The Development of Multisensory Integration in the Brain

Perception ◽  
1997 ◽  
Vol 26 (1_suppl) ◽  
pp. 35-35 ◽  
Author(s):  
M T Wallace
Keyword(s):  
Multisensory Integration ◽  
Time Course ◽  
Receptive Fields ◽  
Developmental Time ◽  
Response Latencies ◽  
Sensory Stimuli ◽  
Sensory Inputs ◽  
Response Enhancement ◽  
Sensory Responses ◽  
The Brain

Multisensory integration in the superior colliculus (SC) of the cat requires a protracted postnatal developmental time course. Kittens 3 – 135 days postnatal (dpn) were examined and the first neuron capable of responding to two different sensory inputs (auditory and somatosensory) was not seen until 12 dpn. Visually responsive multisensory neurons were not encountered until 20 dpn. These early multisensory neurons responded weakly to sensory stimuli, had long response latencies, large receptive fields, and poorly developed response selectivities. Most striking, however, was their inability to integrate cross-modality cues in order to produce the significant response enhancement or depression characteristic of these neurons in adults. The incidence of multisensory neurons increased gradually over the next 10 – 12 weeks. During this period, sensory responses became more robust, latencies shortened, receptive fields decreased in size, and unimodal selectivities matured. The first neurons capable of cross-modality integration were seen at 28 dpn. For the following two months, the incidence of such integrative neurons rose gradually until adult-like values were achieved. Surprisingly, however, as soon as a multisensory neuron exhibited this capacity, most of its integrative features were indistinguishable from those in adults. Given what is known about the requirements for multisensory integration in adult animals, this observation suggests that the appearance of multisensory integration reflects the onset of functional corticotectal inputs.

scholarly journals Development of Thalamocortical Response Transformations in the Rat Whisker-Barrel System

2008 ◽  
Vol 99 (1) ◽  
pp. 356-366 ◽  
Author(s):  
Michael Shoykhet ◽  
Daniel J. Simons
Keyword(s):  
Cortical Neurons ◽  
Time Course ◽  
Receptive Fields ◽  
Second Phase ◽  
Adult Rats ◽  
Response Latencies ◽  
Thalamic Neurons ◽  
Response Properties ◽  
Temporal Domain

Extracellular single-unit recordings were used to characterize responses of thalamic barreloid and cortical barrel neurons to controlled whisker deflections in 2, 3-, and 4-wk-old and adult rats in vivo under fentanyl analgesia. Results indicate that response properties of thalamic and cortical neurons diverge during development. Responses to deflection onsets and offsets among thalamic neurons mature in parallel, whereas among cortical neurons responses to deflection offsets become disproportionately smaller with age. Thalamic neuron receptive fields become more multiwhisker, whereas those of cortical neurons become more single-whisker. Thalamic neurons develop a higher degree of angular selectivity, whereas that of cortical neurons remains constant. In the temporal domain, response latencies decrease both in thalamic and cortical neurons, but the maturation time-course differs between the two populations. Response latencies of thalamic cells decrease primarily between 2 and 3 wk of life, whereas response latencies of cortical neurons decrease in two distinct steps—the first between 2 and 3 wk of life and the second between the fourth postnatal week and adulthood. Although the first step likely reflects similar subcortical changes, the second phase likely corresponds to developmental myelination of thalamocortical fibers. Divergent development of thalamic and cortical response properties indicates that thalamocortical circuits in the whisker-to-barrel pathway undergo protracted maturation after 2 wk of life and provides a potential substrate for experience-dependent plasticity during this time.

scholarly journals Manifold-tiling Localized Receptive Fields are Optimal in Similarity-preserving Neural Networks

2018 ◽  
Author(s):  
Anirvan M. Sengupta ◽  
Mariano Tepper ◽  
Cengiz Pehlevan ◽  
Alexander Genkin ◽  
Dmitri B. Chklovskii
Keyword(s):  
Neural Networks ◽  
Receptive Fields ◽  
Small Neighborhood ◽  
Place Cells ◽  
Optimal Solutions ◽  
Stimulus Space ◽  
Sensory Inputs ◽  
Similarity Preserving ◽  
Low Dimensional ◽  
The Brain

AbstractMany neurons in the brain, such as place cells in the rodent hippocampus, have localized receptive fields, i.e., they respond to a small neighborhood of stimulus space. What is the functional significance of such representations and how can they arise? Here, we propose that localized receptive fields emerge in similarity-preserving networks of rectifying neurons that learn low-dimensional manifolds populated by sensory inputs. Numerical simulations of such networks on standard datasets yield manifold-tiling localized receptive fields. More generally, we show analytically that, for data lying on symmetric manifolds, optimal solutions of objectives, from which similarity-preserving networks are derived, have localized receptive fields. Therefore, nonnegative similarity-preserving mapping (NSM) implemented by neural networks can model representations of continuous manifolds in the brain.

The physiology of wandering behaviour in Manduca sexta. III. Organization of wandering behaviour in the larval nervous system

1986 ◽  
Vol 121 (1) ◽  
pp. 115-132 ◽  
Author(s):  
O. S. Dominick ◽  
J. W. Truman
Keyword(s):  
Manduca Sexta ◽  
Motor Pattern ◽  
Inhibitory Influence ◽  
Sensory Stimuli ◽  
Sensory Inputs ◽  
Spontaneous Movements ◽  
Locomotor Patterns ◽  
Pattern Generators ◽  
Thoracic And Abdominal ◽  
The Brain

The locomotor patterns typical of wandering behaviour were studied electromyographically in abdominal segments of freely moving larvae of Manduca sexta. Crawling locomotion consisted of stereotyped, anteriorly-directed, peristaltic waves of intersegmental muscle contraction. During burrowing the intersegmental muscles of all abdominal segments contracted simultaneously for several consecutive cycles and then performed a single bout of the crawling pattern. Sensory inputs determined which motor patterns were used and how they were modified. Local sensory inputs could modify patterns in the specific segments affected. The neural circuitry that was required to generate the peristaltic and bracing patterns was repeated among the thoracic and abdominal ganglia, and normally wa activated by the suboesophageal ganglion (SEG) and brain. In the absence of connections with the SEG and brain the segmental motor pattern generators could be activated by strong sensory stimuli. When the thoracic and abdominal segments lacked connections with the SEG, spontaneous movements were infrequent prior to wandering, but increased markedly at wandering or following 20-hydroxyecdysone (20-HE) infusion. Prior to wandering the SEG drives spontaneous locomotion in debrained larvae, but this function disappears in wandering larvae, or following 20-HE infusion. Prior to wandering the brain exerted a net inhibitory influence on locomotion. Removal of the medial region of the brain abolished this inhibition, resulting in strong, continuous locomotion which was driven by the lateral region of the brain. This lateral excitatory function of the brain was not altered by 20-HE infusion prior to wandering, nor did it change with the appearance of wandering behaviour. We conclude that the locomotor patterns used during wandering are produced by pattern generators in the segmental ganglia and are modified by sensory information. The circuitry responsible for activating these motor pattern generators is associated with the SEG, and is under the control of the brain. The brain exerts a net inhibitory influence prior to wandering, which becomes excitatory during wandering. Ecdysteroids appear to alter locomotor function by acting at various levels including the segmental ganglia, the SEG and the brain. A model is advanced describing this effect.

Representation and integration of multiple sensory inputs in primate superior colliculus

1996 ◽  
Vol 76 (2) ◽  
pp. 1246-1266 ◽  
Author(s):  
M. T. Wallace ◽  
L. K. Wilkinson ◽  
B. E. Stein
Keyword(s):  
Superior Colliculus ◽  
Multisensory Integration ◽  
Deep Layer ◽  
Subcutaneous Tissue ◽  
Broad Band ◽  
Sensory Modality ◽  
Receptive Fields ◽  
Maximal Response ◽  
Critical Feature ◽  
Response Enhancement

1. The properties of visual-, auditory-, and somatosensory-responsive neurons, as well as of neurons responsive to multiple sensory cues (i.e., multisensory), were examined in the superior colliculus of the rhesus monkey. Although superficial layer neurons responded exclusively to visual stimuli and visual inputs predominated in deeper layers, there was also a rich nonvisual and multisensory representation in the superior colliculus. More than a quarter (27.8%) of the deep layer population responded to stimuli from more than a single sensory modality. In contrast, 37% responded only to visual cues, 17.6% to auditory cues, and 17.6% to somatosensory cues. Unimodal- and multisensory-responsive neurons were clustered by modality. Each of these modalities was represented in map-like fashion, and the different representations were in alignment with one another. 2. Most deep layer visually responsive neurons were binocular and exhibited poor selectivity for such stimulus characteristics as orientation, velocity, and direction of movement. Similarly, most auditory-responsive neurons had contralateral receptive fields and were binaural, but had little frequency selectivity and preferred complex, broad-band sounds. Somatosensory-responsive neurons were overwhelmingly contralateral, high velocity, and rapidly adapting. Only rarely did somatosensory-responsive neurons require distortion of subcutaneous tissue for activation. 3. The spatial congruence among the different receptive fields of multisensory neurons was a critical feature underlying their ability to synthesize cross-modal information. 4. Combinations of stimuli could have very different consequences in the same neuron, depending on their temporal and spatial relationships. Generally, multisensory interactions were evident when pairs of stimuli were separated from one another by < 500 ms, and the products of these interactions far exceeded the sum of their unimodal components. Whether the combination of stimuli produced response enhancement, response depression, or no interaction depended on the location of the stimuli relative to one another and to their respective receptive fields. Maximal response enhancements were observed when stimuli originated from similar locations in space (as when derived from the same event) because they fell within the excitatory receptive fields of the same multisensory neurons. If, however, the stimuli were spatially disparate such that one fell beyond the excitatory borders of its receptive field, either no interaction was produced or this stimulus depressed the effectiveness of the other. Furthermore, maximal response interactions were seen with the pairing of weakly effective unimodal stimuli. As the individual unimodal stimuli became increasingly effective, the levels of response enhancement to stimulus combinations declined, a principle referred to as inverse effectiveness. Many of the integrative principles seen here in the primate superior colliculus are strikingly similar to those observed in the cat. These observations indicate that a set of common principles of multisensory integration is adaptable in widely divergent species living in very different ecological situations. 5. Surprisingly, a few multisensory neurons had individual receptive fields that were not in register with one another. This has not been noted in multisensory neurons of other species, and these "anomalous" receptive fields could present a daunting problem: stimuli originating from the same general location in space cannot simultaneously fall within their respective receptive fields, a stimulus pairing that may result in response depression. Conversely, stimuli that originate from separate events and disparate locations (and fall within their receptive fields) may result in response enhancement. However, the spatial principle of multisensory integration did not apply in these cases. (ABSTRACT TRUNCATED)

scholarly journals Encoding and Decoding Dynamic Sensory Signals with Recurrent Neural Networks: An Application of Conceptors to Birdsongs

2017 ◽  
Author(s):  
Richard Gast ◽  
Patrick Faion ◽  
Kai Standvoss ◽  
Andrea Suckro ◽  
Brian Lewis ◽  
...  
Keyword(s):  
Hierarchical Structure ◽  
Activity Patterns ◽  
Receptive Fields ◽  
Model Performance ◽  
Relevant Information ◽  
Learning Approaches ◽  
Sensory Stimuli ◽  
Dynamic Stimuli ◽  
Neural Populations ◽  
The Brain

AbstractIn a constantly changing environment the brain has to make sense of dynamic patterns of sensory input. These patterns can refer to stimuli with a complex and hierarchical structure which has to be inferred from the neural activity of sensory areas in the brain. Such areas were found to be locally recurrently structured as well as hierarchically organized within a given sensory domain. While there is a great body of work identifying neural representations of various sensory stimuli at different hierarchical levels, less is known about the nature of these representations. In this work, we propose a model that describes a way to encode and decode sensory stimuli based on the activity patterns of multiple, recurrently connected neural populations with different receptive fields. We demonstrate the ability of our model to learn and recognize complex, dynamic stimuli using birdsongs as exemplary data. These birdsongs can be described by a 2-level hierarchical structure, i.e. as sequences of syllables. Our model matches this hierarchy by learning single syllables on a first level and sequences of these syllables on a top level. Model performance on recognition tasks is investigated for an increasing number of syllables or songs to recognize and compared to state-of-the-art machine learning approaches. Finally, we discuss the implications of our model for the understanding of sensory pattern processing in the brain. We conclude that the employed encoding and decoding mechanisms might capture general computational principles of how the brain extracts relevant information from the activity of recurrently connected neural populations.

scholarly journals Task-dependent modulation of SI physiological responses to targets and distractors

2013 ◽  
Vol 109 (4) ◽  
pp. 1036-1044 ◽  
Author(s):  
Elsie Spingath ◽  
Hyun-Sug Kang ◽  
David T. Blake
Keyword(s):  
Time Course ◽  
Cortical Plasticity ◽  
Task Demands ◽  
Neural Responses ◽  
Task Condition ◽  
Sensory Stimuli ◽  
Cortical Implants ◽  
Physically Identical ◽  
The Relationship ◽  
The Brain

Selective attention experimental designs have shown that neural responses to stimuli in primary somatosensory cortex are stronger when the sensory stimuli are task relevant. Other studies have used animals under no task demands for data collection. The relationship between neural responses in the brain during behavior, and while an animal has no task demands, remains underexplored. We trained two animals to perform somatosensory detection for several weeks, followed by somatosensory discrimination for several weeks. Data in response to physically identical stimuli were collected from cortical implants while the animal was under no task demands before each behavioral session and also during that behavioral session. The Fourier spectra of the field potentials during detection or discrimination compared with the no task condition demonstrated suppression of the somatosensory μ-rhythm that is associated with readiness and anticipation of cognitive use of somatosensory and motor inputs. Responses to the task target were stronger during detection and discrimination than in the no task condition. The amplitude normalized time course of the target evoked response was similar in both cases. Evoked responses to the task distractor were not significantly stronger during behavior than in recordings under no task demands. The normalized time course of the distractor responses showed a suppression that peaks 30–35 ms after the onset of the response. The selectivity of this within trial suppression is the same as the selectivity of enduring suppression evident in studies of sensory cortical plasticity, which suggests the same neural process may be responsible for both.

scholarly journals Influence of Subcortical Inhibition on Barrel Cortex Receptive Fields

2009 ◽  
Vol 102 (1) ◽  
pp. 437-450 ◽  
Author(s):  
Akio Hirata ◽  
Juan Aguilar ◽  
Manuel A. Castro-Alamancos
Keyword(s):  
Receptive Field ◽  
High Frequency ◽  
Gaba Receptor ◽  
Barrel Cortex ◽  
Receptive Fields ◽  
Neural Responses ◽  
Sensory Stimuli ◽  
Long Latency ◽  
Actual Degree ◽  
Sensory Responses

Influence of subcortical inhibition on barrel cortex receptive fields. By the time neural responses driven by vibrissa stimuli reach the barrel cortex, they have undergone significant spatial and temporal transformations within subcortical relays. A major regulator of these transformations is thought to be subcortical GABA-mediated inhibition, but the actual degree of this influence is unknown. We used disinhibition produced by GABA receptor antagonists to unmask the excitatory sensory responses that are normally suppressed by inhibition in the main subcortical sensory relays to barrel cortex; principal trigeminal (Pr5) and primary thalamic (VPM) nuclei. We found that, within subcortical relays, inhibition only slightly suppresses short-latency receptive field responses, but robustly suppresses long-latency center and surround receptive field responses. However, the long-latency subcortical effects of inhibition are mostly not reflected in the barrel cortex. The most robust effect of subcortical inhibition on barrel cortex responses is to transiently suppress the receptive field responses of high-frequency sensory stimuli. This transient adaptation caused by subcortical inhibition recovers within a few stimuli and gives way to a steady-state adaptation that is independent of subcortical inhibition.

Integration of Sensory Information in the Brain

Perception ◽  
1997 ◽  
Vol 26 (1_suppl) ◽  
pp. 369-369
Author(s):  
B E Stein
Keyword(s):  
Superior Colliculus ◽  
Multisensory Integration ◽  
Receptive Fields ◽  
Sensory Information ◽  
Specific Response ◽  
Temporal Relationships ◽  
Perceptual Anomalies ◽  
The Many ◽  
Multisensory Information ◽  
The Brain

That sensory cues in one modality affect perception in another has been known for some time, and there are many examples of ‘intersensory’ influences within the broad phenomenon of cross-modal integration. The ability of the CNS to integrate cues from different sensory channels is particularly evident in the facilitated detection and reaction to combinations of concordant cues from different modalities, and in the dramatic perceptual anomalies that can occur when these cues are discordant. A substrate for multisensory integration is provided by the many CNS neurons (eg, in the superior colliculus) which receive convergent input from multiple sensory modalities. Similarities in the principles by which these neurons integrate multisensory information in different species point to a remarkable conservation in the integrative features of the CNS during vertebrate evolution. In general, profound enhancement or depression in neural activity can be induced in the same neuron, depending on the spatial and temporal relationships among the stimuli presented to it. The specific response product obtained in any given multisensory neuron is predictable on the basis of the features of its various receptive fields. Perhaps most striking, however, is the parallel which has been demonstrated between the properties of multisensory integration at the level of the single neuron in the superior colliculus and at the level of overt attentive and orientation behaviour.

scholarly journals A Dependency Capturing Code for Robust Object Representation

2019 ◽  
Author(s):  
Rishabh Raj ◽  
Dar Dahlen ◽  
Kyle Duyck ◽  
C. Ron Yu
Keyword(s):  
Sensory Processing ◽  
Object Representation ◽  
Learning Experience ◽  
Receptive Fields ◽  
Efficient Coding ◽  
Sensory Inputs ◽  
Redundant Feature ◽  
Deep Layers ◽  
Robust Face Recognition ◽  
The Brain

AbstractThe brain has a remarkable ability to recognize objects from noisy or corrupted sensory inputs. How this cognitive robustness is achieved computationally remains unknown. We present a coding paradigm, which encodes structural dependence among features of the input and transforms various forms of the same input into the same representation. The paradigm, through dimensionally expanded representation and sparsity constraint, allows redundant feature coding to enhance robustness and is efficient in representing objects. We demonstrate consistent representations of visual and olfactory objects under conditions of occlusion, high noise or with corrupted coding units. Robust face recognition is achievable without deep layers or large training sets. The paradigm produces both complex and simple receptive fields depending on learning experience, thereby offers a unifying framework of sensory processing.One line abstractWe present a framework of efficient coding of objects as a combination of structurally dependent feature groups that is robust against noise and corruption.

scholarly journals Rotational Dynamics Reduce Interference Between Sensory and Memory Representations

2019 ◽  
Author(s):  
Alexandra Libby ◽  
Timothy J. Buschman
Keyword(s):  
Sensory Information ◽  
Primary Auditory Cortex ◽  
Cell Types ◽  
Neural Population ◽  
Memory Representation ◽  
Sensory Stimuli ◽  
Sensory Inputs ◽  
Continuous Stream ◽  
Statistical Regularities ◽  
The Brain

AbstractSensory stimuli arrive in a continuous stream. By learning statistical regularities in the sequence of stimuli, the brain can predict future stimuli (Xu et al. 2012; Gavornik and Bear 2014; Maniscalco et al. 2018; J. Fiser and Aslin 2002). Such learning requires associating immediate sensory information with the memory of recently encountered stimuli (Ostojic and Fusi 2013; Kiyonaga et al. 2017). However, new sensory information can also interfere with short-term memories (Parthasarathy et al. 2017). How the brain prevents such interference is unknown. Here, we show that sensory representations rotate in neural space over time, to form an independent memory representation, thus reducing interference with future sensory inputs. We used an implicit learning paradigm in mice to study how statistical regularities in a sequence of stimuli are learned and represented in primary auditory cortex. Mice experienced both common sequences of stimuli (e.g. ABCD) and uncommon sequences (e.g. XYCD). Over four days of learning, the neural population representation of commonly associated stimuli (e.g. A and C) converged. This facilitated the prediction of upcoming stimuli, but also led unexpected sensory inputs to overwrite the sensory representation of previous stimuli (postdiction). Surprisingly, we found the memory of previous stimuli persisted in a second, orthogonal dimension. Unsupervised clustering of functional cell types revealed that the emergence of this second memory dimension is supported by two separate types of neurons; a ‘stable’ population that maintained its selectivity throughout the sequence and a ‘switching’ population that dynamically inverted its selectivity. This combination of sustained and dynamic representations produces a rotation of the encoding dimension in the neural population. This rotational dynamic may be a general principle, by which the cortex protects memories of prior events from interference by incoming stimuli.

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