Cortical Representation Research Articles

Search for approaches to transcranial neuromodulation in patients with post-stroke hemiparesis in real clinical practice

BACKGROUND: To increase the efficiency of motor recovery after a stroke in routine clinical practice, the search for selective biomarkers that determine the choice of the optimal strategy for noninvasive neuromodulation of the brain remains relevant. The study of interhemispheric interaction patterns can hypothetically help in determining the correct conceptual model of neuromodulation. AIM: To determine variants of interhemispheric interaction based on a correlation analysis of motor cortex excitability in patients with poststroke hemiparesis stratified by the degree of motor deficit. MATERIALS AND METHODS: This retrospective observational study involved 185 people (men, 56.2%; women, 43.8%) aged 19–88 years with verified poststroke hemiparesis and 40 healthy volunteers (men, 55.0%; women, 45.0%) aged 20–85 years. The patients underwent diagnostic transcranial magnetic stimulation in the projection of the cortical representation of m. abductor pollicis brevis and m. tibialis anterior of both brain hemispheres. The excitability level of the motor cortex and its interhemispheric asymmetry were recorded, and correlation analysis in subgroups stratified by the degree of paresis was performed. RESULTS: No interhemispheric correlation of resting motor thresholds (rMT) was found in patients with a level of muscle strength for the “hand” segment of 0–2 points (р 0.05). In the remaining subgroups, positive interhemispheric correlations of the rMT were noted (p 0.02). A positive correlation of the rMT of the damaged brain hemisphere and interhemispheric asymmetry of the motor cortex excitability for all degrees of paresis was observed when evaluating the cortical representation of the upper limb muscles. A negative correlation between the rMT of the unaffected brain hemisphere and interhemispheric asymmetry was detected for all degrees of motor deficit of the “foot” segment (p 0.02). CONCLUSION: The study did not confirm the concept of interhemispheric competition of the studied functional activity of the brain. Three authentic variants of interhemispheric interaction were identified: unidirectional hemispheric interaction with predominant reactivity of the affected hemisphere, unidirectional hemispheric interaction with predominant reactivity of the unaffected hemisphere, and functional interhemispheric dissociation. The results indicate the need to rethink some approaches to transcranial neuromodulation strategies in the analyzed cohort.

Enhancing tonal‐language learning through music: A review of experimental methods and melodic intonation therapy influences

AbstractThis literature review explores the impact of music on tonal language learning, with a focus on Mandarin Chinese. Utilising searches across major databases such as ERIC (EBSCO), ProQuest Central, Google Scholar, and Web of Science from 2005 to 2024, we selected relevant peer‐reviewed English‐language articles examining music's role in aiding tone acquisition and related cognitive processes. From 30 publications, findings are categorised into theoretical relationships, cognitive effects, melodic intonation therapy (MIT) applications and digital music applications. Theoretical frameworks emphasise the correlation between musicality and language proficiency, highlighting musicians' enhanced tonal perception and production skills. Cognitive effects include music's influence on pronunciation, memory and cultural understanding. MIT's effectiveness in tonal language learning is then discussed, emphasising its potential to improve cortical representations of tone categories. Finally, digital music applications are examined, focusing on language learning apps incorporating music for personalised and engaging learning experiences. The review finds significant literature reporting that music‐based methodologies, aligned with experiential learning paradigms, hold significant potential in Mandarin Chinese acquisition. They enhance listening comprehension, spoken language production, and understanding of grammar and syntax. Similar to MIT principles, music‐assisted tonal language learning utilises exaggerated melody and rhythm to improve language production, especially with complex words. This review is motivated by the recognition of music's potential benefits in language education, especially for tonal languages. It aims to provide educators and researchers with insights into effective methods and applications, guiding instructional practices and stimulating further empirical investigations in this interdisciplinary field. Ultimately, it contributes to the ongoing discourse on optimising tonal language learning methodologies.

The cortical representation of transitivity: Insights from tractography-based inhibitory nTMS

Navigated Transcranial Magnetic Stimulation (nTMS) is commonly used to causally identify cortical regions involved in language processing. Combining tractography with nTMS has been shown to increase induced error rates by targeting stimulation of cortical terminations of white matter fibers. According to functional Magnetic Resonance Imaging (fMRI) data, bilateral cortical areas connected by the arcuate fasciculus (AF) have been implicated in the processing of transitive compared to unergative verbs. To test this connection between transitivity and bilateral perisylvian regions, we administered a tractography-based inhibitory nTMS protocol during action naming of finite transitive (The man reads) and unergative (The man sails) verbs. After tracking the left and right AF, we stimulated the cortical terminations of the tract in frontal, parietal and temporal regions in 20 neurologically healthy native speakers of German. Results revealed that nTMS induced more errors during transitive compared to unergative verb naming when stimulating the left (vs right) AF terminations. This effect was specific to the left temporal terminations of the AF, whereas no differences between the two verb types were identified when stimulating inferior parietal and frontal AF terminations. Induced errors for transitive verbs over left temporal terminations mostly manifested as access errors (i.e., hesitations). Given the inhibitory nature of our nTMS protocol, these results suggest that temporal regions of the left hemisphere play a crucial role in argument structure processing. Our findings align with previous data on the role of left posterior temporal regions in language processing and by providing further evidence from a language production experiment using tractography-based inhibitory nTMS.

Rapid emergence of latent knowledge in the sensory cortex drives learning.

Rapid learning confers significant advantages to animals in ecological environments. Despite the need for speed, animals appear to only slowly learn to associate rewarded actions with predictive cues1-4. This slow learning is thought to be supported by a gradual expansion of predictive cue representation in the sensory cortex2,5. However, evidence is growing that animals learn more rapidly than classical performance measures suggest6-8, challenging the prevailing model of sensory cortical plasticity. Here, we investigated the relationship between learning and sensory cortical representations. We trained mice on an auditory go/no-go task that dissociated the rapid acquisition of task contingencies (learning) from its slower expression (performance)7. Optogenetic silencing demonstrated that the auditory cortex (AC) drives both rapid learning and slower performance gains but becomes dispensable at expert. Rather than enhancement or expansion of cue representations9, two-photon calcium imaging of AC excitatory neurons throughout learning revealed two higher-order signals that were causal to learning and performance. First, a reward prediction (RP) signal emerged rapidly within tens of trials, was present after action-related errors only early in training, and faded at expert levels. Strikingly, silencing at the time of the RP signal impaired rapid learning, suggesting it serves an associative and teaching role. Second, a distinct cell ensemble encoded and controlled licking suppression that drove the slower performance improvements. These two ensembles were spatially clustered but uncoupled from underlying sensory representations, indicating a higher-order functional segregation within AC. Our results reveal that the sensory cortex manifests higher-order computations that separably drive rapid learning and slower performance improvements, reshaping our understanding of the fundamental role of the sensory cortex.

Heartbeat evoked potentials and autonomic arousal during dissociative seizures: insights from electrophysiology and neuroimaging

IntroductionDissociative seizures often occur in the context of dysregulated affective arousal and entail dissociative symptoms such as a disintegration of bodily awareness. However, the interplay between affective arousal and changes...

The neural representation of body part concepts.

Neuropsychological and neuroimaging studies provide evidence for a degree of category-related organization of conceptual knowledge in the brain. Some of this evidence indicates that body part concepts are distinctly represented from other categories; yet, the neural correlates and mechanisms underlying these dissociations are unclear. We expand on the limited prior data by measuring functional magnetic resonance imaging responses induced by body part words and performing a series of analyses investigating the cortical representation of this semantic category. Across voxel-level contrasts, pattern classification, representational similarity analysis, and vertex-wise encoding analyses, we find converging evidence that the posterior middle temporal gyrus, the supramarginal gyrus, and the ventral premotor cortex in the left hemisphere play important roles in the preferential representation of this category compared to other concrete objects.

Decoding state-dependent cortical-cerebellar cellular functional connectivity in the mouse brain

The cortex and cerebellum form multi-synaptic reciprocal connections. We investigate the functional connectivity between single spiking cerebellar neurons and the population activity of the mouse dorsal cortex using mesoscale imaging. Cortical representations of individual cerebellar neurons vary significantly across different brain states but are drawn from a common set of cortical networks. These cortical-cerebellar connectivity features are observed in mossy fibers and Purkinje cells as well as neurons in different cerebellar lobules, albeit with variations across cell types and regions. Complex spikes of Purkinje cells preferably associate with the sensorimotor cortex, whereas simple spikes display more diverse cortical connectivity patterns. The spontaneous functional connectivity patterns align with cerebellar neurons' functional responses to external stimuli in a modality-specific manner. The tuning properties of subsets of cerebellar neurons differ between anesthesia and awake states, mirrored by state-dependent changes in their long-range functional connectivity patterns with mesoscale cortical activity.

Smartphone-based machine learning model for real-time assessment of medical kidney biopsy

BackgroundKidney biopsy is the gold-standard for diagnosing medical renal diseases, but the accuracy of the diagnosis greatly depends on the quality of the biopsy specimen, particularly the amount of renal cortex obtained. Inadequate biopsies, characterized by insufficient cortex or predominant medulla, can lead to inconclusive or incorrect diagnoses, and repeat biopsy. Unfortunately, there has been a concerning increase in the rate of inadequate kidney biopsies, and not all medical centers have access to trained professionals who can assess biopsy adequacy in real time. In response to this challenge, we aimed to develop a machine learning model capable of assessing the percentage cortex of each biopsy pass using smartphone images of the kidney biopsy tissue at the time of biopsy. Methods747 kidney biopsy cores and corresponding smartphone macro images were collected from five unused deceased donor kidneys. Each core was imaged, formalin-fixed, sectioned, and stained with Periodic acid–Schiff (PAS) to determine cortex percentage. The fresh unfixed core images were captured using the macro camera on an iPhone 13 Pro. Two experienced renal pathologists independently reviewed the PAS-stained sections to determine the cortex percentage. For the purpose of this study, the biopsies with less than 30% cortex were labeled as inadequate, while those with 30% or more cortex were classified as adequate. The dataset was divided into training (n=643), validation (n=30), and test (n=74) sets. Preprocessing steps involved converting High-Efficiency Image Container iPhone format images to JPEG, normalization, and renal tissue segmentation using a U-Net deep learning model. Subsequently, a classification deep learning model was trained on the renal tissue region of interest and corresponding class label. ResultsThe deep learning model achieved an accuracy of 85% on the training data. On the independent test dataset, the model exhibited an accuracy of 81%. For inadequate samples in the test dataset, the model showed a sensitivity of 71%, suggesting its capability to identify cases with inadequate cortical representation. The area under the receiver-operating curve (AUC-ROC) on the test dataset was 0.80. ConclusionWe successfully developed and tested a machine learning model for classifying smartphone images of kidney biopsies as either adequate or inadequate, based on the amount of cortex determined by expert renal pathologists. The model's promising results suggest its potential as a smartphone application to assist real-time assessment of kidney biopsy tissue, particularly in settings with limited access to trained personnel. Further refinements and validations are warranted to optimize the model's performance.

How Adversarial REM Dreams May Facilitate Creativity, and Why We Become Aware of Them

The importance of sleep for healthy brain function is widely acknowledged. However, it remains unclear how the internal generation of dreams might facilitate cognitive processes. In this perspective, we review a computational approach inspired by artificial intelligence that proposes a framework for how dreams occurring during rapid-eye-movement (REM) sleep can contribute to learning and creativity. In this framework, REM dreams are characterized by an adversarial process that, against the dream reality, tells a discriminator network to classify the internally created sensory activity as real. Such an adversarial dreaming process is shown to facilitate the emergence of real-world semantic representations in higher cortical areas. We further discuss the potential contributions of adversarial dreaming beyond learning, such as balancing fantastic and realistic dream elements and facilitating the occurrence of creative insights. We characterize non-REM (NREM) dreams, where a single hippocampal memory is replayed at a time, as serving the complementary role of improving the robustness of cortical representations to environmental perturbations. We finally explain how subjects can become aware of the adversarial REM dreams, but less of the NREM dreams, and how content- and state-awareness in wake, dream, and lucid dreaming may appear.

A hierarchy of processing complexity and timescales for natural sounds in human auditory cortex.

Efficient behavior is supported by humans' ability to rapidly recognize acoustically distinct sounds as members of a common category. Within auditory cortex, there are critical unanswered questions regarding the organization and dynamics of sound categorization. Here, we performed intracerebral recordings in the context of epilepsy surgery as 20 patient-participants listened to natural sounds. We built encoding models to predict neural responses using features of these sounds extracted from different layers within a sound-categorization deep neural network (DNN). This approach yielded highly accurate models of neural responses throughout auditory cortex. The complexity of a cortical site's representation (measured by the depth of the DNN layer that produced the best model) was closely related to its anatomical location, with shallow, middle, and deep layers of the DNN associated with core (primary auditory cortex), lateral belt, and parabelt regions, respectively. Smoothly varying gradients of representational complexity also existed within these regions, with complexity increasing along a posteromedial-to-anterolateral direction in core and lateral belt, and along posterior-to-anterior and dorsal-to-ventral dimensions in parabelt. When we estimated the time window over which each recording site integrates information, we found shorter integration windows in core relative to lateral belt and parabelt. Lastly, we found a relationship between the length of the integration window and the complexity of information processing within core (but not lateral belt or parabelt). These findings suggest hierarchies of timescales and processing complexity, and their interrelationship, represent a functional organizational principle of the auditory stream that underlies our perception of complex, abstract auditory information.

A bilingual speech neuroprosthesis driven by cortical articulatory representations shared between languages.

Advancements in decoding speech from brain activity have focused on decoding a single language. Hence, the extent to which bilingual speech production relies on unique or shared cortical activity across languages has remained unclear. Here, we leveraged electrocorticography, along with deep-learning and statistical natural-language models of English and Spanish, to record and decode activity from speech-motor cortex of a Spanish-English bilingual with vocal-tract and limb paralysis into sentences in either language. This was achieved without requiring the participant to manually specify the target language. Decoding models relied on shared vocal-tract articulatory representations across languages, which allowed us to build a syllable classifier that generalized across a shared set of English and Spanish syllables. Transfer learning expedited training of the bilingual decoder by enabling neural data recorded in one language to improve decoding in the other language. Overall, our findings suggest shared cortical articulatory representations that persist after paralysis and enable the decoding of multiple languages without the need to train separate language-specific decoders.

Differences in the organization of the primary motor cortex in people with and without low back pain and associations with motor control and sensory tests

Differences in organization of the primary motor cortex and altered trunk motor control (sensing, processing and motor output) have been reported in people with low back pain (LBP). Little is known to what extent these differences are related. We investigated differences in 1) organization of the primary motor cortex and 2) motor and sensory tests between people with and without LBP, and 3) investigated associations between the organization of the primary motor cortex and motor and sensory tests. We conducted a case-control study in people with (N=25) and without (N=25) LBP. The organization of the primary motor cortex (Center of Gravity (CoG) and Area of the cortical representation of trunk muscles) was assessed using neuronavigated transcranial magnetic stimulation, based on individual MRIs. Sensory tests (quantitative sensory testing, graphaesthesia, two-point discrimination threshold) and a motor test (spiral-tracking test) were assessed. Participants with LBP had a more lateral and lower location of the CoG and a higher temporal summation of pain. For all participants combined, better vibration test scores were associated with a more anterior, lateral, and lower CoG and a better two-point discrimination threshold was associated with a lower CoG. A small subset of variables showed significance. Although this aligns with the concept of altered organization of the primary motor cortex in LBP, there is no strong evidence of the association between altered organization of the primary motor cortex and motor and sensory test performance in LBP. Focusing on subgroup analyses regarding pain duration can be a topic for future research.

The speech neuroprosthesis.

Loss of speech after paralysis is devastating, but circumventing motor-pathway injury by directly decoding speech from intact cortical activity has the potential to restore naturalcommunication and self-expression. Recent discoveries have defined how key features of speech production are facilitated by the coordinated activity of vocal-tract articulatory and motor-planning cortical representations. In this Review, we highlight such progress and how it has led to successful speech decoding, first in individuals implanted with intracranial electrodes for clinicalepilepsy monitoringand subsequently in individuals with paralysis as part ofearlyfeasibility clinical trials to restore speech. We discuss high-spatiotemporal-resolution neural interfaces and the adaptation of state-of-the-art speech computational algorithms that have driven rapidandsubstantial progress indecoding neural activity into text, audible speech, and facial movements. Although restoring natural speech is a long-term goal, speech neuroprostheses already have performance levels that surpass communication rates offered by current assistive-communication technology. Given this accelerated rate of progress in the field, we propose key evaluation metrics for speed and accuracy, among others, to help standardize across studies. We finish by highlighting several directions to more fully explore the multidimensional feature space of speech and language, which will continue to accelerate progress towards a clinically viable speech neuroprosthesis.

Motor function in multiple sclerosis assessed by navigated transcranial magnetic stimulation mapping.

Impaired motor function is a major cause of disability in multiple sclerosis (MS), involving various neuroplasticity processes typically assessed by neuroimaging. This study aimed to determine whether navigated transcranial magnetic stimulation (nTMS) could also provide biomarkers of motor cortex plasticity in patients with MS (pwMS). nTMS motor mapping was performed for hand and leg muscles bilaterally. nTMS variables included the amplitude and latency of motor evoked potentials (MEPs), corticospinal excitability measures, and the size of cortical motor maps (CMMs). Clinical assessment included disability (Expanded Disability Status Scale, EDSS), strength (MRC scale, pinch and grip), and dexterity (9-hole Pegboard Test). nTMS motor mapping was performed in 68 pwMS. PwMS with high disability (EDSS ≥ 3) had enlarged CMMs with less dense distribution of MEPs and various MEP parameter changes compared to pwMS with low disability (EDSS < 3). Patients with progressive MS had also various MEP parameter changes compared to pwMS with relapsing remitting form. MRC score correlated positively with MEP amplitude and negatively with MEP latency, pinch strength correlated negatively with CMM volume and dexterity with MEP latency. This is the first study to perform 4-limb cortical motor mapping in pwMS using a dedicated nTMS procedure. By quantifying the cortical surface representation of a given muscle and the variability of MEP within this representation, nTMS can provide new biomarkers of motor function impairment in pwMS. Our study opens perspectives for the use of nTMS as an objective method for assessing pwMS disability in clinical practice.

Reading instruction causes changes in category-selective visual cortex

Education sculpts specialized neural circuits for skills like reading that are critical to success in modern society but were not anticipated by the selective pressures of evolution. Does the emergence of brain regions that selectively process novel visual stimuli like words occur at the expense of cortical representations of other stimuli like faces and objects? “Neuronal Recycling” predicts that learning to read should enhance the response to words in ventral occipitotemporal cortex (VOTC) and decrease the response to other visual categories such as faces and objects. To test this hypothesis, and more broadly to understand the changes that are induced by the early stages of literacy instruction, we conducted a randomized controlled trial with pre-school children (five years of age). Children were randomly assigned to intervention programs focused on either reading skills or oral language skills and magnetoencephalography (MEG) data collected before and after the intervention was used to measure visual responses to images of text, faces, and objects. We found that being taught reading versus oral language skills induced different patterns of change in category-selective regions of visual cortex, but that there was not a clear tradeoff between the response to words versus other categories. Within a predefined region of VOTC corresponding to the visual word form area (VWFA) we found that the relative amplitude of responses to text, faces, and objects changed, but increases in the response to words were not linked to decreases in the response to faces or objects. How these changes play out over a longer timescale is still unknown but, based on these data, we can surmise that high-level visual cortex undergoes rapid changes as children enter school and begin establishing new skills like literacy.

Метод викликаних потенціалів як перспективний напрямок дослідження ноцицепції у наркотизованих тварин

The sensation of pain is a pathogenetic link in a wide range of diseases, and the study of nociception as its component is an important area of physiology and medicine. However, modern requirements for research conducted using laboratory animals require the search for new approaches to studying nociception and analgesia with minimizing the suffering of subjects in ethological testing and maximizing the transition to instrumental testing. We proposed the use of a standard formalin model of pain in combination with the recording of changes in somatosensory cortex potentials caused by electrical stimulation of efferents at the level of the forelimb. It was found that after subcutaneous injection of 0.30 ml of 4% formalin, the amplitude of evoked potentials increased. Under the conditions of the proposed testing design, both dosedependent and time-dependent effects of the formalin model of pain were observed in an anesthetized animal. The peculiarity of the obtained results was that the fixed somatosensory potentials of the brain in the S1 forelimb region showed sensitivity to the administration of a nociceptive agent in those areas of the body that topographically did not belong to the cortical representation of the forelimbs. This probably indicates the potential universality of this test approach. Thus, it was shown that evoked potentials in the forelimb representation of the primary somatosensory cortex demonstrate a clearly fixed response to painful stimulation in the formalin model of pain and can be used in studies of nociceptive and analgesic effects as a partial alternative to standard ethological testing.

Метод викликаних потенціалів як перспективний напрямок дослідження ноцицепції у наркотизованих тварин

The sensation of pain is a pathogenetic link in a wide range of diseases, and the study of nociception as its component is an important area of physiology and medicine. However, modern requirements for research conducted using laboratory animals require the search for new approaches to studying nociception and analgesia with minimizing the suffering of subjects in ethological testing and maximizing the transition to instrumental testing. We proposed the use of a standard formalin model of pain in combination with the recording of changes in somatosensory cortex potentials caused by electrical stimulation of efferents at the level of the forelimb. It was found that after subcutaneous injection of 0.30 ml of 4% formalin, the amplitude of evoked potentials increased. Under the conditions of the proposed testing design, both dosedependent and time-dependent effects of the formalin model of pain were observed in an anesthetized animal. The peculiarity of the obtained results was that the fixed somatosensory potentials of the brain in the S1 forelimb region showed sensitivity to the administration of a nociceptive agent in those areas of the body that topographically did not belong to the cortical representation of the forelimbs. This probably indicates the potential universality of this test approach. Thus, it was shown that evoked potentials in the forelimb representation of the primary somatosensory cortex demonstrate a clearly fixed response to painful stimulation in the formalin model of pain and can be used in studies of nociceptive and analgesic effects as a partial alternative to standard ethological testing.

Impaired Cortical Tracking of Speech in Children with Developmental Language Disorder.

In developmental language disorder (DLD), learning to comprehend and express oneself with spoken language is impaired, but the reason for this remains unknown. Using millisecond-scale magnetoencephalography recordings combined with machine learning models, we investigated whether the possible neural basis of this disruption lies in poor cortical tracking of speech. The stimuli were common spoken Finnish words (e.g., dog, car, hammer) and sounds with corresponding meanings (e.g., dog bark, car engine, hammering). In both children with DLD (10 boys and 7 girls) and typically developing (TD) control children (14 boys and 3 girls), aged 10-15 years, the cortical activation to spoken words was best modeled as time-locked to the unfolding speech input at ∼100 ms latency between sound and cortical activation. Amplitude envelope (amplitude changes) and spectrogram (detailed time-varying spectral content) of the spoken words, but not other sounds, were very successfully decoded based on time-locked brain responses in bilateral temporal areas; based on the cortical responses, the models could tell at ∼75-85% accuracy which of the two sounds had been presented to the participant. However, the cortical representation of the amplitude envelope information was poorer in children with DLD compared with TD children at longer latencies (at ∼200-300 ms lag). We interpret this effect as reflecting poorer retention of acoustic-phonetic information in short-term memory. This impaired tracking could potentially affect the processing and learning of words as well as continuous speech. The present results offer an explanation for the problems in language comprehension and acquisition in DLD.

Effect of spectral degradation on speech intelligibility and cortical representation.

Noise-vocoded speech has long been used to investigate how acoustic cues affect speech understanding. Studies indicate that reducing the number of spectral channel bands diminishes speech intelligibility. Despite previous studies examining the channel band effect using earlier event-related potential (ERP) components, such as P1, N1, and P2, a clear consensus or understanding remains elusive. Given our hypothesis that spectral degradation affects higher-order processing of speech understanding beyond mere perception, we aimed to objectively measure differences in higher-order abilities to discriminate or interpret meaning. Using an oddball paradigm with speech stimuli, we examined how neural signals correlate with the evaluation of speech stimuli based on the number of channel bands measuring N2 and P3b components. In 20 young participants with normal hearing, we measured speech intelligibility and N2 and P3b responses using a one-syllable task paradigm with animal and non-animal stimuli across four vocoder conditions with 4, 8, 16, or 32 channel bands. Behavioral data from word repetition clearly affected the number of channel bands, and all pairs were significantly different (p < 0.001). We also observed significant effects of the number of channels on the peak amplitude [F(2.006, 38.117) = 9.077, p < 0.001] and peak latency [F(3, 57) = 26.642, p < 0.001] of the N2 component. Similarly, the P3b component showed significant main effects of the number of channel bands on the peak amplitude [F(2.231, 42.391) = 13.045, p < 0.001] and peak latency [F(3, 57) = 2.968, p = 0.039]. In summary, our findings provide compelling evidence that spectral channel bands profoundly influence cortical speech processing, as reflected in the N2 and P3b components, a higher-order cognitive process. We conclude that spectrally degraded one-syllable speech primarily affects cortical responses during semantic integration.

From learned value to sustained bias: how reward conditioning changes attentional priority.

Attentional bias to reward-associated stimuli can occur even when it interferes with goal-driven behavior. One theory posits that dopaminergic signaling in the striatum during reward conditioning leads to changes in visual cortical and parietal representations of the stimulus used, and this, in turn, sustains attentional bias even when reward is discontinued. However, only a few studies have examined neural activity during both rewarded and unrewarded task phases. In the current study, participants first completed a reward-conditioning phase, during which responses to certain stimuli were associated with monetary reward. These stimuli were then included as non-predictive cues in a spatial cueing task. Participants underwent functional brain imaging during both task phases. The results show that striatal activity during the learning phase predicted increased visual cortical and parietal activity and decreased ventro-medial prefrontal cortex activity in response to conditioned stimuli during the test. Striatal activity was also associated with anterior cingulate cortex activation when the reward-conditioned stimulus directed attention away from the target. Our findings suggest that striatal activity during reward conditioning predicts the degree to which reward history biases attention through learning-induced changes in visual and parietal activities.