Neural Processing in the Subsecond Time Range in the Temporal Cortex

1998 ◽  
Vol 10 (3) ◽  
pp. 567-595 ◽  
Author(s):  
Kiyohiko Nakamura
Keyword(s):  
Empirical Data ◽  
Cortical Neurons ◽  
Model Simulation ◽  
Temporal Cortex ◽  
Time Range ◽  
Neural Responses ◽  
Neuronal Populations ◽  
Cortical Areas ◽  
Response Onset ◽  
Ventral Pathway

The hypothesis that cortical processing of the millisecond time range is performed by latency competition between the first spikes produced by neuronal populations is analyzed. First, theorems that describe how the mechanism of latency competition works in a model cortex are presented. The model is a sequence of cortical areas, each of which is an array of neuronal populations that laterally inhibit each other. Model neurons are integrate-and-fire neurons. Second, the model is applied to the ventral pathway of the temporal lobe, and neuronal activity of the superior temporal sulcus of the monkey is reproduced with the model pathway. It consists of seven areas: V1, V2/V3, V4, PIT, CIT, AIT, and STPa. Neural activity predicted with the model is compared with empirical data. There are four main results: (1) Neural responses of the area STPa of the model showed the same fast discrimination between stimuli that the corresponding responses of the monkey did: both were significant within 5 ms of the response onset. (2) The hypothesis requires that the response latency of cortical neurons should be shorter for stronger responses. This requirement was verified by both the model simulation and the empirical data. (3) The model reproduced fast discrimination even when spontaneous random firing of 9 Hz was introduced to all the cells. This suggests that the latency competition performed by neuronal populations is robust. (4) After the first few competitions, the mechanism of latency competition always detected the strongest of input activations with different latencies.

scholarly journals Against memory systems

2002 ◽  
Vol 357 (1424) ◽  
pp. 1111-1121 ◽  
Author(s):  
David Gaffan
Keyword(s):  
Temporal Lobe ◽  
Cortical Neurons ◽  
Medial Temporal Lobe ◽  
Temporal Cortex ◽  
Memory Systems ◽  
Memory System ◽  
Memory Processing ◽  
Multiple Memory Systems ◽  
Cortical Areas ◽  
Severe Impairment

The medial temporal lobe is indispensable for normal memory processing in both human and non–human primates, as is shown by the fact that large lesions in it produce a severe impairment in the acquisition of new memories. The widely accepted inference from this observation is that the medial temporal cortex, including the hippocampal, entorhinal and perirhinal cortex, contains a memory system or multiple memory systems, which are specialized for the acquisition and storage of memories. Nevertheless, there are some strong arguments against this idea: medial temporal lesions produce amnesia by disconnecting the entire temporal cortex from neuromodulatory afferents arising in the brainstem and basal forebrain, not by removing cortex; the temporal cortex is essential for perception as well as for memory; and response properties of temporal cortical neurons make it impossible that some kinds of memory trace could be stored in the temporal lobe. All cortex is plastic, and it is possible that the same rules of plasticity apply to all cortical areas; therefore, memory traces are stored in widespread cortical areas rather than in a specialized memory system restricted to the temporal lobe. Among these areas, the prefrontal cortex has an important role in learning and memory, but is best understood as an area with no specialization of function.

Regional and Laminar Differences in In Vivo Firing Patterns of Primate Cortical Neurons

2005 ◽  
Vol 94 (1) ◽  
pp. 567-575 ◽  
Author(s):  
Shigeru Shinomoto ◽  
Youichi Miyazaki ◽  
Hiroshi Tamura ◽  
Ichiro Fujita
Keyword(s):  
Cortical Neurons ◽  
Temporal Cortex ◽  
Local Variation ◽  
Inferior Temporal Cortex ◽  
Regular Type ◽  
Cortical Areas ◽  
Different Types ◽  
Area Te ◽  
Firing Characteristics

The firing rates of cortical neurons change in time; yet, some aspects of their in vivo firing characteristics remain unchanged and are specific to individual neurons. A recent study has shown that neurons in the monkey medial motor areas can be grouped into 2 firing types, “likely random” and “quasi-regular,” according to a measure of local variation of interspike intervals. In the present study, we extended this analysis to area TE of the inferior temporal cortex and addressed whether this classification applies generally to different cortical areas and whether different types of neurons show different laminar distribution. We found that area TE did consist of 2 groups of neurons with different firing characteristics, one similar to the “likely random” type in the medial motor cortical areas, and the other exhibiting a “clumpy-bursty” firing pattern unique to TE. The quasi-regular type was rarely observed in area TE. The likely random firing type of neuron was more frequently found in layers V–VI than in layers II–III, whereas the opposite was true for the clumpy-bursty firing type. These results show that neocortical areas consist of heterogeneous neurons that differ from one area to another in their basic firing characteristics. Moreover, we show that spike trains obtained from a single cortical neuron can provide a clue that helps to identify its layer localization.

scholarly journals Adaptation in the visual cortex: a case for probing neuronal populations with natural stimuli

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 1246 ◽  
Author(s):  
Michoel Snow ◽  
Ruben Coen-Cagli ◽  
Odelia Schwartz
Keyword(s):  
Cortical Neurons ◽  
Natural Environments ◽  
Single Neurons ◽  
Neural Responses ◽  
Complete Understanding ◽  
Sensory Stimuli ◽  
Neuronal Populations ◽  
Natural Stimuli ◽  
The Past ◽  
Visual Cortical

The perception of, and neural responses to, sensory stimuli in the present are influenced by what has been observed in the past—a phenomenon known as adaptation. We focus on adaptation in visual cortical neurons as a paradigmatic example. We review recent work that represents two shifts in the way we study adaptation, namely (i) going beyond single neurons to study adaptation in populations of neurons and (ii) going beyond simple stimuli to study adaptation to natural stimuli. We suggest that efforts in these two directions, through a closer integration of experimental and modeling approaches, will enable a more complete understanding of cortical processing in natural environments.

Differences in Onset Latency of Macaque Inferotemporal Neural Responses to Primate and Non-Primate Faces

2005 ◽  
Vol 94 (2) ◽  
pp. 1587-1596 ◽  
Author(s):  
Roozbeh Kiani ◽  
Hossein Esteky ◽  
Keiji Tanaka
Keyword(s):  
Temporal Cortex ◽  
Inferior Temporal Cortex ◽  
Complex Object ◽  
Neural Responses ◽  
Onset Latency ◽  
Single Cell Responses ◽  
Response Onset ◽  
Stimulus Features ◽  
Animal Faces ◽  
Human Faces

Neurons in the visual system respond to different visual stimuli with different onset latencies. However, it has remained unknown which stimulus features, aside from stimulus contrast, determine the onset latencies of responses. To examine the possibility that response onset latencies carry information about complex object images, we recorded single-cell responses in the inferior temporal cortex of alert monkeys, while they viewed >1,000 object stimuli. Many cells responded to human and non-primate animal faces with comparable magnitudes but responded significantly more quickly to human faces than to non-primate animal faces. Differences in onset latency may be used to increase the coding capacity or enhance or suppress information about particular object groups by time-dependent modulation.

scholarly journals Formation of Category Representations in Superior Temporal Sulcus

2010 ◽  
Vol 22 (6) ◽  
pp. 1270-1282 ◽  
Author(s):  
Marieke van der Linden ◽  
Miranda van Turennout ◽  
Peter Indefrey
Keyword(s):  
Visual Experience ◽  
Temporal Cortex ◽  
Category Boundary ◽  
Superior Temporal Sulcus ◽  
Neuronal Populations ◽  
Cortical Areas ◽  
Object Categories ◽  
Highly Sensitive ◽  
Fmri Adaptation ◽  
The Brain

The human brain contains cortical areas specialized in representing object categories. Visual experience is known to change the responses in these category-selective areas of the brain. However, little is known about how category training specifically affects cortical category selectivity. Here, we investigated the experience-dependent formation of object categories using an fMRI adaptation paradigm. Outside the scanner, subjects were trained to categorize artificial bird types into arbitrary categories (jungle birds and desert birds). After training, neuronal populations in the occipito-temporal cortex, such as the fusiform and the lateral occipital gyrus, were highly sensitive to perceptual stimulus differences. This sensitivity was not present for novel birds, indicating experience-related changes in neuronal representations. Neurons in STS showed category selectivity. A release from adaptation in STS was only observed when two birds in a pair crossed the category boundary. This dissociation could not be explained by perceptual similarities because the physical difference between birds from the same side of the category boundary and between birds from opposite sides of the category boundary was equal. Together, the occipito-temporal cortex and the STS have the properties suitable for a system that can both generalize across stimuli and discriminate between them.

scholarly journals Dynamic Model of Visual Recognition Predicts Neural Response Properties in the Visual Cortex

1997 ◽  
Vol 9 (4) ◽  
pp. 721-763 ◽  
Author(s):  
Rajesh P. N. Rao ◽  
Dana H. Ballard
Keyword(s):  
Receptive Field ◽  
Cortical Neurons ◽  
Visual Recognition ◽  
Neural Response ◽  
Neural Responses ◽  
Response Properties ◽  
Cortical Areas ◽  
Mdl Principle ◽  
Classical Receptive Field ◽  
Visual Cortical

The responses of visual cortical neurons during fixation tasks can be significantly modulated by stimuli from beyond the classical receptive field. Modulatory effects in neural responses have also been recently reported in a task where a monkey freely views a natural scene. In this article, we describe a hierarchical network model of visual recognition that explains these experimental observations by using a form of the extended Kalman filter as given by the minimum description length (MDL) principle. The model dynamically combines input-driven bottom-up signals with expectation-driven top-down signals to predict current recognition state. Synaptic weights in the model are adapted in a Hebbian manner according to a learning rule also derived from the MDL principle. The resulting prediction-learning scheme can be viewed as implementing a form of the expectation-maximization (EM) algorithm. The architecture of the model posits an active computational role for the reciprocal connections between adjoining visual cortical areas in determining neural response properties. In particular, the model demonstrates the possible role of feedback from higher cortical areas in mediating neurophysiological effects due to stimuli from beyond the classical receptive field. Simulations of the model are provided that help explain the experimental observations regarding neural responses in both free viewing and fixating conditions.

scholarly journals Striatal and hippocampal contributions to flexible navigation in rats and humans

2020 ◽  
Vol 4 ◽  
pp. 239821282097977
Author(s):  
Christoffer J. Gahnstrom ◽  
Hugo J. Spiers
Keyword(s):  
Caudate Nucleus ◽  
Spatial Navigation ◽  
Dorsal Striatum ◽  
Future Research ◽  
Neural Responses ◽  
Learning Models ◽  
Transition Structure ◽  
Cortical Areas ◽  
Reinforcement Learning Models ◽  
Human Neuroimaging

The hippocampus has been firmly established as playing a crucial role in flexible navigation. Recent evidence suggests that dorsal striatum may also play an important role in such goal-directed behaviour in both rodents and humans. Across recent studies, activity in the caudate nucleus has been linked to forward planning and adaptation to changes in the environment. In particular, several human neuroimaging studies have found the caudate nucleus tracks information traditionally associated with that by the hippocampus. In this brief review, we examine this evidence and argue the dorsal striatum encodes the transition structure of the environment during flexible, goal-directed behaviour. We highlight that future research should explore the following: (1) Investigate neural responses during spatial navigation via a biophysically plausible framework explained by reinforcement learning models and (2) Observe the interaction between cortical areas and both the dorsal striatum and hippocampus during flexible navigation.

scholarly journals Subcortical circuits mediate communication between primary sensory cortical areas in mice

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Michael Lohse ◽  
Johannes C. Dahmen ◽  
Victoria M. Bajo ◽  
Andrew J. King
Keyword(s):  
Cortical Neurons ◽  
Common Property ◽  
Primary Auditory Cortex ◽  
Facilitatory Effect ◽  
Thalamic Nuclei ◽  
Auditory Midbrain ◽  
Cortical Areas ◽  
Auditory Responses ◽  
Evoked Activity

AbstractIntegration of information across the senses is critical for perception and is a common property of neurons in the cerebral cortex, where it is thought to arise primarily from corticocortical connections. Much less is known about the role of subcortical circuits in shaping the multisensory properties of cortical neurons. We show that stimulation of the whiskers causes widespread suppression of sound-evoked activity in mouse primary auditory cortex (A1). This suppression depends on the primary somatosensory cortex (S1), and is implemented through a descending circuit that links S1, via the auditory midbrain, with thalamic neurons that project to A1. Furthermore, a direct pathway from S1 has a facilitatory effect on auditory responses in higher-order thalamic nuclei that project to other brain areas. Crossmodal corticofugal projections to the auditory midbrain and thalamus therefore play a pivotal role in integrating multisensory signals and in enabling communication between different sensory cortical areas.

scholarly journals Cortical neurons exhibit diverse myelination patterns that scale between mouse brain regions and regenerate after demyelination

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Cody L. Call ◽  
Dwight E. Bergles
Keyword(s):  
Cortical Neurons ◽  
Regional Differences ◽  
Brain Regions ◽  
Axon Diameter ◽  
Neuronal Identity ◽  
Cortical Areas ◽  
Myelin Sheaths ◽  
Parvalbumin Interneurons ◽  
Selection Of

ABSTRACTAxons in the cerebral cortex show a broad range of myelin coverage. Oligodendrocytes establish this pattern by selecting a cohort of axons for myelination; however, the distribution of myelin on distinct neurons and extent of internode replacement after demyelination remain to be defined. Here we show that myelination patterns of seven distinct neuron subtypes in somatosensory cortex are influenced by both axon diameter and neuronal identity. Preference for myelination of parvalbumin interneurons was preserved between cortical areas with varying myelin density, suggesting that regional differences in myelin abundance arises through local control of oligodendrogenesis. By imaging loss and regeneration of myelin sheaths in vivo we show that myelin distribution on individual axons was altered but overall myelin content on distinct neuron subtypes was restored. Our findings suggest that local changes in myelination are tolerated, allowing regenerated oligodendrocytes to restore myelin content on distinct neurons through opportunistic selection of axons.

Neural Responses in Primary Auditory Cortex Mimic Psychophysical, Across-Frequency-Channel, Gap-Detection Thresholds

2000 ◽  
Vol 84 (3) ◽  
pp. 1453-1463 ◽  
Author(s):  
Jos J. Eggermont
Keyword(s):  
Auditory Cortex ◽  
Cortical Neurons ◽  
Primary Auditory Cortex ◽  
Noise Burst ◽  
Gap Detection ◽  
Frequency Content ◽  
Neural Responses ◽  
Frequency Channel ◽  
Interval Representations ◽  
Onset Response

Responses of single- and multi-units in primary auditory cortex were recorded for gap-in-noise stimuli for different durations of the leading noise burst. Both firing rate and inter-spike interval representations were evaluated. The minimum detectable gap decreased in exponential fashion with the duration of the leading burst to reach an asymptote for durations of 100 ms. Despite the fact that leading and trailing noise bursts had the same frequency content, the dependence on leading burst duration was correlated with psychophysical estimates of across frequency channel (different frequency content of leading and trailing burst) gap thresholds in humans. The duration of the leading burst plus that of the gap was represented in the all-order inter-spike interval histograms for cortical neurons. The recovery functions for cortical neurons could be modeled on basis of fast synaptic depression and after-hyperpolarization produced by the onset response to the leading noise burst. This suggests that the minimum gap representation in the firing pattern of neurons in primary auditory cortex, and minimum gap detection in behavioral tasks is largely determined by properties intrinsic to those, or potentially subcortical, cells.

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