Noradrenergic Pharmacotherapy, Intracerebral Infusion and Adrenal Transplantation Promote Functional Recovery After Cortical Damage

The research described in this review briefly summarizes evidence that short term pharmacological enhancement of noradrenergic (NA) synaptic activity, combined with symptom relevant experience (SRE), promotes functional recovery of some symptoms of cortical damage in rat, cat and human beings even when treatment is initiated from days to weeks after injury. A summary is provided of the numerous drugs tested in rodent cortical injury models which have been proven useful for predicting beneficial or harmful effects on behavioral outcome in human stroke. The pattern of drug effects indicates a central role for NA in functional recovery. Additionally, studies of the effects of direct intraventricular infusion of monoamine neurotransmitters are reviewed and further support the hypothesized role of NA in recovery from some symptoms of cortical injury. The site of NA/SRE interaction to promote recovery from hemiplegia apparently involves the cerebellar hemisphere contralateral to the cortical injury. Microinfusions of NA into the contra- but not ipsilaterai cerebellar hemisphere dramatically enhance recovery. Furthermore, like its systemic action, microinfusion of the α1- NA receptor antagonist, phenoxybenzamine, reinstates hemiplegia. A “permanent” symptom of motor cortex injury in the cat is the complete loss of tactile placing contralateral to the injury which does not spontaneously recover for as long as seven years after ablation. This posturai reflex is temporarily restored for 8-12 hours following amphetamine administration. However, this permanently lost reflex can be enduringly restored by transplanting catecholamine secreting adrenal tissue into the wound cavity. The experiment is reviewed in detail and involves chromaffin cell autografts into the frontal cortex ablation wound cavity producing a restoration of tactile placing for the 7-10 month duration of the study. This enduring restoration of tactile placing is considered a result of the release of catecholamines into the CNS from the grafted chromaffin cells found, by histochemical methods, surviving 7-10 months after transplant. Lastly, we attribute these delayed treatment effects to an attenuation of a diaschisis, or remote functional depression, in morphologically intact areas anatomically connected to the area of injury. The widespread reduction of glycolytic and oxidative metabolism, produced by focal cortical injury, is normalized by the same treatment which alleviates symptoms and is worsened by drugs which exacerbate deficits. These data support the hypothesis that providing SRE during a period of enhanced NA synaptic activity produces an enduring functional recovery after cortical injury by attenuating remote functional depression. This treatment for enhancing recovery is especially attractive since it is effective even when begun weeks after cortical damage

Combining Real-Time fMRI Neurofeedback Training of the DLPFC with N-Back Practice Results in Neuroplastic Effects Confined to the Neurofeedback Target Region

In traditional fMRI, individuals respond to exogenous stimuli and are naïve to the effects of the stimuli on their neural activity patterns. Changes arising in the fMRI signal are analyzed post-hoc to elucidate the spatial and temporal activation of brain regions associated with the tasks performed. The advent of real-time fMRI has enabled a new method to systematically alter brain activity across space and time using neurofeedback training (NFT), providing a new tool to study internally-driven processes such as neuroplasticity. In this work, we combined n-back practice with fMRI-NFT of the left dorsolateral prefrontal cortex (DLPFC) to better understand the relationship between open- and closed-loop neuromodulation. FMRI data were acquired during both traditional n-back and NFT across five imaging sessions. Region-of-interest (ROI) and voxel-wise 2 × 2 within subjects ANOVAs were carried out to determine the effects of, and interaction between, training session and neuromodulation type. A main effect of training session was identified for only a single, highly focused cluster that shared spatial properties with the fMRI-NFT target region (left DLPFC). This finding indicates that combined open- and closed-loop neuroplastic enhancement techniques result in focal changes that are confined to the target area of NFT, and do not affect up- or down-stream network components that are normally engaged during working memory. Additionally, we identified a main effect of neuromodulation type for 15 clusters with significantly different activation between open- and closed-loop neuromodulation during training, 12 of which demonstrated higher activity during the open-loop neuromodulation. Our results, taken together with previous reports, indicate that fMRI-NFT combined with n-back practice leads to a highly focal volume exhibiting neuroplasticity without additional network effects

An MEG study of response latency and variability in the human visual system during a visual-motor integration task

Human reaction times during sensory-motor tasks vary considerably. To begin to understand how this variability arises, we examined neuronal populational response time variability at early versus late visual processing stages. The conventional view is that precise temporal information is gradually lost as information is passed through a layered network of mean-rate \units." We tested in humans whether neuronal populations at different processing stages behave like mean-rate \units". A blind source separation algorithm was applied to MEG signals from sensory-motor integration tasks. Response time latency and variability for multiple visual sources were estimated by detecting single-trial stimulus-locked events for each source. In two subjects tested on four visual reaction time tasks, we reliably identified sources belonging to early and late visual processing stages. The standard deviation of response latency was smaller for early rather than late processing stages. This supports the hypothesis that human populational response time variability increases from early to late visual processing stages

Closed-Loop Targeted Memory Reactivation during Sleep Improves Spatial Navigation

Sounds associated with newly learned information that are replayed during non-rapid eye movement (NREM) sleep can improve recall in simple tasks. The mechanism for this improvement is presumed to be reactivation of the newly learned memory during sleep when consolidation takes place. We have developed an EEG-based closed-loop system to precisely deliver sensory stimulation at the time of down-state to up-state transitions during NREM sleep. Here, we demonstrate that applying this technology to participants performing a realistic navigation task in virtual reality results in a significant improvement in navigation efficiency after sleep that is accompanied by increases in the spectral power especially in the fast (12\u201315 Hz) sleep spindle band. Our results show promise for the application of sleep-based interventions to drive improvement in real-world tasks

MEG and fMRI Fusion for Non-Linear Estimation of Neural and BOLD Signal Changes

The combined analysis of magnetoencephalography (MEG)/electroencephalography and functional magnetic resonance imaging (fMRI) measurements can lead to improvement in the description of the dynamical and spatial properties of brain activity. In this paper we empirically demonstrate this improvement using simulated and recorded task related MEG and fMRI activity. Neural activity estimates were derived using a dynamic Bayesian network with continuous real valued parameters by means of a sequential Monte Carlo technique. In synthetic data, we show that MEG and fMRI fusion improves estimation of the indirectly observed neural activity and smooths tracking of the blood oxygenation level dependent (BOLD) response. In recordings of task related neural activity the combination of MEG and fMRI produces a result with greater signal-to-noise ratio, that confirms the expectation arising from the nature of the experiment. The highly non-linear model of the BOLD response poses a difficult inference problem for neural activity estimation; computational requirements are also high due to the time and space complexity. We show that joint analysis of the data improves the system's behavior by stabilizing the differential equations system and by requiring fewer computational resources