sCRACM relies on photostimulating axons, which can

sCRACM relies on photostimulating axons, which can JAK inhibitor be efficiently excited even when severed from their parent somata.

Therefore, sCRACM can map connections between defined neuronal populations over long length scales, not limited to circuits preserved in brain slices. sCRACM also provides an estimate of the spatial distribution of synapses made by ChR2-positive axons onto the dendritic arbors of recorded neurons. Here, we applied anatomical methods and sCRACM to map inputs from vS1 onto neurons in vM1. vM1 neurons in upper layers (L2/3 and L5A), which harbor mostly cortico-cortical neurons, receive strong input from vS1. These neurons also provide the majority of the projection back to vS1. In contrast, deep layer neurons (L5B and

L6), which include the “corticofugal” neurons that project to motor centers in the brainstem and elsewhere, received only weak input from vS1. We characterized the projections EGFR inhibitor between vibrissal somatosensory cortex (vS1) and vibrissal motor cortex (vM1) using viral-mediated anterograde tracing (Figure 1; see Figure S1 and Movie S1 available online). vS1 was identified by the presence of large barrels. vS1 layers were defined according to well-established cytoarchitectural criteria (Bureau et al., 2006 and Groh et al., 2010). Individual layers contain distinct sets of neurons, with different projection patterns and inputs (Groh et al., 2010, Hattox and these Nelson, 2007, Sato and Svoboda, 2010 and Svoboda et al., 2010). We labeled vS1 neurons by

infection with recombinant adeno-associated viruses (AAV) (Chamberlin et al., 1998) expressing eGFP or tdTomato, and imaged the projections of the infected neurons throughout the brain using a high-resolution slide scanner (excluding most of brainstem and spinal cord). Infected neurons were distributed over several barrel columns (diameter of infection site <1.5 mm) (Figures 1A and 1B), mainly in L2/3 and L5 (Figure S1A). Axonal projections were seen in multiple cortical and subcortical targets. We quantified these projections by integrating the fluorescence intensity over the sections containing specific targets and fluorescent axons (see Supplemental Experimental Procedures).

The fluorescent images were split by dual-view with a CFP/YFP fil

The fluorescent images were split by dual-view with a CFP/YFP filter set and projected onto the CCD camera operated by Volocity (Improvision, Lexington, MA)

or MicroManager ( The 4×-binned images were obtained at 50–100 ms GSK126 mw exposures, 10–20 fps for 5 min. The YFP and CFP fluorescent intensities were measured by in-house-developed ImageJ plugins ( Calcium imaging experiments were performed either by manually recentering moving animals on the stage or through an in-house-developed acquisition software that controls the camera and motorized stage through Micromanager and ImageJ. Each frame of the acquired images was subjected to real-time processing to detect targeted cells, track objects, record stage positions, and recenter the tracked object. During postimaging processing,

two regions of interest Transmembrane Transporters activator were set to detect the anterior-posterior axis. VA8 and DB6 were used as anterior and posterior cells, respectively, in motoneuron imaging. AVA/AVE or AVB and cluster of cells were used in interneuron imaging. The cell position at each time point was determined based on the coordinates of the stage position and cell position in the field of view, and the velocity was calculated by changes in the cell position between each frame. The forward and backward directions were determined by comparing changes in the anterior-posterior axis. Interneuron imaging was performed under two different conditions. (1) Imaging when animals were allowed relatively free movement (Figures 1D, 1E, and 6). This condition allows correlation between motion and changes in calcium

signals. Animals were placed on freshly made 2% Amisulpride wet agarose pads, mounted with a few microliters of M9 buffer, and imaged with a 16× objective through the automated tracking system. We imaged multiple interneurons as a single ROI in the head region of hpIs190 (AVA and AVE) or a single interneuron as an ROI in hpIs179 (AVB). (2) Imaging when animals were allowed restricted movement. Single-neuron imaging of AVA or AVE with hpIs157 and hpIs190 ( Figure 1C; Figures S1B, S1C, S3, and S7), and AVB and AVE simultaneous imaging in a strain carrying both hpIs157 and hpIs179 ( Figure 1F), was carried out under this condition. In both hpIs157 and hpIs190, the closely spaced cell bodies prevented precise tracking at individual neuron resolution when animals were allowed free movement. Animals were mounted on dried 5% agarose pads with a few microliters of M9 buffer, covered by a coverslip, and imaged with a 63× objective.

, 2000) Interestingly, activation of D1 receptors was recently s

, 2000). Interestingly, activation of D1 receptors was recently shown to prolong “up state-like” potentials evoked by repetitive glutamate uncaging on distal SPN dendrites (Plotkin et al., 2011). Generation of these regenerative plateau potentials required NMDA receptors and low-threshold CaV3 channels, which are enriched in distal dendrites and spines (Carter and Sabatini, 2004; Carter et al., 2007; Day et al., Epigenetic inhibitor molecular weight 2006), but it is currently unclear whether

the D1 receptor-evoked enhancement is mediated by direct modulation of NMDA receptors or dendritic K+ and Ca2+ conductances or both. Thus, through its actions on voltage-gated K+ and Ca2+ channels, D1 receptors promote synaptic integration and spike discharge during up states while increasing the threshold for upward transitions, effectively acting to enhance contrast between up and down states. However, Lapatinib ic50 this relatively simple and consistent view of DA’s action on dSPNs is complicated by the reported effects on voltage-gated Na+ currents, which are reduced in amplitude by DA and D1-like receptor agonists (Cepeda et al., 1995; Schiffmann et al., 1995; Surmeier et al.,

1992; Zhang et al., 1998). This observation is largely responsible for the initial conclusion that D1 receptors exert a net inhibitory action on SPN excitability (Nicola et al., 2000). The apparently conflicting actions of DA on various ionic conductances reflect some of the difficulties associated with extrapolating overall neuromodulatory effects of DA from changes in isolated conductances. Given the importance of subthreshold membrane potential fluctuations to SPN function and the inability of somatic current injection protocols

to engage distal dendritic conductances (Day et al., 2008) and to evoke state transitions in acute slices (Wilson, 2004), analyses of spike discharge modulation upon somatic depolarization may not adequately capture DA’s influence on synaptic integration and intrinsic excitability. Nevertheless, although the spike-promoting effects of D1 receptors on K+ and Ca2+ channels MycoClean Mycoplasma Removal Kit may be moderated by reduced Na+ channel availability, most of the evidence accrued to date favors models in which D1 receptors promote dSPN intrinsic excitability (Gerfen and Surmeier, 2011; Wickens and Arbuthnott, 2005). The reported effects of D2 receptor activation on isolated ionic conductances and up state potentials in SPNs largely oppose those of D1 receptors. Through their inhibitory action on PKA, D2 receptors suppress currents attributable to Kir2 channels but enhance depolarization-activated and ATP-sensitive K+ channels (Greif et al., 1995; Perez et al., 2006; Sun et al., 2000; Surmeier and Kitai, 1993), indicating that D2 receptor activation may facilitate up state transitions but stunt their duration and the depolarization achieved. D2 receptors further limit somatic excitability by decreasing Ca2+ influx through somatic CaV1 channels (Hernandez-Lopez et al., 2000; Salgado et al., 2005).

In the presence of such regularities, the past can help predict t

In the presence of such regularities, the past can help predict the future. A way to do this is to use information from the past for building a statistical model of the environment (Winkler et al., 2009). The model is then used for predicting

the future and interpreting it. Indeed, numerous studies have demonstrated sensitivity of neural activity to the overall probability of a stimulus, an important characteristic of the statistical structure of stimulation sequences. Since their introduction as a tool for studying single neurons in the auditory system by Ulanovsky et al. (2003), oddball sequences have been used to study probability sensitivity in a number of animal models and at different levels of auditory pathway, including the inferior colliculus of rats (Malmierca Alectinib ic50 et al., 2009; Zhao et al., 2011), the auditory thalamus of mice (Anderson et al., 2009) and rats (Antunes et al., 2010), and auditory cortex of rats (Farley et al., 2010; Taaseh et al., 2011; von der Behrens et al., 2009).

These studies demonstrated that the probability of appearance of a stimulus affects the responses of many neurons VE-821 mw at least to the same degree as the physical characteristics of the stimulus such as its frequency. In fact, cortical responses to rare tones embedded in sequences of common tones are larger than expected from a model of adaptation in narrow frequency channels, suggesting the presence of true deviance sensitivity in auditory cortex (Taaseh et al., 2011). Oddball sequences are most commonly constructed by selecting the sounds essentially randomly given their probabilities. However, the statistical structure of the auditory environment is richer than that of such random sequences. For example, language and music incorporate sequential dependencies, so that the probability of a sound depends much more subtly on the recent auditory past. The goal of the current study

was to examine the many sensitivity of neuronal responses to statistical contexts that include sequential dependence. We contrasted neuronal responses to sequences in which the overall probability of the rare tone was identical but the rare tone itself was either randomly presented or appeared periodically among the common tones. If the periodic order can be recognized, periodic sequences should evoke less surprise, and therefore smaller neuronal responses. Our data, from intracellular and extracellular recordings in the auditory cortex of anesthetized rats, suggest that neurons are sensitive to the periodic order of presentations, even for periods of length 20 (rare tone probability of 0.05). We recorded responses in the left auditory cortex of halothane-anesthetized rats to sounds presented monaurally to their right ear. We used both intracellular recordings (n = 17 neurons in 16 rats) and extracellular recordings (n = 180 recording locations in 12 rats) to collect membrane potentials, local field potentials (LFPs), and multiunit activity (MUA).

, 2011 for individual brain differences in duration discriminatio

, 2011 for individual brain differences in duration discrimination of the multiseconds range; see Kanai and Rees, 2011 for a review). Our results show that the representation

of the trained duration was associated with neurophysiological changes in functional activity, gray-matter volume, and white-matter connectivity within a sensory-motor circuit comprising occipital, parietal, and insular cortices, plus the cerebellum. Importantly, we found that these changes correlated with the training-induced behavioral changes on a subject-by-subject basis LY2835219 datasheet and that activity and gray-matter volume around the central sulcus before training predicted learning abilities as indexed after training. These findings provide us with the first neurophysiological evidence of structural and functional plasticity associated with the learning of time. Seventeen healthy volunteers were tested on a temporal discrimination task over five consecutive days. The experimental protocol took place from Monday to Friday and was structured in three distinct phases: pretraining, training, and posttraining (see Table 1). The pretraining (day 1) and posttraining this website (day 5) phases consisted of a psychophysics

session followed by an imaging session in which functional and structural (a high-resolution T1-weighted image and DTI) data were acquired. The psychophysics session served to estimate subject-specific temporal discrimination thresholds to be used during fMRI. The training phases (days 1–4) consisted of a single session of behavioral testing during which volunteers were trained in the visual modality only (for ∼1 hr). The task during training consisted of crotamiton the sequential

presentation of the two temporal intervals marked by four brief visual flashes and separated by a short gap (see Figure 1A and Experimental Procedures for more details). One of the two intervals was the “standard duration,” which was equal to 200 ms (T), and the other was the “comparison duration,” which was equal to the standard plus a variable, always positive ΔT1 value (T+ΔT1). Volunteers were asked to indicate which of the two intervals lasted longer. During training the duration of the comparison interval was adjusted adaptively across trials, in order to obtain the ΔT1 threshold leading to 79% correct discrimination. During the training sessions (days 1–4) and the pre- and posttraining psychophysics sessions (day 1 and 5) the standard duration was always 200 ms (T). We assessed whether learning had occurred in two different ways. We first analyzed the psychophysical data of pre- and posttraining sessions in order to identify participants, for whom the 4 days of training improved temporal discrimination performance. For each volunteer we computed the ratio (ΔT1pre − ΔT1post) / ΔT1pre. Positive values indicate lower thresholds in post- compared to pretraining and, thus, that learning did take place.

, 2007, Roth and Häusser, 2001 and Schmidt-Hieber et al , 2007; F

, 2007, Roth and Häusser, 2001 and Schmidt-Hieber et al., 2007; Figures 4G and S4A) and number of branches (Figures S4C to S4D). In contrast, the distance-dependent decrease in both the simulated EPSC and qEPSC amplitudes were highly sensitive to changes in dendritic diameter (0.3 to 2 μm; Figures 4G and S4A). These simulations indicate that under somatic voltage-clamp conditions, poor space clamp of dendritic synaptic conductances can

account for a majority of the distance-dependent amplitude reduction and slowing of somatically recorded EPSCs. Similar results were obtained when simulating current-clamp recordings of EPSPs (Figures 4E and S4E) and Selleckchem GSK-3 inhibitor qEPSPs (Figures 4F and S4F), consistent with cable theory and previous experiments (Spruston et al., 1993, Thurbon et al., 1994 and Williams and Mitchell, 2008). Simulated EPSP and qEPSP exhibited a distance-dependent decrement in amplitude, although to a lesser extent than EPSCs (51% and 40%, respectively, at 47 μm) but were critically influenced by dendritic diameter (Figure 4H). The distance-dependent increase in the local depolarization was similar to that for voltage clamp. Taken together, these simulations demonstrate that passive neuron models with narrow dendritic diameters

AZD8055 ic50 are sufficient to mimic the observed distance-dependent decrease in qEPSC amplitude and slowing of its time course, and predict a dendritic gradient of filtered EPSPs. We next examined whether the large dendritic depolarization could decrease the synaptic current driving force and introduce a nonlinearity that would curtail linear summation of EPSPs within the same dendrite (Bloomfield et al., 1987 and Rall et al., 1967). We studied the subthreshold input-output relationship of single SC dendrites using rapid diffraction-limited one-photon photolysis. Photolysis-evoked EPSPs (pEPSPs) were elicited using a 405 nm and diode (Trigo et al., 2009) and laser

pulse durations between 30 and 100 μs in order to vary the amplitude of pEPSPs. Because of the high density of excitatory synapses (∼0.7 μm intersite distance; Figure 3E), pEPSPs could be evoked at most photolysis locations (Figure 5A). NMDARs were pharmacologically blocked since they are known to be extrasynaptic (Clark and Cull-Candy, 2002). We examined the input-output relationship by comparing the algebraic sum of individual pEPSPs from 5 laser locations (5 μm apart) along the dendrite, with compound pEPSPs in response to quasi-simultaneous (200 μs interval) activation of all 2 to 5 locations. The compound pEPSP were systematically smaller than the algebraic sum of its corresponding individual pEPSPs (Figures 5A and 5B). pEPSPs were converted to number of quanta by dividing them by the measured qEPSP of 2.5 mV (Supplemental Experimental Procedures).

, 2008a and Mallet et al , 2008b) (Figures 1A–1D) We examined wh

, 2008a and Mallet et al., 2008b) (Figures 1A–1D). We examined whether the “antiphase” firing of GP-TI and GP-TA neurons was preserved across these two extreme brain states. For this purpose, some of the GP-TI and GP-TA neurons were also recorded during the activated brain state with its characteristic beta oscillations (Figures 1A and 1B). Dichotomous spike timings of GP-TI and GP-TA neurons during slow oscillations (Figures 1E and PD0332991 nmr 1F) were indeed maintained during cortical beta oscillations (Figures 1G and 1H). GP-TI neurons (n = 14) were, on average, most likely to fire at 44.3° ± 18.4° (mean ± SEM; range

of preferred angles 348°–134°, p < 0.05, Rayleigh tests) with respect to the peaks of cortical beta oscillations at 0°/360°. However,

GP-TA neurons (n = 23) fired at a significantly different phase (p < 0.05, Watson-Williams F test) of 275.8° ± 7.4° (range, 208°–358° p < 0.05, Rayleigh tests). Average firing phases of these identified GP-TI and GP-TA neurons were similar to those of several hundred GPe units recorded with multielectrode arrays ( Mallet et al., 2008a). Different spike-firing patterns of identified neurons were mirrored by inversely-related firing rates, irrespective of brain state. During SWA, GP-TI neurons fired much faster than GP-TA neurons, but during beta oscillations, the situation was reversed and GP-TA neurons fired faster than GP-TI neurons (both p < 0.05, Mann-Whitney tests). Furthermore, most GP-TI neurons (93%) decreased their firing rates during Linifanib (ABT-869) transition from SWA to the activated brain state, whereas most GP-TA neurons (97%) increased firing (Figures 1I and 1J). Regularity of firing was SB431542 cost also different, with GP-TI neurons firing more regularly than GP-TA neurons during SWA but less regularly during beta oscillations (both p < 0.05, Mann-Whitney tests). Both GP-TI and GP-TA neurons fired more regularly during beta oscillations as compared to SWA (Figures 1I and 1J). Importantly, a small sample of

identified GPe neurons (n = 7) fired so infrequently during SWA (mean firing rates of 0.002–0.2 Hz) that we could not statistically classify them as GP-TI or GP-TA neurons. However, we established that these very slow-firing neurons had some other key properties of GP-TA neurons. First, like GP-TA neurons, they all strongly increased their firing rate upon transition from SWA to the activated brain state (0.06 ± 0.02 Hz and 15.3 ± 2.4 Hz, respectively). Second, their firing was significantly modulated in time with cortical beta oscillations (p < 0.05, Rayleigh tests) and they were most likely to fire at phases (283.5° ± 10.5°; range, 246°–318°) that were similar to those preferred by identified GP-TA neurons but not by GP-TI neurons (p > 0.05 and p < 0.05, respectively, both Watson-Williams F tests). Thus, all of these slow-firing GPe cells were classified as GP-TA neurons for group analyses (the molecular profiles of these slow cells were also identical to GP-TA neurons; see below).

Preclinical studies have shown that even relatively low doses of

Preclinical studies have shown that even relatively low doses of dAMPH (equivalent to the doses used in clinical practice) can lead to striatal DA neurotoxicity in rodents and non-human primates (Ricaurte et al., 2005), as evidenced for instance by reductions in striatal DA concentrations and DA transporter (DAT) binding sites. PET studies in dAMPH treated monkeys have shown reductions in striatal [18F]fluoro-l-dopa uptake in vervet monkeys

(Melega et al., BMS-907351 ic50 1996 and Melega et al., 1997). In line with this, in humans, a study by Reneman et al. (2002) has shown that recreational dAMPH use is linked to lower striatal DAT availability. Because the DAT is a structural component of the DA-axon, loss in DAT has been used as a marker for DAergic damage (Reneman et al., 2002). Because dAMPH is frequently prescribed in the treatment of ADHD it is a drug that is relatively easy to obtain for illicit purposes and in fact is misused by subjects both with and without ADHD (Wilens et al., 2008). Therefore it is important to further investigate

DA dysfunction in recreational users of dAMPH. Recreational users, i.e., subjects not being treated for substance abuse, tend to use less frequently and lower dosages than subjects with a substance use disorder. To the best of our knowledge, no other studies have yet investigated the DA system in recreational users of this drug. Studies in abstinent selleck chemicals dAMPH users have demonstrated sustained deficits in several behavioral paradigms, including decision-making (Ersche et al., 2005), memory (Rapeli et al., 2005) and set-shifting (Ornstein et al., 2000). Although functional MRI (fMRI) measures changes in blood oxygenation rather than neurochemistry, it has been suggested that striatal activation during anticipation of reward as measured with fMRI might partially index DAergic function (Schultz, 2002). In addition, fMRI can give region-specific neurovascular responses to a DAergic challenge (Knutson et al., 2004); Willson et al., 2004). In view of this, it is of interest

to investigate anticipation of reward in recreational old users of dAMPH and their reaction to a DA challenge. The combination of a DA challenge with fMRI (pharmacological MRI; phMRI) enables a more direct assessment of DA functions, because brain activity during striatal activation is investigated in addition to the modulating effect of a DA agent (Honey and Bullmore, 2004). A drug that is well known to activate the DA system is methylphenidate (MPH), commonly used in the treatment of ADHD. MPH acts by blocking the DAT, which prevents the reuptake of DA by the presynaptic neuron and thus increases DA concentration in the synaptic cleft. Oral MPH challenges have been used in fMRI investigations involving both healthy and ADHD populations (Shafritz et al., 2004, Bush et al., 2008, Schlosser et al., 2009 and Rubia et al., 2009), but not dAMPH users.

Thus, removing Cdh6 does not disrupt the formation or positioning

Thus, removing Cdh6 does not disrupt the formation or positioning of OPN neurons, which argues that the defective targeting in Cdh6 mutants reflects a failure of specific RGCs to recognize and terminate in their proper targets. We noted variation in the severity of axon targeting defects in Cdh6 mutants, especially at ages P20 and older. In early postnatal animals (P0–P6), 3 out of 11 Cdh3-GFP::Cdh6−/− mice exhibited apparently normal Cdh3-RGC axon targeting. In the remaining 8 Cdh3-GFP::Cdh6−/− mice, the reduction in Cdh3-RGC input to the OPN ranged from severe

(n = 5) to moderate (n = 3). By P20, 3 out of 7 Cdh6−/− mice had no apparent targeting defects, 2 out of seven had severe phenotypes and 2 had moderate phenotypes. Examples of the variation in target innervation defects in the OPN and mdPPN are shown in Figure S4. This variation suggests that other molecules can compensate for early targeting errors caused by removal of Cdh6. One candidate is Cdh3. We attempted to create Cdh3-GFP::Cdh3−/− mice in order to visualize the axons of Cdh3-RGCs in the Cdh3 null background but unfortunately those efforts failed, likely because the Cdh3-GFP transgene and the Cdh3 null cassette are located near one another on the same chromosome. However, whole-eye retinofugal

tracing of Cdh3−/− mutant mice indicated that eye-specific targeting to the dLGN and SC was normal. Input to image-forming areas was also normal in Cdh6−/− mutant mice, as assessed by whole-eye anterograde labeling (Figures 4N–4P). Deciphering the molecular HSP inhibition basis of neural circuit specificity is a longstanding goal of neurobiology. The hypothesis that cadherins generate precise connectivity in the nervous system was

initially put forth by Takeichi and coworkers (Suzuki et al., 1997 and Inoue et al., 1998). Loss-of-function data support that model in lower vertebrates and flies (Inoue and else Sanes, 1997, Lee et al., 2001 and Prakash et al., 2005). Previous studies showed that distinct components of mammalian sensory circuits can be defined by their expression of different cadherins (Suzuki et al., 1997 and Hertel et al., 2008), but evidence that cadherins play a functional role in generating wiring specificity in the mammalian CNS has been lacking. Here, we showed that Cdh6 mediates axon-target matching in a specific non-image-forming visual circuit. These data provide some of the first evidence that a specific classical cadherin can promote wiring specificity in the mammalian visual system. The axon targeting defects we observed in Cdh6 knockout mice raise important questions about the mechanisms by which cadherins impart specificity of neural connections. The simplest explanation is that Cdh6-expressing RGC axons adhere to Cdh6 expressing target neurons via homophilic interactions that occur at the level of the targets.

Thus, input from both hemifields reaches each hemisphere In fact

Thus, input from both hemifields reaches each hemisphere. In fact, in albinism three different resulting cortical organization patterns have been reported. The geniculostriate projection can be reordered resulting in a contiguous retinotopic map of both visual hemifields (“Boston” pattern); alternatively, reordering can be absent with intracortical suppression inducing a lack of behavioral sensitivity of the temporal retina (“Midwestern” pattern)

or without suppression retaining sensitivity (“True Albino” pattern). While the former organization patterns of the visual cortex appear to be reserved to nonprimate models of albinism, the latter is found in both nonprimates and primates (Guillery et al., 1984; Hoffmann et al., 2003). PI3K Inhibitor Library datasheet Our aim was to resolve the organization pattern in human achiasma. We investigated two of these extremely rare achiasmic subjects. Three types of investigations were performed using 1.5, 3, and 7 Tesla MRI: (1) optimized retinotopic mapping (DeYoe et al., 1996; Engel et al., 1994, 1997; Hoffmann et al., 2009; Sereno et al.,

1995; Wandell et al., 2007), (2) characterization of the population GDC-0199 in vitro receptive field (pRF) properties (Dumoulin and Wandell, 2008), and (3) diffusion-tensor imaging (DTI) and tractography to investigate white matter integrity (Sherbondy et al., 2008a, 2008b). Our results indicate that the abnormal visual input in human achiasma does not induce a sizable topographic reorganization in the geniculostriate projection or of the occipital callosal connections. We propose that reorganization of intracortical architecture in the visual system underlies the ability to cope with these abnormal inputs. In subject AC1, visual hemifield representations on the cortical surface were obtained separately for each visual hemifield and eye using fMRI-based retinotopic mapping (DeYoe et al., 1996; Engel et al., 1994, 1997; Hoffmann et al., 2009; Sereno et al., 1995; Wandell et al., 2007). Mapping of either visual hemifield Tolmetin yielded dominant responses on the occipital lobe ipsilateral to

the stimulated eye (Figures 1 and S1). Figure 1 illustrates that stimulation of the right eye revealed orderly eccentricity maps of both hemifields on the right hemisphere only (Figure 1B). Moreover, opposite visual hemifields were represented as a cortical superposition of mirror-symmetrical visual field positions. Accordingly, the phase maps obtained for stimulation in opposite hemifields were highly correlated (Figure 1C) and the borders of the early visual areas were identical for the representation of the contralateral and the ipsilateral visual hemifield as derived from polar angle maps (Figure S1). Similar results were obtained on the left hemisphere for stimulation of the left eye (Figure S1).