David Bodznick

Bio: David Bodznick is an academic researcher from Wesleyan University. The author has contributed to research in topics: Sensory system & Receptive field. The author has an hindex of 21, co-authored 32 publications receiving 1300 citations. Previous affiliations of David Bodznick include Marine Biological Laboratory.

The Generation and Subtraction of Sensory Expectations within Cerebellum-Like Structures

Abstract: The generation of expectations about sensory input and the subtraction of such expectations from actual input appear to be important features of sensory processing. This paper describes the generation

Adaptive mechanisms in the elasmobranch hindbrain

Abstract: The suppression of self-generated electrosensory noise (reafference) and other predictable signals in the elasmobranch medulla is accomplished in part by an adaptive filter mechanism, which now appears to represent a more universal form of the modifiable efference copy mechanism discovered by Bell. It also exists in the gymnotid electrosensory lateral lobe and mechanosensory lateral line nucleus in other teleosts. In the skate dorsal nucleus, motor corollary discharge, proprioceptive and descending electrosensory signals all contribute in an independent and additive fashion to a cancellation input to the projection neurons that suppresses their response to reafference. The form of the cancellation signal is quite stable and apparently well-preserved between bouts of a particular behavior, but it can also be modified within minutes to match changes in the form of the reafference associated with that behavior. Motor corollary discharge, proprioceptive and electrosensory inputs are each relayed to the dorsal nucleus from granule cells of the vestibulolateral cerebellum. Direct evidence from intracellular studies and direct electrical stimulation of the parallel fiber projection support an adaptive filter model that places a principal site of the filter's plasticity at the synapses between parallel fibers and projection neurons.

Signals and noise in the elasmobranch electrosensory system

Abstract: Analyzing signal and noise for any sensory system requires an appreciation of the biological and physical milieu of the animal. Behavioral studies show that elasmobranchs use their electrosensory systems extensively for prey detection, but also for mate recognition and possibly for navigation. These biologically important signals are detected against a background of self-generated bioelectric fields. Noise-suppression mechanisms can be recognized at a number of different levels: behavior, receptor anatomy and physiology, and at the early stages of sensory processing. The peripheral filters and receptor characteristics provide a detector with permissive temporal properties but restrictive spatial characteristics. Biologically important signals probably cover the range from direct current to 10 Hz, whereas the bandwidth of the receptors is more like 0.1-10 Hz. This degree of alternating current coupling overcomes significant noise problems while still allowing the animal to detect external direct current signals by its own movement. Self-generated bioelectric fields modulated by breathing movement have similar temporal characteristics to important external signals and produce very strong modulation of electrosensory afferents. This sensory reafference is essentially similar, or common-mode, across all afferent fibers. The principal electrosensory neurons (ascending efferent neurons; AENs) of the dorsal octavolateralis nucleus show a greatly reduced response to common-mode signals. This suppression is mediated by the balanced excitatory and inhibitory components of their spatial receptive fields. The receptive field characteristics of AENs determine the information extracted from external stimuli for further central processing.

Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects.

Abstract: We describe a model of visual processing in which feedback connections from a higher- to a lower- order visual cortical area carry predictions of lower-level neural activities, whereas the feedforward connections carry the residual errors between the predictions and the actual lower-level activities. When exposed to natural images, a hierarchical network of model neurons implementing such a model developed simple-cell-like receptive fields. A subset of neurons responsible for carrying the residual errors showed endstopping and other extra-classical receptive-field effects. These results suggest that rather than being exclusively feedforward phenomena, nonclassical surround effects in the visual cortex may also result from cortico-cortical feedback as a consequence of the visual system using an efficient hierarchical strategy for encoding natural images.

Neuronal coding of prediction errors.

Abstract: Associative learning enables animals to anticipate the occurrence of important outcomes. Learning occurs when the actual outcome differs from the predicted outcome, resulting in a prediction error. Neurons in several brain structures appear to code prediction errors in relation to rewards, punishments, external stimuli, and behavioral reactions. In one form, dopamine neurons, norepinephrine neurons, and nucleus basalis neurons broadcast prediction errors as global reinforcement or teaching signals to large postsynaptic structures. In other cases, error signals are coded by selected neurons in the cerebellum, superior colliculus, frontal eye fields, parietal cortex, striatum, and visual system, where they influence specific subgroups of neurons. Prediction errors can be used in postsynaptic structures for the immediate selection of behavior or for synaptic changes underlying behavioral learning. The coding of prediction errors may represent a basic mode of brain function that may also contribute to the processing of sensory information and the short-term control of behavior.

The emulation theory of representation: motor control, imagery, and perception.

Abstract: The emulation theory of representation is developed and explored as a framework that can revealingly synthesize a wide vari- ety of representational functions of the brain. The framework is based on constructs from control theory (forward models) and signal processing (Kalman filters). The idea is that in addition to simply engaging with the body and environment, the brain constructs neural circuits that act as models of the body and environment. During overt sensorimotor engagement, these models are driven by efference copies in parallel with the body and environment, in order to provide expectations of the sensory feedback, and to enhance and process sensory information. These models can also be run off-line in order to produce imagery, estimate outcomes of different actions, and eval- uate and develop motor plans. The framework is initially developed within the context of motor control, where it has been shown that inner models running in parallel with the body can reduce the effects of feedback delay problems. The same mechanisms can account for motor imagery as the off-line driving of the emulator via efference copies. The framework is extended to account for visual imagery as the off-line driving of an emulator of the motor-visual loop. I also show how such systems can provide for amodal spatial imagery. Per- ception, including visual perception, results from such models being used to form expectations of, and to interpret, sensory input. I close by briefly outlining other cognitive functions that might also be synthesized within this framework, including reasoning, theory of mind phenomena, and language.

The emulation theory of representation: Motor control, imagery, and perception - eScholarship

Abstract: The emulation theory of representation is developed and explored as a framework that can revealingly synthesize a wide variety of representational functions of the brain. The framework is based on constructs from control theory (forward models) and signal processing (Kalman filters). The idea is that in addition to simply engaging with the body and environment, the brain constructs neural circuits that act as models of the body and environment. During overt sensorimotor engagement, these models are driven by efference copies in parallel with the body and environment, in order to provide expectations of the sensory feedback, and to enhance and process sensory information. These models can also be run off-line in order to produce imagery, estimate outcomes of different actions, and evaluate and develop motor plans. The framework is initially developed within the context of motor control, where it has been shown that inner models running in parallel with the body can reduce the effects of feedback delay problems. The same mechanisms can account for motor imagery as the off-line driving of the emulator via efference copies. The framework is extended to account for visual imagery as the off-line driving of air emulator of the motor-visual loop. I also show how such systems can provide for amodal spatial imagery. Perception, including visual perception, results from such models being used to form expectations of, and to interpret, sensory input. I close by briefly outlining other cognitive functions that might also be synthesized within this framework, including reasoning, theory of mind phenomena, and language.

Cerebellar Long-Term Depression: Characterization, Signal Transduction, and Functional Roles

Abstract: Cerebellar Purkinje cells exhibit a unique type of synaptic plasticity, namely, long-term depression (LTD). When two inputs to a Purkinje cell, one from a climbing fiber and the other from a set of...