Representation Of Stimuli Research Articles

Representational maps in the brain: concepts, approaches, and applications.

Neural systems have evolved to process sensory stimuli in a way that allows for efficient and adaptive behavior in a complex environment. Recent technological advances enable us to investigate sensory processing in animal models by simultaneously recording the activity of large populations of neurons with single-cell resolution, yielding high-dimensional datasets. In this review, we discuss concepts and approaches for assessing the population-level representation of sensory stimuli in the form of a representational map. In such a map, not only are the identities of stimuli distinctly represented, but their relational similarity is also mapped onto the space of neuronal activity. We highlight example studies in which the structure of representational maps in the brain are estimated from recordings in humans as well as animals and compare their methodological approaches. Finally, we integrate these aspects and provide an outlook for how the concept of representational maps could be applied to various fields in basic and clinical neuroscience.

Unravelling the multisensory learning advantage: Different patterns of within and across frequency-specific interactions drive uni- and multisensory neuroplasticity

In the field of learning theory and practice, the superior efficacy of multisensory learning over uni-sensory is well-accepted. However, the underlying neural mechanisms at the macro-level of the human brain remain largely unexplored. This study addresses this gap by providing novel empirical evidence and a theoretical framework for understanding the superiority of multisensory learning. Through a cognitive, behavioral, and electroencephalographic assessment of carefully controlled uni-sensory and multisensory training interventions, our study uncovers a fundamental distinction in their neuroplastic patterns. A multilayered network analysis of pre- and post- training EEG data allowed us to model connectivity within and across different frequency bands at the cortical level. Pre-training EEG analysis unveils a complex network of distributed sources communicating through cross-frequency coupling, while comparison of pre- and post-training EEG data demonstrates significant differences in the reorganizational patterns of uni-sensory and multisensory learning. Uni-sensory training primarily modifies cross-frequency coupling between lower and higher frequencies, whereas multisensory training induces changes within the beta band in a more focused network, implying the development of a unified representation of audiovisual stimuli. In combination with behavioural and cognitive findings this suggests that, multisensory learning benefits from an automatic top-down transfer of training, while uni-sensory training relies mainly on limited bottom-up generalization. Our findings offer a compelling theoretical framework for understanding the advantage of multisensory learning.

Contribution of oxytocin and dopamine to the formation of neural clusters in the neocortex representing multimodal sensory stimuli

We have previously proposed a unified mechanism for the formation of contrasted representations of multimodal sensory stimuli in the activity of neocortical neurons. Contrasting is based on the opposite sign of modification of the efficacy of strong and weak excitatory inputs to the spiny cells of the striatum (the input structure of the basal ganglia) and the subsequent dopamine-dependent activity reorganizations in parallel cortico – basal ganglia – thalamocortical loops. Oxytocin and dopamine (through D1 receptors) can improve the contrast of these representations, contributing to the induction of LTP of the efficacy of excitation of cortical, thalamic, and hippocampal neurons innervating spiny cells. In addition, oxytocin and dopamine can improve contrasting enhancement by increasing the signal-to-noise ratio in the neocortex, hippocampus, and striatum. A proposed mechanism for increasing the signal-to-noise ratio is based on the opposite sign of a long-term modification of the efficacy of monosynaptic excitatory and disynaptic inhibitory inputs, simultaneously affecting the postsynaptic neuron. The proposed mechanisms may underlie the contribution of oxytocin and dopamine to improving the formation and long-term maintenance of activity in neuronal groups with similar receptive fields that form columns in the primary visual cortex, a tonotopic map in the primary auditory cortex, a somatotopic map in the sensorimotor cortex, and distributed clusters in the olfactory piriform cortex. These mechanisms differ from the commonly accepted mechanisms of the formation of neuronal clusters in the neocortex with similar RPs, that are based on afferent and lateral excitation and inhibition, which does not allow providing the specificity and duration of effects. Understanding the mechanisms of involvement of oxytocin and dopamine in the processing of multimodal sensory information may be useful for developing treatments for some disorders of social behavior.

Altered neural representation of olfactory food reward in the nucleus accumbens after acute stress

Acute stress impairs reward processing. The nucleus accumbens (NAcc) plays an important role in the processing of primary rewards such as food. The present study investigates how acute stress affects the olfactory food reward processing in the NAcc using the representational similarity analysis. Forty-eight participants underwent an olfactory fMRI session following either an acute psychosocial stress (N = 24; stress group) or a control (N = 24; control group). Brain activation was recorded during the anticipatory and the perceptual phases of high-calorie food, low-calorie food, and non-food odor stimuli. Compared to the control group, the stress group rated the high-calorie food odor as significantly more pleasant (p = 0.005). In the NAcc, acute stress significantly reduced the dissimilarity of food and non-food odors in the perceptual phase (p = 0.027) and marginally reduced the dissimilarity of high- and low-calorie foods in the anticipatory phase (p = 0.095). Significant negative correlations were observed between the level of NAcc representational differentiation for high- and low-calorie food odors during perception and the difference in pleasantness ratings between high- and low-calorie food odors (r = -0.40, p = 0.005). These findings suggest that acute stress may impair participants’ ability to discriminate between olfactory food rewards, leading individuals to seek out more palatable foods in stressful situations in order to maintain positive emotions.

Distributed feature representations of natural stimuli across parallel retinal pathways

How sensory systems extract salient features from natural environments and organize them across neural pathways is unclear. Combining single-cell and population two-photon calcium imaging in mice, we discover that retinal ON bipolar cells (second-order neurons of the visual system) are divided into two blocks of four types. The two blocks distribute temporal and spatial information encoding, respectively. ON bipolar cell axons co-stratify within each block, but separate laminarly between them (upper block: diverse temporal, uniform spatial tuning; lower block: diverse spatial, uniform temporal tuning). ON bipolar cells extract temporal and spatial features similarly from artificial and naturalistic stimuli. In addition, they differ in sensitivity to coherent motion in naturalistic movies. Motion information is distributed across ON bipolar cells in the upper and the lower blocks, multiplexed with temporal and spatial contrast, independent features of natural scenes. Comparing the responses of different boutons within the same arbor, we find that axons of all ON bipolar cell types function as computational units. Thus, our results provide insights into the visual feature extraction from naturalistic stimuli and reveal how structural and functional organization cooperate to generate parallel ON pathways for temporal and spatial information in the mammalian retina.

Cognitive and developmental contributions to psychometric functions on three auditory tasks during adolescence and young adulthood

Auditory perceptual tasks mature at different rates, with temporal tasks having longer developmental courses. We tested 10- to 23-year-olds on frequency discrimination, temporal-interval discrimination, and gap detection using the method of constant stimuli. During task performance, listening effort data were collected via eye-tracker. A cognitive battery was also administered. Thresholds correlated between the frequency and temporal-interval discrimination conditions, which shared the same standard stimulus, but not between other conditions. The slopes of the psychometric functions did not correlate between conditions, suggesting that different or time-varying factors might contribute to slopes on these conditions. Shallower psychometric functions corresponded to poorer thresholds on only the temporal-interval and gap conditions, implying a potential role for attention, engagement, fatigue, or the stability of the stimulus representations on those conditions. Regression modeling indicated a limited role of age: Age predicted thresholds on the temporal-interval discrimination condition and slopes on both the frequency and temporal-interval discrimination conditions. Testing order affected performance on frequency discrimination (threshold) and temporal-interval discrimination (threshold and slope). The measures of listening effort and cognition that predicted thresholds and slopes also differed between those two conditions. On gap detection, neither threshold nor slope was predicted by any variable. [Work funded by NIDCD.]

Distinct neural signatures underlying information maintenance and manipulation in working memory.

Previous working memory research has demonstrated robust stimulus representations during memory maintenance in both voltage and alpha-band activity in electroencephalography. However, the exact functions of these 2 neural signatures have remained controversial. Here we systematically investigated their respective contributions to memory manipulation. Human participants either maintained a previously seen spatial location, or manipulated the location following a mental rotation cue over a delay. Using multivariate decoding, we observed robust location representations in low-frequency voltage and alpha-band oscillatory activity with distinct spatiotemporal dynamics: location representations were most evident in posterior channels in alpha-band activity, but were most prominent in the more anterior, central channels in voltage signals. Moreover, the temporal emergence of manipulated representation in central voltage preceded that in posterior alpha-band activity, suggesting that voltage might carry stimulus-specific source signals originated internally from anterior cortex, whereas alpha-band activity might reflect feedback signals in posterior cortex received from higher-order cortex. Lastly, while location representations in both signals were coded in a low-dimensional neural subspace, location representation in central voltage was higher-dimensional and underwent a representational transformation that exclusively predicted memory behavior. Together, these results highlight the crucial role of central voltage in working memory, and support functional distinctions between voltage and alpha-band activity.

Early visual cortices reveal interrelated item and category representations in aging.

Neural dedifferentiation, the finding that neural representations tend to be less distinct in older adults compared with younger adults, has been associated with age-related declines in memory performance. Most studies assessing the relation between memory and neural dedifferentiation have evaluated how age impacts the distinctiveness of neural representations for different visual categories (e.g., scenes and objects). However, how age impacts the quality of neural representations at the level of individual items is still an open question. Here, we present data from an age-comparative fMRI study that aimed to understand how the distinctiveness of neural representations for individual stimuli differs between younger and older adults and relates to memory outcomes. Pattern similarity searchlight analyses yielded indicators of neural dedifferentiation at the level of individual items as well as at the category level in posterior occipital cortices. We asked whether age differences in neural distinctiveness at each representational level were associated with inter- and/or intraindividual variability in memory performance. While age-related dedifferentiation at both the item and category level related to between-person differences in memory, neural distinctiveness at the category level also tracked within-person variability in memory performance. Concurrently, neural distinctiveness at the item level was strongly associated with neural distinctiveness at the category level both within and across participants, elucidating a potential representational mechanism linking item- and category-level distinctiveness. In sum, we provide evidence that age-related neural dedifferentiation co-exists across multiple representational levels and is related to memory performance.Significance Statement Age-related memory decline has been associated with neural dedifferentiation, the finding that older adults have less distinctive neural representations than younger adults. This has been mostly shown for category information, while evidence for age differences in the specificity of item representations is meager. We used pattern similarity searchlight analyses to find indicators of neural dedifferentiation at both levels of representation (category and item) and linked distinctiveness to memory performance. Both item- and category-level dedifferentiation in the calcarine cortex were related to interindividual differences in memory performance, while category-level distinctiveness further tracked intraindividual variability. Crucially, neural distinctiveness was strongly tied between the item and category levels, indicating that intersecting representational properties of posterior occipital cortices reflect both individual exemplars and categories.

Role of the left inferior frontal gyrus in transforming format types of action descriptions between stimuli and representations

We performed a functional magnetic resonance imaging study to elucidate the process involved in the transformation of the format types of action descriptions between stimuli and representations. We independently manipulated the format types of both stimuli (visual action [Vi] vs. verbal [Ve] stimulus) and internal representations (Vi vs. Ve representation) and set four types of experimental tasks. Each participant was required to generate a Vi or Ve representation after being presented with a Vi or Ve stimulus, according to each task. Increased activity in the left inferior frontal gyrus (IFG) (Brodmann areas 44 and 45) was found in the transformation contrast: ([Vi stimulus and Ve representation] + [Ve stimulus and Vi representation]) > ([Vi stimulus and Vi representation] + [Ve stimulus and Ve representation]). This result suggests that the left IFG is involved with the transformation process and has the function of generating an internal representation in a format different from that of externally presented stimuli.

Bold colors, sweeping melodies, offensive smells

Abstract This paper presents a corpus-based exploratory study of the figurative conceptualizations of visual, auditory, and olfactory stimuli in English and Hungarian. Through a manual semantic analysis of altogether 6,800 occurrences of 18 sensory nouns (three per sensory modality in each language) in the TenTen corpora, the following conceptualization types of perceptual stimuli have been examined: reification, agentification, animization, and personification. The paper presents the relative frequencies of these conceptualizations along with their subtypes and concrete linguistic manifestations in English and Hungarian. Among a number of interesting observations that call for further investigations, the following findings merit special attention: (1) visual stimuli have the lowest values in every category; (2) in both languages, agentification is the most typical in the case of olfaction; (3) with the exception of representations of olfactory stimuli as living beings, every conceptualization type is more frequent in the Hungarian data.

Asymmetric stimulus representations bias visual perceptual learning.

The primate visual cortex contains various regions that exhibit specialization for different stimulus properties, such as motion, shape, and color. Within each region, there is often further specialization, such that particular stimulus features, such as horizontal and vertical orientations, are over-represented. These asymmetries are associated with well-known perceptual biases, but little is known about how they influence visual learning. Most theories would predict that learning is optimal, in the sense that it is unaffected by these asymmetries. However, other approaches to learning would result in specific patterns of perceptual biases. To distinguish between these possibilities, we trained human observers to discriminate between expanding and contracting motion patterns, which have a highly asymmetrical representation in the visual cortex. Observers exhibited biased percepts of these stimuli, and these biases were affected by training in ways that were often suboptimal. We simulated different neural network models and found that a learning rule that involved only adjustments to decision criteria, rather than connection weights, could account for our data. These results suggest that cortical asymmetries influence visual perception and that human observers often rely on suboptimal strategies for learning.

A generative model of electrophysiological brain responses to stimulation.

Each brain response to a stimulus is, to a large extent, unique. However this variability, our perceptual experience feels stable. Standard decoding models, which utilise information across several areas to tap into stimuli representation and processing, are fundamentally based on averages. Therefore, they can focus precisely on the features that are most stable across stimulus presentations. But which are these features exactly is difficult to address in the absence of a generative model of the signal. Here, I introduce genephys, a generative model of brain responses to stimulation publicly available as a Python package that, when confronted with a decoding algorithm, can reproduce the structured patterns of decoding accuracy that we observe in real data. Using this approach, I characterise how these patterns may be brought about by the different aspects of the signal, which in turn may translate into distinct putative neural mechanisms. In particular, the model shows that the features in the data that support successful decoding-and, therefore, likely reflect stable mechanisms of stimulus representation-have an oscillatory component that spans multiple channels, frequencies, and latencies of response; and an additive, slower response with a specific (cross-frequency) relation to the phase of the oscillatory component. At the individual trial level, still, responses are found to be highly variable, which can be due to various factors including phase noise and probabilistic activations.

A generative model of electrophysiological brain responses to stimulation

Each brain response to a stimulus is, to a large extent, unique. However this variability, our perceptual experience feels stable. Standard decoding models, which utilise information across several areas to tap into stimuli representation and processing, are fundamentally based on averages. Therefore, they can focus precisely on the features that are most stable across stimulus presentations. But which are these features exactly is difficult to address in the absence of a generative model of the signal. Here, I introduce genephys, a generative model of brain responses to stimulation publicly available as a Python package that, when confronted with a decoding algorithm, can reproduce the structured patterns of decoding accuracy that we observe in real data. Using this approach, I characterise how these patterns may be brought about by the different aspects of the signal, which in turn may translate into distinct putative neural mechanisms. In particular, the model shows that the features in the data that support successful decoding—and, therefore, likely reflect stable mechanisms of stimulus representation—have an oscillatory component that spans multiple channels, frequencies, and latencies of response; and an additive, slower response with a specific (cross-frequency) relation to the phase of the oscillatory component. At the individual trial level, still, responses are found to be highly variable, which can be due to various factors including phase noise and probabilistic activations.

Reconstructing Visual Stimulus Representation From EEG Signals Based on Deep Visual Representation Model

Reconstructing Visual Stimulus Representation From EEG Signals Based on Deep Visual Representation Model

Demands on perceptual and mnemonic fidelity are a key determinant of age-related cognitive decline throughout the lifespan.

Aging results in less detailed memories, reflecting reduced fidelity of remembered compared to real-world representations. We tested whether poorer representational fidelity across perception, short-term memory (STM), and long-term memory (LTM) are among the earliest signs of cognitive aging. Our paradigm probed target-lure object mnemonic discrimination and precision of object-location binding. Across the lifespan, cognitive deficits were observed in midlife when detailed stimulus representations were required for perceptual and short/long-term forced choice mnemonic discrimination. A continuous metric of object-location source memory combined with computational modeling demonstrated that errors in STM and LTM in middle-aged adults were largely driven by a loss of precision for retrieved memories, not necessarily by forgetting. On a trial-by-trial basis, fidelity of item and spatial information was more tightly bound in LTM compared to STM with this association being unaffected by age. Standard neuropsychological tests without demands on memory quality (digit span, verbal learning) were less sensitive to age effects than STM and LTM precision. Perceptual discrimination predicted mnemonic discrimination. Neuropsychological proxies for prefrontal executive functions correlated with STM, but not LTM fidelity. Conversely, neuropsychological indicators of hippocampal integrity correlated with mnemonic discrimination and precision of both STM and LTM, suggesting partially dissociable mechanisms of interindividual variability in STM and LTM fidelity. These findings suggest that reduced representational fidelity is a hallmark of cognitive aging across perception, STM, and LTM and can be observed from midlife onward. Continuous memory precision tasks may be promising for the early detection of subtle age-related cognitive decline. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Performance Evaluation of Matrix Factorization for fMRI Data.

A hypothesis in the study of the brain is that sparse coding is realized in information representation of external stimuli, which has been experimentally confirmed for visual stimulus recently. However, unlike the specific functional region in the brain, sparse coding in information processing in the whole brain has not been clarified sufficiently. In this study, we investigate the validity of sparse coding in the whole human brain by applying various matrix factorization methods to functional magnetic resonance imaging data of neural activities in the brain. The result suggests the sparse coding hypothesis in information representation in the whole human brain, because extracted features from the sparse matrix factorization (MF) method, sparse principal component analysis (SparsePCA), or method of optimal directions (MOD) under a high sparsity setting or an approximate sparse MF method, fast independent component analysis (FastICA), can classify external visual stimuli more accurately than the nonsparse MF method or sparse MF method under a low sparsity setting.

The Contribution of the Corpus Callosum to the Symmetrical Representation of Taste in the Human Brain: An fMRI Study of Callosotomized Patients

The present study was designed to establish the contribution of the corpus callosum (CC) to the cortical representation of unilateral taste stimuli in the human primary gustatory area (GI). Unilateral taste stimulation of the tongue was applied to eight patients with partial or total callosal resection by placing a small cotton pad soaked in a salty solution on either side of the tongue. Functional images were acquired with a 1.5 Tesla machine. Diffusion tensor imaging and tractography were also performed. Unilateral taste stimuli evoked bilateral activation of the GI area in all patients, including those with total resection of the CC, with a prevalence in the ipsilateral hemisphere to the stimulated tongue side. Bilateral activation was also observed in the primary somatic sensory cortex (SI) in most patients, which was more intense in the contralateral SI. This report confirms previous functional studies carried out in control subjects and neuropsychological findings in callosotomized patients, showing that gustatory pathways from tongue to cortex are bilaterally distributed, with an ipsilateral predominance. It has been shown that the CC does play a role, although not an exclusive one, in the bilateral symmetrical representation of gustatory sensitivity in the GI area, at least for afferents from one side of the tongue.

Enhanced distractor filtering in habituation contexts: Learning to ignore is easier in familiar environments

Summary Habituation mechanisms play a pivotal role in enabling organisms to filter out irrelevant stimuli and concentrate on essential ones. Through repeated exposure, the brain learns to disregard stimuli that are irrelevant, effectively ceasing to respond to potentially distracting input. Previous studies have demonstrated that the orienting response to visual distractors disrupting visual detection tasks habituates as tasks progress and distractors are encountered repeatedly, as their initial interference diminishes. Theoretical models posit that this reduction is contingent upon the establishment of an internal representation of external stimuli. Moreover, further studies have indicated that habituation can be context- specific, suggesting that the mechanisms involved incorporate information about features of irrelevant stimuli that extend beyond their discrete characteristics. In this contribution, we further delved into the question of whether the context in which habituation occurs retains a general habituative capacity when a new, to-be-ignored stimulus is introduced. We discuss evidence indicating that the context in which habituation has already taken place facilitates the habituation process for a new stimulus. This suggests that it becomes easier to ignore new stimuli in contexts where we have already learned to disregard other stimuli, underscoring the intricate interplay between habituation, context, and attentional processes.

Decomposing Neural Circuit Function into Information Processing Primitives.

It is challenging to measure how specific aspects of coordinated neural dynamics translate into operations of information processing and, ultimately, cognitive functions. An obstacle is that simple circuit mechanisms-such as self-sustained or propagating activity and nonlinear summation of inputs-do not directly give rise to high-level functions. Nevertheless, they already implement simple the information carried by neural activity. Here, we propose that distinct functions, such as stimulus representation, working memory, or selective attention, stem from different combinations and types of low-level manipulations of information or information processing primitives. To test this hypothesis, we combine approaches from information theory with simulations of multi-scale neural circuits involving interacting brain regions that emulate well-defined cognitive functions. Specifically, we track the information dynamics emergent from patterns of neural dynamics, using quantitative metrics to detect where and when information is actively buffered, transferred or nonlinearly merged, as possible modes of low-level processing (storage, transfer and modification). We find that neuronal subsets maintaining representations in working memory or performing attentional gain modulation are signaled by their boosted involvement in operations of information storage or modification, respectively. Thus, information dynamic metrics, beyond detecting which network units participate in cognitive processing, also promise to specify how and when they do it, that is, through which type of primitive computation, a capability that may be exploited for the analysis of experimental recordings.

Stochastic resonance in sparse neuronal network: functional role of ongoing activity to detect weak sensory input in awake auditory cortex of rat.

The awake cortex is characterized by a higher level of ongoing spontaneous activity, but it has a better detectability of weak sensory inputs than the anesthetized cortex. However, the computational mechanism underlying this paradoxical nature of awake neuronal activity remains to be elucidated. Here, we propose a hypothetical stochastic resonance, which improves the signal-to-noise ratio (SNR) of weak sensory inputs through nonlinear relations between ongoing spontaneous activities and sensory-evoked activities. Prestimulus and tone-evoked activities were investigated via in vivo extracellular recording with a dense microelectrode array covering the entire auditory cortex in rats in both awake and anesthetized states. We found that tone-evoked activities increased supralinearly with the prestimulus activity level in the awake state and that the SNR of weak stimulus representation was optimized at an intermediate level of prestimulus ongoing activity. Furthermore, the temporally intermittent firing pattern, but not the trial-by-trial reliability or the fluctuation of local field potential, was identified as a relevant factor for SNR improvement. Since ongoing activity differs among neurons, hypothetical stochastic resonance or "sparse network stochastic resonance" might offer beneficial SNR improvement at the single-neuron level, which is compatible with the sparse representation in the sensory cortex.