169 research outputs found

    fMRI evidence of ‘mirror’ responses to geometric shapes

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    Mirror neurons may be a genetic adaptation for social interaction [1]. Alternatively, the associative hypothesis [2], [3] proposes that the development of mirror neurons is driven by sensorimotor learning, and that, given suitable experience, mirror neurons will respond to any stimulus. This hypothesis was tested using fMRI adaptation to index populations of cells with mirror properties. After sensorimotor training, where geometric shapes were paired with hand actions, BOLD response was measured while human participants experienced runs of events in which shape observation alternated with action execution or observation. Adaptation from shapes to action execution, and critically, observation, occurred in ventral premotor cortex (PMv) and inferior parietal lobule (IPL). Adaptation from shapes to execution indicates that neuronal populations responding to the shapes had motor properties, while adaptation to observation demonstrates that these populations had mirror properties. These results indicate that sensorimotor training induced populations of cells with mirror properties in PMv and IPL to respond to the observation of arbitrary shapes. They suggest that the mirror system has not been shaped by evolution to respond in a mirror fashion to biological actions; instead, its development is mediated by stimulus-general processes of learning within a system adapted for visuomotor control

    Single Neurons in M1 and Premotor Cortex Directly Reflect Behavioral Interference

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    Some motor tasks, if learned together, interfere with each other's consolidation and subsequent retention, whereas other tasks do not. Interfering tasks are said to employ the same internal model whereas noninterfering tasks use different models. The division of function among internal models, as well as their possible neural substrates, are not well understood. To investigate these questions, we compared responses of single cells in the primary motor cortex and premotor cortex of primates to interfering and noninterfering tasks. The interfering tasks were visuomotor rotation followed by opposing visuomotor rotation. The noninterfering tasks were visuomotor rotation followed by an arbitrary association task. Learning two noninterfering tasks led to the simultaneous formation of neural activity typical of both tasks, at the level of single neurons. In contrast, and in accordance with behavioral results, after learning two interfering tasks, only the second task was successfully reflected in motor cortical single cell activity. These results support the hypothesis that the representational capacity of motor cortical cells is the basis of behavioral interference and division between internal models

    A Membrane-Bound Vertebrate Globin

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    The family of vertebrate globins includes hemoglobin, myoglobin, and other O2-binding proteins of yet unclear functions. Among these, globin X is restricted to fish and amphibians. Zebrafish (Danio rerio) globin X is expressed at low levels in neurons of the central nervous system and appears to be associated with the sensory system. The protein harbors a unique N-terminal extension with putative N-myristoylation and S-palmitoylation sites, suggesting membrane-association. Intracellular localization and transport of globin X was studied in 3T3 cells employing green fluorescence protein fusion constructs. Both myristoylation and palmitoylation sites are required for correct targeting and membrane localization of globin X. To the best of our knowledge, this is the first time that a vertebrate globin has been identified as component of the cell membrane. Globin X has a hexacoordinate binding scheme and displays cooperative O2 binding with a variable affinity (P50∼1.3–12.5 torr), depending on buffer conditions. A respiratory function of globin X is unlikely, but analogous to some prokaryotic membrane-globins it may either protect the lipids in cell membrane from oxidation or may act as a redox-sensing or signaling protein

    A Fluctuation-Driven Mechanism for Slow Decision Processes in Reverberant Networks

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    The spike activity of cells in some cortical areas has been found to be correlated with reaction times and behavioral responses during two-choice decision tasks. These experimental findings have motivated the study of biologically plausible winner-take-all network models, in which strong recurrent excitation and feedback inhibition allow the network to form a categorical choice upon stimulation. Choice formation corresponds in these models to the transition from the spontaneous state of the network to a state where neurons selective for one of the choices fire at a high rate and inhibit the activity of the other neurons. This transition has been traditionally induced by an increase in the external input that destabilizes the spontaneous state of the network and forces its relaxation to a decision state. Here we explore a different mechanism by which the system can undergo such transitions while keeping the spontaneous state stable, based on an escape induced by finite-size noise from the spontaneous state. This decision mechanism naturally arises for low stimulus strengths and leads to exponentially distributed decision times when the amount of noise in the system is small. Furthermore, we show using numerical simulations that mean decision times follow in this regime an exponential dependence on the amplitude of noise. The escape mechanism provides thus a dynamical basis for the wide range and variability of decision times observed experimentally
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