisions. The national cumulative curves of EVD cases in Guinea, Sierra Leone, and Liberia show periods of approximate exponential growth. In contrast, local epidemics are asynchronous and exhibit slow growth patterns during 3 or more EVD generations, which can be better approximated by a polynomial than an exponential function. Conclusions: The slower than expected growth pattern of local EVD outbreaks could result from a variety of factors, including behavior changes, success of control interventions, or intrinsic features of the disease such as a high level of clustering. Quantifying the contribution of each of these factors could help refine estimates of final epidemic size and the relative impact of different mitigation efforts in current and future EVD outbreaks