Preconscious prediction of a driver's decision using intracranial recordings.

While driving, we make numerous conscious decisions such as route and turn direction selection. Although drivers are held responsible, the neural processes that govern such decisions are not clear. We recorded intracranial EEG signals from six patients engaged in a computer-based driving simulator. Patients decided which way to turn (left/right) and subsequently reported the time of the decision. We show that power modulations of gamma band oscillations (30-100 Hz) preceding the reported time of decision (up to 5.5 sec) allow prediction of decision content with high accuracy (up to 82.4%) on a trial-by-trial basis, irrespective of subsequent motor output. Moreover, these modulations exhibited a spatiotemporal gradient, differentiating left/right decisions earliest in premotor cortices and later in more anterior and lateral regions. Our results suggest a preconscious role for the premotor cortices in early stages of decision-making, which permits foreseeing and perhaps modifying the content of real-life human choices before they are consciously made.

Differentiating intended sensory outcome from underlying motor actions in the human brain.

To achieve a certain sensory outcome, multiple actions can be executed. For example, unlocking a door might require clockwise or counterclockwise key turns depending on regional norms. Using fMRI in healthy human subjects, we examined the neural networks that dissociate intended sensory outcome from underlying motor actions. Subjects controlled a figure on a computer screen by performing pen traces on an MR-compatible digital tablet. Our design allowed us to dissociate intended sensory outcome (moving the figure in a certain direction) from the underlying motor action (horizontal/vertical pen traces). Using multivoxel pattern analysis and a whole-brain searchlight strategy, we found that activity patterns in left (contralateral) motor and parietal cortex and also right (ipsilateral) motor cortex significantly discriminated direction of pen traces regardless of intended direction of figure movement. Conversely, activity patterns in right superior parietal lobule and premotor cortex, and also left frontopolar cortex, significantly discriminated intended direction of figure movement regardless of underlying direction of hand movement. Together, these results highlight the role of ipsilateral motor cortex in coding movement directions and point to a network of brain regions involved in high order representation of intended sensory outcome that is dissociated from specific motor plans.

Modeling the electrical field created by mass neural activity.

Gamma oscillations of large scale electrical activity are used in electrophysiological studies as markers for neural activity and functional processes in the cortex, yet the nature of this mass neural phenomenon and its relation to the evoked response potentials (ERP) are still not well understood. Many studies associated the gamma oscillations with oscillators around the 40 Hz frequency, yet recent studies have shown that gamma frequencies may be part of a broadband phenomenon ranging from 30 Hz up to 250 Hz. In this study we have examined the possibility that a simple model, based on available neurophysiological parameters, involving an increase in asynchronous (Poisson distributed) neural firing may be sufficient to generate the observed gamma power increases. Our simulation shows a roughly linear increase in gamma power as a function of the aggregated firing rate of the neural population, while the influence of the synchronization level within the neurons on the gamma power is limited. Our model supports the viewpoint that the broadband gamma response is mainly driven by the summed, asynchronous, activity of the neural population. We show that the time frequency spectrogram of the stimulus response can be reconstructed by combining two different phenomena-the broadband gamma power increase due to local processing and the more spatially distributed event related desynchronization (ERD). Our model thus raises the possibility that the broadband gamma response is closely linked to the aggregate population firing rate of the recorded neurons.

Antagonistic relationship between gamma power and visual evoked potentials revealed in human visual cortex.

Scalp electroencephalography and magnetoencephalography studies have revealed a rapid evoked potential "adaptation" where one visual stimulus suppresses the event-related potential (ERP) of the second stimulus. Here, we investigated a similar effect revealed in subdural intracranial recordings in humans. Our results show that the suppression of the subdural ERP is not associated with a reduction in the gamma frequency power, considered to reflect the underlying neural activity. Furthermore, the evoked potential suppression (EPS) phenomenon was not reflected in recognition behavior of the patients. Rather, the EPS was tightly linked to the level of gamma activity preceding the event, and this effect was independent of the interstimulus time interval. Analyzing other frequency bands failed to reveal a similar link. Our results thus show a consistent antagonism between subdural ERP and gamma power although both are considered markers for neural activity. We hypothesize that the ERP suppression is due to a desynchronization of neuronal firing resulting from recurrent neural activity in the vicinity of the freshly stimulated neurons and not an attenuation of the overall neural activity.

An automatic measure for classifying clusters of suspected spikes into single cells versus multiunits.

While automatic spike sorting has been investigated for decades, little attention has been allotted to consistent evaluation criteria that will automatically determine whether a cluster of spikes represents the activity of a single cell or a multiunit. Consequently, the main tool for evaluation has remained visual inspection by a human. This paper quantifies the visual inspection process. The results are well-defined criteria for evaluation, which are mainly based on visual features of the spike waveform, and an automatic adaptive algorithm that learns the classification by a given human and can apply similar visual characteristics for classification of new data. To evaluate the suggested criteria, we recorded the activity of 1652 units (single cells and multiunits) from the cerebrum of 12 human patients undergoing evaluation for epilepsy surgery requiring implantation of chronic intracranial depth electrodes. The proposed method performed similar to human classifiers and obtained significantly higher accuracy than two existing methods (three variants of each). Evaluation on two synthetic datasets is also provided. The criteria are suggested as a standard for evaluation of the quality of separation that will allow comparison between different studies. The proposed algorithm is suitable for real-time operation and as such may allow brain-computer interfaces to treat single cells differently than multiunits.

Encoding of speed and direction of movement in the human supplementary motor area.

OBJECT: The supplementary motor area (SMA) plays an important role in planning, initiation, and execution of motor acts. Patients with SMA lesions are impaired in various kinematic parameters, such as velocity and duration of movement. However, the relationships between neuronal activity and these parameters in the human brain have not been fully characterized. This is a study of single-neuron activity during a continuous volitional motor task, with the goal of clarifying these relationships for SMA neurons and other frontal lobe regions in humans. METHODS: The participants were 7 patients undergoing evaluation for epilepsy surgery requiring implantation of intracranial depth electrodes. Single-unit recordings were conducted while the patients played a computer game involving movement of a cursor in a simple maze. RESULTS: In the SMA proper, most of the recorded units exhibited a monotonic relationship between the unit firing rate and hand motion speed. The vast majority of SMA proper units with this property showed an inverse relation, that is, firing rate decrease with speed increase. In addition, most of the SMA proper units were selective to the direction of hand motion. These relationships were far less frequent in the pre-SMA, anterior cingulate gyrus, and orbitofrontal cortex. CONCLUSIONS: The findings suggest that the SMA proper takes part in the control of kinematic parameters of endeffector motion, and thus lend support to the idea of connecting neuroprosthetic devices to the human SMA.

Computer vision, camouflage breaking and countershading.

Camouflage is frequently used in the animal kingdom in order to conceal oneself from visual detection or surveillance. Many camouflage techniques are based on masking the familiar contours and texture of the subject by superposition of multiple edges on top of it. This work presents an operator, D arg, for the detection of three-dimensional smooth convex (or, equivalently, concave) objects. It can be used to detect curved objects on a relatively flat background, regardless of image edges, contours and texture. We show that a typical camouflage found in some animal species seems to be a 'countermeasure' taken against detection that might be based on our method. Detection by D arg is shown to be very robust, from both theoretical considerations and practical examples of real-life images.

Brain Activity Dissociates Mentalization from Motivation During an Interpersonal Competitive Game.

Studies demonstrating selective brain networks subserving motivation and mentalization (i.e. attributing states of mind to others) during social interactions have not investigated their mutual independence. We report the results of two fMRI studies using a competitive game requiring players to use implicit 'on-line' mentalization simultaneously with motivational processes of gains and losses in playing against a human or a computer opponent. We delineate a network, consisting of bilateral temporoparietal junction, temporal pole (TP), medial prefrontal cortex (MPFC) and right fusiform gyrus, which is sensitive to the opponent's response (challenging>not challenging the player) and opponent type (human>computer). This network is similar to a known explicit 'off-line' mentalization circuit, suggesting its additional involvement in implicit 'on-line' mentalization, a process more applicable to real-life social interactions. Importantly, only MPFC and TP were selective to mentalization compared to motivation, highlighting their specific operation in attributing states of mind to others during social interactions.

Enhanced category tuning revealed by intracranial electroencephalograms in high-order human visual areas.

The functional organization of human sensory cortex was studied by comparing intracranial EEG (iEEG) recordings of local field potentials in neurosurgical patients with functional magnetic resonance imaging (fMRI) obtained in healthy subjects. Using naturalistic movie stimuli, we found a tight correlation between these two measures throughout the human sensory cortex. Importantly, the correlation between the iEEG and fMRI signals was site-specific, exhibiting neuroanatomically specific coupling. In several cortical sites the iEEG activity was confined strictly to one object category. This site selectivity was not limited to faces but included other object categories such as houses and tools. The selectivity of the iEEG signals to images of different object categories was remarkably higher when compared with the selectivity of the corresponding fMRI signals. A plausible interpretation of the fMRI and iEEG results concerns cortical organization in which object categories are organized in a mosaic of narrowly tuned object-selective clusters.

Widespread functional connectivity and fMRI fluctuations in human visual cortex in the absence of visual stimulation.

To what extent does the visual system's activity fluctuate when no sensory stimulation is present? Here, we studied this issue by examining spontaneous fluctuations in BOLD signal in the human visual system, while subjects were placed in complete darkness. Our results reveal widespread slow fluctuations during such rest periods. In contrast to stimulus-driven activity, during darkness, functionally distinct object areas were fluctuating in unison. These fMRI fluctuations became rapidly spatially de-correlated (39% drop in correlation level, P < 0.008) during visual stimulation. Functional connectivity analysis revealed that the slow spontaneous fluctuations during rest had consistent and specific neuro-anatomical distribution which argued against purely hemodynamic noise sources. Control experiments ruled out eye closure, low luminance and mental imagery as the underlying sources of the spontaneous fluctuations. These results demonstrate that, when no stimulus is present, sensory systems manifest a robust level of slow organized fluctuation patterns.

Detection of pseudoperiodic patterns using partial acquisition of magnetic resonance images.

Improving the resolution of magnetic resonance imaging (MRI), or, alternatively, reducing the acquisition time, can be quite beneficial for many applications. The main motivation of this work is the assumption that any information that is a priori available on the target image could be used to achieve this goal. In order to demonstrate this approach, we present a novel partial acquisition strategy and reconstruction algorithm, suitable for the special case of detection of pseudoperiodic patterns. Pseudoperiodic patterns are frequently encountered in the cerebral cortex due to its columnar functional organization (best exemplified by orientation columns and ocular dominance columns of the visual cortex). We present a new MRI research methodology, in which we seek an activity pattern, and a pattern-specific experiment is devised to detect it. Such specialized experiments extend the limits of conventional MRI experiments by substantially reducing the scan time. Using the fact that pseudoperiodic patterns are localized in the Fourier domain, we present an optimality criterion for partial acquisition of the MR signal and a strategy for obtaining the optimal discrete Fourier transform (DFT) coefficients. A by-product of this strategy is an optimal linear extrapolation estimate. We also present a nonlinear spectral extrapolation algorithm, based on projections onto convex sets (POCSs), used to perform the actual reconstruction. The proposed strategy was tested and analyzed on simulated signals and in MRI phantom experiments.

Neural model for physiological responses to frequency and amplitude transitions uncovers topographical order in the auditory cortex.

We characterize primary auditory cortex (AI) units using a neural model for the detection of frequency and amplitude transitions. The model is a generalization of a model for the detection of amplitude transition. A set of neurons, tuned in the spectrotemporal domain, is created by means of neural delays and frequency filtering. The sensitivity of the model to frequency and amplitude transitions is achieved by applying a 2-dimensional rotatable receptive field to the set of spectrotemporally tuned neurons. We evaluated the model using data recorded in AI of anesthetized ferrets. We show that the model is able to fit the responses of AI units to variety of stimuli, including single tones, delayed 2-tone stimuli and various frequency-modulated tones, using only a small number of parameters. Furthermore, we show that the topographical order in maps of the model parameters is higher than in maps created from response indices extracted directly from the responses to any single stimulus. These results suggest a possible ordered organization of a simple rotatable spectrotemporal receptive field in the mammalian AI.

The role of the amygdala in signaling prospective outcome of choice.

Can brain activity reveal a covert choice? Making a choice often evokes distinct emotions that accompany decision processes. Amygdala has been implicated in choice behavior that is guided by a prospective negative outcome. However, its specific involvement in emotional versus cognitive processing of choice behavior has been a subject of controversy. In this study, the human amygdala was monitored by functional magnetic resonance imaging (fMRI) while subjects were playing in a naturalistic choice paradigm against the experimenter. In order to win, players had to occasionally choose to bluff their opponent, risk "getting caught," and suffer a loss. A critical period, when choice has been made but outcome was still unknown, activated the amygdala preferentially following the choice that entailed risk of loss. Thus, the response of the amygdala differentiated between subject's covert choice of either playing fair or foul. These results support a role of the amygdala in choice behavior, both in the appraisal of inherent value of choice and the signaling of prospective negative outcomes.