Explicit Encoding of Multimodal Percepts by Single Neurons in the Human Brain

Different pictures of Marilyn Monroe can evoke the same percept, even if greatly modified as in Andy Warhol’s famous portraits. But how does the brain recognize highly variable pictures as the same percept? Various studies have provided insights into how visual information is processed along the ‘‘ventral pathway,’’ via both single-cell recordings in monkeys and functional imaging in humans. Interestingly, in humans, the same "concept" of Marilyn Monroe can be evoked with other stimulus modalities, for instance by hearing or reading her name. Brain imaging studies have identified cortical areas selective to voices and visual word forms. However, how visual, text, and sound information can elicit a unique percept is still largely unknown. By using presentations of pictures and of spoken and written names, we show that (1) single neurons in the human medial temporal lobe (MTL) respond selectively to representations of the same individual across different sensory modalities; (2) the degree of multimodal invariance increases along the hierarchical structure within the MTL; and (3) such neuronal representations can be generated within less than a day or two. These results demonstrate that single neurons can encode percepts in an explicit, selective, and invariant manner, even if evoked by different sensory modalities

Sparse Representation in the Human Medial Temporal Lobe

Recent experiments characterized individual neurons in the human medial temporal lobe with remarkably selective, invariant, and explicit responses to images of famous individuals or landmark buildings. Here, we used a probabilistic analysis to show that these data are consistent with a sparse code in which neurons respond in a selective manner to a small fraction of stimuli

A Single-Neuron Correlate of Change Detection and Change Blindness in the Human Medial Temporal Lobe

Observers are often unaware of changes in their visual environment when attention is not focused at the location of the change [1,2,3,4]. Because of its rather intriguing nature, this phenomenon, known as change blindness, has been extensively studied with psychophysics [5,6,7] as well as with fMRI [8,9,10,11]. However, whether change blindness can be tracked in the activity of single cells is not clear. To explore the neural correlates of change detection and change blindness, we recorded from single neurons in the human medial temporal lobe (MTL) during a change-detection paradigm. The preferred pictures of the visually responsive units elicited significantly higher firing rates on the attended trials when subjects correctly identified a change (change detection) compared to the unattended trials when they missed it (change blindness). On correct trials, the firing activity of individual units allowed us to predict the occurrence of a change, on a trial-by-trial basis, with 67% accuracy. In contrast, this prediction was at chance for incorrect, unattended trials. The firing rates of visually selective MTL cells thus constitute a neural correlate of change detection

Persistent Single-Neuron Activity during Working Memory in the Human Medial Temporal Lobe

Working memory is an essential component of human cognition. Persistent activity related to working memory has been reported in many brain areas, including the inferior temporal and prefrontal cortex [1; 2; 3; 4; 5; 6; 7 ; 8]. The medial temporal lobe (MTL) contains “concept cells” that respond invariantly to specific individuals or places whether presented as images, text, or speech [9 ; 10]. It is unknown, however, whether the MTL also participates in working memory processes. We thus sought to determine whether human MTL neurons respond to images held in working memory. We recorded from patients with chronically intractable epilepsy as they performed a task that required them to remember three or four sequentially presented pictures across a brief delay. 48% of visually selective neurons continued to carry image-specific information after image offset, but most ceased to encode previously presented images after a subsequent presentation of a different image. However, 8% of visually selective neurons encoded previously presented images during a final maintenance period, despite presentation of further images in the intervening interval. Population activity of stimulus-selective neurons predicted behavioral outcome in terms of correct and incorrect responses. These findings indicate that the MTL is part of a brain-wide network for working memory

Improving data quality in neuronal population recordings

Understanding how the brain operates requires understanding how large sets of neurons function together. Modern recording technology makes it possible to simultaneously record the activity of hundreds of neurons, and technological developments will soon allow recording of thousands or tens of thousands. As with all experimental techniques, these methods are subject to confounds that complicate the interpretation of such recordings, and could lead to erroneous scientific conclusions. Here, we discuss methods for assessing and improving the quality of data from these techniques, and outline likely future directions in this field

Reply to "Comment on 'Performance of different synchronization measures in real data: A case study on electroencephalographic signals'"

We agree with the Comment by Duckrow and Albano [Phys. Rev. E 67, 063901 (2003)] that mutual information, estimated with an optimized algorithm, can be a useful tool for studying synchronization in real data. However, we point out that the improvement they found is mainly due to an interesting but nonstandard embedding technique used, and not so much due to the algorithm used for the estimation of mutual information itself. We also address the issue of stationarity of electroencephalographic (EEG) data

Movement Intention Is Better Predicted than Attention in the Posterior Parietal Cortex

We decoded on a trial-by-trial basis the location of visual targets, as a marker of the locus of attention, and intentions to reach and to saccade in different directions using the activity of neurons in the posterior parietal cortex of two monkeys. Predictions of target locations were significantly worse than predictions of movement plans for the same target locations. Moreover, neural signals in the parietal reach region (PRR) gave better predictions of reaches than saccades, whereas signals in the lateral intraparietal area (LIP) gave better predictions of saccades than reaches. Taking together the activity of both areas, the prediction of either movement in all directions became nearly perfect. These results cannot be explained in terms of an attention effect and support the idea of two segregated populations in the posterior parietal cortex, PRR and LIP, that are involved in different movement plans

Looking for a face in the crowd: Fixation-related potentials in an eye-movement visual search task

Despite the compelling contribution of the study of event related potentials (ERPs) and eye movements to cognitive neuroscience, these two approaches have largely evolved independently. We designed an eye-movement visual search paradigm that allowed us to concurrently record EEG and eye movements while subjects were asked to find a hidden target face in a crowded scene with distractor faces. Fixation event-related potentials (fERPs) to target and distractor stimuli showed the emergence of robust sensory components associated with the perception of stimuli and cognitive components associated with the detection of target faces. We compared those components with the ones obtained in a control task at fixation: qualitative similarities as well as differences in terms of scalp topography and latency emerged between the two. By using single trial analyses, fixations to target and distractors could be decoded from the EEG signals above chance level in 11 out of 12 subjects. Our results show that EEG signatures related to cognitive behavior develop across spatially unconstrained exploration of natural scenes and provide a first step towards understanding the mechanisms of target detection during natural search.Fil: Kaunitz, Lisandro N.. University of Leicester; Reino UnidoFil: Kamienkowski, Juan Esteban. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Laboratorio de Neurociencia Integrativa; Argentina. Universidad Diego Portales; Chile;Fil: Varatharajah, Alexander. University of Leicester; Reino UnidoFil: Sigman, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto de Física del Sur; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Laboratorio de Neurociencia Integrativa; ArgentinaFil: Quian Quiroga, Rodrigo. University of Leicester; Reino UnidoFil: Ison, Matias Julian. University of Leicester; Reino Unid

Local Field Potentials and Spikes in the Human Medial Temporal Lobe are Selective to Image Category

Local field potentials (LFPs) reflect the averaged dendrosomatic activity of synaptic signals of large neuronal populations. In this study, we investigate the selectivity of LFPs and single neuron activity to semantic categories of visual stimuli in the medial temporal lobe of nine neurosurgical patients implanted with intracranial depth electrodes for clinical reasons. Strong selectivity to the category of presented images was found for the amplitude of LFPs in 8% of implanted microelectrodes and for the firing rates of single and multiunits in 14% of microelectrodes. There was little overlap between the LFP- and spike-selective microelectrodes. Separate analysis of the power and phase of LFPs revealed that the mean phase was category-selective around the θ frequency range and that the power of the LFPs was category-selective for high frequencies around the γ rhythm. Of the 36 microelectrodes with amplitude-selective LFPs, 30 were found in the hippocampus. Finally, it was possible to readout information about the category of stimuli presented to the patients with both spikes and LFPs. Combining spiking and LFP activity enhanced the decoding accuracy in comparison with the accuracy obtained with each signal alone, especially for short time intervals

Invariant visual representation by single neurons in the human brain

It takes a fraction of a second to recognize a person or an object even when seen under strikingly different conditions. How such a robust, high-level representation is achieved by neurons in the human brain is still unclear. In monkeys, neurons in the upper stages of the ventral visual pathway respond to complex images such as faces and objects and show some degree of invariance to metric properties such as the stimulus size, position and viewing angle. We have previously shown that neurons in the human medial temporal lobe (MTL) fire selectively to images of faces, animals, objects or scenes. Here we report on a remarkable subset of MTL neurons that are selectively activated by strikingly different pictures of given individuals, landmarks or objects and in some cases even by letter strings with their names. These results suggest an invariant, sparse and explicit code, which might be important in the transformation of complex visual percepts into long-term and more abstract memories