Wood ants are a model system for studying visuallearning and navigation. They can forage for food and navigate to their nests effectively by forming memories of visual features in their surrounding environment. Previous studies of freely behaving ants have revealed many of the behavioural strategies and environmental features necessary for successful navigation. However, little is known about the exact visual properties of the environment that animals learn or the neural mechanisms that allow them to achieve this. As a first step towards addressing this, we developed a classical conditioning paradigm for visuallearning in harnessed wood ants that allows us to control precisely the learned visual cues. In this paradigm, ants are fixed and presented with a visual cue paired with an appetitive sugar reward. Using this paradigm, we found that visual cues learnt by wood ants through Pavlovian conditioning are retained for at least 1 h. Furthermore, we found that memory retention is dependent upon the ants ’ performance during training. Our study provides the first evidence that wood ants can form visual associative memories when restrained. This classical conditioning paradigm has the potential to permit detailed analysis of the dynamics of memory formation and retention, and the neural basis of learning in wood ants.
On the whole, the human studies provided convergent evidence regarding the role of the forebrain commissures in interhemispheric communication. However, in some isolated split- brain animal experiments, researches reported that animals learned the task with the untrained hemisphere faster than one would expect from the initial learning level of the originally trained hemisphere (see Hamilton, 1982, for review). How? The most plausible answer is that this occurred through certain sub-cortical structures which normally provide integration for direct or crossed connections to the left and right hemispheres. These sub-cortical relay stations could conceivably have allowed some minimal memory in the trained hemisphere to be tapped by the untrained hemisphere. Yet, they did not provide a perfect substitute for the forebrain
Zeki, 2000) and that V4 itself is retinotopically mapped, containing complete representations of the two quadrants of the contra-lateral hemifields (McKeetfy and Zeki, 1997; Wade et al, 2002). Other early PET studies (Gulyas et al, 1994b) came to a different conclusion. Their studies found that many areas throughout the brain were involved in colour discrimination. But these studies were poorly controlled for task and for attention, and a re-analysis o f this data using more standard statistical techniques (Frackowiak et al, 1996), found activations for colour stimuli versus black and white stimuli in the lingual gyrus at the location of V4 and were in agreement with the Lueck et al (1989) study. Recently however, some authors have revived the view that colour is processed by a distributed system (Gegenfurtner, 2003, see below). Further discussion over whether V4 was the site of colour processing in the human was triggered by the study of Hadjikhani et al (1998) claiming to have found a new colour centre, V8. The main claim of this study was based on the interpretation of retinotopic maps. Their interpretation was that human V4 is split into dorsal and ventral sub divisions as in the monkey. They proceeded to describe area ‘V4v’, which has only a quarter-field representation o f the visual scene, although no evidence was found (or has ever been found) for the existence of a dorsal V4. They then claimed that there exists a full hemifield representation beyond V4v that was colour sensitive, they named this ‘new’ area V8. More careful analysis of their retinotopy and a subsequent study (Wade et al, 2002) has revealed that V4 has a full hemifield representation that lies in exactly the same location as V8. This discovery is inconsistent with the idea of V4v indicating that V4v (and by implication, V4d) is an ‘improbable area’ (Zeki, 2003b). The true explanation of these findings is that the colour sensitivity measured by Hadjikhani et al was, in fact, that of V4.
dynamic visuo-motor synchronization between patient gaze and its target during visual tracking using EYE-TRAC, a device which quantifies the time taken to predict the location of the target. In mild TBI, scores were worse than in 95% of controls while in acute TBI, initially abnormal scores were followed by an improvement. In further studies of target location prediction during pursuits, TBI patients exhibited poorer prediction and position errors were increased, performance being correlated with the ‘California verbal learning task (CVLT-II)’, a widely used test of episodic verbal learning and memory, suggesting pursuit eye movement as a sensitive method of testing cognitive functioning. 91 Visual tracking may also be directly related to
provide feedback that may improve the efficiency of the algorithm or correct the direction of the model building process. Although the visualization platform we develop can be used to support understanding and knowledge input functions, we focus specifically in this paper on data reduction. In our approach, the interactive system will allow the user to identify potential areas (in some visual space) where additional data is needed to improve or correct the model (as shown in Figure 1.1). This way, only the necessary amount of data is used for learning a model. The aim is to solve a big data problem using a small data solution. In practice, this approach can not only save costs for data acquisitions / collections in applications such as clinical trials, medical analyses, and environmental studies, but also improve the efficiency and robustness of machine learning algorithms as the current somewhat brute-force approach (e.g. in deep learning) may not be necessary with smaller and higher quality data. To achieve this goal, we will need to overcome the following two challenges:
You can try this test yourself. Put your hands behind your back. Then have someone place familiar objects (a spoon, a pen, a book, a watch) in either your right or your left hand and see if you can identify the object. You would not find this task to be very difficult, would you? This is basically what Sperry and Gazzaniga did with the split-brain patients. When an object was placed in the right hand in such a way that the patient could not see or hear it, messages about the object would travel to the left hemisphere and the patient was able to name the object and describe it and its uses. However, when the same objects were placed in the left hand (connected to the right hemisphere), the patients could not name them or describe them in any way. But did the patients know what the object was? In order for the researchers to find out, they asked the subjects to match the object in their left hand (without seeing it, remember) to a group of various objects presented to them. This they could do as easily as you or I. Again, this places verbal ability in the left hemisphere of the brain. Keep in mind that the reason you are able to name unseen objects in your left hand is that the information from the right side of your brain is transmitted via the corpus callosum to the left side, where your center for language says "that's a spoon!"
Brain-compatible learning approach does not provide a ready-made solution for all educational problems but it can help the students in achieving heights is academic pursuits. Results can be further improved when students are made to perform with sufficiently high level of aspiration. So, the role of teacher in arranging the environment and setting the stage is more important here. Brain-compatible approach maximizes learning, it limits the stress of children’s ability to learn, it establishes immediate connection to the real world which will increase learning and it encourages active processing needed to keep connection and foster memory (Konecki, et al.2003). So if it is followed by all the teachers in the schools it can solve most of achievement related problems of the students. In order to have successful implementation it can be made a part of curriculum of teacher education programmes.
A variety of freely available possibilities can be lo- cated on the web. They seem to fall in two categories: either multiple choice formats of stand-alone applica- tions or they are connected to courses (in some cases text books) and home pages of individual teachers. A good example of the former is the internet-grammar website offered by University College London (http:// www.ucl.uk/internet-grammar). The site is thorough with a pleasing lay-out, easy to use, and it gives feed- back. The drawback is that it cannot be customised, and the feedback is a standard text, which is the same irrespective of your correctness level, or the type of errors you make. The learning outcome would depend on the dedication and analytic abilities of the individual user. From an overall point of view, it is a ‘drill-and- kill’ type of tool, and although it does accept student input in the form of ticking off one of two choice possibilities, its feedback makes it resemble a digital textbook.
Production of Plasmodium knowlesi infected mosquitoes All mosquitoes were infected with P. knowlesi malaria 4-6 days after adults emerged from pupae. Prior to infec- tion, mosquitoes were fed 10% sucrose at WRAIR/NMRC, or 10% sucrose or 10% Karo brand syrup at NIH. Previ- ously splenectomized monkeys were infected by iv injec- tion of cryopreserved red blood cells infected with P. knowlesi. Splenectomy allows repeated infections with P. knowlesi without the animals developing immunity. In the authors’ experience, splenectomy does not affect gametocyte numbers or infectivity to mosquitoes. Feeding of mosquitoes on P. knowlesi-infected monkeys was car- ried out at 10 pm. 30-160 mosquitoes in a pint carton were starved for eight hours prior to the feed. Feeding was on a monkey anesthetized with ketamine and acepro- mazine. Hair was clipped on the chest or abdomen, and cups pressed against the skin under drapes for darkness. After feeding for 15-30 minutes, mosquitoes not engorged with blood were removed, and the remaining mosquitoes were maintained at 26°C and 85% humidity. Cotton pads soaked in sugar solution were changed daily. In some experiments, 10% sucrose was supplemented with methyl- paraben (MPB) beginning on the day after feeding. The MPB solution was made by adding 1gm of MPB (Sigma- Aldrich Corps. Louis, MO, USA) to 500 ml of a 10% glucose solution, filter sterilizing, and storing at 4°C.
Sequential day immunofluorescence stainings were per- formed in brain sections to identify the localization of vascu- lar (by CD31) and microglia (by HLA-DR) markers. Tissue was blocked in 5% donkey serum and 2% bovine serum albumin before primary antibody incubation with mouse anti-CD31 (1:80; DakoCytomation) and 0.1% Triton X-100 overnight at 4 ° C. Tissue was incubated in donkey anti-mouse immunoglobulin G conjugated to Alexa Fluor-488 (1:1000; Invitrogen). Tissue was washed and incubated in a second serum block containing 5% goat serum and 2% bovine serum albumin, following the second primary antibody mouse anti- HLA-DR (1:100) with 0.1% Triton X-100 overnight at 4 ° C. Tissue was incubated in Alexa Fluor-594-conjugated goat anti-mouse secondary (1:1,000; Invitrogen). All tissues were incubated in 4 ′ 6-diamidino-2-phenylindole dihydrochloride (DAPI) for 5 minutes (0.005 µ g/mL; Invitrogen), mounted on subbed slides and coverslipped using fluorescent mount- ing medium (Golden Bridge International Inc., Mukiteo, WA, USA).
All students with learning disabilities were tested for their distance and near visual acuity, and visual skills parameters that included near points of convergence, accommodative amplitude, accommodative facility, convergence and diver- gence break and recovery at near, and saccadic tracking skills. Stereoacuity test, cover test, intraocular pressure mea- surement, and anterior and posterior segment examinations, including cyclorefraction, were performed in all subjects to rule out other apparent ocular abnormalities.
This study demonstrates that capuchin monkeys are capable of learning a foraging technique from a conspecific demonstrator and that this process will repeat over several ‘cultural generations’ of group members. To our knowledge, this kind of finding has not previously been shown experimentally in monkeys, and adds to a small body of experiments demonstrating socially learned diffusion effects in a variety of vertebrates (Curio et al. 1978; Lefebvre 1986; Laland & Plotkin 1990; Laland & Williams 1997; Reader & Laland 2000). However, these earlier studies contrasted only a single experimental group with controls, and thus concern only a single behaviour pattern such as pecking through a paper cover to gain food (Lefebvre 1986). In such experimental designs, effects may reflect only the facilitation or targeting of existing elements of behaviour. For example, if we had used only a slide model compared with non-observing controls, a greater occurrence of ‘slide’ in the first group might be because they had discovered through observation that food was in the box and ‘slide’ came naturally to them as a means to obtain it, whilst controls remained ignorant of this opportunity. By contrast, the two-action aspect of our design shows, crucially, that some kind of copying process was at work, to provide the necessary differentiation between the replications that occurred along each chain of individuals seeded with the alternative methods.
campaign. In that case, there would be the cost for employing the research members of the team as well as the development members. The cost to employ team members would be per hour, and I would foresee a project such as this being funded thorough a professional industry or possibly by an educational or visual art research grant. There would also be the software and hardware costs, necessary programs including the Adobe Creative Suite as well as access to the Internet and a computer/hardware system that would perform the developmental aspects of this project. In this case, I have access to both the software and hardware necessary. However, an external cost that may only pertain to me would be the purchasing of necessary development resources, seeing as I have yet to learn some of the development skills I’ll need to complete this project. Other budget elements would include cost of product/application promotions, a photography budget (i.e. to gain rights to use specific photos as educational examples) as well as the hosting cost to display this product on the web. In my case, I will be involved in promoting the thesis exhibition, and I will be promoting my own work by entering design and computer graphics competitions, which sometimes have fees, associated per entry. I will also be hosting the final results, and pooling my resources to get the word out to other students, professors, and professionals that this application is available online to view and interact.
In a developmental study, Gibson, Pick and Osser  examined the development of visual discrimination of letter-like forms with 167 children aged four to eight years. Letter-like forms were constructed comparable to printed Roman capitals, and there were four types of transformations: line to curve or curve to line, rotation or reversal, perspective (slant left and backward tilt) and topological (break and close). All of these transformations except the perspective transformations are critical for discriminating letters. Errors were classified according to the type of transformation. Results found that errors of rotation and reversals were high in children four years old but declined to nearly zero in eight years olds. Similar changes were observed on line to curve transformations. For perspective transformations, the errors were high at four years old, and were still high at eight years of age Errors were few even for the four years on topological transformations and declined to almost zero at eight years. These results suggest that children between four and eight learn to discriminate between features which are critical for
We use classical conditioning of the honeybee (Apis mellifera) proboscis extension reflex with a visual (A) and an olfactory (X) conditioned stimulus in a blocking paradigm. Typically, learning about one element (X) of a compound (AX) is decreased (blocked) if the other component (A) has previously been rewarded alone. Our results show that visual pretraining did not produce blocking in honeybees: instead, forward pairings of A with a reward increased subsequent learning about X relative to a backward pairing control. This finding violates the independence assumption, which holds that elements of inter-modal compound stimuli change associative strength independently of each other. Furthermore, it is at odds with
Second, by providing a strict initial model we make implicit assumptions about the distribution of the sen- sor outputs (e.g., unimodal along the gesture in the case of a strictly linear Markov model). These assump- tions may be unwarranted: while a simple gesture may seem to us a simple sequence of conceptual states, the sensors may see the movement as a complicated tan- gle of perceptual states. This may occur, for example, when the sensors used do not embody the same invari- ances as our own visual system. Figure 2 illustrates a single conceptual state (the upright hand) generating grossly diﬀerent observations. If a single b j (x) cannot encode both observations equally well, then additional Markov states are required to span the single concep- tual state. The addition of these states require the ﬂexibility of the Markov model to deviate from strictly causal topologies.
We first describe zero-shot image tagging in chapter 3. Zero-shot learning trains a model to predict labels that are unseen during the training phase. It is common to transfer knowledge of known training labels to unseen labels via their semantically encoded word vectors. However, unlike commonly studied zero-shot image classification, we want to study a more general image tagging scenario, where each image may possess multiple labels. We begin by looking into a particular image-word relation in this chapter. Our results show that the word vectors of relevant tags for a given image rank ahead of the irrelevant tags, along a principal direction in the word vector space. Inspired by this observation, we propose to solve image tagging by estimating the principal direction for an image. Particularly, we exploit linear mappings and nonlinear deep neural networks to approximate the principal direction from an input image. We arrive at a quite versatile tagging model. It runs fast given a test image, in constant time w.r.t. the training set size. It not only yields superior performance for the conventional tagging task on the NUS-WIDE dataset, but also outperforms competitive baselines on annotating images with previously unseen tags.