Effects of selective attention on spatial form processing in monkey primary and secondary somatosensory cortex

1993 ◽  
Vol 70 (1) ◽  
pp. 444-447 ◽  
Author(s):  
S. S. Hsiao ◽  
D. M. O'Shaughnessy ◽  
K. O. Johnson
Keyword(s):  
Selective Attention ◽  
Visual Detection ◽  
Visual Task ◽  
Neural Responses ◽  
Neuronal Responses ◽  
Spatial Form ◽  
Form Processing ◽  
Secondary Somatosensory Cortex ◽  
Time Out ◽  
Discharge Rates

1. The effects of selective attention were studied in SI and SII cortex of a rhesus monkey trained to perform two tasks, a tactile discrimination task and a visual detection task. In the tactile task, a letter was displayed on a video screen in front of the monkey and the animal was rewarded for responding when the raised letter (6.0 mm letter height) scanning across its finger (15 mm/s) matched the letter on the screen. In the visual task, three illuminated squares were displayed on the screen, and the animal was rewarded for detecting when one of the squares dimmed. The neural responses evoked by the raised letters were recorded continuously while the animal's focus of attention was switched back and forth between the two tasks. 2. Significant differences between the discharge rates evoked by raised letters in the two tasks were observed in approximately 50% of neurons in SI cortex and 80% of neurons in SII cortex. The effects in SII cortex were divided between increased (58%) and decreased (22%) rates. In SI cortex only increased rates were observed. 3. The attentional effects were expressed not only as changes in overall neuronal activity but also as modifications of the form of the responses evoked by the letters. 4. Whether attentional effects were observed depended upon the behavioral relevance of individual letters. During brief periods in the tactile task when a behavioral response could not yield a reward (time-out and reward periods) the neuronal responses were not significantly different from the responses evoked by the same letters during the visual task.(ABSTRACT TRUNCATED AT 250 WORDS)

scholarly journals Evidence accumulation relates to perceptual consciousness and monitoring

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Michael Pereira ◽  
Pierre Megevand ◽  
Mi Xue Tan ◽  
Wenwen Chang ◽  
Shuo Wang ◽  
...  
Keyword(s):  
Posterior Parietal Cortex ◽  
Detection Threshold ◽  
Task Demands ◽  
Neuron Activity ◽  
Neural Responses ◽  
Neuronal Responses ◽  
Neural Basis ◽  
Perceptual Consciousness ◽  
Evidence Accumulation ◽  
Posterior Parietal

AbstractA fundamental scientific question concerns the neural basis of perceptual consciousness and perceptual monitoring resulting from the processing of sensory events. Although recent studies identified neurons reflecting stimulus visibility, their functional role remains unknown. Here, we show that perceptual consciousness and monitoring involve evidence accumulation. We recorded single-neuron activity in a participant with a microelectrode in the posterior parietal cortex, while they detected vibrotactile stimuli around detection threshold and provided confidence estimates. We find that detected stimuli elicited neuronal responses resembling evidence accumulation during decision-making, irrespective of motor confounds or task demands. We generalize these findings in healthy volunteers using electroencephalography. Behavioral and neural responses are reproduced with a computational model considering a stimulus as detected if accumulated evidence reaches a bound, and confidence as the distance between maximal evidence and that bound. We conclude that gradual changes in neuronal dynamics during evidence accumulation relates to perceptual consciousness and perceptual monitoring in humans.

scholarly journals Perceptual detection depends on spike count integration

2019 ◽  
Author(s):  
Jackson J. Cone ◽  
Morgan L. Bade ◽  
Nicolas Y. Masse ◽  
Elizabeth A. Page ◽  
David J. Freedman ◽  
...  
Keyword(s):  
Neural Networks ◽  
Cerebral Cortex ◽  
Visual Cortex ◽  
Recurrent Neural Networks ◽  
Neural Circuit ◽  
Visual Detection ◽  
Spike Count ◽  
Neuronal Responses ◽  
Neuronal Populations ◽  
And Behavior

AbstractWhenever the retinal image changes some neurons in visual cortex increase their rate of firing, while others decrease their rate of firing. Linking specific sets of neuronal responses with perception and behavior is essential for understanding mechanisms of neural circuit computation. We trained mice to perform visual detection tasks and used optogenetic perturbations to increase or decrease neuronal spiking primary visual cortex (V1). Perceptual reports were always enhanced by increments in V1 spike counts and impaired by decrements, even when increments and decrements were delivered to the same neuronal populations. Moreover, detecting changes in cortical activity depended on spike count integration rather than instantaneous changes in spiking. Recurrent neural networks trained in the task similarly relied on increments in neuronal activity when activity was costly. This work clarifies neuronal decoding strategies employed by cerebral cortex to translate cortical spiking into percepts that can be used to guide behavior.

Massive Data Classification of Neural Responses

2010 ◽  
pp. 278-298
Author(s):  
Pedro Tomás ◽  
IST TU Lisbon ◽  
Aleksandar Ilic ◽  
Leonel Sousa
Keyword(s):  
Execution Time ◽  
Data Parallelism ◽  
Data Sets ◽  
Neural Responses ◽  
Neuronal Responses ◽  
Data Set ◽  
Web Interfaces ◽  
Mass Classification ◽  
Neuronal Code

When analyzing the neuronal code, neuroscientists usually perform extra-cellular recordings of neuronal responses (spikes). Since the size of the microelectrodes used to perform these recordings is much larger than the size of the cells, responses from multiple neurons are recorded by each micro-electrode. Thus, the obtained response must be classified and evaluated, in order to identify how many neurons were recorded, and to assess which neuron generated each spike. A platform for the mass-classification of neuronal responses is proposed in this chapter, employing data-parallelism for speeding up the classification of neuronal responses. The platform is built in a modular way, supporting multiple web-interfaces, different back-end environments for parallel computing or different algorithms for spike classification. Experimental results on the proposed platform show that even for an unbalanced data set of neuronal responses the execution time was reduced of about 45%. For balanced data sets, the platform may achieve a reduction in execution time equal to the inverse of the number of back-end computational elements.

scholarly journals A visual encoding model links magnetoencephalography signals to neural synchrony in human cortex

2020 ◽  
Author(s):  
Eline R. Kupers ◽  
Noah C. Benson ◽  
Jonathan Winawer
Keyword(s):  
Visual Stimulation ◽  
Neural Synchrony ◽  
Systematic Effect ◽  
Neural Responses ◽  
Neuronal Responses ◽  
Spatial Pooling ◽  
Visual Encoding ◽  
Model Predictions ◽  
Cortical Regions ◽  
Spatial Topography

AbstractSynchronization of neuronal responses over large distances is hypothesized to be important for many cortical functions. However, no straightforward methods exist to estimate synchrony non-invasively in the living human brain. MEG and EEG measure the whole brain, but the sensors pool over large, overlapping cortical regions, obscuring the underlying neural synchrony. Here, we developed a model from stimulus to cortex to MEG sensors to disentangle neural synchrony from spatial pooling of the instrument. We find that synchrony across cortex has a surprisingly large and systematic effect on predicted MEG spatial topography. We then conducted visual MEG experiments and separated responses into stimulus-locked and broadband components. The stimulus-locked topography was similar to model predictions assuming synchronous neural sources, whereas the broadband topography was similar to model predictions assuming asynchronous sources. We infer that visual stimulation elicits two distinct types of neural responses, one highly synchronous and one largely asynchronous across cortex.

scholarly journals The neural response to the temporal fine structure of continuous musical pieces is not affected by selective attention

2021 ◽  
Author(s):  
Octave Etard ◽  
Rémy Ben Messaoud ◽  
Gabriel Gaugain ◽  
Tobias Reichenbach
Keyword(s):  
Fine Structure ◽  
Selective Attention ◽  
Population Level ◽  
Neural Response ◽  
Temporal Fine Structure ◽  
Neural Responses ◽  
Neural Encoding ◽  
Human Volunteers ◽  
Eeg Recordings ◽  
Single Instrument

AbstractSpeech and music are spectro-temporally complex acoustic signals that a highly relevant for humans. Both contain a temporal fine structure that is encoded in the neural responses of subcortical and cortical processing centres. The subcortical response to the temporal fine structure of speech has recently been shown to be modulated by selective attention to one of two competing voices. Music similarly often consists of several simultaneous melodic lines, and a listener can selectively attend to a particular one at a time. However, the neural mechanisms that enable such selective attention remain largely enigmatic, not least since most investigations to date have focussed on short and simplified musical stimuli. Here we study the neural encoding of classical musical pieces in human volunteers, using scalp electroencephalography (EEG) recordings. We presented volunteers with continuous musical pieces composed of one or two instruments. In the latter case, the participants were asked to selectively attend to one of the two competing instruments and to perform a vibrato identification task. We used linear encoding and decoding models to relate the recorded EEG activity to the stimulus waveform. We show that we can measure neural responses to the temporal fine structure of melodic lines played by one single instrument, at the population level as well as for most individual subjects. The neural response peaks at a latency of 7.6 ms and is not measurable past 15 ms. When analysing the neural responses elicited by competing instruments, we find no evidence of attentional modulation. Our results show that, much like speech, the temporal fine structure of music is tracked by neural activity. In contrast to speech, however, this response appears unaffected by selective attention in the context of our experiment.

No Evidence of Attentional Modulation of the Neural Response to the Temporal Fine Structure of Continuous Musical Pieces

2021 ◽  
pp. 1-14
Author(s):  
Octave Etard ◽  
Rémy Ben Messaoud ◽  
Gabriel Gaugain ◽  
Tobias Reichenbach
Keyword(s):  
Fine Structure ◽  
Selective Attention ◽  
Neural Activity ◽  
Low Frequency ◽  
Population Level ◽  
Neural Response ◽  
Temporal Fine Structure ◽  
Neural Responses ◽  
Attentional Modulation ◽  
Eeg Recordings

Abstract Speech and music are spectrotemporally complex acoustic signals that are highly relevant for humans. Both contain a temporal fine structure that is encoded in the neural responses of subcortical and cortical processing centers. The subcortical response to the temporal fine structure of speech has recently been shown to be modulated by selective attention to one of two competing voices. Music similarly often consists of several simultaneous melodic lines, and a listener can selectively attend to a particular one at a time. However, the neural mechanisms that enable such selective attention remain largely enigmatic, not least since most investigations to date have focused on short and simplified musical stimuli. Here, we studied the neural encoding of classical musical pieces in human volunteers, using scalp EEG recordings. We presented volunteers with continuous musical pieces composed of one or two instruments. In the latter case, the participants were asked to selectively attend to one of the two competing instruments and to perform a vibrato identification task. We used linear encoding and decoding models to relate the recorded EEG activity to the stimulus waveform. We show that we can measure neural responses to the temporal fine structure of melodic lines played by one single instrument, at the population level as well as for most individual participants. The neural response peaks at a latency of 7.6 msec and is not measurable past 15 msec. When analyzing the neural responses to the temporal fine structure elicited by competing instruments, we found no evidence of attentional modulation. We observed, however, that low-frequency neural activity exhibited a modulation consistent with the behavioral task at latencies from 100 to 160 msec, in a similar manner to the attentional modulation observed in continuous speech (N100). Our results show that, much like speech, the temporal fine structure of music is tracked by neural activity. In contrast to speech, however, this response appears unaffected by selective attention in the context of our experiment.

scholarly journals Impact of visual motion adaptation on neural responses to objects and its dependence on the temporal characteristics of optic flow

2011 ◽  
Vol 105 (4) ◽  
pp. 1825-1834 ◽  
Author(s):  
Pei Liang ◽  
Roland Kern ◽  
Rafael Kurtz ◽  
Martin Egelhaaf
Keyword(s):  
Optic Flow ◽  
Visual Motion ◽  
Induced Response ◽  
Neural Responses ◽  
Neuronal Responses ◽  
Motion Adaptation ◽  
Preferred Direction ◽  
Pure Rotation ◽  
Normal Behavior ◽  
Natural Dynamics

It is still unclear how sensory systems efficiently encode signals with statistics as experienced by animals in the real world and what role adaptation plays during normal behavior. Therefore, we studied the performance of visual motion-sensitive neurons of blowflies, the horizontal system neurons, with optic flow that was reconstructed from the head trajectories of semi-free-flying flies. To test how motion adaptation is affected by optic flow dynamics, we manipulated the seminatural optic flow by targeted modifications of the flight trajectories and assessed to what extent neuronal responses to an object located close to the flight trajectory depend on adaptation dynamics. For all types of adapting optic flow object-induced response increments were stronger in the adapted compared with the nonadapted state. Adaptation with optic flow characterized by the typical alternation between translational and rotational segments produced this effect but also adaptation with optic flow that lacked these distinguishing features and even pure rotation at a constant angular velocity. The enhancement of object-induced response increments had a direction-selective component because preferred-direction rotation and natural optic flow were more efficient adaptors than null-direction rotation. These results indicate that natural dynamics of optic flow is not a basic requirement to adapt neurons in a specific, presumably functionally beneficial way. Our findings are discussed in the light of adaptation mechanisms proposed on the basis of experiments previously done with conventional experimenter-defined stimuli.

Cardiac input to medullary reticular formation: neuronal responses to mechanical stimuli

1986 ◽  
Vol 251 (4) ◽  
pp. R680-R689
Author(s):  
R. W. Blair
Keyword(s):  
Reticular Formation ◽  
Sensory Modality ◽  
Receptive Fields ◽  
Arterial Occlusion ◽  
Large Mass ◽  
Mechanical Stimuli ◽  
Neuronal Responses ◽  
Medullary Reticular Formation ◽  
Discharge Rates ◽  
Reticular Neurons

Neurons in the medullary reticular formation were tested for responses to mechanical stimuli applied to the heart in cats anesthetized with chloralose and paralyzed with pancuronium. In most experiments baroreceptors were denervated. Aortic occlusion excited 15 neurons (19%) and decreased the mean discharge rates of five neurons (6%). Discrete probing of the heart elicited one to three spikes from 18 of 27 neurons tested. Thirteen of these cells had defined cardiac receptive fields; fields were large, often encompassing most of the left ventricle. Of 12 neurons tested for responses during fibrillation, 8 were excited, 2 were inhibited, and 2 were unaffected. Neurons often exhibited different sensitivities to these mechanical stimuli, as well as to ischemia produced during coronary arterial occlusion. Neurons were more likely to respond to stimuli that affected a large mass of myocardium. In addition to cardiac input, 98% of neurons in this study also received input from at least one additional sensory modality, and 39 cells were excited by somatic, auditory, and visual stimuli. Results indicate that medullary reticular neurons are responsive to mechanical events in the heart as well as to myocardial ischemia and respond to other sensory modalities.

Stochastic Nature of Precisely Timed Spike Patterns in Visual System Neuronal Responses

1999 ◽  
Vol 81 (6) ◽  
pp. 3021-3033 ◽  
Author(s):  
M. W. Oram ◽  
M. C. Wiener ◽  
R. Lestienne ◽  
B. J. Richmond
Keyword(s):  
Visual System ◽  
Statistical Models ◽  
Temporal Structure ◽  
Response Strength ◽  
Spike Count ◽  
Neural Responses ◽  
Neuronal Responses ◽  
V1 Neurons ◽  
Stochastic Nature ◽  
Spike Patterns

Stochastic nature of precisely timed spike patterns in visual system neuronal responses. It is not clear how information related to cognitive or psychological processes is carried by or represented in the responses of single neurons. One provocative proposal is that precisely timed spike patterns play a role in carrying such information. This would require that these spike patterns have the potential for carrying information that would not be available from other measures such as spike count or latency. We examined exactly timed (1-ms precision) triplets and quadruplets of spikes in the stimulus-elicited responses of lateral geniculate nucleus (LGN) and primary visual cortex (V1) neurons of the awake fixating rhesus monkey. Large numbers of these precisely timed spike patterns were found. Information theoretical analysis showed that the precisely timed spike patterns carried only information already available from spike count, suggesting that the number of precisely timed spike patterns was related to firing rate. We therefore examined statistical models relating precisely timed spike patterns to response strength. Previous statistical models use observed properties of neuronal responses such as the peristimulus time histogram, interspike interval, and/or spike count distributions to constrain the parameters of the model. We examined a new stochastic model, which unlike previous models included all three of these constraints and unlike previous models predicted the numbers and types of observed precisely timed spike patterns. This shows that the precise temporal structures of stimulus-elicited responses in LGN and V1 can occur by chance. We show that any deviation of the spike count distribution, no matter how small, from a Poisson distribution necessarily changes the number of precisely timed spike patterns expected in neural responses. Overall the results indicate that the fine temporal structure of responses can only be interpreted once all the coarse temporal statistics of neural responses have been taken into account.

scholarly journals Heading direction with respect to a reference point modulates place-cell activity

2018 ◽  
Author(s):  
P.E. Jercog ◽  
Y. Ahmadian ◽  
C. Woodruff ◽  
R. Deb-Sen ◽  
L.F. Abbott ◽  
...  
Keyword(s):  
Reference Point ◽  
Dorsal Hippocampus ◽  
Cell Activity ◽  
Pyramidal Cells ◽  
Neural Responses ◽  
Neuronal Responses ◽  
Ca1 Pyramidal Cells ◽  
Electrophysiological Recordings ◽  
Heading Direction ◽  
Freely Moving

AbstractUtilizing electrophysiological recordings from CA1 pyramidal cells in freely moving mice, we find that a majority of neural responses are modulated by the heading-direction of the animal relative to a point within or outside their enclosure that we call a reference point. Our findings identify a novel representation in the neuronal responses in the dorsal hippocampus.

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