Biomedical subjects

S Grossberg

Publications and source records attributed to S Grossberg.

At least 55 records · Page 3Linked to original sources

PubMed1997

A neural model of multimodal adaptive saccadic eye movement control by superior colliculus.

How does the saccadic movement system select a target when visual, auditory, and planned movement commands differ? How do retinal, head-centered, and motor error coordinates interact during the selection process? Recent data on superior colliculus (SC) reveal a spreading wave of activation across buildup cells the peak activity of which covaries with the current gaze error. In contrast, the locus of peak activity remains constant at burst cells, whereas their activity level decays with residual gaze error. A neural model answers these questions and simulates burst and buildup responses in visual, overlap, memory, and gap tasks. The model also simulates data on multimodal enhancement and suppression of activity in the deeper SC layers and suggests a functional role for NMDA receptors in this region. In particular, the model suggests how auditory and planned saccadic target positions become aligned and compete with visually reactive target positions to select a movement command. For this to occur, a transformation between auditory and planned head-centered representations and a retinotopic target representation is learned. Burst cells in the model generate teaching signals to the spreading wave layer. Spreading waves are produced by corollary discharges that render planned and visually reactive targets dimensionally consistent and enable them to compete for attention to generate a movement command in motor error coordinates. The attentional selection process also helps to stabilize the map-learning process. The model functionally interprets cells in the superior colliculus, frontal eye field, parietal cortex, mesencephalic reticular formation, paramedian pontine reticular formation, and substantia nigra pars reticulata.

Animals↗

PubMed1997

Neural control of interlimb oscillations. I. Human bimanual coordination.

How do humans and other animals accomplish coordinated movements? How are novel combinations of limb joints rapidly assembled into new behavioral units that move together in in-phase or anti-phase movement patterns during complex movement tasks? A neural central pattern generator (CPG) model simulates data from human bimanual coordination tasks. As in the data, anti-phase oscillations at low frequencies switch to in-phase oscillations at high frequencies, in-phase oscillations occur at both low and high frequencies, phase fluctuations occur at the anti-phase in-phase transition, a "seagull effect" of larger errors occurs at intermediate phases, and oscillations slip toward in-phase and anti-phase when driven at intermediate phases. These oscillations and bifurcations are emergent properties of the CPG model in response to volitional inputs. The CPG model is a version of the Ellias-Grossberg oscillator. Its neurons obey Hodgkin-Huxley type equations whose excitatory signals operate on a faster time scale than their inhibitory signals in a recurrent on-center off-surround anatomy. When an equal command or GO signal activates both model channels, the model CPG can generate both in-phase and anti-phase oscillations at different GO amplitudes. Phase transitions from either in-phase to anti-phase oscillations, or from anti-phase to in-phase oscillations, can occur in different parameter ranges, as the GO signal increases.

Extremities↗

PubMed1997

Neural control of interlimb oscillations. II. Biped and quadruped gaits and bifurcations.

Behavioral data concerning animal and human gaits and gait transitions are simulated as emergent properties of a central pattern generator (CPG) model. The CPG model is a version of the Ellias-Grossberg oscillator. Its neurons obey Hodgkin-Huxley type equations whose excitatory signals operate on a faster time scale than their inhibitory signals in a recurrent on-center off-surround anatomy. A descending command or GO signal activates the gaits and triggers gait transitions as its amplitude increases. A single model CPG can generate both in-phase and anti-phase oscillations at different GO amplitudes. Phase transitions from either in-phase to anti-phase oscillations or from anti-phase to in-phase oscillations can occur in different parameter ranges, as the GO signal increases. Quadruped vertebrate gaits, including the amble, the walk, all three pairwise gaits (trot, pace, and gallop), and the pronk are simulated using this property. Rapid gait transitions are simulated in the order--walk, trot, pace, and gallop--that occurs in the cat, along with the observed increase in oscillation frequency. Precise control of quadruped gait switching uses GO-dependent modulation of inhibitory interactions, which generates a different functional anatomy at different arousal levels. The primary human gaits (the walk and the run) and elephant gaits (the amble and the walk) are simulated, without modulation, by oscillations with the same phase relationships but different waveform shapes at different GO signal levels, much as the duty cycles of the feet are longer in the walk than in the run. Relevant neural data from spinal cord, globus pallidus, and motor cortex, among other structures, are discussed.

Animals↗

PubMed1997

Contour integration across polarities and spatial gaps: from local contrast filtering to global grouping.

This article introduces an experimental paradigm to selectively probe the multiple levels of visual processing that influence the formation of object contours, perceptual boundaries, and illusory contours. The experiments test the assumption that, to integrate contour information across space and contrast sign, a spatially short-range filtering process that is sensitive to contrast polarity inputs to a spatially long-range grouping process that pools signals from opposite contrast polarities. The stimuli consisted of thin subthreshold lines, flashed upon gaps between collinear inducers which potentially enable the formation of illusory contours. The subthreshold lines were composed of one or more segments with opposite contrast polarities. The polarity nearest to the inducers was varied to differentially excite the short-range filtering process. The experimental results are consistent with neurophysiological evidence for cortical mechanisms of contour processing and with the Boundary Contour System model, which identifies the short-range filtering process with cortical simple cells, and the long-range grouping process with cortical bipole cells.

Contrast Sensitivity↗

PubMed1997

A neural model of high-level motion processing: line motion and formotion dynamics.

The percepts known variously as the line motion illusion, motion induction, and transformational apparent motion have attracted a great deal of experimental interest, since they sensitively probe interactions between preattentive and attentive vision processes. The present article develops a neural model that qualitatively explains essentially all the data reported thus far, and quantitatively simulates key illustrative percepts. The model suggests how these data arise from neural mechanisms of preattentive boundary and surface formation, long-range apparent motion, formotion interactions, and spatial attention. The boundary and surface formation processes model aspects of the interblob V1-->interstripe V2-->V4 and blob V1-->thin stripe V2-->V4 cortical processing streams, respectively. The long-range apparent motion process models aspects of the V1-->MT-->MST processing stream. An interstream V2-->MT form-motion interaction is proposed to allow the motion processing stream to track transient properties of emergent boundaries and filled-in surface colors from the form processing stream. It does so by generating motion waves using the long-range apparent motion process. This interstream interaction controls the formation of form-motion percepts, which are herein called formotion percepts. Other transients directly cause motion waves within the motion processing stream. All the data are attributed to properties of such motion waves. It is also suggested how bottom-up motion mechanisms can engage top-down attention as part of the motion capture process that solves the aperture problem. This interaction is proposed to occur between areas MT and MST. The model hereby explains how attention can be engaged even in percepts whose explanation can be derived from preattentive mechanisms.

Attention↗

PubMed1997

Visual brain and visual perception: how does the cortex do perceptual grouping?

How the brain generates visual percepts is a central problem in neuroscience. We propose a detailed neural model of how lateral geniculate nuclei and the interblob cortical stream through V1 and V2 generate context-sensitive perceptual groupings from visual inputs. The model suggests a functional role for cortical layers, columns, maps and networks, and proposes homologous circuits for V1 and V2 with larger-scale processing in V2. An integrated treatment of interlaminar, horizontal, orientational and endstopping cortical interactions and a role for corticogeniculate feedback in grouping are proposed. Modeled circuits simulate parametric psychophysical data about boundary grouping and illusory contour formation.

Animals↗

PubMed1997

Neural dynamics of variable-rate speech categorization.

What is the neural representation of a speech code as it evolves in time? A neural model simulates data concerning segregation and integration of phonetic percepts. Hearing two phonetically related stops in a VC-CV pair (V = vowel; C = consonant) requires 150 ms more closure time than hearing two phonetically different stops in a VC1-C2V pair. Closure time also varies with long-term stimulus rate. The model simulates rate-dependent category boundaries that emerge from feedback interactions between a working memory for short-term storage of phonetic items and a list categorization network for grouping sequences of items. The conscious speech code is a resonant wave. It emerges after bottom-up signals from the working memory select list chunks which read out top-down expectations that amplify and focus attention on consistent working memory items. In VC1-C2V pairs, resonance is reset by mismatch of C2 with the C1 expectation. In VC-CV pairs, resonance prolongs a repeated C.

Computer Simulation↗

PubMed1997

Cortical dynamics of three-dimensional figure-ground perception of two-dimensional pictures.

This article develops the FACADE theory of 3-dimensional (3-D) vision and figure-ground separation to explain data concerning how 2-dimensional pictures give rise to 3-D percepts of occluding and occluded objects. The model describes how geometrical and contrastive properties of a picture can either cooperate or compete when forming the boundaries and surface representation that subserve conscious percepts. Spatially long-range cooperation and spatially short-range competition work together to separate the boundaries of occluding figures from their occluded neighbors. This boundary ownership process is sensitive to image T junctions at which occluded figures contact occluding figures. These boundaries control the filling-in of color within multiple depth-sensitive surface representations. Feedback between surface and boundary representations strengthens consistent boundaries while inhibiting inconsistent ones. Both the boundary and the surface representations of occluded objects may be amodally completed, while the surface representations of unoccluded objects become visible through modal completion. Functional roles for conscious modal and amodal representations in object recognition, spatial attention, and reaching behaviors are discussed. Model interactions are interpreted in terms of visual, temporal, and parietal cortices.

Attention↗

PubMed1997

Selective switch between latency and lytic replication of Kaposi's sarcoma herpesvirus and Epstein-Barr virus in dually infected body cavity lymphoma cells.

The BC-1 cell line, derived from a body cavity-based, B-cell lymphoma, is dually infected with Epstein-Barr virus (EBV) and Kaposi's sarcoma-associated herpesvirus (KSHV). In these studies, the relationships between these two gammaherpesviruses and BC-1 cells were characterized and compared. Single-cell cloning experiments suggested that all BC-1 cells contain both genomes. In more than 98% of cells, both viruses were latent. The two viruses could be differentially induced into their lytic cycles by chemicals. EBV was activated into DNA replication and late-gene expression by the phorbol ester tetradecanoyl phorbol acetate (TPA). KSHV was induced into DNA replication and late-gene expression by n-butyrate. Amplification of both EBV and KSHV DNAs was inhibited by phosphonoacetic acid. Induction of the KSHV lytic cycle by n-butyrate was accompanied by the disappearance of host-cell beta-actin mRNA. Induction of EBV by TPA was not accompanied by such an effect on host-cell gene expression. Induction of the KSHV lytic cycle by n-butyrate was associated with the expression of several novel polypeptides. Recognition of one of these, p40, served as the basis of development of an assay for antibodies to KSHV in the sera of infected patients. BC-1 cells released infectious EBV; however, there was no evidence for the release of encapsidated KSHV genomes by BC-1 cells, even though n-butyrate-treated cells contained numerous intranuclear nucleocapsids. The differential inducibility of these two herpesviruses in the same cell line points to the importance of viral factors in the switch from latency to lytic cycle.

Animals↗

PubMed1996

Metabotropic glutamate receptor activation in cerebellar Purkinje cells as substrate for adaptive timing of the classically conditioned eye-blink response.

To understand how the cerebellum adaptively times the classically conditioned nictitating membrane response (NMR), a model of the metabotropic glutamate receptor (mGluR) second messenger system in cerebellar Purkinje cells is constructed. In the model, slow responses, generated postsynaptically by mGluR-mediated phosphoinositide hydrolysis and calcium release from intracellular stores, bridge the interstimulus interval (ISI) between the onset of parallel fiber activity associated with the conditioned stimulus (CS) and climbing fiber activity associated with unconditioned stimulus (US) onset. Temporal correlation of metabotropic responses and climbing fiber signals produces persistent phosphorylation of both AMPA receptors and Ca(2+)-dependent K+ channels. This is responsible for long-term depression (LTD) of AMPA receptors. The phosphorylation of Ca(2+)-dependent K+ channels leads to a reduction in baseline membrane potential and a reduction of Purkinje cell population firing during the CS-US interval. The Purkinje cell firing decrease disinhibits cerebellar nuclear cells, which then produce an excitatory response corresponding to the learned movement. Purkinje cell learning times the response, whereas nuclear cell learning can calibrate it. The model reproduces key features of the conditioned rabbit NMR: Purkinje cell population response is timed properly; delay conditioning occurs for ISIs of up to 4 sec, whereas trace conditioning occurs only at shorter ISIs; mixed training at two different ISIs produces a double-peaked response; and ISIs of 200-400 msec produce maximal responding. Biochemical similarities between timed cerebellar learning and photoreceptor transduction, and circuit similarities between the timed cerebellar circuit and a timed dentate-CA3 hippocampal circuit, are noted.

Animals↗

PubMed1996

Cortical dynamics of form and motion integration: persistence, apparent motion, and illusory contours.

How does the visual system generate percepts of moving forms? How does this happen when the forms are emergent percepts, such as illusory contours or segregated textures, and the motion percept is apparent motion between the emergent forms? We develop a neural model of form-motion interactions to explain and simulate parametric properties of psychophysical motion data and to make predictions about how the parallel cortical processing streams V1-->MT and V1-->V2-->MT control form-motion interactions. The model explains how an illusory contour can move in apparent motion to another illusory contour or to a luminance-derived contour; how illusory contour persistence relates to the upper interstimulus interval (ISI) threshold for apparent motion; and how upper and lower ISI thresholds for seeing apparent motion between two flashes decrease with stimulus duration and narrow with spatial separation (Korte's laws). The model accounts for these data by suggesting how the persistence of a boundary segmentation in the V1-->V2 processing stream influences the quality of apparent motion in the V1-->MT stream through V2-->MT interactions. These data may all be explained by an analysis of how orientationally tuned form perception mechanisms and directionally tuned motion perception mechanisms interact.

Contrast Sensitivity↗

PubMed1996

Cortical dynamics of boundary segmentation and reset: persistence, afterimages, and residual traces.

In previous work with a neural-network model of boundary segmentation and reset, the percept of persistence was linked to the duration of a boundary segmentation after stimulus offset. In particular, the model simulated the decrease of persistence duration with an increase in stimulus duration and luminance. Further evidence is revealed for the neural mechanisms involved in the theory. Simulations show that the model reset signals generate orientational afterimages, such as the MacKay effect, when the reset signals can be grouped by a subsequent boundary segmentation that generates illusory contours through them. Simulations also show that the same mechanisms explain properties of residual traces, which increase in duration with stimulus duration and luminance. The model hereby discloses previously unsuspected mechanistic links between data about persistence and afterimages, and helps to clarify the sometimes controversial issues surrounding distinctions between persistence, residual traces, and afterimages.

Afterimage↗

PubMed1995

A spectral network model of pitch perception.

A model of pitch perception, called the spatial pitch network or SPINET model, is developed and analyzed. The model neurally instantiates ideas from the spectral pitch modeling literature and joins them to basic neural network signal processing designs to stimulate a broader range of perceptual pitch data than previous spectral models. The components of the model are interpreted as peripheral mechanical and neural processing stages, which are capable of being incorporated into a larger network architecture for separating multiple sound sources in the environment. The core of the new model transforms a spectral representation of an acoustic source into a spatial distribution of pitch strengths. The SPINET model uses a weighted "harmonic sieve" whereby the strength of activation of a given pitch depends upon a weighted sum of narrow regions around the harmonics of the nominal pitch value, and higher harmonics contribute less to a pitch than lower ones. Suitably chosen harmonic weighting functions enable computer simulations of pitch perception data involving mistuned components, shifted harmonics, and various types of continuous spectra including rippled noise. It is shown how the weighting functions produce the dominance region, how they lead to octave shifts of pitch in response to ambiguous stimuli, and how they lead to a pitch region in response to the octave-spaced Shepard tone complexes and Deutsch tritones without the use of attentional mechanisms to limit pitch choices. An on-center off-surround network in the model helps to produce noise suppression, partial masking, and edge pitch. Finally, it is shown how peripheral filtering and short-term energy measurements produce a model pitch estimate that is sensitive to certain component phase relationships.

Cochlea↗

PubMed1994

Cortical dynamics of feature binding and reset: control of visual persistence.

An analysis of the reset of visual cortical circuits responsible for the binding or segmentation of visual features into coherent visual forms yields a model that explains properties of visual persistence. The reset mechanisms prevent massive smearing of visual percepts in response to rapidly moving images. The model simulates relationships among psychophysical data showing inverse relations of persistence to flash luminance and duration, greater persistence of illusory contours than real contours, a U-shaped temporal function for persistence of illusory contours, a reduction of persistence due to adaptation with a stimulus of like orientation, an increase of persistence with spatial separation of a masking stimulus. The model suggests that a combination of habituative, opponent, and endstopping mechanisms prevent smearing and limit persistence. Earlier work with the model has analyzed data about boundary formation, texture segregation, shape-from-shading, and figure-ground separation. Thus, several types of data support each model mechanism and new predictions are made.

Adaptation, Ocular↗

PubMed1994

A neural theory of attentive visual search: interactions of boundary, surface, spatial, and object representations.

Visual search data are given a unified quantitative explanation by a model of how spatial maps in the parietal cortex and object recognition categories in the inferotemporal cortex deploy attentional resources as they reciprocally interact with visual representations in the prestriate cortex. The model visual representations are organized into multiple boundary and surface representations. Visual search in the model is initiated by organizing multiple items that lie within a given boundary or surface representation into a candidate search grouping. These items are compared with object recognition categories to test for matches or mismatches. Mismatches can trigger deeper searches and recursive selection of new groupings until a target object is identified. The model provides an alternative to Feature Integration and Guided Search models.

Algorithms↗

PubMed1994

3-D vision and figure-ground separation by visual cortex.

A neural network theory of three-dimensional (3-D) vision, called FACADE theory, is described. The theory proposes a solution of the classical figure-ground problem for biological vision. It does so by suggesting how boundary representations and surface representations are formed within a boundary contour system (BCS) and a feature contour system (FCS). The BCS and FCS interact reciprocally to form 3-D boundary and surface representations that are mutually consistent. Their interactions generate 3-D percepts wherein occluding and occluded object parts are separated, completed, and grouped. The theory clarifies how preattentive processes of 3-D perception and figure-ground separation interact reciprocally with attentive processes of spatial localization, object recognition, and visual search. A new theory of stereopsis is proposed that predicts how cells sensitive to multiple spatial frequencies, disparities, and orientations are combined by context-sensitive filtering, competition, and cooperation to form coherent BCS boundary segmentations. Several factors contribute to figure-ground pop-out, including: boundary contrast between spatially contiguous boundaries, whether due to scenic differences in luminance, color, spatial frequency, or disparity; partially ordered interactions from larger spatial scales and disparities to smaller scales and disparities; and surface filling-in restricted to regions surrounded by a connected boundary. Phenomena such as 3-D pop-out from a 2-D picture, Da Vinci stereopsis, 3-D neon color spreading, completion of partially occluded objects, and figure-ground reversals are analyzed. The BCS and FCS subsystems model aspects of how the two parvocellular cortical processing streams that join the lateral geniculate nucleus to prestriate cortical area V4 interact to generate a multiplexed representation of Form-And-Color-And-DEpth, or FACADE, within area V4. Area V4 is suggested to support figure-ground separation and to interact with cortical mechanisms of spatial attention, attentive object learning, and visual search. Adaptive resonance theory (ART) mechanisms model aspects of how prestriate visual cortex interacts reciprocally with a visual object recognition system in inferotemporal (IT) cortex for purposes of attentive object learning and categorization. Object attention mechanisms of the What cortical processing stream through IT cortex are distinguished from spatial attention mechanisms of the Where cortical processing stream through parietal cortex. Parvocellular BCS and FCS signals interact with the model What stream. Parvocellular FCS and magnocellular motion BCS signals interact with the model Where stream.(ABSTRACT TRUNCATED AT 400 WORDS)

Depth Perception↗

PubMed1993

Neural representations for sensory-motor control, I: Head-centered 3-D target positions from opponent eye commands.

This article describes how corollary discharges from outflow eye movement commands can be transformed by two stages of opponent neural processing into a head-centered representation of 3-D target position. This representation implicitly defines a cyclopean coordinate system whose variables approximate the binocular vergence and spherical horizontal and vertical angles with respect to the observer's head. Various psychophysical data concerning binocular distance perception and reaching behavior are clarified by this representation. The representation provides a foundation for learning head-centered and body-centered invariant representations of both foveated and non-foveated 3-D target positions. It also enables a solution to be developed of the classical motor equivalence problem, whereby many different joint configurations of a redundant manipulator can all be used to realize a desired trajectory in 3-D space.

Brain↗

PubMed1993

Normal and amnesic learning, recognition and memory by a neural model of cortico-hippocampal interactions.

The processes by which humans and other primates learn to recognize objects have been the subject of many models. Processes such as learning, categorization, attention, memory search, expectation and novelty detection work together at different stages to realize object recognition. In this article, Gail Carpenter and Stephen Grossberg describe one such class of model (Adaptive Resonance Theory, ART) and discuss how its structure and function might relate to known neurological learning and memory processes, such as how infero-temporal cortex can recognize both specialized and abstract information, and how medial temporal amnesia might be caused by lesions in the hippocampal formation. This model also suggests how hippocampal and inferotemporal processing might be linked during recognition learning.

Amnesia↗