Common Neural Code Research Articles

A common neural code for meaning in discourse production and comprehension

How does the brain code the meanings conveyed by language? Neuroimaging studies have investigated this by linking neural activity patterns during discourse comprehension to semantic models of language content. Here, we applied this approach to the production of discourse for the first time. Participants underwent fMRI while producing and listening to discourse on a range of topics. We used a distributional semantic model to quantify the similarity between different speech passages and identified where similarity in neural activity was predicted by semantic similarity. When people produced discourse, speech on similar topics elicited similar activation patterns in a widely distributed and bilateral brain network. This network was overlapping with, but more extensive than, the regions that showed similarity effects during comprehension. Critically, cross-task neural similarities between comprehension and production were also predicted by similarities in semantic content. This result suggests that discourse semantics engages a common neural code that is shared between comprehension and production. Effects of semantic similarity were bilateral in all three RSA analyses, even while univariate activation contrasts in the same data indicated left-lateralised BOLD responses. This indicates that right-hemisphere regions encode semantic properties even when they are not activated above baseline. We suggest that right-hemisphere regions play a supporting role in processing the meaning of discourse during both comprehension and production.

A common neural code for representing imagined and inferred tastes

A common neural code for representing imagined and inferred tastes

A common neural code for representing imagined and inferred tastes

Inferences about the taste of foods are a key aspect of our everyday experience of food choice. Despite this, gustatory mental imagery is a relatively under-studied aspect of our mental lives. In the present study, we examined subjects during high-field fMRI as they actively imagined basic tastes and subsequently viewed pictures of foods dominant in those specific taste qualities. Imagined tastes elicited activity in the bilateral dorsal mid-insula, one of the primary cortical regions responsive to the experience of taste. In addition, within this region we reliably decoded imagined tastes according to their dominant quality - sweet, sour, or salty – thus indicating that, like actual taste, imagined taste activates distinct quality-specific neural patterns. Using a cross-task decoding analysis, we found that the neural patterns for imagined tastes and food pictures in the mid-insula were reliably similar and quality-specific, suggesting a common code for representing taste quality regardless of whether explicitly imagined or automatically inferred when viewing food. These findings have important implications for our understanding of the mechanisms of mental imagery and the multimodal nature of presumably primary sensory brain regions like the dorsal mid-insula.

The effect of task demands on the neural patterns generated by novel instruction encoding

Verbal instructions allow fast and optimal implementation of novel behaviors. Previous research has shown that different control-related variables structure neural activity in frontoparietal regions during the encoding of novel instructed tasks. However, it is uncertain whether different task goals modulate the organizing effect of these variables. In this study, we investigated whether the neural encoding of three task-relevant variables (dimension integration, response set complexity and target category) is modulated by implementation and memorization demands. To do so, we combined functional Magnetic Resonance Imaging (fMRI), an instruction-following paradigm and multivariate analyses. We addressed how and where distributed activity patterns encoded the instructions' variables and the impact of the implementation and memorization demands on the fidelity of these representations. We further explored the nature of the neural code underpinning this process. Our results reveal, first, that the content of to-be-implemented and to-be-memorized instructions is represented in overlapping brain regions, flexibly using a common neural code across tasks. Importantly, they also suggest that preparing to implement the instructions increases the decodability of task-relevant information in frontoparietal areas, in comparison with memorization demands. Overall, our work emphasizes both similarities and differences in task coding under the two contextual demands. These findings qualify the previous understanding of novel instruction processing, suggesting that representing task attributes in a generalizable code, together with the increase in encoding fidelity induced by the implementation goals, could be key mechanisms for proactive control in novel scenarios.

The role of neural tuning in quantity perception.

Perception of quantities, such as numerosity, timing, and size, is essential for behavior and cognition. Accumulating evidence demonstrates neurons processing quantities are tuned, that is, have a preferred quantity amount, not only for numerosity, but also other quantity dimensions and sensory modalities. We argue that quantity-tuned neurons are fundamental to understanding quantity perception. We illustrate how the properties of quantity-tuned neurons can underlie a range of perceptual phenomena. Furthermore, quantity-tuned neurons are organized in distinct but overlapping topographic maps. We suggest that this overlap in tuning provides the neural basis for perceptual interactions between different quantities, without the need for a common neural representational code.

Distinct and common neural coding of semantic and non-semantic control demands

The flexible retrieval of knowledge is critical in everyday situations involving problem solving, reasoning and social interaction. Current theories emphasise the importance of a left-lateralised semantic control network (SCN) in supporting flexible semantic behaviour, while a bilateral multiple-demand network (MDN) is implicated in executive functions across domains. No study, however, has examined whether semantic and non-semantic demands are reflected in a common neural code within regions specifically implicated in semantic control. Using functional MRI and univariate parametric modulation analysis as well as multivariate pattern analysis, we found that semantic and non-semantic demands gave rise to both similar and distinct neural responses across control-related networks. Though activity patterns in SCN and MDN could decode the difficulty of both semantic and verbal working memory decisions, there was no shared common neural coding of cognitive demands in SCN regions. In contrast, regions in MDN showed common patterns across manipulations of semantic and working memory control demands, with successful cross-classification of difficulty across tasks. Therefore, SCN and MDN can be dissociated according to the information they maintain about cognitive demands.

Common neural code for reward and information value

Adaptive information seeking is critical for goal-directed behavior. Growing evidence suggests the importance of intrinsic motives such as curiosity or need for novelty, mediated through dopaminergic valuation systems, in driving information-seeking behavior. However, valuing information for its own sake can be highly suboptimal when agents need to evaluate instrumental benefit of information in a forward-looking manner. Here we show that information-seeking behavior in humans is driven by subjective value that is shaped by both instrumental and noninstrumental motives, and that this subjective value of information (SVOI) shares a common neural code with more basic reward value. Specifically, using a task where subjects could purchase information to reduce uncertainty about outcomes of a monetary lottery, we found information purchase decisions could be captured by a computational model of SVOI incorporating utility of anticipation, a form of noninstrumental motive for information seeking, in addition to instrumental benefits. Neurally, trial-by-trial variation in SVOI was correlated with activity in striatum and ventromedial prefrontal cortex. Furthermore, cross-categorical decoding revealed that, within these regions, SVOI and expected utility of lotteries were represented using a common code. These findings provide support for the common currency hypothesis and shed insight on neurocognitive mechanisms underlying information-seeking behavior.

The language of music: Common neural codes for structured sequences in music and natural language

The ability to process structured sequences is a central feature of natural language but also characterizes many other domains of human cognition. In this fMRI study, we measured brain metabolic response in musicians as they generated structured and non-structured sequences in language and music. We employed a univariate and multivariate cross-classification approach to provide evidence that a common neural code underlies the production of structured sequences across the two domains. Crucially, the common substrate includes Broca’s area, a region well known for processing structured sequences in language. These findings have several implications. First, they directly support the hypothesis that language and music share syntactic integration mechanisms. Second, they show that Broca’s area is capable of operating supramodally across these two domains. Finally, these results dismiss the recent hypothesis that domain general processes of neighboring neural substrates explain the previously observed “overlap” between neuroimaging activations across the two domains.

Processing number and length in the parietal cortex: Sharing resources, not a common code

A current intense discussion in numerical cognition concerns the relationship between the processing of numerosity and other non-numerical quantities. In particular, it is a matter of debate whether number and other quantities (e.g., size, length) are represented separately in the brain or whether they share a common generalized magnitude representation. We acquired high-resolution functional MRI data while adult subjects engaged in a magnitude comparison task involving either numerosity (i.e., which of the two sets has more elements?) or line length (i.e., which of the two lines is longer?). We compared the activation evoked by the two different types of quantity and observed a common recruitment of a vast portion of occipital and parietal cortices. Using MVPA, we demonstrated that some of the commonly activated regions represented the discrete and continuous quantities via a similar distance-dependent magnitude code. However, we found no effect of distance across the two quantity representations, failing to support the existence of a common, dimension invariant, generalized quantity code. Taken together, these findings indicate that although the processing of number and length is supported by partially overlapping neural resources, representations within these regions do not appear to be based on a common neural code.

Theories of Person Perception Predict Patterns of Neural Activity During Mentalizing.

Social life requires making inferences about other people. What information do perceivers spontaneously draw upon to make such inferences? Here, we test 4 major theories of person perception, and 1 synthetic theory that combines their features, to determine whether the dimensions of such theories can serve as bases for describing patterns of neural activity during mentalizing. While undergoing functional magnetic resonance imaging, participants made social judgments about well-known public figures. Patterns of brain activity were then predicted using feature encoding models that represented target people's positions on theoretical dimensions such as warmth and competence. All 5 theories of person perception proved highly accurate at reconstructing activity patterns, indicating that each could describe the informational basis of mentalizing. Cross-validation indicated that the theories robustly generalized across both targets and participants. The synthetic theory consistently attained the best performance-approximately two-thirds of noise ceiling accuracy--indicating that, in combination, the theories considered here can account for much of the neural representation of other people. Moreover, encoding models trained on the present data could reconstruct patterns of activity associated with mental state representations in independent data, suggesting the use of a common neural code to represent others' traits and states.

A common neural code for social and monetary rewards in the human striatum.

Although managing social information and decision making on the basis of reward is critical for survival, it remains uncertain whether differing reward type is processed in a uniform manner. Previously, we demonstrated that monetary reward and the social reward of good reputation activated the same striatal regions including the caudate nucleus and putamen. However, it remains unclear whether overlapping activations reflect activities of identical neuronal populations or two overlapping but functionally independent neuronal populations. Here, we re-analyzed the original data and addressed this question using multivariate-pattern-analysis and found evidence that in the left caudate nucleus and bilateral nucleus accumbens, social vs monetary reward were represented similarly. The findings suggest that social and monetary rewards are processed by the same population of neurons within these regions of the striatum. Additional findings demonstrated similar neural patterns when participants experience high social reward compared to viewing others receiving low social reward (potentially inducing schadenfreude). This is possibly an early indication that the same population of neurons may be responsible for processing two different types of social reward (good reputation and schadenfreude). These findings provide a supplementary perspective to previous research, helping to further elucidate the mechanisms behind social vs non-social reward processing.

Decoding “us” and “them”: Neural representations of generalized group concepts.

Humans form social coalitions in every society on earth, yet we know very little about how the general concepts us and them are represented in the brain. Evolutionary psychologists have argued that the human capacity for group affiliation is a byproduct of adaptations that evolved for tracking coalitions in general. These theories suggest that humans possess a common neural code for the concepts in-group and out-group, regardless of the category by which group boundaries are instantiated. The authors used multivoxel pattern analysis to identify the neural substrates of generalized group concept representations. They trained a classifier to encode how people represented the most basic instantiation of a specific social group (i.e., arbitrary teams created in the lab with no history of interaction or associated stereotypes) and tested how well the neural data decoded membership along an objectively orthogonal, real-world category (i.e., political parties). The dorsal anterior cingulate cortex/middle cingulate cortex and anterior insula were associated with representing groups across multiple social categories. Restricting the analyses to these regions in a separate sample of participants performing an explicit categorization task, the authors replicated cross-categorization classification in anterior insula. Classification accuracy across categories was driven predominantly by the correct categorization of in-group targets, consistent with theories indicating in-group preference is more central than out-group derogation to group perception and cognition. These findings highlight the extent to which social group concepts rely on domain-general circuitry associated with encoding stimuli's functional significance. (PsycINFO Database Record

Assessing human mirror activity with EEG mu rhythm: A meta-analysis.

A fundamental issue in cognitive neuroscience is how the brain encodes others' actions and intentions. In recent years, a potential advance in our knowledge on this issue is the discovery of mirror neurons in the motor cortex of the nonhuman primate. These neurons fire to both execution and observation of specific types of actions. Researchers use this evidence to fuel investigations of a human mirror system, suggesting a common neural code for perceptual and motor processes. Among the methods used for inferring mirror system activity in humans are changes in a particular frequency band in the electroencephalogram (EEG) called the mu rhythm. Mu frequency appears to decrease in amplitude (reflecting cortical activity) during both action execution and action observation. The current meta-analysis reviewed 85 studies (1,707 participants) of mu that infer human mirror system activity. Results demonstrated significant effect sizes for mu during execution (Cohen's d = 0.46, N = 701) as well as observation of action (Cohen's d = 0.31, N = 1,508), confirming a mirroring property in the EEG. A number of moderators were examined to determine the specificity of these effects. We frame these meta-analytic findings within the current discussion about the development and functions of a human mirror system, and conclude that changes in EEG mu activity provide a valid means for the study of human neural mirroring. Suggestions for improving the experimental and methodological approaches in using mu to study the human mirror system are offered.

Detecting and interpreting conscious experiences in behaviorally non-responsive patients

Decoding the contents of consciousness from brain activity is one of the most challenging frontiers of cognitive neuroscience. The ability to interpret mental content without recourse to behavior is most relevant for understanding patients who may be demonstrably conscious, but entirely unable to speak or move willfully in any way, precluding any systematic investigation of their conscious experience. The lack of consistent behavioral responsivity engenders unique challenges to decoding any conscious experiences these patients may have solely based on their brain activity. For this reason, paradigms that have been successful in healthy individuals cannot serve to interpret conscious mental states in this patient group. Until recently, patient studies have used structured instructions to elicit willful modulation of brain activity according to command, in order to decode the presence of willful brain-based responses in this patient group. In recent work, we have used naturalistic paradigms, such as watching a movie or listening to an audio-story, to demonstrate that a common neural code supports conscious experiences in different individuals. Moreover, we have demonstrated that this code can be used to interpret the conscious experiences of a patient who had remained non-responsive for several years. This approach is easy to administer, brief, and does not require compliance with task instructions. Rather, it engages attention naturally through meaningful stimuli that are similar to the real-world sensory information in a patient's environment. Therefore, it may be particularly suited to probing consciousness and revealing residual brain function in highly impaired, acute, patients in a comatose state, thus helping to improve diagnostication and prognostication for this vulnerable patient group from the critical early stages of severe brain-injury.

A common neural code for perceived and inferred emotion.

Although the emotions of other people can often be perceived from overt reactions (e.g., facial or vocal expressions), they can also be inferred from situational information in the absence of observable expressions. How does the human brain make use of these diverse forms of evidence to generate a common representation of a target's emotional state? In the present research, we identify neural patterns that correspond to emotions inferred from contextual information and find that these patterns generalize across different cues from which an emotion can be attributed. Specifically, we use functional neuroimaging to measure neural responses to dynamic facial expressions with positive and negative valence and to short animations in which the valence of a character's emotion could be identified only from the situation. Using multivoxel pattern analysis, we test for regions that contain information about the target's emotional state, identifying representations specific to a single stimulus type and representations that generalize across stimulus types. In regions of medial prefrontal cortex (MPFC), a classifier trained to discriminate emotional valence for one stimulus (e.g., animated situations) could successfully discriminate valence for the remaining stimulus (e.g., facial expressions), indicating a representation of valence that abstracts away from perceptual features and generalizes across different forms of evidence. Moreover, in a subregion of MPFC, this neural representation generalized to trials involving subjectively experienced emotional events, suggesting partial overlap in neural responses to attributed and experienced emotions. These data provide a step toward understanding how the brain transforms stimulus-bound inputs into abstract representations of emotion.

Classifying the wandering mind: Revealing the affective content of thoughts during task-free rest periods

Many powerful human emotional thoughts are generated in the absence of a precipitating event in the environment. Here, we tested whether we can decode the valence of internally driven, self-generated thoughts during task-free rest based on neural similarities with task-related affective mental states. We acquired functional magnetic resonance imaging (fMRI) data while participants generated positive and negative thoughts as part of an attribution task (Session A) and while they reported the occurrence of comparable mental states during task-free rest periods (Session B). With the use of multivariate pattern analyses (MVPA), we identified response patterns in the medial orbitofrontal cortex (mOFC) that encode the affective content of thoughts that are generated in response to an external experimental cue. Importantly, these task driven response patterns reliably predicted the occurrence of affective thoughts generated during unconstrained rest periods recorded one week apart. This demonstrates that at least certain elements of task-cued and task-free affective experiences rely on a common neural code. Furthermore, our findings reveal the role that the mOFC plays in determining the affective tone of unconstrained thoughts. More generally, our results suggest that MVPA is an important methodological tool for attempts to understand unguided subject driven mental states such as mind-wandering and daydreaming based on neural similarities with task-based experiences.

Information coding in a laminar computational model of cat primary visual cortex

Neural populations across cortical layers perform different computational tasks. However, it is not known whether information in different layers is encoded using a common neural code or whether it depends on the specific layer. Here we studied the laminar distribution of information in a large-scale computational model of cat primary visual cortex. We analyzed the amount of information about the input stimulus conveyed by the different representations of the cortical responses. In particular, we compared the information encoded in four possible neural codes: (1) the information carried by the firing rate of individual neurons; (2) the information carried by spike patterns within a time window; (3) the rate-and-phase information carried by the firing rate labelled by the phase of the Local Field Potentials (LFP); (4) the pattern-and-phase information carried by the spike patterns tagged with the LFP phase. We found that there is substantially more information in the rate-and-phase code compared with the firing rate alone for low LFP frequency bands (less than 30Hz). When comparing how information is encoded across layers, we found that the extra information contained in a rate-and-phase code may reach 90% in Layer 4, while in other layers it reaches only 60%, compared to the information carried by the firing rate alone. These results suggest that information processing in primary sensory cortices could rely on different coding strategies across different layers.

FMRI Adaptation Reveals Mirror Neurons in Human Inferior Parietal Cortex

Mirror neurons, as originally described in the macaque, have two defining properties [1, 2]: They respond specifically to a particular action (e.g., bringing an object to the mouth), and they produce their action-specific responses independent of whether the monkey executes the action or passively observes a conspecific performing the same action. In humans, action observation and action execution engage a network of frontal, parietal, and temporal areas. However, it is unclear whether these responses reflect the activity of a single population that represents both observed and executed actions in a common neural code or the activity of distinct but overlapping populations of exclusively perceptual and motor neurons [3]. Here, we used fMRI adaptation to show that the right inferior parietal lobe (IPL) responds independently to specific actions regardless of whether they are observed or executed. Specifically, responses in the right IPL were attenuated when participants observed a recently executed action relative to one that had not previously been performed. This adaptation across action and perception demonstrates that the right IPL responds selectively to the motoric and perceptual representations of actions and is the first evidence for a neural response in humans that shows both defining properties of mirror neurons.

A common neural code for frequency- and amplitude-modulated sounds.

Most naturally occurring sounds are modulated in amplitude or frequency; important examples include animal vocalizations and species-specific communication signals in mammals, insects, reptiles, birds and amphibians. Deciphering the information from amplitude-modulated (AM) sounds is a well-understood process, requiring a phase locking of primary auditory afferents to the modulation envelopes. The mechanism for decoding frequency modulation (FM) is not as clear because the FM envelope is flat (Fig. 1). One biological solution is to monitor amplitude fluctuations in frequency-tuned cochlear filters as the instantaneous frequency of the FM sweeps through the passband of these filters. This view postulates an FM-to-AM transduction whereby a change in frequency is transmitted as a change in amplitude. This is an appealing idea because, if such transduction occurs early in the auditory pathway, it provides a neurally economical solution to how the auditory system encodes these important sounds. Here we illustrate that an FM and AM sound must be transformed into a common neural code in the brain stem. Observers can accurately determine if the phase of an FM presented to one ear is leading or lagging, by only a fraction of a millisecond, the phase of an AM presented to the other ear. A single intracranial image is perceived, the spatial position of which is a function of this phase difference.

Broad directional tuning in spinal projections to the cerebellum.

1. Spinocerebellar neurons that project in the dorsal spinocerebellar tract (DSCT) receive mono- and polysynaptic inputs from specific sensory receptors in the hindlimb, and they project mossy fiber terminals to the cerebellar vermis. We examined the functional organization of these neurons and found that it relates to whole-limb parameters like limb posture and direction of limb movement. 2. We recorded the activity of 444 DSCT units during passive perturbations of the hind foot in anesthetized cats. The movements were either confined a single joint (the ankle; 234 cells) or involved the entire hindlimb (210 cells). The cells exhibited opposite responses for opposite directions of whole-limb movement, but a variety of response patterns for opposite directions of movement at one joint. We interpret the result to imply that the population encodes information about the whole limb rather than single joints. 3. Most of the 78 neurons recorded during passive limb placements (63%) responded to changes in limb length and also changes in limb orientation. In fact, the activity of most of the cells was broadly tuned with respect to the direction of passive limb movements generated by moving the hind foot in the sagittal plane. Changes in unit activity could be described by a cosine tuning function with respect to foot positions (72% of responses) and directions of foot movement (50%). 4. The similarity of this behavior to that of neurons in the motor cortex and cerebellar nuclei recorded during voluntary movements is consistent with a common neural code to represent the sensorimotor parameters of limb movement.