Societies of highly social animals feature vast lifespan differences between closely related individuals. Among social insects, the honey bee is the best established model to study how plasticity in lifespan and aging is explained by social factors.
The worker caste of honey bees includes nurse bees, which tend the brood, and forager bees, which collect nectar and pollen. Previous work has shown that brain functions and flight performance senesce more rapidly in foragers than in nurses. However, brain functions can recover, when foragers revert back to nursing tasks. Such patterns of accelerated and reversed functional senescence are linked to changed metabolic resource levels, to alterations in protein abundance and to immune function. Vitellogenin, a yolk protein with adapted functions in hormonal control and cellular defense, may serve as a major regulatory element in a network that controls the different aging dynamics in workers.
Here we describe how the emergence of nurses and foragers can be monitored, and manipulated, including the reversal from typically short-lived foragers into longer-lived nurses. Our representative results show how individuals with similar chronological age differentiate into foragers and nurse bees under experimental conditions. We exemplify how behavioral reversal from foragers back to nurses can be validated. Last, we show how different cellular senescence can be assessed by measuring the accumulation of lipofuscin, a universal biomarker of senescence.
For studying mechanisms that may link social influences and aging plasticity, this protocol provides a standardized tool set to acquire relevant sample material, and to improve data comparability among future studies.
22 Related JoVE Articles!
RNAi-mediated Double Gene Knockdown and Gustatory Perception Measurement in Honey Bees (Apis mellifera)
Institutions: Arizona State University , Norwegian University of Life Sciences.
This video demonstrates novel techniques of RNA interference (RNAi) which downregulate two genes simultaneously in honey bees using double-stranded RNA (dsRNA) injections. It also presents a protocol of proboscis extension response (PER) assay for measuring gustatory perception.
RNAi-mediated gene knockdown is an effective technique downregulating target gene expression. This technique is usually used for single gene manipulation, but it has limitations to detect interactions and joint effects between genes. In the first part of this video, we present two strategies to simultaneously knock down two genes (called double gene knockdown). We show both strategies are able to effectively suppress two genes, vitellogenin (vg
) and ultraspiracle (usp
), which are in a regulatory feedback loop. This double gene knockdown approach can be used to dissect interrelationships between genes and can be readily applied in different insect species.
The second part of this video is a demonstration of proboscis extension response (PER) assay in honey bees after the treatment of double gene knockdown. The PER assay is a standard test for measuring gustatory perception in honey bees, which is a key predictor for how fast a honey bee's behavioral maturation is. Greater gustatory perception of nest bees indicates increased behavioral development which is often associated with an earlier age at onset of foraging and foraging specialization in pollen. In addition, PER assay can be applied to identify metabolic states of satiation or hunger in honey bees. Finally, PER assay combined with pairing different odor stimuli for conditioning the bees is also widely used for learning and memory studies in honey bees.
Neuroscience, Issue 77, Genetics, Behavior, Neurobiology, Molecular Biology, Chemistry, Biochemistry, biology (general), genetics (animal and plant), animal biology, RNA interference, RNAi, double stranded RNA, dsRNA, double gene knockdown, vitellogenin gene, vg, ultraspiracle gene, usp, vitellogenin protein, Vg, ultraspiracle protein, USP, green fluorescence protein, GFP, gustatory perception, proboscis extension response, PER, honey bees, Apis mellifera, animal model, assay
Tactile Conditioning And Movement Analysis Of Antennal Sampling Strategies In Honey Bees (Apis mellifera L.)
Institutions: Bielefeld University.
Honey bees (Apis mellifera
L.) are eusocial insects and well known for their complex division of labor and associative learning capability1, 2
. The worker bees spend the first half of their life inside the dark hive, where they are nursing the larvae or building the regular hexagonal combs for food (e.g.
pollen or nectar) and brood3
. The antennae are extraordinary multisensory feelers and play a pivotal role in various tactile mediated tasks4
, including hive building5
and pattern recognition6
. Later in life, each single bee leaves the hive to forage for food. Then a bee has to learn to discriminate profitable food sources, memorize their location, and communicate it to its nest mates7
. Bees use different floral signals like colors or odors7, 8
, but also tactile cues from the petal surface9
to form multisensory memories of the food source. Under laboratory conditions, bees can be trained in an appetitive learning paradigm to discriminate tactile object features, such as edges or grooves with their antennae10, 11, 12, 13
. This learning paradigm is closely related to the classical olfactory conditioning of the proboscis extension response (PER) in harnessed bees14
. The advantage of the tactile learning paradigm in the laboratory is the possibility of combining behavioral experiments on learning with various physiological measurements, including the analysis of the antennal movement pattern.
Neuroscience, Issue 70, Physiology, Anatomy, Entomology, Behavior, Sensilla, Bees, behavioral sciences, Sense Organs, Honey bee, Apis mellifera L., Insect antenna, Tactile sampling, conditioning, Proboscis extension response, Motion capture
Using a Comparative Species Approach to Investigate the Neurobiology of Paternal Responses
Institutions: Randolph-Macon College, Marshall University.
A goal of behavioral neuroscience is to identify underlying neurobiological factors that regulate specific behaviors. Using animal models to accomplish this goal, many methodological strategies require invasive techniques to manipulate the intensity of the behavior of interest (e.g., lesion methods, pharmacological manipulations, microdialysis techniques, genetically-engineered animal models). The utilization of a comparative species approach allows researchers to take advantage of naturally occurring differences in response strategies existing in closely related species. In our lab, we use two species of the Peromyscus
genus that differ in paternal responses. The male California deer mouse (Peromyscus californicus
) exhibits the same parental responses as the female whereas its cousin, the common deer mouse (Peromyscus maniculatus
) exhibits virtually no nurturing/parental responses in the presence of pups. Of specific interest in this article is an exploration of the neurobiological factors associated with the affiliative social responses exhibited by the paternal California deer mouse. Because the behavioral neuroscience approach is multifaceted, the following key components of the study will be briefly addressed: the identification of appropriate species for this type of research; data collection for behavioral analysis; preparation and sectioning of the brains; basic steps involved in immunocytochemistry for the quantification of vasopressin-immunoreactivity; the use of neuroimaging software to quantify the brain tissue; the use of a microsequencing video analysis to score behavior and, finally, the appropriate statistical analyses to provide the most informed interpretations of the research findings.
Neuroscience, Issue 55, Peromyscus, mouse, paternal behavior, vasopressin, immunocytochemistry, microsequencing behavioral analysis
From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
Institutions: Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory.
Modern 3D electron microscopy approaches have recently allowed unprecedented insight into the 3D ultrastructural organization of cells and tissues, enabling the visualization of large macromolecular machines, such as adhesion complexes, as well as higher-order structures, such as the cytoskeleton and cellular organelles in their respective cell and tissue context. Given the inherent complexity of cellular volumes, it is essential to first extract the features of interest in order to allow visualization, quantification, and therefore comprehension of their 3D organization. Each data set is defined by distinct characteristics, e.g.
, signal-to-noise ratio, crispness (sharpness) of the data, heterogeneity of its features, crowdedness of features, presence or absence of characteristic shapes that allow for easy identification, and the percentage of the entire volume that a specific region of interest occupies. All these characteristics need to be considered when deciding on which approach to take for segmentation.
The six different 3D ultrastructural data sets presented were obtained by three different imaging approaches: resin embedded stained electron tomography, focused ion beam- and serial block face- scanning electron microscopy (FIB-SEM, SBF-SEM) of mildly stained and heavily stained samples, respectively. For these data sets, four different segmentation approaches have been applied: (1) fully manual model building followed solely by visualization of the model, (2) manual tracing segmentation of the data followed by surface rendering, (3) semi-automated approaches followed by surface rendering, or (4) automated custom-designed segmentation algorithms followed by surface rendering and quantitative analysis. Depending on the combination of data set characteristics, it was found that typically one of these four categorical approaches outperforms the others, but depending on the exact sequence of criteria, more than one approach may be successful. Based on these data, we propose a triage scheme that categorizes both objective data set characteristics and subjective personal criteria for the analysis of the different data sets.
Bioengineering, Issue 90, 3D electron microscopy, feature extraction, segmentation, image analysis, reconstruction, manual tracing, thresholding
Radio Frequency Identification and Motion-sensitive Video Efficiently Automate Recording of Unrewarded Choice Behavior by Bumblebees
Institutions: University of Ottawa.
We present two methods for observing bumblebee choice behavior in an enclosed testing space. The first method consists of Radio Frequency Identification (RFID) readers built into artificial flowers that display various visual cues, and RFID tags (i.e.
, passive transponders) glued to the thorax of bumblebee workers. The novelty in our implementation is that RFID readers are built directly into artificial flowers that are capable of displaying several distinct visual properties such as color, pattern type, spatial frequency (i.e.
, “busyness” of the pattern), and symmetry (spatial frequency and symmetry were not manipulated in this experiment). Additionally, these visual displays in conjunction with the automated systems are capable of recording unrewarded
choice behavior. The second method consists of recording choice behavior at artificial flowers using motion-sensitive high-definition camcorders. Bumblebees have number tags glued to their thoraces for unique identification. The advantage in this implementation over RFID is that in addition to observing landing behavior, alternate measures of preference such as hovering and antennation may also be observed. Both automation methods increase experimental control, and internal validity by allowing larger scale studies that take into account individual differences. External validity is also improved because bees can freely enter and exit the testing environment without constraints such as the availability of a research assistant on-site. Compared to human observation in real time, the automated methods are more cost-effective and possibly less error-prone.
Neuroscience, Issue 93, bumblebee, unlearned behaviors, floral choice, visual perception, Bombus spp, information processing, radio-frequency identification, motion-sensitive video
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
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
Combining Magnetic Sorting of Mother Cells and Fluctuation Tests to Analyze Genome Instability During Mitotic Cell Aging in Saccharomyces cerevisiae
Institutions: Rensselaer Polytechnic Institute.
has been an excellent model system for examining mechanisms and consequences of genome instability. Information gained from this yeast model is relevant to many organisms, including humans, since DNA repair and DNA damage response factors are well conserved across diverse species. However, S. cerevisiae
has not yet been used to fully address whether the rate of accumulating mutations changes with increasing replicative (mitotic) age due to technical constraints. For instance, measurements of yeast replicative lifespan through micromanipulation involve very small populations of cells, which prohibit detection of rare mutations. Genetic methods to enrich for mother cells in populations by inducing death of daughter cells have been developed, but population sizes are still limited by the frequency with which random mutations that compromise the selection systems occur. The current protocol takes advantage of magnetic sorting of surface-labeled yeast mother cells to obtain large enough populations of aging mother cells to quantify rare mutations through phenotypic selections. Mutation rates, measured through fluctuation tests, and mutation frequencies are first established for young cells and used to predict the frequency of mutations in mother cells of various replicative ages. Mutation frequencies are then determined for sorted mother cells, and the age of the mother cells is determined using flow cytometry by staining with a fluorescent reagent that detects bud scars formed on their cell surfaces during cell division. Comparison of predicted mutation frequencies based on the number of cell divisions to the frequencies experimentally observed for mother cells of a given replicative age can then identify whether there are age-related changes in the rate of accumulating mutations. Variations of this basic protocol provide the means to investigate the influence of alterations in specific gene functions or specific environmental conditions on mutation accumulation to address mechanisms underlying genome instability during replicative aging.
Microbiology, Issue 92, Aging, mutations, genome instability, Saccharomyces cerevisiae, fluctuation test, magnetic sorting, mother cell, replicative aging
A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
Institutions: University of Western Ontario.
The ability to adjust behavior to sudden changes in the environment develops gradually in childhood and adolescence. For example, in the Dimensional Change Card Sort task, participants switch from sorting cards one way, such as shape, to sorting them a different way, such as color. Adjusting behavior in this way exacts a small performance cost, or switch cost, such that responses are typically slower and more error-prone on switch trials in which the sorting rule changes as compared to repeat trials in which the sorting rule remains the same. The ability to flexibly adjust behavior is often said to develop gradually, in part because behavioral costs such as switch costs typically decrease with increasing age. Why aspects of higher-order cognition, such as behavioral flexibility, develop so gradually remains an open question. One hypothesis is that these changes occur in association with functional changes in broad-scale cognitive control networks. On this view, complex mental operations, such as switching, involve rapid interactions between several distributed brain regions, including those that update and maintain task rules, re-orient attention, and select behaviors. With development, functional connections between these regions strengthen, leading to faster and more efficient switching operations. The current video describes a method of testing this hypothesis through the collection and multivariate analysis of fMRI data from participants of different ages.
Behavior, Issue 87, Neurosciences, fMRI, Cognitive Control, Development, Functional Connectivity
Experimental Manipulation of Body Size to Estimate Morphological Scaling Relationships in Drosophila
Institutions: University of Houston, Michigan State University.
The scaling of body parts is a central feature of animal morphology1-7
. Within species, morphological traits need to be correctly proportioned to the body for the organism to function; larger individuals typically have larger body parts and smaller individuals generally have smaller body parts, such that overall body shape is maintained across a range of adult body sizes. The requirement for correct proportions means that individuals within species usually exhibit low variation in relative trait size. In contrast, relative trait size can vary dramatically among species and is a primary mechanism by which morphological diversity is produced. Over a century of comparative work has established these intra- and interspecific patterns3,4
Perhaps the most widely used approach to describe this variation is to calculate the scaling relationship between the size of two morphological traits using the allometric equation y=bxα, where x and y are the size of the two traits, such as organ and body size8,9
. This equation describes the within-group (e.g., species, population) scaling relationship between two traits as both vary in size. Log-transformation of this equation produces a simple linear equation, log(y) = log(b) + αlog(x) and log-log plots of the size of different traits among individuals of the same species typically reveal linear scaling with an intercept of log(b) and a slope of α, called the 'allometric coefficient'9,10
. Morphological variation among groups is described by differences in scaling relationship intercepts or slopes for a given trait pair. Consequently, variation in the parameters of the allometric equation (b and α) elegantly describes the shape variation captured in the relationship between organ and body size within and among biological groups (see 11,12
Not all traits scale linearly with each other or with body size (e.g., 13,14
) Hence, morphological scaling relationships are most informative when the data are taken from the full range of trait sizes. Here we describe how simple experimental manipulation of diet can be used to produce the full range of body size in insects. This permits an estimation of the full scaling relationship for any given pair of traits, allowing a complete description of how shape covaries with size and a robust comparison of scaling relationship parameters among biological groups. Although we focus on Drosophila
, our methodology should be applicable to nearly any fully metamorphic insect.
Developmental Biology, Issue 56, Drosophila, allometry, morphology, body size, scaling, insect
Appetitive Associative Olfactory Learning in Drosophila Larvae
Institutions: University of Konstanz, University of Fribourg.
In the following we describe the methodological details of appetitive associative olfactory learning in Drosophila
larvae. The setup, in combination with genetic interference, provides a handle to analyze the neuronal and molecular fundamentals of specifically associative
learning in a simple larval brain.
Organisms can use past experience to adjust present behavior. Such acquisition of behavioral potential can be defined as learning, and the physical bases of these potentials as memory traces1-4
. Neuroscientists try to understand how these processes are organized in terms of molecular and neuronal changes in the brain by using a variety of methods in model organisms ranging from insects to vertebrates5,6
. For such endeavors it is helpful to use model systems that are simple and experimentally accessible. The Drosophila
larva has turned out to satisfy these demands based on the availability of robust behavioral assays, the existence of a variety of transgenic techniques and the elementary organization of the nervous system comprising only about 10,000 neurons (albeit with some concessions: cognitive limitations, few behavioral options, and richness of experience questionable)7-10
larvae can form associations between odors and appetitive gustatory reinforcement like sugar11-14
. In a standard assay, established in the lab of B. Gerber, animals receive a two-odor reciprocal training: A first group of larvae is exposed to an odor A together with a gustatory reinforcer (sugar reward) and is subsequently exposed to an odor B without reinforcement 9
. Meanwhile a second group of larvae receives reciprocal training while experiencing odor A without reinforcement and subsequently being exposed to odor B with reinforcement (sugar reward). In the following both groups are tested for their preference between the two odors. Relatively higher preferences for the rewarded odor reflect associative learning - presented as a performance index (PI). The conclusion regarding the associative nature of the performance index is compelling, because apart from the contingency between odors and tastants, other parameters, such as odor and reward exposure, passage of time and handling do not differ between the two groups9
Neuroscience, Issue 72, Developmental Biology, Neurobiology, Biochemistry, Molecular Biology, Physiology, Behavior, Drosophila, fruit fly, larvae, instar, olfaction, olfactory system, odor, 1-octanol, OCT, learning, reward, sugar, feeding, animal model
Simultaneous Long-term Recordings at Two Neuronal Processing Stages in Behaving Honeybees
Institutions: University of Würzburg.
In both mammals and insects neuronal information is processed in different higher and lower order brain centers. These centers are coupled via convergent and divergent anatomical connections including feed forward and feedback wiring. Furthermore, information of the same origin is partially sent via parallel pathways to different and sometimes into the same brain areas. To understand the evolutionary benefits as well as the computational advantages of these wiring strategies and especially their temporal dependencies on each other, it is necessary to have simultaneous access to single neurons of different tracts or neuropiles in the same preparation at high temporal resolution. Here we concentrate on honeybees by demonstrating a unique extracellular long term access to record multi unit activity at two subsequent neuropiles1
, the antennal lobe (AL), the first olfactory processing stage and the mushroom body (MB), a higher order integration center involved in learning and memory formation, or two parallel neuronal tracts2
connecting the AL with the MB. The latter was chosen as an example and will be described in full. In the supporting video the construction and permanent insertion of flexible multi channel wire electrodes is demonstrated. Pairwise differential amplification of the micro wire electrode channels drastically reduces the noise and verifies that the source of the signal is closely related to the position of the electrode tip. The mechanical flexibility of the used wire electrodes allows stable invasive long term recordings over many hours up to days, which is a clear advantage compared to conventional extra and intracellular in vivo
Neuroscience, Issue 89, honeybee brain, olfaction, extracellular long term recordings, double recordings, differential wire electrodes, single unit, multi-unit recordings
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
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
Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
Institutions: Rutgers University, Koç University, New York University, Fairfield University.
We describe a high-throughput, high-volume, fully automated, live-in 24/7 behavioral testing system for assessing the effects of genetic and pharmacological manipulations on basic mechanisms of cognition and learning in mice. A standard polypropylene mouse housing tub is connected through an acrylic tube to a standard commercial mouse test box. The test box has 3 hoppers, 2 of which are connected to pellet feeders. All are internally illuminable with an LED and monitored for head entries by infrared (IR) beams. Mice live in the environment, which eliminates handling during screening. They obtain their food during two or more daily feeding periods by performing in operant (instrumental) and Pavlovian (classical) protocols, for which we have written protocol-control software and quasi-real-time data analysis and graphing software. The data analysis and graphing routines are written in a MATLAB-based language created to simplify greatly the analysis of large time-stamped behavioral and physiological event records and to preserve a full data trail from raw data through all intermediate analyses to the published graphs and statistics within a single data structure. The data-analysis code harvests the data several times a day and subjects it to statistical and graphical analyses, which are automatically stored in the "cloud" and on in-lab computers. Thus, the progress of individual mice is visualized and quantified daily. The data-analysis code talks to the protocol-control code, permitting the automated advance from protocol to protocol of individual subjects. The behavioral protocols implemented are matching, autoshaping, timed hopper-switching, risk assessment in timed hopper-switching, impulsivity measurement, and the circadian anticipation of food availability. Open-source protocol-control and data-analysis code makes the addition of new protocols simple. Eight test environments fit in a 48 in x 24 in x 78 in cabinet; two such cabinets (16 environments) may be controlled by one computer.
Behavior, Issue 84, genetics, cognitive mechanisms, behavioral screening, learning, memory, timing
A Proboscis Extension Response Protocol for Investigating Behavioral Plasticity in Insects: Application to Basic, Biomedical, and Agricultural Research
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
Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
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
) (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
Membrane Potentials, Synaptic Responses, Neuronal Circuitry, Neuromodulation and Muscle Histology Using the Crayfish: Student Laboratory Exercises
Institutions: University of Kentucky, University of Toronto.
The purpose of this report is to help develop an understanding of the effects caused by ion gradients across a biological membrane. Two aspects that influence a cell's membrane potential and which we address in these experiments are: (1) Ion concentration of K+
on the outside of the membrane, and (2) the permeability of the membrane to specific ions. The crayfish abdominal extensor muscles are in groupings with some being tonic (slow) and others phasic (fast) in their biochemical and physiological phenotypes, as well as in their structure; the motor neurons that innervate these muscles are correspondingly different in functional characteristics. We use these muscles as well as the superficial, tonic abdominal flexor muscle to demonstrate properties in synaptic transmission. In addition, we introduce a sensory-CNS-motor neuron-muscle circuit to demonstrate the effect of cuticular sensory stimulation as well as the influence of neuromodulators on certain aspects of the circuit. With the techniques obtained in this exercise, one can begin to answer many questions remaining in other experimental preparations as well as in physiological applications related to medicine and health. We have demonstrated the usefulness of model invertebrate preparations to address fundamental questions pertinent to all animals.
Neuroscience, Issue 47, Invertebrate, Crayfish, neurophysiology, muscle, anatomy, electrophysiology
Barnes Maze Testing Strategies with Small and Large Rodent Models
Institutions: University of Missouri, Food and Drug Administration.
Spatial learning and memory of laboratory rodents is often assessed via navigational ability in mazes, most popular of which are the water and dry-land (Barnes) mazes. Improved performance over sessions or trials is thought to reflect learning and memory of the escape cage/platform location. Considered less stressful than water mazes, the Barnes maze is a relatively simple design of a circular platform top with several holes equally spaced around the perimeter edge. All but one of the holes are false-bottomed or blind-ending, while one leads to an escape cage. Mildly aversive stimuli (e.g.
bright overhead lights) provide motivation to locate the escape cage. Latency to locate the escape cage can be measured during the session; however, additional endpoints typically require video recording. From those video recordings, use of automated tracking software can generate a variety of endpoints that are similar to those produced in water mazes (e.g.
distance traveled, velocity/speed, time spent in the correct quadrant, time spent moving/resting, and confirmation of latency). Type of search strategy (i.e.
random, serial, or direct) can be categorized as well. Barnes maze construction and testing methodologies can differ for small rodents, such as mice, and large rodents, such as rats. For example, while extra-maze cues are effective for rats, smaller wild rodents may require intra-maze cues with a visual barrier around the maze. Appropriate stimuli must be identified which motivate the rodent to locate the escape cage. Both Barnes and water mazes can be time consuming as 4-7 test trials are typically required to detect improved learning and memory performance (e.g.
shorter latencies or path lengths to locate the escape platform or cage) and/or differences between experimental groups. Even so, the Barnes maze is a widely employed behavioral assessment measuring spatial navigational abilities and their potential disruption by genetic, neurobehavioral manipulations, or drug/ toxicant exposure.
Behavior, Issue 84, spatial navigation, rats, Peromyscus, mice, intra- and extra-maze cues, learning, memory, latency, search strategy, escape motivation
Cortical Source Analysis of High-Density EEG Recordings in Children
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
Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging
Institutions: University of Alabama at Birmingham.
Newly emerging theories suggest that the brain does not function as a cohesive unit in autism, and this discordance is reflected in the behavioral symptoms displayed by individuals with autism. While structural neuroimaging findings have provided some insights into brain abnormalities in autism, the consistency of such findings is questionable. Functional neuroimaging, on the other hand, has been more fruitful in this regard because autism is a disorder of dynamic processing and allows examination of communication between cortical networks, which appears to be where the underlying problem occurs in autism. Functional connectivity is defined as the temporal correlation of spatially separate neurological events1. Findings from a number of recent fMRI studies have supported the idea that there is weaker coordination between different parts of the brain that should be working together to accomplish complex social or language problems2,3,4,5,6
. One of the mysteries of autism is the coexistence of deficits in several domains along with relatively intact, sometimes enhanced, abilities. Such complex manifestation of autism calls for a global and comprehensive examination of the disorder at the neural level. A compelling recent account of the brain functioning in autism, the cortical underconnectivity theory,2,7
provides an integrating framework for the neurobiological bases of autism. The cortical underconnectivity theory of autism suggests that any language, social, or psychological function that is dependent on the integration of multiple brain regions is susceptible to disruption as the processing demand increases. In autism, the underfunctioning of integrative circuitry in the brain may cause widespread underconnectivity. In other words, people with autism may interpret information in a piecemeal fashion at the expense of the whole. Since cortical underconnectivity among brain regions, especially the frontal cortex and more posterior areas 3,6
, has now been relatively well established, we can begin to further understand brain connectivity as a critical component of autism symptomatology.
A logical next step in this direction is to examine the anatomical connections that may mediate the functional connections mentioned above. Diffusion Tensor Imaging (DTI) is a relatively novel neuroimaging technique that helps probe the diffusion of water in the brain to infer the integrity of white matter fibers. In this technique, water diffusion in the brain is examined in several directions using diffusion gradients. While functional connectivity provides information about the synchronization of brain activation across different brain areas during a task or during rest, DTI helps in understanding the underlying axonal organization which may facilitate the cross-talk among brain areas. This paper will describe these techniques as valuable tools in understanding the brain in autism and the challenges involved in this line of research.
Medicine, Issue 55, Functional magnetic resonance imaging (fMRI), MRI, Diffusion tensor imaging (DTI), Functional Connectivity, Neuroscience, Developmental disorders, Autism, Fractional Anisotropy
Brain Imaging Investigation of the Memory-Enhancing Effect of Emotion
Institutions: University of Alberta, University of Illinois, Urbana-Champaign, Duke University, University of Illinois, Urbana-Champaign.
Emotional events tend to be better remembered than non-emotional events1,2
. One goal of cognitive and affective neuroscientists is
to understand the neural mechanisms underlying this enhancing effect of emotion on memory. A method that has proven particularly influential in the
investigation of the memory-enhancing effect of emotion is the so-called subsequent memory paradigm (SMP). This method was originally used to investigate the
neural correlates of non-emotional memories3
, and more recently we and others also applied it successfully to studies of emotional memory (reviewed in4, 5-7
Here, we describe a protocol that allows investigation of the neural correlates of the memory-enhancing effect of emotion using the SMP in conjunction with
event-related functional magnetic resonance imaging (fMRI). An important feature of the SMP is that it allows separation of brain activity specifically
associated with memory from more general activity associated with perception. Moreover, in the context of investigating the impact of emotional stimuli,
SMP allows identification of brain regions whose activity is susceptible to emotional modulation of both general/perceptual and memory-specific processing.
This protocol can be used in healthy subjects8-15
, as well as in clinical patients where there are alterations in the neural correlates of emotion perception
and biases in remembering emotional events, such as those suffering from depression and post-traumatic stress disorder (PTSD)16, 17
Neuroscience, Issue 51, Affect, Recognition, Recollection, Dm Effect, Neuroimaging
Morris Water Maze Experiment
Institutions: Michigan State University (MSU).
The Morris water maze is widely used to study spatial memory and learning. Animals are placed in a pool of water that is colored opaque with powdered non-fat milk or non-toxic tempera paint, where they must swim to a hidden escape platform. Because they are in opaque water, the animals cannot see the platform, and cannot rely on scent to find the escape route. Instead, they must rely on external/extra-maze cues. As the animals become more familiar with the task, they are able to find the platform more quickly. Developed by Richard G. Morris in 1984, this paradigm has become one of the "gold standards" of behavioral neuroscience.
Behavior, Issue 19, Declarative, Hippocampus, Memory, Procedural, Rodent, Spatial Learning
The Resident-intruder Paradigm: A Standardized Test for Aggression, Violence and Social Stress
Institutions: University Groningen, Radboud University Nijmegen.
This video publication explains in detail the experimental protocol of the resident-intruder paradigm in rats. This test is a standardized method to measure offensive aggression and defensive behavior in a semi natural setting. The most important behavioral elements performed by the resident and the intruder are demonstrated in the video and illustrated using artistic drawings. The use of the resident intruder paradigm for acute and chronic social stress experiments is explained as well. Finally, some brief tests and criteria are presented to distinguish aggression from its more violent and pathological forms.
Behavior, Issue 77, Neuroscience, Medicine, Anatomy, Physiology, Genetics, Basic Protocols, Psychology, offensive aggression, defensive behavior, aggressive behavior, pathological, violence, social stress, rat, Wistar rat, animal model