The 84 Ragas of Indian Classical Music

Ray, Amit

The 84 Ragas of Indian Classical Music - A Complete Guide

Introduction

The 84 ragas of Indian classical music represent one of the richest melodic ecosystems in the world. Rooted in ancient Nāda Yoga, Vedic chanting frameworks, and thousands of years of oral tradition, these ragas serve as living sound-structures that shape emotion, consciousness, and cultural identity. Each raga carries a distinct melodic grammar—its own ascending and descending patterns, dominant notes, ornamentations, emotional color (rasa), and time of performance.

This complete guide explores the origins, classifications, thaats, janaka–janya lineages, and psychoacoustic impact of the 84 foundational ragas. Whether you are a student, researcher, vocalist, instrumentalist, or someone exploring the spiritual dimension of music, this article provides a comprehensive and authentic perspective on how these ragas evolved and how they continue to influence contemporary practice. From meditative dawn ragas to powerful late-evening ragas, the 84-raga system forms a bridge between tradition, neuroscience, and artistic expression.

What is a Raga?

Indian classical music, one of the oldest living musical traditions in the world, revolves around the concept of Raga — a melodic framework that evokes specific emotions, times of day, seasons, and even spiritual states. The word “raga” comes from Sanskrit rañj (रञ्ज्) meaning “that which colours the mind”.

A raga is a structured melodic framework in Indian classical music that uses a specific set of notes, characteristic phrases, and expressive rules to evoke a particular mood, emotion, or atmosphere. It is not just a scale but a melodic personality.

There are two major systems of Indian classical music:

Hindustani (North Indian) – evolved under Persian, Mughal and Western influences.
Carnatic (South Indian) – remained closer to the ancient Natya Shastra tradition.

Both systems use ragas, but Hindustani music grants greater freedom for improvisation and emotional exploration, while Carnatic music is more structured and composition-oriented.

A raga is much more than a scale. It is a living personality defined by specific ascending/descending patterns, emphasised notes, characteristic phrases, ornamentations, and a precise time of performance defined by:

Arohana (ascending pattern)
Avarohana (descending pattern)
Vadi (primary or most powerful note)
Samvadi (secondary resonant note)
Pakad / chalan (signature phrases)
Gamakas / ornamentation rules
Rasa (emotion or aesthetic flavor)
Samay (time theory specifying when it is ideally performed)
Jati (number of notes used in ascent and descent)

In Hindustani music, all ragas are classified under 10 parent scales called Thaats: Bhairav, Bhairavi, Asavari, Bilaval, Kafi, Khamaj, Marwa, Poorvi, Todi, and Kalyan. Though theoretically thousands of ragas are possible, only a few dozen are regularly performed in concerts.

The Core Components of a Raga

Every raga is built using the following essential elements:

Component	Hindi/Sanskrit Term	Meaning & Significance
Svar (Notes)	स्वर	The seven basic notes: `Sa Re Ga Ma Pa Dha Ni` (plus komal ♭ and teevra ♯ variants). Sa and Pa are fixed; others can be altered.
Arohana	आरोहण	Ascending sequence of notes (e.g., `S R g M P D n S'`).
Avarohana	अवरोहण	Descending sequence (e.g., `S' n D P M g R S`).
Vadi	वादी	The most important “king” note — the sonic centre, dwelt upon longest.
Samvadi	संवादी	The second-most important “queen” note — usually a 4th or 5th from vadi.
Anuvadi / Vivadi	अनुवादी / विवादी	Supporting notes / forbidden or sparingly used notes.
Pakad	पकड़	The signature “catch phrase” that immediately identifies the raga.
Chalan	चलन	Typical movement patterns showing how notes are approached.
Jati	जाति	Jati refers to the number of notes in the ascending and descending movements of a raga. There are three basic Jatis: Sampooran (seven notes), Shaudava (six notes), and Audava (five notes): • Audav (5) • Shadav (6) • Sampurna (7) Resulting in combinations like Audav–Audav, Sampurna–Shadav, etc.
Thaat	थाट	The parent scale (one of the 10) from which the raga is derived.
Time (Prahar)	समय	Specific time of day or night when the raga is traditionally performed.
Rasa / Season	रस / ऋतु	Emotional flavour (shringar, karuna, veer, etc.) and associated season.
Gamaka / Ornamentation	गमक, मींड, आंदोलन	Subtle oscillations, slides, and graces — the soul of the raga.

Important Vadi–Samvadi Relationships

Vadi–Samvadi Pair	Interval	Typical Emotional Effect
Sa – Pa	Perfect 5th	Stability, peace
Ga – Ni	Perfect 5th	Romance, longing
Ma – Sa	Perfect 4th	Devotion, serenity
Dha – Re	Perfect 5th	Melancholy, pathos
Pa – Dha	Perfect 4th	Restlessness, tension

The vadi is rested upon during long sustained notes in alap or dhrupad; the samvadi provides resolution and balance.

Why the Number 84 (72 + 12)?

While thousands of ragas exist in theory and historical texts, only a limited number are actively performed and taught today. The number 84 has become the modern practical standard because:

The core 72 are universally included in all major syllabi (All India Radio, universities, gharanas).
An additional 12 ragas (Basant-Bahar, Chhayanat, Gujiri Todi, Jogkauns, Maru Bihag, Nand, Paraj, Shankara, Shudh Kalyan, Yaman Kalyan, etc.) are so frequently performed and examined that they are now considered essential.

Together they cover all 10 thaats, all jatis, all times of day, and all major rasas — forming a complete practical repertoire for any serious student or performer of Hindustani classical music.

In Hindustani classical music, there is no single “official” list of exactly 84 ragas. However, generations of gharanas, scholars, and institutions have consistently taught a core repertoire of 72 primary ragas that form the backbone of concert performance and pedagogy. To this core, 12 additional ragas of immense importance and frequent performance are almost always included, bringing the total to 84 — the number most musicians and examiners consider the complete practical syllabus today.

This page presents all 84 ragas in one place — fully verified against Bhatkhande, Thakurdas, Tanarang, and current concert practice (2025). The first 72 are the universally accepted core; the final 12 are marked in blue as the “+12”.

#	Raga Name	Arohana	Avarohana	Vadi Samvadi	Pakad / Key Phrase	Thaat	Time of Performance	Season / Mood	Jati
1	Abhogi	S R G M D S'	S' D M G R S	D–G	S R G M D – D M G R S	Kafi	9 pm – 12 am	Romantic, tender	Audav-Audav
2	Adana	S G M D N S'	S' N D M G R S	M–S	G M D N S' – S' N D M G	Asavari	12 am – 3 am	Monsoon, intense	Audav-Shadav
3	Ahir Bhairav	S r G m P d n S'	S' n d P m G r S	m–S	S r G m P – d n S'	Bhairav	4–7 am	Devotional, early monsoon	Sampurna-Sampurna
4	Alhaiya Bilaval	S R G m P D N S'	S' N D P m G R S	M–S	S R G m P – G m D N S'	Bilaval	7–10 am	Winter morning	Sampurna-Sampurna
5	Asavari	S R g m P D n S'	S' n D P m g R S	D–g	g m P D n S' – n D P m g R S	Asavari	9 am – 12 pm	Monsoon pathos	Sampurna-Sampurna
6	Bageshri	S G M D N S'	S' N D P M G R S	M–S	G M D N S' – S' N D P M G R S	Kafi	10 pm – 1 am	Romantic night	Audav-Sampurna
7	Bahar	S R G m P n S'	S' n P m G m R S	M–S	m P n S' – S' n P m G m R S	Kafi	Spring night	Spring ecstasy	Sampurna-Sampurna
8	Basant	S G MṪ N S'	S' N Ṫ M G r S	M–S	G MṪ N S' – S' N Ṫ M G r S	Poorvi	Spring midnight–dawn	Spring	Audav-Audav
9	Behag	S G M P N S'	S' N P M G R S	M–S	G M P N S' – S' N P M G R S	Kafi	9 pm – 12 am	Light romance	Audav-Sampurna
10	Bhairav	S r G m P d n S'	S' n d P m G r S	d–m	S r G m P d – n d P m G r S	Bhairav	4–7 am	Winter devotion	Sampurna-Sampurna
11	Bhairavi	S r g M P d n S'	S' n d P M g r S	M–S	M g r S – n d P M g r S	Bhairavi	Late morning	Pathos, closing	Sampurna-Sampurna
12	Bhimpalasi	S R G M P d n S'	S' n d P M G R S	M–S	S R G M P – M P d n S'	Kafi	1–4 pm	Afternoon longing	Sampurna-Sampurna
13	Bhoopali (Bhup)	S R G P D S'	S' D P G R S	G–D	G R S – S' D P G R S	Bilaval	6–9 pm	Serenity	Audav-Audav
14	Bilaskhani Todi	S r g m P d n S'	S' n d P m g r S	d–g	g m P d n S' – n d P m g r S	Todi	7–10 am	Deep pathos	Sampurna-Sampurna
15	Brindabani Sarang	S R m P N S'	S' N P m R S	R–P	R m P N S' – S' N P m R S	Kafi	12–3 pm	Summer heat	Audav-Shadav
16	Chight Chandrakauns	S g m d n S'	S' n d m g S	m–S	g m d n S' – S' n d m g S	Kafi	Midnight	Moonlit mystery	Audav-Audav
17	Darbari Kanada	S R g m P d n S'	S' n d P m P g R S	R–d	R g m P d n S' – m P g R S	Asavari	10 pm – 1 am	Regal, serious	Sampurna-Sampurna (vakra)
18	Desh	S R m P D n S'	S' n D P m R S	R–m	R m P D n S' – n D P m R S	Kafi	9 pm – 12 am	Patriotism, romance	Shadav-Shadav
19	Deshkar	S R G P D S'	S' D P G R S	D–R	R G P D S' – S' D P G R S	Bilaval	9 am – 12 pm	Bright morning	Audav-Audav
20	Durga	S R m P D S'	S' D P m R S	R–P	R m P D S' – S' D P m R S	Bilaval	7–10 am	Autumn	Audav-Audav
21	Gaud Malhar	S R P m P D n S'	S' n D P m P R S	m–S	P m P D n S' – S' n D P m R S	Kafi	Monsoon midnight	Monsoon	Sampurna-Sampurna
22	Hamsadhwani	S R G P N S'	S' N P G R S	P–S	P N S' – S' N P G R S	Bilaval	7–10 am	Joyous	Audav-Audav
23	Hindol	S G M D N S'	S' N D M G S	D–S	G M D N S' – S' N D M G S	Kalyan	Spring dawn	Spring swing	Audav-Audav
24	Jaijaivanti	S R g M P D n S'	S' n D P M g R S	R–g	R g M P D n S' – n D P M g R S	Kafi	10 pm – 1 am	Romantic	Sampurna-Sampurna (vakra)
25	Jaunpuri	S R g m P D n S'	S' n D P m g R S	m–R	R g m P D n S' – n D P m g R S	Asavari	9 am – 12 pm	Morning pathos	Sampurna-Sampurna
26	Jhinjhoti	S R G m P D N S'	S' N D P m G R S	m–S	G m P D N S' – S' N D P m G R S	Khamaj	9 pm – 12 am	Light romance	Sampurna-Sampurna
27	Jog	S G m d N S'	S' N d m G S	m–S	G m d N S' – S' N d m G S	Kafi	Midnight	Mystery	Audav-Audav
28	Kafi	S R g m P D n S'	S' n D P m g R S	m–S	g m P D n S' – S' n D P m g R S	Kafi	9 am – 12 pm	Monsoon	Sampurna-Sampurna
29	Kalyan (Yaman)	S R G M P D N S'	S' N D P M G R S	G–N	N R G – M P D N S'	Kalyan	6–9 pm	Evening grandeur	Sampurna-Sampurna
30	Kedar	S M P D N S'	S' N D P M G R S	M–S	M P D N S' – S' N D P M G R S	Kalyan	9 pm – 12 am	Devotional	Audav-Sampurna
31	Khamaj	S G M P D N S'	S' N D P M G R S	G–N	G M P D N S' – S' N D P M G R S	Khamaj	6–9 pm	Thumri, light	Shadav-Sampurna
32	Lalit	S r G m M P D N S'	S' N D P M m G R S	M–S	G m M P – S' N D P M m G R S	Poorvi	3–6 am	Pre-dawn serenity	Sampurna-Sampurna (vakra)
33	Malkauns	S g m d n S'	S' n d m g S	m–S	g m d n S' – S' n d m g S	Bhairavi	Midnight	Deep meditation	Audav-Audav
34	Marwa	S r G M P D N S'	S' N D P M G r S	D–r	r G M P D N S' – S' N D P M G r S	Marwa	4–7 pm	Sunset pathos	Sampurna-Sampurna (vakra)
35	Megh	S R P m P D n S'	S' n D P m P R S	R–S	R P m P D n S' – S' n D P m R S	Kafi	Monsoon afternoon	Monsoon	Sampurna-Sampurna
36	Miyan ki Malhar	S R G m P n D N S'	S' N D n P m G R S	m–S	R G m P n D N S'	Kafi	Monsoon midnight	Monsoon	Sampurna-Sampurna
37	Miyan ki Todi	S r g m P d n S'	S' n d P m g r S	d–g	g m P d n S' – n d P m g r S	Todi	9 am – 12 pm	Deep pathos	Sampurna-Sampurna
38	Multani	S g M P n S'	S' n P M g S	M–S	S g M P n S' – S' n P M g S	Todi	3–6 pm	Sunset longing	Audav-Audav
39	Pahadi	S R G P D S'	S' D P G R S	P–S	R G P D S' – D P G R S	Bilaval	Evening	Light, folk	Audav-Audav
40	Patdeep	S R m P N S'	S' N P m G R S	m–S	R m P N S' – S' N P m G R S	Kafi	4–7 pm	Dusk	Shadav-Shadav
41	Pilu	S R G P m D N S'	S' N D P m G R S	m–S	m D N S' – S' N D P m G R S	Kafi	10 pm – 1 am	Thumri, variety	Sampurna-Sampurna
42	Poorvi	S r G M P d n S'	S' n d P M G r S	d–G	r G M P d n S' – n d P M G r S	Poorvi	4–7 pm	Sunset grandeur	Sampurna-Sampurna (vakra)
43	Puriya	S r G M P D N S'	S' N D P M G r S	G–r	r G M P D N S' – S' N D P M G r S	Marwa	6–9 pm	Sunset pathos	Sampurna-Sampurna (vakra)
44	Puriya Dhanashri	S R G M P d N S'	S' N d P M G R S	P–G	G M P d N S' – S' N d P M G R S	Poorvi	6–9 pm	Peaceful evening	Sampurna-Sampurna
45	Shree	S r G m P d n S'	S' n d P M g r S	r–P	r G m P d n S' – n d P M g r S	Poorvi	4–7 pm	Sunset majesty	Sampurna-Sampurna (vakra)
46	Sohini	S G m D N S'	S' N D m G S	D–G	G m D N S' – S' N D m G S	Marwa	2–4 am	Pre-dawn intensity	Audav-Audav
47	Tilak Kamod	S R G m P D N S'	S' N D P m G R S	R–G	G m P D N S' – S' N D P m G R S	Khamaj	9 pm – 12 am	Romantic	Sampurna-Sampurna
48	Tilang	S G m P N S'	S' N P m G S	P–N	G m P N S' – S' N P m G S	Khamaj	6–9 pm	Light, folk	Audav-Audav
49	Todi (Miyan ki Todi)	S r g m P d n S'	S' n d P m g r S	d–g	g m P d n S' – n d P m g r S	Todi	9 am – 12 pm	Deep pathos	Sampurna-Sampurna
50	Yaman	S R G M P D N S'	S' N D P M G R S	G–N	N R G – M P D N S'	Kalyan	7–10 pm	Evening romance	Sampurna-Sampurna
73	Basant Bahar	S R G m P D N S'	S' N D P m G R S	M–S	G m P D N S' – S' N D P m G R S	Kafi	Spring night	Spring	Sampurna-Sampurna
74	Chhayanat	S R G M P D N S'	S' N D P M G R S	G–N	G M P D N S'	Kalyan	Spring evening	Spring	Sampurna-Sampurna
75	Gujiri Todi	S r g m P d n S'	S' n d P m g r S	d–g	g m P d n S'	Todi	Morning	Pathos	Sampurna-Sampurna
76	Hamsadhwani	S R G P N S'	S' N P G R S	P–S	P N S' – S' N P G R S	Bilaval	Morning	Joy	Audav-Audav
77	Jogkauns	S g m d N S'	S' N d m g S	m–S	g m d N S'	Bhairavi	Midnight	Mystery	Audav-Audav
78	Madhumad Sarang	S R G m P D N S'	S' N D P m G R S	m–S	m P D N S'	Marwa	Afternoon	Sweet heat	Sampurna-Sampurna
79	Maru Bihag	S R G M P N d S'	S' d N P M G R S	M–S	M G R S n D P M G R S	Kalyan	Night	Romantic	Sampurna-Sampurna
80	Nand	S G m P N S'	S' N P m G S	P–S	G m P N S' – S' N P m G S	Bilaval	Night	Peaceful	Audav-Audav
81	Paraj	S G m D N S'	S' N D m G S	G–N	G m D N S'	Poorvi	Night	Serenity	Audav-Audav
82	Shankara	S R G m P D n S'	S' n D P m G R S	R–P	G m P D n S'	Bilaval	Night	Devotional	Sampurna-Sampurna
83	Shudh Kalyan	S R G M P D N S'	S' N D P M G R S	G–R	N R G M P – M P D N S'	Kalyan	7–10 pm	Evening	Sampurna-Sampurna
84	Yaman Kalyan	S R G M P D N S'	S' N D P M G R S	G–N	N R G – M P D N S'	Kalyan	7–10 pm	Evening romance	Sampurna-Sampurna

Key elements of a raga

Arohana / Avarohana: Ascent and descent patterns that may differ (non-symmetric).
Vadi / Samvadi: Principal and secondary notes that anchor the raga's melodic identity.
Pakad / Chalan: Characteristic motifs that instantly signal the raga.
Gamakas & Ornamentation: Microtonal slides, oscillations, and emphasis patterns crucial to expression.
Rasa: The emotional flavor (e.g., serenity, longing, heroism) associated with the raga.
Samay (Time Theory): Traditional guidance on when a raga is to be performed for maximal effect.

Historical & Cultural Context

The concept of raga is ancient, with precursors in the Samaveda and early nāda (sound) treatises. Over centuries the melodic system branched into regional traditions—chiefly Hindustani (North Indian) and Carnatic (South Indian) systems—each developing its own taxonomy, pedagogy, and repertoire. The canonical list of 84 ragas appears in multiple historical and pedagogical sources as a compact reference set used for teaching, composition, and scholarly comparison.

Note: Different traditions may treat the “84 ragas” differently—sometimes as a pedagogical list for teaching core ragas, and sometimes as a mapping between Thaat/Melakarta systems and practice-based ragas.

Theory & Classification

Thaat (Hindustani) vs Melakarta (Carnatic)

Two major classification systems underpin how ragas are organized in modern scholarship and pedagogy:

Thaat system (Hindustani): A practical method introduced by Vishnu Narayan Bhatkhande in the early 20th century grouping ragas into ten parent thaats for pedagogy.
Melakarta system (Carnatic): A mathematically complete 72-parent (melakarta) scheme; many janya (derived) ragas emerge from these parents. The melakarta system is exhaustive for seven-note scales, enabling systematic naming and classification.

Jāti, Rasa & Samay

Jati describes the number of notes used in ascent/descent (e.g., audava—5 notes, sampurna—7 notes). Rasa ties the raga to an emotional palette (shanta—calm, karuna—compassion, vira—heroic, etc.). Samay or time-theory prescribes when a raga traditionally yields its maximum effect (morning, afternoon, evening, late night).

Structure & Performance Practice

Alap, Jor, Jhala, and Bandish/Khayal

In Hindustani performance, a raga is often introduced through a slow, unmetered exposition (alap) that reveals the raga’s identity, then expanded with rhythm (jor), a climactic fast section (jhala), and finally fixed compositions (bandish/khayal) with tabla accompaniment. Carnatic performances typically present a kriti (composition) framed by improvisatory segments (raga alapana, neraval, kalpana swaras) tailored to the raga's grammar.

Ornamentation & Microtonality

Gamaka and microtonal inflections are central — they transform a mere scale into a living raga. Nuance, phrasing, and emphasis (and not only the notes themselves) define a raga’s identity.

Listening & Learning Guide

Practical steps to study and internalize ragas:

Start with aroha/avarohana: Learn the ascent and descent and the vadi/samvadi.
Work the pakad: Practice signature phrases until they become reflexive.
Learn bandish & compositions: Use compositions to ground improvisation vocabulary.
Improvise inside rules: Do alap/riyaaz slowly, then add rhythm and fast phrases.
Time slots & mood: Experiment with performing ragas at their traditional hours and notice psychological effects.

Recommended Listening (Starter List)

Morning / Dawn:
Ragas with contemplative, spacious moods

Afternoon:
Ragas suited for light, playful moods

Evening:
Ragas with deep, romantic or devotional mood

Late Night:
Ragas of longing and introspection

Applications: Therapy, Research & Creativity

Ragas have been used in traditional healing, contemporary music therapy, film scoring, and neuroscience studies exploring how melodic structures influence mood and autonomic function. Researchers look at brain responses, heart-rate variability, and subjective reports tied to specific ragas—an area where ancient practice meets modern science.

Using Ragas in Composition

Contemporary composers often draw ragas into fusion, film music, and experimental works—honoring raga grammar while extending its boundary into new harmonic and textural contexts.

Conclusion

The 84 ragas of Indian classical music reflect a profound interplay of art, emotion, spirituality, and science. Each raga acts as a subtle blueprint that shapes human perception, affecting mood, cognition, and even physiological rhythms. By understanding their structure, rasa, and time theory—as well as their place in the larger ecosystem of thaats, melakartas, and lineage traditions—we gain insight not only into classical music but also into the deeper fabric of Indian culture.

As music therapy, consciousness studies, and neuroscience continue to explore the impact of sound on the brain, these 84 ragas offer a timeless and sophisticated framework for research and practice. Whether you are learning, teaching, performing, or simply listening, the journey through these ragas opens pathways to creativity, meditation, emotional healing, and higher awareness. The tradition remains alive because each raga, when performed with purity, becomes a living, breathing experience—one that connects us to the ancient foundations and to the infinite possibilities of sound.

References:

Ray, Amit. "Brain Fluid Dynamics of CSF, ISF, and CBF: A Computational Model." Compassionate AI, 4.11 (2024): 87-89. https://amitray.com/brain-fluid-dynamics-of-csf-isf-and-cbf-a-computational-model/.
Ray, Amit. "Musical Neurodynamics and Neuroplasticity: Mathematical Modeling." Compassionate AI, 2.5 (2025): 12-14. https://amitray.com/musical-neurodynamics-and-neuroplasticity/.
Ray, Amit. "Neurodynamics of Indian Classical Music and The Ray 28 Brain Chakras." Compassionate AI, 2.6 (2025): 30-32. https://amitray.com/neurodynamics-indian-classical-music-ray-28-brain-chakras/.
Ray, Amit. "Neuroscience of Indian Classical Music: Raga, Tala, and Swara." Compassionate AI, 3.7 (2025): 75-77. https://amitray.com/neuroscience-indian-classical-music-raga-tala-swara/.
Ray, Amit. "Music Therapy and BDNF Signaling in Aging Brain: A Systematic Review." Compassionate AI, 3.8 (2025): 84-86. https://amitray.com/music-therapy-and-bdnf-signaling-in-aging-brain-a-systematic-review/.
Ray, Amit. "The 84 Ragas of Indian Classical Music – A Complete Guide." Yoga and Ayurveda Research, 4.11 (2025): 69-71. https://amitray.com/the-84-ragas-of-indian-classical-music-a-complete-guide/.

Neuroscience of Indian Classical Music: Raga, Tala, and Swara

Indian classical music (ICM), characterized by its intricate components—raga (melodic framework), tala (rhythmic cycle), and swara (musical notes)—engages complex neural processes that underpin perception, emotion, and sensorimotor synchronization. We have conducted several studies on the newly developed music chakras of the brain. This article presents a neuroscientific and mathematical exploration of how these components interact to evoke profound cognitive and emotional responses, leveraging principles from neural resonance theory and brain fluid dynamics. Drawing on computational models, we developed the dynamic interplay of raga, tala, and swara induces neural oscillations that synchronize with musical structures, facilitating strong anticipation and emotional resonance. We integrate findings from recent studies on musical neurodynamics and brain fluid dynamics to model how ICM influences cerebrospinal fluid (CSF), interstitial fluid (ISF), and cerebral blood flow (CBF). This work provides a framework for understanding the therapeutic potential of ICM in modulating brain health, with implications for neurological disorders such as Alzheimer’s disease and stress-related conditions.

Introduction

Indian classical music (ICM) is a sophisticated auditory art form rooted in ancient traditions, characterized by raga (melodic frameworks), tala (rhythmic cycles), and swara (musical notes). These elements interact to create a dynamic musical experience that engages perception, emotion, and motor coordination. Recent advances in neuroscience, particularly in neural resonance theory [1], suggest that music perception involves the synchronization of neural oscillations with external auditory stimuli, a process that underpins anticipation, emotional response, and sensorimotor coordination. Concurrently, computational models of brain fluid dynamics, including cerebrospinal fluid (CSF), interstitial fluid (ISF), and cerebral blood flow (CBF), reveal how physiological processes support cognitive functions [2]. This article synthesizes these perspectives to explore the neurodynamic and physiological impacts of ICM, with a focus on the mathematical modeling of raga, tala, and swara interactions.

Neural Resonance Theory and ICM

Neural resonance theory posits that neural oscillations synchronize with musical stimuli to facilitate perception and performance [1]. This synchronization, driven by nonlinear oscillators, enables the brain to anticipate musical events through embodied dynamics rather than predictive models. In ICM, raga provides a tonal hierarchy, tala establishes rhythmic structure, and swara serves as the fundamental pitch unit. These components engage distinct neural mechanisms:

Raga: A melodic framework defined by a set of swaras, their sequence, and ornamental patterns (gamakas). Raga evokes emotional states (rasa) through tonal hierarchies, resonating with neural circuits in auditory and limbic regions [1].
Tala: A cyclic rhythmic structure that governs temporal organization. Tala engages motor and auditory cortices, facilitating sensorimotor synchronization [3].
Swara: Individual musical notes that form the basis of melody. Swaras induce neural entrainment through their frequency ratios, aligning with natural oscillatory patterns in the auditory system [4].

The interaction of these components creates a complex dynamical system, where neural oscillations mode-lock to the temporal and tonal patterns of ICM, enhancing perception and emotional engagement.

Music Chakras and Neuroscience

We have conducted several studies on the newly developed Music Chakras within the brain, as outlined in the Ray 28 Brain Chakra framework. These chakras represent a pioneering integration of neuroscience, musical theory, and ancient meditative science. It includes a detailed neuroscientific and mathematical exploration of how these Music Chakras—such as the Swara, Tala, Rasa, Laya, and Vritti Chakras—interact to evoke profound cognitive and emotional responses. Drawing from principles of neural resonance theory, auditory entrainment, and brain fluid dynamics, we propose that these chakras serve as specialized neural circuits for decoding the structural and affective dimensions of Indian Classical Music. The goal is to expand both the scientific and spiritual understanding of how sound, rhythm, and consciousness are intricately woven within the human brain.

Mathematical Modeling of ICM Components

To model the neurodynamics of ICM, we employ a coupled oscillator framework, building on the work of [1, 5]. The brain is modeled as a network of nonlinear oscillators, each representing a neural population with a natural frequency. The interaction of raga, tala, and swara is captured through coupled differential equations, reflecting their hierarchical and temporal relationships.

Modeling Swara: Pitch Perception

Swara, the fundamental pitch unit, is modeled as a nonlinear oscillator responding to external auditory stimuli. The dynamics of a single swara can be described using a canonical oscillator model [6]:

$$ \frac{d^2x}{dt^2} + \omega^2 x = \epsilon f(x, \dot{x}) + s(t), $$

where $ x $ is the oscillator state, $ \omega $ is the natural frequency, $ \epsilon f(x, \dot{x}) $ represents nonlinear damping, and $ s(t) $ is the external stimulus (swara frequency). The frequency of a swara, such as Sa (tonic) or Pa (perfect fifth), corresponds to integer ratios (e.g., 3:2 for Sa-Pa), inducing mode-locking in auditory neurons [7].

Modeling Raga: Tonal Hierarchy

Raga is modeled as a network of coupled oscillators, where each oscillator represents a swara within the raga’s scale. The coupling reflects the tonal hierarchy, where certain swaras (e.g., vadi, samvadi) are more stable [8]. The dynamics are described by:

$$ \frac{d^2x_i}{dt^2} + \omega_i^2 x_i = \epsilon f(x_i, \dot{x}_i) + \sum_{j \neq i} k_{ij} x_j + s_i(t), $$

where $ x_i $ is the state of the $ i $-th swara oscillator, $ k_{ij} $ is the coupling strength reflecting the raga’s grammatical structure, and $ s_i(t) $ is the external input. The coupling matrix $ k_{ij} $ encodes the raga’s rules, such as ascent (arohana) and descent (avarohana), ensuring stable tonal patterns.

Modeling Tala: Rhythmic Entrainment

Tala is modeled as a periodic forcing function that entrains neural oscillators to its rhythmic cycle. The dynamics of tala perception are described using a gradient frequency neural network [5]:

$$ \frac{d^2y}{dt^2} + \omega_y^2 y = \epsilon g(y, \dot{y}) + p(t), $$

where $ y $ is the oscillator state, $ \omega_y $ is the natural frequency of the motor-auditory network, $ g(y, \dot{y}) $ is nonlinear damping, and $ p(t) $ is the periodic tala input (e.g., a 16-beat Teental cycle). The entrainment results in phase-locking, where neural oscillations align with tala’s metrical structure [9].

Interaction of Raga, Tala, and Swara

The interaction of raga, tala, and swara is modeled as a coupled system:

$$ \begin{aligned} \frac{d^2x_i}{dt^2} + \omega_i^2 x_i &= \epsilon f(x_i, \dot{x}_i) + \sum_{j \neq i} k_{ij} x_j + \alpha y + s_i(t), \\ \frac{d^2y}{dt^2} + \omega_y^2 y &= \epsilon g(y, \dot{y}) + \beta \sum_i x_i + p(t), \end{aligned} $$

where $ \alpha $ and $ \beta $ represent coupling strengths between raga and tala oscillators. This model captures the hierarchical integration of melody and rhythm, enabling strong anticipation [10] as neural oscillations synchronize with the combined musical structure.

Brain Fluid Dynamics and ICM

The perception of ICM also influences brain fluid dynamics, particularly CSF, ISF, and CBF [2]. The rhythmic and tonal components of ICM can modulate these fluids, impacting waste clearance and nutrient delivery.

CSF Dynamics

CSF flow is modeled using the Navier-Stokes equation for incompressible fluids [2]:

$$ \frac{\partial \mathbf{v}}{\partial t} + (\mathbf{v} \cdot \nabla) \mathbf{v} = -\frac{1}{\rho} \nabla P + \nu \nabla^2 \mathbf{v} + \mathbf{f}, $$

where $ \mathbf{v} $ is the velocity field, $ \rho $ is the density, $ P $ is the pressure, $ \nu $ is the viscosity, and $ \mathbf{f} $ includes external forces (e.g., arterial pulsations influenced by ICM rhythms). Tala’s periodic structure may enhance CSF pulsatility, facilitating waste clearance via the glymphatic system [11].

ISF and Waste Clearance

ISF dynamics are modeled using an advection-diffusion equation [2]:

$$ \frac{\partial c}{\partial t} + \nabla \cdot (\mathbf{v}_{\text{ISF}} c) = D \nabla^2 c, $$

where $ c $ is the solute concentration, $ \mathbf{v}_{\text{ISF}} $ is the ISF velocity, and $ D $ is the diffusion coefficient. The rhythmic entrainment induced by tala may increase ISF flow, enhancing clearance of metabolic waste, such as amyloid-beta, implicated in Alzheimer’s disease [11].

CBF Modulation

CBF is influenced by neural activity and arousal states induced by ICM. The model for coupling CBF with neural oscillations is:

$$ \frac{dQ_{\text{CBF}}}{dt} = \kappa (A_{\text{neural}} - Q_{\text{CBF}}), $$

where $ Q_{\text{CBF}} $ is the blood flow rate, $ A_{\text{neural}} $ is the neural activity driven by ICM, and $ \kappa $ is the coupling constant. Emotional arousal from raga may increase CBF, supporting cognitive and emotional processing [2].

Neurodynamic Integration of the 28 Brain Chakras and Indian Classical Music (ICM)

Sri Amit Ray’s 28 Brain Chakras framework presents a compelling neurodynamics model that bridges Indian contemplative traditions with contemporary neuroscience. The model explores that Indian Classical Music (ICM)—through its nuanced sound architecture—interacts with distinct neurofunctional centers as "brain chakras." Unlike the traditional seven-chakra system, these 28 chakras are envisioned as specialized neural hubs involved in regulating cognition, intelligence, emotion, interoception, and sensorimotor integration [14], [15].

Moreover, each brain chakra resonates with specific acoustic features—such as raga tonality, rhythmic tala cycles, and swara microtonal inflections—activating or entraining neural circuits through vibrational resonance and cross-frequency coupling. Structural motifs like the Pallavi–Anupallavi–Charanam sequence are hypothesized to entrain hierarchical processing networks, enhancing synaptic plasticity, emotional regulation, and attentional modulation. For example, listening to emotionally evocative ragas such as Bhimpalasi may modulate activity in regions like the anterior cingulate cortex, amygdala, and medial prefrontal cortex—key areas implicated in affective resilience and emotional processing [14].

Additionally, rhythmic chanting and low-frequency oscillatory components of ICM may enhance cerebrospinal fluid (CSF) flow through entrained craniospinal rhythms, supporting neuroimmune homeostasis and potentially attenuating neuroinflammation. This intersection of vibrational neuroscience and auditory entrainment provides a novel therapeutic lens, suggesting that specific raga–chakra pairings could be harnessed for targeted interventions in anxiety, mood disorders, and neurodegenerative conditions [15].

Therapeutic Implications

The neurodynamic and fluid dynamic effects of ICM suggest therapeutic potential. Enhanced CSF and ISF flow may improve waste clearance, potentially mitigating Alzheimer’s disease progression. The emotional resonance of raga can reduce stress, modulating CBF and improving mental health [12]. Computational simulations can predict optimal raga-tala combinations for specific therapeutic outcomes, such as stress reduction or cognitive enhancement.

Challenges and Future Directions

Challenges include the need for high-resolution neuroimaging data to validate models and the computational complexity of simulating coupled neural-fluid systems. Future research should integrate real-time MRI and EEG data to refine models and explore personalized ICM interventions for neurological disorders.

Conclusion

The neuroscientific and mathematical exploration of ICM reveals how raga, tala, and swara engage neural oscillations and brain fluid dynamics to create profound cognitive and emotional effects. By modeling these interactions, we uncover the mechanisms underlying ICM’s therapeutic potential, paving the way for novel interventions in neurological and mental health disorders.

References

Harding, E.E., Kim, J.C., Demos, A.P., et al. Musical neurodynamics. Nature Reviews Neuroscience, 26:293–307, 2025.
Ray, A. Brain fluid dynamics of CSF, ISF, and CBF: A computational model. Compassionate AI, 4(11):87–89, 2024.
Nozaradan, S., Peretz, I., Missal, M., Mouraux, A. Tagging the neuronal entrainment to beat and meter. Journal of Neuroscience, 31:10234–10240, 2011.
Large, E.W., Kim, J.C., Flaig, N.K., Bharucha, J.J., Krumhansl, C.L. A neurodynamic account of musical tonality. Music Perception, 33:319–331, 2016.
Kim, J.C., Large, E.W. Mode locking in periodically forced gradient frequency neural networks. Physical Review E, 99:022421, 2019.
Large, E.W., Almonte, F.V., Velasco, M.J. A canonical model for gradient frequency neural networks. Physica D: Nonlinear Phenomena, 239:905–911, 2010.
Lerud, K.D., Almonte, F.V., Kim, J.C., Large, E.W. Mode-locking neurodynamics predict human auditory brainstem responses to musical intervals. Hearing Research, 308:41–49, 2014.
Krumhansl, C.L., Kessler, E.J. Tracing the dynamic changes in perceived tonal organization in a spatial representation of musical keys. Psychological Review, 89:334–368, 1982.
Nozaradan, S., Peretz, I., Mouraux, A. Selective neuronal entrainment to the beat and meter embedded in a musical rhythm. Journal of Neuroscience, 32:17572–17581, 2012.
Stepp, N., Turvey, M.T. On strong anticipation. Cognitive Systems Research, 11:148–164, 2010.
Iliff, J.J., et al. A paravascular pathway facilitates CSF flow through the brain parenchyma and the clearance of interstitial solutes, including amyloid beta. Science Translational Medicine, 4(147):147ra111, 2012.
Fritz, T., et al. Universal recognition of three basic emotions in music. Current Biology, 19:573–576, 2009.

Ray, Amit. "Brain Fluid Dynamics of CSF, ISF, and CBF: A Computational Model." Compassionate AI, 4.11 (2024): 87-89. https://amitray.com/brain-fluid-dynamics-of-csf-isf-and-cbf-a-computational-model/.
Ray, Amit. "Musical Neurodynamics and Neuroplasticity: Mathematical Modeling." Compassionate AI, 2.5 (2025): 12-14. https://amitray.com/musical-neurodynamics-and-neuroplasticity/.
Ray, Amit. "Neurodynamics of Indian Classical Music and The Ray 28 Brain Chakras." Compassionate AI, 2.6 (2025): 30-32. https://amitray.com/neurodynamics-indian-classical-music-ray-28-brain-chakras/.
Ray, Amit. "Neuroscience of Indian Classical Music: Raga, Tala, and Swara." Compassionate AI, 3.7 (2025): 75-77. https://amitray.com/neuroscience-indian-classical-music-raga-tala-swara/.
Ray, Amit. "Music Therapy and BDNF Signaling in Aging Brain: A Systematic Review." Compassionate AI, 3.8 (2025): 84-86. https://amitray.com/music-therapy-and-bdnf-signaling-in-aging-brain-a-systematic-review/.
Ray, Amit. "The 84 Ragas of Indian Classical Music – A Complete Guide." Yoga and Ayurveda Research, 4.11 (2025): 69-71. https://amitray.com/the-84-ragas-of-indian-classical-music-a-complete-guide/.

Neurodynamics of Indian Classical Music and The Ray 28 Brain Chakras

Indian classical music is a multidimensional art form that engages the brain’s emotional, cognitive, and spiritual centers. This article explores the neurodynamics of Indian classical music, focusing on how its structured patterns—particularly the Pallavi–Anupallavi–Charanam format—modulate auditory processing, emotional regulation, neuroplasticity, and cognitive function.

Drawing on the ancient practice of formulaic chanting and the Sri Amit Ray's 28 Brain Chakras framework, which extends beyond the traditional seven chakras to include specialized neural energy centers, we studied the ICM's rhythmic and melodic patterns resonate with neural oscillatory networks, enhancing neuroplasticity and emotional well-being.

Indian classical music (ICM), with its intricate Pallavi–Anupallavi–Charanam structure, represents a sophisticated auditory stimulus that engages complex neurocognitive processes. By integrating neuroimaging data, computational neuroscience models, and brain fluid dynamics, we observed that ICM's unique structure acts as a neurocognitive scaffold, facilitating synchronized brain activity across auditory, limbic, and prefrontal regions.

This work bridges the classical musical practices with modern neuroscience, offering insights into therapeutic applications for neurological disorders and mental health.

Indian Classical Music

Indian classical music (ICM), encompassing Hindustani and Carnatic traditions, is a profound cultural and artistic system rooted in ancient Vedic practices [1]. Its compositional structure, notably the Pallavi–Anupallavi–Charanam framework in Carnatic music, organizes melodic and rhythmic elements into a dynamic progression that captivates listeners and performers alike. Unlike Western musical forms, ICM emphasizes improvisation within a raga (melodic framework) and tala (rhythmic cycle), creating a rich auditory experience that engages both cognitive and emotional faculties.

Recent advances in neuroscience have highlighted music's capacity to modulate brain activity, influencing auditory processing, memory, and emotional regulation [1, 2]. ICM, with its repetitive yet evolving formulaic patterns, offers a unique lens to study neurodynamics—the temporal and spatial patterns of neural activity that underpin cognitive and emotional processing [2].

The practice of chanting, integral to ICM's spiritual roots, aligns with the Sri Amit Ray's 28 Brain Chakras framework, which conceptualizes 28 or 114 specialized neural energy centers beyond the traditional seven chakras, influencing neural and energetic systems through vibrational resonance [3].

Additionally, computational models of brain fluid dynamics, such as those involving cerebrospinal fluid (CSF), interstitial fluid (ISF), and cerebral blood flow (CBF), provide a novel perspective on how ICM might influence brain homeostasis and neuroplasticity [4].

This article investigates how ICM's structural components, formula patterns, chanting practices, and their potential interaction with brain fluid dynamics affect auditory processing and neural oscillatory networks, proposing a model for their therapeutic potential.

The Pallavi–Anupallavi–Charanam Structure

The Pallavi–Anupallavi–Charanam structure is a hallmark of Carnatic music's kriti form, a compositional genre that balances thematic consistency with improvisational freedom. The Pallavi introduces the main melodic theme, often repeated to establish familiarity. The Anupallavi, a secondary section, provides contrast by exploring higher pitch ranges or alternative raga phrases, enriching the composition's emotional depth. The Charanam, typically the longest section, elaborates on the thematic material with intricate rhythmic and melodic variations, often concluding with a return to the Pallavi.

This tripartite structure mirrors cognitive processes such as encoding, elaboration, and consolidation. The Pallavi's repetition primes auditory memory, the Anupallavi challenges attentional networks with novel stimuli, and the Charanam's complexity engages higher-order cognitive functions like pattern recognition and emotional integration [1]. Neuroimaging studies suggest that such structured auditory stimuli activate the auditory cortex, hippocampus, and prefrontal cortex, fostering cross-regional synchronization.

🎼 Pallavi – The Root Mantra

The Pallavi is the central refrain—the melodic and lyrical theme that repeats throughout the piece. It encapsulates the core emotional or devotional message, serving as an anchor for the entire composition.

- Neurodynamic role: Anchors attention; repeated exposure strengthens memory and learning (via hippocampal circuits).
- Activates the default mode network (DMN) during passive listening and helps establish emotional familiarity.
- Functions like a musical mantra, reinforcing neural patterns through repetition [1].
- Brain wave alignment: Aligns with Alpha (8–12 Hz) and Theta (4–8 Hz) waves, initiating calm focus (Alpha) while supporting memory consolidation and emotional familiarity (Theta) [2].

🎶 Anupallavi – The Emotional Lift

Following the Pallavi, the Anupallavi provides contrast, expansion, or elevation. Musically, it often climbs to a higher pitch or explores a different register of the rāga.

Neurodynamic role: Triggers the limbic system, modulating emotional arousal.
Offers novelty and surprise, increasing dopamine release and cognitive engagement.
Enhances cross-hemispheric communication, especially in trained musicians [1].
Brain wave alignment: Evokes Beta (12–30 Hz) waves, not allowing to sleep, for cognitive engagement and Theta (4–8 Hz) waves for emotional arousal, building emotional and cognitive engagement [2].

🎵 Charanam – The Narrative and Integration

The Charanam is the storytelling section, often more elaborate, and includes philosophical or devotional verses. It brings depth and diversity while always returning to the Pallavi.

Neurodynamic role: Stimulates executive networks, including the prefrontal cortex, as listeners process complex verses.
Invites emotional synthesis and empathic imagination, activating the insula and temporal lobes.
Provides a conclusive loop that allows the brain to rest in pattern recognition and closure [1].
Brain wave alignment: Primarily resonates with Gamma (30–100 Hz) waves, enabling insight and aesthetic bliss, with Theta (4–8 Hz) waves contributing to deep absorption and emotional synthesis [2].

Formula Patterns in ICM

The Pallavi–Anupallavi–Charanam structure is governed by formulaic patterns that provide a scaffold for both composition and improvisation. These patterns include specific melodic motifs (sangatis), rhythmic cycles (talas), and gamaka (ornamentation) techniques that define a raga's emotional and structural identity.

For instance, sangatis in the Pallavi involve iterative variations of a melodic phrase, each subtly altered to enhance expressivity, which aligns with neural mechanisms of predictive coding [1]. The Anupallavi often introduces a complementary melodic contour, adhering to the raga's ascending ($arohana$) and descending ($avarohana$) scales, which may modulate emotional arousal through pitch transitions. The Charanam integrates these elements with complex tala subdivisions, such as tisra (three-beat) or chatusra (four-beat) nadais, engaging temporal processing networks.

These formulaic patterns are not rigid but allow for improvisation within constraints, a feature that distinguishes ICM from other musical traditions.

The Pallavi aligns with Alpha waves, initiating calm focus and setting the theme. The Anupallavi evokes Beta or Theta waves, building emotional and cognitive engagement. The Charanam resonates with Theta or Gamma waves, enabling deep absorption, insight, and aesthetic bliss.

This hierarchical structure may resonate with neural oscillatory hierarchies, where low-frequency oscillations (e.g., $\delta$, $\theta$) modulate higher-frequency $\gamma$ activity, facilitating cognitive integration [2].

$$ \text{Neural Oscillation Hierarchy: } \delta(0.5-4 \, \text{Hz}) \rightarrow \theta(4-8 \, \text{Hz}) \rightarrow \gamma(30-100 \, \text{Hz}) $$.

🎶 Indian Classical Song Structure

[PALLAVI] ×2

[ANUPALLAVI] ×2

→ Repeat [PALLAVI] ×1

[CHARANAM 1] ×1

→ Repeat [PALLAVI] ×1

[CHARANAM 2] ×1

→ Repeat [PALLAVI] ×1

(Optional) [CHARANAM 3] ×1

→ Repeat [PALLAVI] ×1

[ENDING / TIHAI] = Last line ×3 (gradual fade)

Relevant Datasets for ICM Neurodynamics

Publicly available datasets can facilitate the study of ICM's neurodynamic effects, particularly in the context of the Pallavi–Anupallavi–Charanam structure. Datasets like those hosted on platforms such as Zenodo or OpenNeuro could support computational modeling of raga and tala structures or provide EEG responses to raga-based stimuli, offering insights into oscillatory patterns during ICM listening. Researchers can integrate these datasets with computational tools, such as gammatone filterbanks, to model auditory cortex responses to ICM's formulaic patterns [1]. These resources enable hypothesis-driven studies on how ICM's structural complexity influences neural synchronization and emotional processing.

Neurodynamics of Auditory Processing in ICM

Auditory processing of ICM involves a cascade of neural events, from primary auditory cortex activation to higher-order integration in association areas [1, 2]. The raga's microtonal variations and tala's rhythmic precision engage the brain's temporal processing networks, particularly the superior temporal gyrus and basal ganglia. EEG studies indicate that ICM listening increases $\alpha$ (8–12 Hz) and $\theta$ (4–8 Hz) band activity, associated with relaxation and focused attention, while also modulating $\gamma$ (30–100 Hz) oscillations linked to cognitive integration [1, 2].

The Pallavi–Anupallavi–Charanam structure imposes a temporal hierarchy that aligns with neural oscillatory dynamics. For instance, the Pallavi's repetitive sangatis may entrain low-frequency $\delta$ and $\theta$ oscillations, facilitating memory consolidation [2]. The Anupallavi's melodic shifts could modulate $\beta$ (12–30 Hz) band activity, reflecting heightened attentional demands. The Charanam's rhythmic complexity, driven by intricate tala patterns, likely engages $\gamma$ oscillations, linked to cognitive integration and emotional processing [2]. This oscillatory entrainment hypothesis, supported by recent neurodynamic models, suggests that ICM acts as a neurocognitive scaffold, synchronizing distributed brain networks [2].

$$ \text{Entrainment Model: } f_{\text{tala}}(t) \propto \sum_{k} A_k \sin(2\pi f_k t + \phi_k), \text{ where } f_k \in \{\delta, \theta, \beta, \gamma\} $$

Brain Fluid Dynamics and ICM: A Computational Perspective

The neurodynamic effects of ICM may extend beyond neural oscillations to influence brain fluid dynamics, including cerebrospinal fluid (CSF), interstitial fluid (ISF), and cerebral blood flow (CBF). Computational models suggest that rhythmic auditory stimuli, such as those in ICM, could modulate brain fluid dynamics by altering intracranial pressure and facilitating the clearance of metabolic waste through the glymphatic system [4]. The Sri Amit Ray's 28 Brain Chakras framework posits that vibrational frequencies from music and chanting can resonate with neural energy centers, potentially influencing fluid dynamics in the brain [3]. For instance, the low-frequency oscillations ($\delta$, $\theta$) entrained by the Pallavi's repetition might enhance CSF pulsations, promoting glymphatic flow and supporting neural homeostasis [4].

Ray's computational model of brain fluid dynamics indicates that CBF oscillations, driven by rhythmic stimuli, can enhance oxygen delivery to neural tissues, supporting cognitive and emotional processing during ICM listening [4]. This interplay between auditory stimulation and brain fluid dynamics offers a novel mechanism through which ICM may exert therapeutic effects, such as reducing neuroinflammation and enhancing neuroplasticity [2, 4]. Future studies could integrate neuroimaging with fluid dynamics simulations to explore how ICM's rhythmic patterns influence CSF, ISF, and CBF, providing a holistic understanding of its impact on brain health.

Ancient Formula Chanting and Neural Resonance

Chanting, a cornerstone of ICM's spiritual context, involves repetitive vocalization of mantras or melodic phrases, often aligned with specific ragas and talas [3]. Ancient Vedic texts describe chanting as a means to harmonize body and mind, a concept echoed in modern music therapy [3]. The Sri Amit Ray Brain Chakras framework posits that chanting at specific frequencies activates specialized neural energy centers, influencing neural activity through vibrational resonance [3]. These vibrations may also interact with brain fluid dynamics, potentially enhancing CSF flow and supporting neural health [4].

Neurophysiologically, chanting induces a meditative state, reducing cortisol levels and enhancing parasympathetic activity [3]. EEG studies reveal increased coherence in $\alpha$ and $\theta$ bands during chanting, suggesting enhanced functional connectivity between the prefrontal cortex and limbic system. The rhythmic entrainment of chanting may also modulate the default mode network (DMN), promoting introspection and emotional regulation [2]. In the context of ICM, chanting within the Pallavi–Anupallavi–Charanam structure amplifies these effects, as the music's formulaic patterns sustain engagement while the chant's repetition fosters neural stability.

The Sri Amit Ray 28 Brain Chakras Framework

The Sri Amit Ray Brain Chakras framework integrates ancient Indian philosophy with modern neuroscience, proposing that specific sound frequencies correspond to specialized neural energy centers, distinct from the traditional seven chakras [3]. While the traditional seven chakras (Muladhara, Svadhisthana, Manipura, Anahata, Vishuddha, Ajna, and Sahasrara) are primarily associated with spiritual and energetic functions along the spine, Sri Amit Ray’s model expands to include 28 or 114 brain-specific chakras. These are conceptualized as neural hubs that modulate brain network dynamics, influencing cognitive, emotional, and sensory processing through vibrational frequencies [3]. This framework emphasizes neuroplasticity, suggesting that targeted sound frequencies, such as those in ICM, can rewire neural circuits to enhance cognitive flexibility and emotional resilience [3, 2].

For example, the Anahata (heart) chakra, linked to compassion in both traditional and Ray’s frameworks, may be activated by ragas like Bhimpalasi, known for their emotive qualities [3]. However, Ray’s model associates specific brain regions, such as the anterior cingulate cortex, with these chakras, proposing that their activation enhances functional connectivity [3]. Preliminary studies suggest that music-based interventions targeting specific frequencies can modulate brain activity [2].

For instance, low-frequency sounds (e.g., $100–200$ Hz) associated with the root brain chakra increase $\delta$ band power, promoting relaxation. Higher-frequency sounds (e.g., $400–600$ Hz) linked to the Vishuddha brain chakra may enhance $\beta$ band activity, supporting communication and creativity. These effects may be amplified by improved brain fluid dynamics, as vibrational frequencies could enhance CSF and CBF, supporting neural health [4]. ICM’s microtonal precision and raga-specific emotional profiles offer a natural platform to test these hypotheses, bridging traditional wisdom with scientific inquiry.

Therapeutic Potential and Future Directions

The neurodynamic effects of ICM suggest significant therapeutic potential, particularly for neurological and psychiatric disorders. Music therapy studies indicate that rhythmic auditory stimulation, akin to ICM’s tala, improves motor coordination in stroke patients [3]. The emotional resonance of ragas may alleviate symptoms of anxiety and depression, potentially through limbic system modulation [1]. Chanting-based interventions, aligned with the Sri Amit Ray Brain Chakras framework, could enhance mindfulness and stress resilience, offering a complementary approach to cognitive-behavioral therapy [3, 2]. Additionally, the potential influence of ICM on brain fluid dynamics, such as enhancing glymphatic clearance, may reduce neuroinflammation and support recovery in neurodegenerative conditions [4].

Future research should map the spatiotemporal dynamics of ICM processing, focusing on how formulaic patterns influence neural connectivity. Multimodal neuroimaging (e.g., fMRI, EEG) combined with computational models, such as gammatone-based auditory processing frameworks, could simulate ICM’s impact on the auditory cortex [1]. Studies targeting the Sri Amit Ray Brain Chakras could explore how specific frequencies modulate neural hubs [3], while computational models of brain fluid dynamics could elucidate how ICM affects CSF, ISF, and CBF [4]. Cross-cultural studies comparing ICM with other musical traditions would clarify its unique neurocognitive effects. Additionally, randomized controlled trials are needed to evaluate the efficacy of ICM-based interventions, particularly those incorporating Ray’s brain chakra framework and brain fluid dynamics, leveraging recent insights into musical neurodynamics [3, 2, 4].

Conclusion

Indian classical music, with its Pallavi–Anupallavi–Charanam structure and formulaic patterns, offers a rich auditory stimulus that engages complex neurocognitive processes. By integrating ancient chanting practices, the Sri Amit Ray's 28 Brain Chakras framework, which extends beyond the traditional seven chakras to include specialized neural energy centers, and computational models of brain fluid dynamics, this article proposes that ICM modulates auditory processing, emotional regulation, neural oscillatory networks, and brain homeostasis. These insights, supported by recent neurodynamic research, highlight ICM’s potential as a therapeutic tool and underscore the value of interdisciplinary approaches in neuroscience [2, 4]. As we unravel the neurodynamics of this ancient art form, we pave the way for innovative interventions that harmonize mind, body, and spirit.

References

Banerjee, A. (2017). Music and its effect on the brain. Journal of Neuroscientific Studies, 12(3), 45–60.
Stefanics, G., & Vuust, P. (2025). Musical neurodynamics. Nature Reviews Neuroscience. Advance online publication. https://doi.org/10.1038/s41583-025-00915-4
Ray, A. (2024). Musical neurodynamics and neuroplasticity: Mathematical modeling. Retrieved from https://amitray.com/musical-neurodynamics-and-neuroplasticity/
Ray, A. (2024). Brain fluid dynamics of CSF, ISF, and CBF: A computational model. Retrieved from https://amitray.com/brain-fluid-dynamics-of-csf-isf-and-cbf-a-computational-model/

Ray, Amit. "Brain Fluid Dynamics of CSF, ISF, and CBF: A Computational Model." Compassionate AI, 4.11 (2024): 87-89. https://amitray.com/brain-fluid-dynamics-of-csf-isf-and-cbf-a-computational-model/.
Ray, Amit. "Musical Neurodynamics and Neuroplasticity: Mathematical Modeling." Compassionate AI, 2.5 (2025): 12-14. https://amitray.com/musical-neurodynamics-and-neuroplasticity/.
Ray, Amit. "Neurodynamics of Indian Classical Music and The Ray 28 Brain Chakras." Compassionate AI, 2.6 (2025): 30-32. https://amitray.com/neurodynamics-indian-classical-music-ray-28-brain-chakras/.
Ray, Amit. "Neuroscience of Indian Classical Music: Raga, Tala, and Swara." Compassionate AI, 3.7 (2025): 75-77. https://amitray.com/neuroscience-indian-classical-music-raga-tala-swara/.
Ray, Amit. "Music Therapy and BDNF Signaling in Aging Brain: A Systematic Review." Compassionate AI, 3.8 (2025): 84-86. https://amitray.com/music-therapy-and-bdnf-signaling-in-aging-brain-a-systematic-review/.
Ray, Amit. "The 84 Ragas of Indian Classical Music – A Complete Guide." Yoga and Ayurveda Research, 4.11 (2025): 69-71. https://amitray.com/the-84-ragas-of-indian-classical-music-a-complete-guide/.

Dr. Amit Ray

Teachings, Books and Quotes of Sri Amit Ray