Electrophysiological differences between upper and lower limb movements in the human subthalamic nucleus

ObjectiveFunctional processes in the brain are segregated in both the spatial and spectral domain. Motivated by findings reported at the cortical level in healthy participants we test the hypothesis in the basal ganglia of Parkinson’s disease patients that lower frequency beta band activity relates to motor circuits associated with the upper limb and higher beta frequencies with lower limb movements.MethodsWe recorded local field potentials (LFPs) from the subthalamic nucleus using segmented “directional” DBS leads, during which patients performed repetitive upper and lower limb movements. Movement-related spectral changes in the beta and gamma frequency-ranges and their spatial distributions were compared between limbs.ResultsWe found that the beta desynchronization during leg movements is characterised by a strikingly greater involvement of higher beta frequencies (24–31 Hz), regardless of whether this was contralateral or ipsilateral to the limb moved. The spatial distribution of limb-specific movement-related changes was evident at higher gamma frequencies.ConclusionLimb processing in the basal ganglia is differentially organised in the spectral and spatial domain and can be captured by directional DBS leads.SignificanceThese findings may help to refine the use of the subthalamic LFPs as a control signal for adaptive DBS and neuroprosthetic devices.     

Impaired function of fibroblast growth factor 23 / Klotho protein axis in prediabetes and diabetes mellitus: Promising predictor of cardiovascular risk

The discovery of clear molecular mechanisms of early cardiac and vascular complications in patients with prediabetes and known diabetes mellitus are core element of stratification at risk with predictive model creation further. Previous clinical studies have shown a pivotal role of impaired signaling axis of fibroblast growth factor 23 (FGF23), FGF23 receptor isoforms and its co-factor Klotho protein in cardiovascular (CV) complications in prediabetes and diabetes. Although there were data received in clinical studies, which confirmed a causative role of altered function of FGF-23/Klotho protein axis in manifestation of CV disease in prediabetes and type 2 diabetes mellitus (T2DM), the target therapy of these diseases directing on improvement of metabolic profiles, systemic and adipokine-relating inflammation by beneficial restoring of dysregulation in FGF-23/Klotho protein axis remain to be not fully clear. The aim of the review was to summarize findings regarding the role of impaired FGF-23/Klotho protein axis in developing CV complications in patients with prediabetes and type 2 diabetes mellitus. It has been elucidated that elevated levels of FGF-23 and deficiency of Klotho protein in peripheral blood are predictors of CV disease and CV outcomes in patients with (pre) diabetes, while predictive values of dynamic changes of the concentrations of these biomarkers require to be elucidated in detail in the future.     

Brain activation during the voiding phase of micturition in healthy adults: A meta‐analysis of neuroimaging studies

Several studies have used a variety of neuroimaging techniques to measure brain activity during the voiding phase of micturition. However, there is a lack of consensus on which regions of the brain are activated during voiding. The aim of this meta‐analysis is to identify the brain regions that are consistently activated during voiding in healthy adults across different studies. We searched the literature for neuroimaging studies that reported brain co‐ordinates that were activated during voiding. We excluded studies that reported co‐ordinates only for bladder filling, during pelvic floor contraction only, and studies that focused on abnormal bladder states such as the neurogenic bladder. We used the activation‐likelihood estimation (ALE) approach to create a statistical map of the brain and identify the brain co‐ordinates that were activated across different studies. We identified nine studies that reported brain activation during the task of voiding in 91 healthy subjects. Together, these studies reported 117 foci for ALE analysis. Our ALE map yielded six clusters of activation in the pons, cerebellum, insula, anterior cingulate cortex (ACC), thalamus, and the inferior frontal gyrus. Regions of the brain involved in executive control (frontal cortex), interoception (ACC, insula), motor control (cerebellum, thalamus), and brainstem (pons) are involved in micturition. This analysis provides insight into the supraspinal control of voiding in healthy adults and provides a framework to understand dysfunctional voiding. Clin. Anat., 2018. © 2018 Wiley Periodicals, Inc.     

Functional MRI activation patterns of cerebellum in patients with epilepsy and brain tumors

Function of cerebellum in control and coordination of motor function has been well established for several years. Recent functional magnetic resonance imaging (MRI) studies reveal activation of cerebellum with memory, speech and language tasks. We hypothesize that during every function in the brain signals are relayed to cerebellum. We seek to analyze cognitive, emotional and social functions of cerebellum in patients with brain tumors and epilepsy utilizing functional Magnetic Resonance Imaging. Fifty‐one consecutive adult patients who underwent functional MRI examination were retrospectively analyzed for various activation patterns involving cerebellum. The neuropsychological battery of tasks assessed motor, language, memory, visual and auditory functions. Cognitive ability of all participants was assessed by Montreal cognitive assessment (MOCA). Patterns were analyzed for specific lobes and locations in the cerebellum. We found that simultaneous cerebellar activation is a consistent finding with brain activation during every functional MRI task that we tested except visual task. The patterns of functional MRI cerebellar activation were similar in both patient subgroups and control subjects compared to previously described patterns in normal subjects. Clin. Anat. 32:1053–1060, 2019. © 2019 Wiley Periodicals, Inc.     

Identifying areas for improvement in paediatric trauma care in NSW Australia using a clinical,system and human factors peer-review tool

BackgroundThere is known variability in the quality of care delivered to injured children. Identifying where care improvement can be made is critical. This study aimed to review paediatric trauma cases across the most populous Australian State to identify factors contributing to clinical incidents.MethodsMedical records from three New South Wales Paediatric Trauma Centres were reviewed for children <16 years requiring intensive care; with an injury severity score of ≥9, or who died following injury between July 2015 and September 2016. Records were peer-reviewed by nurse surveyors who identified cases that might not meet the expected standard of care or where the child died following the injury. A multidisciplinary panel conducted the peer-review using a major trauma peer-review tool. Records were reviewed independently, then discussed to establish consensus.ResultsA total 535 records were reviewed and 41 cases were peer-reviewed. The median (IQR) age was 7 (2–12) years, the median ISS was 25 (IQR 16–30). The peer-review identified a combination of clinical (85%), systems (51%) and communication (12%) problems that contributed to difficulties in care delivery. In 85% of records, staff actions were identified to contribute to events; with medical task failure the most frequently identified cause (89%).ConclusionThe peer-review of paediatric trauma cases assisted in the identification of contributing factors to clinical incidents in trauma care resulting in 26 recommendations for change. The prioritisation and implementation of these recommendations, alongside a uniform State-wide trauma case review process with consistent criteria (definitions), performance indicators, monitoring and reporting would facilitate improvement in health service delivery to children sustaining severe injury.     

From the Cover: Communication consumes 35 times more energy than computation in the human cortex,but both costs are needed to predict synapse number

Darwinian evolution tends to produce energy-efficient outcomes. On the other hand, energy limits computation, be it neural and probabilistic or digital and logical. Taking a particular energy-efficient viewpoint, we define neural computation and make use of an energy-constrained computational function. This function can be optimized over a variable that is proportional to the number of synapses per neuron. This function also implies a specific distinction between adenosine triphosphate (ATP)-consuming processes, especially computation per se vs. the communication processes of action potentials and transmitter release. Thus, to apply this mathematical function requires an energy audit with a particular partitioning of energy consumption that differs from earlier work. The audit points out that, rather than the oft-quoted 20 W of glucose available to the human brain, the fraction partitioned to cortical computation is only 0.1 W of ATP [L. Sokoloff, Handb. Physiol. Sect. I Neurophysiol. 3, 1843–1864 (1960)] and [J. Sawada, D. S. Modha, “Synapse: Scalable energy-efficient neurosynaptic computing” in Application of Concurrency to System Design (ACSD) (2013), pp. 14–15]. On the other hand, long-distance communication costs are 35-fold greater, 3.5 W. Other findings include 1) a 108-fold discrepancy between biological and lowest possible values of a neuron’s computational efficiency and 2) two predictions of N, the number of synaptic transmissions needed to fire a neuron (2,500 vs. 2,000).

The purpose of the brain is to process information, but that leaves us with the problem of finding appropriate definitions of information processing. We assume that given enough time and given a sufficiently stable environment (e.g., the common internals of the mammalian brain), then Nature’s constructions approach an optimum. The problem is to find which function or combined set of functions is optimal when incorporating empirical values into these function(s). The initial example in neuroscience is ref. 1, which shows that information capacity is far from optimized, especially in comparison to the optimal information per joule which is in much closer agreement with empirical values. Whenever we find such an agreement between theory and experiment, we conclude that this optimization, or near optimization, is Nature’s perspective. Using this strategy, we and others seek quantified relationships with particular forms of information processing and require that these relationships are approximately optimal (1–7). At the level of a single neuron, a recent theoretical development identifies a potentially optimal computation (8). To apply this conjecture requires understanding certain neuronal energy expenditures. Here the focus is on the energy budget of the human cerebral cortex and its primary neurons. The energy audit here differs from the premier earlier work (9) in two ways: The brain considered here is human not rodent, and the audit here uses a partitioning motivated by the information-efficiency calculations rather than the classical partitions of cell biology and neuroscience (9). Importantly, our audit reveals greater energy use by communication than by computation. This observation in turn generates additional insights into the optimal synapse number. Specifically, the bits per joule optimized computation must provide sufficient bits per second to the axon and presynaptic mechanism to justify the great expense of timely communication. Simply put from the optimization perspective, we assume evolution would not build a costly communication system and then not supply it with appropriate bits per second to justify its costs. The bits per joule are optimized with respect to N, the number of synaptic activations per interpulse interval (IPI) for one neuron, where N happens to equal the number of synapses per neuron times the success rate of synaptic transmission (below).To measure computation, and to partition out its cost, requires a suitable definition at the single-neuron level. Rather than the generic definition “any signal transformation” (3) or the neural-like “converting a multivariate signal to a scalar signal,” we conjecture a more detailed definition (8). To move toward this definition, note two important brain functions: estimating what is present in the sensed world and predicting what will be present, including what will occur as the brain commands manipulations. Then, assume that such macroscopic inferences arise by combining single-neuron inferences. That is, conjecture a neuron performing microscopic estimation or prediction. Instead of sensing the world, a neuron’s sensing is merely its capacitive charging due to recently active synapses. Using this sampling of total accumulated charge over a particular elapsed time, a neuron implicitly estimates the value of its local latent variable, a variable defined by evolution and developmental construction (8). Applying an optimization perspective, which includes implicit Bayesian inference, a sufficient statistic, and maximum-likelihood unbiasedness, as well as energy costs (8), produces a quantified theory of single-neuron computation. This theory implies the optimal IPI probability distribution. Motivating IPI coding is this fact: The use of constant amplitude signaling, e.g., action potentials, implies that all information can only be in IPIs. Therefore, no code can outperform an IPI code, and it can equal an IPI code in bit rate only if it is one to one with an IPI code. In neuroscience, an equivalent to IPI codes is the instantaneous rate code where each message is IPI−1. In communication theory, a discrete form of IPI coding is called differential pulse position modulation (10); ref. 11 explicitly introduced a continuous form of this coding as a neuron communication hypothesis, and it receives further development in ref. 12.Results recall and further develop earlier work concerning a certain optimization that defines IPI probabilities (8). An energy audit is required to use these developments. Combining the theory with the audit leads to two outcomes: 1) The optimizing N serves as a consistency check on the audit and 2) future energy audits for individual cell types will predict N for that cell type, a test of the theory. Specialized approximations here that are not present in earlier work (9) include the assumptions that 1) all neurons of cortex are pyramidal neurons, 2) pyramidal neurons are the inputs to pyramidal neurons, 3) a neuron is under constant synaptic bombardment, and 4) a neuron’s capacitance must be charged 16 mV from reset potential to threshold to fire.Following the audit, the reader is given a perspective that may be obvious to some, but it is rarely discussed and seemingly contradicts the engineering literature (but see ref. 6). In particular, a neuron is an incredibly inefficient computational device in comparison to an idealized physical analog. It is not just a few bits per joule away from optimal predicted by the Landauer limit, but off by a huge amount, a factor of 108. The theory here resolves the efficiency issue using a modified optimization perspective. Activity-dependent communication and synaptic modification costs force upward optimal computational costs. In turn, the bit value of the computational energy expenditure is constrained to a central limit like the result: Every doubling of N can produce no more than 0.5 bits. In addition to 1) explaining the 108 excessive energy use, other results here include 2) identifying the largest “noise” source limiting computation, which is the signal itself, and 3) partitioning the relevant costs, which may help engineers redirect focus toward computation and communication costs rather than the 20-W total brain consumption as their design goal.     

The Natural Course of Serum D-Dimer,C-Reactive Protein,and Erythrocyte Sedimentation Rate Levels After Uneventful Primary Total Joint Arthroplasty

BackgroundThis study aimed to assess the baseline levels of D-dimer, C-reactive protein (CRP), and erythrocyte sedimentation rate (ESR) and monitor the natural course of these serum markers after uneventful primary total joint arthroplasty.MethodsThis prospective study enrolled 81 patients undergoing primary total knee arthroplasty or total hip arthroplasty. The level of serum D-dimer, CRP, and ESR was measured preoperatively and on postoperative days 1, 3, 5, 15, and 45. Mean peak values, peak times, and distribution were compared between D-Dimer, CRP, and ESR.ResultsThe mean preoperative serum D-dimer, CRP, and ESR level was 412 ± 260 (range 200-980) ng/mL, 2.93 ± 2.1 (range 1-18) mg/L, and 22.88 ± 17.5 (range 3-102) mm/h, respectively. The highest mean peak for D-dimer, CRP, and ESR was at postoperative day 1, 3, and 5, respectively.ConclusionD-dimer levels reached peak levels on postoperative day 1 and then declined rapidly to a plateau level by postoperative day 3. A second, albeit small, peak in the level of D-dimer occurred on postoperative day 15. The level of CRP and ESR remained elevated for much longer with CRP returning to baseline on postoperative day 45 and the level of ESR had not returned back to normal on postoperative day 45.