Faculty Bibliography

A major challenge in neuroscience is linking behavior to the collective activity of neural assemblies. Understanding of input-output relationships of neurons and circuits requires methods with the spatial selectivity and temporal resolution appropriate for mechanistic analysis of neural ensembles in the behaving animal, i.e. recording of representatively large samples of isolated single neurons. Ensemble monitoring of neuronal activity has progressed remarkably in the past decade in both small and large-brained animals, including human subjects. Multiple-site recording with silicon-based devices are particularly effective because of their scalability, small volume and geometric design. Here, we describe methods for recording multiple single neurons and local field potential in behaving rodents, using commercially available micro-machined silicon probes with custom-made accessory components. There are two basic options for interfacing silicon probes to preamplifiers: printed circuit boards and flexible cables. Probe supplying companies (http://www.neuronexustech.com/; http://www.sbmicrosystems.com/; http://www.acreo.se/) usually provide the bonding service and deliver probes bonded to printed circuit boards or flexible cables. Here, we describe the implantation of a 4-shank, 32-site probe attached to flexible polyimide cable, and mounted on a movable microdrive. Each step of the probe preparation, microdrive construction and surgery is illustrated so that the end user can easily replicate the process.

BACKGROUND: Emerging neuroscientific and genetic findings emphasize the dimensional rather than the categorical aspects of psychiatric disorders. However, the integration of dimensional approaches within the current categorical diagnostic framework remains unclear. Here, we used resting state functional magnetic resonance imaging to examine whether dimensional measures of psychiatric symptomatology capture brain-behavior relationships unaccounted for by categorical diagnoses. Additionally, we examined whether dimensional brain-behavior relationships are modified by the presence of a categorically defined illness, attention-deficit/hyperactivity disorder (ADHD). METHODS: Resting state functional magnetic resonance imaging scans were collected from 37 typically developing children (aged 10.2 +/- 2; 21 female subjects) and 37 children meeting DSM-IV Text Revision criteria for ADHD (9.7 +/- 2; 11 female subjects). Parent-rated Child Behavior Checklist Externalizing and Internalizing scores served as dimensional measures in our analyses of default network (DN) resting state functional connectivity (RSFC). RESULTS: Regardless of diagnosis, we observed several significant relationships between DN RSFC and both internalizing and externalizing scores. Increased internalizing scores were associated with stronger positive intra-DN RSFC, while increased externalizing scores were associated with reduced negative RSFC between DN and task-positive regions such as dorsal anterior cingulate cortex. Several of these brain-behavior relationships differed depending on the categorical presence of ADHD. CONCLUSIONS: Our findings suggest that while categorical diagnostic boundaries provide an inadequate basis for understanding the pathophysiology of psychiatric disorders, psychiatric illness cannot be viewed simply as an extreme of typical neural or behavioral function. Efforts to understand the neural underpinnings of psychiatric illness should incorporate both categorical and dimensional clinical assessments

Alzheimer's disease (AD) and epilepsy are separated in the medical community, but seizures occur in some patients with AD, and AD is a risk factor for epilepsy. Furthermore, memory impairment is common in patients with epilepsy. The relationship between AD and epilepsy remains an important question because ideas for therapeutic approaches could be shared between AD and epilepsy research laboratories if AD and epilepsy were related. Here we focus on one of the many types of epilepsy, temporal lobe epilepsy (TLE), because patients with TLE often exhibit memory impairment, depression and other comorbidities that occur in AD. Moreover, the seizures that occur in patients with AD may be nonconvulsive, which occur in patients with TLE. Here we first compare neuropathology in TLE and AD with an emphasis on the hippocampus, which is central to both AD and TLE research. Then we compare animal models of AD pathology with animal models of TLE. Although many aspects of the comparisons are still controversial, there is one conclusion that we suggest is clear: some animal models of TLE could be used to help address questions in AD research, and some animal models of AD pathology are bona fide animal models of epilepsy.

To survive in a dynamic environment, an organism must be able to effectively learn, store, and recall the expected benefits and costs of potential actions. The nature of the valuation and decision processes is thus of fundamental interest to researchers at the intersection of psychology, neuroscience, and economics. Although normative theories of choice have outlined the theoretical structure of these valuations, recent experiments have begun to reveal how value is instantiated in the activity of neurons and neural circuits. Here, we review the various forms of value coding that have been observed in different brain systems and examine the implications of these value representations for both neural circuits and behavior. In particular, we focus on emerging evidence that value coding in a number of brain areas is context dependent, varying as a function of both the current choice set and previously experienced values. Similar contextual modulation occurs widely in the sensory system, and efficient coding principles derived in the sensory domain suggest a new framework for understanding the neural coding of value.

Introduction: Pompe disease is a rare, autosomal recessive disorder caused by deficiency of the glycogen-degrading lysosomal enzyme acid alpha-glucosidase. Late-onset Pompe disease is a multisystem condition, with a heterogeneous clinical presentation that mimics other neuromuscular disorders. Methods: Objective is to propose consensus-based treatment and management recommendations for late-onset Pompe disease. Methods: A systematic review of the literature by a panel of specialists with expertise in Pompe disease was undertaken. Conclusions: A multidisciplinary team should be involved to properly treat the pulmonary, neuromuscular, orthopedic, and gastrointestinal elements of late-onset Pompe disease. Presymptomatic patients with subtle objective signs of Pompe disease (and patients symptomatic at diagnosis) should begin treatment with enzyme replacement therapy (ERT) immediately; presymptomatic patients without symptoms or signs should be observed without use of ERT. After 1 year of ERT, patients' condition should be reevaluated to determine whether ERT should be continued. Muscle Nerve, 2012.

This paper reviews our recent work addressing the role of both synaptic-input and connectivity-architecture fluctuations in coarse-grained descriptions of integrate-and-fire (I&F) point-neuron network models. Beginning with the most basic coarse-grained description, the all-to-all coupled, mean-field model, which ignores all fluctuations, we add the effects of the two types of fluctuations one at a time. To study the effects of synaptic-input fluctuations, we derive a kinetic-theoretic description, first in the form of a Boltzmann equation in (2+1) dimensions, simplifying that to an advection-diffusion equation, and finally reducing the dimension to a system of two (1+1)-dimensional kinetic equations via the maximum entropy principle. In the limit of an infinitely-fast conductance relaxation time, we derive a Fokker-Planck equation which captures the bifurcation between a bistable, hysteretic operating regime of the network when the amount of synaptic-input fluctuations is small, and a stable regime when the amount of fluctuations increases. To study the effects of complex neuronal-network architecture, we incorporate the network connectivity statistics in the mean-field description, and investigate the dependence of these statistics on the statistical properties of the neuronal firing rates for three network examples with increasingly complex connectivity architecture

BACKGROUND:: To define the clinical neuro-ophthalmic abnormalities of patients with familial dysautonomia (FD). METHODS:: Sixteen patients (32 eyes) with the clinical and molecular diagnoses of FD underwent thorough neuro-ophthalmic clinical evaluation. RESULTS:: Visual acuity ranged from 0.05 to 1.0 decimal units and was reduced in 15 of 16 patients. Mild to moderate corneal opacities were found in most patients but were visually significant in only 2 eyes. Red-green color vision was impaired in almost all cases. Depression of the central visual fields was present on automated visual fields in all patients, even in those with normal visual acuity. Temporal optic nerve pallor was present in all cases and was associated with retinal nerve fiber layer loss in the papillomacular region. Various ocular motility abnormalities also were observed. CONCLUSION:: Patients with FD have a specific type of optic neuropathy with predominant loss of papillomacular nerve fibers, a pattern similar to other hereditary optic neuropathies caused by mutations either in nuclear or in mitochondrial DNA, affecting mitochondrial protein function. Defects of eye movements, particularly saccades, also appear to be a feature of patients with FD

The functional MRI (fMRI) community has zealously embraced resting state or intrinsic functional connectivity approaches to mapping brain organization. Having demonstrated their utility for charting the large-scale functional architecture of the brain, the field is now leveraging task-independent methods for the investigation of phenotypic variation and the identification of biomarkers for clinical conditions. Enthusiasm aside, questions regarding the significance and validity of intrinsic brain phenomena remain. Here, we discuss these challenges and outline current developments that, in moving the field toward discovery science, permit a shift from cartography toward a mechanistic understanding of the neural bases of variation in cognition, emotion and behavior.

Abstract Objective. Brain iron deficiency has been supposed to be involved in the pathophysiology of ADHD. Available studies assessing iron in ADHD are based on serum ferritin, a peripheral marker of iron status. To what extent serum ferritin correlates with brain iron (BI) is unclear. The main aim of this study was to compare BI, estimated with magnetic resonance imaging (MRI) in the putamen, pallidum, caudate, and thalamus, between children with and without ADHD. The secondary aim was to assess the correlation between serum ferritin and BI levels. Methods. Thirty-six children (18 with and 18 without ADHD, the latter including nine healthy controls and nine psychiatric controls) completed MRI and blood sampling. Brain iron levels were estimated by imaging T2*. Results. Children with ADHD showed significantly lower estimated BI in right and left thalamus compared to healthy controls. Estimated BI did not differ significantly between children with ADHD and psychiatric controls. Children with ADHD had significantly lower levels of serum ferritin than healthy as well as psychiatric controls. Serum ferritin and T2* values did not correlate significantly in most regions. Conclusions. Low iron in the thalamus may contribute to ADHD pathophysiology.

Respiratory sinus arrhythmia (RSA) is largely mediated by the autonomic nervous system through its modulating influence on the heart beats. We propose a robust algorithm for quantifying instantaneous RSA as applied to heart beat intervals and respiratory recordings under dynamic breathing patterns. The blood volume pressure-derived heart beat series (pulse intervals, PIs) are modeled as an inverse Gaussian point process, with the instantaneous mean PI modeled as a bivariate regression incorporating both past PIs and respiration values observed at the beats. A point process maximum likelihood algorithm is used to estimate the model parameters, and instantaneous RSA is estimated via a frequency domain transfer function evaluated at instantaneous respiratory frequency where high coherence between respiration and PIs is observed. The model is statistically validated using Kolmogorov-Smirnov goodness-of-fit analysis, as well as independence tests. The algorithm is applied to subjects engaged in meditative practice, with distinctive dynamics in the respiration patterns elicited as a result. The presented analysis confirms the ability of the algorithm to track important changes in cardiorespiratory interactions elicited during meditation, otherwise not evidenced in control resting states, reporting statistically significant increase in RSA gain as measured by our paradigm.