scholarly journals Reorganization in processing of spectral and temporal input in the rat posterior auditory field induced by environmental enrichment

2012 ◽  
Vol 107 (5) ◽  
pp. 1457-1475 ◽  
Author(s):  
Vikram Jakkamsetti ◽  
Kevin Q. Chang ◽  
Michael P. Kilgard
Keyword(s):  
Environmental Enrichment ◽  
Sensory Input ◽  
Response Times ◽  
Neuronal Response ◽  
Receptive Fields ◽  
Primary Auditory Cortex ◽  
Response Strength ◽  
Sensory Cortex ◽  
Primary Sensory Cortex ◽  
Auditory Field

Environmental enrichment induces powerful changes in the adult cerebral cortex. Studies in primary sensory cortex have observed that environmental enrichment modulates neuronal response strength, selectivity, speed of response, and synchronization to rapid sensory input. Other reports suggest that nonprimary sensory fields are more plastic than primary sensory cortex. The consequences of environmental enrichment on information processing in nonprimary sensory cortex have yet to be studied. Here we examine physiological effects of enrichment in the posterior auditory field (PAF), a field distinguished from primary auditory cortex (A1) by wider receptive fields, slower response times, and a greater preference for slowly modulated sounds. Environmental enrichment induced a significant increase in spectral and temporal selectivity in PAF. PAF neurons exhibited narrower receptive fields and responded significantly faster and for a briefer period to sounds after enrichment. Enrichment increased time-locking to rapidly successive sensory input in PAF neurons. Compared with previous enrichment studies in A1, we observe a greater magnitude of reorganization in PAF after environmental enrichment. Along with other reports observing greater reorganization in nonprimary sensory cortex, our results in PAF suggest that nonprimary fields might have a greater capacity for reorganization compared with primary fields.

scholarly journals Sensory cortex is optimised for prediction of future input

2017 ◽  
Author(s):  
Yosef Singer ◽  
Yayoi Teramoto ◽  
Ben D. B. WiIJmore ◽  
Andrew J. King ◽  
Jan W. H. Schnupp ◽  
...  
Keyword(s):  
Sensory Processing ◽  
Cortical Neurons ◽  
Sensory Input ◽  
Receptive Fields ◽  
Primary Auditory Cortex ◽  
Feedforward Neural Networks ◽  
Sensory Cortex ◽  
Natural Scenes ◽  
Recent Past ◽  
The Brain

Neurons in sensory cortex are tuned to diverse features in natural scenes. But what determines which features neurons become selective to? Here we explore the idea that neuronal selectivity is optimised to represent features in the recent past of sensory input that best predict immediate future inputs. We tested this hypothesis using simple feedforward neural networks, which were trained to predict the next few video or audio frames in clips of natural scenes. The networks developed receptive fields that closely matched those of real cortical neurons, including the oriented spatial tuning of primary visual cortex, the frequency selectivity of primary auditory cortex and, most notably, in their temporal tuning properties. Furthermore, the better a network predicted future inputs the more closely its receptive fields tended to resemble those in the brain. This suggests that sensory processing is optimised to extract those features with the most capacity to predict future input.Impact statementPrediction of future input explains diverse neural tuning properties in sensory cortex.

Spectrotemporal Organization of Excitatory and Inhibitory Receptive Fields of Cat Posterior Auditory Field Neurons

2001 ◽  
Vol 86 (1) ◽  
pp. 475-491 ◽  
Author(s):  
William C. Loftus ◽  
Mitchell L. Sutter
Keyword(s):  
Response Times ◽  
Frequency Tuning ◽  
Population Analysis ◽  
Receptive Fields ◽  
Primary Auditory Cortex ◽  
Stimulus Onset ◽  
Spike Response ◽  
Threshold Response ◽  
Spectrotemporal Receptive Fields ◽  
Auditory Field

The excitatory and inhibitory frequency/intensity response areas (FRAs) and spectrotemporal receptive fields (STRFs) of posterior auditory cortical field (PAF) single neurons were investigated in barbiturate anesthetized cats. PAF neurons' pure-tone excitatory FRAs (eFRAs) exhibited a diversity of shapes, including some with very broad frequency tuning and some with multiple distinct excitatory frequency ranges (i.e., multipeaked eFRAs). Excitatory FRAs were analyzed after selectively excluding spikes on the basis of spike response times relative to stimulus onset. This analysis indicated that spikes with shorter response times were confined to narrow regions of the eFRAs, while spikes with longer response times were more broadly distributed over the eFRA. First-spike latencies in higher threshold response peaks of multipeaked eFRAs were ∼10 ms longer, on average, than latencies in lower threshold response peaks. STRFs were constructed to examine the dynamic frequency tuning of neurons. More than half of the neurons (51%) had STRFs with “sloped” response maxima, indicating that the excitatory frequency range shifted with time. A population analysis demonstrated that the median first-spike latency varied systematically as a function of frequency with a median slope of ∼12 ms per octave. Inhibitory frequency response areas were determined by simultaneous two-tone stimulation. As in primary auditory cortex (A1), a diversity of inhibitory band structures was observed. The largest class of neurons (25%) had an inhibitory band flanking each eFRA edge, i.e., one lower and one upper inhibitory band in a “center-surround” organization. However, in comparison to a previous report of inhibitory structure in A1 neurons, PAF exhibited a higher incidence of neurons with more complex inhibitory band structure (for example, >2 inhibitory bands). As was the case with eFRAs, spikes with longer response times contributed to the complexity of inhibitory FRAs. These data indicate that PAF neurons integrate temporally varying excitatory and inhibitory inputs from a broad spectral extent and, compared with A1, may be suited to analyzing acoustic signals of greater spectrotemporal complexity than was previously thought.

Coherent Electrical Activity Between Vibrissa Sensory Areas of Cerebellum and Neocortex Is Enhanced During Free Whisking

2002 ◽  
Vol 87 (4) ◽  
pp. 2137-2148 ◽  
Author(s):  
Sean M. O'Connor ◽  
Rune W. Berg ◽  
David Kleinfeld
Keyword(s):  
Electrical Activity ◽  
Sensory Input ◽  
Field Potential ◽  
Sensory Cortex ◽  
Brain Areas ◽  
Low Coherence ◽  
Primary Sensory Cortex ◽  
High Level ◽  
The Brain ◽  
Local Field Potential Lfp

We tested if coherent signaling between the sensory vibrissa areas of cerebellum and neocortex in rats was enhanced as they whisked in air. Whisking was accompanied by 5- to 15-Hz oscillations in the mystatial electromyogram, a measure of vibrissa position, and by 5- to 20-Hz oscillations in the differentially recorded local field potential (∇LFP) within the vibrissa area of cerebellum and within the ∇LFP of primary sensory cortex. We observed that only 10% of the activity in either cerebellum or sensory neocortex was significantly phase-locked to rhythmic motion of the vibrissae; the extent of this modulation is in agreement with the results from previous single-unit measurements in sensory neocortex. In addition, we found that 40% of the activity in the vibrissa areas of cerebellum and neocortex was significantly coherent during periods of whisking. The relatively high level of coherence between these two brain areas, in comparison with their relatively low coherence with whisking per se, implies that the vibrissa areas of cerebellum and neocortex communicate in a manner that is incommensurate with whisking. To the extent that the vibrissa areas of cerebellum and neocortex communicate over the same frequency band as that used by whisking, these areas must multiplex electrical activity that is internal to the brain with activity that is that phase-locked to vibrissa sensory input.

scholarly journals Dissociable influences of primary auditory cortex and the posterior auditory field on neuronal responses in the dorsal zone of auditory cortex

2015 ◽  
Vol 113 (2) ◽  
pp. 475-486
Author(s):  
Melanie A. Kok ◽  
Daniel Stolzberg ◽  
Trecia A. Brown ◽  
Stephen G. Lomber
Keyword(s):  
Auditory Cortex ◽  
Receptive Fields ◽  
Primary Auditory Cortex ◽  
Population Level ◽  
Noise Burst ◽  
Hierarchical Organization ◽  
Neuronal Responses ◽  
Tone Frequency ◽  
Hierarchical Processing ◽  
Auditory Field

Current models of hierarchical processing in auditory cortex have been based principally on anatomical connectivity while functional interactions between individual regions have remained largely unexplored. Previous cortical deactivation studies in the cat have addressed functional reciprocal connectivity between primary auditory cortex (A1) and other hierarchically lower level fields. The present study sought to assess the functional contribution of inputs along multiple stages of the current hierarchical model to a higher order area, the dorsal zone (DZ) of auditory cortex, in the anaesthetized cat. Cryoloops were placed over A1 and posterior auditory field (PAF). Multiunit neuronal responses to noise burst and tonal stimuli were recorded in DZ during cortical deactivation of each field individually and in concert. Deactivation of A1 suppressed peak neuronal responses in DZ regardless of stimulus and resulted in increased minimum thresholds and reduced absolute bandwidths for tone frequency receptive fields in DZ. PAF deactivation had less robust effects on DZ firing rates and receptive fields compared with A1 deactivation, and combined A1/PAF cooling was largely driven by the effects of A1 deactivation at the population level. These results provide physiological support for the current anatomically based model of both serial and parallel processing schemes in auditory cortical hierarchical organization.

Interactive effects among several stimulus parameters on the responses of striate cortical complex cells

1991 ◽  
Vol 66 (2) ◽  
pp. 379-389 ◽  
Author(s):  
T. J. Gawne ◽  
B. J. Richmond ◽  
L. M. Optican
Keyword(s):  
Striate Cortex ◽  
Neuronal Response ◽  
Receptive Fields ◽  
Response Strength ◽  
Interactive Effects ◽  
Temporal Modulation ◽  
Complex Cells ◽  
Black And White ◽  
Interaction Terms ◽  
Stimulus Parameters

1. Although neurons within the visual system are often described in terms of their responses to particular patterns such as bars and edges, they are actually sensitive to many different stimulus features, such as the luminances making up the patterns and the duration of presentation. Many different combinations of stimulus parameters can result in the same neuronal response, raising the problem of how the nervous system can extract information about visual stimuli from such inherently ambiguous responses. It has been shown that complex cells transmit significant amounts of information in the temporal modulation of their responses, raising the possibility that different stimulus parameters are encoded in different aspects of the response. To find out how much information is actually available about individual stimulus parameters, we examined the interactions among three stimulus parameters in the temporally modulated responses of striate cortical complex cells. 2. Sixteen black and white patterns were presented to two awake monkeys at each of four luminance-combinations and five durations, giving a total of 320 unique stimuli. Complex cells were recorded in layers 2 and 3 of striate cortex, with the stimuli centered on the receptive fields as determined by mapping with black and white bars. 3. An analysis of variance (ANOVA) was applied to these data with the three stimulus parameters of pattern, the luminance-combinations, and duration as the independent variables. The ANOVA was repeated with the magnitude and three different aspects of the temporal modulation of the response as the dependent variables. For the 19 neurons studied, many of the interactions between the different stimulus parameters were statistically significant. For some response measures the interactions accounted for more than one-half of the total response variance. 4. We also analyzed the stimulus-response relationships with the use of information theoretical techniques. We defined input codes on the basis of each stimulus parameter alone, as well as their combinations, and output codes on the basis of response strength, and on three measures of temporal modulation, also taken individually and together. Transmitted information was greatest when the response of a neuron was interpreted as a temporally modulated message about combinations of all three stimulus parameters. The interaction terms of the ANOVA suggest that the response of a complex cell can only be interpreted as a message about combinations of all three stimulus parameters.(ABSTRACT TRUNCATED AT 400 WORDS)

Spectrotemporal Structure of Receptive Fields in Areas AI and AAF of Mouse Auditory Cortex

2003 ◽  
Vol 90 (4) ◽  
pp. 2660-2675 ◽  
Author(s):  
Jennifer F. Linden ◽  
Robert C. Liu ◽  
Maneesh Sahani ◽  
Christoph E. Schreiner ◽  
Michael M. Merzenich
Keyword(s):  
Receptive Field ◽  
Auditory Cortex ◽  
Receptive Fields ◽  
Primary Auditory Cortex ◽  
Dynamic Stimuli ◽  
Tuning Curves ◽  
Response Characteristics ◽  
Spectrotemporal Receptive Fields ◽  
Auditory Field ◽  
Tonal Stimuli

The mouse is a promising model system for auditory cortex research because of the powerful genetic tools available for manipulating its neural circuitry. Previous studies have identified two tonotopic auditory areas in the mouse—primary auditory cortex (AI) and anterior auditory field (AAF)— but auditory receptive fields in these areas have not yet been described. To establish a foundation for investigating auditory cortical circuitry and plasticity in the mouse, we characterized receptive-field structure in AI and AAF of anesthetized mice using spectrally complex and temporally dynamic stimuli as well as simple tonal stimuli. Spectrotemporal receptive fields (STRFs) were derived from extracellularly recorded responses to complex stimuli, and frequency-intensity tuning curves were constructed from responses to simple tonal stimuli. Both analyses revealed temporal differences between AI and AAF responses: peak latencies and receptive-field durations for STRFs and first-spike latencies for responses to tone bursts were significantly longer in AI than in AAF. Spectral properties of AI and AAF receptive fields were more similar, although STRF bandwidths were slightly broader in AI than in AAF. Finally, in both AI and AAF, a substantial minority of STRFs were spectrotemporally inseparable. The spectrotemporal interaction typically appeared in the form of clearly disjoint excitatory and inhibitory subfields or an obvious spectrotemporal slant in the STRF. These data provide the first detailed description of auditory receptive fields in the mouse and suggest that although neurons in areas AI and AAF share many response characteristics, area AAF may be specialized for faster temporal processing.

Reorganization in the Cutaneous Core of the Human Thalamic Principal Somatic Sensory Nucleus (Ventral Caudal) in Patients With Dystonia

1999 ◽  
Vol 82 (6) ◽  
pp. 3204-3212 ◽  
Author(s):  
Fred A. Lenz ◽  
Nancy N. Byl
Keyword(s):  
Essential Tremor ◽  
Average Length ◽  
Receptive Fields ◽  
Body Part ◽  
The Body ◽  
Sensory Cortex ◽  
Body Parts ◽  
Primary Sensory Cortex ◽  
Wide Range ◽  
Sensory Nucleus

A wide range of observations suggest that sensory inputs play a significant role in dystonia. For example, the map of the hand representation in the primary sensory cortex (area 3b) is altered in monkeys with dystonia-like movements resulting from overtraining in a gripping task. We investigated whether similar reorganization occurs in the somatic sensory thalamus of patients with dystonia (dystonia patients). We studied recordings of neuronal activity and microstimulation-evoked responses from the cutaneous core of the human principal somatic sensory nucleus (ventral caudal, Vc) of 11 dystonia patients who underwent stereotactic thalamotomy. Fifteen patients with essential tremor who underwent similar procedures were used as controls. The cutaneous core of Vc was defined as the part of the cellular thalamic region where the majority of cells had receptive fields (RFs) to innocuous cutaneous stimuli. The proportion of RFs including multiple parts of the body was greater in dystonia patients (29%) than in patients with essential tremor (11%). Similarly, the percentage of projected fields (PFs) including multiple body parts was higher in dystonia patients (71%) than in patients with essential tremor (41%). A match at a thalamic site was said to occur if the RF and PF at that site included a body part in common. Such matches were significantly less prevalent in dystonia patients (33%) than in patients with essential tremor (58%). The average length of the trajectory where the PF included a consistent, cutaneous RF was significantly longer in patients with dystonia than in control patients with essential tremor. The findings of sensory reorganization in Vc thalamus are congruent with those reported in the somatic sensory cortex of monkeys with dystonia-like movements resulting from overtraining in a gripping task.

scholarly journals Comparison of the Neuronal Activity in the SMA and the Ventral Cingulate Cortex During Prehension in the Monkey

1997 ◽  
Vol 77 (1) ◽  
pp. 153-166 ◽  
Author(s):  
Geneviève Cadoret ◽  
Allan M. Smith
Keyword(s):  
Neuronal Activity ◽  
Grip Force ◽  
Response Times ◽  
Neuronal Response ◽  
Receptive Fields ◽  
Cingulate Cortex ◽  
Hand Movements ◽  
Proprioceptive Stimulation ◽  
Pulse Perturbation ◽  
Parallel Activation

Cadoret, Geneviève and Allan M. Smith. Comparison of the neuronal activity in the SMA and the ventral cingulate cortex during prehension in the monkey. J. Neurophysiol. 77: 153–166, 1997. Two monkeys were trained to use the thumb and forefinger to lift and hold an instrumented apparatus within a narrow position window for 1 s. The device was equipped to measure the position and the grip and lifting forces exerted by the animal. On blocks of trials the weight and surface texture could be varied or a force-pulse perturbation could be systematically delivered 750 ms after the object entered the window. If unopposed, the perturbation would displace the hand from the position window, and in preparation for this perturbation the monkeys either increased their grip force before the perturbation or raised the object higher within the position window. Two clearly separated clusters of cells in the medial wall of the frontal lobe were found to be active in relation to the task. One group of cells ( n = 115) was located in the caudal and medial part of area 6, in the supplementary motor area (SMA), and the other ( n = 92) was located in the ventral bank of the cingulate sulcus (CMAv), in area 23c. In each area, neurons were characterized by their sensorimotor features clearly related to the hand in addition to their modulated activity in the task. In the SMA, 71% (42 of 59) of the neurons tested for receptive fields responded to peripheral and mainly proprioceptive stimulation, and 71% of them (30 of 42) received inputs from the hand. In the CMAv, 77% (48 of 62) of the neurons responded to peripheral proprioceptive stimulation, and 77% (37 of 48) exhibited receptive fields originating from the hand. Intracortical microstimulation applied to 43 sites in the SMA evoked discrete hand movements at 12 loci, whereas in the CMAv hand movements were observed at 8 of 27 sites tested with an average threshold of >15 μA. A strong similarity was observed between the SMA and CMAv neurons in their sensorimotor features as well as the modulation of their activity in relation to the prehension task. In both areas the activity was poorly related to grip force and significant correlation with peak grip force was observed for only 9 and 7% of the CMAv and SMA neurons, respectively. In the SMA only five cells exhibited increased activity before the perturbation and in the CMAv no changes in activity were found despite the presence of clear preparatory increases in grip force in anticipation of the perturbation. The perturbation evoked reflexlike excitation of 38% (25 of 65) of the neurons in the CMAv and 28% (20 of 71) of the cells in the SMA; these cells were similar in magnitude and latency (∼50 ms) in both areas. In both the SMA and CMAv, most of the neurons increased their firing rate <200 ms before the grip force onset and the overlap in the distribution of neuronal response times suggests a parallel activation of the SMA and CMAv neurons during the prehension task.

scholarly journals Sensory cortex is optimized for prediction of future input

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Yosef Singer ◽  
Yayoi Teramoto ◽  
Ben DB Willmore ◽  
Jan WH Schnupp ◽  
Andrew J King ◽  
...  
Keyword(s):  
Neural Networks ◽  
Sensory Processing ◽  
Cortical Neurons ◽  
Mammalian Species ◽  
Receptive Fields ◽  
Primary Auditory Cortex ◽  
Feedforward Neural Networks ◽  
Sensory Cortex ◽  
Natural Scenes ◽  
The Brain

Neurons in sensory cortex are tuned to diverse features in natural scenes. But what determines which features neurons become selective to? Here we explore the idea that neuronal selectivity is optimized to represent features in the recent sensory past that best predict immediate future inputs. We tested this hypothesis using simple feedforward neural networks, which were trained to predict the next few moments of video or audio in clips of natural scenes. The networks developed receptive fields that closely matched those of real cortical neurons in different mammalian species, including the oriented spatial tuning of primary visual cortex, the frequency selectivity of primary auditory cortex and, most notably, their temporal tuning properties. Furthermore, the better a network predicted future inputs the more closely its receptive fields resembled those in the brain. This suggests that sensory processing is optimized to extract those features with the most capacity to predict future input.

scholarly journals Mouse V1 population correlates of visual detection rely on heterogeneity within neuronal response patterns

eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Jorrit S Montijn ◽  
Pieter M Goltstein ◽  
Cyriel MA Pennartz
Keyword(s):  
Visual Detection ◽  
Neuronal Response ◽  
Visual Stimuli ◽  
Response Strength ◽  
Response Patterns ◽  
Activation Patterns ◽  
Neuronal Populations ◽  
Two Photon ◽  
Primary Sensory Cortex

Previous studies have demonstrated the importance of the primary sensory cortex for the detection, discrimination, and awareness of visual stimuli, but it is unknown how neuronal populations in this area process detected and undetected stimuli differently. Critical differences may reside in the mean strength of responses to visual stimuli, as reflected in bulk signals detectable in functional magnetic resonance imaging, electro-encephalogram, or magnetoencephalography studies, or may be more subtly composed of differentiated activity of individual sensory neurons. Quantifying single-cell Ca2+ responses to visual stimuli recorded with in vivo two-photon imaging, we found that visual detection correlates more strongly with population response heterogeneity rather than overall response strength. Moreover, neuronal populations showed consistencies in activation patterns across temporally spaced trials in association with hit responses, but not during nondetections. Contrary to models relying on temporally stable networks or bulk signaling, these results suggest that detection depends on transient differentiation in neuronal activity within cortical populations.

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