Modulation of Human Memory by Deep Brain Stimulation of the Entorhinal-Hippocampal Circuitry

Therapy for Alzheimer's disease: Missing targets and functional markers?

The development of the next generation therapy for Alzheimer's disease (AD) presents a huge challenge given the number of promising treatment candidates that failed in trials, despite recent advancements in understanding of genetic, pathophysiologic and clinical characteristics of the disease. This review reflects some of the most current concepts and controversies in developing disease-modifying and new symptomatic treatments. It elaborates on recent changes in the AD research strategy for broadening drug targets, and potentials of emerging non-pharmacological treatment interventions. Established and novel biomarkers are discussed, including emerging cerebrospinal fluid and plasma biomarkers reflecting tau pathology, neuroinflammation and neurodegeneration. These fluid biomarkers together with neuroimaging findings can provide innovative objective assessments of subtle changes in brain reflecting disease progression. A particular emphasis is given to neurophysiological biomarkers which are well-suited for evaluating the brain overall neural network integrity and function. Combination of multiple biomarkers, including target engagement and outcome biomarkers will empower translational studies and facilitate successful development of effective therapies.

Expectation-driven novelty effects in episodic memory

Novel and unexpected stimuli are often prioritised in memory, given their inherent salience. Nevertheless, not all forms of novelty show such an enhancement effect. Here, we discuss the role expectation plays in modulating the way novelty affects memory processes, circuits, and subsequent performance. We first review independent effects of expectation on memory, and then consider how different types of novelty are characterised by expectation. We argue that different types of novelty defined by expectation implicate differential neurotransmission in memory formation brain regions and may also result in the creation of different types of memory. Contextual novelty, which is unexpected by definition, is often associated with better recollection, supported by dopaminergic-hippocampal interactions. On the other hand, expected stimulus novelty is supported by engagement of medial temporal cortices, as well as the hippocampus, through cholinergic modulation. Furthermore, when expected stimulus novelty results in enhanced memory, it is predominantly driven by familiarity. The literature reviewed here highlights the complexity of novelty-sensitive memory systems, the distinction between types of novelty, and how they are differentially affected by expectancy.

Stimulation of the right entorhinal white matter enhances visual memory encoding in humans

BACKGROUND

While deep brain stimulation has been successful in treating movement disorders, such as in Parkinson's disease, its potential application in alleviating memory disorders is inconclusive.

OBJECTIVE/HYPOTHESIS

We investigated the role of the location of the stimulating electrode on memory improvement and hypothesized that entorhinal white versus gray matter stimulation would have differential effects on memory.

METHODS

Intracranial electrical stimulation was applied to the entorhinal area of twenty-two participants with already implanted electrodes as they completed visual memory tasks.

RESULTS

We found that stimulation of right entorhinal white matter during learning had a beneficial effect on subsequent memory, while stimulation of adjacent gray matter or left-sided stimulation was ineffective. This finding was consistent across three different visually guided memory tasks.

CONCLUSIONS

Our results highlight the importance of precise stimulation site on modulation of human hippocampal-dependent memory and suggest that stimulation of afferent input into the right hippocampus may be an especially promising target for enhancement of visual memory.

NGF and the Amyloid Precursor Protein in Alzheimer's Disease: From Molecular Players to Neuronal Circuits

Alzheimer's disease (AD), one of the most common causes of dementia in elderly people, is characterized by progressive impairment in cognitive function, early degeneration of basal forebrain cholinergic neurons (BFCNs), abnormal metabolism of the amyloid precursor protein (APP), amyloid beta-peptide (Aβ) depositions, and neurofibrillary tangles. According to the cholinergic hypothesis, dysfunction of acetylcholine-containing neurons in the basal forebrain contributes markedly to the cognitive decline observed in AD. In addition, the neurotrophic factor hypothesis posits that the loss nerve growth factor (NGF) signalling in AD may account for the vulnerability to atrophy of BFCNs and consequent impairment of cholinergic functions. Though acetylcholinesterase inhibitors provide only partial and symptomatic relief to AD patients, emerging data from in vivo magnetic resonance imaging (MRI) and positron emission tomography (PET) studies in mild cognitive impairment (MCI) and AD patients highlight the early involvement of BFCNs in MCI and the early phase of AD. These data support the cholinergic and neurotrophic hypotheses of AD and suggest new targets for AD therapy.Different mechanisms account for selective vulnerability of BFCNs to AD pathology, with regard to altered metabolism of APP and tau. In this review, we provide a general overview of the current knowledge of NGF and APP interplay, focusing on the role of APP in regulating NGF receptors trafficking/signalling and on the involvement of NGF in modulating phosphorylation of APP, which in turn controls APP intracellular trafficking and processing. Moreover, we highlight the consequences of APP interaction with p75NTR and TrkA receptor, which share the same binding site within the APP juxta-membrane domain. We underline the importance of insulin dysmetabolism in AD pathology, in the light of our recent data showing that overlapping intracellular signalling pathways stimulated by NGF or insulin can be compensatory. In particular, NGF-based signalling is able to ameliorates deficiencies in insulin signalling in the medial septum of 3×Tg-AD mice. Finally, we present an overview of NGF-regulated microRNAs (miRNAs). These small non-coding RNAs are involved in post-transcriptional regulation of gene expression , and we focus on a subset that are specifically deregulated in AD and thus potentially contribute to its pathology.

Brain-Machine Interfaces: The Role of the Neurosurgeon

Neurotechnology is set to expand rapidly in the coming years as technological innovations in hardware and software are translated to the clinical setting. Given our unique access to patients with neurologic disorders, expertise with which to guide appropriate treatments, and technical skills to implant brain-machine interfaces (BMIs), neurosurgeons have a key role to play in the progress of this field. We outline the current state and key challenges in this rapidly advancing field, including implant technology, implant recipients, implantation methodology, implant function, and ethical, regulatory, and economic considerations. Our key message is to encourage the neurosurgical community to proactively engage in collaborating with other health care professionals, engineers, scientists, ethicists, and regulators in tackling these issues. By doing so, we will equip ourselves with the skills and expertise to drive the field forward and avoid being mere technicians in an industry driven by those around us.

Probing Network Mechanisms of Brain Stimulation in the Mood Circuit

Direct brain stimulation has diverse effects on network activity. In this issue of Neuron, Qiao et al. (2020) demonstrate a novel approach for using stimulation to characterize and modulate interactions between areas of the mood processing network.

Perspective: Evolution of Control Variables and Policies for Closed-Loop Deep Brain Stimulation for Parkinson's Disease Using Bidirectional Deep-Brain-Computer Interfaces

A deep brain stimulation system capable of closed-loop neuromodulation is a type of bidirectional deep brain-computer interface (dBCI), in which neural signals are recorded, decoded, and then used as the input commands for neuromodulation at the same site in the brain. The challenge in assuring successful implementation of bidirectional dBCIs in Parkinson's disease (PD) is to discover and decode stable, robust and reliable neural inputs that can be tracked during stimulation, and to optimize neurostimulation patterns and parameters (control policies) for motor behaviors at the brain interface, which are customized to the individual. In this perspective, we will outline the work done in our lab regarding the evolution of the discovery of neural and behavioral control variables relevant to PD, the development of a novel personalized dual-threshold control policy relevant to the individual's therapeutic window and the application of these to investigations of closed-loop STN DBS driven by neural or kinematic inputs, using the first generation of bidirectional dBCIs.