Indirect synaptic inputs from filiform hair sensory neurons contribute to the receptive fields of giant interneurons in the first-instar cockroach

1998 ◽  
Vol 183 (4) ◽  
pp. 467-476 ◽  
Author(s):  
E. S. Hill ◽  
J. M. Blagburn
Keyword(s):  
Sensory Neurons ◽  
Receptive Fields ◽  
Synaptic Inputs ◽  
Giant Interneurons ◽  
First Instar ◽  
Filiform Hair

Regeneration of cercal filiform hair sensory neurons in the first-instar cockroach restores escape behavior

1997 ◽  
Vol 33 (4) ◽  
pp. 439-458 ◽  
Author(s):  
Michael Stern ◽  
Vernita L. Ediger ◽  
Charles R. Gibbon ◽  
Jonathan M. Blagburn ◽  
Jonathan P. Bacon
Keyword(s):  
Sensory Neurons ◽  
Escape Behavior ◽  
First Instar ◽  
Filiform Hair

Ectopic sensory neurons in mutant cockroaches compete with normal cells for central targets

Development ◽  
1992 ◽  
Vol 115 (3) ◽  
pp. 773-784
Author(s):  
J.P. Bacon ◽  
J.M. Blagburn
Keyword(s):  
Sensory Neurons ◽  
Periplaneta Americana ◽  
Normal Development ◽  
Lateral Position ◽  
Competitive Interactions ◽  
Afferent Neuron ◽  
Synaptic Connections ◽  
First Instar ◽  
Terminal Ganglion ◽  
Filiform Hair

The cercus of the first instar cockroach, Periplaneta americana, bears two filiform hairs, lateral (L) and medial (M), each of which is innervated by a single sensory neuron. These project into the terminal ganglion of the CNS where they make synaptic connections with a number of ascending interneurons. We have discovered mutant animals that have more hairs on the cercus; the most typical phenotype, called “Space Invader” (SI), has an extra filiform hair in a proximo-lateral position on one of the cerci. The afferent neuron of this supernumerary hair (SIN) “invades the space” occupied by L in the CNS and makes similar synaptic connections to giant interneurons (GIs). SIN and L compete for these synaptic targets: the size of the L EPSP in a target interneuron GI3 is significantly reduced in the presence of SIN. Morphometric analysis of the L afferent in the presence or absence of SIN shows no anatomical concomitant of competition. Ablation of L afferent allows SIN to increase the size of its synaptic input to GI3. Less frequently in the mutant population, we find animals with a supernumerary medical (SuM) sensillum. Its afferent projects to the same neuropilar region as the M afferent, makes the same set of synaptic connections to GIs, and competes with M for these synaptic targets. The study of these competitive interactions between identified afferents and identified target interneurons reveals some of the dynamic processes that go on in normal development to shape the nervous system.

Synesthetic Binding and the Reactivation Model of Memory

2017 ◽  
Author(s):  
Berit Brogaard
Keyword(s):  
Sensory Neurons ◽  
Memory Retrieval ◽  
Brain Activity ◽  
Receptive Fields ◽  
Memory Model ◽  
Multisensory Perception ◽  
Feedback Mechanisms

Despite the recent surge in research on, and interest in, synesthesia, the mechanism underlying this condition is still unknown. Feedforward mechanisms involving overlapping receptive fields of sensory neurons as well as feedback mechanisms involving a lack of signal disinhibition have been proposed. Here I show that a broad range of studies of developmental synesthesia indicate that the mechanism underlying the phenomenon may in some cases involve the reinstatement of brain activity in sensory or cognitive streams in a way that is similar to what happens during memory retrieval of semantically associated items. In the chapter’s final sections I look at the relevance of synesthesia research, given the memory model, to our understanding of multisensory perception and common mapping patterns.

Leech Mechanosensation

2017 ◽  
Author(s):  
Brian D. Burrell
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Sensory Neurons ◽  
Receptive Fields ◽  
Model Systems ◽  
Sensory Cells ◽  
Mechanical Stimuli ◽  
Nociceptive Neurons ◽  
Mechanosensory Neurons ◽  
The Central Nervous System

The medicinal leech (Hirudo verbana) is an annelid (segmented worm) and one of the classic model systems in neuroscience. It has been used in research for over 50 years and was one of the first animals in which intracellular recordings of mechanosensory neurons were carried out. Remarkably, the leech has three main classes of mechanosensory neurons that exhibit many of the same properties found in vertebrates. The most sensitive of these neurons are the touch cells, which are rapidly adapting neurons that detect low-intensity mechanical stimuli. Next are the pressure cells, which are slow-adapting sensory neurons that respond to higher intensity, sustained mechanostimulation. Finally, there are nociceptive neurons, which have the highest threshold and respond to potentially damaging mechanostimuli, such as a pinch. As observed in mammals, the leech has separate mechanosensitive and polymodal nociceptors, the latter responding to mechanical, thermal, and chemical stimuli. The cell bodies for all three types of mechanosensitive neurons are found in the central nervous system where they are arranged as bilateral pairs. Each neuron extends processes to the skin where they form discrete receptive fields. In the touch and pressure cells, these receptive fields are arranged along the dorsal-ventral axis. For the mechano-only and polymodal nociceptive neurons, the peripheral receptive fields overlap with the mechano-only nociceptor, which also innervates the gut. The leech also has a type of mechanosensitive cell located in the periphery that responds to vibrations in the water and is used, in part, to detect potential prey nearby. In the central nervous system, the touch, pressure, and nociceptive cells all form synaptic connections with a variety of motor neurons, interneurons, and even each other, using glutamate as the neurotransmitter. Synaptic transmission by these cells can be modulated by a variety of activity-dependent processes as well as the influence of neuromodulatory transmitters, such as serotonin. The output of these sensory neurons can also be modulated by conduction block, a process in which action potentials fail to propagate to all the synaptic release sites, decreasing synaptic output. Activity in these sensory neurons leads to the initiation of a number of different motor behaviors involved in locomotion, such as swimming and crawling, as well as behaviors designed to recoil from aversive/noxious stimuli, such as local bending and shortening. In the case of local bending, the leech is able to bend in the appropriate direction away from the offending stimuli. It does so through a combination of which mechanosensory cell receptive fields have been activated and the relative activation of multiple sensory cells decoded by a layer of downstream interneurons.

scholarly journals The accuracy of membrane potential reconstruction based on spiking receptive fields

2012 ◽  
Vol 107 (8) ◽  
pp. 2143-2153 ◽  
Author(s):  
Deepankar Mohanty ◽  
Benjamin Scholl ◽  
Nicholas J. Priebe
Keyword(s):  
Membrane Potential ◽  
Receptive Fields ◽  
Sensory Stimulation ◽  
Spike Rate ◽  
Rate Data ◽  
Noise Stimulus ◽  
Synaptic Inputs ◽  
Common Technique ◽  
The Relationship ◽  
Membrane Potential Fluctuations

A common technique used to study the response selectivity of neurons is to measure the relationship between sensory stimulation and action potential responses. Action potentials, however, are only indirectly related to the synaptic inputs that determine the underlying, subthreshold, response selectivity. We present a method to predict membrane potential, the measurable result of the convergence of synaptic inputs, based on spike rate alone and then test its utility by comparing predictions to actual membrane potential recordings from simple cells in primary visual cortex. Using a noise stimulus, we found that spike rate receptive fields were in precise correspondence with membrane potential receptive fields ( R2 = 0.74). On average, spike rate alone could predict 44% of membrane potential fluctuations to dynamic noise stimuli, demonstrating the utility of this method to extract estimates of subthreshold responses. We also found that the nonlinear relationship between membrane potential and spike rate could also be extracted from spike rate data alone by comparing predictions from the noise stimulus with the actual spike rate. Our analysis reveals that linear receptive field models extracted from noise stimuli accurately reflect the underlying membrane potential selectivity and thus represent a method to generate estimates of the underlying average membrane potential from spike rate data alone.

scholarly journals An offset ON-OFF receptive field is created by gap junctions between distinct types of retinal ganglion cells

2020 ◽  
Author(s):  
Sam Cooler ◽  
Gregory W. Schwartz
Keyword(s):  
Retinal Ganglion Cells ◽  
Ganglion Cells ◽  
Cell Model ◽  
Receptive Fields ◽  
Visual Space ◽  
Retinal Ganglion ◽  
Precise Location ◽  
Synaptic Inputs ◽  
Retinotopic Maps ◽  
Edge Location

SummaryReceptive fields (RFs) are a foundational concept in sensory neuroscience. The RF of a sensory neuron is shaped by the properties of its synaptic inputs from connected neurons. In the early visual system, retinotopic maps define a strict relationship between the location of a cell’s dendrites and its RF location in visual space1–3. Retinal ganglion cells (RGCs), the output cells of the retina, form dendritic mosaics that tile retinal space and have corresponding RF mosaics that tile visual space1,2. The precise location of dendrites in some RGCs has been shown to predict their RF shape4. Previously described ON-OFF RGCs have aligned dendrites in ON and OFF synaptic layers, so the cells respond to increments and decrements of light at the same locations in visual space5–8. Here we report a systematic offset between the ON and OFF RFs of an RGC type. Surprisingly, this property does not come from offset ON and OFF dendrites but instead arises from electrical synapses with RGCs of a different type. This circuit represents a new channel for direct communication between ON and OFF RGCs. Using a multi-cell model, we find that offset ON-OFF RFs could improve the precision with which edge location is represented in an RGC population.

Responses of lumbosacral spinal units to mechanical stimuli related to analysis of lordosis reflex in female rats

1980 ◽  
Vol 43 (1) ◽  
pp. 27-45 ◽  
Author(s):  
L. M. Kow ◽  
F. P. Zemlan ◽  
D. W. Pfaff
Keyword(s):  
Sensory Neurons ◽  
Single Unit ◽  
Receptive Fields ◽  
Female Rats ◽  
Mechanical Stimuli ◽  
Firing Rates ◽  
Mixed Response ◽  
Spinal Segments ◽  
Necessary And Sufficient ◽  
Gray Units

1. To analyze further the sensory mechanisms for triggering the lordosis reflex, single-unit (n = 345) activity was recorded extracellularly from spinal segments L5-S1 of urethan-anesthetized female rats. Unit responses to pressure on the skin (necessary and sufficient for evoking lordosis) and other mechanical stimuli were studied. 2. Units were classified according to their responses to the battery of mechanical stimuli: 16% of the units responded only to pressure. The majority of these pressure-responsive units were excited, while a few were inhibited or responded differently, depending on the site stimulated; 52% did not respond to pressure, but responded to brushing, muscle-joint, and/or visceral stimulation, or did not respond at all. The remaining 32% responded to pressure plus other forms of stimulation. 3. Units responding only to the movement of individual types of hair tended to be located in the dorsal horn, more dorsal than units responding only to pressure (found primarily in the intermediate gray). Units responding to subdermal stimulation were usually found at greater depths. Segmental and somatotopic distributions of spinal units observed were very similar to those reported for cat (3) and monkey (5). 4. Compared to primary sensory units (28), spinal units had higher resting firing rates, more complicated responses to a given stimulus, a wider variety of unit types, and much larger receptive fields. These comparisons tend to indicate convergence of primary sensory neurons onto individual spinal units. 5. The range of pressure thresholds of pressure-responsive units is comparable to the range effective for triggering lordosis. We postulate that excitation of units responding only to pressure is centrally involved in triggering the lordosis reflex. Those units not responding to pressure are probably irrelevant for this behavior. Presently undetermined are the roles of units with complex or mixed-response types.

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