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Rising Indian hip-hop artist Big Ghuman is renowned for his avant-garde approach to the contemporary hip-hop subgenre. Big Ghuman has been able to carve out a distinctive place for himself in the Indian music scene by fusing Indian culture and Western elements.

His songs have engaging beats, soulful melodies, and meaningful words that connect with his listeners. The unbridled intensity and shameless attitude that Big Ghuman delivers to every performance define his style.

Big Ghuman, despite being relatively new to the scene, has already caught the interest of both music critics and fans. He is swiftly rising to prominence as one of India's most promising Hip Hop musicians thanks to the praise his music has received for its authenticity and originality.

In the Indian music scene, Big Ghuman is an act to keep an eye on. He is ready to elevate the Contemporary Hip Hop genre with his distinctive fusion of Indian and Western inspirations, solidifying his status as one of the most dynamic and forward-thinking artists of his time.

Big Ghuman is a well-known hip-hop musician from India nowadays. His career features a number of well-known songs, including "Sip Sip," "No Match," and "Still." A fan favorite, "Mittran Da Naa" has a memorable beat and lyrics that exhibit Big Ghuman's distinctive approach.

"MAST MAST," another well-liked single from Big Ghuman, combines conventional Punjabi and modern Hip Hop components. Another outstanding track that demonstrates Big Ghuman's talent for fusing several genres into a coherent sound is "Punjabi Boys."

The songs "Face Off" and "No Time Out (feat. Big Ghuman)" are two more that highlight Big Ghuman's skill as a lyricist and musician. With its cheerful speed and catchy melody, "Jatts in Canada" is another well-liked song. The slower, more reflective song "Daru" demonstrates Big Ghuman's range as a musician.

All things considered, Big Ghuman has made a name for himself in India's current Hip Hop scene. His distinctive fusion of traditional Punjabi music with contemporary Hip Hop elements has gained him a devoted fan base and favorable reviews.

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Indian contemporary hip-hop musician Big Ghuman has been regularly releasing new music for his followers. His most recent song, "No Match," which was released in 2023, is evidence of his artistic development. The song has his trademark flow and enticing sounds, along with lyrics that speak to his fans' hearts.

The song "Mittran Da Naa" by Big Ghuman, which he released in 2021, expresses his love for his birthplace and the people he grew up with. He sings about his youth and the experiences he has with his buddies, which gives the song a nostalgic tone. The song is a favorite among fans since it perfectly combines his musical style and roots.

Big Ghuman released "Face Off" in 2020, a song that showcases his skill as a lyricist and his natural ability to change up his flow. His tremendous intensity and delivery are complemented by the song's hard-hitting tempo. The song demonstrates his versatility as a musician and his capacity to create music that appeals to a variety of listeners.

Overall, Big Ghuman's most recent musical output is evidence of his maturation and improvement as a musician. He is a distinctive and fascinating musician to watch in the Hip Hop music landscape because of his ability to combine his heritage with his modern style.

A modern Hip Hop rapper from India named Big Ghuman has worked with several performers over the years. 'Mittran Da Naa' with Sultaan, 'Punjabi Boys' also with Sultaan, 'Sip Sip' with Sultaan, 'No Time Out' with Big Ghuman and Sultaan, and 'Jatts in Canada' with Sultaan are just a few of his notable collaborations.

'Sip Sip' with Sultaan is one of the most significant collaborations to stand out. The cheerful, catchy song has become a youth anthem and is quite popular. Big Ghuman's distinctive style of fusing modern Hip Hop beats with Punjabi lyrics is evident throughout the song. Sultaan's addition to the song gives it a distinctive taste and elevates it to the status of a crossover success.

The collaboration 'No Time Out' with Big Ghuman and Sultaan is another noteworthy one. The song is a powerful track that highlights both performers' lyrical skill. For many fans, the song serves as an anthem of inspiration because of its powerful message of perseverance and never giving up. Fans and reviewers alike have praised the song, firmly establishing Big Ghuman as one of India's top Hip Hop acts.

Sultaan and Big Ghuman have worked together on some of his most significant pieces. He was able to expand his fanbase and solidify his position as India's top Hip Hop artist because to these partnerships. Some of the most well-known Hip Hop songs in India are the product of Sultaan's singular blending of modern beats with Punjabi lyrics.

Karaminder Ghuman: No patience for you. No patience, no new patients it's like that one Drake song, no new friends. It was except no new patients. All right. No patience. And that was quite frustrating. So frustrating. It like, I felt a little depressed. I felt a little beaten down by it like, this is so frustrating.

Karaminder Ghuman: It can yell. It can, um, Rotate it. And it's got also like little butt kicker transducers in the seat. It's got vibration, it's got even little compressed air around your neck and your feet. It's got fans inside the cinema. It's got strobes as well. It's got smoke and fog in the front. Uh, if it's raining, there's effects for rain, there's also effects for water right in your face, if applies for it.

Despite sharing similar typical retinotopic eccentricity, word and face stimuli are highly distinct along several axes that are hypothesized to influence where they are processed in VTC (Op de Beeck et al., 2019). Word- and face-processing operates on very different low-level visual properties (Kay and Yeatman, 2017), follows different developmental trajectories (Saygin et al., 2016), and feeds into distinct networks that support either language or social interactions (Stevens et al., 2015, 2017), respectively. Despite this, the cortical localizations for word- and face-processing in VTC are remarkably close together, and it remains debated whether or not there are regions in VTC that independently encode word or face information at all (Behrmann and Plaut, 2013). However, electrical stimulation and lesion studies suggest that they are independent in VTC (Hirshorn et al., 2016; Sabsevitz et al., 2020).

Neuroimaging studies have separately mapped word- and face-processing networks in VTC. Printed word recognition is thought to be conducted in part by a network of regions along the left occipitotemporal sulcus, that differ in the complexity of their responses and are hierarchically organized (Halgren et al., 1994; Cohen et al., 2000; Vinckier et al., 2007; Dehaene and Cohen, 2011; Lerma-Usabiaga et al., 2018). Face-processing is thought to be conducted in part by a network of regions distributed bilaterally along the midfusiform sulcus (Tsao et al., 2008; Weiner and Grill-Spector, 2010). However, few studies have investigated VTC's responses to word and face stimuli within the same participants (Allison et al., 1994; Haxby et al., 1994; Puce et al., 1996; Matsuo et al., 2015; Harris et al., 2016). Those that have, have relied on low sample sizes or imaging modalities with differential sensitivity to different aspects of neural activity (e.g., high- and low-frequency neural activity) (Engell et al., 2012; Jonas et al., 2016). Therefore, much remains unknown about how visual word- and face-processing networks organize relative to one another, and to what degree they overlap (Haxby et al., 1994; Puce et al., 1996; Dehaene et al., 2010; Matsuo et al., 2015; Harris et al., 2016).

Further, it is unclear whether the nodes within these processing networks differ in the temporal dynamics of their responses, although previous studies have suggested that different regions may contribute to distinct stages of word- and face-processing (Federmeier and Kutas, 1999; Vinckier et al., 2007; Li et al., 2019). Additionally, category-selective maps derived from BOLD responses may be incomplete because of BOLD's increased sensitivity to early stimulus evoked activity (100-300 ms after stimulus presentations) relative to later responses (Jacques et al., 2016; Ghuman and Martin, 2019) and greater correlation with high-frequency broadband activity in invasive neural recordings compared with lower-frequency electrical potentials (Engell et al., 2012; Jacques et al., 2016).

Thirty-one of the participants saw pictures of faces, words, bodies, hammers, houses, and phase-scrambled faces. The remaining participants viewed a modified set of stimuli with the same viewing parameters described above. One participant viewed pictures of consonant-strings and pseudowords instead of hammers, two viewed shoes instead of words, one viewed consonant-strings and pseudowords instead of hammers and houses, and one viewed general tools and animals instead of hammers.

A subset of the participants that underwent the category localizer task also participated in word and/or face individuation tasks (Table 1). These tasks shared identical presentation parameters as the category-localizer task (i.e., interstimulus interval, stimulus-on time, and viewing angle) but contained different images. Twelve underwent a word individuation task that included pictures of real words, pseudowords, and consonant-strings or false-fonts. Participants again were instructed to respond if a given stimulus was repeated twice in a row. Every stimulus (i.e., individual word) was presented 60 times. Twenty underwent a face individuation task where they viewed individuals of varying identity and emotions. Participants were instructed to indicate whether each face was male or female during this task. Each identity was repeated 60 times. ff782bc1db