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During social interactions, we continuously integrate current and previous information over varying timescales to infer other people's action intentions. Motor cognition theories argue for a hierarchical organization of goal-directed actions based on temporal scales. Accordingly, transient motor primitives are represented at lower levels of the hierarchy, a combination of primitives building motor sequences at subordinate levels, and more stable overarching action goals at superordinate levels. A neural topography of hierarchal timescales for information accumulation was previously shown in the visual and auditory domains. However, whether such a temporal hierarchy can also account for observed goal-directed action representations in motor pathways remains to be determined. Thus, the current study examined the neural architecture underlying the processing of observed goal-directed actions using inter-subject correlation (ISC) of fMRI activity. Observers (n = 24) viewed sequential hand movements presented in their intact order or piecewise scrambled at three timescales pertaining to goal-directed action evolution (Primitives: ± 1.5 s, Sub-Goals: ± 4 s, and High-Goals: ± 10 s). The results revealed differential intrinsic temporal capacities for integrating goal-directed action information across brain areas engaged in action observation. Longer timescales (> ± 10 s) were found in the posterior parietal and dorsal premotor compared to the ventral premotor (± 4 s) and anterior parietal (± 1.5 s) cortex. Moreover, our results revealed a hemispheric bias with more extended timescales in the right MT+, primary somatosensory, and early visual cortices compared to their homotopic regions in the left hemisphere. Our findings corroborate a hierarchical neural mapping of observed actions based on temporal scales of goals and provide further support for a ubiquitous time-dependent neural organization of information processing across multiple modalities.

Functional neuroimaging analysis takes noisy multidimensional measurements as input and produces statistical inferences regarding the functional properties of brain regions as output. Such inferences are most commonly model-based, in that they assume a model of how neural activity translates to the measured signal (blood oxygenation level-dependent signal in the case of functional MRI). The use of models increases statistical sensitivity and makes it possible to ask fine-grained theoretical questions. However, this comes at the cost of making theoretical assumptions about the underlying data-generating process. An advantage of model-free approaches is that they can be used in cases where model assumptions are known not to hold. To this end, we introduce a randomization-based, model-free approach to functional neuroimaging. TWISTER randomization makes it possible to infer functional selectivity from correlations between experimental runs. We provide a proof of concept in the form of a visuomotor mapping experiment and discuss the possible strengths and limitations of this new approach in light of our empirical results.

Subjects underwent deep-brain stimulation through electrodes implanted to identify the foci of their epileptic seizures. The efficiency with which they navigated a virtual environment supports the conclusion that deep-brain stimulation improved memory in these persons. Loss of the ability to remember is one of the most dreaded afflictions of the human condition. Decades of research and clinical observations have established that declarative memory, the ability to remember recently experienced facts and events, depends on the hippocampus and associated structures in the medial temporal lobe, including the entorhinal, perirhinal, and parahippocampal cortexes. 1 Deep-brain stimulation has emerged as a technique to treat neurologic and neuropsychiatric disorders, including Parkinson's disease, dystonia, depression, and obsessive–compulsive disorder. 2 – 5 The nature of the stimulation-induced modification of the neural circuit that results in improvement in patients with these disorders is not completely . . .

Visual feedback in general, and from the body in particular, is known to influence the performance of motor skills in humans. However, it is unclear how the acquisition of motor skills depends on specific visual feedback parameters such as the size of performing effector. Here, 21 healthy subjects physically trained to perform sequences of finger movements with their right hand. Through the use of 3D Virtual Reality devices, visual feedback during training consisted of virtual hands presented on the screen, tracking subject's hand movements in real time. Importantly, the setup allowed us to manipulate the size of the displayed virtual hands across experimental conditions. We found that performance gains increase with the size of virtual hands. In contrast, when subjects trained by mere observation (i.e., in the absence of physical movement), manipulating the size of the virtual hand did not significantly affect subsequent performance gains. These results demonstrate that when it comes to short-term motor skill learning, the size of visual feedback matters. Furthermore, these results suggest that highest performance gains in individual subjects are achieved when the size of the virtual hand matches their real hand size. These results may have implications for optimizing motor training schemes.

Interlimb coupling refers to the interaction between movements of one limb and movements of other limbs. Understanding mechanisms underlying this effect is important to real life because it reflects the level of interdependence between the limbs that plays a role in daily activities including tool use, cooking, or playing musical instruments. Interlimb coupling involves multiple brain regions working together, including coordination of neural activity in sensory and motor regions across the two hemispheres. Traditional neuroscience research took a univariate approach to identify neural features that correspond to behavioural coupling measures. Yet, this approach reduces the complexity of the neural activity during interlimb tasks to one value. In this brief research report, we argue that identifying neural correlates of interlimb coupling would benefit from a multivariate approach in which full patterns from multiple sources are used to predict behavioural coupling. We demonstrate the feasibility of this approach in an exploratory EEG study where participants ( n = 10) completed 240 trials of a well-established drawing paradigm that involves interlimb coupling. Using artificial neural network (ANN), we show that multivariate representation of the EEG signal significantly captures the interlimb coupling during bimanual drawing whereas univariate analyses failed to identify such correlates. Our findings demonstrate that analysing distributed patterns of multiple EEG channels is more sensitive than single-value techniques in uncovering subtle differences between multiple neural signals. Using such techniques can improve identification of neural correlates of complex motor behaviours.

Performing actions with auditory consequences modulates the response in auditory cortex to otherwise identical stimuli passively heard. Such modulation has been suggested to occur through a corollary discharge sent from the motor cortex during voluntary actions. However, the relationship between the effector used to generate the sound, type of modulation and changes in perceptual sensitivity are unclear. Here we use functional magnetic resonance imaging on healthy subjects and demonstrate bilateral enhancement in the auditory cortex to self-generated versus externally generated sounds. Furthermore, we find that this enhancement is stronger when the sound-producing hand is contralateral to the auditory cortex. At the behavioural level, binaural hearing thresholds are lower for self-generated sounds and monaural thresholds are lower for sounds triggered by the hand ipsilateral to the stimulated ear. Together with functional connectivity analysis, our results suggest that a corollary discharge sent from active motor cortex enhances activity in the auditory cortex and increases perceptual sensitivity in a lateralized manner. Self-generated sounds and externally generated sounds are both processed in the auditory cortex, but it is unclear how. Daniel et al . find that compared to externally generated sounds, self-generated sounds produce enhanced responses in the auditory cortex that are due to motor cortex corollary discharges.

The emergence of memory, a trace of things past, into human consciousness is one of the greatest mysteries of the human mind. Whereas the neuronal basis of recognition memory can be probed experimentally in human and nonhuman primates, the study of free recall requires that the mind declare the occurrence of a recalled memory (an event intrinsic to the organism and invisible to an observer). Here, we report the activity of single neurons in the human hippocampus and surrounding areas when subjects first view cinematic episodes consisting of audiovisual sequences and again later when they freely recall these episodes. A subset of these neurons exhibited selective firing, which often persisted throughout and following specific episodes for as long as 12 seconds. Verbal reports of memories of these specific episodes at the time of free recall were preceded by selective reactivation of the same hippocampal and entorhinal cortex neurons. We suggest that this reactivation is an internally generated neuronal correlate for the subjective experience of spontaneous emergence of human recollection.

Performing actions with sensory consequences modifies physiological and behavioral responses relative to otherwise identical sensory input perceived in a passive manner. It is assumed that such modifications occur through an efference copy sent from motor cortex to sensory regions during performance of voluntary actions. In the auditory domain most behavioral studies report attenuated perceived loudness of self-generated auditory action-consequences. However, several recent behavioral and physiological studies report enhanced responses to such consequences. Here we manipulated the intensity of self-generated and externally-generated sounds and examined the type of perceptual modification (enhancement vs. attenuation) reported by healthy human subjects. We found that when the intensity of self-generated sounds was low, perceived loudness is enhanced. Conversely, when the intensity of self-generated sounds was high, perceived loudness is attenuated. These results might reconcile some of the apparent discrepancies in the reported literature and suggest that efference copies can adapt perception according to the differential sensory context of voluntary actions.

One of the central tasks of the human auditory system is to extract sound features from incoming acoustic signals that are most critical for speech perception. Specifically, phonological features and phonemes are the building blocks for more complex linguistic entities, such as syllables, words and sentences. Previous ECoG and EEG studies showed that various regions in the superior temporal gyrus (STG) exhibit selective responses to specific phonological features. However, electrical activity recorded by ECoG or EEG grids reflects average responses of large neuronal populations and is therefore limited in providing insights into activity patterns of single neurons. Here, we recorded spiking activity from 45 units in the STG from six neurosurgical patients who performed a listening task with phoneme stimuli. Fourteen units showed significant responsiveness to the stimuli. Using a Naïve-Bayes model, we find that single-cell responses to phonemes are governed by manner-of-articulation features and are organized according to sonority with two main clusters for sonorants and obstruents. We further find that ‘neural similarity’ (i.e. the similarity of evoked spiking activity between pairs of phonemes) is comparable to the ‘perceptual similarity’ (i.e. to what extent two phonemes are judged as sounding similar) based on perceptual confusion, assessed behaviorally in healthy subjects. Thus, phonemes that were perceptually similar also had similar neural responses. Taken together, our findings indicate that manner-of-articulation is the dominant organization dimension of phoneme representations at the single-cell level, suggesting a remarkable consistency across levels of analyses, from the single neuron level to that of large neuronal populations and behavior.

Spontaneous cortical waves have been widely observed, although previous evidence from humans has been indirect, using functional magnetic resonance imaging. This study reports that there are slow modulations in neuronal firing rates and gamma local field potentials in human auditory cortex in the absence of sensory stimuli or task. Animal studies have shown robust electrophysiological activity in the sensory cortex in the absence of stimuli or tasks. Similarly, recent human functional magnetic resonance imaging (fMRI) revealed widespread, spontaneously emerging cortical fluctuations. However, it is unknown what neuronal dynamics underlie this spontaneous activity in the human brain. Here we studied this issue by combining bilateral single-unit, local field potentials (LFPs) and intracranial electrocorticography (ECoG) recordings in individuals undergoing clinical monitoring. We found slow (<0.1 Hz, following 1/ f -like profiles) spontaneous fluctuations of neuronal activity with significant interhemispheric correlations. These fluctuations were evident mainly in neuronal firing rates and in gamma (40–100 Hz) LFP power modulations. Notably, the interhemispheric correlations were enhanced during rapid eye movement and stage 2 sleep. Multiple intracranial ECoG recordings revealed clear selectivity for functional networks in the spontaneous gamma LFP power modulations. Our results point to slow spontaneous modulations in firing rate and gamma LFP as the likely correlates of spontaneous fMRI fluctuations in the human sensory cortex.