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Efficient coding and statistically optimal weighting of covariance among acoustic attributes in novel sounds.
To the extent that sensorineural systems are efficient, redundancy should be extracted to optimize transmission of information, but perceptual evidence for this has been limited. Stilp and colleagues recently reported efficient coding of robust correlation (r?=?.97) among complex acoustic attributes (attack/decay, spectral shape) in novel sounds. Discrimination of sounds orthogonal to the correlation was initially inferior but later comparable to that of sounds obeying the correlation. These effects were attenuated for less-correlated stimuli (r?=?.54) for reasons that are unclear. Here, statistical properties of correlation among acoustic attributes essential for perceptual organization are investigated. Overall, simple strength of the principal correlation is inadequate to predict listener performance. Initial superiority of discrimination for statistically consistent sound pairs was relatively insensitive to decreased physical acoustic/psychoacoustic range of evidence supporting the correlation, and to more frequent presentations of the same orthogonal test pairs. However, increased range supporting an orthogonal dimension has substantial effects upon perceptual organization. Connectionist simulations and Eigenvalues from closed-form calculations of principal components analysis (PCA) reveal that perceptual organization is near-optimally weighted to shared versus unshared covariance in experienced sound distributions. Implications of reduced perceptual dimensionality for speech perception and plausible neural substrates are discussed.
Acute animal preparations have been used in research prospectively investigating electrode designs and stimulation techniques for integration into neural auditory prostheses, such as auditory brainstem implants1-3 and auditory midbrain implants4,5. While acute experiments can give initial insight to the effectiveness of the implant, testing the chronically implanted and awake animals provides the advantage of examining the psychophysical properties of the sensations induced using implanted devices6,7. Several techniques such as reward-based operant conditioning6-8, conditioned avoidance9-11, or classical fear conditioning12 have been used to provide behavioral confirmation of detection of a relevant stimulus attribute. Selection of a technique involves balancing aspects including time efficiency (often poor in reward-based approaches), the ability to test a plurality of stimulus attributes simultaneously (limited in conditioned avoidance), and measure reliability of repeated stimuli (a potential constraint when physiological measures are employed). Here, a classical fear conditioning behavioral method is presented which may be used to simultaneously test both detection of a stimulus, and discrimination between two stimuli. Heart-rate is used as a measure of fear response, which reduces or eliminates the requirement for time-consuming video coding for freeze behaviour or other such measures (although such measures could be included to provide convergent evidence). Animals were conditioned using these techniques in three 2-hour conditioning sessions, each providing 48 stimulus trials. Subsequent 48-trial testing sessions were then used to test for detection of each stimulus in presented pairs, and test discrimination between the member stimuli of each pair. This behavioral method is presented in the context of its utilisation in auditory prosthetic research. The implantation of electrocardiogram telemetry devices is shown. Subsequent implantation of brain electrodes into the Cochlear Nucleus, guided by the monitoring of neural responses to acoustic stimuli, and the fixation of the electrode into place for chronic use is likewise shown.
18 Related JoVE Articles!
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Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
Authors: Marcus Cheetham, Lutz Jancke.
Institutions: University of Zurich.
Mori's Uncanny Valley Hypothesis1,2 proposes that the perception of humanlike characters such as robots and, by extension, avatars (computer-generated characters) can evoke negative or positive affect (valence) depending on the object's degree of visual and behavioral realism along a dimension of human likeness (DHL) (Figure 1). But studies of affective valence of subjective responses to variously realistic non-human characters have produced inconsistent findings 3, 4, 5, 6. One of a number of reasons for this is that human likeness is not perceived as the hypothesis assumes. While the DHL can be defined following Mori's description as a smooth linear change in the degree of physical humanlike similarity, subjective perception of objects along the DHL can be understood in terms of the psychological effects of categorical perception (CP) 7. Further behavioral and neuroimaging investigations of category processing and CP along the DHL and of the potential influence of the dimension's underlying category structure on affective experience are needed. This protocol therefore focuses on the DHL and allows examination of CP. Based on the protocol presented in the video as an example, issues surrounding the methodology in the protocol and the use in "uncanny" research of stimuli drawn from morph continua to represent the DHL are discussed in the article that accompanies the video. The use of neuroimaging and morph stimuli to represent the DHL in order to disentangle brain regions neurally responsive to physical human-like similarity from those responsive to category change and category processing is briefly illustrated.
Behavior, Issue 76, Neuroscience, Neurobiology, Molecular Biology, Psychology, Neuropsychology, uncanny valley, functional magnetic resonance imaging, fMRI, categorical perception, virtual reality, avatar, human likeness, Mori, uncanny valley hypothesis, perception, magnetic resonance imaging, MRI, imaging, clinical techniques
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Stimulating the Lip Motor Cortex with Transcranial Magnetic Stimulation
Authors: Riikka Möttönen, Jack Rogers, Kate E. Watkins.
Institutions: University of Oxford.
Transcranial magnetic stimulation (TMS) has proven to be a useful tool in investigating the role of the articulatory motor cortex in speech perception. Researchers have used single-pulse and repetitive TMS to stimulate the lip representation in the motor cortex. The excitability of the lip motor representation can be investigated by applying single TMS pulses over this cortical area and recording TMS-induced motor evoked potentials (MEPs) via electrodes attached to the lip muscles (electromyography; EMG). Larger MEPs reflect increased cortical excitability. Studies have shown that excitability increases during listening to speech as well as during viewing speech-related movements. TMS can be used also to disrupt the lip motor representation. A 15-min train of low-frequency sub-threshold repetitive stimulation has been shown to suppress motor excitability for a further 15-20 min. This TMS-induced disruption of the motor lip representation impairs subsequent performance in demanding speech perception tasks and modulates auditory-cortex responses to speech sounds. These findings are consistent with the suggestion that the motor cortex contributes to speech perception. This article describes how to localize the lip representation in the motor cortex and how to define the appropriate stimulation intensity for carrying out both single-pulse and repetitive TMS experiments.
Behavior, Issue 88, electromyography, motor cortex, motor evoked potential, motor excitability, speech, repetitive TMS, rTMS, virtual lesion, transcranial magnetic stimulation
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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Authors: Phoebe Spetsieris, Yilong Ma, Shichun Peng, Ji Hyun Ko, Vijay Dhawan, Chris C. Tang, David Eidelberg.
Institutions: The Feinstein Institute for Medical Research.
The scaled subprofile model (SSM)1-4 is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain image data while rejecting lesser components (Figure 1). Applied directly to voxel-by-voxel covariance data of steady-state multimodality images, an entire group image set can be reduced to a few significant linearly independent covariance patterns and corresponding subject scores. Each pattern, termed a group invariant subprofile (GIS), is an orthogonal principal component that represents a spatially distributed network of functionally interrelated brain regions. Large global mean scalar effects that can obscure smaller network-specific contributions are removed by the inherent logarithmic conversion and mean centering of the data2,5,6. Subjects express each of these patterns to a variable degree represented by a simple scalar score that can correlate with independent clinical or psychometric descriptors7,8. Using logistic regression analysis of subject scores (i.e. pattern expression values), linear coefficients can be derived to combine multiple principal components into single disease-related spatial covariance patterns, i.e. composite networks with improved discrimination of patients from healthy control subjects5,6. Cross-validation within the derivation set can be performed using bootstrap resampling techniques9. Forward validation is easily confirmed by direct score evaluation of the derived patterns in prospective datasets10. Once validated, disease-related patterns can be used to score individual patients with respect to a fixed reference sample, often the set of healthy subjects that was used (with the disease group) in the original pattern derivation11. These standardized values can in turn be used to assist in differential diagnosis12,13 and to assess disease progression and treatment effects at the network level7,14-16. We present an example of the application of this methodology to FDG PET data of Parkinson's Disease patients and normal controls using our in-house software to derive a characteristic covariance pattern biomarker of disease.
Medicine, Issue 76, Neurobiology, Neuroscience, Anatomy, Physiology, Molecular Biology, Basal Ganglia Diseases, Parkinsonian Disorders, Parkinson Disease, Movement Disorders, Neurodegenerative Diseases, PCA, SSM, PET, imaging biomarkers, functional brain imaging, multivariate spatial covariance analysis, global normalization, differential diagnosis, PD, brain, imaging, clinical techniques
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Functional Imaging of Auditory Cortex in Adult Cats using High-field fMRI
Authors: Trecia A. Brown, Joseph S. Gati, Sarah M. Hughes, Pam L. Nixon, Ravi S. Menon, Stephen G. Lomber.
Institutions: University of Western Ontario, University of Western Ontario, University of Western Ontario, University of Western Ontario, University of Western Ontario, University of Western Ontario, University of Western Ontario.
Current knowledge of sensory processing in the mammalian auditory system is mainly derived from electrophysiological studies in a variety of animal models, including monkeys, ferrets, bats, rodents, and cats. In order to draw suitable parallels between human and animal models of auditory function, it is important to establish a bridge between human functional imaging studies and animal electrophysiological studies. Functional magnetic resonance imaging (fMRI) is an established, minimally invasive method of measuring broad patterns of hemodynamic activity across different regions of the cerebral cortex. This technique is widely used to probe sensory function in the human brain, is a useful tool in linking studies of auditory processing in both humans and animals and has been successfully used to investigate auditory function in monkeys and rodents. The following protocol describes an experimental procedure for investigating auditory function in anesthetized adult cats by measuring stimulus-evoked hemodynamic changes in auditory cortex using fMRI. This method facilitates comparison of the hemodynamic responses across different models of auditory function thus leading to a better understanding of species-independent features of the mammalian auditory cortex.
Neuroscience, Issue 84, Central Nervous System, Ear, Animal Experimentation, Models, Animal, Functional Neuroimaging, Brain Mapping, Nervous System, Sense Organs, auditory cortex, BOLD signal change, hemodynamic response, hearing, acoustic stimuli
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Fabrication, Operation and Flow Visualization in Surface-acoustic-wave-driven Acoustic-counterflow Microfluidics
Authors: Marco Travagliati, Richie Shilton, Fabio Beltram, Marco Cecchini.
Institutions: Istituto Italiano di Tecnologia, Scuola Normale Superiore and Istituto Nanoscienze-CNR.
Surface acoustic waves (SAWs) can be used to drive liquids in portable microfluidic chips via the acoustic counterflow phenomenon. In this video we present the fabrication protocol for a multilayered SAW acoustic counterflow device. The device is fabricated starting from a lithium niobate (LN) substrate onto which two interdigital transducers (IDTs) and appropriate markers are patterned. A polydimethylsiloxane (PDMS) channel cast on an SU8 master mold is finally bonded on the patterned substrate. Following the fabrication procedure, we show the techniques that allow the characterization and operation of the acoustic counterflow device in order to pump fluids through the PDMS channel grid. We finally present the procedure to visualize liquid flow in the channels. The protocol is used to show on-chip fluid pumping under different flow regimes such as laminar flow and more complicated dynamics characterized by vortices and particle accumulation domains.
Physics, Issue 78, Microfluidics, Acoustics, Engineering, flow characteristics, flow measurement, flow visualization (general applications), fluidics, surface acoustic wave, flow visualization, acoustofluidics, MEMS, STICS, PIV, microfabrication, acoustics, particle dynamics, fluids, flow, imaging, visualization
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Activating Molecules, Ions, and Solid Particles with Acoustic Cavitation
Authors: Rachel Pflieger, Tony Chave, Matthieu Virot, Sergey I. Nikitenko.
Institutions: UMR 5257 CEA-CNRS-UM2-ENSCM.
The chemical and physical effects of ultrasound arise not from a direct interaction of molecules with sound waves, but rather from the acoustic cavitation: the nucleation, growth, and implosive collapse of microbubbles in liquids submitted to power ultrasound. The violent implosion of bubbles leads to the formation of chemically reactive species and to the emission of light, named sonoluminescence. In this manuscript, we describe the techniques allowing study of extreme intrabubble conditions and chemical reactivity of acoustic cavitation in solutions. The analysis of sonoluminescence spectra of water sparged with noble gases provides evidence for nonequilibrium plasma formation. The photons and the "hot" particles generated by cavitation bubbles enable to excite the non-volatile species in solutions increasing their chemical reactivity. For example the mechanism of ultrabright sonoluminescence of uranyl ions in acidic solutions varies with uranium concentration: sonophotoluminescence dominates in diluted solutions, and collisional excitation contributes at higher uranium concentration. Secondary sonochemical products may arise from chemically active species that are formed inside the bubble, but then diffuse into the liquid phase and react with solution precursors to form a variety of products. For instance, the sonochemical reduction of Pt(IV) in pure water provides an innovative synthetic route for monodispersed nanoparticles of metallic platinum without any templates or capping agents. Many studies reveal the advantages of ultrasound to activate the divided solids. In general, the mechanical effects of ultrasound strongly contribute in heterogeneous systems in addition to chemical effects. In particular, the sonolysis of PuO2 powder in pure water yields stable colloids of plutonium due to both effects.
Chemistry, Issue 86, Sonochemistry, sonoluminescence, ultrasound, cavitation, nanoparticles, actinides, colloids, nanocolloids
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Flying Insect Detection and Classification with Inexpensive Sensors
Authors: Yanping Chen, Adena Why, Gustavo Batista, Agenor Mafra-Neto, Eamonn Keogh.
Institutions: University of California, Riverside, University of California, Riverside, University of São Paulo - USP, ISCA Technologies.
An inexpensive, noninvasive system that could accurately classify flying insects would have important implications for entomological research, and allow for the development of many useful applications in vector and pest control for both medical and agricultural entomology. Given this, the last sixty years have seen many research efforts devoted to this task. To date, however, none of this research has had a lasting impact. In this work, we show that pseudo-acoustic optical sensors can produce superior data; that additional features, both intrinsic and extrinsic to the insect’s flight behavior, can be exploited to improve insect classification; that a Bayesian classification approach allows to efficiently learn classification models that are very robust to over-fitting, and a general classification framework allows to easily incorporate arbitrary number of features. We demonstrate the findings with large-scale experiments that dwarf all previous works combined, as measured by the number of insects and the number of species considered.
Bioengineering, Issue 92, flying insect detection, automatic insect classification, pseudo-acoustic optical sensors, Bayesian classification framework, flight sound, circadian rhythm
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Investigating the Neural Mechanisms of Aware and Unaware Fear Memory with fMRI
Authors: David C. Knight, Kimberly H. Wood.
Institutions: University of Alabama at Birmingham.
Pavlovian fear conditioning is often used in combination with functional magnetic resonance imaging (fMRI) in humans to investigate the neural substrates of associative learning 1-5. In these studies, it is important to provide behavioral evidence of conditioning to verify that differences in brain activity are learning-related and correlated with human behavior. Fear conditioning studies often monitor autonomic responses (e.g. skin conductance response; SCR) as an index of learning and memory 6-8. In addition, other behavioral measures can provide valuable information about the learning process and/or other cognitive functions that influence conditioning. For example, the impact unconditioned stimulus (UCS) expectancies have on the expression of the conditioned response (CR) and unconditioned response (UCR) has been a topic of interest in several recent studies 9-14. SCR and UCS expectancy measures have recently been used in conjunction with fMRI to investigate the neural substrates of aware and unaware fear learning and memory processes 15. Although these cognitive processes can be evaluated to some degree following the conditioning session, post-conditioning assessments cannot measure expectations on a trial-to-trial basis and are susceptible to interference and forgetting, as well as other factors that may distort results 16,17 . Monitoring autonomic and behavioral responses simultaneously with fMRI provides a mechanism by which the neural substrates that mediate complex relationships between cognitive processes and behavioral/autonomic responses can be assessed. However, monitoring autonomic and behavioral responses in the MRI environment poses a number of practical problems. Specifically, 1) standard behavioral and physiological monitoring equipment is constructed of ferrous material that cannot be safely used near the MRI scanner, 2) when this equipment is placed outside of the MRI scanning chamber, the cables projecting to the subject can carry RF noise that produces artifacts in brain images, 3) artifacts can be produced within the skin conductance signal by switching gradients during scanning, 4) the fMRI signal produced by the motor demands of behavioral responses may need to be distinguished from activity related to the cognitive processes of interest. Each of these issues can be resolved with modifications to the setup of physiological monitoring equipment and additional data analysis procedures. Here we present a methodology to simultaneously monitor autonomic and behavioral responses during fMRI, and demonstrate the use of these methods to investigate aware and unaware memory processes during fear conditioning.
Neuroscience, Issue 56, fMRI, conditioning, learning, memory, fear, contingency awareness, neuroscience, skin conductance
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Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Authors: Hans-Peter Müller, Jan Kassubek.
Institutions: University of Ulm.
Diffusion tensor imaging (DTI) techniques provide information on the microstructural processes of the cerebral white matter (WM) in vivo. The present applications are designed to investigate differences of WM involvement patterns in different brain diseases, especially neurodegenerative disorders, by use of different DTI analyses in comparison with matched controls. DTI data analysis is performed in a variate fashion, i.e. voxelwise comparison of regional diffusion direction-based metrics such as fractional anisotropy (FA), together with fiber tracking (FT) accompanied by tractwise fractional anisotropy statistics (TFAS) at the group level in order to identify differences in FA along WM structures, aiming at the definition of regional patterns of WM alterations at the group level. Transformation into a stereotaxic standard space is a prerequisite for group studies and requires thorough data processing to preserve directional inter-dependencies. The present applications show optimized technical approaches for this preservation of quantitative and directional information during spatial normalization in data analyses at the group level. On this basis, FT techniques can be applied to group averaged data in order to quantify metrics information as defined by FT. Additionally, application of DTI methods, i.e. differences in FA-maps after stereotaxic alignment, in a longitudinal analysis at an individual subject basis reveal information about the progression of neurological disorders. Further quality improvement of DTI based results can be obtained during preprocessing by application of a controlled elimination of gradient directions with high noise levels. In summary, DTI is used to define a distinct WM pathoanatomy of different brain diseases by the combination of whole brain-based and tract-based DTI analysis.
Medicine, Issue 77, Neuroscience, Neurobiology, Molecular Biology, Biomedical Engineering, Anatomy, Physiology, Neurodegenerative Diseases, nuclear magnetic resonance, NMR, MR, MRI, diffusion tensor imaging, fiber tracking, group level comparison, neurodegenerative diseases, brain, imaging, clinical techniques
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A Proboscis Extension Response Protocol for Investigating Behavioral Plasticity in Insects: Application to Basic, Biomedical, and Agricultural Research
Authors: Brian H. Smith, Christina M. Burden.
Institutions: Arizona State University.
Insects modify their responses to stimuli through experience of associating those stimuli with events important for survival (e.g., food, mates, threats). There are several behavioral mechanisms through which an insect learns salient associations and relates them to these events. It is important to understand this behavioral plasticity for programs aimed toward assisting insects that are beneficial for agriculture. This understanding can also be used for discovering solutions to biomedical and agricultural problems created by insects that act as disease vectors and pests. The Proboscis Extension Response (PER) conditioning protocol was developed for honey bees (Apis mellifera) over 50 years ago to study how they perceive and learn about floral odors, which signal the nectar and pollen resources a colony needs for survival. The PER procedure provides a robust and easy-to-employ framework for studying several different ecologically relevant mechanisms of behavioral plasticity. It is easily adaptable for use with several other insect species and other behavioral reflexes. These protocols can be readily employed in conjunction with various means for monitoring neural activity in the CNS via electrophysiology or bioimaging, or for manipulating targeted neuromodulatory pathways. It is a robust assay for rapidly detecting sub-lethal effects on behavior caused by environmental stressors, toxins or pesticides. We show how the PER protocol is straightforward to implement using two procedures. One is suitable as a laboratory exercise for students or for quick assays of the effect of an experimental treatment. The other provides more thorough control of variables, which is important for studies of behavioral conditioning. We show how several measures for the behavioral response ranging from binary yes/no to more continuous variable like latency and duration of proboscis extension can be used to test hypotheses. And, we discuss some pitfalls that researchers commonly encounter when they use the procedure for the first time.
Neuroscience, Issue 91, PER, conditioning, honey bee, olfaction, olfactory processing, learning, memory, toxin assay
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Training Synesthetic Letter-color Associations by Reading in Color
Authors: Olympia Colizoli, Jaap M. J. Murre, Romke Rouw.
Institutions: University of Amsterdam.
Synesthesia is a rare condition in which a stimulus from one modality automatically and consistently triggers unusual sensations in the same and/or other modalities. A relatively common and well-studied type is grapheme-color synesthesia, defined as the consistent experience of color when viewing, hearing and thinking about letters, words and numbers. We describe our method for investigating to what extent synesthetic associations between letters and colors can be learned by reading in color in nonsynesthetes. Reading in color is a special method for training associations in the sense that the associations are learned implicitly while the reader reads text as he or she normally would and it does not require explicit computer-directed training methods. In this protocol, participants are given specially prepared books to read in which four high-frequency letters are paired with four high-frequency colors. Participants receive unique sets of letter-color pairs based on their pre-existing preferences for colored letters. A modified Stroop task is administered before and after reading in order to test for learned letter-color associations and changes in brain activation. In addition to objective testing, a reading experience questionnaire is administered that is designed to probe for differences in subjective experience. A subset of questions may predict how well an individual learned the associations from reading in color. Importantly, we are not claiming that this method will cause each individual to develop grapheme-color synesthesia, only that it is possible for certain individuals to form letter-color associations by reading in color and these associations are similar in some aspects to those seen in developmental grapheme-color synesthetes. The method is quite flexible and can be used to investigate different aspects and outcomes of training synesthetic associations, including learning-induced changes in brain function and structure.
Behavior, Issue 84, synesthesia, training, learning, reading, vision, memory, cognition
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Cortical Source Analysis of High-Density EEG Recordings in Children
Authors: Joe Bathelt, Helen O'Reilly, Michelle de Haan.
Institutions: UCL Institute of Child Health, University College London.
EEG is traditionally described as a neuroimaging technique with high temporal and low spatial resolution. Recent advances in biophysical modelling and signal processing make it possible to exploit information from other imaging modalities like structural MRI that provide high spatial resolution to overcome this constraint1. This is especially useful for investigations that require high resolution in the temporal as well as spatial domain. In addition, due to the easy application and low cost of EEG recordings, EEG is often the method of choice when working with populations, such as young children, that do not tolerate functional MRI scans well. However, in order to investigate which neural substrates are involved, anatomical information from structural MRI is still needed. Most EEG analysis packages work with standard head models that are based on adult anatomy. The accuracy of these models when used for children is limited2, because the composition and spatial configuration of head tissues changes dramatically over development3.  In the present paper, we provide an overview of our recent work in utilizing head models based on individual structural MRI scans or age specific head models to reconstruct the cortical generators of high density EEG. This article describes how EEG recordings are acquired, processed, and analyzed with pediatric populations at the London Baby Lab, including laboratory setup, task design, EEG preprocessing, MRI processing, and EEG channel level and source analysis. 
Behavior, Issue 88, EEG, electroencephalogram, development, source analysis, pediatric, minimum-norm estimation, cognitive neuroscience, event-related potentials 
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Transcranial Magnetic Stimulation for Investigating Causal Brain-behavioral Relationships and their Time Course
Authors: Magdalena W. Sliwinska, Sylvia Vitello, Joseph T. Devlin.
Institutions: University College London.
Transcranial magnetic stimulation (TMS) is a safe, non-invasive brain stimulation technique that uses a strong electromagnet in order to temporarily disrupt information processing in a brain region, generating a short-lived “virtual lesion.” Stimulation that interferes with task performance indicates that the affected brain region is necessary to perform the task normally. In other words, unlike neuroimaging methods such as functional magnetic resonance imaging (fMRI) that indicate correlations between brain and behavior, TMS can be used to demonstrate causal brain-behavior relations. Furthermore, by varying the duration and onset of the virtual lesion, TMS can also reveal the time course of normal processing. As a result, TMS has become an important tool in cognitive neuroscience. Advantages of the technique over lesion-deficit studies include better spatial-temporal precision of the disruption effect, the ability to use participants as their own control subjects, and the accessibility of participants. Limitations include concurrent auditory and somatosensory stimulation that may influence task performance, limited access to structures more than a few centimeters from the surface of the scalp, and the relatively large space of free parameters that need to be optimized in order for the experiment to work. Experimental designs that give careful consideration to appropriate control conditions help to address these concerns. This article illustrates these issues with TMS results that investigate the spatial and temporal contributions of the left supramarginal gyrus (SMG) to reading.
Behavior, Issue 89, Transcranial magnetic stimulation, virtual lesion, chronometric, cognition, brain, behavior
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Creating Objects and Object Categories for Studying Perception and Perceptual Learning
Authors: Karin Hauffen, Eugene Bart, Mark Brady, Daniel Kersten, Jay Hegdé.
Institutions: Georgia Health Sciences University, Georgia Health Sciences University, Georgia Health Sciences University, Palo Alto Research Center, Palo Alto Research Center, University of Minnesota .
In order to quantitatively study object perception, be it perception by biological systems or by machines, one needs to create objects and object categories with precisely definable, preferably naturalistic, properties1. Furthermore, for studies on perceptual learning, it is useful to create novel objects and object categories (or object classes) with such properties2. Many innovative and useful methods currently exist for creating novel objects and object categories3-6 (also see refs. 7,8). However, generally speaking, the existing methods have three broad types of shortcomings. First, shape variations are generally imposed by the experimenter5,9,10, and may therefore be different from the variability in natural categories, and optimized for a particular recognition algorithm. It would be desirable to have the variations arise independently of the externally imposed constraints. Second, the existing methods have difficulty capturing the shape complexity of natural objects11-13. If the goal is to study natural object perception, it is desirable for objects and object categories to be naturalistic, so as to avoid possible confounds and special cases. Third, it is generally hard to quantitatively measure the available information in the stimuli created by conventional methods. It would be desirable to create objects and object categories where the available information can be precisely measured and, where necessary, systematically manipulated (or 'tuned'). This allows one to formulate the underlying object recognition tasks in quantitative terms. Here we describe a set of algorithms, or methods, that meet all three of the above criteria. Virtual morphogenesis (VM) creates novel, naturalistic virtual 3-D objects called 'digital embryos' by simulating the biological process of embryogenesis14. Virtual phylogenesis (VP) creates novel, naturalistic object categories by simulating the evolutionary process of natural selection9,12,13. Objects and object categories created by these simulations can be further manipulated by various morphing methods to generate systematic variations of shape characteristics15,16. The VP and morphing methods can also be applied, in principle, to novel virtual objects other than digital embryos, or to virtual versions of real-world objects9,13. Virtual objects created in this fashion can be rendered as visual images using a conventional graphical toolkit, with desired manipulations of surface texture, illumination, size, viewpoint and background. The virtual objects can also be 'printed' as haptic objects using a conventional 3-D prototyper. We also describe some implementations of these computational algorithms to help illustrate the potential utility of the algorithms. It is important to distinguish the algorithms from their implementations. The implementations are demonstrations offered solely as a 'proof of principle' of the underlying algorithms. It is important to note that, in general, an implementation of a computational algorithm often has limitations that the algorithm itself does not have. Together, these methods represent a set of powerful and flexible tools for studying object recognition and perceptual learning by biological and computational systems alike. With appropriate extensions, these methods may also prove useful in the study of morphogenesis and phylogenesis.
Neuroscience, Issue 69, machine learning, brain, classification, category learning, cross-modal perception, 3-D prototyping, inference
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Surface Renewal: An Advanced Micrometeorological Method for Measuring and Processing Field-Scale Energy Flux Density Data
Authors: Andrew J. McElrone, Thomas M. Shapland, Arturo Calderon, Li Fitzmaurice, Kyaw Tha Paw U, Richard L. Snyder.
Institutions: United States Department of Agriculture-Agricultural Research Service, University of California, Davis, University of Chile, University of California, Davis, URS Corporation Australia Pty. Ltd..
Advanced micrometeorological methods have become increasingly important in soil, crop, and environmental sciences. For many scientists without formal training in atmospheric science, these techniques are relatively inaccessible. Surface renewal and other flux measurement methods require an understanding of boundary layer meteorology and extensive training in instrumentation and multiple data management programs. To improve accessibility of these techniques, we describe the underlying theory of surface renewal measurements, demonstrate how to set up a field station for surface renewal with eddy covariance calibration, and utilize our open-source turnkey data logger program to perform flux data acquisition and processing. The new turnkey program returns to the user a simple data table with the corrected fluxes and quality control parameters, and eliminates the need for researchers to shuttle between multiple processing programs to obtain the final flux data. An example of data generated from these measurements demonstrates how crop water use is measured with this technique. The output information is useful to growers for making irrigation decisions in a variety of agricultural ecosystems. These stations are currently deployed in numerous field experiments by researchers in our group and the California Department of Water Resources in the following crops: rice, wine and raisin grape vineyards, alfalfa, almond, walnut, peach, lemon, avocado, and corn.
Environmental Sciences, Issue 82, Conservation of Natural Resources, Engineering, Agriculture, plants, energy balance, irrigated agriculture, flux data, evapotranspiration, agrometeorology
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Cross-Modal Multivariate Pattern Analysis
Authors: Kaspar Meyer, Jonas T. Kaplan.
Institutions: University of Southern California.
Multivariate pattern analysis (MVPA) is an increasingly popular method of analyzing functional magnetic resonance imaging (fMRI) data1-4. Typically, the method is used to identify a subject's perceptual experience from neural activity in certain regions of the brain. For instance, it has been employed to predict the orientation of visual gratings a subject perceives from activity in early visual cortices5 or, analogously, the content of speech from activity in early auditory cortices6. Here, we present an extension of the classical MVPA paradigm, according to which perceptual stimuli are not predicted within, but across sensory systems. Specifically, the method we describe addresses the question of whether stimuli that evoke memory associations in modalities other than the one through which they are presented induce content-specific activity patterns in the sensory cortices of those other modalities. For instance, seeing a muted video clip of a glass vase shattering on the ground automatically triggers in most observers an auditory image of the associated sound; is the experience of this image in the "mind's ear" correlated with a specific neural activity pattern in early auditory cortices? Furthermore, is this activity pattern distinct from the pattern that could be observed if the subject were, instead, watching a video clip of a howling dog? In two previous studies7,8, we were able to predict sound- and touch-implying video clips based on neural activity in early auditory and somatosensory cortices, respectively. Our results are in line with a neuroarchitectural framework proposed by Damasio9,10, according to which the experience of mental images that are based on memories - such as hearing the shattering sound of a vase in the "mind's ear" upon seeing the corresponding video clip - is supported by the re-construction of content-specific neural activity patterns in early sensory cortices.
Neuroscience, Issue 57, perception, sensory, cross-modal, top-down, mental imagery, fMRI, MRI, neuroimaging, multivariate pattern analysis, MVPA
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Basics of Multivariate Analysis in Neuroimaging Data
Authors: Christian Georg Habeck.
Institutions: Columbia University.
Multivariate analysis techniques for neuroimaging data have recently received increasing attention as they have many attractive features that cannot be easily realized by the more commonly used univariate, voxel-wise, techniques1,5,6,7,8,9. Multivariate approaches evaluate correlation/covariance of activation across brain regions, rather than proceeding on a voxel-by-voxel basis. Thus, their results can be more easily interpreted as a signature of neural networks. Univariate approaches, on the other hand, cannot directly address interregional correlation in the brain. Multivariate approaches can also result in greater statistical power when compared with univariate techniques, which are forced to employ very stringent corrections for voxel-wise multiple comparisons. Further, multivariate techniques also lend themselves much better to prospective application of results from the analysis of one dataset to entirely new datasets. Multivariate techniques are thus well placed to provide information about mean differences and correlations with behavior, similarly to univariate approaches, with potentially greater statistical power and better reproducibility checks. In contrast to these advantages is the high barrier of entry to the use of multivariate approaches, preventing more widespread application in the community. To the neuroscientist becoming familiar with multivariate analysis techniques, an initial survey of the field might present a bewildering variety of approaches that, although algorithmically similar, are presented with different emphases, typically by people with mathematics backgrounds. We believe that multivariate analysis techniques have sufficient potential to warrant better dissemination. Researchers should be able to employ them in an informed and accessible manner. The current article is an attempt at a didactic introduction of multivariate techniques for the novice. A conceptual introduction is followed with a very simple application to a diagnostic data set from the Alzheimer s Disease Neuroimaging Initiative (ADNI), clearly demonstrating the superior performance of the multivariate approach.
JoVE Neuroscience, Issue 41, fMRI, PET, multivariate analysis, cognitive neuroscience, clinical neuroscience
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A Low Cost Setup for Behavioral Audiometry in Rodents
Authors: Konstantin Tziridis, Sönke Ahlf, Holger Schulze.
Institutions: University of Erlangen-Nuremberg.
In auditory animal research it is crucial to have precise information about basic hearing parameters of the animal subjects that are involved in the experiments. Such parameters may be physiological response characteristics of the auditory pathway, e.g. via brainstem audiometry (BERA). But these methods allow only indirect and uncertain extrapolations about the auditory percept that corresponds to these physiological parameters. To assess the perceptual level of hearing, behavioral methods have to be used. A potential problem with the use of behavioral methods for the description of perception in animal models is the fact that most of these methods involve some kind of learning paradigm before the subjects can be behaviorally tested, e.g. animals may have to learn to press a lever in response to a sound. As these learning paradigms change perception itself 1,2 they consequently will influence any result about perception obtained with these methods and therefore have to be interpreted with caution. Exceptions are paradigms that make use of reflex responses, because here no learning paradigms have to be carried out prior to perceptual testing. One such reflex response is the acoustic startle response (ASR) that can highly reproducibly be elicited with unexpected loud sounds in naïve animals. This ASR in turn can be influenced by preceding sounds depending on the perceptibility of this preceding stimulus: Sounds well above hearing threshold will completely inhibit the amplitude of the ASR; sounds close to threshold will only slightly inhibit the ASR. This phenomenon is called pre-pulse inhibition (PPI) 3,4, and the amount of PPI on the ASR gradually depends on the perceptibility of the pre-pulse. PPI of the ASR is therefore well suited to determine behavioral audiograms in naïve, non-trained animals, to determine hearing impairments or even to detect possible subjective tinnitus percepts in these animals. In this paper we demonstrate the use of this method in a rodent model (cf. also ref. 5), the Mongolian gerbil (Meriones unguiculatus), which is a well know model species for startle response research within the normal human hearing range (e.g. 6).
Neuroscience, Issue 68, Physiology, Anatomy, Medicine, otolaryngology, behavior, auditory startle response, pre-pulse inhibition, audiogram, tinnitus, hearing loss
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