Allen Song

Spinal cord injury (SCI) induces severe deficiencies in sensory-motor and autonomic functions and has a significant negative impact on patients' quality of life. There is currently no systematic rehabilitation technique assuring recovery of the neurological impairments caused by a complete SCI. Here, we report significant clinical improvement in a group of seven chronic SCI patients (six AIS A, one AIS B) following a 28-month, multi-step protocol that combined training with non-invasive brain-machine interfaces, visuo-tactile feedback and assisted locomotion. All patients recovered significant levels of nociceptive sensation below their original SCI (up to 16 dermatomes, average 11 dermatomes), voluntary motor functions (lower-limbs muscle contractions plus multi-joint movements) and partial sensory function for several modalities (proprioception, tactile, pressure, vibration). Patients also recovered partial intestinal, urinary and sexual functions. By the end of the protocol, all patients had their AIS classification upgraded (six from AIS A to C, one from B to C). These improvements translated into significant changes in the patients' quality of life as measured by standardized psychological instruments. Reexamination of one patient that discontinued the protocol after 12 months of training showed that the 16-month break resulted in neurological stagnation and no reclassification. We suggest that our neurorehabilitation protocol, based uniquely on non-invasive technology (therefore necessitating no surgical operation), can become a promising therapy for patients diagnosed with severe paraplegia (AIS A, B), even at the chronic phase of their lesion.

Cerebral Palsy (CP) refers to a heterogeneous group of permanent but non-progressive movement disorders caused by injury to the developing fetal or infant brain (Bax et al., 2005). Because of its serious long-term consequences, effective interventions that can help improve motor function, independence, and quality of life are critically needed. Our ongoing longitudinal clinical trial to treat children with CP is specifically designed to meet this challenge. To maximize the potential for functional improvement, all children in this trial received autologous cord blood transfusions (with order randomized with a placebo administration over 2 years) in conjunction with more standard physical and occupational therapies. As a part of this trial, magnetic resonance imaging (MRI) is used to improve our understanding of how these interventions affect brain development, and to develop biomarkers of treatment efficacy. In this report, diffusion tensor imaging (DTI) and subsequent brain connectome analyses were performed in a subset of children enrolled in the clinical trial (n = 17), who all exhibited positive but varying degrees of functional improvement over the first 2-year period of the study. Strong correlations between increases in white matter (WM) connectivity and functional improvement were demonstrated; however no significant relationships between either of these factors with the age of the child at time of enrollment were identified. Thus, our data indicate that increases in brain connectivity reflect improved functional abilities in children with CP. In future work, this potential biomarker can be used to help differentiate the underlying mechanisms of functional improvement, as well as to identify treatments that can best facilitate functional improvement upon un-blinding of the timing of autologous cord blood transfusions at the completion of this study.

Reward has been shown to promote human performance in multiple task domains. However, an important debate has developed about the uniqueness of reward-related neural signatures associated with such facilitation, as similar neural patterns can be triggered by increased attentional focus independent of reward. Here, we used functional magnetic resonance imaging to directly investigate the neural commonalities and interactions between the anticipation of both reward and task difficulty, by independently manipulating these factors in a cued-attention paradigm. In preparation for the target stimulus, both factors increased activity within the midbrain, dorsal striatum, and fronto-parietal areas, while inducing deactivations in default-mode regions. Additionally, reward engaged the ventral striatum, posterior cingulate, and occipital cortex, while difficulty engaged medial and dorsolateral frontal regions. Importantly, a network comprising the midbrain, caudate nucleus, thalamus, and anterior midcingulate cortex exhibited an interaction between reward and difficulty, presumably reflecting additional resource recruitment for demanding tasks with profitable outcome. This notion was consistent with a negative correlation between cue-related midbrain activity and difficulty-induced performance detriments in reward-predictive trials. Together, the data demonstrate that expected value and attentional demands are integrated in cortico-striatal-thalamic circuits in coordination with the dopaminergic midbrain to flexibly modulate resource allocation for an effective pursuit of behavioral goals.

Neuroscience methods entailing in vivo measurements of brain activity have greatly contributed to our understanding of brain function for the past decades, from the invasive early studies in animals using single-cell electrical recordings, to the noninvasive techniques in humans of scalp-recorded electroencephalography (EEG) and magnetoencephalography (MEG), positron emission tomography (PET), and, most recently, blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI). A central objective of these techniques is to measure neuronal activities with high spatial and temporal resolution. Each of these methods, however, has substantial limitations in this regard. Single-cell recording is invasive and only typically records cellular activity in a single location; EEG/MEG cannot generally provide accurate and unambiguous delineations of neuronal activation spatially; and the most sophisticated BOLD-based fMRI methods are still fundamentally limited by their dependence on the very slow hemodynamic responses upon which they are based. Even the latest neuroimaging methodology (e.g., multimodal EEG/fMRI) does not yet unambiguously provide accurate localization of neuronal activation spatially and temporally. There is hence a need to further develop noninvasive imaging methods that can directly image neuroelectric activity and thus truly achieve a high temporal resolution and spatial specificity in humans. Here, we discuss the theory, implementation, and potential utility of an MRI technique termed Lorentz effect imaging (LEI) that can detect spatially incoherent yet temporally synchronized, minute electrical activities in the neural amplitude range (microamperes) when they occur in a strong magnetic field. Moreover, we demonstrate with our preliminary results in phantoms and in vivo, the feasibility of imaging such activities with a temporal resolution on the order of milliseconds.

Many decisions are made under uncertainty; that is, with limited information about their potential consequences. Previous neuroimaging studies of decision making have implicated regions of the medial frontal lobe in processes related to the resolution of uncertainty. However, a different set of regions in dorsal prefrontal and posterior parietal cortices has been reported to be critical for selection of actions to unexpected or unpredicted stimuli within a sequence. In the current study, we induced uncertainty using a novel task that required subjects to base their decisions on a binary sequence of eight stimuli so that uncertainty changed dynamically over time (from 20 to 50%), depending on which stimuli were presented. Activation within prefrontal, parietal, and insular cortices increased with increasing uncertainty. In contrast, within medial frontal regions, as well as motor and visual cortices, activation did not increase with increasing uncertainty. We conclude that the brain response to uncertainty depends on the demands of the experimental task. When uncertainty depends on learned associations between stimuli and responses, as in previous studies, it modulates activation in the medial frontal lobes. However, when uncertainty develops over short time scales as information is accumulated toward a decision, dorsal prefrontal and posterior parietal contributions are critical for its resolution. The distinction between neural mechanisms subserving different forms of uncertainty resolution provides an important constraint for neuroeconomic models of decision making.