Microsaccades differentially modulate neural activity in the striate and extrastriate visual cortex

Size: px
Start display at page:

Download "Microsaccades differentially modulate neural activity in the striate and extrastriate visual cortex"

Transcription

1 Exp Brain Res (1998) 123: Springer-Verlag 1998 RESEARCH NOTE David A. Leopold Nikos K. Logothetis Microsaccades differentially modulate neural activity in the striate and extrastriate visual cortex Received: 25 May 1998 / Accepted: 3 August 1998 Abstract Saccadic eye movements in primates continually shift the location at which a given stimulus strikes the retina. Even during periods of steady fixation, microsaccades frequently jerk the center of gaze by small but resolvable distances, yet perception remains stable and continuous, uninterrupted by sudden jumps or shifts. The effect of such fixational eye movements on the activity of single neurons was examined in several regions of the visual cortex in macaque monkeys. We found that the firing of many neurons in striate and extrastriate cortex is profoundly influenced by saccades much smaller than the neurons receptive fields. In striate cortex (V1) many cells showed a transient decrease in their firing shortly following a saccade. In sharp contrast, cells in the extrastriate areas V2 and V4 showed strong excitatory responses that closely coincided in time with the striate depression. No appreciable activity change was observed in the inferotemporal cortex (IT) following saccades. This activity pattern is consistent with the notion that topographic extrastriate areas receive extraretinal input associated with saccadic events. Such signals may be necessary for the stable perception of objects and scenes during eye movements, mediating the mapping between central object representations and the constantly changing retinotopic input. Key words Electrophysiology Saccades Saccadic suppression Fixation Striate Extrastriate Visual perception Monkeys Perceptual stability Introduction During normal vision the eyes are never completely still but display a variety of conjugate and nonconjugate movements that continually shift the images on the retinae. D.A. Leopold ( ) N.K. Logothetis Max Planck Institute for Biological Cybernetics, Spemannstrasse 38, D Tuebingen, Germany Tel.: , Fax: Even during periods of steady fixation, microsaccades fast, conjugate jerks, generally smaller than 1/3 readjust the direction of gaze up to several times per second in both monkeys and humans (Carpenter 1988; Skavenski et al. 1975). Given their preponderance, as well as the large number of electrophysiological studies carried out in awake monkeys in recent decades, it is perhaps surprising that little is known about the influence of microsaccades upon activity in the cortical visual areas. Several studies have examined the effects of large saccades on the activity of neurons in the striate cortex (V1) and lateral geniculate nucleus (LGN) in cats and monkeys (Adey and Noda 1973; Toyama et al. 1984; Wurtz 1969b; Duffy and Burchfiel 1975). Such studies have generally sought neural correlates for saccadic suppression, the well-known reduction in sensitivity to flashed targets around the time of a saccade (Burr et al. 1994; Volkmann 1962). Accordingly, many neurons in these areas show a transient depression in their firing with each saccade (Wurtz 1969b; Duffy and Burchfiel 1975). Excitatory responses have also been reported in striate and extrastriate areas when saccades displace a neuron s receptive field across an excitatory stimulus (Wurtz 1969b; Fischer et al. 1981). While some investigators have attributed such signals to transient input through normal retinal pathways (since the effect does not depend on whether the eye or stimulus moves) (Judge et al. 1980; Wurtz 1969a), others have argued that the phasic changes are due to a central corollary discharge signal (von Holst and Mittelstaedt 1950). The latter notion is supported by the occurrence of saccade-related responses in complete darkness (Duffy and Burchfiel 1975) and even during oculomotor paralysis when eye movements are attempted but never executed (Toyama et al. 1984). What effects might microsaccades have on the activity of neurons in the cortical visual areas? Given their small amplitude, one might imagine that they would modulate the activity of V1 neurons with small receptive fields, but that their influence would diminish in the extrastriate areas as the receptive fields increased in size. Although

2 342 recent experiments have examined the influence of small saccades on overall spiking variability (Gur et al. 1997; O Keefe et al. 1997), no study (to the knowledge of the authors) has directly examined the deterministic physiological effects of microsaccades on the firing of cortical neurons. In the present study we examined saccade-related activity-changes of single neurons in the foveal representation of striate and extrastriate cortex in monkeys fixating a visual stimulus. Materials and methods Single neurons were recorded in striate cortex (V1), areas V2 and V4, and the inferotemporal cortex (IT) of two monkeys (Macaca mulatta) while they fixated for periods lasting up to 25 s in the context of a discrimination task using dioptic or dichoptic (rivalrous) stimuli. During the entire fixation period the monkeys were required to maintain their gaze within a virtual square (generally 0.8 across) centered on the fixation point (0.15 ). For recordings in the early areas stimuli consisted of circular patches of oriented gratings (generally <1 in diameter) placed in the neuron s receptive field (nearly always at the center of gaze). During the IT recordings receptive-field stimuli consisted of photographs of animate objects and two-dimensional geometrical patterns centered on the fixation point. In all cases the monkey was required to discriminate two dissimilar patterns, one that excited the neuron and one that had little influence over its firing rate. Further details of the task and the electrophysiological procedures used are described elsewhere (Leopold and Logothetis 1996; Sheinberg and Logothetis 1997). The monkeys were cared for in accordance with the National Institutes of Health Guide and the guidelines of the Animal Protocol Review Committee of the Baylor College of Medicine. Details regarding surgery, animal training, and visual stimulus are provided in the references (Leopold and Logothetis 1996; Sheinberg and Logothetis 1997). Recordings were performed with sharpened, glass-coated Pt-Ir wire electrodes using standard extracellular recording procedures. The eye position signal was measured using the scleral search coil technique and sampled at 200 Hz during the experimental sessions. This signal was then interpolated using cubic splines and resampled at 1 khz. Small saccadic movements were extracted offline using an iterative algorithm that relied upon first identifying potential saccades based on eye velocity and then accepting or rejecting each candidate by comparing several of its parameters to the well-known phenomenology of small saccades (Carpenter 1988; Zuber et al. 1965). Only candidates with periods of at least 8 ms of monotonic positional changes, flanked by instances of stable fixation, were considered to be valid. Corrective saccades were also identified but excluded in the present analysis. Microsaccades had a median amplitude of 10.1 arcmin, a median interval of 597 ms, and lasted on average 20 ms. Results In order to evaluate the influence of such eye movements on the activity of cells in the different visual areas, microsaccade-aligned histograms were generated for a time period starting 100 ms before and ending 400 ms after the onset of movement (several examples are shown in Fig. 1a). Such analysis revealed profound effects of microsaccades on the activity of cortical neurons, which was manifested differentially in the different visual areas. Figure 1a (top row) shows that, in agreement with previous studies, many striate cortical neurons exhibited inhibitory and excitatory postsaccadic responses, even though microsaccade amplitudes never exceeded a fraction of a degree. Roughly 37% (13/35) of striate cells were suppressed following microsaccades, while a smaller fraction (17%, 6/35) showed an enhancement during this period. The remaining cells showed no significant changes. In contrast, the early extrastriate areas showed an entirely different pattern of activity that could be divided into two groups: those showing excitatory responses and those showing no microsaccade-related responses. In V2 (Fig. 1a, row 2), neurons were roughly equally divided, with 45% (13/29) giving an excitatory burst after a saccade and 52% (15/29) giving no response at all (one neuron, not shown, exhibited a slight depression). Area V4 showed the most pronounced activity shortly following the saccade (Fig. 1a, row 3), both in the magnitude of the activity within individual cells and in the percentage of cells affected. Significant excitatory responses (roughly 74%, 56/76 cells) were of two distinct types: transient postsaccadic bursts and sustained responses with slightly longer latencies. The first type began roughly 100 ms after the start of the saccade and reached a peak at about ms. Sustained responses had latencies of over 125 ms and remained above baseline for at least 200 ms. Only 20 out of 76 cells failed to show any microsaccaderelated activity. Figure 1b depicts a typical V4 neuron whose activity was strongly modulated by microsaccades. For emphasis, analysis is restricted to movements less than 9 arcmin in amplitude. The upper and middle panels show the activity of the cell as a function of time. Black tick marks represent individual action potentials before and following saccade onset (dotted vertical line), for many trials. The lower panel shows the trajectory of only downward microsaccades. Note that this cell gives consistent responses to even miniscule fixational eye movements. As in previous studies (Duffy and Burchfiel 1975; Toyama et al. 1984), the direction of the saccade was important for determining its effect on cell activity. Even for the smallest saccades, many cells demonstrated a reliable directionality in their responses which was uncorrelated with the orientation of the stimulus. This is in contrast to the effect of saccade amplitude, where cell responses remained constant for saccades over a range of 5 21 arcmin. Only when saccades grew to near half a degree were population responses in V1 and V2 (but not V4) degraded, possibly directly due to differences in receptive field sizes in the different areas. Finally, the effects of saccades depended on the stimulus present in the receptive field, as microsaccades during stimulation with the preferred grating usually produced larger excitatory or inhibitory effects than during null stimulation (see Fig. 2a). Neurons recorded from the inferotemporal cortex were considerably less responsive to microsaccades than those in the earlier areas (Fig. 1, row 4). For the majority of IT cells (74%, 50/68), the histograms revealed no structure when spike trains were aligned with saccadic

3 343 Fig. 1 a Saccade-elicited activity of neurons in each of the areas studied. Perisaccadic time histograms were generated using the saccade onset as trigger events. Each histogram shows the average influence of a microsaccade on the cell s instantaneous spiking rate. Dotted vertical lines correspond to the saccade onset time; vertical gray lines show 100-ms increments. b Activity of a typical V4 neuron during microsaccades. Upper and middle panels show the spiking of the cell as a function of time before and after microsaccade onset (vertical dotted line). Black tick marks represent individual action potentials, where each row represents one saccade. The gray histogram beneath shows the average instantaneous rate for all saccades above. The bottom panel shows saccade amplitudes and directions, where the circle represents the eye position at the end of the saccade. All saccades in this figure are <9 arcmin and in the downwards direction events. For a fraction of the cells (21%, 14/68), there was a slight increase in activity following a saccade, with a latency that generally approached 200 ms, while for 4 of the 68 neurons (6%, 4/68) a weak, long-latency, transient depression was observed that reached a minimum roughly 200 ms after the microsaccade. Figure 2a shows the average time course of neuronal changes in response to microsaccades during preferred and null receptive field stimulation (thick traces) and to flashed excitatory stimuli (gray-shaded area) for each of the areas studied. The vertical black lines depict the onset of the saccade or stimulus. While in the extrastriate areas the latency of the postsaccadic activity was similar to that of a normal flash response, the depression in area V1 was shifted such that its lowest point was reached at the time of the flash response latency. In area IT the few cells that demonstrated weak saccade-related excitation did so considerably after the time that a normal flash-response would be expected. The mean stimulus response latency in V1 was found to be slightly longer than that in other areas. This is likely to reflect a recording bias from the supra- and infragranular layers in V1, where latencies are known to be considerably longer than in layer 4, supporting the notion of largely parallel image analysis even in the initial cortical processing stages (Bullier and Nowak 1995). To allow a direct comparison of the time courses of the responses in each of the areas studied, normalized average rate functions from the neurons of each area are superimposed in Fig. 2b. Note the increase in the firing rate of V2 neurons at the same time at which V1 cells exhibit activity suppression. Roughly 30 ms later, V4 cells start a brisk activity increase that peaks 140 ms after the saccade. Finally, the inferotemporal cortex shows a slight increase in activity beginning at approximately 180 ms. The scale on the left depicts the mean fractional activity change in the normalized instantaneous rate for each of the cell groups. Aligning to saccade offset rather than onset had little influence on the average responses.

4 344 Fig. 2 a Comparison of population-averaged postsaccadic and stimulus-evoked responses. Each panel represents the average activity of all cells within a given area following either a microsaccade (thick lines) or the presentation of an excitatory stimulus (gray-shaded region). In the former case, the vertical black line corresponds to the onset of the microsaccade and the population s average perisaccadic activity can be seen from 50 ms before to 350 ms after saccade onset. The thick lines correspond to responses occurring while the preferred (upper trace) and null (lower trace) stimuli were present dioptically in the cell s receptive field. Preferred and null stimulation is pooled in area IT, where firing rate changes were negligible. Microsaccades during periods of binocular rivalry are not included. In the case of the stimulus-evoked response, the same vertical black line corresponds to the dioptic presentation of the excitatory stimulus alone on the screen. The area is shown in bold type in the upper right corner and the total number of cells averaged from that area is shown in parentheses. Only those neurons are included that were tested both during the discrimination task and under passive conditions in which an excitatory stimulus was flashed in the receptive field. b Mean fractional activity changes in the different visual areas following a microsaccade. Differently colored curves represent the overall mean normalized response from all microsaccades and all cells in each of the areas. The vertical black line signifies the onset of the microsaccade. Before averaging cell responses from an area, each cell s mean response is computed and then normalized to its own presaccadic firing rate. The color-coding and the number of cells used to compute each trace are shown in the gray box at the upper right Discussion Despite their small amplitude, microsaccades have a significant and primarily suppressive influence on neurons in the striate cortex, similar to that reported previously for larger saccades (Wurtz 1969b; Duffy and Burchfiel 1975). The dips in spiking activity, whether they have an external or endogenous origin, may be related to the elevation in perceptual thresholds associated with saccadic suppression. Such elevations have also been reported to arise during spontaneous fixational movements (Beeler 1967) (but see also Krauskopf et al. 1966), and may generally serve to eliminate the perception of motion or blur that might otherwise accompany a saccade (Burr et al. 1994). More difficult to explain is the marked excitatory activity observed in the early extrastriate areas. Such signals cannot be easily attributed to normal retinal stimulation, as saccade amplitudes were often an order of magnitude smaller in size than the receptive fields of the cells they affected. This was especially true in area V4, where receptive fields are larger than in the earlier areas but microsaccades generated the largest responses. In fact, in area V4 the mean difference in overall firing rate during preferred and null stimulation can be almost entirely accounted for by postmicrosaccadic activity (see Fig. 2a). One possibility is that such responses reflect extraretinal input that is related to maintaining stability in perception during saccades. Microsaccades, despite their small amplitude, jerk the retinal image by an amount that would be perceptible if not for specific stabilizing mechanisms. Many theories of perceptual stability rest upon the cortex receiving information about eye movements, often through a corollary discharge signal (Bridgeman et al. 1994). Such signals could serve to reconcile an incoming sensory map after an eye movement with a stored perceptual representation. Input from subcortical structures represents one possible source of a corollary discharge. For example, many units in the internal medullary lamina of the thalamus (IML), which receives input from brainstem structures involved in eye movement programming, show saccaderelated activity (Schlag-Rey and Schlag 1984). One particularly interesting class of cells in the central thalamus, the so-called pause-rebound units, demonstrates an in-

5 hibitory activity-dip during or just after saccades, followed by a strong excitatory rebound tens of milliseconds later. It has been speculated that this pattern could serve as a clocking mechanism, where information about saccadic movements would reach the cortex just as visual information from the new eye position arrives (Schlag and Schlag-Rey 1983). Alternatively, extraretinal saccade-related signals could stem from higher cortical areas, perhaps drawing simultaneously from the inferotemporal lobe, where neurons show invariance in their responses to position and scale (Ito et al. 1995) and the parietal areas, where receptive field coordinates are updated based on intended saccades (Duhamel et al. 1992). If the maintenance of perceptual stability during saccades relies on the continual association of a new sensory map in V1 with a more abstract and stable representation in IT, it is possible that the signals observed in the extrastriate areas reflect this update process. Regardless of its origin, microsaccade-related activity has a profound impact on neurons in the striate and extrastriate cortical areas. One implication of this result, which has been previously suggested based on recordings in area V1 (Gur et al. 1997), is that much of the variability in neuronal responses can be accounted for by fixational eye movements. This has broad-reaching implications for descriptions of the brain in which visual capacity is compared with neural reliability (Britten et al. 1992). If a great portion of a spiking variability arises from the largely deterministic effects of eye movements, much of which has been previously characterized as noise may be instead a signal that is not yet understood. The results presented here support this notion. However, the effects of microsaccades appear to extend beyond simply increasing variability with each small eye movement the visual cortex is bombarded with a strong, synchronized (and perhaps synchronizing) pulse. This presence of such activity in the earlier areas, combined with its absence in IT, supports the notions that sensory and perceptual signals converge in the topographic extrastriate areas, but that neural activity in the inferotemporal cortex reflects what is actually perceived. Inferotemporal neurons ignore microsaccades (matching perception), while activity in the earlier areas must reflect each small movement. This is similar to previously published results in which the neural responses during ambiguous vision better reflected perception in IT than in the earlier topographic areas (Leopold and Logothetis 1996; Sheinberg and Logothetis 1997). Further studies are needed, in particular those exploiting simultaneous recordings from neurons in the different visual areas, to better understand the nature and significance of the signals reported here. Acknowledgements We thank Dr. David Sheinberg for generously providing the data from the inferotemporal cortex. In addition we thank Drs. Francis Crick, Christof Koch, Bill Merigan and David Sheinberg for useful comments on the manuscript. Work for this project was supported by the Division of Neuroscience at Baylor College of Medicine and by the Max Planck Society. References 345 Adey RW, Noda H (1973) Influence of eye movements on geniculo-striate excitability in the cat. J Physiol 235: Beeler GW (1967) Visual threshold changes resulting from spontaneous saccadic eye movements. Vision Res 7: Bridgeman B, Van der Heijden AHC, Velichkovsky BM (1994) A theory of visual stability across saccadic eye movements. Behav Brain Sci 17: Britten KH, Shadlen MN, Newsome WT, Movshon JA (1992) The analysis of visual motion: a comparison of neuronal and psychophysical performance. J Neurosci 12: Bullier J, Nowak LG (1995) Parallel versus serial processing: new vistas on the distributed organization of the visual system. Curr Opin Neurobiol 5: Burr DC, Morrone MC, Ross J (1994) Selective suppression of the magnocellular visual pathway during saccadic eye movements. Nature 371: Carpenter RHS (1988) Movements of the eyes, 2nd edn. Pion, London Duffy FH, Burchfiel JL (1975) Eye movement-related inhibition of primate visual neurons. Brain Res 89: Duhamel J-R, Colby CL, Goldberg ME (1992) The updating of the representation of visual space in parietal cortex by intended eye movements. Science 255:90 92 Fischer B, Boch R, Bach M (1981) Stimulus versus eye movements: comparison of neural activity in the striate and prelunate visual cortex (A17 and A19) of trained rhesus monkey. Exp Brain Res 43:69 77 Gur M, Beylin A, Snodderly DM (1997) Response variability of neurons in primary visual cortex (V1) of alert monkeys. J Neurosci 17: Holst E von, Mittelstaedt H (1950) Das Reafferenzprinzip. Naturwissenschaften Ito M, Tamura H, Fujita I, Tanaka K (1995) Size and position invariance of neuronal responses in monkey inferotemporal cortex. J Neurophysiol 73: Judge SJ, Wurtz RH, Richmond BJ (1980) Vision during saccadic eye movements. I. Visual interactions in the striate cortex. J Neurophysiol 43: Krauskopf J, Graf V, Gaardner K (1966) Lack of inhibition during involuntary saccades. Am J Psychol 79:73 81 Leopold DA, Logothetis NK (1996) Activity changes in early visual cortex reflect monkeys percepts during binocular rivalry. Nature 379: O Keefe LP, Bair W, Movshon JA (1997) Response variability of MT neurons in macaque monkeys. Soc Neurosci Abstr 23: 1125(288.1) Schlag J, Schlag-Rey M (1983) Thalamic units firing upon refixation may be responsible for plasticity in visual cortex. Exp Brain Res 50: Schlag-Rey M, Schlag J (1984) Visuomotor functions of central thalamus in monkey. I. Unit activity related to spontaneous eye movements. J Neurophysiol 51: Sheinberg DL, Logothetis NK (1997) The role of temporal cortical areas in perceptual organization. Proc Natl Acad Sci USA 94: Skavenski AA, Robinson DA, Steinman RM, Timberlake TG (1975) Miniature eye movements of fixation in rhesus monkey. Vision Res 15: Toyama K, Komatsu Y, Shibuki K (1984) Integration of retinal and motor signals of eye movements in striate cortex cells of the alert cat. J Neurophysiol 51: Volkmann FC (1962) Vision during voluntary saccadic eye movements. J Opt Soc Am A 52: Wurtz RH (1969a) Comparison of effects of eye movements and stimulus movements in striate cortex neurons of the monkey. J Neurophysiol 32: Wurtz RH (1969b) Response of striate cortex neurons to stimuli during rapid eye movements in the monkey. J Neurophysiol 32: Zuber BL, Stark L, Cook G (1965) Microsaccades and the velocity-amplitude relationship for saccadic eye movements. Science 150:

Visual area MT responds to local motion. Visual area MST responds to optic flow. Visual area STS responds to biological motion. Macaque visual areas

Visual area MT responds to local motion. Visual area MST responds to optic flow. Visual area STS responds to biological motion. Macaque visual areas Visual area responds to local motion MST a Visual area MST responds to optic flow MST a Visual area STS responds to biological motion STS Macaque visual areas Flattening the brain What is a visual area?

More information

The Visual Cortex 0 http://www.tutis.ca/neuromd/index.htm 20 February 2013

The Visual Cortex 0 http://www.tutis.ca/neuromd/index.htm 20 February 2013 T he Visual Cortex 0 Chapter contents Contents Chapter 2... 0 T he Visual Cortex... 0 Chapter Contents... 1 Introduction... 2 Optic Chiasm... 2 Where do the eye's ganglion cells project to?... 3 To where

More information

Correlated Neuronal Response: Time Scales and Mechanisms

Correlated Neuronal Response: Time Scales and Mechanisms Correlated Neuronal Response: Time Scales and Mechanisms Wyeth Bair Howard Hughes Medical nst. NYU Center for Neural Science 4 Washington P., Room 809 New York, NY 10003 Ehud Zohary Dept. of Neurobiology

More information

Video-Based Eye Tracking

Video-Based Eye Tracking Video-Based Eye Tracking Our Experience with Advanced Stimuli Design for Eye Tracking Software A. RUFA, a G.L. MARIOTTINI, b D. PRATTICHIZZO, b D. ALESSANDRINI, b A. VICINO, b AND A. FEDERICO a a Department

More information

CHAPTER 6 PRINCIPLES OF NEURAL CIRCUITS.

CHAPTER 6 PRINCIPLES OF NEURAL CIRCUITS. CHAPTER 6 PRINCIPLES OF NEURAL CIRCUITS. 6.1. CONNECTIONS AMONG NEURONS Neurons are interconnected with one another to form circuits, much as electronic components are wired together to form a functional

More information

THE HUMAN BRAIN. observations and foundations

THE HUMAN BRAIN. observations and foundations THE HUMAN BRAIN observations and foundations brains versus computers a typical brain contains something like 100 billion miniscule cells called neurons estimates go from about 50 billion to as many as

More information

consciousness vision: WHEN YOU first look at the

consciousness vision: WHEN YOU first look at the IN THEIR SEARCH FOR THE MIND, SCIENTISTS ARE FOCUSING ON VISUAL PERCEPTION HOW WE INTERPRET WHAT WE SEE vision: consciousness a window BY NIKOS K. LOGOTHETIS WHEN YOU first look at the center image in

More information

GAZE STABILIZATION SYSTEMS Vestibular Ocular Reflex (VOR) Purpose of VOR Chief function is to stabilize gaze during locomotion. Acuity declines if

GAZE STABILIZATION SYSTEMS Vestibular Ocular Reflex (VOR) Purpose of VOR Chief function is to stabilize gaze during locomotion. Acuity declines if GAZE STABILIZATION SYSTEMS Vestibular Ocular Reflex (VOR) Purpose of VOR Chief function is to stabilize gaze during locomotion. Acuity declines if slip exceeds 3-5 deg/sec. Ex: Head bobbing and heel strike

More information

207-2. Selective Saccadic Palsy

207-2. Selective Saccadic Palsy 207-2 Selective Saccadic Palsy Selective Saccadic Palsy after Cardiac Surgery Selective loss of all forms of saccades (voluntary and reflexive quick phases of nystagmus) with sparing of other eye movements.

More information

Masters research projects. 1. Adapting Granger causality for use on EEG data.

Masters research projects. 1. Adapting Granger causality for use on EEG data. Masters research projects 1. Adapting Granger causality for use on EEG data. Background. Granger causality is a concept introduced in the field of economy to determine which variables influence, or cause,

More information

Processing the Image or Can you Believe what you see? Light and Color for Nonscientists PHYS 1230

Processing the Image or Can you Believe what you see? Light and Color for Nonscientists PHYS 1230 Processing the Image or Can you Believe what you see? Light and Color for Nonscientists PHYS 1230 Optical Illusions http://www.michaelbach.de/ot/mot_mib/index.html Vision We construct images unconsciously

More information

A model of memory, learning and recognition

A model of memory, learning and recognition A model of memory, learning and recognition Bruce Hoeneisen Universidad San Francisco de Quito 6 May 2002 Abstract We propose a simple model of recognition, short-term memory, longterm memory and learning.

More information

Motion processing: the most sensitive detectors differ in temporally localized and extended noise

Motion processing: the most sensitive detectors differ in temporally localized and extended noise ORIGINAL RESEARCH ARTICLE published: 15 May 2014 doi: 10.3389/fpsyg.2014.00426 Motion processing: the most sensitive detectors differ in temporally localized and extended noise Rémy Allard 1,2,3 * and

More information

The Physiology of the Senses Lecture 11 - Eye Movements www.tutis.ca/senses/

The Physiology of the Senses Lecture 11 - Eye Movements www.tutis.ca/senses/ The Physiology of the Senses Lecture 11 - Eye Movements www.tutis.ca/senses/ Contents Objectives... 2 Introduction... 2 The 5 Types of Eye Movements... 2 The eyes are rotated by 6 extraocular muscles....

More information

N.Galley, R.Schleicher and L.Galley Blink parameter for sleepiness detection 1

N.Galley, R.Schleicher and L.Galley Blink parameter for sleepiness detection 1 N.Galley, R.Schleicher and L.Galley Blink parameter for sleepiness detection 1 Blink Parameter as Indicators of Driver s Sleepiness Possibilities and Limitations. Niels Galley 1, Robert Schleicher 1 &

More information

The role of context in Müller-Lyer illusion: The case of negative Müller-Lyer illusion

The role of context in Müller-Lyer illusion: The case of negative Müller-Lyer illusion Review of Psychology, 2013, Vol. 20, No. 1-2, 29-36 UDC 159.9 The role of context in Müller-Lyer illusion: The case of negative Müller-Lyer illusion PAVLE VALERJEV and TANJA GULAN The Müller-Lyer illusion

More information

What constitutes good visualization research?

What constitutes good visualization research? Visualization Viewpoints Editor: TheresaMarie Rhyne Toward a Perceptual Theory of Flow Visualization Colin Ware University of New Hampshire What constitutes good visualization research? Are researchers

More information

The Binding Problem Solutions to the spatial binding problem

The Binding Problem Solutions to the spatial binding problem The Binding Problem Objects have different features such as color, shape, sound, and smell. Some, such as color and sound, are represented separately from the instant they hit our sensory receptors. Other

More information

Auditory neuroanatomy: the Spanish heritage. Santiago Ramón y Cajal, 1852 1934

Auditory neuroanatomy: the Spanish heritage. Santiago Ramón y Cajal, 1852 1934 Auditory neuroanatomy: the Spanish heritage Santiago Ramón y Cajal, 1852 1934 Rafael Lorente de Nó, 1902 1990 3 The nervous system is made up of cells. Estimates of the number of cells vary from

More information

Spatial and Temporal Properties of Cone Signals in Alert Macaque Primary Visual Cortex

Spatial and Temporal Properties of Cone Signals in Alert Macaque Primary Visual Cortex 10826 The Journal of Neuroscience, October 18, 2006 26(42):10826 10846 Behavioral/Systems/Cognitive Spatial and Temporal Properties of Cone Signals in Alert Macaque Primary Visual Cortex Bevil R. Conway

More information

Bernice E. Rogowitz and Holly E. Rushmeier IBM TJ Watson Research Center, P.O. Box 704, Yorktown Heights, NY USA

Bernice E. Rogowitz and Holly E. Rushmeier IBM TJ Watson Research Center, P.O. Box 704, Yorktown Heights, NY USA Are Image Quality Metrics Adequate to Evaluate the Quality of Geometric Objects? Bernice E. Rogowitz and Holly E. Rushmeier IBM TJ Watson Research Center, P.O. Box 704, Yorktown Heights, NY USA ABSTRACT

More information

Trade-Off between Object Selectivity and Tolerance in Monkey Inferotemporal Cortex

Trade-Off between Object Selectivity and Tolerance in Monkey Inferotemporal Cortex 12292 The Journal of Neuroscience, November 7, 2007 27(45):12292 12307 Behavioral/Systems/Cognitive Trade-Off between Object Selectivity and Tolerance in Monkey Inferotemporal Cortex Davide Zoccolan, Minjoon

More information

Independence of Visual Awareness from the Scope of Attention: an Electrophysiological Study

Independence of Visual Awareness from the Scope of Attention: an Electrophysiological Study Cerebral Cortex March 2006;16:415-424 doi:10.1093/cercor/bhi121 Advance Access publication June 15, 2005 Independence of Visual Awareness from the Scope of Attention: an Electrophysiological Study Mika

More information

Analog VLSI Circuits for Attention-Based, Visual Tracking

Analog VLSI Circuits for Attention-Based, Visual Tracking Analog VLSI Circuits for Attention-Based, Visual Tracking Timothy K. Horiuchi Computation and Neural Systems California Institute of Technology Pasadena, CA 91125 timmer@klab.caltech.edu Christof Koch

More information

In a number of recent studies investigators have shown that

In a number of recent studies investigators have shown that Cortical correlates of learning in monkeys adapting to a new dynamical environment F. Gandolfo, C.-S. R. Li*, B. J. Benda, C. Padoa Schioppa, and E. Bizzi Department of Brain and Cognitive Sciences, Massachusetts

More information

Agent Simulation of Hull s Drive Theory

Agent Simulation of Hull s Drive Theory Agent Simulation of Hull s Drive Theory Nick Schmansky Department of Cognitive and Neural Systems Boston University March 7, 4 Abstract A computer simulation was conducted of an agent attempting to survive

More information

Eye-tracking. Benjamin Noël

Eye-tracking. Benjamin Noël Eye-tracking Benjamin Noël Basics Majority of all perceived stimuli through the eyes Only 10% through ears, skin, nose Eye-tracking measuring movements of the eyes Record eye movements to subsequently

More information

Attentional tradeoffs maintain the tracking of moving objects across saccades

Attentional tradeoffs maintain the tracking of moving objects across saccades Attentional tradeoffs maintain the tracking of moving objects across saccades Martin Szinte 1*, Marisa Carrasco 2, Patrick Cavanagh 3 & Martin Rolfs 4 1. Allgemeine und Experimentelle Psychologie, Ludwig-Maximilians-Universität

More information

Anna Martelli Ravenscroft

Anna Martelli Ravenscroft Left vs Right processing of & Place in fovea & periphery Psych204b Background: Anna Martelli Ravenscroft Vision depends on multiple regions of the brain, from the specialized photoreceptors of the retina,

More information

Decoding mental states from brain activity in humans

Decoding mental states from brain activity in humans NEUROIMAGING Decoding mental states from brain activity in humans John-Dylan Haynes* and Geraint Rees Abstract Recent advances in human neuroimaging have shown that it is possible to accurately decode

More information

Next Generation Artificial Vision Systems

Next Generation Artificial Vision Systems Next Generation Artificial Vision Systems Reverse Engineering the Human Visual System Anil Bharath Maria Petrou Imperial College London ARTECH H O U S E BOSTON LONDON artechhouse.com Contents Preface xiii

More information

COGNITIVE INFLUENCES ON SENSORY PROCESSING

COGNITIVE INFLUENCES ON SENSORY PROCESSING COGNITIVE INFLUENCES ON SENSORY PROCESSING OF VISUAL MOTION Dissertation zur Erlangung des Doktorgrades der Mathematisch-Naturwissenschaftlichen Fakultäten der Georg-August Universität zu Göttingen vorgelegt

More information

Attentive tracking shifts the perceived location of a nearby flash q

Attentive tracking shifts the perceived location of a nearby flash q Vision Research xxx (2005) xxx xxx www.elsevier.com/locate/visres Attentive tracking shifts the perceived location of a nearby flash q Won Mok Shim *, Patrick Cavanagh Department of Psychology, Harvard

More information

Overview of Methodology. Human Electrophysiology. Computing and Displaying Difference Waves. Plotting The Averaged ERP

Overview of Methodology. Human Electrophysiology. Computing and Displaying Difference Waves. Plotting The Averaged ERP Human Electrophysiology Overview of Methodology This Week: 1. Displaying ERPs 2. Defining ERP components Analog Filtering Amplification Montage Selection Analog-Digital Conversion Signal-to-Noise Enhancement

More information

Integration, segregation, and binocular combination

Integration, segregation, and binocular combination 38 J. Opt. Soc. Am. A/ Vol. 22, No. 1/ January 2005 Mansouri et al. Integration, segregation, and binocular combination Behzad Mansouri and Robert F. Hess McGill Vision Research, 687 Pine Avenue W, H4-14

More information

Spectral fingerprints of large-scale neuronal interactions

Spectral fingerprints of large-scale neuronal interactions Spectral fingerprints of large-scale neuronal interactions Markus Siegel 1 *, Tobias H. Donner 2 * and Andreas K. Engel 3 Abstract Cognition results from interactions among functionally specialized but

More information

The Number of Cortical Neurons Used to See

The Number of Cortical Neurons Used to See The Number of Cortical Neurons Used to See Krisha Mehta Bronx High School of Science Mentor: Dr.Denis Pelli Teacher: Mr.Lee K. K. Mehta (2013) The number of cortical neurons used to see. Intel Science

More information

2 Neurons. 4 The Brain: Cortex

2 Neurons. 4 The Brain: Cortex 1 Neuroscience 2 Neurons output integration axon cell body, membrane potential Frontal planning control auditory episodes soma motor Temporal Parietal action language objects space vision Occipital inputs

More information

Programs for diagnosis and therapy of visual field deficits in vision rehabilitation

Programs for diagnosis and therapy of visual field deficits in vision rehabilitation Spatial Vision, vol. 10, No.4, pp. 499-503 (1997) Programs for diagnosis and therapy of visual field deficits in vision rehabilitation Erich Kasten*, Hans Strasburger & Bernhard A. Sabel Institut für Medizinische

More information

EFFECTS OF SELECTIVE ATTENTION

EFFECTS OF SELECTIVE ATTENTION EFFECTS OF SELECTIVE ATTENTION ON SENSORY PROCESSING OF VISUAL MOTION Dissertation zur Erlangung des Doktorgrades der Mathematisch-Naturwissenschaftlichen Fakultäten der Georg-August Universität zu Göttingen

More information

Brain Computer Interfaces (BCI) Communication Training of brain activity

Brain Computer Interfaces (BCI) Communication Training of brain activity Brain Computer Interfaces (BCI) Communication Training of brain activity Brain Computer Interfaces (BCI) picture rights: Gerwin Schalk, Wadsworth Center, NY Components of a Brain Computer Interface Applications

More information

Quantifying Spatial Presence. Summary

Quantifying Spatial Presence. Summary Quantifying Spatial Presence Cedar Riener and Dennis Proffitt Department of Psychology, University of Virginia Keywords: spatial presence, illusions, visual perception Summary The human visual system uses

More information

History of eye-tracking in psychological research

History of eye-tracking in psychological research History of eye-tracking in psychological research In the 1950s, Alfred Yarbus showed the task given to a subject has a very large influence on the subjects eye movements. Yarbus also wrote about the relation

More information

Sensory-motor control scheme based on Kohonen Maps and AVITE model

Sensory-motor control scheme based on Kohonen Maps and AVITE model Sensory-motor control scheme based on Kohonen Maps and AVITE model Juan L. Pedreño-Molina, Antonio Guerrero-González, Oscar A. Florez-Giraldo, J. Molina-Vilaplana Technical University of Cartagena Department

More information

Chapter 12: Sound Localization and the Auditory Scene

Chapter 12: Sound Localization and the Auditory Scene Chapter 12: Sound Localization and the Auditory Scene What makes it possible to tell where a sound is coming from in space? When we are listening to a number of musical instruments playing at the same

More information

Chapter 14: The Cutaneous Senses

Chapter 14: The Cutaneous Senses Chapter 14: The Cutaneous Senses Skin - heaviest organ in the body Cutaneous System Epidermis is the outer layer of the skin, which is made up of dead skin cells Dermis is below the epidermis and contains

More information

The Physiology of the Senses Lecture 1 - The Eye www.tutis.ca/senses/

The Physiology of the Senses Lecture 1 - The Eye www.tutis.ca/senses/ The Physiology of the Senses Lecture 1 - The Eye www.tutis.ca/senses/ Contents Objectives... 2 Introduction... 2 Accommodation... 3 The Iris... 4 The Cells in the Retina... 5 Receptive Fields... 8 The

More information

Relative image size, not eye position, determines eye dominance switches

Relative image size, not eye position, determines eye dominance switches Vision Research 44 (2004) 229 234 Rapid Communication Relative image size, not eye position, determines eye dominance switches Martin S. Banks a,b, *, Tandra Ghose a, James M. Hillis c a Vision Science

More information

The Cerebellum and the Timing of Coordinated Eye and Hand Tracking

The Cerebellum and the Timing of Coordinated Eye and Hand Tracking Brain and Cognition 48, 212 226 (2002) doi:10.1006/brcg.2001.1314, available online at http://www.idealibrary.com on The Cerebellum and the Timing of Coordinated Eye and Hand Tracking R. C. Miall and G.

More information

Introduction to Machine Learning and Data Mining. Prof. Dr. Igor Trajkovski trajkovski@nyus.edu.mk

Introduction to Machine Learning and Data Mining. Prof. Dr. Igor Trajkovski trajkovski@nyus.edu.mk Introduction to Machine Learning and Data Mining Prof. Dr. Igor Trakovski trakovski@nyus.edu.mk Neural Networks 2 Neural Networks Analogy to biological neural systems, the most robust learning systems

More information

Studying Human Face Recognition with the Gaze-Contingent Window Technique

Studying Human Face Recognition with the Gaze-Contingent Window Technique Studying Human Face Recognition with the Gaze-Contingent Window Technique Naing Naing Maw (nnmaw@cs.umb.edu) University of Massachusetts at Boston, Department of Computer Science 100 Morrissey Boulevard,

More information

Neu. al Network Analysis of Distributed Representations of Dynamical Sensory-Motor rrransformations in the Leech

Neu. al Network Analysis of Distributed Representations of Dynamical Sensory-Motor rrransformations in the Leech 28 Lockery t Fang and Sejnowski Neu. al Network Analysis of Distributed Representations of Dynamical Sensory-Motor rrransformations in the Leech Shawn R. LockerYt Van Fangt and Terrence J. Sejnowski Computational

More information

Visual Attention and Emotional Perception

Visual Attention and Emotional Perception Visual Attention and Emotional Perception Luiz Pessoa 1 and Leslie G. Ungerleider 2 (1) Department of Psychology, Brown University, Providence, RI (2) Laboratory of Brain & Cognition, National Institute

More information

Are There Neural Correlates of Consciousness? 1

Are There Neural Correlates of Consciousness? 1 Alva Noë and Evan Thompson Are There Neural Correlates of Consciousness? 1 In the past decade, the notion of a neural correlate of consciousness (or NCC) has become a focal point for scientific research

More information

An Introduction to ERP Studies of Attention

An Introduction to ERP Studies of Attention An Introduction to ERP Studies of Attention Logan Trujillo, Ph.D. Post-Doctoral Fellow University of Texas at Austin Cognitive Science Course, Fall 2008 What is Attention? Everyone knows what attention

More information

It's Great But Not Necessarily About Attention

It's Great But Not Necessarily About Attention It's Great But Not Necessarily About Attention Jochen Braun Institute of Neuroscience University of Plymouth School of Computing Plymouth, Devon PL4 8AA U.K. jbraun@plymouth.ac.uk Copyright (c) Jochen

More information

Wiring optimization in the brain

Wiring optimization in the brain Wiring optimization in the brain Dmitri B. Chklovskii Sloan Center for Theoretical Neurobiology The Salk Institute La Jolla, CA 92037 mitya@salk.edu Charles F. Stevens Howard Hughes Medical Institute and

More information

Brain Maps The Sensory Homunculus

Brain Maps The Sensory Homunculus Brain Maps The Sensory Homunculus Our brains are maps. This mapping results from the way connections in the brain are ordered and arranged. The ordering of neural pathways between different parts of the

More information

The accurate calibration of all detectors is crucial for the subsequent data

The accurate calibration of all detectors is crucial for the subsequent data Chapter 4 Calibration The accurate calibration of all detectors is crucial for the subsequent data analysis. The stability of the gain and offset for energy and time calibration of all detectors involved

More information

Tinnitus and the Brain

Tinnitus and the Brain Tinnitus and the Brain Dirk De Ridder & Berthold Langguth Moving animals have developed a brain in order to reduce the inherent uncertainty present in an ever changing environment. The auditory system

More information

Colour Perception and its physiological basis

Colour Perception and its physiological basis Blutner/Colour/Colour Perception 1 Colour Perception and its physiological basis Basic phenomena of colour perception - Simultaneous contrast - Mach bands - Afterimages - Chromatic adaptation - Intuitions

More information

Online simulations of models for backward masking

Online simulations of models for backward masking Online simulations of models for backward masking Gregory Francis 1 Purdue University Department of Psychological Sciences 703 Third Street West Lafayette, IN 47907-2004 11 July 2002 Revised: 30 January

More information

Chapter 8: Perceiving Depth and Size

Chapter 8: Perceiving Depth and Size Chapter 8: Perceiving Depth and Size Cues to Depth Perception Oculomotor - cues based on sensing the position of the eyes and muscle tension 1. Convergence knowing the inward movement of the eyes when

More information

Powerful advances in whole-field electrophysiology measurements

Powerful advances in whole-field electrophysiology measurements Powerful advances in whole-field electrophysiology measurements Introducing Advanced electrophysiology focused on your research needs. Phoenix Research Labs electrophysiology tools are not adaptations

More information

Video Game Design Using an Eye Movement Dependent Model of Visual Attention

Video Game Design Using an Eye Movement Dependent Model of Visual Attention Video Game Design Using an Eye Movement Dependent Model of Visual Attention James J. Clark Centre For Intelligent Machines, McGill University and Li Jie Centre For Intelligent Machines, McGill University

More information

PRIMING OF POP-OUT AND CONSCIOUS PERCEPTION

PRIMING OF POP-OUT AND CONSCIOUS PERCEPTION PRIMING OF POP-OUT AND CONSCIOUS PERCEPTION Peremen Ziv and Lamy Dominique Department of Psychology, Tel-Aviv University zivperem@post.tau.ac.il domi@freud.tau.ac.il Abstract Research has demonstrated

More information

Is perception discrete or continuous?

Is perception discrete or continuous? Opinion Vol.7 No.5 May 2003 207 Is perception discrete or continuous? Rufin VanRullen 1 and Christof Koch 2 1 CNRS, Centre de Recherche Cerveau et Cognition, 31062 Toulouse, France 2 California Institute

More information

Telemetry in monkey neurophysiology Remote monitoring of neuronal brain signals

Telemetry in monkey neurophysiology Remote monitoring of neuronal brain signals Telemetry in monkey neurophysiology Remote monitoring of neuronal brain signals Alexander Gail German Primate Center Göttingen, GE Thomas Recording GmbH Giessen, GE This R&D project is part of EUPRIM -

More information

C L I N I C A L A N D E X P E R I M E N T A L OPTOMETRY ORIGINAL PAPER. Contradictory influence of context on predominance during binocular rivalry

C L I N I C A L A N D E X P E R I M E N T A L OPTOMETRY ORIGINAL PAPER. Contradictory influence of context on predominance during binocular rivalry C L I N I C A L A N D E X P E R I M E N T A L Binocular rivalry Carter, Campbell, Liu and Wallis OPTOMETRY ORIGINAL PAPER Contradictory influence of context on predominance during binocular rivalry Clin

More information

Have you ever missed a call while moving? : The Optimal Vibration Frequency for Perception in Mobile Environments

Have you ever missed a call while moving? : The Optimal Vibration Frequency for Perception in Mobile Environments Have you ever missed a call while moving? : The Optimal Vibration Frequency for Perception in Mobile Environments Youngmi Baek and Rohae Myung Dept. of Industrial and Information Engineering Korea University

More information

On-Line Learning with Structural Adaptation in a Network of Spiking Neurons for Visual Pattern Recognition

On-Line Learning with Structural Adaptation in a Network of Spiking Neurons for Visual Pattern Recognition On-Line Learning with Structural Adaptation in a Network of Spiking Neurons for Visual Pattern Recognition Simei Gomes Wysoski, Lubica Benuskova, and Nikola Kasabov Knowledge Engineering and Discovery

More information

Obtaining Knowledge. Lecture 7 Methods of Scientific Observation and Analysis in Behavioral Psychology and Neuropsychology.

Obtaining Knowledge. Lecture 7 Methods of Scientific Observation and Analysis in Behavioral Psychology and Neuropsychology. Lecture 7 Methods of Scientific Observation and Analysis in Behavioral Psychology and Neuropsychology 1.Obtaining Knowledge 1. Correlation 2. Causation 2.Hypothesis Generation & Measures 3.Looking into

More information

Visual development in babies and infants

Visual development in babies and infants Visual development in babies and infants Marko Nardini UCL Institute of Ophthalmology Vision a major function of the primate brain vision develops rapidly in early life and serves as a base for development

More information

MUSIC RECOGNITION DIANA DEUTSCH. Psychological Review, 1969, 76, 300 307. University of California, San Diego

MUSIC RECOGNITION DIANA DEUTSCH. Psychological Review, 1969, 76, 300 307. University of California, San Diego Psychological Review, 1969, 76, 300 307 MUSIC RECOGNITION DIANA DEUTSCH University of California, San Diego Music recognition is discussed, and it is argued that this involves certain specific processes

More information

A Guided User Experience Using Subtle Gaze Direction

A Guided User Experience Using Subtle Gaze Direction A Guided User Experience Using Subtle Gaze Direction Eli Ben-Joseph and Eric Greenstein Stanford University {ebj, ecgreens}@stanford.edu 1 Abstract This paper demonstrates how illumination modulation can

More information

Attraction of flashes to moving dots

Attraction of flashes to moving dots Vision Research 47 (2007) 2603 2615 www.elsevier.com/locate/visres Attraction of flashes to moving dots Ozgur Yilmaz a, *, Srimant P. Tripathy a,c, Saumil S. Patel a,b,d, Haluk Ogmen a,b,c a University

More information

VISUAL PERCEPTUAL CONFLICTS AND ILLUSIONS

VISUAL PERCEPTUAL CONFLICTS AND ILLUSIONS 12 VISUAL PERCEPTUAL CONFLICTS AND ILLUSIONS Leonard A. Temme Melvyn E. Kalich Ian P. Curry Alan R. Pinkus H. Lee Task Clarence E. Rash Vision is arguably the most important of the human senses for a Warfighter.

More information

Models of Cortical Maps II

Models of Cortical Maps II CN510: Principles and Methods of Cognitive and Neural Modeling Models of Cortical Maps II Lecture 19 Instructor: Anatoli Gorchetchnikov dy dt The Network of Grossberg (1976) Ay B y f (

More information

Why can't you tickle yourself?

Why can't you tickle yourself? REVIEW NEUROREPORT Why can't you tickle yourself? Sarah-Jayne Blakemore, CA Daniel Wolpert and Chris Frith Wellcome Department of Cognitive Neurology, Institute of Neurology, University College London,

More information

Moving objects appear to slow down at low contrasts

Moving objects appear to slow down at low contrasts Neural Networks 16 (2003) 933 938 www.elsevier.com/locate/neunet 2003 Special issue Moving objects appear to slow down at low contrasts Stuart Anstis* Department of Psychology, University of California,

More information

Tonal Detection in Noise: An Auditory Neuroscience Insight

Tonal Detection in Noise: An Auditory Neuroscience Insight Image: http://physics.ust.hk/dusw/ Tonal Detection in Noise: An Auditory Neuroscience Insight Buddhika Karunarathne 1 and Richard H.Y. So 1,2 1 Dept. of IELM, Hong Kong University of Science & Technology,

More information

Template-based Eye and Mouth Detection for 3D Video Conferencing

Template-based Eye and Mouth Detection for 3D Video Conferencing Template-based Eye and Mouth Detection for 3D Video Conferencing Jürgen Rurainsky and Peter Eisert Fraunhofer Institute for Telecommunications - Heinrich-Hertz-Institute, Image Processing Department, Einsteinufer

More information

Self Organizing Maps: Fundamentals

Self Organizing Maps: Fundamentals Self Organizing Maps: Fundamentals Introduction to Neural Networks : Lecture 16 John A. Bullinaria, 2004 1. What is a Self Organizing Map? 2. Topographic Maps 3. Setting up a Self Organizing Map 4. Kohonen

More information

Problem-Based Group Activities for a Sensation & Perception Course. David S. Kreiner. University of Central Missouri

Problem-Based Group Activities for a Sensation & Perception Course. David S. Kreiner. University of Central Missouri -Based Group Activities for a Course David S. Kreiner University of Central Missouri Author contact information: David Kreiner Professor of Psychology University of Central Missouri Lovinger 1111 Warrensburg

More information

Eye movement trajectories and what they tell us

Eye movement trajectories and what they tell us Neuroscience and Biobehavioral Reviews 30 (2006) 666 679 www.elsevier.com/locate/neubiorev Review Eye movement trajectories and what they tell us Stefan Van der Stigchel *, Martijn Meeter, Jan Theeuwes

More information

RESEARCH ON SPOKEN LANGUAGE PROCESSING Progress Report No. 29 (2008) Indiana University

RESEARCH ON SPOKEN LANGUAGE PROCESSING Progress Report No. 29 (2008) Indiana University RESEARCH ON SPOKEN LANGUAGE PROCESSING Progress Report No. 29 (2008) Indiana University A Software-Based System for Synchronizing and Preprocessing Eye Movement Data in Preparation for Analysis 1 Mohammad

More information

Perception. T ake a dream. You are walking through the woods. In a clearing you come upon a marble. Learning Objectives C H A P T ER REVISED PAGES

Perception. T ake a dream. You are walking through the woods. In a clearing you come upon a marble. Learning Objectives C H A P T ER REVISED PAGES SMITMC02_0131825089.QXD 02/17/2006 07:12 PM Page 49 Perception C H A P T ER R2 Learning Objectives 1. What It Means to Perceive 2. How It Works: The Case of Visual Perception 2.1. The Structure of the

More information

Analecta Vol. 8, No. 2 ISSN 2064-7964

Analecta Vol. 8, No. 2 ISSN 2064-7964 EXPERIMENTAL APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS IN ENGINEERING PROCESSING SYSTEM S. Dadvandipour Institute of Information Engineering, University of Miskolc, Egyetemváros, 3515, Miskolc, Hungary,

More information

Bi 360: Midterm Review

Bi 360: Midterm Review Bi 360: Midterm Review Basic Neurobiology 1) Many axons are surrounded by a fatty insulating sheath called myelin, which is interrupted at regular intervals at the Nodes of Ranvier, where the action potential

More information

DYNAMIC PREDICTIONS: OSCILLATIONS AND SYNCHRONY IN TOP DOWN PROCESSING

DYNAMIC PREDICTIONS: OSCILLATIONS AND SYNCHRONY IN TOP DOWN PROCESSING DYNAMIC PREDICTIONS: OSCILLATIONS AND SYNCHRONY IN TOP DOWN PROCESSING Andreas K. Engel*, Pascal Fries and Wolf Singer Classical theories of sensory processing view the brain as a passive, stimulus-driven

More information

PS3019 Cognitive and Clinical Neuropsychology

PS3019 Cognitive and Clinical Neuropsychology PS3019 Cognitive and Clinical Neuropsychology Lectures 7 & 8 Dissociation between perception and action in brain damaged and healthy individuals Essential Reading - Goodale & Milner, Sight Unseen, Chapters

More information

CHAPTER 5 PREDICTIVE MODELING STUDIES TO DETERMINE THE CONVEYING VELOCITY OF PARTS ON VIBRATORY FEEDER

CHAPTER 5 PREDICTIVE MODELING STUDIES TO DETERMINE THE CONVEYING VELOCITY OF PARTS ON VIBRATORY FEEDER 93 CHAPTER 5 PREDICTIVE MODELING STUDIES TO DETERMINE THE CONVEYING VELOCITY OF PARTS ON VIBRATORY FEEDER 5.1 INTRODUCTION The development of an active trap based feeder for handling brakeliners was discussed

More information

2013- Postdoctoral Research Associate - Systems Neurobiology Laboratories, The Salk Institute. La Jolla, CA. Advisor: Edward M. Callaway, Ph.D.

2013- Postdoctoral Research Associate - Systems Neurobiology Laboratories, The Salk Institute. La Jolla, CA. Advisor: Edward M. Callaway, Ph.D. Bryan J. Hansen, Ph.D. Research Associate The Salk Institute Systems Neurobiology Laboratories 10010 North Torrey Pines Road La Jolla, CA 92037 Phone: 858-453-4100 x1073 Email: bhansen@salk.edu Website:

More information

Synaptic depression creates a switch that controls the frequency of an oscillatory circuit

Synaptic depression creates a switch that controls the frequency of an oscillatory circuit Proc. Natl. Acad. Sci. USA Vol. 96, pp. 8206 8211, July 1999 Neurobiology Synaptic depression creates a switch that controls the frequency of an oscillatory circuit FARZAN NADIM*, YAIR MANOR, NANCY KOPELL,

More information

A SPARSE CODING MODEL OF V1 PRODUCES SURROUND SUPPRESSION EFFECTS IN RESPONSE TO NATURAL SCENES

A SPARSE CODING MODEL OF V1 PRODUCES SURROUND SUPPRESSION EFFECTS IN RESPONSE TO NATURAL SCENES A SPARSE CODING MODEL OF V1 PRODUCES SURROUND SUPPRESSION EFFECTS IN RESPONSE TO NATURAL SCENES A Thesis Presented to The Academic Faculty by Allie Del Giorno In Partial Fulfillment of the Requirements

More information

MANAGING QUEUE STABILITY USING ART2 IN ACTIVE QUEUE MANAGEMENT FOR CONGESTION CONTROL

MANAGING QUEUE STABILITY USING ART2 IN ACTIVE QUEUE MANAGEMENT FOR CONGESTION CONTROL MANAGING QUEUE STABILITY USING ART2 IN ACTIVE QUEUE MANAGEMENT FOR CONGESTION CONTROL G. Maria Priscilla 1 and C. P. Sumathi 2 1 S.N.R. Sons College (Autonomous), Coimbatore, India 2 SDNB Vaishnav College

More information

Computer Networks and Internets, 5e Chapter 6 Information Sources and Signals. Introduction

Computer Networks and Internets, 5e Chapter 6 Information Sources and Signals. Introduction Computer Networks and Internets, 5e Chapter 6 Information Sources and Signals Modified from the lecture slides of Lami Kaya (LKaya@ieee.org) for use CECS 474, Fall 2008. 2009 Pearson Education Inc., Upper

More information

he "Prof' at the Department of Machine Intelligence and Perception at the University

he Prof' at the Department of Machine Intelligence and Perception at the University LEON GLASS Looking at Dots he "Prof' at the Department of Machine Intelligence and Perception at the University of Edinburgh, H. C. Longuet-Higgins, had just returned from a trip to the States where he

More information

E190Q Lecture 5 Autonomous Robot Navigation

E190Q Lecture 5 Autonomous Robot Navigation E190Q Lecture 5 Autonomous Robot Navigation Instructor: Chris Clark Semester: Spring 2014 1 Figures courtesy of Siegwart & Nourbakhsh Control Structures Planning Based Control Prior Knowledge Operator

More information

Vocabulary & General Concepts of Brain Organization

Vocabulary & General Concepts of Brain Organization Vocabulary & General Concepts of Brain Organization Jeanette J. Norden, Ph.D. Professor Emerita Vanderbilt University School of Medicine Course Outline Lecture 1: Vocabulary & General Concepts of Brain

More information