The Timing of Reward-Seeking Action Tracks Visually-Cued Theta Oscillations in Primary Visual Cortex

An emerging body of work challenges the view that primary visual cortex (V1) represents the visual world faithfully. Theta oscillations in the local field potential (LFP) of V1 have been found to convey temporal expectations and, specifically, to express the delay between a visual stimulus and the reward that it portends. We extend this work by showing how these oscillatory states in male, wild-type rats can even relate to the timing of a visually cued reward-seeking behavior. In particular, we show that, with training, high precision and accuracy in behavioral timing tracks the power of these oscillations and the time of action execution covaries with their duration. These LFP oscillations are also intimately related to spiking responses at the single-unit level, which themselves carry predictive timing information. Together, these observations extend our understanding of the role of cortical oscillations in timing generally and the role of V1 in the timing of visually cued behaviors specifically.Fil: Levy, Joshua M.. University Johns Hopkins; Estados UnidosFil: Zold, Camila Lidia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Fisiología y Biofísica Bernardo Houssay. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Fisiología y Biofísica Bernardo Houssay; ArgentinaFil: Namboodiri, Vijay Mohan K.. University of North Carolina; Estados UnidosFil: Hussain Shuler, Marshall G. University Johns Hopkins; Estados Unido

Optogenetic Dissection of the Basal Forebrain Neuromodulatory Control of Cortical Activation, Plasticity, and Cognition

The basal forebrain (BF) houses major ascending projections to the entire neocortex that have long been implicated in arousal, learning, and attention. The disruption of the BF has been linked with major neurological disorders, such as coma and Alzheimer's disease, as well as in normal cognitive aging. Although it is best known for its cholinergic neurons, the BF is in fact an anatomically and neurochemically complex structure. Recent studies using transgenic mouse lines to target specific BF cell types have led to a renaissance in the study of the BF and are beginning to yield new insights about cell-type-specific circuit mechanisms during behavior. These approaches enable us to determine the behavioral conditions under which cholinergic and noncholinergic BF neurons are activated and how they control cortical processing to influence behavior. Here we discuss recent advances that have expanded our knowledge about this poorly understood brain region and laid the foundation for future cell-type-specific manipulations to modulate arousal, attention, and cortical plasticity in neurological disorders. SIGNIFICANCE STATEMENT: Although the basal forebrain is best known for, and often equated with, acetylcholine-containing neurons that provide most of the cholinergic innervation of the neocortex, it is in fact an anatomically and neurochemically complex structure. Recent studies using transgenic mouse lines to target specific cell types in the basal forebrain have led to a renaissance in this field and are beginning to dissect circuit mechanisms in the basal forebrain during behavior. This review discusses recent advances in the roles of basal forebrain cholinergic and noncholinergic neurons in cognition via their dynamic modulation of cortical activity

The sinus tarsi approach in displaced intra-articular calcaneal fractures: a systematic review

Purpose: Although open reduction and internal fixation is currently considered the gold standard in surgical treatment of displaced intra-articular calcaneal fractures, various different approaches exist including the limited lateral approach. The aim of this systematic review was to combine the results of studies using the sinus tarsi approach, which is the most frequently applied limited lateral approach. Method: A literature search in the electronic databases of the Cochrane Library and Pubmed Medline, between January 1st 2000 to December 1st 2010, was conducted to identify studies in which the sinus tarsi approach or a modified sinus tarsi approach was utilized for the treatment of displaced intra-articular calcaneal fractures. The methodological quality of the included studies was assessed using the Coleman methodology score. Results: A total of eight case series reporting on 256 patients with 271 calcaneal fractures was identified. Overall good to excellent outcome was reached in three-quarters of all patients. An average complication rate of minor wound complications of 4.1% was reported and major wound complications in 0.7%. The need for a secondary subtalar arthrodesis occurred at an average rate of 4.3%. The average Coleman methodology score was 56.8 (range 39-72) points. Conclusion: The results, i.e. functional outcome and complication rates, of the sinus tarsi approach compare similarly or favourably to the extended lateral approach. Therefore, in the process of tailoring the best treatment modality to the right patient and the right fracture type, the sinus tarsi approach might be a valuable asset

Rationalizing spatial exploration patterns of wild animals and humans through a temporal discounting framework

Understanding the exploration patterns of foragers in the wild provides fundamental insight into animal behavior. Recent experimental evidence has demonstrated that path lengths (distances between consecutive turns) taken by foragers are well fitted by a power law distribution. Numerous theoretical contributions have posited that “Lévy random walks”—which can produce power law path length distributions—are optimal for memoryless agents searching a sparse reward landscape. It is unclear, however, whether such a strategy is efficient for cognitively complex agents, from wild animals to humans. Here, we developed a model to explain the emergence of apparent power law path length distributions in animals that can learn about their environments. In our model, the agent’s goal during search is to build an internal model of the distribution of rewards in space that takes into account the cost of time to reach distant locations (i.e., temporally discounting rewards). For an agent with such a goal, we find that an optimal model of exploration in fact produces hyperbolic path lengths, which are well approximated by power laws. We then provide support for our model by showing that humans in a laboratory spatial exploration task search space systematically and modify their search patterns under a cost of time. In addition, we find that path length distributions in a large dataset obtained from free-ranging marine vertebrates are well described by our hyperbolic model. Thus, we provide a general theoretical framework for understanding spatial exploration patterns of cognitively complex foragers

A Machine Learning Algorithm to Identify Patients at Risk of Unplanned Subsequent Surgery After Intramedullary Nailing for Tibial Shaft Fractures

Objectives: In the SPRINT trial, 18% of patients with a tibial shaft fracture (TSF) treated with intramedullary nailing (IMN) had one or more unplanned subsequent surgical procedures. It is clinically relevant for surgeon and patient to anticipate unplanned secondary procedures, other than operations that can be readily expected such as reconstructive procedures for soft tissue defects. Therefore, the objective of this study was to develop a machine learning (ML) prediction model using the SPRINT data that can give individual patients and their care team an estimate of their particular probability of an unplanned second surgery. Methods: Patients from the SPRINT trial with unilateral TSFs were randomly divided into a training set (80%) and test set (20%). Five ML algorithms were trained in recognizing patterns associated with subsequent surgery in the training set based on a subset of variables identified by random forest algorithms. Performance of each ML algorithm was evaluated and compared based on (1) area under the ROC curve, (2) calibration slope and intercept, and (3) the Brier score. Results: Total data set comprised 1198 patients, of whom 214 patients (18%) underwent subsequent surgery. Seven variables were used to train ML algorithms: (1) Gustilo-Anderson classification, (2) Tscherne classification, (3) fracture location, (4) fracture gap, (5) polytrauma, (6) injury mechanism, and (7) OTA/AO classification. The best-performing ML algorithm had an area under the ROC curve, calibration slope, calibration intercept, and the Brier score of 0.766, 0.954, -0.002, and 0.120 in the training set and 0.773, 0.922, 0, and 0.119 in the test set, respectively. Conclusions: An ML algorithm was developed to predict the probability of subsequent surgery after IMN for TSFs. This ML algorithm may assist surgeons to inform patients about the probability of subsequent surgery and might help to identify patients who need a different perioperative plan or a more intensive approach.Orthopaedics, Trauma Surgery and Rehabilitatio